Tumorgrafts as in vivo surrogates for women with ovarian cancer.
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE66667 | GEO | 2015/03/09
SECONDARY ACCESSION(S): PRJNA277697
REPOSITORIES: GEO
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Project description:This SuperSeries is composed of the following subset Series: GSE32530: Primary tumorgrafts as advanced models for breast cancer that authentically reflect tumor histopathology, growth, metastasis, and patient outcomes (copy number) GSE32531: Patient-derived tumor grafts authentically reflect tumor pathology, growth, metastasis, and disease outcomes (expression) Refer to individual Series
2011-10-22 | E-GEOD-32532 | biostudies-arrayexpress
Project description:Gene expression profiling on 63 stage III-IV papillary serous ovarian cancer samples resected during primary debulking at the University of Turin, Italy. Only the primary ovarian mass and no metastases were included in this analysis. The study focused on ovarian cancer chemokine expressions Only the primary ovarian mass and no metastases were included in this analysis.
2014-10-31 | E-GEOD-62873 | biostudies-arrayexpress
Project description:Gene expression profiling on 63 stage III-IV papillary serous ovarian cancer samples resected during primary debulking at the University of Turin, Italy. Only the primary ovarian mass and no metastases were included in this analysis. The study focused on ovarian cancer chemokine expressions
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Project description:In the last decades platinum-based neo-adjuvant chemotherapy (NACT) has been recognized as a reliable therapeutic strategy in patients with un-resectable advanced epithelial ovarian cancer (EOC). However, the molecular changes induced by NACT at miRNA level, and their prognostic role has not been clarified until now. In order to uncover miRNAs that are altered in EOC tumor which received NACT, we performed whole-miRNA analysis on 82 FIGO Stage IIIC-IV high-grade serous (HGS) tumors, whose samples had been collected at complete primary debulking (PDS) and at interval-debulking surgery (IDS) after fter 4 courses of NACT.
2016-01-20 | E-MTAB-3696 | biostudies-arrayexpress
Project description:Ovarian cancer (OC) displays the highest mortality among gynecological tumors, mainly due to early peritoneal dissemination, the high frequency of tumor relapse following primary debulking and the development of chemoresistance. All these events are thought to be initiated and sustained by a subpopulation of neoplastic cells, termed ovarian cancer stem cells (OCSC), that are endowed with self-renewing and tumor-initiating properties. This implies that interfering with OCSC function should offer novel therapeutic perspectives to defeat OC progression. To this aim, a better understanding of the molecular and functional makeup of OCSC in clinically relevant model systems is essential. We have profiled the transcriptome of OCSC vs. their bulk cell counterpart from a panel of patient-derived OC cell cultures. This revealed that Matrix Gla Protein (MGP), classically known as a calcification-preventing factor in cartilage and blood vessels, is markedly enriched in OCSC. Functional assays showed that MGP confers several stemness-associated traits to OC cells, including a transcriptional reprogramming. Patient-derived organotypic cultures pointed to the peritoneal microenvironment as a major inducer of MGP expression in OC cells. Furthermore, MGP was found to be necessary and sufficient for tumor initiation in OC mouse models, by shortening tumor latency and increasing dramatically the frequency of tumor-initiating cells. Mechanistically, MGP-driven OC stemness was mediated by the stimulation of Hedgehog signaling, in particular through the induction of the Hedgehog effector GLI1, thus highlighting a novel MGP/Hedgehog pathway axis in OCSC. Finally, MGP expression was found to correlate with poor prognosis in OC patients, and was increased in tumor tissue after chemotherapy, supporting the clinical relevance of our findings. Thus, MGP is a novel driver in OCSC pathophysiology, with a major role in stemness and in tumor initiation.
2023-05-10 | PXD037543 | Pride
Project description:The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC) is not well understood. Comprehensive molecular analyses were performed including high-pass whole-genome sequencing, targeted deep DNA sequencing, RNA sequencing, reverse-phase protein arrays, mass spectrometry-based proteomics and phosphoproteomics, and immune profiling on primary and metastatic sites from highly clinically annotated HGSC samples. Samples were obtained pre-treatment based on a laparoscopic triage algorithm from patients who underwent R0 tumor debulking or received neoadjuvant chemotherapy (NACT) with excellent or poor response.
2020-05-27 | PXD014980 | Pride
Project description:Epithelial ovarian cancer is a very heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Rational therapeutic approaches need to account for interpatient and intratumoral heterogeneity in treatment design. Detailed characterization of in vitro models representing the different histological and molecular subtypes is therefore imperative. Strikingly, from ~100 available ovarian cancer cell lines the origin and which subtype they represent is largely unknown. We have extensively and uniformly characterized 39 ovarian cancer cell lines (with mRNA/microRNA expression, exon sequencing, dose response curves for clinically relevant therapeutics) and obtained all available information on the clinical features and tissue of origin of the original ovarian cancer to refine the putative histological subtypes. From 39 ovarian cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes (21 Epithelial, 7 Round, 12 Spindle) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes for the Spindle subtype. Clinical validation showed a clear association of the spindle-like tumors with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the morphological subtypes associated with the molecular C1-6 subtypes identified by Tothill et al. [1], Spindle clustered with C1-stromal subtype, Round with C5-mesenchymal and Epithelial with C4 subtype. We provide a uniformly generated data resource for 39 ovarian cancer cell lines, the ovarian cancer cell line panel (OCCP). This should be the basis for selecting models to develop subtype specific treatment approaches, which is very much needed to prolong the survival of ovarian cancer patients. Gene expression was measured for 32 ovarian cancer cell lines using the GeneChip Human Exon 1.0 ST Array (Affymetrix). Morphological subtypes were assigned based on cell morphology, size, growth pattern and proliferation rate during culturing of the cell lines.
2014-09-18 | E-GEOD-53418 | biostudies-arrayexpress
Project description:Tumor specimens were collected from women with ovarian tumors at primary surgery in a study covering most of Denmark called the MALOVA-study (MALignant OVArian cancer study). This multidisciplinary study on ovarian cancer covers epidemiology (life style factors), biochemistry, and molecular biology with the purpose of identifying risk factors and prognostic factors for EOC. The study has been approved by the Scientific Ethic Committees in the study area (KF01-384/95). Sample collection went on from 1994 to 1999, and the study is described in details in other articles(20;21;24;30). Histopathological classification of the ovarian tumors was based on the typing criteria of the WHO. Pathology reports and tissue were collected from the participating hospitals. One pathologist specialized in ovarian tumors, reviewed the tissue specimens without knowledge of the primary diagnoses. Subsequently, the reviewed diagnosis was compared to the original diagnosis and agreement on invasiveness was present in 98 % of the cases. The histopathological type was refined in 14% of the cases. FIGO stages were obtained from clinical records and were reviewed by two gynecologists, both specialized in OC. Reviewed data were used for further analysis. Furthermore all other relevant hospital files were collected, and data concerning, debulking status, CA-125 level prior to operation, amount and type of chemotherapy and cause of death (if dead) were registered. Patients were scored as Âradical (optimally debulked) if no macroscopic residual tumor nodules were left, and as Ânon-radical (sub-optimally debulked) if macroscopic nodules were left. All fresh tumor samples included in this study were intended to be snap frozen within 20 minutes after the tumor was removed, but exact transportation time is not known. All samples have been stored at -80ºC. We selected samples from the largest and most common histological subtype, the serous ovarian cancers, all stages. The tumor sample material consisted of 70 stage III/IV tumors and 19 stage I/II tumors. Further patient information can be obtained from the submitters on request.
2007-10-01 | E-MEXP-1085 | biostudies-arrayexpress
Project description:Purpose: The majority of patients with epithelial ovarian cancer (EOC) is diagnosed at advanced stage and has a poor prognosis. A proportion of these patients though will fare well, with a prognosis similar to patients with early stage disease while others die very quickly. Clinicopathological prognostic factors do not allow precise identification of these subgroups. Thus we have validated a molecular subclassification as prognostic factor in EOC. Experimental Design: One hundred ninety-four patients with EOC stage II to IV were characterized by whole-genome expression profiling of tumor tissues and classified using a published 112 gene-set, derived from a FIGO stage directed supervised classification approach. Results: The 194 tumor samples were classified into two subclasses of 95 (subclass 1) and 99 (subclass 2) tumors, grouping all 9 FIGO II tumors in subclass 1 (p=0.001). Subclass 2 (54% of advanced stage tumors) correlated significantly with peritoneal carcinomatosis and non-optimal debulking. Patients with subclass 2 tumors had a worse progression free survival (HR 1.67, p=0.005) by univariate analysis, but it was not an independent factor in multiple analysis. However, overall survival was impaired both, univariate (HR 3.68, p<0.001) and in models corrected for relevant clinicopathologic parameters (HR 3.13, p<0.001). Significance analysis of microarrays revealed 2,115 genes differentially expressed in both subclasses (FDR 5%). Conclusion: In this validation study we showed that in advanced-stage epithelial ovarian cancer two approximately equally large molecular subtypes exist, independent from classical clinocopathological parameters presenting with highly different whole genome expression profiles and an impressively different overall survival. Purpose: The majority of patients with epithelial ovarian cancer (EOC) is diagnosed at advanced stage and has a poor prognosis. A proportion of these patients though will fare well, with a prognosis similar to patients with early stage disease while others die very quickly. Clinicopathological prognostic factors do not allow precise identification of these subgroups. Thus we have validated a molecular subclassification as prognostic factor in EOC. Experimental Design: One hundred ninety-four patients with EOC stage II to IV were characterized by whole-genome expression profiling of tumor tissues and classified using a published 112 gene-set, derived from a FIGO stage directed supervised classification approach. Results: The 194 tumor samples were classified into two subclasses of 95 (subclass 1) and 99 (subclass 2) tumors, grouping all 9 FIGO II tumors in subclass 1 (p=0.001). Subclass 2 (54% of advanced stage tumors) correlated significantly with peritoneal carcinomatosis and non-optimal debulking. Patients with subclass 2 tumors had a worse progression free survival (HR 1.67, p=0.005) by univariate analysis, but it was not an independent factor in multiple analysis. However, overall survival was impaired both, univariate (HR 3.68, p<0.001) and in models corrected for relevant clinicopathologic parameters (HR 3.13, p<0.001). Significance analysis of microarrays revealed 2,115 genes differentially expressed in both subclasses (FDR 5%). Conclusion: In this validation study we showed that in advanced-stage epithelial ovarian cancer two approximately equally large molecular subtypes exist, independent from classical clinocopathological parameters presenting with highly different whole genome expression profiles and an impressively different overall survival. Targeted therapies in second line treatment gain more and more importance in managing recurrent or progressive carcinomas, particularly in ovarian cancer, a cancer entity characterized by a very high recurrence rate. One step ahead, it is necessary to define new therapeutic targets and to select patients who might benefit from these therapies already in first line settings. A robust molecular subclassification could provide both, an adequate patient selection and potential new targets. Notably, the validation of such a subclassification is of outstanding importance to obtain a reliable basis for a specific clinical decision and a rational for the expensive development of new targeted therapies. This work provides a comprehensive basis for both. The expression values of 204 epithelial ovarian cancer tissues are determined and used for the validation of a subclassification approach (Cancer Sci. 2009 Aug;100(8):1421-8.)
2014-01-01 | E-GEOD-49997 | biostudies-arrayexpress
Project description:We previously generated genetically engineered mouse (GEM) models based on perturbation of Tp53, Rb with or without Brca1 or Brca2 that develop serous epithelial ovarian cancer (SEOC) closely resembling the human disease on histologic and molecular levels. We have adapted these GEM models to orthotopic allografts that uniformly develop tumors with short latency in immunocompetent recipients and are ideally suited for routine preclinical studies. To monitor passaged tumors at the molecular level, we analyzed transcriptional profiles of a set of primary SEOC and matching derived passaged tumors. We have merged this dataset with previously published ( doi: 10.1158/0008-5472.CAN-11-3834; PMID 22617326) dataset of murine primary ovarian tumors from our GEM models (GSE46169) and merged and compared them to expression profiles of human dataset published previously (doi: 10.1038/nature10166). The high mortality rate from ovarian cancers can be attributed to late-stage diagnosis and lack of effective treatment. Despite enormous effort to develop better targeted therapies, platinum-based chemotherapy still remains the standard of care for ovarian cancer patients, and resistance occurs at a high rate. One of the rate limiting factors for translation of new drug discoveries into clinical treatments has been the lack of suitable preclinical cancer models with high predictive value. We previously generated genetically engineered mouse (GEM) models based on perturbation of Tp53, Rb with or without Brca1 or Brca2 that develop serous epithelial ovarian cancer (SEOC) closely resembling the human disease on histologic and molecular levels. Here, we describe an adaptation of these GEM models to orthotopic allografts that uniformly develop tumors with short latency and are ideally suited for routine preclinical studies. RNA was isolated from flash frozen ovarian tumors using Trizol and Qiagen RNeasy columns
2013-10-30 | E-GEOD-51927 | biostudies-arrayexpress