Cervical Fluids Are a Source of Protein Biomarkers for Early, Non-Invasive Endometrial Cancer Diagnosis

Cervical sample; Endometrial cancer; ProteinMostra cervical; Càncer d'endometri; ProteïnaMuestra cervical; Cáncer de endometrio; ProteínaBackground: Abnormal uterine bleeding is the main symptom of endometrial cancer (EC), but it is highly nonspecific. This represents a huge burden for women’s health since all women presenting with bleeding will undergo sequential invasive tests, which are avoidable for 90–95% of those women who do not have EC. Methods: This study aimed to evaluate the potential of cervical samples collected with five different devices as a source of protein biomarkers to diagnose EC. We evaluated the protein quantity and the proteome composition of five cervical sampling methods. Results: Samples collected with a Rovers Cervex Brush® and the HC2 DNA collection device, Digene, were the most suitable samples for EC proteomic studies. Most proteins found in uterine fluids were also detected in both cervical samples. We then conducted a clinical retrospective study to assess the expression of 52 EC-related proteins in 41 patients (22 EC; 19 non-EC), using targeted proteomics. We identified SERPINH1, VIM, TAGLN, PPIA, CSE1L, and CTNNB1 as potential protein biomarkers to discriminate between EC and symptomatic non-EC women with abnormal uterine bleeding in cervical fluids (AUC > 0.8). Conclusions: This study opens an avenue for developing non-invasive protein-based EC diagnostic tests, which will improve the standard of care for gynecological patients.This research was funded by grants from the Instituto de Salud Carlos III (ISCIII) grant number PI17/02155, PI20/00644 to E.C. and S.C., and the IFI19/00029 to E.C.-d.l.-R.; from Fundación Científica Asociación Española Contra el Cáncer (AECC) grant number GCTRA1804MATI; and the INVES20051COLA to E.C.; the CIBERONC network grant number CB16/12/00328; and the ERA PerMed ERA-NET grant (PERME212443COLA funded by AECC and AEC21_2/00030 funded by ISCIII); and 2021 SGR 1157 by AGAUR. The present work has been also supported by a Televie grant 5/20/5—TLV/DD to G.D

In silico Approach for Validating and Unveiling New Applications for Prognostic Biomarkers of Endometrial Cancer

Bioinformática; Cáncer de endometrio; Biomarcador pronósticoBioinformàtica; Càncer d'endometri; Biomarcador pronòsticBioinformatics; Endometrial cancer; Prognostic biomarkerEndometrial cancer (EC) mortality is directly associated with the presence of prognostic factors. Current stratification systems are not accurate enough to predict the outcome of patients. Therefore, identifying more accurate prognostic EC biomarkers is crucial. We aimed to validate 255 prognostic biomarkers identified in multiple studies and explore their prognostic application by analyzing them in TCGA and CPTAC datasets. We analyzed the mRNA and proteomic expression data to assess the statistical prognostic performance of the 255 proteins. Significant biomarkers related to overall survival (OS) and recurrence-free survival (RFS) were combined and signatures generated. A total of 30 biomarkers were associated either to one or more of the following prognostic factors: histological type (n = 15), histological grade (n = 6), FIGO stage (n = 1), molecular classification (n = 16), or they were associated to OS (n = 11), and RFS (n = 5). A prognostic signature composed of 11 proteins increased the accuracy to predict OS (AUC = 0.827). The study validates and identifies new potential applications of 30 proteins as prognostic biomarkers and suggests to further study under-studied biomarkers such as TPX2, and confirms already used biomarkers such as MSH6, MSH2, or L1CAM. These results are expected to advance the quest for biomarkers to accurately assess the risk of EC patients.This research was funded by grants from the Instituto de Salud Carlos III (ISCIII) grant number PI17/02155, PI20/00644, and the IFI19/00029 to E.C.-d.l.R., the Ministerio de ciencia, Innovación y Universidades through a RETOS Colaboración (RTC-2017-6261-1), both co-financed by the European Regional Development Fund (FEDER); from Fundación Científica Asociación Española Contra el Cáncer (AECC) grant number GCTRA1804MATI and CIBERONC network grant number CB16/12/00328; and Grups Consolidats de la Generalitat de Catalunya (2017SGR1661). E.C. is supported by an Investigator Grant from AECC (INVES20051COLA). E.M.-G. was supported by Televie grant F5/20/5-TLV/DD

Genomic Validation of Endometrial Cancer Patient-Derived Xenograft Models as a Preclinical Tool

Bioinformatics; Endometrial cancer; Molecular markerBioinformática; Cáncer endometrial; Marcador molecularBioinformàtica; Càncer d'endometri; Marcador molecularEndometrial cancer (EC) is the second most frequent gynecological cancer worldwide. Although improvements in EC classification have enabled an accurate establishment of disease prognosis, women with a high-risk or recurrent EC face a dramatic situation due to limited further treatment options. Therefore, new strategies that closely mimic the disease are required to maximize drug development success. Patient-derived xenografts (PDXs) are widely recognized as a physiologically relevant preclinical model. Hence, we propose to molecularly and histologically validate EC PDX models. To reveal the molecular landscape of PDXs generated from 13 EC patients, we performed histological characterization and whole-exome sequencing analysis of tumor samples. We assessed the similarity between PDXs and their corresponding patient’s tumor and, additionally, to an extended cohort of EC patients obtained from The Cancer Genome Atlas (TCGA). Finally, we performed functional enrichment analysis to reveal differences in molecular pathway activation in PDX models. We demonstrated that the PDX models had a well-defined and differentiated molecular profile that matched the genomic profile described by the TCGA for each EC subtype. Thus, we validated EC PDX’s potential to reliably recapitulate the majority of histologic and molecular EC features. This work highlights the importance of a thorough characterization of preclinical models for the improvement of the success rate of drug-screening assays for personalized medicine.This research was funded by grants from the Instituto de Salud Carlos III (ISCIII) grant number PI17/02071, PI20/01566, and from the Ministerio de ciencia, Innovación y Universidades through a RETOS Colaboración (RTC-2017-6261-1), both co-financed by the European Regional Development Fund (FEDER); from Fundación Científica Asociación Española Contra el Cáncer (AECC) grant number GCTRA1804MATI, Biomedical Research Center Network (CIBERONC) grant number CB16/12/00328 and Generalitat de Catalunya, grant number 2017SGR1661. B.V.-M. is supported by a predoctoral fellowship (PERIS-SLT017/20/000183) from Generalitat de Catalunya. E.C. is supported by an Investigator Grant from AECC (INVES20051COLA)

Metabolomic and lipidomic profiling identifies the role of the RNA editing pathway in endometrial carcinogenesis

Endometrial cancer (EC) remains the most common malignancy of the genital tract among women in developed countries. Although much research has been performed at genomic, transcriptomic and proteomic level, there is still a significant gap in the metabolomic studies of EC. In order to gain insights into altered metabolic pathways in the onset and progression of EC carcinogenesis, we used high resolution mass spectrometry to characterize the metabolomic and lipidomic profile of 39 human EC and 17 healthy endometrial tissue samples. Several pathways including lipids, Kynurenine pathway, endocannabinoids signaling pathway and the RNA editing pathway were found to be dysregulated in EC. The dysregulation of the RNA editing pathway was further investigated in an independent set of 183 human EC tissues and matched controls, using orthogonal approaches. We found that ADAR2 is overexpressed in EC and that the increase in expression positively correlates with the aggressiveness of the tumor. Furthermore, silencing of ADAR2 in three EC cell lines resulted in a decreased proliferation rate, increased apoptosis, and reduced migration capabilities in vitro. Taken together, our results suggest that ADAR2 functions as an oncogene in endometrial carcinogenesis and could be a potential target for improving EC treatment strategies.This work was supported by the Spanish Ministry of Health (RD12/0036/0035), the Spanish Ministry of Economy and Competitivy (PI14/02043), the AECC (Grupos Estables de Investigacion 2011 - AECC- GCB 110333 REVE), the Fundació La Marató TV3 (2/C/2013), the CIRIT Generalitat de Catalunya (2014 SGR 1330) and the European Commission, 7th Framework Program, IRSES (PROTBIOFLUID –269285) – Belgium. Te Spanish Ministry of Economy and Competitiveness (IJCI-2015-25000) granted Dr. Colás and and the AGAUR Generalitat de Catalunya (2015FI_B00703) granted Tatiana Altadill. Te authors would like to acknowledge the Proteomics and Metabolomics Shared Resource partially supported by Cancer Center Support Grant NIH/NCI grant P30-CA051008. Te Institut de Salud Carlos III (FIS (PI13/01701)) also supported this project. Tissue samples were obtained with the support of “Xarxa Catalana de Bancs de Tumors” and “Plataforma de Biobancos” ISCIII (PT13/0010/0014)

In silico Approach for Validating and Unveiling New Applications for Prognostic Biomarkers of Endometrial Cancer

Endometrial cancer (EC) mortality is directly associated with the presence of prognostic factors. Current stratification systems are not accurate enough to predict the outcome of patients. Therefore, identifying more accurate prognostic EC biomarkers is crucial. We aimed to validate 255 prognostic biomarkers identified in multiple studies and explore their prognostic application by analyzing them in TCGA and CPTAC datasets. We analyzed the mRNA and proteomic expression data to assess the statistical prognostic performance of the 255 proteins. Significant biomarkers related to overall survival (OS) and recurrence-free survival (RFS) were combined and signatures generated. A total of 30 biomarkers were associated either to one or more of the following prognostic factors: histological type (n = 15), histological grade (n = 6), FIGO stage (n = 1), molecular classification (n = 16), or they were associated to OS (n = 11), and RFS (n = 5). A prognostic signature composed of 11 proteins increased the accuracy to predict OS (AUC = 0.827). The study validates and identifies new potential applications of 30 proteins as prognostic biomarkers and suggests to further study under-studied biomarkers such as TPX2, and confirms already used biomarkers such as MSH6, MSH2, or L1CAM. These results are expected to advance the quest for biomarkers to accurately assess the risk of EC patients

Shaping endometrial cancer diagnosis via the identification of protein biomarkers in gynecological fluids

El càncer d'endometri (CE) és el sisè tumor més comú en dones a tot el món, amb 417.367 casos nous i 97.370 morts el 2020. El diagnòstic precoç del CE s'associa amb el 95% de la taxa de supervivència als 5 anys, mentre que el diagnòstic avançat la redueix al 17%. Actualment, no existeix cap prova de cribratge per a la detecció precoç del CE. Només les dones que presenten els símptomes clàssics del CE, principalment un sagnat uterí anormal (SUA), inicien el llarg procés de diagnòstic del CE, basat en l'obtenció invasiva de biòpsies endometrials. Això suposa una gran càrrega per a la salut femenina, ja que el SUA és un símptoma molt poc específic. Per tant, el desenvolupament i la implementació d'una prova no invasiva per distingir les condicions benignes dels CE urgeix. A més del diagnòstic, les biòpsies endometrials haurien de proporcionar informació sobre la histologia i grau tumorals per avaluar del risc preoperatori en pacients amb CE, utilitzat per guiar el tractament quirúrgic. Malauradament, el limitat material contingut en les biòpsies i l'elevada variabilitat en la interpretació patològica entre especialistes resulta en un 11% i 27% de discordances entre el diagnòstic preoperatori i el final en la determinació del tipus i grau histològic, respectivament. Per tant, la mesura objectiva dels factors pronòstics i/o la identificació de nous biomarcadors pronòstics també són urgents per guiar un tractament quirúrgic òptim en pacients amb CE. L'objectiu d'aquesta tesi és posicionar els fluids ginecològics, com les biòpsies líquides uterines i els fluids cervicals, com a font de biomarcadors de CE altament sensibles i específics. En aquesta tesi, hem volgut identificar biomarcadors altament sensibles, específics i reproduïbles que millorin el diagnòstic i l'avaluació del risc preoperatori dels tumors endometrials en fluids ginecològics, seguint dos enfocs diferents. El primer va ser investigar el fluid de les biòpsies pipelle, és a dir, els fluids uterins, com a font de biomarcadors de tipus i grau histològic, així com la predicció de recurrència. Per aconseguir-ho, vam realitzar una extensa revisió literària identificant 255 proteïnes, 30 de les quals es van validar en un anàlisi in-silico. Paral·lelament, vam generar una biblioteca espectral amb el proteoma dels fluids uterins (n= 42 CE) que posteriorment es va utilitzar per realitzar un estudi clínic retrospectiu en fluids uterins de 149 pacients amb CE quantificats per espectrometria de masses (EM) d'adquisició independent de les dades. L'estudi va permetre definir panells de 2 proteïnes que permeten el diagnòstic del tipus histològic amb sensibilitats que oscil·len entre el 90,9-100%, grau histològic amb una sensibilitat del 85,3%, i predir recurrència amb sensibilitats entre el 85,7-100%. Per avançar en el diagnòstic del CE, el segon enfocament es va dirigir a la identificació de biomarcadors proteics en fluids cervicals pel diagnòstic precís i no invasiu del CE. Vam realitzar dos estudis clínics retrospectius utilitzant els fluids cervicals, incloent un estudi de descobriment amb 59 pacients i un estudi de verificació amb 241 pacients mitjançant EM. Com a resultat, vam identificar biomarcadors de diagnòstic de CE i vam desenvolupar panells proteics que diagnostiquen el CE amb una sensibilitat del 95,4%. Adicionalment, vam identificar panells proteics per determinar el tipus i el grau histològic amb AUC de 0,91 i 0,97, respectivament. S'espera que els resultats d'aquesta tesi generin un canvi de paradigma en el maneig de les dones que pateixen SUA i millorin la detecció precoç del CE. Hem identificat panells de proteïnes que permeten una avaluació objectiva i més precisa del risc preoperatori per a pacients amb CE en fluids uterins i que permeten desenvolupar un diagnòstic de CE precís, objectiu i no invasiu basat en fluids cervicals.El cáncer de endometrio (CE) es el sexto tumor más común en mujeres a nivel mundial, con 417.367 nuevos casos y 97.370 muertes en 2020. El diagnóstico temprano del CE se asocia con el 95% de la tasa de supervivencia a los 5 años, mientras que el diagnóstico avanzado la reduce hasta el 17%. Actualmente no existe ninguna prueba de cribado para la detección precoz del CE. Solo las mujeres que presentan los síntomas clásicos del CE, principalmente un sangrado uterino anormal (SUA), inician el largo proceso de diagnóstico del CE, basado en la obtención invasiva de biopsias endometriales. Esto representa una gran carga para la salud de la mujer, ya que el SUA es un síntoma muy inespecífico. Por lo tanto, urge el desarrollo y la implementación de una prueba no invasiva para distinguir las patologías benignas de los CE. Además del diagnóstico, las biopsias endometriales deben proporcionar información sobre la histología y grado tumorales para evaluar el riesgo preoperatorio en pacientes con CE, utilizado para guiar el tratamiento quirúrgico. Desafortunadamente, el limitado material contenido en las biopsias y la alta variabilidad en la interpretación patológica entre especialistas resulta en un 11% y 27% de discordancias entre el diagnóstico preoperatorio y el final en la determinación del tipo histológico y grado, respectivamente. Por lo tanto, la medición objetiva de los factores pronósticos y/o la identificación de nuevos biomarcadores pronósticos también se necesita con urgencia para guiar un tratamiento quirúrgico óptimo en pacientes con CE. El objetivo de esta tesis es posicionar los fluidos ginecológicos, como las biopsias líquidas uterinas y los fluidos cervicales, como fuente de biomarcadores de CE altamente sensibles y específicos. En esta tesis, nuestro objetivo fue identificar biomarcadores altamente sensibles, específicos y reproducibles que mejoraran el diagnóstico y la evaluación del riesgo preoperatorio de tumores endometriales en fluidos ginecológicos, siguiendo dos enfoques diferentes. El primero fue investigar el fluido de las biopsias pipelle, es decir, los fluidos uterinos, como fuente de biomarcadores de tipo y grado histológico, y predicción de recurrencia. Para lograrlo, realizamos una extensa revisión literaria identificando 255 proteínas, 30 de las cuales fueron validadas en un análisis in-silico. Paralelamente, generamos una biblioteca espectral con el proteoma de fluidos uterinos (n=42 CE) que posteriormente se utilizó para realizar un estudio clínico retrospectivo en fluidos uterinos de 149 pacientes con CE cuantificados mediante espectrometría de masas (EM) de adquisición independiente de datos. El estudio permitió definir paneles de 2 proteínas que permiten el diagnóstico de tipo histológico con sensibilidades entre el 90,9-100%, grado histológico con sensibilidad del 85,3%, y predicen recurrencia con sensibilidades del 85,7-100%. Para avanzar en el diagnóstico del CE, el segundo enfoque se dirigió a identificar biomarcadores proteicos en los fluidos cervicales para diagnosticar el CE de manera precisa y no invasiva. Realizamos dos estudios clínicos retrospectivos sobre fluidos cervicales, incluyendo un estudio de descubrimiento de 59 pacientes y un estudio de verificación de 241 pacientes mediante EM. Como resultado, identificamos biomarcadores de diagnóstico de CE y desarrollamos paneles de proteínas que diagnostican el CE llegando a una sensibilidad del 95,4%. Además, también identificamos paneles de proteínas para determinar el tipo histológico y el grado con AUCs de 0,91 y 0,97, respectivamente. Se espera que los resultados de esta tesis generen un cambio de paradigma en el manejo de las mujeres que sufren SUA y mejoren la detección temprana del CE. Identificamos paneles de proteínas que permiten una evaluación objetiva y más precisa del riesgo preoperatorio para pacientes con CE en fluidos uterinos, y que permiten el desarrollo de un diagnóstico preciso, objetivo y no invasivo del CE basado en fluidos cervicales.Endometrial cancer (EC) is the sixth most common tumor in women worldwide, with 417,367 new cases and 97,370 deaths in 2020. Early diagnosis of EC is associated with 95% of 5-year survival rate, while advanced diagnosis drops the survival rate down to 17%. Today, there is no screening test for the early detection of EC. Only women presenting the classic symptoms of EC, i.e., mainly an abnormal uterine bleeding (AUB), start the multistep process of EC diagnosis, which relies on the invasive acquisition of endometrial biopsies. This accounts for a huge burden for women's health since AUB is a highly unspecific symptom. Therefore, the development and implementation of a non-invasive test to distinguish benign from malignant conditions is urgently needed. In addition to diagnosis, endometrial biopsies should provide information regarding tumor histology and tumor grade to provide the pre-operative risk assessment in EC patients, which is used to guide the surgical treatment. Unfortunately, the limited material contained in endometrial biopsies and the high inter-observer variability in the pathological interpretation, results in 11% and 27% of discordances in the determination of EC histological type and grade, respectively, between preoperative and final diagnosis. Thus, the objective measurement of prognostic factors and/or the identification of novel prognostic biomarkers is as well urgently needed to guide an optimal EC surgical treatment. This thesis was performed aiming to position gynecological fluids, such as uterine liquid biopsies and cervical fluids, as a source of highly sensitive and specific EC biomarkers. In this thesis, we aimed to identify highly sensitive, specific, and reproducible biomarkers that improve the diagnosis and pre-operative risk assessment of EC tumors in gynecological fluids, following two different approaches. The first was to investigate the fluid of pipelle biopsies i.e., uterine fluids, as a source of biomarkers of histological type and grade, and recurrence prediction. To achieve this, we performed an extensive literature review identifying 255 proteins, 30 of which were further validated in an in-silico analysis. In parallel, we generated a spectral library with the proteome of uterine fluids (n=42 EC) that was subsequently used to conduct a clinical retrospective study in uterine fluids of 149 EC patients quantified by data-independent acquisition mass spectrometry (MS). The study allowed us to define panels of 2 proteins that allow diagnosis of histological type with sensitivities ranging from 90.9-100%, histological grade with sensitivity of 85.3%, and predict recurrence with sensitivities ranging from 85.7-100%. As a step towards advancing on EC diagnosis, the second approach was directed to investigate on the identification of protein biomarkers in cervical fluids to accurately and non-invasively diagnose EC. We conducted two clinical retrospective studies on cervical fluids, including a discovery study of 59 patients and a verification study of 241 patients by MS approaches. As a result, we identified EC diagnostic biomarkers and developed protein signatures that accurately diagnose EC with a sensitivity of 95.4%. Additionally, we also identify protein signatures to determine the histological type and grade with AUCs of 0.91 and 0.97, respectively. The results of this thesis are expected to generate a change in the paradigm on how clinicians manage women suffering from AUB, and to improve early detection of EC. We identified protein signatures that permit an objective and more accurate preoperative risk assessment for EC patients in uterine fluids, and that allow the development of a non-invasive, accurate and objective EC diagnosis based on cervical fluids

Cervical Fluids Are a Source of Protein Biomarkers for Early, Non-Invasive Endometrial Cancer Diagnosis

Background: Abnormal uterine bleeding is the main symptom of endometrial cancer (EC), but it is highly nonspecific. This represents a huge burden for women’s health since all women presenting with bleeding will undergo sequential invasive tests, which are avoidable for 90–95% of those women who do not have EC. Methods: This study aimed to evaluate the potential of cervical samples collected with five different devices as a source of protein biomarkers to diagnose EC. We evaluated the protein quantity and the proteome composition of five cervical sampling methods. Results: Samples collected with a Rovers Cervex Brush® and the HC2 DNA collection device, Digene, were the most suitable samples for EC proteomic studies. Most proteins found in uterine fluids were also detected in both cervical samples. We then conducted a clinical retrospective study to assess the expression of 52 EC-related proteins in 41 patients (22 EC; 19 non-EC), using targeted proteomics. We identified SERPINH1, VIM, TAGLN, PPIA, CSE1L, and CTNNB1 as potential protein biomarkers to discriminate between EC and symptomatic non-EC women with abnormal uterine bleeding in cervical fluids (AUC > 0.8). Conclusions: This study opens an avenue for developing non-invasive protein-based EC diagnostic tests, which will improve the standard of care for gynecological patients

Prognostic Biomarkers in Endometrial Cancer : A Systematic Review and Meta-Analysis

Endometrial cancer (EC) is the sixth most common cancer in women worldwide and its mortality is directly associated with the presence of poor prognostic factors driving tumor recurrence. Stratification systems are based on few molecular, and mostly clinical and pathological parameters, but these systems remain inaccurate. Therefore, identifying prognostic EC biomarkers is crucial for improving risk assessment pre- and postoperatively and to guide treatment decisions. This systematic review gathers all protein biomarkers associated with clinical prognostic factors of EC, recurrence and survival. Relevant studies were identified by searching the PubMed database from 1991 to February 2020. A total number of 398 studies matched our criteria, which compiled 255 proteins associated with the prognosis of EC. MUC16, ESR1, PGR, TP53, WFDC2, MKI67, ERBB2, L1CAM, CDH1, PTEN and MMR proteins are the most validated biomarkers. On the basis of our meta-analysis ESR1, TP53 and WFDC2 showed potential usefulness for predicting overall survival in EC. Limitations of the published studies in terms of appropriate study design, lack of high-throughput measurements, and statistical deficiencies are highlighted, and new approaches and perspectives for the identification and validation of clinically valuable EC prognostic biomarkers are discusse

In silico Approach for Validating and Unveiling New Applications for Prognostic Biomarkers of Endometrial Cancer

Endometrial cancer (EC) mortality is directly associated with the presence of poor prognostic factors. Molecular prognostic factors have been identified, but none are used in clinical practice due to lack of validation studies. This study aims to validate a set of 255 prognostic biomarkers previously identified in an extensive literature review and explore new prognostic applications by analyzing them in The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases. A total of 30 biomarkers were validated and associated to a histological type (n = 15), histological grade (n = 6), FIGO stage (n = 1), molecular classification (n = 16), overall survival (n = 11), and recurrence-free survival (n = 5). Our results encourage further studies of understudied biomarkers such as TPX2, and validates already broadly studied biomarkers such as MSH6, MSH2, or L1CAM, among others. Finally, our results present a significant step to advance the quest for biomarkers to accurately assess the risk of EC patients. Endometrial cancer (EC) mortality is directly associated with the presence of prognostic factors. Current stratification systems are not accurate enough to predict the outcome of patients. Therefore, identifying more accurate prognostic EC biomarkers is crucial. We aimed to validate 255 prognostic biomarkers identified in multiple studies and explore their prognostic application by analyzing them in TCGA and CPTAC datasets. We analyzed the mRNA and proteomic expression data to assess the statistical prognostic performance of the 255 proteins. Significant biomarkers related to overall survival (OS) and recurrence-free survival (RFS) were combined and signatures generated. A total of 30 biomarkers were associated either to one or more of the following prognostic factors: histological type (n = 15), histological grade (n = 6), FIGO stage (n = 1), molecular classification (n = 16), or they were associated to OS (n = 11), and RFS (n = 5). A prognostic signature composed of 11 proteins increased the accuracy to predict OS (AUC = 0.827). The study validates and identifies new potential applications of 30 proteins as prognostic biomarkers and suggests to further study under-studied biomarkers such as TPX2, and confirms already used biomarkers such as MSH6, MSH2, or L1CAM. These results are expected to advance the quest for biomarkers to accurately assess the risk of EC patients

Genomic Validation of Endometrial Cancer Patient-Derived Xenograft Models as a Preclinical Tool

Endometrial cancer (EC) is the second most frequent gynecological cancer worldwide. Although improvements in EC classification have enabled an accurate establishment of disease prognosis, women with a high-risk or recurrent EC face a dramatic situation due to limited further treatment options. Therefore, new strategies that closely mimic the disease are required to maximize drug development success. Patient-derived xenografts (PDXs) are widely recognized as a physiologically relevant preclinical model. Hence, we propose to molecularly and histologically validate EC PDX models. To reveal the molecular landscape of PDXs generated from 13 EC patients, we performed histological characterization and whole-exome sequencing analysis of tumor samples. We assessed the similarity between PDXs and their corresponding patient's tumor and, additionally, to an extended cohort of EC patients obtained from The Cancer Genome Atlas (TCGA). Finally, we performed functional enrichment analysis to reveal differences in molecular pathway activation in PDX models. We demonstrated that the PDX models had a well-defined and differentiated molecular profile that matched the genomic profile described by the TCGA for each EC subtype. Thus, we validated EC PDX's potential to reliably recapitulate the majority of histologic and molecular EC features. This work highlights the importance of a thorough characterization of preclinical models for the improvement of the success rate of drug-screening assays for personalized medicine