Transcriptome analysis the early and advanced stage of ovarian cancer
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ABSTRACT:
PROVIDER: PRJNA675113 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13001255_1.fastq.gz | Fastqsanger.gz | |||
| SRR13001255_2.fastq.gz | Fastqsanger.gz | |||
| SRR13001256_1.fastq.gz | Fastqsanger.gz | |||
| SRR13001256_2.fastq.gz | Fastqsanger.gz | |||
| SRR13001257_1.fastq.gz | Fastqsanger.gz |
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Project description:We aim to explore the common gene between proteomics and transcriptomics and pathway mechanism related to layer classification. Our results will provide several potential biomarkers in early diagnosis of ovarian cancer.Transcriptomics methods were performed to compare the differences between early ovarian cancer specimens (n = 3, stage Ⅰ / Ⅱ) and advanced ovarian cancer specimens (n = 6, stage Ⅲ / Ⅳ), and the similarities and differences of the data obtained were analyzed.
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Project description:BACKGROUND: Because of the distinct clinical presentation of early and advanced stage ovarian cancer, we aim to clarify whether these disease entities are solely separated by time of diagnosis or whether they arise from distinct molecular events. METHODS: Sixteen early and sixteen advanced stage ovarian carcinomas, matched for histological subtype and differentiation grade, were included. Genomic aberrations were compared for each early and advanced stage ovarian cancer by array comparative genomic hybridization. To study how the aberrations correlate to the clinical characteristics of the tumors we clustered tumors based on the genomic aberrations. RESULTS: The genomic aberration patterns in advanced stage cancer equalled those in early stage, but were more frequent in advanced stage (p?=?0.012). Unsupervised clustering based on genomic aberrations yielded two clusters that significantly discriminated early from advanced stage (p?=?0.001), and that did differ significantly in survival (p?=?0.002). These clusters however did give a more accurate prognosis than histological subtype or differentiation grade. CONCLUSION: This study indicates that advanced stage ovarian cancer either progresses from early stage or from a common precursor lesion but that they do not arise from distinct carcinogenic molecular events. Furthermore, we show that array comparative genomic hybridization has the potential to identify clinically distinct patients. Sixteen early and sixteen advanced stage ovarian carcinomas
2012-08-22 | E-GEOD-24418 | biostudies-arrayexpress
Project description:BACKGROUND: Because of the distinct clinical presentation of early and advanced stage ovarian cancer, we aim to clarify whether these disease entities are solely separated by time of diagnosis or whether they arise from distinct molecular events. METHODS: Sixteen early and sixteen advanced stage ovarian carcinomas, matched for histological subtype and differentiation grade, were included. Genomic aberrations were compared for each early and advanced stage ovarian cancer by array comparative genomic hybridization. To study how the aberrations correlate to the clinical characteristics of the tumors we clustered tumors based on the genomic aberrations. RESULTS: The genomic aberration patterns in advanced stage cancer equalled those in early stage, but were more frequent in advanced stage (p = 0.012). Unsupervised clustering based on genomic aberrations yielded two clusters that significantly discriminated early from advanced stage (p = 0.001), and that did differ significantly in survival (p = 0.002). These clusters however did give a more accurate prognosis than histological subtype or differentiation grade. CONCLUSION: This study indicates that advanced stage ovarian cancer either progresses from early stage or from a common precursor lesion but that they do not arise from distinct carcinogenic molecular events. Furthermore, we show that array comparative genomic hybridization has the potential to identify clinically distinct patients.
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Project description:A set of 45 surgical specimens has been profiled for miRNA expression to validate miRNA alterations associated to early relapse in advanced stage ovarian cancer patients.
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Project description:A set of 45 surgical specimens has been profiled for miRNA expression to validate miRNA alterations associated to early relapse in advanced stage ovarian cancer patients. Fresh frozen samples were collected from a series of consecutive patients with high-grade advanced stage ovarian cancer who underwent primary surgery at INT-Milan. After surgery all patients received postoperative platinum-based chemotherapy. All patients signed an Institutional Review Board approved consent for bio-banking, clinical data collection and molecular analysis. Clinical codes: Histotype: according to WHO classification guidelines Stage: according to International Federation of Gynecological and Obstetrics (FIGO) guidelines Grading: according to WHO classification guidelines Debulking: NED: not evident disease; mRD: minimal residual disease; GRD: gross residual disease Therapy code: P: Platinum without taxanes; PT: Platinum/paclitaxel
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Project description:This SuperSeries is composed of the following subset Series: GSE25202: microRNA alterations associated to clinical response in advanced stage ovarian cancer patients (training set). GSE25203: microRNA alterations associated to clinical response in advanced stage ovarian cancer patients (test set). Refer to individual Series
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Project description:To identify the potential ovarian cancer stem cell gene expression profile from isolated side population of fresh ascites obtained from women with high-grade advanced stage papillary serous ovarian adenocarcinoma Microarrays were used to interrogate the differentially expressed genes between side population (SP) and main population (MP) isolated from fresh ascites obtained from women with high-grade advanced stage papillary serous ovarian adenocarcinoma, and the results were analyzed by paired T-test using BRB-ArrayTools Gene expression profiling was completed for 10 SP and MP pairs using the Affymetrix human U133 Plus 2.0 Arrays
2011-11-23 | E-GEOD-33874 | biostudies-arrayexpress
Project description:To identify and evaluate the prognostic ability of progression-free survival-related profile for advanced-stage ovarian cancer, advanced-stage serous ovarian cancer tissues from 110 patients who received primary surgery and a platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays of more than 40,000 transcripts. We first selected 88 genes by a univariate Cox proportional hazard analysis (p<0.01) and next optimized regression coefficients by ridge regression model using 10-fold cross-validation. The prognostic index was independently associated with PFS time compared to other clinical factors in multivariate analysis [hazard ratio (HR), 3.72; 95% confidence interval (CI), 2.66–5.43; p,0.0001]. In an external dataset, multivariate analysis revealed that this prognostic index was significantly correlated with PFS time (HR, 1.54; 95% CI, 1.20–1.98; p = 0.0008). Furthermore, the correlation between the prognostic index and overall survival time was confirmed in the two independent external datasets (log rank test, p = 0.0010 and 0.0008). In multivariable analysis, our prognostic index was independently associated with progression-free survival times compared to other clinical factors (p<0.001). Furthermore, the prognostic ability of our prognostic index was validated in external, publicly available dataset (n = 87), and was proved in multivariate analysis (p = 0.0032). These results suggest that disease progression or recurrence of advanced-stage serous ovarian cancer can be predicted by gene expression profile. The prognostic ability of our index based on the 88-gene expression profile in ridge regression Cox hazard model was shown to be independent of other clinical factors in predicting cancer prognosis across two distinct datasets. Further study will be necessary to improve predictive accuracy of the prognostic index toward clinical application for evaluation of the risk of recurrence in patients with advanced-stage serous ovarian cancer.
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