ArticleBritish journal of cancer2011
A seven-gene prognostic model for platinum-treated ovarian carcinomas.
Article in British journal of cancer, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 4 of them syntheses that pooled it.
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Who cites it
24 citing papers in PubMed, 4 syntheses or guidelines pooled it, 44 citations in OpenAlex.
- Pooled it
- Pooled it
- Risk prediction for late-stage ovarian cancer by meta-analysis of 1525 patient samples.Journal of the National Cancer Institute · 2014Pooled it
- Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer.Journal of the National Cancer Institute · 2014Pooled it
- Deciphering Folate Receptor alphaGene Expression and mRNA Signatures in Ovarian Cancer: Implications for Precision Therapies.International journal of molecular sciences · 2024Article
- Glutamine metabolism prognostic index predicts tumour microenvironment characteristics and therapeutic efficacy in ovarian cancer.Journal of cellular and molecular medicine · 2024Article
- Epigenetically programmed resistance to chemo- and immuno-therapies.Advances in cancer research · 2023Article
- Establishment and validation of a novel invasion-related gene signature for predicting the prognosis of ovarian cancer.Cancer cell international · 2022Article
- Identification of a Novel Tumor Microenvironment Prognostic Signature for Advanced-Stage Serous Ovarian Cancer.Cancers · 2021Article
- Differential gene expression identifies a transcriptional regulatory network involving ER-alpha and PITX1 in invasive epithelial ovarian cancer.BMC cancer · 2021Article
- Identification and Development of Subtypes With Poor Prognosis in Pan-Gynecological Cancer Based on Gene Expression in the Glycolysis-Cholesterol Synthesis Axis.Frontiers in oncology · 2021Article
- Development and validation of prognostic gene signature for basal-like breast cancer and high-grade serous ovarian cancer.Breast cancer research and treatment · 2020Article
- Development and Validation of a Novel 11-Gene Prognostic Model for Serous Ovarian Carcinomas Based on Lipid Metabolism Expression Profile.International journal of molecular sciences · 2020Article
- The identification of nuclear αvβ3 integrin in ovarian cancer: non-paradigmal localization with cancer promoting actions.Oncogenesis · 2020Article
- Clinical Interest of Combining Transcriptomic and Genomic Signatures in High-Grade Serous Ovarian Cancer.Frontiers in genetics · 2020Article
- Large-scale integrated analysis of ovarian cancer tumors and cell lines identifies an individualized gene expression signature for predicting response to platinum-based chemotherapy.Cell death & disease · 2019Article
- Novel Model for Comprehensive Assessment of Robust Prognostic Gene Signature in Ovarian Cancer Across Different Independent Datasets.Frontiers in genetics · 2019Article
- The rise of genomic profiling in ovarian cancer.Expert review of molecular diagnostics · 2016Review
- Identification of Cathepsin K in the Peritoneal Metastasis of Ovarian Carcinoma Using In-silico, Gene Expression Analysis.Journal of Cancer · 2016Article
- Risk prediction model for epithelial ovarian cancer using molecular markers and clinical characteristics.Journal of ovarian research · 2015Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPrognosis of ovarian carcinoma is poor, heterogeneous, and not accurately predicted by histoclinical features. We analysed gene expression profiles of ovarian carcinomas to identify a multigene expression model associated with survival after platinum-based therapy.
methodsData from 401 ovarian carcinoma samples were analysed. The learning set included 35 cases profiled using whole-genome DNA chips. The validation set included 366 cases from five independent public data sets.
resultsWhole-genome unsupervised analysis could not distinguish poor from good prognosis samples. By supervised analysis, we built a seven-gene optimal prognostic model (OPM) out of 94 genes identified as associated with progression-free survival. Using the OPM, we could classify patients in two groups with different overall survival (OS) not only in the learning set, but also in the validation set. Five-year OS was 57 and 27% for the predicted 'Favourable' and 'Unfavourable' classes, respectively. In multivariate analysis, the OPM outperformed the individual current prognostic factors, both in the learning and the validation sets, and added independent prognostic information.
conclusionWe defined a seven-gene model associated with outcome in 401 ovarian carcinomas. Prospective studies are warranted to confirm its prognostic value, and explore its potential ability for better tailoring systemic therapies in advanced-stage tumours.
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