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Background: As a major subtype of ovarian cancer, high grade FIGO stage IIIc serous ovarian carcinoma (HG3cSOC), has various prognosis due to genetic heterogeneity. Methods: The transcriptome of 401 primary FIGO IIIc serous ovarian samples was screened, seven genes based prognostic model was developed. The prognostic valueof risk score in four different cohorts (TCGA-cohort, Poland-cohort, Japan-cohort and USA-cohort) was validated. The relationship between risk score and other clinical indicators were analyzed. The guide value of risk score for platinum-taxol chemotherapy was also assayed. Tissue microenvironment difference among samples with different risk scores was investigated. Results: High-risk group (N=200, median survival months: 39.6, 95% CI: 35.9-46.3 months) had a significantly worse prognosis than low-risk group (N=201, median survival months: 52.6, 95% CI: 45.2-64.9 months;). The risk score's performance was validated in Japan-cohort (N=90, Poland-cohort (N=48) and USA-cohort (N=84). The risk score is independent from age, primary tumor size, grade and treatment methods and the performance of risk score is uniform in subgroups. Furthermore, the risk score predicted the response of HG3cSOC to platinum-based regimen after surgery, and this finding was further validated in newly collected China-cohort (N=102). Gene Set Enrichment Analysis (GSEA) and tumor infiltration analysis revealed that risk score reflected the immune infiltration and cell-cell interaction status, and the migration function of candidate genes were also verified. Conclusions: The optimized seven genes-based model is a valuable and robust model in predicting the survival of HG3cSOC, and served as a valuable marker for the response to platinum-based chemotherapy.
Pubmed ID: 30585265
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International functional genomics data collection generated from microarray or next-generation sequencing (NGS) platforms. Repository of functional genomics data supporting publications. Provides genes expression data for reuse to the research community where they can be queried and downloaded. Integrated with the Gene Expression Atlas and the sequence databases at the European Bioinformatics Institute. Contains a subset of curated and re-annotated Archive data which can be queried for individual gene expression under different biological conditions across experiments. Data collected to MIAME and MINSEQE standards. Data are submitted by users or are imported directly from the NCBI Gene Expression Omnibus.
View all literature mentionsSoftware package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.
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View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
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