ArticleScientific reports2017
The Prognostic 97 Chemoresponse Gene Signature in Ovarian Cancer.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 33 citations in OpenAlex.
- Gene expression profile association with poor prognosis in epithelial ovarian cancer patients.Scientific reports · 2021Trial
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- Residual ANTXR1+ myofibroblasts after chemotherapy inhibit anti-tumor immunity via YAP1 signaling pathway.Nature communications · 2024Article
- A prognostic model for ovarian neoplasms established by an integrated analysis of 1580 transcriptomic profiles.Scientific reports · 2023Article
- Molecular Management of High-Grade Serous Ovarian Carcinoma.International journal of molecular sciences · 2022Review
- Bioinformatics: From NGS Data to Biological Complexity in Variant Detection and Oncological Clinical Practice.Biomedicines · 2022Review
- Review
- Stiffness increases with myofibroblast content and collagen density in mesenchymal high grade serous ovarian cancer.Scientific reports · 2021Article
- Article
- Article
- Extracellular Vesicle Molecular Signatures Characterize Metastatic Dynamicity in Ovarian Cancer.Frontiers in oncology · 2021Article
- 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
- Gene Expression Indicates Altered Immune Modulation and Signaling Pathway Activation in Ovarian Cancer Patients Resistant to Topotecan.International journal of molecular sciences · 2019Article
- Comparative genomic analysis of collagen gene diversity.3 Biotech · 2019Article
- High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints.International journal of molecular sciences · 2019Review
- Cluster analysis on high dimensional RNA-seq data with applications to cancer research - An evaluation study.PloS one · 2019Article
- RAD-ical New Insights into RAD51 Regulation.Genes · 2018Review
- Imaging Mass Spectrometry Reveals Crosstalk between the Fallopian Tube and the Ovary that Drives Primary Metastasis of Ovarian Cancer.ACS central science · 2018Article
- Ovarian Cancers: Genetic Abnormalities, Tumor Heterogeneity and Progression, Clonal Evolution and Cancer Stem Cells.Medicines (Basel, Switzerland) · 2018Review
- The Progression and Prospects of the Gene Expression Profiling in Ovarian Epithelial Cancer.Gynecology and minimally invasive therapyReview
Corrections and comments
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Authors and funding
14 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patient diagnosis and care would be significantly improved by understanding the mechanisms underlying platinum and taxane resistance in ovarian cancer. Here, we aim to establish a gene signature that can identify molecular pathways/transcription factors involved in ovarian cancer progression, poor clinical outcome, and chemotherapy resistance. To validate the robustness of the gene signature, a meta-analysis approach was applied to 1,020 patients from 7 datasets. A 97-gene signature was identified as an independent predictor of patient survival in association with other clinicopathological factors in univariate [hazard ratio (HR): 3.0, 95% Confidence Interval (CI) 1.66-5.44, p = 2.7E-4] and multivariate [HR: 2.88, 95% CI 1.57-5.2, p = 0.001] analyses. Subset analyses demonstrated that the signature could predict patients who would attain complete or partial remission or no-response to first-line chemotherapy. Pathway analyses revealed that the signature was regulated by HIF1α and TP53 and included nine HIF1α-regulated genes, which were highly expressed in non-responders and partial remission patients than in complete remission patients. We present the 97-gene signature as an accurate prognostic predictor of overall survival and chemoresponse. Our signature also provides information on potential candidate target genes for future treatment efforts in ovarian cancer.
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