12 research outputs found

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

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    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

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    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

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

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    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)

    Poor outcome in hypoxic endometrial carcinoma is related to vascular density

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    Background Identification of endometrial carcinoma (EC) patients at high risk of recurrence is lacking. In this study, the prognostic role of hypoxia and angiogenesis was investigated in EC patients. Methods Tumour slides from EC patients were stained by immunofluorescence for carbonic anhydrase IX (CAIX) as hypoxic marker and CD34 for assessment of microvessel density (MVD). CAIX expression was determined in epithelial tumour cells, with a cut-off of 1%. MVD was assessed according to the Weidner method. Correlations with disease-specific survival (DSS), disease-free survival (DFS) and distant disease-free survival (DDFS) were calculated using Kaplan–Meier curves and Cox regression analysis. Results Sixty-three (16.4%) of 385 ECs showed positive CAIX expression with high vascular density. These ECs had a reduced DSS compared to tumours with either hypoxia or high vascular density (log-rank p = 0.002). Multivariable analysis showed that hypoxic tumours with high vascular density had a reduced DSS (hazard ratio [HR] 3.71, p = 0.002), DDFS (HR 2.68, p = 0.009) and a trend for reduced DFS (HR 1.87, p = 0.054). Conclusions This study has shown that adverse outcome in hypoxic ECs is seen in the presence of high vascular density, suggesting an important role of angiogenesis in the metastatic process of hypoxic EC. Differential adjuvant treatment might be indicated for these patients.publishedVersio

    Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study

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    Background: Bayesian networks (BNs) are machine-learning-based computational models that visualize causal relationships and provide insight into the processes underlying disease progression, closely resembling clinical decision-making. Preoperative identification of patients at risk for lymph node metastasis (LNM) is challenging in endometrial cancer, and although several biomarkers are related to LNM, none of them are incorporated in clinical practice. The aim of this study was to develop and externally validate a preoperative BN to predict LNM and outcome in endometrial cancer patients.Methods and findings: Within the European Network for Individualized Treatment of Endometrial Cancer (ENI-TEC), we performed a retrospective multicenter cohort study including 763 patients, median age 65 years (interquartile range [IQR] 58-71), surgically treated for endometrial cancer between February 1995 and August 2013 at one of the 10 participating European hospitals. A BN was developed using score-based machine learning in addition to expert knowledge. Our main outcome measures were LNM and 5-year disease-specific survival (DSS). Preoperative clinical, histopathological, and molecular biomarkers were included in the network. External validation was performed using 2 prospective study cohorts: the Molecular Markers in Treatment in Endometrial Cancer (MoMaTEC) study cohort, including 446 Norwegian patients, median age 64 years (IQR 59-74), treated between May 2001 and 2010; and the PIpelle Prospective ENDOmetrial carcinoma (PIPENDO) study cohort, including 384 Dutch patients, median age 66 years (IQR 60-73), treated between September 2011 and December 2013. A BN called ENDORISK (preoperative risk stratification in endometrial cancer) was developed including the following predictors: preoperative tumor grade; immunohistochemical expression of estrogen receptor (ER), progesterone receptor (PR), p53, and L1 cell adhesion molecule (L1CAM); cancer antigen 125 serum level; thrombocyte count; imaging results on lymphadenopathy; and cervical cytology. In the MoMaTEC cohort, the area under the curve (AUC) was 0.82 (95% confidence interval [CI] 0.76-0.88) for LNM and 0.82 (95% CI 0.77-0.87) for 5-year DSS. In the PIPENDO cohort, the AUC for 5-year DSS was 0.84 (95% CI 0.78-0.90). The network was well-calibrated. In the MoMaTEC cohort, 249 patients (55.8%) were classified with Conclusions: In this study, we illustrated how BNs can be used for individualizing clinical decision-making in oncology by incorporating easily accessible and multimodal biomarkers. The network shows the complex interactions underlying the carcinogenetic process of endometrial cancer by its graphical representation. A prospective feasibility study will be needed prior to implementation in the clinic.</div

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

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    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

    Clear Cell Carcinoma (CCC) of the Cervix Is a Human Papillomavirus (HPV)-independent Tumor Associated With Poor Outcome: A Comprehensive Analysis of 58 Cases

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    Cervical clear cell carcinoma (CCC) is a rare human papillomavirus-independent adenocarcinoma. While recent studies have focused on gastric-type endocervical adenocarcinoma (GTA), little is known about CCC. A total of 58 (CCCs) were collected from 14 international institutions and retrospectively analyzed using univariable and multivariable methods and compared with 36 gastric-type adenocarcinomas and 173 human papillomavirus-associated (HPVA) endocervical adenocarcinoma (ECA) regarding overall survival (OS) and recurrence-free survival (RFS). Most cases were FIGO stage I (72.4%), with Silva C pattern of invasion (77.6%), and the majority were treated with radical surgery (84.5%) and adjuvant therapy (55.2%). Lymphovascular invasion was present in 31%, while lymph node metastasis was seen in 24.1%; 10.3% were associated with abdominopelvic metastases at the time of diagnosis; 32.8% had recurrences, and 19% died of disease. We did not find statistically significant differences in OS and RFS between CCC and GTA at 5 and 10 years (P=0.313 and 0.508, respectively), but there were significant differences in both OS and RFS between CCC and HPVA ECA (P=0.003 and 0.032, respectively). Also, OS and RFS in stage I clear cell and GTA were similar (P=0.632 and 0.692, respectively). Multivariate analysis showed that OS is influenced by the presence of recurrence (P=0.009), while RFS is influenced by the FIGO stage (P=0.025). Cervical CCC has poorer outcomes than HPVA ECA and similar outcomes to human papillomavirus-independent GTA. Oncologic treatment significantly influences RFS in univariate analysis but is not an independent prognostic factor in multivariate analysis suggesting that alternative therapies should be investigated

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

    No full text
    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

    Metabolomic and Lipidomic Profiling Identifies The Role of the RNA Editing Pathway in Endometrial Carcinogenesis

    No full text
    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

    The cutoff for estrogen and progesterone receptor expression in endometrial cancer revisited: a european network for individualized treatment of endometrial cancer collaboration study

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    There is no consensus on the cutoff for positivity of estrogen receptor (ER) and progesterone receptor (PR) in endometrial cancer (EC). Therefore, we determined the cutoff value for ER and PR expression with the strongest prognostic impact on the outcome. Immunohistochemical expression of ER and PR was scored as a percentage of positive EC cell nuclei. Cutoff values were related to disease-specific survival (DSS) and disease-free survival (DFS) using sensitivity, specificity, and multivariable regression analysis. The results were validated in an independent cohort. The study cohort (n = 527) included 82% of grade 1-2 and 18% of grade 3 EC. Specificity for DSS and DFS was highest for the cutoff values of 1-30%. Sensitivity was highest for the cutoff values of 80-90%. ER and PR expression were independent markers for DSS at cutoff values of 10% and 80%. Consequently, three subgroups with distinct clinical outcomes were identified: 0-10% of ER/PR expression with, unfavorable outcome (5-year DSS = 75.9-83.3%); 20-80% of ER/PR expression with, intermediate outcome (5-year DSS = 93.0-93.9%); and 90-100% of ER/PR expression with, favorable outcome (5-year DSS = 97.8-100%). The association between ER/PR subgroups and outcomes was confirmed in the validation cohort (n = 265). We propose classification of ER and PR expression based on a high-risk (0-10%), intermediate-risk (20-80%), and low-risk (90-100%) group
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