Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1247242 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR32998200_1.fastq.gz | Fastqsanger.gz | |||
| SRR32998200_2.fastq.gz | Fastqsanger.gz | |||
| SRR32998300_1.fastq.gz | Fastqsanger.gz | |||
| SRR32998300_2.fastq.gz | Fastqsanger.gz | |||
| SRR32998201_1.fastq.gz | Fastqsanger.gz |
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Project description:Background: Better understanding of prognostic factors in tubo-ovarian high-grade serous carcinoma (HGSC) is critical, as diagnosis confers an aggressive disease course. Variation in tumor DNA methylation shows promise predicting outcome, yet prior studies were largely platform-specific and unable to evaluate multiple molecular features. Methods: We analyzed genome-wide DNA methylation in 1,040 frozen HGSC, including 325 previously reported upon, seeking a multi-platform quantitative methylation signature which we evaluated in relation to clinical features, tumor characteristics, time to recurrence/death, extent of CD8+ tumor-infiltrating lymphocytes (TILs), gene expression molecular subtypes, and gene expression of the ATP-binding cassette transporter TAP1. Results: Methylation signature was associated with shorter time to recurrence, independent of clinical factors (N=715 new set, HR 1.65, 95% CI 1.10-2.46, p=0.015; N=325 published set HR 2.87, 95% CI 2.17-3.81, p=2.2 x 10-13) and remained prognostic after adjustment for gene expression molecular subtype and TAP1 expression (N=599, HR 2.22, 95% CI 1.66-2.95, p=4.1 x 10-8). Methylation signature was inversely related to CD8+ TIL levels (p=2.4 x 10-7) and TAP1 expression (p=0.0011) and was associated with gene expression molecular subtype (p=5.9 x 10-4) in covariate-adjusted analysis. Conclusions: Multi-center analysis identified a novel quantitative tumor methylation signature of HGSC applicable to numerous commercially available platforms indicative of shorter time to recurrence/death, adjusting for other factors. Along with immune cell composition analysis, these results suggest a role for DNA methylation in the immunosuppressive microenvironment. Impact: This work aids in identification of targetable epigenome processes and stratification of patients for whom tailored treatment may be most beneficial.
2023-02-22 | GSE223467 | GEO
Project description:PURPOSE: We investigated whether tumor tissue obtained at diagnosis expresses a specific gene profile that is predictive of findings at second-look surgery in patients with epithelial ovarian cancer (EOC). PATIENTS AND METHODS: Tumor tissue obtained at the time of diagnosis was profiled with oligonucleotide microarrays. Class prediction analysis was performed in a training set of 24 patients who had undergone a second-look procedure. The resultant predictive signature was then tested on an independent validation set comprised of 36 patients. RESULTS: A 93-gene signature referred to as the Chemotherapy Response Profile (CRP) was identified through its association with pathologic complete response. When applied to a separate validation set, the CRP distinguished between patients with unfavorable versus favorable overall survival (median 41 months v not yet reached, respectively, log-rank P = .007), with a median follow-up of 52 months. The signature maintained independent prognostic value in multivariate analysis, controlling for other known prognostic factors such as age, stage, grade, and debulking status. There was no genetic overlap between the CRP and our previously described Ovarian Cancer Prognostic Profile (OCPP), which demonstrated similar prognostic value. The combination of the CRP and OCPP yielded better prognostic discrimination then either profile alone. Genes present in the CRP include BAX, a proapoptotic protein previously associated with chemotherapy response in ovarian cancer. CONCLUSION: Identification of a gene expression profile based on pathologic response in EOC provides independent prognostic information and offers potential insights into the mechanism of drug resistance. Efforts to identify a more tailored profile using selected genes from both the CRP and OCPP are underway. keyword(s): Correlation with outcome All microarray experiments were performed at the BIDMC Genomics Center. Ovarian cancer samples were collected at the time of primary debulking surgery and frozen at 80°C. Tumor samples were pulverized in liquid nitrogen and homogenized in Trizol solution, followed by RNA isolation, probe labeling, and Affymetrix GeneChip hybridization using standard manufacturer protocols. The dChip algorithm was used for data normalization and for generating gene expression signal values. Two outlier arrays as identified by the dChip software were excluded from further analysis.
2011-08-11 | E-GEOD-31245 | biostudies-arrayexpress
Project description:Epithelial ovarian cancer is the leading cause of death among gynecologic malignancies. Diagnosis usually occurs after metastatic spread, largely reflecting vague symptoms of early disease combined with lack of an effective screening strategy. Epigenetic mechanisms of gene regulation, including DNA methylation, are fundamental to normal cellular function and also play a major role in carcinogenesis. To elucidate the biological and clinical relevance of DNA methylation in ovarian cancer, we conducted expression microarray analysis of 43 cell lines and 17 primary culture specimens grown in the presence or absence of DNA methyltransferase (DNMT) inhibitors. Two parameters, induction of expression and standard deviation among untreated samples, identified 378 candidate methylated genes, many relevant to TGF-beta signaling. We analyzed 43 of these genes and they all exhibited methylation. Treatment with DNMT inhibitors increased TGF-beta pathway activity. Hierarchical clustering of ovarian cancers using the 378 genes reproducibly generated a distinct gene cluster strongly correlated with TGF-beta pathway activity that discriminates patients based on age. These data suggest that accumulation of age-related epigenetic modifications leads to suppression of TGF-beta signaling and contributes to ovarian carcinogenesis. Seventeen primary cultures of ovarian cells (two pooled normal ovarian surface epithelium, two serous borderline tumors, one endometrioid and twelve serous epithelial ovarian cancers) were mock treated or treated with 5 µM 5-AzaC for 72 hours, followed by gene expression microarray analysis to enable identification of genes differentially expressed as a result of inhibition of DNA methyltransferase activity.
2010-11-17 | E-GEOD-25427 | biostudies-arrayexpress
Project description:PURPOSE: We investigated whether tumor tissue obtained at diagnosis expresses a specific gene profile that is predictive of findings at second-look surgery in patients with epithelial ovarian cancer (EOC). PATIENTS AND METHODS: Tumor tissue obtained at the time of diagnosis was profiled with oligonucleotide microarrays. Class prediction analysis was performed in a training set of 24 patients who had undergone a second-look procedure. The resultant predictive signature was then tested on an independent validation set comprised of 36 patients. RESULTS: A 93-gene signature referred to as the Chemotherapy Response Profile (CRP) was identified through its association with pathologic complete response. When applied to a separate validation set, the CRP distinguished between patients with unfavorable versus favorable overall survival (median 41 months v not yet reached, respectively, log-rank P = .007), with a median follow-up of 52 months. The signature maintained independent prognostic value in multivariate analysis, controlling for other known prognostic factors such as age, stage, grade, and debulking status. There was no genetic overlap between the CRP and our previously described Ovarian Cancer Prognostic Profile (OCPP), which demonstrated similar prognostic value. The combination of the CRP and OCPP yielded better prognostic discrimination then either profile alone. Genes present in the CRP include BAX, a proapoptotic protein previously associated with chemotherapy response in ovarian cancer. CONCLUSION: Identification of a gene expression profile based on pathologic response in EOC provides independent prognostic information and offers potential insights into the mechanism of drug resistance. Efforts to identify a more tailored profile using selected genes from both the CRP and OCPP are underway. keyword(s): Correlation with outcome
2011-08-12 | GSE31245 | GEO
Project description:Objective: Many patients with ovarian cancer disease relapse within 6 months after adjuvant chemotherapy, with a limited prognosis. Epigenetic modifications have been shown to play an important role in tumor development and formation. Therefore, global analysis of DNA methylation patterns might reveal specific CpG sites that correlate with progression-free interval (PFI) after therapy. Methods: Twenty samples of advanced ovarian cancer with a predominantly serous papillary histological subtype were subjected to DNA methylation profiling. Illumina HumanMethylation27 BeadChip technology was used for simultaneous analysis of 27,578 CpG sites in 114,000 genes. Results: Differential DNA methylation of various cytosines correlated with PFI. However, this becomes only significant by classification according to PFI with a cutoff of 128 months. Longer survival was associated with hypomethylation at specific CpG sites (e.g. GREB1, TGIF and TOB1) and hypermethylation in other genes (e.g. TMCO5, PTPRN and GUCY2C). Gene ontology analysis revealed that differentially methylated genes were significantly overrepresented in the categories telomere organization, mesoderm development and immune regulation. Conclusion: Epigenetic modifications at specific CpG sites correlate with PFI in ovarian cancer. Therefore, such analysis might be of prognostic value. Bisulphite converted DNA from the 20 samples were hybridised to the Illumina Infinium 27k Human Methylation Beadchip
2011-05-04 | E-GEOD-25033 | biostudies-arrayexpress
Project description:Ovarian cancer is the most lethal malignancy in the United States. While studies on ovarian cancer pathogenesis were mainly focused on the epithelial component of the tumor, understanding in the role of cancer associated fibroblasts (CAFs) in ovarian cancer progression is limited. In the present study, we describe the use of microdissected transcriptome profiles for the identification of cancer–stroma crosstalk networks with prognostic value, which presents a unique opportunity for developing new treatment strategies for ovarian cancer.
2018-10-22 | GSE115635 | GEO
Project description:To identify the gene signature accounting for the distinct clinical outcomes in ovarian clear cell cancer patients Clear cell ovarian cancer is an epithelial ovarian cancer histotype that is less responsive to chemotherapy and carries poorer prognosis than serous and endometrioid histotypes. Despite this, patients with these tumors are treated in a similar fashion as all other ovarian cancers. Previous genomic analysis has suggested that clear cell cancers represent a unique tumor subtype. Here we generated the first whole genomic expression profiling using epithelial component of clear cell ovarian cancers and normal ovarian surface specimens isolated by laser capture microdissection. Arrays analyzed using BRB ArrayTools and PathwayStudio software was used to identify the signaling pathways. Gene expression profiling was completed for 10 clear cell ovarian cancer specimens and 10 normal ovarian surface epithelium using the Affymetrix human U133 Plus 2.0 Arrays
2011-05-24 | E-GEOD-29450 | biostudies-arrayexpress
Project description:Integration of several ovarian cancer datasets to identify a reproducible predictors of survival Four microarray datasets from different institutions were reprocessed in a uniform manner, into a single training dataset. Survival analysis was performed and a validation cohort (61 patients from 3 institutions) was profiled using a custom array to confirm the prognostic value of the predictors. The four datasets were obtained from the following reports: Spentzos D, Levine DA, Ramoni MF, et al. Gene expression signature with independent prognostic significance in epithelial ovarian cancer. J Clin Oncol 2004;22:4700-10 Bild AH, Yao G, Chang JT, et al. Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature 2006;439:353-7 Marquez RT, Baggerly KA, Patterson AP, et al. Patterns of gene expression in different histotypes of epithelial ovarian cancer correlate with those in normal fallopian tube, endometrium, and colon. Clin Cancer Res 2005;11:6116-26 Zhang L, Volinia S, Bonome T, et al. Genomic and epigenetic alterations deregulate microRNA expression in human epithelial ovarian cancer. Proc Natl Acad Sci U S A 2008;105:7004-9 61 samples
2011-06-15 | E-GEOD-19161 | biostudies-arrayexpress
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:Cisplatin and carboplatin are the primary first-line therapies for the treatment of ovarian cancer. However, resistance to these platinum-based drugs occurs in the large majority of initially responsive tumors, subsequently resulting in a poor long-term prognosis. To model the onset of drug resistance, and investigate the DNA methylation alterations associated with cisplatin resistance, we treated clonally derived, drug-sensitive A2780 epithelial ovarian cancer cells with increasing concentrations of cisplatin. After several cycles of drug selection, the isogenic drug-sensitive and -resistant pairs were subjected to global CGI methylation microarray analyses. We treated clonally derived, drug-sensitive A2780 epithelial ovarian cancer cells with increasing concentrations of cisplatin. After several cycles of drug selection, the isogenic drug-sensitive and -resistant pairs were subjected to global CGI methylation analyses by differential methylation hybridization (DMH) using a customed 44K promoter CGI microarray.
2010-06-19 | E-GEOD-15373 | biostudies-arrayexpress