The role of activated leukocyte cell adhesion molecule (ALCAM) in endometrial cancer progression and dissemination
Laura Devis Jauregui
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The role of activated leukocyte cell adhesion molecule (ALCAM) in endometrial cancer progression and dissemination
Laura Devis Jauregui
The role of activated leukocyte cell adhesion molecule (ALCAM) in endometrial cancer progression and dissemination Memoria presentada por
Laura Devis Jauregui para optar al grado de
Doctora por la Universitat Autònoma de Barcelona (UAB) Tesis doctoral realizada en el Grup de Recerca Biomèdica en Ginecologia del Institut de Recerca de l’Hospital Universitari de la Vall d’Hebron, bajo la dirección del Dr. Jaume Reventós, Dra. Eva Colás y Dr. Antonio Gil.
Tesis adscrita al departamento de Biología Celular, Fisiología e Inmunología de la Facultad de Medicina de la UAB, en el programa de doctorado de Biología Celular, bajo la coordinación y tutoría de la Dra. Joaquima Navarro. Universitat Autònoma de Barcelona, 1 de Marzo de 2017
Dr. Jaume Reventós (director)
Dra. Joaquima Navarro (tutora)
Dra. Eva Colás (directora)
Dr. Antonio Gil (director)
Laura Devis Jauregui (estudiante)
A mi ama A mi padre A Angel
Agradecimientos/Acknowledges Parece que se cierra una etapa, una etapa de aprendizaje y crecimiento personal, una etapa de frustraciones pero también de éxitos y buenos momentos. Con el cambio de aire, llega también la ilusión por lo que está a punto de empezar pero no sin antes echar la vista atrás y agradecer a todas las personas que me han ayudado durante el proceso, en muchas facetas distintas. Estas líneas pretenden reflejar la inmensa gratitud que siento hacia todas ellas, gratitud que sin duda no puede expresarse con palabras. A mis directores de tesis, el Dr. Jaume Reventós, la Dra. Eva Colás y el Dr. Antonio Gil. A Jaume por sus consejos, por ser la primera persona que confió en mí, por brindarme la oportunidad de dar mis primeros pasos en el mundo de la investigación y hacerme un sitio en su laboratorio. A Eva, por confiar también en mí, querer que hiciese la tesis en el laboratorio desde el primer momento, por su apoyo constante a lo largo de todo el proceso y hasta el final, por el camino recorrido juntas. A Antonio, por su buena voluntad y disposición constante, su cercanía y su compromiso. A todos los coautores de los artículos que forman la base de esta tesis. Quisiera hacer una mención especial a la Dra. Sylvie Dufour y a la Dra. Françoise Brochard, así como a todo su equipo, por los buenos momentos que he vivido con ellos y por participar activamente en el desarrollo de los artículos, por su ayuda durante mi estancia de investigación en sus laboratorios (URM 144 y 168, Institut Curie, Paris), por la confianza depositada en mí y su cálida acogida en su equipo. “Merci Sylvie et Françoise pour votre accueil chaleureux au sein de vos laboratoires, pour votre participation active pendant le séjour et par la suite dans la réalisation des articles de cette thèse. Merci Vasilica et Bill, pour votre aide et les bons moments ensemble”. A mis compañeros de “Endometrio”, Irene, Elena, Cristian y Tati. A Irene y Elena por compartir estos años, por los ánimos y por la terapia de grupo. Porque parecía que no, pero al final parece que si, porque será verdad que todo llega y que ya estamos las tres en la línea de meta. Y porque he tenido la suerte de disfrutaros como compañeras y confidentes estos años.
A Cristian por hacer más fácil la recta final, por estar siempre dispuesto a ayudar y a colaborar, por todos los ánimos y por el “asado”. A Tati por su fuerza y la energía que nos transmite y contagia. Al resto del equipo del Grup de Recerca Biomèdica en Ginecologia del VHIR. A la Dra. Anna Santamaría por su activa participación e implicación en una parte de los artículos que conforman esta tesis. Anna, gracias por darme confianza, por ser tan justa y por tu cariño. A Blanca, por ser compañera de travesía, por entendernos muy bien y porque haya más “Manchesters” juntas en el futuro. A Lucía, por hacer el día a día más fácil, siempre con una sonrisa cariñosa. ¡Vosotras también estáis ya en la línea de meta campeonas!
A Mireia, por sus ánimos y sus consejos, por
aguantar que le quitase la tranquilidad del despacho en muchas ocasiones, por su cariño. A Eli, porque ella ya sabe que en el fondo está pluriempleada, y que nos ayuda a mantener la cordura, ¡aunque a veces te la hagamos perder a ti! A Júlia, por su alegría contagiosa y por hacerlo todo siempre más divertido. A Nuria, por tener otro trocito de la “terreta” cerca, por los ensayos a mil manos entre las dos y por su cariño. A Iolanda y a Marta, el otro trocito de “terreta”, y a Leire, por su cariño y ánimos durante los meses en que pude coincidir con vosotras. A Gabriel, por hacerme reír en muchas ocasiones, por tener palabras bonitas muchas veces de esas que sin querer ayudan a pasar los días mejor. A Alfonso, por su cariño, su empatía y por traerme chocolate a cultivos cuando mis ánimos lo necesitaban. A los que han empezado esta aventura, Berta, Manuel ¡Suerte¡ Y a todos vosotros¡nos vemos fuera! A mi amiga Laura Lobato, porque nuestras vidas siempre se entrecruzan. Porque tenía que vivir mi estancia en Paris contigo y porque increíblemente también tenía que vivir la de Buenos Aires. Porque tu eres la parte más esencial de “mí”/“nuestro” Buenos Aires y porque estemos preparadas para el resto de sorpresas que nos depara el futuro. A uno de los mejores regalos que directa o indirectamente me trajo Paris, poder disfrutar de la amistad de personas tan especiales, buenas y bonitas como Chema, Fer, Olalla, Marta y Aleix. Gracias por haberos convertido en parte fundamental de mi día a día y por hacerlo todo mejor.
A Adri y Marina, por todos estos años juntos y por lo afortunada que soy por teneros a los dos, siempre. Por todos los buenos momentos con dos de las mejores personas que conozco y por todo lo que nos queda por venir. A mis grandes amigas, Bea, Ziggie, Amparo y Amanda por ser mi gran apoyo fuera del laboratorio, porque ya no se cuentan los años juntas, los momentos, las ciudades, las vivencias compartidas y las que nos quedan por vivir, por ser mis grandes confidentes y por hacerlo todo más bonito. ¡Os quiero chicas! A mi familia catalana-aragonesa: Roser, Angel, Miriam, Jose e Ingrid por su inmenso cariño y su apoyo desde el primer momento. En especial, a Ingrid que con su llegada nos llenó a todos de alegría e ilusión. A mi familia Portugaluja, a mis queridos y añorados tíos Imanol e Iñaki, a mis tías Mertxe, Lucía y Marina, por su enorme cariño y en especial a mis maravillosos primos Ane, Leire, Eneko y Jon con quienes tengo la suerte de mantener un vínculo tan especial. A mi tía y madrina Loli, por estar siempre ahí, por su cariño y por confiar continuamente en mi con más fuerza que yo misma. A todos vosotros, eskerrik asko. A mis abuelitos Lola y Manolo, a mi amama Vicen y mi aitite Iñaki porque sé que también hubiesen disfrutado de este momento y se hubiesen sentido orgullosos. A mi padre por recordarme siempre que crea en mi misma, por los descansos en el oasis de Oropesa, por el “arròs al forn” cuando lo he necesitado, por sus consejos, por intentar calmar mis ansias y neuras (sobre todo en la recta final!), por su cariño incondicional, por sus ánimos y su optimismo. Moltes gràcies papa, t’estime. A mi ama por ser la responsable de que hoy haya llegado hasta aquí. Por ser cariño, inspiración y admiración. Por enseñarme siempre los valores de la constancia, del tesón y la voluntad. Por recogerme y levantarme siempre que lo he necesitado, por recordarme siempre lo que es realmente importante, por hacerme reír a carcajadas, por darme siempre todo y quererme tan incondicionalmente. Por ser tú. Maite zaitut.
A Angel, por ser mi compañero de viaje todos estos años. Por aguantar las frustraciones y también ser cómplice y responsable de los mejores momentos de mi vida, por hacerme sentir siempre tan querida. Per tot, t’estimo Angel.
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Index of figures Figure 1. Estimated incidence ASR(W) of corpus uteri cancer per 100,000 personyear .................................................................................................................... 16 Figure 2. Incidence ASR(W) in Spain, Europe and USA by age .............................. 17 Figure 3. Incidence/Mortality ASR(W) per 100,000 .................................................. 18 Figure 4. Evolution of mortality in Spain by age cohort and its trends ...................... 18 Figure 5. Endometrial cancer: stage at diagnosis and 5-year survival rate by race.. 20 Figure 6. Proposed model for endometrial cancer type I .......................................... 21 Figure 7. Biopsy by aspiration and by hysteroscopy ................................................ 28 Figure 8. Endometrial hyperplasia ............................................................................ 30 Figure 9. Endometrioid adenocarcinoma of the endometrium .................................. 34 Figure 10. Mucinous adenocarcinoma containing mucin in the cytoplasm ............... 35 Figure 11. Serous adenocarcinoma .......................................................................... 36 Figure 12. Clear cell adenocarcinoma ...................................................................... 37 Figure 13. Mixed carcinoma ..................................................................................... 37 Figure 14. Squamous cell carcinoma ....................................................................... 38 Figure 15. Transitional disposition of neoplastic cells ............................................... 39 Figure 16. Small cell carcinoma ................................................................................ 40 Figure 17. FIGO staging from Cancer Research UK ................................................ 41 Figure 18. Molecular events associated with endometrioid endometrial carcinoma . 45 Figure 19. Molecular events associated with non-endometrioid endometrial carcinoma .......................................................................................................... 47 Figure 20. TCGA molecular classification of endometrial cancer ............................. 48 Figure 21. Drivers and mediators of EMT ................................................................. 59 Figure 22. Schematic representation of the principal cell adhesion molecules ........ 66 Figure 23. NCAM and N-cadherin signalling in neurons ........................................... 68 Figure 24. Schematic representation of the cell adhesion molecules VVC2C2C2 subgroup in the immunoglobulin superfamily .................................................... 70 Figure 25. ALCAM-ALCAM interactions between cells ............................................ 71 Figure 26. ALCAM-positivity is a marker of recurrence .......................................... 109 Figure 27. Univariate survival analyses according to ALCAM expression in 174 EEC patients ............................................................................................................ 111 Figure 28. Inhibition of ALCAM in Hec1A cell line .................................................. 112 Figure 29. ALCAM inhibition decreased migration and invasion in Hec1A cell line 114 Figure 30. ALCAM inhibition decreased cell-cell adhesion in Hec1A cell line ........ 115
Figure 31. ALCAM inhibition had no effect on cell proliferation or progression throuhgh the cell cycle ..................................................................................... 115 Figure 32. Inhibition of ALCAM in Ishikawa cell line ............................................... 116 Figure 33. ALCAM inhibition in Ishikawa cell line decreased migration and invasion ......................................................................................................................... 116 Figure 34. ALCAM-depletion decreased primary tumour size in an orthotopic mice model of EEC ................................................................................................... 118 Figure 35. ALCAM-depletion reduced metastasis in an orthotopic mice model of EEC ......................................................................................................................... 119 Figure 36. Gene expression analysis of ALCAM-depleted cell lines ...................... 121 Figure 37. Gene ontology analyses of deregulated ALCAM-depleted cell lines ..... 122 Figure 38. LAMC2, TXNRD1 and FLNB were decreased at mRNA level in ALCAMdepleted cells ................................................................................................... 125 Figure 39. LAMC2, TXNRD1 and FLNB were decreased at protein level in ALCAMdepleted cells ................................................................................................... 125 Figure 40. RT-qPCR performed on deregulated genes from the microarray study.127 Figure 41. ALCAM patterns at the tumour .............................................................. 130 Figure 42. ALCAM expression was decreased at the invasive front of patients with myometrial invasion ......................................................................................... 134 Figure 43. Soluble ALCAM detected in uterine aspirates is a marker of myometrial invasion. ........................................................................................................... 137 Figure 44. Soluble ALCAM and MMP-9 expressions were correlated in uterine aspirates .......................................................................................................... 139 Figure 45. ALCAM was decreased at the invasive front of the primary tumours in a controlled model of EEC dissemination ........................................................... 141 Figure 46. ALCAM staining was significantly decreased at the invasive front of the primary tumours in a controlled model of EEC dissemination ......................... 142 Figure 47. Hec1A and Hec1A-ETV5 orthotopic murine models followed by IVIS ... 142 Figure 48. The expression of full ALCAM protein was decreased at the invasive front of Hec1A-ETV5 cells ........................................................................................ 143 Figure 49. ALCAM recovery in mesenchymal Hec1A-ETV5 cells .......................... 144 Figure 50. ALCAM overexpression in mesenchymal Hec1A-ETV5 cells decreased cell migration .................................................................................................... 146 Figure 51. ALCAM recovery in mesenchymal Hec1A-ETV5 cells increased cell-cell adhesion .......................................................................................................... 147 Figure 52. ALCAM recovery in mesenchymal Hec1A-ETV5 cells and p-ERK ........ 147
Index of tables Table 1. Ten leading cancers in women ................................................................... 16 Table 2. Cumulative survival rate (CSR) ................................................................... 19 Table 3. Features of the methods used for obtaining endometrial biopsies .............. 29 Table 4. Clinicopathological classification of endometrial cancer ............................. 32 Table 5. Histological types of epithelial endometrial carcinoma ................................ 33 Table 6. Revised FIGO staging ................................................................................. 41 Table 7. Genetic alterations in endometrial cancer by type ...................................... 42 Table 8. Risk group classification to guide adjuvant treatment ................................. 50 Table 9. Surgical procedures depending on staging ................................................. 52 Table 10. Recommended adjuvant treatment based on the assessed risk .............. 54 Table 11. The role of the IgSF members in the steps of metastasis ......................... 67 Table 12. ALCAM levels in various malignancies ..................................................... 75 Table 13. TMA description (i) .................................................................................... 82 Table 14. TMA description (ii) ................................................................................... 83 Table 15. Clinicopathological parameters of selected uterine aspirates ................... 83 Table 16. Summary of generated cells ..................................................................... 91 Table 17. Primers designed for SYBR Green RT-qPCR ........................................... 95 Table 18. Clinicopathologic parameters according to ALCAM expression (N=174) 108 Table 19. ALCAM expression signature of EEC recurrence (N=174) ..................... 110 Table 20. Multivariate Cox regression model for patients with early stage tumours (N=134) ............................................................................................................ 112 Table 21. List of the selected genes deregulated in the gene expression analysis of Hec1A shALCAM cells relative to Hec1A shControl ........................................ 124 Table 22. Patterns of ALCAM in the tumour: univariate linear regression analysis. 130 Table 23. ALCAM patterns at the superficial tumour: multivariate linear regression analysis ............................................................................................................ 131 Table 24. ALCAM patterns at the invasive front of the tumour: multivariate linear regression analysis .......................................................................................... 132 Table 25. ALCAM expression and clinical parameters ........................................... 133 Table 26. Multivariate logistic regression model, at the invasive front, related to the myometrial invasion >50% (N=89)................................................................... 134 Table 27. ALCAM and MMP-9 at the invasive front of the tumour .......................... 136 Table 28. ALCAM correlation with MMP-9 in uterine aspirates ............................... 138 Table 29. Matrix correlation MMP-9 forms .............................................................. 138
Deoxythymidine triphosphate External beam radiation Endometrial carcinoma Extracellular matrix Ethylenediaminetetraacetic acid Endometrioid endometrial cancer Epidermal growth factor Epidermal growth factor receptor Endometrial intraepithelial neoplasia Enzyme-linked immunosorbent assay Epithelial-to-mesenchymal transition Oestrogen receptor Ezrin, Radixin, Moesin European Society of Gynaecologic Oncology European Society for Medical Oncology European Society for Radiotherapy and Oncology Ethanol Ets transcription factor family Ets variant 5 EUROan CAncer REgistry based study on survival and care of cancer patients Focal adhesion kinase Fetal bovine serum F-box/WD repeat-containing protein 7 Fold change False discovery rate Fibroblast growth factor Fibroblast growth factor receptor International Federation of Gynaecology and Obstetrics Filamin B Tyrosine-protein kinase Fyn Glyceraldehyde-3-phosphate dehydrogenase Gene Expression Omnibus Green fluorescent protein GLOBOCAN 2012: Estimated Cancer Incidence, Mortality and Prevalence Worldwide Glycogen synthase kinase 3 beta Hours Haematoxylin and eosin Hepes buffered saline Human embryonic kidney cells 293 Dehydrogenase/reductase member 2 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid Human epidermal growth factor receptor 2 Hepatocyte growth factor Hereditary non-polyposis colorectal cancer Horseradish peroxidase
Abbreviations and acronyms IARC ICAM-1 ICAM-2 IF Ig IGF-1 IgSF IHC IL-6 ILK IPA IRS JNK Ki67 KLF17 KRAS L1CAM LAMC2 LD LH LIV-1 LOH LPP LVSI mA MAPK/ERK MCAM MELF µg µl μm mg min ml MLH1 mM mm MMP-2 MMP-3 MMP-9 MMR MPA MRI mRNA MSH2
International Agency for Research on Cancer Intercellular adhesion molecule 1 Intercellular adhesion molecule 2 Immunofluorescence Immunoglobulin Insulin-like growth factor 1 Immunoglobulin superfamily Immunohistochemistry Interleukine 6 Integrin-linked kinase Ingenuity pathway analysis Immunoreactive scores c-Jun N-terminal kinase Marker of proliferation ki67 Kruppel like factor 17 Kirsten rat sarcoma viral oncogene homolog LOXL2 Lysyl oxidase-like 2 L1 cell adhesion molecule Laminin subunit gamma 2 Low DNA Luteinizing hormone Oestrogen-regulated protein LIV-1, Solute carrier family 39 member 6 Loss of heterozygosity Lipoma-preferred partner Lymphovascular space invasion Milliamps Mitogen-activated protein kinase (ERK1/2) Melanoma cell adhesion molecule Microcystic elongated and fragmented Micrograms Microliters Micrometres Milligrams Minutes Millilitres MutL homolog 1 Millimolar Millimetres Matrix metalloproteinase 2 Matrix metalloproteinase 3 Matrix metalloproteinase 9 Mismatch repair system Medroxyprogesterone acetate Magnetic resonance imaging Messenger RNA MutS homolog 2
MSH6 MSI MTA 3 mTOR N.S NCAM NF-Kβ ng NK4 nm Notch OR p-ERK p38 PBS PCA PCOS PCR PCRD PDGF PEA3 PECAM-1 PEG-PLL PEI PFA PI PI3K PIK3CA PIK3R1 PKC POLE PPP2R1A PR PTEN PVDF rcf RIN RIPA RLP22 RNA ROC rpm RT RT-qPCR sALCAM SD
MutS homolog 6 Microsatellite instability Metastasis associated 1 family member 3 Mammalian target of rapamycin No statistically significant Neural cell adhesion molecule Nuclear factor-kappa B Nanograms Natural killer cells protein 4 Nanometres Notch receptor family Odds ratio Phospho-p44/42 MAPK (Erk1/2) P38 mitogen-activated protein kinase Phosphate‐buffered saline Principal component analysis Polycystic ovary syndrome Polymerase chain reaction Positive-charge-rich domain Platelet-derived growth factor Polyoma enhancer activator 3 Platelet and endothelial cell adhesion molecule 1 Poly(ethylene glycol)-b-poly-L-lysine Polyethylenimine Paraformaldehyde Propidium iodide Phosphoinositide-3-kinase Phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic Phosphatidylinositol 3-kinase regulatory subunit alpha Protein kinase C Polimerase ɛ Serine/threonine-protein phosphatase 2A Progesterone receptor Phosphatase and tensin homolog Polyvinylidene difluoride Relative centrifugal force RNA integrity number Radioimmunoprecipitation assay buffer Receptor like protein 22 Ribonucleic acid Receiver operating characteristic Revolution per minute Reverse transcription Real-time quantitative PCR Soluble ALCAM Standard deviation
Abbreviations and acronyms SDF-1 SDS-PAGE
Stromal derived factor 1 Sodium dodecyl sulphate polyacrylamide gel electrophoresis
SEER SEGO SEM SF SHARP1 SLN Smad2 Smad3 SNAIL SPSS SRCR STAT-3 TBS TCGA TGF-β TMA TMB TNF-α TP53 TWIST TXNRD1 UA UV VCAM-1 VE-cadherin VEGF WB WHO WNT ZEB1 ZEB2
Surveillance, Epidemiology, and End Results. Program of the National Cancer Institute Spanish Society of Gynaecology and Obstetrics Standard error of the mean Separation force Basic helix-loop-helix family member e41 Sentinel lymph node Mothers against decantaplegic homolog 2 Mothers against decantaplegic homolog 3 Snail family zinc finger Statistical Package for Social Science Scavenger receptor cysteine-rich domains Signal transducer and activator transcription 3 Tris-buffered saline The Cancer Genome Atlas Transforming growth factor beta Tissue microarray 3,3',5,5' Tetramethylbenzidine Tumour necrosis factor alpha Tumour protein p53 Twist basic helix‐loop‐helix transcription factor Thioredoxin reductase 1 Uterine aspirate Ultraviolet Vascular cell adhesion molecule 1 Vascular endothelial cadherin Vascular endothelial growth factor Western blot World Health Organization Wingless-type MMTV integration site family Zinc finger E-box binding homeobox 1 Zinc finger E-box binding homeobox 2
Chapter 1. Introduction
1.1 Endometrial cancer 1.1.1 Epidemiology Incidence and mortality Endometrial cancer is the sixth most common cancer in women worldwide, the fourth in developed countries, and the third in Spain
(Table 1). Moreover, it is
the most common gynaecologic malignancy of the female genital tract in western countries. Based on the last Globocan data, the number of estimated cases in 2012 is 319,605 women in the world 2. The estimated incidence ASR(W) (age-worldstandardized rate) is 8.2/100,000 and the accumulated risk (0-74 years) is 0.97%. In Spain, the estimation is of 5,121 cases diagnosed in 2012 and the accumulated risk is 1.4%. The geographic distribution of endometrial cancer in the world is considerably unequal (Figure 1). The highest incidence ASR(W) is registered in the more developed regions: 14.7 vs. 5.5 for the less developed regions. The accumulated risk in the more and less developed regions are 1.79% and 0.63%, respectively. The estimated incidence ASR(W) for the US is 19.5 and 13.9 for Europe.
World Breast Colon Lung Cervix uteri Stomach Corpus uteri
25.1 9.2 8.8 7.9 4.8
Breast Colon Lung Corpus uteri Thyroid
28.1 11.8 10.0 5.3 4.3
Breast Colon Corpus uteri Lung Ovary
29.0 14.9 5.9 5.7 3.7
Non-Hodgkin lymphoma Melanoma Others
3.2 3.1 27.7
Table 1. Ten leading cancers in women (type and percentage of diagnosed women) from Globocan 2012 (http://globocan.iarc.fr).
Figure 1. Estimated incidence ASR(W) of corpus uteri cancer per 100,000 person-year (from http://globocan.iarc.fr).
The latest available data (Cancer Incidence in Five Continents Volume X, CI5X, based on diagnoses made in the period 2003-2007), which allows comparing the structure of these ASR(W) incidence rates by age (Figure 2), shows very similar profiles between Spain, Europe and the US with a maximum incidence 9>
Chapter 1. Introduction reached at 65 years. However, we observed that the incidence for this age is slightly higher for Europe and the US compared to Spain.
Figure 2. Incidence ASR(W) in Spain, Europe and USA by age from IARC.
In the last few years, the incidence of endometrial cancer has increased, presumably related to different reasons such as increased life expectancy of the population, increased percentage of obese women and associated pathologies like diabetes and hypertension 3. Although endometrial carcinoma presents a high incidence, this does not translate into high mortality rates (Figure 3). In fact, although endometrial cancer is the third most prevalent cancer, it is the ninth cause of death related to cancer in Spain, with a significant increase in hospital morbidity. The mortality ASR(W) for Spain is 1.9 and its 5-year prevalence is 95.5 per 100,000.
Figure 3. Incidence/Mortality ASR(W) per 100,000 (from http://globocan.iarc.fr).
In addition, as represented in the trend graph from 1980-2012, we observe a generalized increase in mortality in the cohorts over 65 years (Figure 4). This could be explained by the increased life expectancy of the Spanish population.
Figure 4. Evolution of mortality in Spain by age cohort and its trends from the IARC.
Chapter 1. Introduction Survival The survival of patients with cancer is the main indicator of the effectiveness of the healthcare system. It is presented as the proportion of cases surviving 1-, 3and 5-years from the time of diagnosis. The 1- and 5-year survival rates for endometrial cancer in Spain are 89.00% and 74.43%, respectively (data obtained from the European Cancer Registry Based Study on Survival and Care-EUROCARE 5 for the period 2000-2007) 4. These survival rates are slightly below the European average (90.45% and 76.19%, respectively) (Table 2). Compared to the previous EUROCARE 4, for the period 1995-1999, the rate has increased by 1.30%. Population
Survival is strongly influenced by the stage of the cancer at the time of diagnosis and the effectiveness of therapeutic procedures. Specific studies from data of the US shows that around 67% of cases are diagnosed when the tumour is still localized, 21% at regional stage and 8% at distant stage 1. Depending on whether the cancer is diagnosed at local, regional, or distant stages, the 5-year survival rates are 95%, 68%, or 17%, respectively (Figure 5). As seen in the graphs, endometrial cancer may be associated with race. The relative survival for Caucasians exceeds that of African Americans at every stage of diagnosis.
Figure 5. Endometrial cancer: stage at diagnosis and 5-year survival rate by race. On the left, distribution of endometrial cancer by race and stage at diagnosis (USA 2005-2011). On the right, 5-year survival rates among patients diagnosed with endometrial cancer by race and 1 stage at diagnosis (USA 2005-2011), from Siegel et al. .
1.1.2 Risk factors Although the aetiology of endometrial cancer is not clear, several risk factors have been identified: the association with long-term exposure to endogenous or exogenous oestrogen, obesity, hypertension, diabetes mellitus, some granulosa cell oestrogen-secreting tumours and genetic factors 5–7.
220.127.116.11 Long-term unopposed endogenous and exogenous oestrogen exposure Endometrial cancer, type I (section 18.104.22.168), has been associated with an excess of oestrogen exposure. In fact, prolonged exposure to oestrogen (specially unopposed by progesterone) promotes uncontrolled cell proliferation of the endometrium and an increase in its thickness. In addition, it also inhibits apoptosis through a downstream cascade of transcriptional changes that include the modulation of tumour suppressor functions. Moreover, uncontrolled processes of cell determination and differentiation increase the risk of random mutations, DNA replication errors and as consequence an increase in the possibility of cancer development. Then, all these changes might lead to endometrial hyperplasia, which is known to be the precursor lesion of endometrial cancer (see section 22.214.171.124) (Figure 6) 6.
Chapter 1. Introduction
High oestrogen level unopposed by progesterone
Figure 6. Proposed model for endometrial cancer type I, adapted from Ali AT. et al. .
A) Endogenous oestrogen exposure The most well known conditions related to hyperoestrogenism and hence, to an elevated risk of endometrial carcinoma, are age, early menarche, late menopause, infertility, nulliparity and chronic anovulation, since all of these situations increase the lifetime exposure to oestrogen. These risk factors are briefly described below. Age Endometrial cancer affects especially women older than 50 years, in more than 90% of cases. The mean age of detection is comprised between 62.6 and 68.7 years 8,9 presenting a maximum at 65 years. Only around 3-5% of the cases are presented in women <40 years. In fact, oestrogens have a larger effect after the menopause, since the compensatory levels of progesterone produced by the ovaries before the menopause have disappeared leading to an unopposed hyperoestrogenism.
Menarche and menopause Early menarche and late menopause are risk factors for the development of endometrial carcinoma
. Early menarche is associated with an earlier onset
of ovulatory cycles and exposure to oestrogens. If this event is also accompanied by late age at menopause, the time of oestrogen exposure will be even longer because of the increased number of menstrual cycles 12. Infertility and nulliparity Infertility is one of the main causes of endometrial cancer in women <40 years 16
. This is due to irregular menstrual periods or infrequent ovulation and chronic
, both processes associated with increased oestrogen production
and progesterone deficiency 6. Also, nulliparity is associated with 2- to 3-fold increase in the risk of endometrial cancer due to a higher number of ovulatory menstrual cycles with absence of pregnancy and lactation 11. Polycystic ovary syndrome (PCOS) Polycystic ovary syndrome (PCOS) is the most common ovulatory disorder that may cause chronic infertility when not treated. PCOS is characterized by a deficiency in progesterone levels that leads to the appearance of irregular menstrual cycles or even anovulation. Women diagnosed with PCOS have 3 times more risk of developing endometrial cancer
. This is due to a
prolonged anovulation and consequential release of oestrogens. Unopposed oestrogen may enhance the development and growth of endometrial cancer, especially in young women.
B) Exogenous oestrogen exposure Oestrogen therapy Oestrogen therapy is the use of oestrogen to balance the symptoms of the menopause
. The use of oestrogen alone increases the risk of endometrial
cancer by 5-fold as it prolongs the exposure to oestrogen by delaying the age of the menopause. It has also been associated to an increase in the incidence of hyperplasia from 20-50% after one year of therapy without progesterone
Chapter 1. Introduction The risk is related to the dose and the duration of the exposure to oestrogen and even continues to be higher when women no longer use oestrogen. Hormone replacement therapy Once the effects of using oestrogen alone were evidenced by an increase in the incidence of endometrial cancer, hormone replacement therapy was used as a substitute. This therapy consists of a combination of oestrogen and progestin, the last one used to attenuate the risk of unopposed oestrogen exposure
The results concerning the study of the associated risk of hormone replacement therapy are still controversial. Although most studies have shown an increase in the risk of endometrial cancer, some have found a decrease in the risk, or even no reported association 11,26–28. Tamoxifen Tamoxifen is the hormonal anti-oestrogen therapy used in pre-menopausal women with oestrogen-receptor-positive breast cancer, and a standard treatment in post-menopausal women with breast cancer. It is a selective oestrogen receptor modulator that, while presenting antagonistic effects in specific tissues, like for the breast, it presents agonistic effects in others tissues, including the uterus. The endometrial activity of tamoxifen appears to depend upon menopausal status
. The increased risk of developing endometrial
cancer with the use of tamoxifen in postmenopausal women is well established.
126.96.36.199 Obesity The association between obesity and the incidence of endometrial cancer has been demonstrated
. Obesity is one of the major contributors to the
increasing occurrence of endometrial carcinoma in western countries
postmenopausal women have the propensity for a chronic oestrogenic stimulation that is not counterbalanced and this could lead to endometrial hyperplasia and endometrial carcinoma. Large-scale conversion of adrenal precursors into oestrone and oestradiol by the adipose tissues in women with obesity are the main reasons for excessive endogenous oestrogen levels 7. Androgens produced by the adrenal cortex and postmenopausal ovaries are converted into oestrogens by aromatase enzymes that are also found in
. In addition, increased fat accumulation has been associated
with high levels of cytokines TNF-α, leading to stimulation of de novo synthesis of oestrogen
. Obesity is also associated with increased levels of insulin and
insulin-like growth factor-1 (IGF-1). Both of them are ligands of the PI3K signalling pathway and could lead to the activation of the pathway, and as consequence, stimulating processes like cell proliferation and survival 31,34.
188.8.131.52 Diabetes and hypertension Though the exact causes are not still well understood, the association of the incidence of endometrial cancer with hypertension and diabetes has been described 31,35.
184.108.40.206 Genetic factors The hereditary component only represents approximately 5% to 10% of all reported endometrial cancer cases. Patients with inherited diseases such as Lynch II syndrome, Cowden syndrome or Peutz-Jeghers syndrome and BRCA mutation present an increased risk of developing endometrial cancer. Lynch II syndrome Lynch II syndrome or hereditary non-polyposis colorectal cancer (HNPCC), is an autosomal dominant disease caused by pathogenic germ line mutations in DNA mismatch repair (MMR) genes
. Endometrial cancer represents the
second most common cancer in families diagnosed with HNPCC. In addition to an increased risk of suffering endometrial cancer, these patients also present an increased risk of developing ovarian, colorectal and gastric cancers 37. Cowden syndrome and Peutz-Jeghers syndrome Cowden syndrome is an autosomal dominant inherited disease, and part of the PTEN hamartoma tumour syndrome. Cowden syndrome patients have increased risk of both benign and cancerous tumours of breast, thyroid, colorectal, kidney, skin, and endometrium endometrial cancer is 5-10% 39.
. The cancer lifetime risk for
Chapter 1. Introduction BRCA Women with mutated breast cancer genes, BRCA1 or BRCA2, have up to an 87% risk of developing breast cancer by age 70 and also a high risk of developing ovarian cancer. However, the link between having a BRCA1 or BRCA2 mutation and a higher risk of developing uterine cancer is not clear. A recent study suggests that women presenting a BRCA1 mutation have a slightly higher risk of developing serous or serous-like endometrial cancer 40.
1.1.3 Protective factors In contrast to the risk factors explained before, lower levels of oestrogen exposure are related to a decreased incidence of endometrial cancer
the factors related to the lower levels of oestrogen exposure are, women with delayed menarche, with a high number of children and/or longer period of lactation. In addition, the use of oral contraceptives also decreases the risk of developing endometrial cancer
. In all aforementioned conditions, the levels
of progesterone are increased resulting in the thinning and atrophy of the uterine glands. Although smoking is clearly related to many adverse effects, it has been associated to a decrease in the risk of developing endometrial cancer
Smoking presents an anti-oestrogenic effect, maybe involved in the absorption and metabolism of hormones, and it is also related with the loss of weight and earlier menopause. Lastly, some practices such as physical activity also provide protection against endometrial cancer 45.
1.1.4 Diagnosis 220.127.116.11 Screening recommendations based on the assessed risk for endometrial cancer Women at average and increased risk for endometrial cancer Women at average and increased risk for endometrial cancer, due to the use of unopposed oestrogen therapy, late menopause, undergoing tamoxifen
treatment, nulliparity, infertility, obesity, diabetes or hypertension, should be informed of the risks and symptoms of endometrial cancer and strongly advised to inform gynaecologists of any associated symptoms in order to diagnose the malignancy in an early stage and to receive the appropriate treatment
is no indication for a general population screening, as it does not present advantages in the early detection of endometrial cancer or reduction in mortality. The histological study will only be performed after presenting any symptomatology
. In fact, some studies lead to the conclusion that a general
screening in asymptomatic women will increase the number of unnecessary biopsies because of false-positive test results, due to anxiety or complications from the biopsies 47,48. Women at high risk for endometrial cancer Women diagnosed with HNPCC, women with a family history of the mutation, and women without genetic testing results but from families with a suspected autosomal dominant predisposition to colon cancer, are considered at high risk for endometrial cancer. For these women, an annual screening from 35 years of age is recommended. Due to the limited efficacy of screening, when women have no desire of having more children, the option of prophylactic hysterectomy and bilateral salpingo-oophorectomy should be considered 8,49.
18.104.22.168 Suspected diagnosis: clinical examination Signs and symptomatology The most common early symptom of endometrial cancer is abnormal vaginal bleeding. The blood originates in the uterine cavity, where the tumour is located, and drains out of the vagina 8. In fact, abnormal vaginal bleeding is present in around 90% of endometrial cancer patients. Women in the pre- and perimenopausal periods could experience irregular bleeding changes
due to hormonal
but when the bleeding occurs in postmenopausal women it should
always be treated as a sign that deserves an evaluation by the clinician
probability of cancer in postmenopausal women which present irregular vaginal bleeding is comprised between 5-10%, the overall risk increases when women get older and with risk factors 53.
Chapter 1. Introduction Some frequently reported symptoms of endometrial cancer are: lower abdominal pain or pelvic cramping, thin white or clear vaginal discharge in postmenopausal women, changes in bowel or bladder functions, anaemia and shortness of breath. However, most of them have been related to a more advanced stage of the disease 54 . Pelvic examination During a pelvic examination, the gynaecologist inspects the vulva for irritations, lesions or abnormal vaginal discharge. Palpation of the vulva is performed and an examination of the internal organs is undertaken in order to evaluate if they are enlarged or tender. The use of a speculum into the vagina allows an examination of the cervix and the vaginal walls. In general, the results of a pelvic examination are normal in the size, shape and consistency of the uterus, until the disease is in an advanced stage. Transvaginal ultrasound Transvaginal ultrasound is the diagnostic imaging technique of choice for the evaluation of the endometrium in patients presenting abnormal vaginal bleeding 3
. This technique leads the clinicians to discard others pathologies like myomas,
polyps and also to evaluate the thickness of the endometrium. The use of ultrasound in premenopausal women presents increased difficulty because of the changes in the thickness of the endometrial wall due to cyclic hormonal variations. Transvaginal ultrasound normality is set to a cut-off of <4-5 mm, including both endometrial layers
. In a recent meta-analysis, the authors
found a diagnostic accuracy characterized by a sensitivity of 95% and 98% with a specificity of 47% and 35%, respectively, at a cut-off of ≤4 mm and ≤3 mm. They reported that the use of transvaginal ultrasound is justified, and recommend decreasing the cut-off to ≤3 mm
. Although it presents a high
sensitivity, a final definitive diagnosis will usually require endometrial sampling (Section 22.214.171.124). Moreover, transvaginal ultrasound has been described as a potential tool to determine pre-operatively, myometrial infiltration (sensitivity 62-78%, specificity 81-94%) and cervical stroma infiltration (sensitivity 77-86%, specificity 85-99%) 58–61
126.96.36.199 Confirmatory diagnosis: pathological examination When there is a suspicion of endometrial cancer, the gold standard diagnosis is pathological examination of an endometrial biopsy (Figure 7), i.e. a sample of the endometrium is collected and analysed microscopically by the pathologist.
Endometrial Biopsy By aspiration
Figure 7. Biopsy by aspiration and by hysteroscopy.
Endometrial biopsies can be performed by aspiration, with a straw-like device (pipelle) that suctions in the uterine cavity, or by the use of a hysteroscope and a catheter. The hysteroscope is placed in the vagina to enable the visualization of the uterine cavity, and the catheter is introduced through the cervical opening to collect small pieces of selected endometrial tissue. When biopsy by aspiration is not suitable for the patient, due to cervical stenosis or discomfort, or when the result from its analysis is not conclusive, a biopsy by hysteroscopy should be done
. Although both techniques are
excellent diagnostic tools, the biopsy by aspiration presents some advantages (Table 3). The Spanish Society of Gynaecology and Obstetrics (SEGO) consider the endometrial biopsy by aspiration as the first method of choice for diagnosis 3.
Chapter 1. Introduction Biopsy by aspiration
Biopsy by hysteroscopy
Less expensive Less painful Performed as an office procedure No anaesthesia Faster
More expensive More invasive Performed at the hospital Previous anaesthesia Previous blood testing required Increased risk of dissemination of endometrial cancer cells in the peritoneal cavity 63
No dissemination of endometrial cancer cells
Table 3. Features of the methods used for obtaining endometrial biopsies.
1.1.5 Endometrial preneoplastic lesions 188.8.131.52 Endometrial hyperplasia Endometrial hyperplasia is defined as an increase in the gland to stroma ratio, greater than 1:1. Although the exact pathogenesis of the hyperplasia is not clear, this lesion is thought to result from excessive or unopposed oestrogen stimulation. However, it has also been described as an abnormal response by the endometrial glands to normal levels of oestrogen in some women 64. The most commonly used classification system for endometrial hyperplasia is the World Health Organization (WHO) system, which is based on the architectural pattern of the endometrial glands and the presence or absence of cytologic atypia
. This classification leads to four possible categories: simple
hyperplasia without atypia, complex hyperplasia without atypia, simple hyperplasia with atypia and complex hyperplasia with atypia 66 (Figure 8): •
Endometrial hyperplasia (simple or complex): irregularity and cystic dilatation of glands (simple) or crowding and budding of glands (complex) without atypia.
Endometrial hyperplasia with atypia (simple or complex): simple or complex architectural pattern of endometrial glands, with atypical changes including cell stratification, tufting, loss of nuclear polarity, enlarged nuclei, and an increase in mitotic activity.
Kurman et al. found that, without treatment for a mean of 13 years, lesions with different degrees of complexity and atypia progressed to adenocarcinoma. Simple hyperplasia was associated with a 1% rate of progression to endometrial
cancer, complex hyperplasia was associated with a 3% rate, simple hyperplasia with atypia was associated with an 8% rate, and complex hyperplasia with atypia was the most significantly associated with cancer progression reaching a rate of 29% 67.
Figure 8. Endometrial hyperplasia (A) simple without atypia, (B) simple with atypia, (C) complex without atypia and (D) complex with atypia.
Despite the WHO classification having a good correlation in general with the risk of progression to cancer, this system presents limitations in the variability and the reproducibility of the diagnosis amongst specialized pathologists
This is why an alternative classification, proposed in origin by the International Endometrial Collaborative Group, divides the lesion into benign hyperplasia and endometrial intraepithelial neoplasia (EIN) 64. EIN is a premalignant clonal glandular proliferation with strict histologically defined criteria and improved prognostic value. By using computerized morphometric analysis, the stromal volume can be measured: epithelial crowding in precancers displaces stroma to a point at which the stromal volume is less than approximately half of the total tissue volume (stroma epithelium
Chapter 1. Introduction gland lumen)
. Women with EIN who remain cancer free for the first year
after diagnosis, have a 45-fold increased risk of eventual progression to endometrial cancer 72. Although 85% of EIN lesions would be diagnosed as atypical hyperplasia in the WHO classification system, this means that the other 15% of EIN without atypia would not be properly classified at high risk of progression according to this classification
. This fact highlights the evident limitation of the WHO
1.1.6 Classification Endometrial cancer is composed of biologically and histologically by diverse neoplasms with different pathogeneses. In order to include this heterogeneity on current classification systems, the clinicians estimate the histological type and grade of the tumours, as well as the anatomical site and the clinical and pathological extent of the disease.
184.108.40.206 Dualistic classification In 1983, Bokhman et al. described a dualistic model of endometrial cancer
This classification has been used to categorize this malignancy up to present. Based on clinical, pathological and molecular features, two main categories of endometrial carcinoma have been described: type I (endometrioid) and type II (non-endometrioid). This section will only address the clinical and pathological aspects. The molecular features of each type will be explained in section 220.127.116.11. Type I or endometrioid adenocarcinomas represent around 80-90% of endometrial carcinomas
. They normally express oestrogen and progesterone
receptors and are associated with excessive exposure to oestrogen. They occur in pre- or perimenopausal women and are usually preceded by endometrial hyperplasia with or without atypia
. They are usually well-differentiated
tumours (low-grade) and are composed of glands that resemble in major measure the normal endometrium. Rare mucinous adenocarcinomas are also
considered type I carcinomas, since they usually express oestrogen and progesterone receptors and they are also basically low-grading tumours 74. Type II or non-endometrioid carcinomas only represent around 10-20%. The most common non-endometrioid cancer is the serous carcinoma, followed by the clear cell carcinoma. They are high-grade tumours and present a significantly worse prognosis. By contrast with type I tumours, type II are hormone-independent tumours and related to EIN precursor lesions. When diagnosed, around 20% of patients present myometrial invasion and/or lymph node involvement, the main indicators associated with a poor prognosis and a decrease in the survival rate. A summary of the principal characteristics of endometrioid and nonendometrioid tumours are listed in Table 4. Features
Diagnosis in early stage
Diagnosis in advanced stage
Associated with unopposed oestrogen exposure
Not associated with oestrogen exposure
Table 4. Clinicopathological classification of endometrial cancer.
18.104.22.168 Histological classification The current classification of endometrial adenocarcinomas by the International Society of Gynaecological Pathologists and the WHO
cancers based on their histology and the features of the individual cancer cells (Table 5).
Endometrioid adenocarcinoma Endometrioid adenocarcinoma is the most common endometrial cancer (8085%). It has been defined as a primary endometrial adenocarcinoma containing glands with resemblance to the normal endometrium glands (Figure 9). Endometrioid adenocarcinoma is characterized by a diverse spectrum of histological differentiation going from a very well-differentiated carcinoma that resembles a complex hyperplasia with atypia to a poorly-differentiated carcinoma that can even be compared to an undifferentiated carcinoma
fact, they are graded based on the amount of solid growth of the glandular component, adjusted by nuclear features 75. •
Histologic Grade 2: well-formed glands with interspersed solid sheets of neoplastic cells (<50% solid growth).
Histologic Grade 3: solid sheets of cells with hardly recognizable glands, presenting nuclear atypia and higher mitotic activity (> 50% solid growth).
Severe nuclear atypia raises the grade by one.
A common feature of the endometrioid adenocarcinoma is the presence of glandular or villoglandular structures, lined by simple to pseudostratified columnar cells with their axes perpendicular to the basement membrane and slightly elongated nuclei polarized in the same direction.
Figure 9. Endometrioid adenocarcinoma of the endometrium, grade 1.
This histology presents some variants comprising: adenocarcinomas with squamous, secretory or ciliated differentiation. Mucinous adenocarcinoma Mucinous adenocarcinoma represents the 0.6-5% of endometrial cancer cases. It is characterized by the presence of intracytoplasmic mucin (Figure 10). It has been observed that both endometrioid and clear cell adenocarcinomas may have large amounts of intraluminal mucin, but the mucinous adenocarcinoma is the only one that contains mucin within the cytoplasm 65.
Chapter 1. Introduction
Figure 10. Mucinous adenocarcinoma containing mucin in the cytoplasm.
microglandular pattern that could be confused with a microglandular hyperplasia 76,77
. These neoplasms have been reported as microglandular carcinomas. Rare
intestinal differentiation can be observed in mucinous adenocarcinomas, containing goblet cells 65. Mucinous adenocarcinomas are graded like endometrioid adenocarcinomas, but they are usually grade 1. Serous adenocarcinoma Serous carcinoma is the major type II or non-endometrioid carcinoma (5-10%). It has been described as a primary adenocarcinoma of the endometrium, which comprises a complex pattern of papillae with cellular budding and could contain psammoma bodies. The papillae usually have fibrovascular cores, secondary and tertiary papillary processes and sloughing of the cells
(Figure 11). The nuclei are generally
rounded and non-perpendicular to the basement membrane. The nuclei present poor differentiation and are more often apically localized. They usually present eosinophilic macronucleoli, solid cell nests and foci of necrosis. Psammoma bodies are found in about 30% of cases and can be found in high quantity. When the tumour grows in a glandular pattern, the glands are generally complex and "labyrinthine".
Figure 11. Serous adenocarcinoma. Papillae covered by cuboid and cylindrical cells with pleomorphic nucleus.
Serous carcinoma could come from an endometrial intraepithelial neoplasia 81,82
. In contrast with endometrioid adenocarcinomas, serous carcinoma is a
high-grade carcinoma and is not graded
. Moreover, it has been observed in
older patients, frequently diagnosed at advanced stages and highly related to recurrence and a poor outcome. Clear cell adenocarcinoma Clear cell adenocarcinoma is the second most common type II or nonendometrioid carcinoma (1-4%). Clear cell adenocarcinoma is composed of clear or hobnail cells arranged in solid, tubulocystic or papillary patterns or a combination of both. Histologically, it is composed of clear, glycogen-filled cells and hobnail cells that project individually into lumens and papillary spaces (Figure 12). It contains large, highly pleomorphic nuclei and multinucleated forms. The architectural growth pattern could be tubular, papillary, tubulocystic or solid and more frequently a mixture of them. Occasionally the neoplastic cells present granular eosinophilic cytoplasm 65,84.
Chapter 1. Introduction
Figure 12. Clear cell adenocarcinoma.
Like serous carcinoma, it is present in older patient populations, diagnosed at advanced stages and not graded. Mixed cell adenocarcinoma Mixed adenocarcinoma (Figure 13) is composed of both type I and type II carcinomas in which the less represented type comprises at least 10% of the tumour volume. The pathologist will report the percentage of the minor component and it has been found that ≥25% of a type II tumour suggests a worse prognosis 83.
Figure 13. Mixed carcinoma of endometrioid (left) and serous (right) carcinomas. Only the serous component presents positive p53 nuclear staining.
Squamous cell carcinoma Squamous cell carcinoma is composed of squamous cells of varying degrees of differentiation
(Figure 14). It occurs in postmenopausal women and it is
associated with cervical stenosis and pyometra, however it is really uncommon (0.1-0.5%).
Its appearance is essentially identical to squamous cell carcinoma of the cervix, including a rare verrucous variant 85,86. The prognosis of this endometrial cancer is really poor, whereas the verrucous variant is more favourable. Transitional cell carcinoma Transitional cell carcinoma is an extremely rare endometrial carcinoma. It is composed of at least 90% of cells resembling urothelial transitional cells (Figure 15). If the percentage of transitional cells is smaller, the tumour would be diagnosed as mixed carcinoma with transitional cell differentiation 65.
Chapter 1. Introduction
Figure 15. Transitional disposition of neoplastic cells.
The tumours are often polypoid or papillary and the transitional component is graded 2-3. All endometrial transitional cell carcinomas are cytokeratin-20 negative and cytokeratin-7 positive
. Human papillomavirus type 16 has
been described in 22% of studied cases, suggesting an etiologic role 87. Small cell carcinoma Small cell carcinoma is a rare tumour <1% of all endometrial carcinomas. It resembles the small lung cell carcinoma (Figure 16). Small cell carcinomas are positive for cytokeratin and frequently positive for neuroendocrine markers, while one half of all cases are positive for vimentin. The prognosis is better than all small cell carcinoma in other organs with a 5year survival of around 60% 89.
Figure 16. Small cell carcinoma. Sheet distribution of small atypical cells.
Undifferentiated carcinoma Undifferentiated carcinomas are characterized by a lack of differentiation.
22.214.171.124 FIGO staging The International Federation of Gynaecology and Obstetrics (FIGO) developed its classification and staging system for endometrial cancer in 1958. The staging of endometrial cancer was changed from clinical to surgico-pathologic in 1988. The surgical staging was updated in 2009 (Table 6), to solve the problems observed in reproducibility, accuracy, and predictive value noticed during previous years
. The FIGO staging provides relevant information to assess
the spread of the tumour in the body (Figure 17). It uses surgical and pathological staging. For the pathological assessment all these parameters are evaluated: •
Tumour size and location
Extension of tumour to Fallopian tubes and ovaries
Tumour grade and histology
Lymphovascular space invasion (LVSI)
Lymph node status
Chapter 1. Introduction Stage I
Tumour confined to the corpus uteri
No or <50% invasion of the myometrium
Invasion ≥50% of the myometrium
Tumour invades cervical stroma but does not extend beyond the uterus
Local and/or regional spread of the tumour
Tumour invades serosa of the corpus uteri and/or adnexae
Vaginal and/or parametrial involvement
Positive pelvic lymph nodes
Positive para-aortic lymph nodes with or without pelvic nodes
Distant metastases including intra-abdominal and/or inguinal lymph nodes Table 6. Revised FIGO staging, adapted from Plataniotis et al.
Figure 17. FIGO staging from Cancer Research UK (CRUK) CC BY-SA 4.0, via Wikimedia commons.
1.1.7 Molecular bases Tumour development comprises genetic, epigenetic and functional changes at the cell metabolism, regulation of gene expression and cell division. Oncogenes and tumour suppressor genes are two categories of genes that play a key role in cancer development. Proto-oncogenes are involved in processes of growth and maintenance of tissues and organs. They stimulate cell division, stop apoptosis and control cell differentiation. Gain-of-function mutations change proto-oncogenes in oncogenes. At the cellular level, the oncogenes act as dominant, under activation or aberrant increased expression, one mutated copy (allele) is sufficient to alter the phenotype of the cell to malignant 93. By contrast, tumour suppressor genes promote tumorigenicity through a loss-of-function in both alleles. Damage in tumour suppressor genes allows tumour growth and cell death escape.
126.96.36.199 Dualistic model In addition to the clinical and pathological aspects (section 188.8.131.52) the dualistic classification of endometrial cancer on genetic alterations
divides type I and type II cancers based
. The predominant molecular alterations for each type
are given in Table 7 and in the following sections.
Type I (%)
Type II (%)
ER and PR expression
Table 7. Genetic alterations in endometrial cancer by type (%), adapted from N. Bansal et al. ER and PR: oestrogen and progesterone receptors.
Chapter 1. Introduction
A) Type I endometrioid endometrial cancer PTEN silencing Phospatase and TENsin homolog (PTEN) gene codes a 47 KDa protein with tyrosine kinase activity that acts as a tumour suppressor gene. PTEN is altered in around 80% of endometrioid endometrial cancers due to mutations that lead to a loss of expression to a loss of heterozygosity (LOH)
. Inactivation of PTEN is
, and to a lesser extent due
or promoter hypermethylation. Loss of
PTEN has been found in precancerous lesions and as a consequence linked to an early event in endometrial cancer, which probably originated in response to hormonal associated risks 98. PTEN has been observed to have both lipid and phosphatase activity, leading to different functions
. The lipid phosphatase activity negatively regulates the
level of phosphatidylinositol (3,4,5)-triphosphate and partially, in co-operation with increased p27, causes cell cycle arrest at the G1/S stage
. Mutation of
PTEN increases the activation of phosphatidylinositol 3-kinase (PI3KCA) leading to AKT phosphorylation
. The PTEN phosphatase activity is involved
in inhibition of focal adhesion formation, cell spread and migration, as well as MAPK signalling inhibition. Consequently, altered PTEN expression leads to tumour cell growth, escape to apoptosis, and atypical cell spreading and migration. Microsatellite instability The human genome is divided into DNA coding sequences (1.5%) and noncoding sequences (98.5%). Around half of noncoding DNA consists of different types of repetitive sequences, whose function is to maintain the chromosomal structure and is involved in the evolution of genes and genomes 101
. Microsatellite DNA are sections of 2-5 nucleotides in various places of the
genome, which due to their repetitive structure are susceptible to replication errors. Accumulated mutations in these sequences during DNA replication and defects in the mismatch repair system (MMR) lead to microsatellite instability (MSI)
. The most well known members of the MMR are: MLH1, MSH2 or
MSH6. MSI has been described in around 20% of sporadic endometrioid endometrial carcinomas
. In endometrial cancer, MLH1 inactivation due to <;
hypermethylation of CpG islands is the most common mechanism leading to MSI 104. MSI has been reported to be more common in endometrioid than nonendometrioid cancers
. In fact, an association between MSI and PTEN
mutation has been reported for endometrioid endometrial carcinomas. In patients presenting MSI the ratio of mutation in PTEN increases up to 60-80% compared to a 24-35% in tumours without MSI
. This suggests that PTEN
could be a target gene for mutations in a deficient DNA repair scenario. KRAS KRAS oncogene codes a 21 KDa protein involved in the signal transduction pathway of cell proliferation and differentiation. Mutation in KRAS results in an activation of the pathway leading to unregulated proliferation and reduced cell differentiation 99. KRAS mutations have been found in 10–30% of endometrial carcinomas, predominantly in endometrioid tumours
. The KRAS mutation has also
been found in 16% of endometrial hyperplasia cases
. Consequently, this
mutation is related to an early event in endometrial cancer. CTNNB1 The CTNNB1 gene codes the β-catenin protein, a component of the adherens junctions and of the E-cadherin complex. As a consequence it has a relevant role in tissue architecture maintenance, cell differentiation, and signal transduction. Moreover, β-catenin is a downstream member of the WNT signalling pathway, which is related to embryogenesis and tumorigenesis
Mutation in this gene leads to protein stabilization and as a consequence, protein accumulation in the cytoplasm, the nucleus and constitutive target gene activity 111. β-catenin nuclear accumulation has been widely reported in endometrioid compared to non-endometrioid endometrial carcinomas, and also in hyperplasia with atypia. Thus, the CTNNB1 mutation is linked to an early event in endometrial carcinogenesis 112.
Chapter 1. Introduction Oestrogen and progesterone receptors Oestrogen (ER) and progesterone (PR) receptors belong to a group of nuclear receptors. They act as transcription factors by binding to specific locations on the DNA. ER belongs to the group of receptors under 17β-oestradiol activation. It presents two different subtypes, ERα and ERβ, encoded by different genes. While ERα is the main receptor in the endometrium and leads to increased proliferation, ERβ has an antiproliferative effect and modulates the ERα mediated functions 99. The balance of the two different isoforms is crucial in type I endometrioid carcinoma. In fact, significant differences in the ERα/β mRNA ratios and protein expression between normal endometrium and endometrial carcinoma were evidenced. Decreasing levels of ERα have been described in both well-differentiated and poorly-differentiated tumours compared to control postmenopausal women 113. The PR is an intracellular receptor that binds to progesterone. Two isoforms of PR have been observed, PR-A and PR-B, each one with a different molecular weight. In the endometrium, PR-A downregulates the effects of ERα activity while PR-B acts as an oestrogen agonist. As in the case of the ERs, the imbalance of the PR isoforms ratio is critical in endometrial tumorigenesis
The absence of ER and PR has been related to tumour aggressiveness and bad prognosis 113,115. A summary of the molecular events associated to the development of endometrioid endometrial carcinoma is presented in Figure 18.
Figure 18. Molecular events associated with endometrioid endometrial carcinoma.
B) Type II non-edometrioid endometrial cancer Aneuploidy p53 mutation The p53 gene encodes a tumour suppressor protein containing transcriptional activation, DNA binding, and oligomerization domains. It has a crucial function by stopping the propagation of cells with DNA damage. Mutation in the p53 tumour suppressor gene is the most common mutation in type II (nonendometrioid) endometrial cancer, and it is present in around 80-90% of these tumours. After DNA damage, p53 accumulates in the nucleus and causes cell cycle arrest and apoptosis
. Mutated p53 leads to a non-functional protein
that accumulates within the cell and acts as a double negative inhibitor of the wild-type p53 95. Her2/neu amplification Her2/neu (c-erbB2) is an oncogene, that codes for a transmembrane glycoprotein receptor, tyrosine kinase, which is involved in cell growth, survival, adhesion, migration and differentiation
. Amplification of Her2/neu has been
described in 10-30% of all endometrial carcinomas and in 40-80% of serous endometrial cancer 116. CDH1 Cadherin 1 or epithelial cadherin (E-cadherin) is a protein that in humans is encoded by the CDH1 gene. It is a transmembrane cell adhesion molecule, composed of 5 extracellular domains and one cytoplasmic tail, which lead to linkage to the actin cytoskeleton. Reduced E-cadherin has been related to a decrease in cell-cell adhesion and as a previous step in cell migration. Negative or low E-cadherin staining has been found in 62% and 87% of serous and clear cell carcinoma, respectively 117. p16 The CDKN2A tumour suppressor gene codes for two proteins, one of them is the p16 protein, whose function is to regulate cell cycle. By binding to cyclin dependent kinases 4 and 6 (CDK4 and CDK6), p16 blocks their abilities to
Chapter 1. Introduction stimulate cell cycle progression. Inactivation of this gene occurs in around 40% of type II endometrial cancers and leads to uncontrolled cell growth 95,102. The molecular features associated with the development of a non-endometrioid carcinoma are represented in Figure 19.
Figure 19. Molecular events associated with non-endometrioid endometrial carcinoma.
184.108.40.206 TCGA model Although the dualistic classification has been broadly used, it is not entirely accurate since some endometrial cancers present shared characteristics of both type I and type II groups. Thus, a molecular classification was pursued in order to develop a more accurate subtype classification of endometrial cancer. The Cancer Genome Atlas (TCGA) Research Network proposed a novel classification based on an integrated genomic characterization of endometrial carcinoma
.The authors performed a genomic, transcriptomic and proteomic
characterization of 373 endometrial carcinomas using array and sequencing based technologies. Thanks to this extensive characterization and data analysis, the authors described a novel classification that divides endometrial carcinomas into 4 subtypes and also identifies similarities between endometrial cancer and others types of cancers. The four groups can be observed in Figure 20, and are listed as follows: •
Pole (ultramutated): this group classifies around 10% of endometrioid endometrial cancers. It is characterized by an ultrahigh somatic mutation frequency and a common hotspot mutation in the exonuclease domain of POLE. It comprises few copy-number aberrations, increased frequency of C→A transversions, and mutations in PTEN, PIK3R1, PIK3CA, FBXW7 and KRAS. It presents an excellent progression free-survival.
Microsatellite instability (MSI): this group is characterized by MLH1 promoter methylation. It also presents frameshift deletions in RLP22, frequent non-synonymous KRAS mutations, and few mutations in FBXW7, CTNNB1, PPP2R1A and p53.
Low copy-number: this group is composed basically of endometrioid tumours, with high mutation frequency in CTNNB1.
High copy-number: this group is composed essentially of serous-like tumours. Most of these tumours have p53 mutations and a high frequency of FBXW7 and PPP2R1A mutations. It presents a worse progression free-survival.
Figure 20. TCGA molecular classification of endometrial cancer. Recurrently mutated genes in 118 the four groups. Figure from G. Getz et al. .
The molecular data demonstrated that around 25% of tumours classified as high-grade endometrioid have similarities with serous carcinomas, including p53 mutations and a high copy-number. The genomic-based classification might lead to a better understanding and facilitate the development of treatments tailored to specific disease groups and thus, improve the management of these patients.
1.1.8 Prognostic factors It is generally well accepted that endometrial cancer presents a favourable prognosis, due to its early detection. However, there are still relevant subgroups
Chapter 1. Introduction of patients presenting poor prognosis. Thus, it is important to identify accurate predictive and prognostic factors that may envisage the development of recurrent disease, in order to improve the choice of primary and adjuvant therapy. Several studies demonstrated that the prognostic factors for endometrial cancer could be divided into uterine and extra-uterine factors 119–123. The uterine factors are: the histological type and grade of the tumour, the depth of myometrial infiltration, vascular invasion, the presence of endometrial hyperplasia with atypia, cervical involvement, DNA ploidy and S-phase fraction, and expression of ER and PR. By contrast, the extra-uterine factors include: a positive peritoneal cytology, adnexal involvement, presence of pelvic and para-aortic lymph node metastasis, and/or peritoneal metastasis. Among those, the most significant factors are the histological type and grade, the depth of myometrial invasion, and lymphovascular invasion
. The FIGO stage is the single most
important prognostic factor and the most used as a reference, with a significant reduction in survival in advanced stages 1. In fact, the 5-year survival rate decreases from 81% in stage I to 69% for stage II, 51% for stage III, and 16% for stage IV
. Although the spread to regional lymph nodes is an
important prognostic factor, the role of lymphadenectomy in women with earlystage tumours still remains controversial 127. Prognostic factors are assessed before and after surgical treatment to define the staging of the tumour and the risk of recurrence of each patient. Apart from medical history, clinical examination, and endometrial biopsy, the initial preoperative evaluation includes blood count, liver and renal functions tests and chest X-ray
. Magnetic resonance imaging (MRI) should be requested to
determine the cervical and nodal involvement as well as the myometrial invasion. Before surgery, the preoperative staging relies on the type and grade of the tumour, the depth of myometrial infiltration and the extent of cervical involvement, and the medical condition of the patient. The pre-operative staging will guide the extent of the surgery, which is always the primary treatment of endometrial cancer. Accurate staging of the tumour is always achieved after surgery, and it is called clinical staging.
220.127.116.11 EMT phenotype EMT is a complex process that is crucial in physiological processes, such as embryonic development, but also in pathogenic processes. In cancer, EMT is responsible for inducing a more invasive and aggressive phenotype in tumour cells. During the EMT process, epithelial cells lose their basal apical polarity and cell-cell contacts, undergo a dramatic remodelling of the cytoskeleton, change to a spindle shape morphology, and acquire a migratory phenotype. The EMT process could be initiated by several extracellular signals and secreted soluble factors that lead to the activation of specific signalling pathways and transcription factors
(Figure 21, explained in detail in section
18.104.22.168). In addition, some authors have suggested the initiation of EMT caused by dynamic interactions between the tumour microenvironment and the cancer cells 172.
Figure 21. Drivers and mediators of EMT, from Kang and Massague
A hallmark of EMT is the loss of E-cadherin expression coupled with an overexpression of mesenchymal markers like N-cadherin and cadherin 11. This
process is known as “cadherin switch” and leads to the disassembly of the cellcell junction
. In addition, cells acquire markers like smooth muscle actin,
vimentin, fibronectin and increased metalloproteinase activity (MMP-2, MMP-3 and MMP-9) 174. Loss of E-cadherin has been demonstrated to be crucial for endometrial cancer progression. In fact, a decrease in E-cadherin expression has been associated with tumour dedifferentiation, myometrial invasion and patients with advanced stage
. Moreover, negative E-cadherin expression has been found in
tumours with poor prognostic factors, such as grade 3 and non-endometrioid tumours 168,177. Several developmentally important genes that induced EMT have been described as E-cadherin repressors. One of them is the zinc finger protein SNAIL, a DNA binding factor that recognizes E-box motifs in target promoters, including the E-cadherin promoter
. SNAIL has been observed to participate
in endometrial progression and dedifferentiation
. In fact, SNAIL and E-
cadherin protein expression presented an inverse correlation in both primary tumours and metastasis. Moreover, an association between reduced expression of E-cadherin, nuclear expression of SNAIL and lymph node metastasis and death risk has also been established 180. Another known E-cadherin repressor is TWIST
. In fact, TWIST has been
shown to promote EMT in endometrioid endometrial cancer by direct repression of E-cadherin or by upregulation of the EMT inducer BMI-1
. TWIST helps
EMT and is responsible for a more infiltrating cell phenotype, promoting myometrial invasion and worse patient survival. Kruppel like factor 17 (KLF17) has been observed to promote EMT through the regulation of TWIST, leading to endometrioid endometrial cancer progression 183
The zinc finger protein ZEB1 has also been shown to control endometrial cancer motility in the Ishikawa cell line. ZEB1 expression in this cell line results in decreased E-cadherin and increased migration
. Moreover, a correlation
between the ZEB1 expression and the progression of gynaecological carcinomas has been found 185. >8
Chapter 1. Introduction
22.214.171.124 Molecular factors that induce EMT in endometrial cancer There are multiple factors responsible for producing EMT in endometrial cancer, some of which are described below. ETV5 In recent years, in our laboratory, a crucial role for the Ets translocation variant 5 (ETV5) in endometrial cancer progression has been proposed. ETV5 is a transcription factor, that belongs to the PEA3 subfamily of the Ets family, characterized by a sequence of 85 amino acids in an evolutionarily conserved DNA-binding domain that regulates the expression of diverse genes by binding to its promoter in a central A/GGAA/T core motif
. ETV5 is overexpressed
in endometrioid endometrial cancer with a significant increase in patients diagnosed in stage IB (FIGO 2009), associated with myometrial infiltration
ETV5 was found to correlate with metalloproteinases MMP-2 and -9 in endometrioid endometrial cancer tissues
. ETV5 transcriptionally activates
the zinc finger E-box-binding transcription factor ZEB1, resulting in decreased E-Cadherin. Overexpression of ETV5 in Hec1A led to an EMT. These included a modulation of cell-cell adhesion, cell-cell contact, cellular junctions and actin cytoskeleton reorganization. In addition, cellular functions like cell-to-cell signalling, cell movement, and adhesion to substrates were also altered 190. In an orthotopic murine model, ETV5 overexpression induces a more aggressive and infiltrative pattern of myometrial invasion. ETV5 function is mediated both in vitro and in vivo through the increased activity of MMP-2
We have also evidenced the role of ETV5 as a protective factor against oxidative stress induced by the Hep27 as well as its ETV5-dependent mitochondrial location in Hec1A cells 192. Moreover, we identified the role of the lipoma-preferred partner (LPP), which acts as a novel co-regulatory partner of ETV5 in the transcriptional regulation of the EMT process
. When ETV5 promoted EMT, LPP is reorganized from
cell-cell contacts to focal adhesions and after an external stimuli, it translocated to the nucleus establishing a crosstalk between the tumour cells and their microenvironment. All of this demonstrates its validity as an in vitro and in vivo
model that mimics invasive endometrial cancer cells in the invasive area of the tumour. Oestrogen and progesterone receptors The role of ER and PR in endometrial cancer is commonly accepted. Oestrogen has been proposed to stimulate endometrial cancer invasion by interactions between the cancer and stromal cells
. It stimulates tumour necrosis alpha
(TNF-α), which induces stromal hepatocyte growth factor (HGF) expression and as a consequence an increase in NK4, resulting in invasion of endometrial cancer cells
. ERα loss has been associated with increased EMT, vascular
invasion and myometrial invasion
while ERβ has been described as an
important factor in progression of myometrial invasion
. Van der Horst et al.
proposed that a loss of progesterone throughout the disease might promote EMT
. In this study, PR modulated cell lines were treated with
medroxyprogesterone acetate (MPA), resulting in decreased migration and downregulation of EMT markers. A downregulation of EGF, IGF-1, IL-6, integrin/ILK, PDGF, TGF-β, VEGF and Wnt/β-catenin signalling were found in the PR modulated cell lines. TGF- : TGF-β members have been described as promoters of cancer, and involved in cell proliferation, survival, migration, and invasion and as important inducers of EMT in both development and cancer
. TGF-β1 promoting EMT was
associated with the initial steps of endometrial cancer
. TGF-β binds to a
heteromeric complex of transmembrane serine/threonine kinase, the type I (RI) and type II receptors (RII). RI phosphorylates Smad2 and Smad3, which then form a heteromeric complex with Smad4, translocate into the nucleus and regulate TGF-β-responsive gene transcription
. The annulment of TGF-β
receptor signalling produced apoptosis and reduced the aggressive phenotype of endometrial cancer cells by reversal of autocrine TGF-β induced EMT 200. Other factors Other growth factors such as, EGF, IGF-1, VEGF, PDGF and FGF, and signalling pathways like Notch and Wnt/β-catenin play a major role in E-
Chapter 1. Introduction cadherin repression
. The Notch pathway induces EMT by activating
nuclear factor-Kβ (NF-Kβ) pathway or by modulating the activity of TGF. In endometrial cancer, overexpression of SHARP1 in Ishikawa cell line suppresses EMT and metastasis by attenuating NOTCH1 signalling
Wnt pathway leads to EMT through the inhibition of phosphorylation of βcatenin mediated by glycogen synthase kinase 3 beta (GSK3)
. In high-grade
endometrial cancer, the nuclear accumulation of β-catenin and its association with E-cadherin loss was related to the acquisition of an aggressive phenotype 204
. EGFR was found overexpressed in endometrial cancer
and shown to
stimulate EMT through SNAIL upregulation and consequent E-cadherin downregulation 206.
126.96.36.199 MELF type invasion Recently, a new pattern of myometrial invasion named MELF has been observed which appears in low-grade endometrioid endometrial cancers and is related to a poorer prognosis. MELF changes were more frequently found in tumours with local mucinous differentiation and often associated with vascular invasion and fibromyxoid stromal alteration. They may represent a specific tumour-stromal reaction within the myometrium and are localized specifically at the deep invasive front of tumours. The MELF pattern is characterized by the loss of standard glandular architecture, attenuation of neoplastic epithelium and infiltration of stroma by small nests of cells and individual tumour cells
. It is characterized by the
presence of microcystic, elongated and fragmented invasive glands (MELF) 209,210
that have been shown to be accompanied by a decrease in E-cadherin
. In addition to the reduced E-cadherin, they are also described by a
strong cytokeratin-7 staining, increased cyclin-D1 and p16, loss of membranous β-catenin, frequent negative staining for hormone receptors, and they are more often present in patients presenting KRAS mutation
. Another finding that
supports the hypothesis that MELFs represent active areas of the tumour is the increase in fascin expression described by Stewart et al. 213.
188.8.131.52 Tumour microenvironment Malignant tumours are complex structures that consist of cancer cells and the surrounding tumour stroma
. For tumour growth and systemic dissemination
dynamics, interactions between the cancer cells and the local/distant host environment are required 215. The extracellular matrix (ECM) and the stromal cells compose the endometrial tumour microenvironment
. The ECM suffers deep reorganization, to provide
structural support to the cells, with increased collagens, proteoglycans, and glycosaminoglycans
, whereas the stromal cells, comprising stem and
progenitor cells of the stroma, cancer-associated fibroblasts (CAFs), pericytes, endothelial cells, and inflammatory cells, supply the epithelium with abnormal paracrine factors, which enable EMT and metastatic progression through interactions with the cancer cells 218. The role of the tumour microenvironment has been evidenced in endometrial cancer. Some authors described that secretions from normal endometrial fibroblasts could inhibit proliferation, through inhibition of PI3K signalling, in the Ishikawa cell line
. Endometrial cancer cells evidenced an increase in cell
motility and invasiveness in response to CAFs secretion, suggesting a protumorigenic role in cancer progression. In fact, the use of inhibitors for PI3K/Akt and MAPK/ERK demonstrated a suppression of CAF mediated endometrial cancer proliferation 221. Although the mechanisms by which CAFs regulate invasion are not widely known, they have been found to promote cancer progression and metastasis, through the release of stromal derived factor 1 (SDF1)
growth factor (HGF) and c-Met compose another important ligand/receptor pair, which is known to produce mitogenic and motogenic effects on various cell types. Moreover, c-Met positive staining has been correlated to advanced stages
. In addition to these findings, some authors have evidenced the
interactions between tumour cells and the microenvironment, demonstrating how factors released by the surrounding stroma, play an important role in activating the expression of transcription factors in those cells undergoing an EMT
. In this way, cancer cells at the invasive front of certain carcinomas
Chapter 1. Introduction can be seen to have undergone EMT, suggesting that these cancer cells were under different microenvironmental stimuli from those received by cancer cells at the cores of these lesions. More research to deepen the understanding of the dialogue between CAFs and tumour cells is necessary.
1.2 Adhesion molecules and tumour dissemination Metastasis is a major clinical problem and one of the main causes of cancer death. The metastatic pathway is a multistep process by which cancer cells give rise to metastatic lesions in a new tissue or organ. Five sequential steps describe the metastatic pathway, including (1) cell proliferation in the primary tumour and angiogenesis, (2) local cell invasion, (3) intravasation and dissemination, (4) extravasation and (5) colonization and proliferation in new tissue or organ
. Moreover, cancer cells have to escape from the
immunological attack to successfully metastasize. As explained in the previous section, the detachment of tumour cells from the primary site is accompanied by the acquisition of an invasive phenotype through EMT and a switch in the cellcell adhesion repertoire. Cell migration of tumour cells is prone to a dynamic regulation of adhesion and de-adhesion processes, evidencing the necessity of cellular plasticity of adhesion molecules to enable metastatic spreading. The main types of cell adhesion molecules (CAMs) are: cadherins, integrins, immunoglobulin superfamily members and selectins (Figure 22). These proteins are typically transmembrane receptors and are composed of three domains: an intracellular domain that allows interactions with the cytoskeleton, a transmembrane domain, and an extracellular domain that interacts with other CAMs. They mediate cell-cell adhesion, cell-extracellular matrix adhesions, and translate external stimuli within the cell by interacting with a complex network of cytoskeletal
mechanisms, including transcriptional regulation, post-translational changes, and cleavage from the cell surface
, allowing a rapid response to external
signals like growth factors or cytokines.
Much has been written about cadherins, integrins and their role in cancer metastasis, however the immunoglobulin superfamily (IgSF) has received less attention. Nevertheless, the IgSF plays a key role in cell-cell adhesion and several members among this family have been linked to cancer progression.
Figure 22. Schematic representation of the principal cell adhesion molecules, from K. Reiss et 229 al. .
1.2.1 The immunoglobulin superfamily The immunoglobulin superfamily (IgSF) is composed of over 765 members, comprising a different range of proteins, including cell surface glycoproteins, proteins of the T cell receptors complex, virus receptors and major histocompatibility complex class I and II molecules
. IgSF members are
characterized by the presence of variable immunoglobulin Ig-like domains. Each one composed of a sandwich structure with two opposed antiparallel β-pleated sheets stabilized by a disulphide bridge and fibronectin type III repetitions
The majority of the IgSF members present the same structure: an extracellular >>
Chapter 1. Introduction domain, a single transmembrane domain and a cytoplasmic tail. However, some are linked to the cell surface through a glycosylphosphatidylinositol anchor
. Through their N-terminal domains, they mediate both homotypic and
heterotypic calcium-independent adhesion
. The extracellular interactions of
the IgSF can lead to signalling within the cell, due to their C-terminal cytoplasmic tail, which is linked to cytoskeletal or adaptor proteins. Some of the most important members of the IgSF are the intercellular adhesion molecule 1 (ICAM-1), vascular cell adhesion molecule 1 (VCAM-1), platelet endothelial cell adhesion molecule 1 (PECAM-1), neural cell adhesion molecule (NCAM), activated leukocyte cell adhesion molecule (ALCAM), L1 cell adhesion molecule (L1CAM) and melanoma cell adhesion molecule (MCAM). Several of the IgSF members have been described as biomarkers for cancer progression in different cancer types: glioma, melanoma, breast, endometrial, ovarian, prostate and colon cancer
. The specific functions associated with each IgSF
member in the metastatic process are listed in Table 11. Stage in metastasis
(i) Apoptotic evasion
(1) Cell proliferation in primary tumour
(2) Local cell invasion (i) Cell-cell interactions (ii) Directional cell migration and cell polarity (iii) Matrix degradation
MCAM, ALCAM, L1CAM MCAM MCAM, NCAM
(3) Intravasation and
MCAM, ALCAM, NCAM,
(6) Immunological scape
NCAM, MCAM, L1CAM
(5) Colonization and proliferation
ICAM-1, VCAM-1, PECAM-1,
L1CAM, PECAM-1 As for (1) and (2)
As for (1) and (2) MCAM, ALCAM, NCAM
Table 11. The role of the IgSF members in the steps of metastasis, adapted from Wong et al. 236 .
Thanks to its role in neurite outgrowth, axon guidance, and long-term potentiation, NCAM is one of the most studied members of the IgSF. NCAM
binds to FGFR, through its fibronectin type III domains, prevents FGFR endocytosis and leads to its activation. NCAM also associates with other signaltransduction molecules, like FYN and FAK
, resulting in sustained MAPK
activation together with increased cell motility, increased cell-substrate adhesion, cell migration, and invasion
. The N-cadherin binding to FGFR is
dependent on NCAM and the union of the complex, leading ultimately to the activation of β1-integrin mediated cell matrix adhesion (Figure 23).
Figure 23. NCAM and N-cadherin signalling in neurons, from Cavallaro et al.
MCAM has also been found to recruit the protein tyrosine kinase FYN to its cytoplasmic tail, leading to FAK activation
. The same was found for L1CAM,
whose expression in ovarian cancer has been linked to sustained FAK phosphorylation and resistance to apoptosis 240. Several members of the IgSF have been associated with an increase in apoptosis evasion and in angiogenesis. In fact, the expression of NCAM seems to be associated with the activation of NF-Kβ
. In addition, MCAM has been
described as an activator of the NF-Kβ pathway via the upstream p38 mitogen-
Chapter 1. Introduction activated protein kinase (MAPK)
. After acquiring apoptotic resistance,
tumour progression depends on new blood vessel formation. As regards to the role of the IgSF members in angiogenesis, the vascular endothelial growth factor (VEGF), which is secreted by tumour cells and stroma, has been shown to stimulate the expression of ICAM-1, VCAM-1 and PECAM-1 in endothelial cells. The IgSF has also been associated with the promotion of local invasion, by increasing MCAM, ALCAM and L1CAM homophilic cell-cell interactions. In fact, they have been shown to control directional cell migration and regulate the expression of metalloproteinases responsible of the degradation of ECM and tumour cells dissemination 236. Although much remains to be investigated regarding the exact mechanisms, the relation of the IgSF members to the metastatic cascade seems evident. Specifically, ALCAM has been implicated in the progression of several cancer types, but its role in tumorigenesis or its specific signalling pathways still remain unclear.
1.2.2 Activated leukocyte molecule (ALCAM)
184.108.40.206 Introduction ALCAM is a member of the IgSF and was identified by expression cloning based on its ability to bind to CD6 243,244. The human gene for ALCAM is located on chromosome 3 (3q13.1q13.2), is composed of 16 exons and has a size of over 200 kb. ALCAM orthologs are expressed in many species with alternative names such as ALCAM, CD166, MEMD, SB10 antigen and HCA in humans; HB2, KG-CAM and F84.1 antigen in rat; MuSC in mouse; DM GRASP, SC1 and BEN in chicken; and Neurolin and E21 antigen in zebrafish 245,246. ALCAM is a type I transmembrane glycoprotein of 105 kDa (69 kDa after deglycosylation) composed of an extracellular domain of 500 amino acids, a transmembrane domain of 22 amino acids, and a short cytoplasmic domain of 34 amino acids. The ALCAM extracellular domain consists of five Ig-like domains (2 NH2-terminal, membrane-distal variable-V-type and 3 membraneproximal-constant –C2-type Ig folds) 243,245 (Figure 24).
Figure 24. Schematic representation of the cell adhesion molecules VVC2C2C2 subgroup in the immunoglobulin superfamily. Members are type I transmembrane proteins with five extracellular NH2-terminal immunoglobulin domains (D1, D2, D3, D4 and D5), a 245 transmembrane domain, and a C-terminal cytoplasmic tail, from Swart et al. .
The fact that the cytoplasmic tail of ALCAM is highly conserved suggests that ALCAM-related functions could be partially explained by conveying extracellular signals into the cytoplasm. Despite the participation of ALCAM in many different biological processes, ALCAM knockout mice are fertile and have no visible defects
. However, an axon fasciculation and a neuromuscular synapse
defects have been identified 248.
220.127.116.11 Molecular basis of the cell adhesion mediated by ALCAM: structure-function analysis Heterophilic and homophilic interactions of ALCAM with its partners involve different parts of its structure and present significant differences regarding strength and function. In fact, the affinity of the homophilic interactions (Kd=2948 μM, koff ≥5.3 s-1) is two orders of magnitude lower than the ALCAM-CD6 interaction (Kd=0.4-1 μM, koff ≥0.4-0.63 s-1) 249. ALCAM homophilic adhesion The extracellular region of ALCAM is composed of two functional and structural modules, a ligand binding module composed of the membrane distal V-type Ig loops (D1-D2) that mediates receptor trans-trans-interactions between opposing cells, and an avidity module composed of the three membrane proximal C2-type Ig-loops (D3-D5). The strength of the avidity is controlled by recruitment of ALCAM molecules to the site of cell-cell contact and by receptor cisoligomerization via the C-type immunoglobulin domains
. Coordination of
both modules is necessary for stable ALCAM-ALCAM interaction, leading to the
Chapter 1. Introduction formation of a tight bilayered ALCAM network (Figure 25) 251.
Figure 25. ALCAM-ALCAM interactions between cells , from Van Kempen et al. and Swart et al. The extracellular structures of ALCAM consist of two functional modules. Immunoglobulin domain D1 is an essential part of the ligand-binding module and in trans-interactions between ALCAM molecules on the neighbouring cells. The D4-D5 domains are involved in cisoligomerization at the cell surface.
Zimmerman et al. described the interaction between ALCAM and the actin cytoskeleton
. This interaction could be allowed by the presence in its short
cytoplasmic tail of a positive-charge-rich domain (PCRD) as well as a PDZbinding motif KTEA placed at the C-terminus
. The inhibition of actin
polymerization by low levels of cytochalasin D toughly stimulates homotypic ALCAM–ALCAM interactions, increases protein lateral mobility, and the formation of ALCAM clusters in the cell surface, demonstrating that cytoskeleton regulates ALCAM-mediated adhesion
. Although little is known
about its cytoplasmic partners and how it interacts with the actin, ALCAM has been observed to form a supra-molecular complex with Syntenin-1 and Ezrin 256
. PKCα also plays a role in the cytoskeleton-dependent avidity modulation of
ALCAM 252 and regulates the supra-molecular complex formed by ALCAM-Ezrin 254
In summary, activation of ALCAM-mediated adhesion is dynamically regulated through actin cytoskeleton-dependent clustering. Furthermore, it has been associated with cell motility and metastasis in different tumours 257.
ALCAM heterophilic adhesion Among the heterophilic interactions mediated by ALCAM, the most studied is the one between ALCAM and CD6. However, additional interactions with other proteins have been suggested. CD6 is a surface receptor present on T-lymphocytes, thymocytes and a subset of B cells. It belongs to the SRCR family, characterized by the presence of scavenger receptor cysteine-rich domains. ALCAM has been identified as the only known ligand for CD6
. Cell clustering promoted by ALCAM-CD6
heterophilic interaction, comprises the NH2-terminal Ig domain (D1) of ALCAM and the membrane-proximal SRCR domain of CD6 258,259 with a stoichiometry of 1:1. These interactions are significantly stronger than ALCAM homophilic interactions
. In addition, these interactions are needed for the binding of
thymocytes to thymic epithelial cells and of T-cells to activated leukocytes. They are thought to be relevant for T-cell proliferation and maturation 261. ALCAM has been shown to directly associate with another tetraspanin, CD9, in a protein complex on the leukocyte surface that also includes the metalloproteinase ADAM 17. Through these interactions, CD9 upregulates both homophilic and heterophilic ALCAM interactions 262. ALCAM has also been seen to interact with L1CAM and this interaction seems to target retinal axons during development 248,263,264. Several reports indicate a functional link between ALCAM and cadherins. In fact, ALCAM expression has been localized in cell-cell contact areas, where it may interact with other cell–cell adhesion molecules. In a panel of prostate cancer cells that lacked the gene encoding α-catenin, upon reconstitution of the α-catenin/E-cadherin complex by α-N-catenin transfection, ALCAM relocalized from the cytoplasm to the cell membrane where it co-localized with E-cadherin 265
. Ofori-Acquah et al. 266 reports the existence of a complex formed by ALCAM
with vascular endothelial (VE)-cadherin and N-Cadherin in pulmonary microvascular endothelial cells. In the same cells, discs-large (Dlg), a component of adherens junctions in a number of epithelial tissue types immunoprecipitated together with ALCAM.
Chapter 1. Introduction
18.104.22.168 Regulation of ALCAM concentration in the cell Transcriptional regulation, endocytosis, and/or metalloproteinase shedding can control the concentration of ALCAM in the cell. ALCAM clustering in the plasma membrane induces its rapid internalization via dynamin- and clathrin-dependent endocytosis, which is controlled by PI3K and mitogen-activated protein kinase ERK. The ALCAM cytoplasmic tail has been observed to interact directly with ubiquitin and this ubiquitination seems to be responsible for ALCAM endocytosis, affecting its function in axon navigation 268,269
. ALCAM is continuously recycled through endocytic pathways and is
detectable in early endosomes. In addition to ubiquitination, ALCAM concentration in the cell surface can be controlled by metalloproteinase cleavage. In a panel of ovarian cancer cell lines, ALCAM was shed by ADAM 17, leading to the generation of a soluble ALCAM composed of most of its extracellular domain 270. Soluble ALCAM has also been found in ascites and sera of patients, suggesting that a similar process might occur in vivo.
22.214.171.124 General functions Although ALCAM was initially identified and primarily expressed in activated leukocytes, it is widely expressed in human tissues and cells, including neuronal,
mesenchymal origin activation
. ALCAM contribution has been described in T-cell
hematopoiesis. However, the pathologic state of ALCAM expression has been associated with different cancers, such as melanoma, colon, prostate, breast, ovarian, bladder and oesophageal squamous cell cancers 271. ALCAM in hematopoietic cells ALCAM and CD6 are actively recruited at the T-cell-APC (antigen-presenting cell) interface and enable immunological synapse stabilization
interaction contributes to the early and later stages of dendritic cell induced T-
cell activation and proliferation
. In addition, ALCAM plays a role in mediating
the transmigration of T-cells and monocytes across the blood-barrier
ALCAM-CD6 interaction results in activation of three mitogen-activated protein kinase cascades, ERK1/2, p38 and JNK 275. ALCAM in vertebrate development ALCAM is expressed on endometrial luminal and glandular epithelial cell surfaces and on the blastocyst cell surface
but not in embryos, at the 8-cell
or morula stages. However, ALCAM expression presents a distinctive, temporal and spatial distribution in development of several tissues
. In a Xenopus
model, loss of ALCAM results in lack of cardiac morphogenesis
ALCAM is strongly associated with haematopoiesis and vasculogenesis 279. The knockdown of Alcama (the zebrafish ortholog of mouse and human ALCAM) in zebrafish presented imperfections in neural crest differentiation, resulting in cartilage defects
. Alcama played a crucial, non-autonomous role
in pharyngeal endoderm during zebrafish cartilage morphogenesis. Moreover, double knockdown of Alcama and Nadl1.1 (the zebrafish ortholog of mouse and human L1CAM) evidenced that the two proteins interact during cartilage morphogenesis. ALCAM has also been described as a guidance molecule in migration and neuronal outgrowth during development 276,281. ALCAM in multipotent and stem cells ALCAM has been used, with other markers, to define multipotent cells from a wide spectrum of tissues like umbilical cord blood bone marrow
, dental pulp
and intervertebral disc
, foetal lung
. However, the exact
function of ALCAM in the multipotent capacity of these cells still remains not fully understood. ALCAM in neuronal network ALCAM has been involved in the extension of axons guidance and mapping
as well as in axonal
. Moreover, as explained before, ALCAM knockout
mice presented irregularities in axon fasciculation and a delay in maturation of neuromuscular junctions 247,248. ?<
Chapter 1. Introduction ALCAM in cancer ALCAM was first identified as MEMD in melanoma cell lines
. Since then,
ALCAM has been associated with tumorigenesis of many cancers comprising melanoma
pancreatic 297 and thyroid cancer 298. In those cancers, the potential use of ALCAM as a biomarker of recurrence was evidenced, but it has been linked to contradictory results, greatly limiting its value to predict a clinical outcome. In fact, even for the same type of malignancy ALCAM has been described as a marker of good prognosis, of poor prognosis, or even completely unrelated to survival (Table 12). Tumour type Melanoma Prostate cancer Breast cancer
Level of ALCAM in studied malignancies Increased expression in vertical phase growth Up-regulated in low-grade tumours compared to high-grade tumours Reduced expression is associated with poor prognosis (nodal involvement, higher grade, higher TNM stage, and worse NPI) and clinical outcome (local recurrence and death)
Intraductal and invasive carcinomas have high ALCAM expression; high cytoplasmic ALCAM expression is associated with shortened patient disease-free survival
Up-regulation is an early event in malignant transformation; membranous ALCAM expression correlates with shortened patient survival
Loss of membranous ALCAM indicated worse patient prognosis
No relation with patient survival
Increased expression in bladder cancer with correlation between ALCAM expression and stage/grade
Oesophageal squamous cell carcinoma
Overexpression of ALCAM is associated with poor prognosis (late clinical stage, enhanced tumour invasiveness, and nodal metastasis)
Table 12. ALCAM levels in various malignancies, adapted from Ofori et al.
Also, ALCAM localization within the tumour (membranous or cytoplasmic staining) has been linked to different outcomes. The role of ALCAM in cancer seems related to the specific context and its function appears induced by the
tumour tissue of origin. Some authors have associated these contradictory results to the heterogeneous shedding of the protein within the same tumour 299. Serum levels of ALCAM have recently been explored as a diagnostic tool in ovarian, oesophageal, pancreatic, breast, thyroid and colon malignancies 299,301– 305
Although the exact function of ALCAM still remains not fully understood, its participation in cancer progression has been extensively studied. Interestingly, in vivo mouse model studies
based on the upregulation of a truncated
ALCAM, lacking the D1 domain, reflected reduced subcutaneous tumour growth but were accompanied by an accelerated spontaneous lung metastasis in a melanoma transplant tumour model. On the contrary, a secreted variant of ALCAM containing only the V-type domain 1 (D1) has been observed to confer ligand binding and attenuated invasion in the highly metastatic BLM melanoma cells 307. ALCAM-mediated cell-cell adhesion has also been shown to contribute to MMP2 activation. BLM melanoma cells transfected with a dominant-negative ALCAM mutant (ΔN-ALCAM) presented inhibition of MMP-2 activation, but increased invasive behaviour, suggesting less dependence on MMP-2 activity. The authors evidenced the role of ALCAM as a cell density sensor and initiator of a signal toward MMP-2 activation 308. Further research is needed to evaluate the contribution of ALCAM in each tumour type, as well as to study its interactions with other cellular intermediates, and to determine whether ALCAM could be a potential therapeutic target to treat primary or metastatic disease.
Chapter 2. Objectives
Around 80% of endometrial cancer patients are diagnosed when the tumour is still localized and confined to the uterus, which is usually associated with a better prognosis. The recurrence risk assessment is defined based on the evaluation of clinical prognostic factors like FIGO staging, grade, and tumour histology, to guide the management of patients. Early-diagnosed patients are categorized following this classification and receive the established treatment according to their assessed risk. However, a small but consistent number of these patients diagnosed continue to relapse or even die of the disease. Therefore, it is of vital importance to find markers to predict recurrence for all those patients for whom a sufficiently robust risk factor is still not known.
Regarding the other 20% of patients, diagnosed at a more advanced stage of the disease, they present myometrial invasion and/or lymph node affectation, which are both related to a poor prognosis and patient survival. In particular, myometrial invasion is one of the most relevant risk factors, being strongly correlated with high-risk cancer and being also associated with an increase in the rate of recurrence and a decrease in the 5-year survival rate. Despite myometrial invasion supposing a critical step in cancer dissemination, the molecular mechanisms involved in the acquisition of migratory and invasive
capabilities of tumour cells, which allow the infiltration of the myometrium, still remain unclear. Cancer progression combines multiple processes, which involve many cell adhesion molecules. Aberrant expression of these molecules has been related to loss of cell-cell adhesion, disaggregation of tumour cells from the lamina propria, and acquisition of an invasive and migratory phenotype. ALCAM is a member of the immunoglobulin superfamily, which participates in both homotypic and heterotypic interactions between adjacent cells. In the last few years, ALCAM expression has been related to the tumorigenesis of many cancers, but its exact function and mechanisms are still not fully understood. Under this scenario, this thesis has focused on two specific objectives: (i) The study of ALCAM as a marker of recurrence in endometrioid endometrial cancer and its function in tumour progression. (ii) The characterization of the molecular mechanisms associated with ALCAM in the superficial and the invasive front of the tumour and its relation to myometrial infiltration. Both objectives aimed to improve survival of endometrial cancer patients. The former will enhance the accuracy of current methods for risk assessment; and the latter will permit the identification of key molecules in the myometrial invasion process to advance personalized treatment.
The tasks of these two main research objectives, are presented as follows: (i) The study of ALCAM as a marker of recurrence in endometrioid endometrial cancer and its function in tumour progression. a.
immunohistochemical expression of ALCAM in endometrioid endometrial tumours, and specifically in the early stage of the disease, as a reliable marker of recurrence. b.
The lentiviral silencing, by using two specific hairpins, of ALCAM in Hec1A and Ishikawa endometrial cancer cell lines and its validation at mRNA and protein level.
A behavioural study of the Hec1A and Ishikawa endometrial cancer
Chapter 2. Objectives cell lines and their stable populations with ALCAM downregulation, examining cell migration on a 2D and 3D model, invasion, cell-cell adhesion by measuring the strength with a dual micropipette technique and cell proliferation. d.
An orthotopic murine model, by inoculating Hec1A shControl and shALCAM cells directly into the uterus of mice, to evaluate the effects of ALCAM depletion in primary tumour and metastasis formation.
A microarray study profiling to elucidate ALCAM-dependent gene expression in Hec1A cell line and the identification of the principal altered functions and pathways by using IPA and PANTHER software.
Validation of the ALCAM-dependent genes by using RT-qPCR in Hec1A ALCAM-depleted and ALCAM-overexpressing cells. This is conducted with the aim of finally validating, by western blot, the selected target genes presenting a coherent behaviour between the ALCAM loss- and gain-of-function.
(ii) The characterization of the molecular mechanisms associated with ALCAM in the superficial and the invasive front of the tumour and its relation to myometrial infiltration. a.
The immunohistochemical study of ALCAM and its relation with a set of epithelial and mesenchymal markers, which are of relevant importance in endometrial cancer dissemination, at the superficial and the invasive front of endometrioid endometrial tumours.
The detection of soluble ALCAM in uterine aspirates by ELISA and its evaluation to discriminate patients presenting myometrial infiltration.
A study of ALCAM cleavage by MMP-9. The MMP-9 expression and activity in uterine aspirates were measured by using the zymography and correlated with soluble ALCAM in the same biological fluid.
An orthotopic murine model, by inoculating Hec1A luciferase and Hec1A-ETV5 luciferase overexpressing cells directly into the uterus of the mice, to evaluate the immunohistochemical expression and localization of ALCAM in the inner tumour and at the invasive front. In addition, this in vivo model, which mimics the first steps of myometrial infiltration, leads to the study of the relationship between ALCAM, ETV5 and MMP-9.
A behavioural study of the Hec1A-ETV5 mesenchymal endometrial cell and the effects of full-length and cytoplasmic-truncated ALCAM recovery, by examining cell migration using an aggregate spreading on a fibronectin coated surface and cell-cell adhesion using the dual micropipette technique.
Characterization of the ERK1/2 pathway involved in ALCAM rescue in Hec1A-ETV5 overexpressing cells by western blot.
Chapter 3. Materials and methods
The materials and methods used in this thesis are described in this section including the individual specifications for each objective (i) and (ii).
3.1 Human endometrial cancer samples Ethical approval was obtained by each participating institution. Samples were obtained after informed consent was signed.
3.1.1 Tissues Objective (i): For the 10-year retrospective multicentre study, a total of 174 EEC formalin fixed paraffin embedded tissue samples were recruited from: Vall d’Hebron Hospital (Barcelona, Spain), Arnau de Vilanova Hospital (Lleida, Spain), Hospital del Mar (Barcelona, Spain), University Hospital of Santiago de Compostela (Santiago de Compostela, Spain), MD Anderson Cancer Center Madrid (Madrid, Spain) and Virgen del Rocio Hospital (Sevilla, Spain). The clinicopathological parameters of these patients are described in Table 13.
Σ (%) 172 (100.0)
Table 13. TMA description (i).
Objective (ii): A total of 116 endometrioid endometrial carcinomas (EEC) formalin-fixed, paraffin-embedded tissue samples were recruited from the Pathology Department of the Hospital del Mar (Barcelona, Spain). The Clinicopathologic characteristics of these patients are detailed in Table 14.
Chapter 3. Materials and methods Variable FIGO Stage
Σ (%) 116 (100.0)
Table 14. TMA description (ii).
3.1.2 Uterine aspirates A total of 40 uterine aspirates from patients diagnosed with endometrial cancer were collected in the Vall d’Hebron Hospital (Barcelona, Spain). Uterine aspirates were collected by aspiration with a Cornier Pipelle (Eurogine Ref. 03040200) in the office of the gynaecologist or prior to surgery in the operating room and transferred to 1.5 ml microtubes. The clinical and pathological characteristics of the patients are described in Table 15. Variable
Table 15. Clinicopathological parameters of selected uterine aspirates.
126.96.36.199 Uterine aspirates processing Phosphate buffer saline 1x (PBS) was added in a 1:1 (v/v) ratio to uterine aspirates, and centrifuged at 2,500 rcf for 20 min in order to separate the soluble fraction (supernatant) from the solid fraction (pellet). The separated fractions were kept at −80°C until use.
3.2 Protein detection 3.2.1 Immunohistochemistry Immunohistochemistry (IHC) is based on the utilization of monoclonal and/or polyclonal antibodies for the detection of specific antigens in tissue sections. IHC is an important application to determine the tissue distribution of an antigen of interest in health and disease. It is widely used for diagnosis of cancers because specific tumour antigens are expressed de novo or upregulated in certain cancers. For visualizing the antibody-antigen interaction, the secondary antibody is conjugated to an enzyme such as peroxidase that will catalyse a colour-producing reaction. Objective (i): Two different tumour areas of each patient tissue block were selected for tissue microarray (TMA) construction. Sections were incubated with the primary antibody for 1 h at room temperature using 1:100 mAb ALCAM (MOG/07; Abcam, Cambridge, USA). Epitope retrieval was performed in citrate buffer pH 9. After incubation, the reaction was visualized with the EnVision
diaminobenzidine chromogen as a substrate. Sections were counterstained with haematoxylin & eosin. A pathologist evaluated ALCAM expression using two criteria: an intensity score (ranging from 1-3) and a % of positive staining cells [0-100%]. The product of the two assessments yielded final values on a scale ranging from 0-300. The cut-off for the dichotomization corresponds to the first quartile of the distribution of the ALCAM expression value in the cohort: ALCAM positive ≥ 30.
Chapter 3. Materials and methods Objective (ii): For each patient, 2 spots from the superficial area and 2 spots from the invasive front were selected for TMA construction. ALCAM, E-cadherin, βcatenin,
expressions were analysed in both areas of the tumour.
extracellular ALCAM ectodomain, antigen retrieval and primary antibody incubation were performed as in objective (i). To detect MMP-2, MMP-9, and ETV5, citrate buffer pH 9 was used for antigen retrieval. Then the sections were incubated with 1:100 rAb ETV5 (H-100; Santa Cruz Biotechnology, CA, USA), 1:50 mAb MMP-2 (CA-4001; Abcam, Cambridge, MA, USA) and 1:50 rAb MMP-9 (3852; Cell Signalling Technology, Beverly, MA, USA) for 1h (MMPs) or 2h (ETV5) at room temperature.
Detection of COX-2 was
performed with antigen retrieval citrate pH 6 buffer and incubation was performed
Biotechnology, CA, USA). Primary antibodies mAb E-cadherin and mAb βCatenin (36 and 14; Roche, Basel, Switzerland) were used with Ventana Benchmark automated slide stainer, 24 min at 36ºC. A pathologist evaluated the expression of each protein using immunoreactive scores (IRS). ALCAM, E-Cadherin and COX-2 expressions were evaluated from the product of the intensity (ranging from 1-3) and the percentage [0100%] of neoplastic cells with positive staining. The product of the two assessments yielded final values on a scale ranging from 0-300. ETV5, βcatenin, MMP-2 and MMP-9 were only evaluated based on the “percentage”, and so, in scale IRS [0-100%]. For the selected candidates, the IRS was dichotomized (positive/negative), by using the average of their staining (calculated with both the superficial and the invasive staining) and the cut-off value was established with the first quartile of the distributions of the ALCAM, ETV5 and MMP-9 expressions values (Tukey’s first hinge). The cut-off for each protein was: ALCAM positive ≥ 65, ETV5 positive ≥ 25, MMP-9 positive >5.
3.2.2 Western blot and protein cell extraction Western blot (WB) is a technique used to detect specific proteins in
homogenate tissue samples or cellular extracts. Gel electrophoresis is used in order to separate denatured proteins by length and electric charge. Then, the proteins are transferred to a nitrocellulose or PVDF membrane. Finally, specific antibodies are used to target the desired protein. Before protein extraction, cultured cells were washed with PBS 1x and then scraped with 1 ml of PBS 1x. Pellets obtained after centrifugation during 5 minutes at 500 rcf were used to extract total protein. Cell lysates were obtained using RIPA buffer (Tris 20 mM pH 8.8, NaCl 150 mM, EDTA 5 mM, Triton X-100 1%, 1:100 protease inhibitors) and PhosphoStop 1x (Roche, Basel, Switzerland), incubated at 4ºC for 1h and passed through a syringe for cell disruption. After 15 minutes of centrifugation at 15,000 rcf, supernatants containing proteins were quantified by BioRad DCTM Protein Assay (Reagent A, Reagent B and Reagent S, Bio-Rad Laboratories, Hercules, CA, USA) and then boiled with Laemmli Buffer (100 mM Tris-HCl pH 6.8, 4% SDS and 20% glycerol) during 5 minutes at 95ºC. After centrifugation, the protein fractions were stored at -20ºC until use. For western blot, samples were run on a 10% SDS-PAGE and transferred to a PVDF membrane (Bio-Rad Laboratories, Hercules, CA, USA). Membranes were blocked in 5% non-fat milk solution (TBS-0.1% Tween) for 1 hour at room temperature and incubated with indicated primary antibody diluted in 5% non-fat milk solution overnight at 4°C. The membranes were washed 3 times for 10 minutes in TBS-0.1% Tween at room temperature and incubated for 1 hour with the corresponding horseradish peroxidase (HRP)-conjugated secondary
Chemiluminescence System (Amersham Pharmacia Biotech, Little Chalfont, UK) as described by the manufacturer's instructions. Incubation with primary antibodies was performed using 1:500 mAb ALCAM (MOG/07, Abcam, Cambridge, UK); 1:500 mAb LAMC2 (CL2980, Abcam, Cambridge, USA); 1:2000 rAb α-Tubulin, (11H10, Cell Signalling, Beverly, MA, USA); 1:2000 rAb TXNRD1, (HPA001395, Atlas, Bromma, Sweden); 1:1000 rAb FLNB, (HPA004747, Atlas); 1:2000 rAb ERK1/2 (9102, Cell Signalling, Beverly); 1:1000 rAb P-ERK1/2 (9101, Cell Signalling).
Chapter 3. Materials and methods
3.2.3 Enzyme-linked immunosorbent assay (ELISA) The ALCAM Duoset ELISA kit (R&D Systems, Minneapolis, MN, USA) was used to detect ALCAM levels in the supernatant of the uterine aspirates. All samples were diluted 1:100 in BSA 1%. All steps were performed at room temperature. For the plate preparation, the 96-well microplates were coated with 100 μl/well of capture antibody at 2 μg/ml and incubated overnight. Each well was washed three times with 400 μl of 0.05% Tween 20 in PBS 1x. Then, plates were blocked by adding 300 μl of BSA 1% to each well, incubated for 1 h and afterwards washed. For the assay procedure, 100 μl of each sample and standards were added per well and incubated 2 h. After washing, 100 μl/well of the detection antibody at 100 ng/ml were added and incubated 2 h. Subsequently to another washing step, 100 μl/well of Streptavidin-HRP (1:200) were added and incubated for 20 min. After washing, 100 μl/well of substrate solution (3,3’,5,5’-tetramethylbenzidine (TMB), hydrogen peroxide (H2O2), and proprietary catalysing and stabilising agents) were added and incubated for 20 min in the dark. The reaction was stopped by the addition of 50 μl of 2N H2SO4 to each well. The optical density of each well was immediately determined, by using a microplate reader set to 450 nm and 570 nm for correction.
3.2.4 Immunofluorescence Immunofluorescence (IF) uses the specificity of antibodies to their antigen to target fluorescent dyes to specific biomolecules, allowing the visualization of their expression and distribution in the cell. IF was used to localize ALCAM-cherry in the transiently transfected Hec1AETV5 cells. Cells seeded onto glass coverslips were fixed with 4% paraformaldehyde (PFA) for 15 min, treated with 50mM NH4Cl for 30 min to prevent autofluorescence, blocked in PBS BSA 4% and incubated with DAPI for 15 min at room temperature in the dark. Coverslips were mounted using
the Aqua/Poly Mount medium (Polysciences Europe GmbH, Eppelheim, Germany). Fluorescence images were captured with Spectral Confocal Microscope FV1000 (Olympus, Hamburg, Germany).
3.3 Zymography Zymography is an electrophoretic method for measuring proteolytic activity. It is based on a sodium dodecyl sulphate gel impregnated with a protein substrate, which is degraded by the proteases resolved during the incubation period. Coomassie blue staining of the gel reveals sites of proteolysis as white bands on a dark blue background. Proteins with metalloprotease activity (MMP-2 and -9) were identified by zymography. Equal quantities of protein, from the uterine aspirates, were size fractionated under non-reducing conditions on SDS-PAGE gels impregnated with gelatin (7.5%; 1.5 mg/ml), at 20 mA/gel, 4ºC. Gels were washed with 2.5% TritonX-100 (2x15 min); 50 mM Tris-HCl pH 7.5/2.5 Triton X-100 (2x15 min); 50mM Tris-HCl pH 7.5 (2x15 min) to remove SDS, before incubation in assay buffer (50 mM Tris-HCl 7.5/150 mM NaCl/10 mM CaCl2; 1% Triton X100; NaN3 0.02%; 24h, 37ºC, gentle shaking). Enzyme activity was visualized by staining the gels with 0.25% Coomassie Blue, and appeared as clear bands within the stained gel. Activity was semiquantitatively determined by densitometry. One control sample was loaded on each gel to normalize band intensities between gels.
3.4 Cell lines, constructs and cell lines generation 3.4.1 Human cell lines Hec1A (ATCC®HTB-122TM) and Ishikawa (#99040201, Sigma-Aldrich, St Louis, MO, USA) endometrial cancer cell lines were grown in McCoy’s and DMEM/F-12
supplemented with 10% FBS and 1% penicillin-streptomycin in a 5% CO2
Chapter 3. Materials and methods humidified atmosphere at 37ºC. Both cell lines were established from an endometrial adenocarcinoma. The Hek 293T human embryonic kidney cell line was maintained in DMEM (Gibco, Grand Island, NY, US) supplemented with 10% FBS and 1% penicillin-streptomycin in a 5% CO2 humidified atmosphere at 37ºC.
3.4.2 Lentiviral stable generation cell lines for ALCAM knockdown Hec1A (ATCC®HTB-122TM) and Ishikawa (#99040201, Sigma-Aldrich, St Louis, MO, USA) endometrial cancer cells were used for infection. To generate downregulated stably transfected cells, we used the lentiviral pGIPZ vectors: shALCAM1 (V3LHS-3600072), shALCAM2 (V3LHS-3600074) and the empty control vector, shControl (GE Healthcare Bio-Sciences, Pittsburgh, PA, USA). To generate downregulated stably transfected cells, we used lentiviral vectors carrying a CMV-driven Lac Z gene packaged with attenuated HIV-derived constructs and pseudotyped with VSV-G envelope, prepared by transient transfection of Hek 293T cells, together with pGIPZ against ALCAM. The 293T cells were split into 100 mm culture dishes at a density of 4x106 cells per plate using 10 ml of DMEM media supplemented with 10% FBS and 1% penicillin-streptomycin. One hour prior to transfection, the medium was changed for free DMEM without FBS or antibiotics. The viral, packaging and envelope vectors (ratio 3:2:1, respectively) were put in 0.5 ml of H2O and 62.5 μL of CaCl2 2M. The mixture was added dropwise in 0.5 ml of buffer HBS 2x at pH 7.1 (0.28 M NaCl, 0.05 M HEPES and 1.5 mM Na2HPO4; optimal pH range, 7.00–7.28) under continuous bubbling. The day after transfection, the medium was replaced by new completed DMEM. Lentiviral supernatants were collected 48 h after transfection, centrifuged at 2,500 rpm to precipitate any 293T cells and filtered through 0.45-μm-pore-size filters. Cleaned lentiviral medium was used to infect cells in the presence of polybrene (8 μg/ml; Millipore, Billerica, MA, USA). Fresh medium was added to the 293T cells and the collection and infection was repeated the following day. Puromycin (1
µg/ml, Sigma, St. Louis, MO, USA) was used to select and maintain a mixed population of the shRNA expressing cells.
3.4.3 ETV5 and ALCAM overexpression in endometrial cancer cell lines The modified Hec1A cell line for the overexpression of ETV5 was previously generated and characterized by Monge M. et al.
and maintained in
selection with Geneticin (500 μg/ml; Invitrogen, Carlsbad, CA, USA). For ALCAM overexpression, we amplified ALCAM full-length and ALCAM without the cytoplasmic tail (ALCAMcytoless) from an EC tissue, using the forward primer 5’-GCAACTCGAGATGGAATCCAAGGGGGCCA-3’, and 2 reverse primers 5’-GCTTGAATTCCGGCTTCAGTTTTGTGATTGTT-3’ and 5’GCTTGAATTCGCAGCCAGTAGACGACACCAG-3’, amplified
Laboratories, Mountain View, CA, USA) with XhoI and EcorI. Transfection was performed using Lipofectamine 2000 (Invitrogen, Life technologies, Carlsbad, CA, USA) following manufacturers’ instructions. Full-length ALCAM was stably overexpressed in Hec1A. To generate stable cultures, cells were selected and maintained with Geneticine (500 μg/ml; Invitrogen, Carlsbad, CA, USA) and the Cherry positive mixed population was selected by flow cytometry. The two constructs of ALCAM overexpression were transiently transfected in Hec1A-ETV5.
3.4.4 Luciferase expression in Hec1A and Hec1A-ETV5 cell lines To monitor non-invasively tumour grafts of Hec1A and Hec1A-ETV5 cells, they were infected with lentivirus bearing pLenti CMV V5-LUC Blast (w567-1) (Addgene, Cambridge, MA, USA) to constitutively express the luciferase reporter gene. Lentivirus transfection and stable cells expressing luciferase generation were performed by L. Alonso-Alconada and M. Abal in the University Hospital of Santiago de Compostela (CHUS). To produce lentiviral particles, 293T cells were co-transfected with polyethyleneimine (PEI method)
Chapter 3. Materials and methods with the virion packaging elements (VSV-G and D8.9) and the FSV on 293T human embryonic kidney. Supernatants were collected after 3 days, concentrated by centrifugation through a filter column of 100 kDa (VWR International LLC, West Chester, PE, USA) for 1 h at 4,000 rpm. Cells were incubated overnight in the presence of medium containing lentiviral particles. After this period, medium was replaced for fresh medium and cells were incubated for at least 72 h to allow endogenous protein knockdown. Stable infected cells expressing luciferase were selected with Blasticidine S HCl (3 μg/ml; Invitrogen, Carlsbad, CA, USA). A summary of the generated cells with each specific modification is illustrated in Table 16. Cell line
Hec1A + GFP-ETV5 vector + ALCAM without the cytoplasmic tail pmCherry-N1 vector
Hec 1A Luciferase
Hec1A + pLenti CMV V5-LUC
Hec1A + GFP-ETV5 vector + pLenti CMV V5-LUC
Table 16. Summary of generated cells.
3.5 RNA extraction and reverse transcription 3.5.1 Total RNA extraction and quantification Total RNA was collected and purified using the RNeasy kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. Before extraction, cultured cells were washed with PBS 1x and then scraped. Cell suspensions were centrifuged at 1,500 rpm and cleaned again with PBS 1x. Cell pellets obtained after centrifugation were used to extract RNA. To quantify the isolated RNA two different techniques were used: 1) Nanodrop (Thermo Fisher Scientific, Waltham, MA, USA). This microvolume spectrophotomer allows the determination of the absorbance at 260 nm (RNA) and 280 nm (protein) in small volume samples. Sample purity value is given as a ratio of 260/280 nm. 2) Bioanalyzer Assay (Agilent, Santa Clara, CA, USA). This microfluidicbased platform is used for sizing, quantification and quality control of DNA, RNA, proteins and cells. In addition to measuring total RNA, the Bioanalyzer allows the determination of RNA integrity (RNA integrity number, RIN).
3.5.2 RNA reverse transcription Reverse transcription (RT) is the procedure of converting RNA into DNA. A reverse transcriptase enzyme (DNA polymerase) with other reagents (dNTPs and primers) converts mRNA into complementary DNA (cDNA). By definition, cDNA is double-stranded DNA that originates from the mRNA. RT is needed prior to the determination of gene expression levels inside the cells using RTqPCR. One microgram of total purified RNA was used for reverse transcriptase reaction using 1 μl of Random Primers (50 μM, Invitrogen, Carlsbad, CA, USA), 1 μl of dNTPs mixture (10 mM, Promega Madison, WI, USA) and sterile distilled water to reach 13 μl of total volume for each reaction. The
Chapter 3. Materials and methods thermocycler program used for the RT is described as follows: 5 min at 65ºC, then an incubation of 1 minute on ice; addition of 4 μl of 5X First-Strand Buffer, 1 μl of DTT (0.1 M, and 1 μl of SuperScript III (Invitrogen, Carlsbad, CA, USA); and incubation for 5 min at 25ºC, 60 min at 50ºC, 10 min at 70ºC, and a final step at 4ºC.
3.6 Gene expression analysis 3.6.1 Quantitative real-time PCR (RT-qPCR) The polymerase chain reaction (PCR) is a technique used to amplify DNA across several orders of magnitude, generating thousands to millions of copies of a specific DNA sequence. The method relies on thermal cycling, consisting of cycles of repeated heating and cooling of the reaction for DNA melting and enzymatic replication of the DNA. Almost all PCR applications employ a heat-stable DNA polymerase, which assembles a new DNA strand by using single-stranded DNA as a template and DNA oligonucleotides, under specific thermal cycling conditions. Real-time quantitative PCR (RT-qPCR) is a PCR technique used to measure the quantity of a PCR product in real-time. It quantitatively measures starting amounts of DNA, cDNA, or RNA. This technique is commonly used to determine whether a DNA sequence is present and the number of copies in the sample. RT-qPCR was performed following the manufacturer’s protocol for SYBR® Green (Roche, Basel, Switzerland). SYBR® Green is a commonly used fluorescent dye that binds double-stranded DNA molecules by intercalating between the DNA bases. It is used in quantitative PCR because the fluorescence can be measured at the end of each amplification cycle to determine, relatively or absolutely, how much DNA has been amplified. The master mix formulation contains a blend of dTTP and dUTP, which ensures optimal PCR results and compatibility with AmpErase® UNG treatment. In addition, the master mix includes AmpliTaq Gold® DNA Polymerase, LD (Low DNA). The enzyme is provided in an inactive state to automate the Hot Start
PCR technique and allow flexibility in the reaction setup, including pre-mixing of PCR reagents at room temperature. SYBR® Green designed primers are listed in Table 17. Fold-change (FC) expression values were calculated with the ddCT-method. Data were normalized to GAPDH. SYMBOL IGFBP6
Gene ID Homo sapiens insulinlike growth factor binding protein 6, mRNA. Homo sapiens N-myc downstream regulated gene 1, mRNA. Homo sapiens cytoplasmic FMR1 interacting protein 2, mRNA. Homo sapiens four and a half LIM domains 2, mRNA.
Homo sapiens laminin, beta 3, mRNA.
Homo sapiens laminin, gamma 2, mRNA.
Homo sapiens CD44 molecule (Indian blood group), mRNA. Homo sapiens kallikreinrelated peptidase 6, mRNA. Homo sapiens lectin galactoside-binding soluble, 1, mRNA. Homo sapiens thioredoxin reductase 1, mRNA. Homo sapiens metastasis suppressor 1, mRNA. Homo sapiens filamin B, beta (actin binding protein 278), mRNA. Homo sapiens integrin, beta 4, mRNA. PREDICTED: Homo sapiens lemur tyrosine kinase 3, mRNA. Homo sapiens calpain 1, (mu/I) large subunit, mRNA. Homo sapiens S100 calcium binding protein A14, mRNA. Homo sapiens S100 calcium binding protein A10, mRNA. Homo sapiens plasminogen activator, urokinase, mRNA.
Chapter 3. Materials and methods
Homo sapiens plasminogen activator, urokinase receptor, mRNA. Homo sapiens integrin, beta 1 (fibronectin receptor, beta polypeptide, antigen CD29 includes MDF2, MSK12), mRNA.
Homo sapiens EPH receptor A2, mRNA.
Homo sapiens AHNAK nucleoprotein, mRNA.
Homo sapiens activated leukocyte cell adhesion molecule (ALCAM), mRNA.
Table 17. Primers designed for SYBR® Green RT-qPCR.
3.6.2 Microarray analysis A DNA microarray (also DNA chip or biochip) consists of a collection of microscopic DNA spots attached to a solid surface. Each spot contains a specific DNA sequence, known as a probe or reporter. Gene expression arrays provide a comprehensive view of gene activity in biological samples. Common uses of gene expression microarrays include genome-wide differential expression studies, disease classification, pathway analysis, expression-based quantitative trait loci mapping, among others.
188.8.131.52 Microarray analysis Illumina HumanHT-12 v4 Triplicates of Hec1A shControl and Hec1A shALCAM1 were used to carry out this study. The concentration and the quality of isolated RNA were first measured by Bioanalyzer Assay (Agilent, Santa Clara, CA, USA). Microarray analysis was performed by the Genome Analysis Platform in the CIC Biogune (Derio, Bizkaia, Spain). The gene expression profile was studied with the HumanHT-12 v4 Expression BeadChip (Illumina Inc, San Diego, CA, USA), which targets 31,325 annotated genes with >47,000 probes. RNA was subjected to reverse transcription to produce first and second strand cDNA and
manufacturer's instructions. The labelled cRNA was hybridized overnight to
the arrays. The beadchips were washed, stained with dye-labelled streptavidin, and scanned with an Illumina IScan to measure the intensity. The raw data images were analysed with Illumina Genome Studio software, which generated the average probe intensity for each sample. Raw data for the analysis were extracted with Illumina’s GenomeStudio data analysis software, in the form of GenomeStudio’s Final Report (sample probe profile). Gene expression data was analysed using the R/Bioconductor statistical computing environment (www.r-project.org, www.bioconductor.org). Using the lumi Bioconductor package, raw expression data were background corrected, log2 transformed and normalized. Probes not detected in at least one sample were excluded for subsequent analyses as they are considered to represent transcripts that are not expressed. For the detection of differentially expressed genes, a linear model was fitted to the corrected, transformed and normalized data and empirical Bayes moderated t-statistics were calculated using the limma package from Bioconductor. Adjustment of p-values was done by the determination of false discovery rates (FDR) using the Benjami-Hochberg procedure. Microarray data is available on the GEO database (GSE86543).
3.7 Gene ontology analysis For the gene ontology analysis, deregulated genes from the microarray with a fold-change >1.2 and an adjusted p-value <0.05 were introduced in the PANTHER database
and in the QIAGEN’S Ingenuity® Pathway Analysis
(IPA® QIAGEN Redwood City, CA, USA) to identify the most significant canonical routes, biological processes and gene interaction networks in which they are involved.
3.8 Migration 2D and 3D assays Cell migration is a key process in the development and maintenance of multicellular organisms. Tissue formation during embryonic development, wound healing and immune responses, require the orchestrated movement
Chapter 3. Materials and methods of cells. Errors during this process have serious consequences, including tumour formation and metastasis.
3.8.1 Wound healing assay The wound healing assay is a method that allows the study of directional cell migration in vitro. It mimics cell migration during wound healing in vivo. The assay consists in making a “wound” in a confluent cell monolayer and then capturing images at time 0h and at different time points until the wound closes. The images are used to quantify the migration rate of the different cell lines. To perform the wound healing migration assay, we used Hec1A and Ishikawa shControl and shALCAM cell lines. A total of 5-8×105 cells were seeded into 24-well plates and cultured until confluence. A wound was made by scraping the cell monolayer with a 10μl pipette tip. Images were captured at 0, 24 and 48 h using an inverted microscope FSX100 (Olympus, Hamburg, Germany) to measure the wound closure rate.
3.8.2 Aggregate model We used a 3D spheroid model to quantify the spreading of the aggregates with ALCAM-depletion on a fibronectin-coated pattern (Hec1A shControl and Hec1A shALCAM). The aggregate model was also used to test the effect on migration in Hec1A-ETV5 cells after ALCAM-recovery. Moreover, this specific model allows the study of competition between cell–cell and cell–substratum adhesion on tissue spreading.
184.108.40.206 Spheroid formation and coated surface preparation Aggregates were obtained from 5 ml of cell suspension in CO2-equilibrated culture medium at a concentration of 4x105 cells/ml in 25 ml Erlenmeyer flasks and placed in a gyratory orbital shaker at 75 rpm at 37°C for 22 h. The flasks were pretreated with 2% dimethylchlorosilane in chloroform to prevent adhesion of cells to the glass surface.
For the preparation of coated glass substrates: twenty-five mm circular glass coverslips were sonicated in ethanol for 5 min, dried at ambient temperature, and exposed to deep UV for 5 min. Fibronectin (Sigma-Aldrich, St Louis, MO, USA) coating was performed using a 0.1 mg/ml solution of fibronectin in PBS (pH 7.4) for 1 h. A Mixed coating of fibronectin and PEG-PLL (PLL(20)-g[3.5]PEG(2), Surface Solution) was made by mixing at various rates 0.1 mg/ml fibronectin in PBS and 0.1 mg/ml PEG-PLL in Hepes solution (pH 7.3) for 1 h. Coverslips were then rinsed with PBS (pH 7.4).
220.127.116.11 Aggregate spreading Cell aggregates were deposited randomly on fibronectin-coated coverslips, which were placed in a magnetic imaging chamber (Chamlide CMB, CMB25-1) filled with CO2-equilibrated culture medium. Spreading was observed using a NIKON confocal microscope equipped with an x10 air objective and a 37°C heating cube system. Bright field images were recorded with a CCD camera (Luca-R, Andor) using NIS-Elements software every 15 min for 36-48 h. The area of each aggregate was measured with Image J software at time 0h and at the end of the assay (National Institutes of Health, Bethesda, MA, USA). For Hec1A-ETV5 ALCAM-recovery, cell aggregates were deposited on 200 μm striped fibronectin-coated surface. The increased spreading was measured at different time points with Image J software (National Institutes of Health, Bethesda), which allowed calculating the speed of migration for each cell line.
3.9 Invasion The movement of cancer cells into surrounding tissue and the vasculature is the first step in the spread of metastatic cancers. Cell invasion is related to, and encompasses, cell migration, but in addition invasive cells move through the extracellular matrix into neighbouring tissues in a process that involves ECM degradation and proteolysis. [email protected]
Chapter 3. Materials and methods
3.9.1 Transwell invasion assay A total of 5x105 cells were seeded on 8 μm pore size transwell filters of the CytoSelect 24-well cell invasion assay kit according to manufacturers’ instruction (Cell Biolabs, San Diego, CA, USA), and allowed to invade for 3648 h. The upper faces of the inserts were coated with a basement membrane matrix solution. Only the cells able to degrade the matrix proteins in the layer and travel through the pores of the polycarbonate membrane are considered invasive cells. Invading cells were stained with DAPI and Phalloidin and counted with Image J (National Institutes of Health, Bethesda, MA, USA).
3.10 Cell-cell adhesion Tumour cells often show aberrant cell-cell and/or cell-matrix adhesion. This cell-cell adhesion change has been correlated with tumour invasion and metastasis. Cell adhesion molecules are responsible for cell adhesion and they can also function as ligand-activated cell surface receptors, activating signals involved in the regulation of cell shape, migration, proliferation, differentiation, and survival. These two functions show considerable interdependence with the regulatory processes exercising feedback control over cell adhesion, often through inside-out signalling.
3.10.1 Dual-pipette adhesion force assay The dual pipette assay used here, provides an overall quantification in terms of mechanical force of the adhesive properties of the cells conferred by ALCAM modulation during the development of adhesion. To preserve intact the cell surface proteins, cells were dissociated with Cell dissociation enzyme-free buffer (Gibco, NY, USA), rinsed and then transferred in working medium (CO2-independent medium, Invitrogen, CA, USA) and used immediately. Two isolated cells were brought gently into contact and held for a predetermined period of time (1, 4, 10 and 20 min). The cells were manipulated in suspension, to eliminate matrix-mediated signalling, by diminishing the contribution of generalized membrane events, and avoiding
the initiation of intercellular adhesion through lamellipodial and filopodial activities. Isolated cells were manipulated at 37ºC with two micropipettes, each
hydraulic/pneumatic system and a pressure sensor making it possible to control and measure the aspiration applied to the cells. The cell doublet was cyclically brought back into contact with the left pipette and then withdrawn to the right, each time a stepwise increase in the strength of aspiration by the left pipette was applied, until the cell doublet was disrupted. A pressure sensor measured the aspiration applied to the left pipette. Aspiration was monitored continuously during the separation process, and the values recorded for each of the last two cycles in the series (Pn-1 and Pn) were used to calculate the separation force (SF) for each doublet using the equation: SF = π (d/2)2 (Pn1+Pn)/2 where d is the inside diameter of left pipette. SF was considered to be zero for pairs of cells that did not form adherent doublets in this assay. Results for 15–40 measurements were used to obtain the mean force of separation for a specific contact time.
3.11 Cell proliferation Cell proliferation and differentiation is crucial from embryogenesis to development of whole organism and also in maintenance of adult tissue homoeostasis. Abnormal cell proliferation has been also associated with various human diseases like cancer. Consequently, cell proliferation assays become critical to examine the rate of cell proliferation in vitro and in vivo. There exist several assays to determine cell proliferation rate like amount of deoxyribonucleic acid synthesis, metabolic activity of cells, different antigens associated with cell proliferation and adenosine triphosphate concentration. One of the simplest methods uses crystal violet staining. During cell death, adherent cells detach from cell culture plates. This characteristic is used for the indirect quantification of cell death and finally to determine the difference in the proliferation rate between cells. Crystal violet dye binds to proteins and DNA. Cells that undergo cell death lose their
Chapter 3. Materials and methods adherence and are subsequently lost from the cell population, decreasing the amount of crystal violet staining.
3.11.1 Crystal violet A total of 4,000 cells per well were seeded into 96-well plates. Cell viability was measured after 0, 24, 48, 72, 96 and 120 h. Cells were fixed with 50 μl/well of Formaldehyde 4% and incubated for 20 min. After washing, cells were stained with 100 μl/well crystal violet 0.5% in H2O (Sigma, St Louis, MO, USA) and incubated at room temperature for 20 min. Crystal violet was washed by immersing and shaking plates in water and leaving to dry for 5 min. Then, crystal violet was dissolved in 100 μl/well of 15% acetic acid for 10 min with shaking, and finally the supernatant was read at 595 nm.
3.12 Cell cycle assay for flow cytometry Cancer is a disease accompanied by uncontrolled cell division. Its development and progression are usually linked to a series of changes in the activity of cell cycle regulators. The DNA of mammalian, yeast, plant or bacterial cells can be stained by a variety of DNA binding dyes. The principle of these dyes is that they are stoichiometric and as a consequence bind in proportion to the amount of DNA present in the cell. Cells that are in S phase will have more DNA than cells in G1. They will take up proportionally higher quantity of dye and will fluoresce more brightly until they have doubled their DNA content. The cells in G2 will be approximately twice as bright as cells in G1.
3.12.1 Propidium iodide DNA staining Propidium iodide (PI) is an intercalating agent and a fluorescent molecule that can be used to stain cells. After 48 h, a total of 1x106 cells were trypsinized, resuspended in 300 µl of PBS, and fixed with 700 µl of pre-cooled absolute EtOH for 2 h on ice. EtOH was slowly added while mixing to avoid aggregates. Cells were pelleted (5,000 rpm), resuspended in working solution
(940 µl of PBS, 30 µl of solution A and 30 µl of solution B) and incubated for 30 min at room temperature. Finally, cells were analysed by flow cytometry. Solution A: Sodium Citrate (38 mM) and propidium Iodide (500 µg/ml). Solution B: RNAse A (10 mg/ml in PBS).
3.13 Mouse model The use of clinically relevant mouse models, which mimic the tumour growth, progression, invasion and metastases steps, is an essential requirement to better understand the endometrial cancer molecular mechanisms. Previously in the laboratory, we developed an orthotopic murine model that represents a realistic approach towards the process of dissemination of endometrial cancer. Tumour cells are directly injected into the uterus of the mice and so they are localized in the same microenvironment as the original tumour, replicating the processes of tumour growth and myometrial infiltration under endometrial stimuli.
3.13.1 Orthotopic murine model of endometrial cancer All the procedures were performed according to the guidelines of the Spanish Council for Animal Care and the institutional guidelines for animal welfare (CEEA 23/16). For objective (i), we tested the ability of Hec1A ALCAM-depleted cells in tumour growth and dissemination. For this, a total of 24 six-week old female athymic nude mice (Charles River Laboratories, Inc, Wilmington, MA, USA) were inoculated by transmyometrial injection of stably transfected Hec1A shControl and Hec1A shALCAM2 cells (n=12 per group). Mice were anesthetized with 2% isofluorane (ABBOT Laboratories, Madrid, Spain), and the lower abdomen was swabbed with Betadine®. A longitudinal incision (medial laparotomy) was performed and the murine uterus was exposed. EC cells were inoculated into the uterine body and the uterine horns. A 27G insulin syringe (Myjector® 1 ml, Terumo, Somerset, NJ, USA) was used for the injection. The strain on the endometrial cavity and the expulsion of a small 98:
Chapter 3. Materials and methods quantity of fluid through the vagina ensured the correct localization of the injection. Mice were sacrificed seven weeks after the injection. Tumour growth and dissemination were evaluated macroscopically and histologically ex vivo. For histological analysis, all extracted tissues were formalin-fixed, stained with haematoxylin and eosin (H&E), and evaluated by a pathologist. Ki67 expression was scored by using the ACIS® III Instrument automated imaging system (DAKO, Glostrup, Denmark). For objective (ii), Hec1A control and Hec1A-ETV5 luciferase cells were injected into the uterus of 5 and 4 mice, respectively and following the aforementioned protocol. The in vivo model was performed by L. AlonsoAlconada and M. Abal in the CHUS (Santiago, Spain). Mice were followed weekly after cell injection and before sacrifice by using IVIS system (Xenogen Corporation) coupled to Living Imaging software 4.2 (Xenogen Corporation) to detect
Lifescience Corp, Hopkinton, MA, USA) was used as the substrate for the luciferase expressing tumour cells and injected intraperitoneally at a concentration of 150 mg/kg in PBS. Mice were sacrificed 3 weeks after injection and before metastases could be observed.
3.14 Statistical analysis The statistical approaches used for objective (i) are explained as follows: For categorical variables The relationship between ALCAM expression and clinicopathological parameters was tested in univariate analysis by chi-square and Fisher's exact test, two-sided p-values. Stratified analysis was performed to study the relation between recurrence and ALCAM status. Follow-up studies were analysed by Kaplan-Meier and Cox’s proportional hazards test. Recurrencefree survival was evaluated in the present study, but not overall survival as the number of deaths from disease did not allow a reliable statistical analysis.
For continuous variables The normal distribution of data was verified (Shapiro-Wilk or KolmogorovSmirnov) and accordingly, parametric (t-test, ANOVA, and multiple post-hoc comparisons (Scheffe, Dunnet) and non-parametric (Mann-Whitney) tests were performed for each comparison. The statistical approaches used for objective (ii) are explained as follows: For continuous variables Univariate regression analyses were performed to evaluate the association between ALCAM and different epithelial and mesenchymal markers at the superficial and the invasive front. Variables that were statistically significant in univariate linear regression analysis were included in the multiple linear regression models. For each cohort, a stepwise method was used to select the explanatory variables based on analysis of variance, checking the normality (Shapiro-Wilk or Kolmogorov-Smirnov) and the independence of residuals (Durbin-Watson). Receiver operating characteristic (ROC) curve analysis was conducted on individual marker soluble ALCAM (sALCAM), detected in uterine aspirates at diagnosis, to discriminate patients presenting myometrial infiltration. To explore its relationship with the levels of the different forms of MMP-9 present in the uterine aspirates, we performed a factor analysis with extraction of principal component (PCA) for MMP-9 expression and then a regression analysis with sALCAM levels. The normal distribution of data was verified (Shapiro-Wilk) and levels were Ln-transformed for linear analysis. Non-parametric tests (Mann Whitney) were used for comparisons of data sets whose distributions deviate from normal. For categorical variables The relationships between ALCAM expression, at the superficial and the invasive front, and clinicopathological parameters were tested in univariate analysis by Chisquare and Fisher’s exact test.
Stratified analysis was
performed to study the molecular features ALCAM/MMP-9/ETV5 and the correlation between ALCAM/MMP-9 and clinicopathological parameters. The 98<
Chapter 3. Materials and methods odds ratios (OR) were calculated across the strata, with their 95 % confidence interval (IC 95 %) obtained through bootstrapping methods. In addition, logistic regression multivariate analysis was done for the clinicopathological parameters and status biomarkers to determine independent predictors for myometrial infiltration. Categorical variables are presented as an absolute number and percentage. For both objectives, measurements were made in triplicate in three independent experiments and presented with the Mean±SD (except for the separation force experiments, which were presented by Mean±SEM). All statistical analyses were performed using the IBM SPSS Statistics 21. All two-sided pvalues<0.05 were considered statistically significant.
Chapter 4. Results
The results section is organized into two blocks, where we provide the results obtained when addressing the two main objectives of this thesis, previously described in Chapter 2.
4.1 ALCAM as a marker of recurrence and as a promoter of tumour progression in EEC 4.1.1 Framework As stated in Chapter 1, 18.104.22.168 section, abnormal vaginal bleeding is an early symptom of endometrial cancer and as consequence allows the diagnosis of around 75% of patients at an early stage of the tumour. Recurrence risk groups are basically defined based on the assessment of clinical prognostic factors like age, FIGO staging, grade, and histology, to guide the management of patients. Despite those early-diagnosed patients are classified and treated according to their established risk of recurrence, a number of them relapse or even die of the disease. For this reason, in order to improve the proper classification of these patients, the main objective of this section was to evaluate the immunohistochemical
determination of ALCAM in 174 EEC primary tumours as a reliable marker of recurrence. In addition, we used in vitro and in vivo orthotopic murine models as well as microarray technology, to unveil the functions regulated by ALCAM to promote EEC dissemination and metastasis.
4.1.2 ALCAM-positive expression is a marker of recurrence in early stage moderately-poorly differentiated tumours Among the 174 EEC patients analysed for ALCAM expression, we found 131 (76.20%) to be ALCAM-positive (Table 18).
Variable, No. (%) Age ≤64 years >64 years
Σ 172 76 96
ALCAM Positive* 131 (76.2) 56 (73.7) 75 (78.1)
ALCAM Negative† 41 (23.8) 20 (26.3) 21 (21.9)
FIGO Stage IA Stage IB Stage II Stage III
172 85 49 25 13
132 (76.7) 70 (82.4) 38 (77.6) 16 (64.0) 8 (61.5)
40 (23.3) 15 (17.6) 11 (22.4) 9 (36.0) 5 (38.5)
Grade Grade 1 Grade 2 Grade 3
172 99 46 27
130 (75.6) 81 (81.8) 29 (63.0) 20 (74.1)
42 (24.4) 18 (18.2) 17 (37.0) 7 (25.9)
*ALCAM positive ≥ 30 †ALCAM negative < 30 Table 18. Clinicopathologic parameters according to ALCAM expression (N=174).
predominantly localized at the membrane and the cytoplasm (Figure 26-D). Of the included cancers, 77.9% were early stage EEC (stage IA and IB according to the FIGO classification), containing 88 well-differentiated (G1) and 45 moderately-poorly differentiated tumours (G2-G3); whereas 22.1% of remaining cases were diagnosed at advanced stages.
Figure 26. ALCAM-positivity is a marker of recurrence. (A) Patients diagnosed with tumours in early stage (rate of recurrence in ALCAM positive tumours is 27.8% vs. ALCAM negative tumours is 7.7%, p=0.039); (B) patients diagnosed with moderately-poorly differentiated tumours (59.2% versus 25%, p=0.007); and (C) patients diagnosed with early stage moderatelypoorly differentiated tumours (55.9% versus 9.1%, p=0.012). (D) Representative images of ALCAM expression in a recurrent (left) and non-recurrent (right) early stage moderately-poorly differentiated tumour.
The univariate analysis between ALCAM expression and the most common prognostic factors only showed a minor correlation with tumour grade when studied in the whole population (Table 18). Interestingly, in a stratified analysis, ALCAM expression showed a significant correlation with the recurrence for patients diagnosed in early stage (N=134) (p=0.039), with moderately-poorly differentiated tumours (N=73) (p=0.007), and with tumours combining these two clinical parameters (N=45) (p=0.012) (Table 19). Specifically, in the subset of patients diagnosed at early stage, the recurrence rate was significantly higher for ALCAM-positive patients compared to ALCAM-negative patients (27.8% vs 7.7%). The results were similar for patients with moderately-poorly differentiated tumours (59.2% vs. 25.0%); and noteworthy, for the early stage moderately-poorly differentiated cohort in which the percentage of ALCAMpositivity in recurrent patients increased up to a 55.9% compared to a 9.1% for ALCAM-negative patients (Figure 26A-C).
Early Stage I
Advanced Stages II-III
Differentiated tumors (G1)
15 (44.1) 10 (90.9)
19 (55.9) 1 (9.1)
Variable, No. (%) Staging
Moderately- Poorly differentiated tumors (G2-3)
Early Stage I & ModeratelyPoorly differentiated tumors ALCAM Positive* ALCAM Negative†
* ALCAM positive ≥ 30
† ALCAM negative < 30
Table 19. ALCAM expression signature of EEC recurrence (N=174).
These results were supported by univariate Cox regression and Kaplan Meier analyses. Recurrence-free survival was lower in patients with ALCAM-positive tumours than in patients with ALCAM-negative expression. For early stage EEC patients, median recurrence-free survival in ALCAM-negative patients was 111.44 months vs. 95.47 months for ALCAM-positive cancers (p=0.031) with a hazard ration (HR) of 4.237 (p=0.048) (Figure 27-A). Similarly, for patients with moderately-poorly differentiated tumours, recurrence-free survival was 93.243 vs. 64.762 months (p=0.011) with a HR 2.966 (p=0.016) (Figure 27-B). Again, the highest difference was observed in patients with early stage moderately-poorly differentiated tumours, in which ALCAM reached a HR 9.259 (p=0.034). In this subcohort, recurrence-free survival was significantly longer in
Chapter 4. Results
Figure 27. Univariate survival analyses according to ALCAM expression in 174 EEC patients, (A) early stage, (B) moderately-poorly differentiated, and (C) early stage moderately-poorly differentiated tumours. Differences in survival between ALCAM positive (ALCAM pos) and ALCAM negative (ALCAM neg) groups were assessed by the two-sided log-rank test. The HR (95% CI) for each comparison is given below the graphs.
ALCAM-negative cancers than in patients with ALCAM-positive expression (110.636 vs. 68.279 months, respectively; p=0.008) (Figure 27-C). Furthermore, in the early stage patients, ALCAM-positivity was identified as an independent prognostic factor of recurrence with a HR 6.027 (p=0.015) together with the tumour grade with a HR 5.634 (p<0.001) in a multivariate Cox regression analysis (Table 20).
Recurrence-free survival 95% Interval confidence
Age ≤64 years >64 years Grade Differentiated tumours (G1) Moderateley-poorly differentiated tumours (G2-3)
Table 20. Multivariate Cox regression model for patients with early stage tumours (N=134).
4.1.3 Inhibition of ALCAM in EEC cell lines decreased cell migration, invasion and cell-cell adhesion To understand the role of ALCAM in endometrial tumour progression and dissemination2 we studied the effect of ALCAM inhibition in the Hec1A EEC cells. We generated two ALCAM-depleted Hec1A cell lines by using two specific shRNAs obtaining >70% of inhibition (Figure 28A-B).
Figure 28. Inhibition of ALCAM in Hec1A cell line. (A) Stable downregulation of ALCAM in Hec1A cell line was analysed by western blot and (B) by RT-qPCR, normalized with GAPDH as housekeeping (**p<0.01).
Chapter 4. Results We used in vitro 2D and 3D models to evaluate the role of ALCAM in EEC motility and a dual-micropipette assay to determine quantitatively ALCAM function in cell-cell adhesion. ALCAM-depletion decreased the wound closure rate of Hec1A cells in a 2D wound healing assay (Figure 29-A). To mimic the tumour progression in patients, we used a 3D model to quantitatively study the spreading of cell aggregates with ALCAM-depletion on a fibronectin-coated surface. Three-dimensional models fill the gap between 2D cell cultures and animal systems as they mimic characteristics of the in vivo environment
Specifically, this model allows the study of the competition between cell–cell and cell–substratum adhesion on tissue spreading
. We found that, in
agreement with 2D studies, ALCAM-depleted cells presented a decreased motility in the 3D model (Figure 29-B). In addition, ALCAM-depleted cells showed a significant reduced invasive capability on a matrigel transwell assay (Figure 29-C). Finally, we evaluated how ALCAM affects the formation and strength of cell-cell adhesion. Two isolated cells maintained in suspension, to avoid cell-matrix interactions, were put into contact to initiate adhesion by using two micropipettes. After a defined period of contact, we measured the forces required to separate them. The mean separation force (SF) is used as readout of the strength of adhesion for a specific contact time. In both control and ALCAM-depleted cells the SF required to disrupt the cell doublet increased with the time of contact. However, at all time points, the intercellular cell adhesion was weaker in the ALCAM-depleted cells (Figure 30). Cell-cell adhesion and aggregate spheroid assays pointed to ALCAM as an important player in the overall balance of adhesion, which is crucial in cancer processes. Those effects were independent of cell proliferation, as no significant differences were shown in cell viability or progression through the cell cycle (Figure 31).
Figure 29. ALCAM inhibition decreased migration and invasion in Hec1A cell line. (A) ALCAM inhibition decreased wound closure rate at 24 and 48 h. Up, wound is delimited with a dotted line at 0 h and 48 h for each cell line. Bottom, the gap closure is quantified at 24 and 48 h. (B) The effect of ALCAM silencing in cell motility was assessed by a 3D spheroid-spreading model on fibronectin-coated surface. The spreading area is outlined in the upper image and measured at 48 h in the bar graph. (C) ALCAM depletion decreased the invasive abilities of Hec1A cells in a matrigel transwell assay after 36 h. (For all, **p<0.01, *p<0.05).
Chapter 4. Results
Figure 30. ALCAM inhibition decreased cell-cell adhesion in Hec1A cell line. (A) Two cells were put into contact to form adhesion. (B) After 4, 10 and 20 min ALCAM inhibition decreased the cell-cell adhesion in Hec1A cells as shown by the quantification of the separation force for each time point. (*p<0.05, Mean ± SEM).
Figure 31. ALCAM inhibition had no effect on cell proliferation or progression throughout the cell cycle. (A) A crystal violet assay was performed at 0, 24, 48, 72, 96 and 120 h. ALCAM inhibition had no effect on cell proliferation in Hec1A cell line. (B) The percentages of cells in G1, S and G2 were quantified by using propidium iodide DNA staining and flow citometry. ALCAM inhibition in Hec1A had no effect on cell cycle progression.
The same results were observed with the ALCAM-depleted Ishikawa EEC cell line (Figure 32). Specifically, Ishikawa shALCAM cells presented lower rate of wound closure, decreased invasive ability, and no differences in cell proliferation were observed (Figure 33). Taken together, these results supported the role of ALCAM in key processes for tumour dissemination, leading to less aggressive phenotypes when supressed.
Figure 32. Inhibition of ALCAM in Ishikawa cell line. Stable downregulation of ALCAM by two shRNAs in Ishikawa cell line was analysed by (A) western blot and (B) by RT-qPCR and normalized to GAPDH as a reference transcript (**p<0.01).
Figure 33. ALCAM inhibition in Ishikawa cell line decreased migration and invasion. (A) ALCAM inhibition decreased the wound closure rate in a 2D wound healing assay at 24 h and 48 h (24 h *p<0.05; 48 h **p<0.01). (B) ALCAM depletion decreased the invasive abilities of Ishikawa cells in a Matrigel transwell assay after 36 h (**p<0.01). (C) A crystal violet assay was performed at 0, 24, 48, 72, 96 and 120 h. ALCAM inhibition had no effect on cell proliferation in the Ishikawa cell line.
Chapter 4. Results
4.1.4 Depletion of ALCAM reduced primary tumour size and inhibited metastasis in an orthotopic murine model of EEC To assess the effect of ALCAM on tumour development and metastasis we used a clinically relevant EEC orthotopic murine model. We inoculated stably transfected control or ALCAM-depleted cells into the uterus of mice and after 7 weeks both conditions developed solid tumours (Figure 34-A). Hec1A shControl tumours were larger than those generated by shALCAM cells (Figure 34B-C). However, no differences were observed in the H&E or Ki67 staining (Figure 34A; p=0.3), indicating that the dissimilarity in tumour size was not due to cell proliferation. These results might indicate that ALCAM interferes with the ability of tumour cells to communicate with the surrounding microenvironment. Reinforcing this hypothesis, mice with ALCAM-depleted cells developed fewer metastases and more significantly, fewer local metastases than the control (Figure 35A-B). Local metastases were differentially found in the peritoneum, pelvic fat, kidney, spleen, pancreas, colon, liver and diaphragm (Figure 35-C). Accordingly, we observed that a larger proportion of control mice presented macro metastases (>5 mm) (Figure 35D-E). Taken together, we evidenced that ALCAM-depletion profoundly affected the ability of tumour cells in developing metastasis.
Figure 34. ALCAM-depletion decreased primary tumour size in an orthotopic mice model of EEC. (A) Up, representative H&E sections of the mice uterus, both cell lines produced solid primary tumours (T arrow) within the normal mice uterus (N arrow). Below, Ki67 representative images of the primary tumours showed no differences in cell proliferation. (B) Image of 6 uteri containing representative primary tumours in Hec1A shControl and shALCAM (the 3 largest and smallest tumours for each cell line). (C) ALCAM-depletion inhibited significantly the size of the primary tumour (p<0.05).
Figure 35. ALCAM-depletion reduced metastasis in an orthotopic mice model of EEC. (A) ALCAM-depletion reduced the total number of metastases per mouse and (B) reduced significantly the number of metastases produced by local invasion (p<0.05). (C) Graph representing the percentage of mice affected by metastases in the shControl and the shALCAM groups per organ. (D) The number of metastases >5 mm was significantly higher in the control group (p<0.05). (E) Representative images of colon and kidney metastases in Hec1A shControl and shALCAM mice (tumours are indicated by arrows).
4.1.5 Microarray analysis of ALCAM-dependent gene expression in Hec1A cell line To elucidate the molecular mechanisms governed by ALCAM to promote EC dissemination and metastasis, we performed a cDNA microarray to compare the gene expression profile of Hec1A shControl and shALCAM cells. A total of 315 genes were found to be deregulated with FC >1.2 and adjusted p-value <0.05.
Among those, a heatmap of the 50 most deregulated genes is
represented in Figure 36. All the differentially expressed genes were introduced in IPA and PANTHER databases for gene ontology analysis. We found that the deregulated genes were related to commonly altered pathways in cancer (Figure 37-A) and among those, the integrin signalling pathway was the most significantly altered (Figure 37-B). The IPA analysis revealed that the most enriched functions corresponded to cell movement, cell migration and cell invasion. We also observed that ALCAM inhibition had an effect in cellular assembly and organization through the regulation of genes involved in formation of cellular protrusions, microtubule dynamics, organization of cytoplasm and cytoskeleton among others; as well as functions related to cell-to-cell adhesion (Figure 37C). All of them presented a negative z-score and thus are predicted to be inhibited
Chapter 4. Results
Figure 36. Gene expression analysis of ALCAM-depleted cell lines. Heatmap of the most significant deregulated genes of microarray data for three replicates of Hec1A shALCAM and Hec1A shControl cell lines.
Figure 37. Gene ontology analyses of deregulated ALCAM-depleted cell lines. (A) Signalling pathways of deregulated genes in ALCAM-depleted cells by Panther analysis. The legend describes the most important affected pathways. (B) The integrin signalling pathway was the most significant represented pathway (p<0.05) and the specific genes are represented in the graph and described in the legend. (C) Functional categories of deregulated genes in ALCAM inhibited cells by Ingenuity pathway analysis. The activation z-score was generated by the software using the information about the direction of gene regulation. The representation of the number of genes deregulated for each functional category evidenced enrichment in cell motility and invasion.
Chapter 4. Results
4.1.6 ALCAM regulates LAMC2, FLNB and TXNRD1 during EEC dissemination To characterize the downstream effectors of ALCAM-mediated functions, we selected from the microarray data the most deregulated genes (FC >1.4, adjusted p-value <0.05) related to cell motility, cell movement and cell invasion functions. Additionally, genes from the plasminogen activating cascade, which participated in the same functions, were included (Table 21). The levels of 21 genes were validated by RT-qPCR, using both knockdown and Hec1A-ALCAM overexpressing cells. Among those, six genes -LAMC2, TXNRD1, FLNB, EPHA2, PLAU and KLK6-, presented a coherent behaviour in ALCAM-depleted and ALCAM-overexpressing cells (Figure 38A-B). LAMC2, TXNRD1 and FLNB also showed decreased protein levels in ALCAM-depleted cells (Figure 39A-B). This finding supported their role as downstream effectors of the ALCAM-related functions. The genes that were not fully consistent by RT-qPCR are presented in Figure 40A-B.
SYMBOL CD24 IGFBP6
CYFIP2 FHL2 LAMB3 LAMC2 CD44 KLK6 LGALS1
Gene ID Homo sapiens CD24 molecule, mRNA. Homo sapiens insulin-like growth factor binding protein 6, mRNA. Homo sapiens N-myc downstream regulated gene 1, mRNA. Homo sapiens cytoplasmic FMR1 interacting protein 2, mRNA. Homo sapiens four and a half LIM domains 2, mRNA. Homo sapiens laminin, beta 3, mRNA. Homo sapiens laminin, gamma 2, mRNA. Homo sapiens CD44 molecule (Indian blood group), mRNA. Homo sapiens kallikreinrelated peptidase 6, mRNA. Homo sapiens lectin, galactoside-binding, soluble, 1, mRNA.
TXNRD1 MTSS1 FLNB ITGB4 LMTK3 CAPN1
Homo sapiens thioredoxin reductase 1, mRNA. Homo sapiens metastasis suppressor 1, mRNA. Homo sapiens filamin B, beta (actin binding protein 278), mRNA. Homo sapiens integrin, beta 4, mRNA. PREDICTED: Homo sapiens lemur tyrosine kinase 3, mRNA. Homo sapiens calpain 1, (mu/I) large subunit, mRNA.
Homo sapiens S100 calcium binding protein A14, mRNA.
Homo sapiens S100 calcium binding protein A10, mRNA.
Homo sapiens plasminogen activator, urokinase, mRNA. Homo sapiens plasminogen activator, urokinase receptor, mRNA. Homo sapiens integrin, beta 1 (fibronectin receptor, beta polypeptide, antigen CD29 includes MDF2, MSK12), mRNA. Homo sapiens EPH receptor A2, mRNA. Homo sapiens AHNAK nucleoprotein, mRNA.
Table 21. List of the selected genes deregulated in the gene expression analysis of Hec1A shALCAM cells relative to Hec1A shControl.
Chapter 4. Results
Figure 38. LAMC2, TXNRD1 and FLNB were decreased at mRNA level in ALCAM-depleted cells. The expressions of PLAU, FLNB, EPHA2, LAMC2, TXNRD1 and KLK6 were analysed by RT-qPCR in Hec1A cells with (A) ALCAM-depletion (B) and overexpression versus control (*p<0.01).
Figure 39. LAMC2, TXNRD1 and FLNB were decreased at protein level in ALCAM-depleted cells. (A) Western blot analysis confirmed the down-regulation at protein level of LAMC2, TXNRD1 and FLNB in ALCAM inhibited cells. (B) Western blot was quantified using Image J software.
Chapter 4. Results
Figure 40. RT-qPCR performed on deregulated genes from the microarray study. Genes with FC >1.4 (except for PLAUR, FC >1.2) and adjusted p-value<0.05, all associated with the functional category of cell migration and invasion. (A, B) Genes included in this figure are not fully consistent to ALCAM expression, as they either present contradictory results or are not validated in both ALCAM-overexpressing and depleted cells (*p<0.01).
4.2 Characterization of the molecular mechanisms associated with ALCAM in EEC and its relation to myometrial invasion 4.2.1 Framework The first step of myometrial invasion is characterized by the dissociation of tumour cells from the epithelial layer of the endometrial glands, and their infiltration through the basement membrane into the adjacent layer, the myometrium
. For that to happen, several authors suggested that epithelial
tumour cells undergo an EMT, either transiently or stably. Specifically, it is known that in invading tumours this process could take place at the invasive front of the tumour
. As explained in Chapter 1 section 22.214.171.124,
multiple factors have been described as being responsible for producing EMT in EC, such as ETV5, oestrogen and progesterone receptors, and TGF-β, among others 312. ALCAM expression in the cell surface can be regulated by endocytosis or 268,315,270
protein cleavage by ADAM 17 metalloproteinase
, generating a soluble
96kDa and a truncated membrane-bound. Interestingly, in addition to its clear association
, ALCAM shedding has also been reported in the serum
of breast, ovarian, thyroid and pancreatic cancer patients and in all cases has been related to poor clinical outcome 303,305,318,319. We have previously demonstrated that ALCAM is an important player in EEC dissemination
. For this reason, in this results section, we go further in our
understanding of ALCAM in EEC tumorigenesis by evaluating its full-form expression (non-cleaved protein) in different areas of the tumour as well as its relation with key molecules associated to the epithelial (E-cadherin, β-catenin) and mesenchymal (ETV5, COX-2, MMP-2 and -9) context in EC. Moreover, we evaluated the levels of shed ALCAM (sALCAM) in uterine aspirates as a potential prognostic tool to predict myometrial invasion at the time of diagnosis. 9:@
Chapter 4. Results
4.2.2 ALCAM partners differed in the superficial compared to the invasive area of the tumour We studied the immunohistochemical expression of ALCAM extracellular domain (non-cleaved protein) and a representative set of epithelial (Ecadherin/β-catenin adhesion complex) and mesenchymal molecules involved in EEC dissemination (ETV5, COX-2, MMP-2 and -9), in both the superficial and the invasive areas of the tumour. As our previous results indicated the differential behaviour of ALCAM regarding tumour differentiation, analyses were performed in the whole population and in the well-differentiated (G1) and poorlydifferentiated (G2-3) subcohorts 320 . Univariate regression analyses were performed as a first approach to evaluate the association between ALCAM and epithelial or mesenchymal markers. Variables significantly correlated with ALCAM (Table 22) were included in multivariate linear regression models. Multivariate linear regression analyses evidenced a significantly positive correlation between ALCAM and the adhesion complex only at the superficial area of the tumour. Whilst β-catenin was retained in the whole population and the well-differentiated cohort (R=0.416 and 0.391, respectively), E-cadherin was retained in the moderately-poorly differentiated tumours (R=0.445) (Table 23, Figure 41). By contrast, at the invasive front of the tumour, the model performed in all patients retained COX-2 and MMP-9. Specifically, COX-2 is presented as a predictor that correlated positively with ALCAM, whilst MMP-9 was negatively correlated. However, the best regression adjustment was reached in the moderately-poorly differentiated subcohort of patients, in which the model retained ETV5 and MMP-9 with a R=0.559. Both molecules showed a negative correlation with ALCAM (Table 24, Figure 41). Altogether, the results suggest a different functional profile of the molecule that correlated strongly with the epithelial markers at the superficial tumour; and by contrast, evidenced a correlation with mesenchymal markers at the invasive front.
All cases β
Superficial area of the tumour β-catenin
Invasive front of the tumour
Table 22. Patterns of ALCAM in the tumour: univariate linear regression analysis.
Figure 41. ALCAM patterns at the tumour. Upper: full-length ALCAM was positively correlated positively with the E-cadherin/β-catenin complex at the superficial area of the tumour and its mainly localized at the cell membrane. Down: At the invasive front, full-length ALCAM was significantly inversely correlated with MMP-9 and ETV5, in the moderately-poorly differentiated EEC.
Chapter 4. Results
Superficial area of the tumour Summary model 2
MMP-9 MMP-2 Moderatelypoorly differentiated
Table 23. ALCAM patterns at the superficial area of the tumour: multivariate linear regression analysis.
Invasive front of the tumour
Summary model 2
ETV5 Grade Welldifferentiated
ETV5 MMP-9 Moderatelypoorly differentiated
Table 24. ALCAM patterns at the invasive front of the tumour: multivariate linear regression analysis.
4.2.3 ALCAM-negativity at the invasive front of the tumour is a marker of myometrial invasion In order to further investigate in the role of ALCAM at the invasive front, as well as in its relationship with ETV5 and MMP-9, categorized analyses were performed. In the superficial area, uncleaved ALCAM expression was unrelated to the clinical parameters of myometrial invasion, tumour grade, and tumour progression. Interestingly, it acts as a marker of tumour progression and invasion when analysed at the invasive front. In that case, ALCAM was shown to significantly decrease throughout the tumour stages and in tumours with myometrial invasion >50% (Table 25, Figure 42A-B). In fact, the potential of ALCAM-negativity as an independent prognostic factor of myometrial invasion
Chapter 4. Results was confirmed by multivariate logistic regression analysis with an OR 3.273, together with the tumour grade (OR 3.484) (Table 26). Σ
Variable, No. (%)
Superficial area of the tumour FIGO
82 (70.7) 43 (74.1)
34 (29.3) 15 (25.9)
Invasive front of the tumour
71 (67.0) 43 (78.2)
35 (33.0) 12 (21.8)
* Positive ≥ 65
† Negative < 65
Table 25. ALCAM expression and clinical parameters.
Figure 42. ALCAM expression was decreased at the invasive front of patients with myometrial invasion. (A) ALCAM-negativity, at the invasive front, is a marker of myometrial invasion. (B) At the invasive front, ALCAM-negative tumours increased from a 21.8% in patients without myometrial invasion to a 45.1% in patients presenting myometrial infiltration (p= 0.014).
Table 26. Multivariate logistic regression model, at the invasive front, related to myometrial invasion >50% (N=89).
Chapter 4. Results ALCAM maintained a close and inverse relation with MMP-9 in the invasive front of the tumours (p=0.004; OR 0.26) (Table 27). This relation was only maintained in poor prognosis tumours when the cohort was divided according to clinical parameters, i.e. either in tumours with moderately-poorly differentiated EEC histology (p=0.02; OR 0.08) or in patients presenting >50% of myometrial infiltration (p=0.016; OR 0.19). Interestingly, when we studied this relationship in terms of ETV5-expression, we observed that ALCAM and MMP-9 correlation was only significant in the ETV5-positive tumours (p=0.009). Altogether, our results demonstrated that ALCAM-negativity is a marker for myometrial invasion. Moreover, its close and inverse relation with MMP-9 led us speculate that ALCAM-negativity might be due to an increased shedding of the protein by the metalloproteinase at the invasive front of poor prognostic tumours. This dialog could be orchestrated by the mesenchymal transcription factor ETV5, whose up-regulation has been strongly associated with the myometrial infiltration event.
4.2.4 ALCAM shedding in uterine aspirates is a marker of myometrial invasion and is closely related to MMP-9 expression In order to evaluate the possible association between ALCAM shedding and myometrial invasion, we analysed the expression of soluble ALCAM (sALCAM) in 40 uterine aspirates (UA) from moderately-poorly differentiated EEC patients presenting different grades of myometrial infiltration. The UA is a body fluid that is collected from inside of the uterine cavity, and is formed mainly by the secretion of the tumour cells and other cells from the endometrium, enabling the detection of cleaved ALCAM by ELISA. We confirmed that sALCAM was significantly increased in patients presenting myometrial invasion >50% (Figure 43-A). Moreover, ROC analysis showed that sALCAM in UAs is a significant predictor of myometrial infiltration (AUC 0.80; p=0.001) (Figure 43-B). In fact, when ALCAM is set at a cut-off of 9.375 ng/mg, the model presents a sensitivity of 87% and a specificity of 70.6%.
Table 27. ALCAM and MMP-9 at the invasive front of the tumour.
Chapter 4. Results
Figure 43. Soluble ALCAM detected in uterine aspirates is a marker of myometrial invasion. (A) Soluble ALCAM detected by ELISA in uterine aspirates was significantly increased in patients presenting myometrial invasion (***p<0.001). ALCAM values were normalized to total protein amount from the uterine aspirates. (B) ROC curve of sALCAM individual marker demonstrated its prognostic value to discriminate patients with myometrial invasion (AUC=0.800; p=0.001).
Then, the relation between sALCAM and MMP-9 was assessed in UA by performing a gelatine zymography of the same patients (Figure 44-A). Univariate linear regression analyses (Table 28) evidenced a significant positive correlation between sALCAM with all MMP-9 detected forms, with the exception of the more labile active form. No correlation was found with the MMP-2 forms (data not shown). In order to avoid the problems derived from the simultaneous use of several measurements that reflect expressions of molecular forms of the same enzyme (Table 29), PCA was addressed to explore the close relationship
among the four MMP-9 forms and reduce their number before performing regression analysis. Two main components C1, which explains 75.18% of the variability of the original dataset, and C2 which only explains 13.86%, were extracted (Figure 44-B). Regression analyses showed a strong and positive correlation between sALCAM and C1 at the global level and specifically in patients presenting myometrial invasion >50% (R=0.575; p=0.004) (Table 28, Figure 44C-D). These results suggested that at the invasive front of the tumour ALCAM extracellular shedding by MMP-9 could be an important player in myometrial invasion.
Univariate linear regression Myometrial infiltration <50%
Myometrial infiltration >50%
C1 Regression Factor Score
Table 28. ALCAM correlation with MMP-9 in uterine aspirates.
MMP-9 forms (*) MMP-9 Dimeric MMP-9 Dimeric
MMP-9 NGAL 0.815***
MMP-9 Active (*ln-transformed)
MMP-9 Latent 0.826***
MMP-9 Active 0.552***
Table 29. Matrix correlation MMP-9 forms.
Chapter 4. Results
Figure 44. Soluble ALCAM and MMP-9 expressions were correlated in uterine aspirates. (A) Two different examples of gelatine zymography from uterine aspirates and detection of the different forms of MMP-9 and MMP-2. (B) Principal component analysis from the MMP-9 detected molecular forms evidenced two principal components: C1 (75.18% of the variability) and C2 (13.86% of the variability). The factor loadings, correlation between the original variables and the main components of each form can be observed in the graph. The KMO obtained was 0.80 and the t Barlett <0.001. (C) The principal component C1 and the sALCAM were significantly correlated in all patients (R=0.447; p=0.004). (D) The correlation between the C1 component and sALCAM was significant in patients with myometrial invasion >50% (R=0.575; p=0.004).
4.2.5 ALCAM and MMP-9 are important actors at the invasive front of an in vivo model of EEC dissemination The ETV5 overexpression in Hec1A cell line has been extensively used as a model that mimics the step of tumour invasion in EEC
, as ETV5
overexpression is known to induce EMT in EEC. Furthermore, the parental Hec1A cell line is representative of moderately-poorly differentiated EEC superficial tumours. In order to study ALCAM in a controlled environment, which represents a realistic approach towards the process of dissemination of EC, we generated orthotopic murine models by injecting Hec1A (n=5) or its ETV5 stable overexpressing cells (n=4) directly in the mice uterus. In these models, tumour cells are localized in the same microenvironment of the original tumour, resembling the processes of tumour growth and myometrial infiltration under endometrial stimuli. As expected, the tumours generated by the ETV5-overexpressing cells presented larger myometrial invasion and tumour burden as seen in the H&E and in the quantified luminescence from the IVIS images (Figure 45, Figure 47). While in the ETV5-overexpressing tumours, we observed disseminated cells in finger-like strands or single-cells projecting into the stroma at the invasive front; in the Hec1A tumours, cells invade forming clusters from the primary tumour (see arrows, Figure 45). The immunohistochemical staining of uncleaved ALCAM, MMP-9 and ETV5 in the mice’s primary tumours unveiled that ALCAM expression is reduced in the invasive front of ETV5-overexpressing compared to Hec1A tumours (p<0.05; Figure 46), and moreover, the pattern of expression is modified from a very membranous staining in Hec1A tumours to a diffuse cytoplasmic staining in ETV5 overexpressing cells (Figure 45, 48). This could be promoted by the shedding of ALCAM in ETV5 overexpressing tumours. In relation to this, we observed that the intensity of ALCAM and MMP-9 markers showed no variation between the superficial or the invasive area in the Hec1A tumours.
overexpressing tumours. In those, MMP-9 increased was concomitant with a
Chapter 4. Results decrease in ALCAM, when comparing the superficial to the invasive front of the tumour (Figure 46-B, Figure 47).
Figure 45. ALCAM was decreased at the invasive front of the primary tumours in a controlled model of EEC dissemination. Upper: Immunohistochemistry of ETV5, ALCAM and MMP-9 in Hec1A control mice. Both ALCAM and MMP-9 presented a homogeneous staining between the superficial and invasive front or disseminated cells. Black arrow signals a cluster of disseminated cells released from the primary tumour. Down: Immunohistochemistry of ETV5, ALCAM and MMP-9 in Hec1A-ETV5 mice. ALCAM expression was decreased at the invasive front of the tumour, concomitant with an increase of MMP-9 expression. Black arrows evidenced disseminated cells in finger-strand or individual cells, released from the ETV5-overexpressed primary tumour.
Figure 46. ALCAM staining was significantly decreased at the invasive front of the primary tumours in a controlled model of EEC dissemination. (A) Representation of the intensity of staining of the two molecules. ALCAM expression was only significantly decreased at the invasive front of the ETV5-overexpressing mice, compared to control (*p<0.05). (B) Relative intensity of the two markers at the invasive front compared to the superficial tumour. While in the control mice, ALCAM and MMP-9 where homogeneous across the section, in the ETV5overexpressing mice we observed a decrease in ALCAM expression concomitant with an increase in MMP-9 expression in the invasive front of the primary tumours.
Figure 47. Hec1A and Hec1A-ETV5 orthotopic murine models followed by IVIS. (A) IVIS images of the injected mice evidenced a larger tumour growth in the ETV5-overexpressing cells. (B) Quantification of the luminescence of the primary tumours ex vivo evidenced a higher intensity in the ETV5-overexpressing mice (p=0.032, one-sided test).
Chapter 4. Results
Figure 48. The expression of the full ALCAM protein was decreased at the invasive front of Hec1A-ETV5 cells. Upper: Images of ALCAM expression in Hec1A control mice, presenting less invasion and scattered clusters of cells. Down: Images of ALCAM in Hec1A-ETV5 mice, with higher rate of invasion and disseminated cells, with a finger-strand pattern. ALCAM staining was more homogeneous in the control model with lower invasion and more collective invasion.
As a result of the in vivo model, we evidenced that the cell-cell contacts of the Hec1A invading cells seem to be preserved, as shown by the highly collective migration and a homogeneous ALCAM expression. However, the ETV5overexpressing invading cells were more prone to present switching between thin cords and single-cells, both presented decreased or more transient contacts and higher rate of cleaved ALCAM expression. Moreover, we finally confirmed that in an invasive scenario, ALCAM and MMP-9 are important actors at the invasive front of the tumour. Whilst ALCAM diminishes its expression as an uncleaved protein, MMP-9 increases its expression, probably promoting ALCAM shedding.
4.2.6 Full ALCAM recovery impaired migration and decreased cell-cell adhesion of invasive EEC cells In order to understand the role of ALCAM in the invasive Hec1A-ETV5 model, we constructed two ALCAM overexpression vectors: a full-length ALCAM and an ALCAM containing only the extracellular and transmembrane region
(ALCAMcytoless) in pmCherry-N1 vectors (Figure 49-A). We transiently transfected the Hec1A-ETV5 cells with the Cherry empty-vector as a control, and both ALCAM constructs. As expected, ALCAM overexpression was localized primarily in the plasma membrane and in the cytoplasm. (Figure 49-B).
Figure 49. ALCAM recovery in mesenchymal Hec1A-ETV5 cells. (A) Representation of the two vectors constructed to overexpress ALCAM: full-length and ALCAMcytoless inserted in the pmCherry-N1 construct. (B) Images of the Hec1A-ETV5 cell line transfected with the pmCherry vector as a control, and both ALCAM-overexpression constructs.
To evaluate the effects of ALCAM-recovery in ETV5-overexpressing cells, we used 3D in vitro approaches that closely mimic the in vivo settings. We used a spheroid model to quantitatively study the spreading of cell aggregates on a striped fibronectin-coated surface. In addition to reproducing characteristics of the in vivo environment, as stated in objective (i), this model also allows us to analyse the effects of the competition between cell–cell and cell–substratum adhesion on tissue spreading
. In both conditions (ALCAM full-length and
ALCAMcytoless) the speed was significantly decreased compared to the control cells (Figure 50-A). However, the larger difference was found in the transfected cells expressing full-length ALCAM. In fact, we observed that the mean time of 9<<
Chapter 4. Results disaggregation of the Cherry-control spheroids was around 5 h, while ALCAM full-length and ALCAMcytoless expressing aggregates needed approximately 21 h and 18 h, respectively (Figure 50-B). Moreover, the pattern of spreading in control cells presented a more spindle-shaped phenotype, with larger presence of individual cells and protrusions, and highly dynamic transient cell-cell contacts, migration in a sheet fashion and presentation of chemotactic abilities. In contrast, full-ALCAM and ALCAMcytoless cells presented an increased intercellular adhesion phenotype and a more collective pattern of spreading (Figure 50-B). Consequently, ALCAM recovery clearly impaired the migratory abilities of ETV5 overexpressing cell lines. To verify these effects we evaluated how ALCAM-rescue affects the formation and strength of cell-cell adhesion. We used two micropipettes to put into contact two isolated cells maintained in suspension, to avoid cell-matrix interactions, and to initiate adhesion. Single cells were chosen under a fluorescence microscope to verify the Cherry-transfection. The mean separation force (SF) is used as a read-out of the strength of adhesion for a precise contact time. In all the cases, the SF required to disrupt the cell doublet increased with the contact time. We observed that at 4 min both ALCAM transfected cells presented significantly larger adhesion than the control line (Figure 51A-B). Cells expressing full-length ALCAM displayed stronger intercellular adhesion, as shown by the two-fold increase in their SF compared to control cells, and were more adhesive than cells expressing ALCAMcytoless. In contrast, at 10 min only the full-length ALCAM-transfected cells presented significantly stronger adhesion than the control. Thus, we showed that ALCAM shedding was important to also reduce ETV5-adhesive properties. In this particular context, the cytoplasmic tail was an important player in cell-cell adhesion formation or maturation.
Figure 50. ALCAM overexpression in mesenchymal Hec1A-ETV5 cells decreased cell migration. (A) Effect of ALCAM overexpression on migration was assessed by a 3D spheroidspreading model on 200 μm fibronectin-coated stripes. On the left, box plot of the speed of migration for each cell line. On the right, representative images at time 0h and at 24h are illustrated and the spreading reached at 24h is outlined in the images. Migration decreased in cells transfected with full-length ALCAM (**p<0.01) and ALCAMcytoless (*p<0.05) compared to control. (B) Images of the 3D spheroid-spreading model are illustrated at different time points. In the control cells, the spheroids were almost disaggregated after 5 h, whilst the mean time for disaggregation for the ALCAMcytoless cells was around 18 h, and more than 21 h for the fulllength ALCAM cells.
The molecular pathway by which ETV5 promotes its invasive functions in EEC has been recently postulated by Alonso-Alconada et al.
. The authors
described how ETV5 works through the BDNF–TrkB–ERK1/2 axis by inducing ERK1/2 phosphorylation, leading to the promotion of migration and invasion. In this work, we observed that ALCAM-overexpression was concomitant with a decrease in p-ERK levels, without reverting to an epithelial phenotype (Figure 52), but impairing the migratory and adhesive properties promoted by ETV5. Although overexpression of the extracellular-ALCAM is sufficient to reduce the
Chapter 4. Results levels of ERK phosphorylation and to decrease spheroid spreading, full-length ALCAM is necessary to increase cell-cell adhesion with time.
Figure 51. ALCAM recovery in mesenchymal Hec1A-ETV5 cells increased cell-cell adhesion. (A) Two Cherry transiently transfected cells were put into contact and allowed to form adhesion. After 4 and 10 min, we applied an increasing measurable force (nN) up to the disruption of the formed cell doublet. (B) Full-length ALCAM-overexpression increased cell-cell adhesion at all points, as shown by quantification of the separation force (***p<0.001, Mean±SEM). However, ALCAMcytoless only increased cell-cell adhesion at 4 min and showed no differences with control line at 10 min.
Figure 52. ALCAM recovery in mesenchymal Hec1A-ETV5 cells and p-ERK. Western blot analysis of ALCAM-overexpression in Hec1A-ETV5 cells demonstrated a significant decrease in the levels of ERK-phosphorylation.
Chapter 5. Discussion
Endometrial cancer (EC) is the most common gynaecological cancer in the western countries and the second leading cause of gynaecological malignancy worldwide 1. Endometrial cancers are classified into two broad categories, endometrioid and non-endometrioid carcinoma, which are associated with different pathogeneses and prognoses
endometrial cancers (EEC) comprise ≈80% of the tumours, present a better outcome, and are manifest basically of low-grade endometrioid histology whereas non-endometrioid endometrial carcinomas (NEEC) are usually represented by serous carcinomas. While EEC are associated with a premalignant hyperplastic lesion and are related to hyperoestrogenism, NEEC are associated with atrophic endometrium and hormone-independent carcinomas
. The symptomatology allows an early stage diagnosis, when
the disease is confined in the uterus. These patients are classified in FIGO stage I, and present a favourable prognosis. The FIGO stage, assessed after pathological examination of the hysterectomy sample, is the most compelling independent prognostic factor. The main goal of risk stratification systems in EC is to identify those patients who will benefit from a specific adjuvant treatment. A general consensus was recently reached between the European Society for Medical Oncology (ESMO), the European Society for Radiotherapy & Oncology (ESTRO) and
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The role of activated leukocyte cell adhesion molecule ... - DDD â UAB
The role of activated leukocyte cell adhesion molecule (ALCAM) in endometrial cancer progression and dissemination
Laura Devis Jauregui
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