SynthesisJournal of the National Cancer Institute2014
Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer.
Abstract readComparative StudyMeta-AnalysisSystematic Review
In one paragraph
Synthesis in Journal of the National Cancer Institute, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers, 7 of them syntheses that pooled it.
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75citing papers in PubMed, 7 pooled it
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What it found
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Who cites it
75 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Integration of single-cell and bulk RNA-sequencing data reveals the prognostic potential of epithelial gene markers for prostate cancer.Molecular oncology · 2025Pooled it
- The Impact of Stroma Admixture on Molecular Subtypes and Prognostic Gene Signatures in Serous Ovarian Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Pooled it
- Pooled it
- MARCKS contributes to stromal cancer-associated fibroblast activation and facilitates ovarian cancer metastasis.Oncotarget · 2016Pooled it
- Pooled it
- E2F4 Program Is Predictive of Progression and Intravesical Immunotherapy Efficacy in Bladder Cancer.Molecular cancer research : MCR · 2015Pooled it
- Risk prediction for late-stage ovarian cancer by meta-analysis of 1525 patient samples.Journal of the National Cancer Institute · 2014Pooled it
- Gene expression profile association with poor prognosis in epithelial ovarian cancer patients.Scientific reports · 2021Trial
- A tumor profiling resource for ovarian cancer: insights into chemotherapy-driven heterogeneity and personalized treatment strategy.Nature communications · 2026Article
- Adenosine Pathway-Based Prognostic Signature for Predicting Clinical Outcomes and Immune Microenvironment Characteristics in Epithelial Ovarian Cancer.Journal of clinical practice and research · 2026Article
- Telomerase-Associated Genes as Prognostic Markers in High-Grade Serous Ovarian Cancer.Medical science monitor : international medical journal of experimental and clinical research · 2026Article
- Transcriptomic subtypes in high-grade serous ovarian cancer are driven by tumor cellular composition.bioRxiv : the preprint server for biology · 2026Article
- Revisiting Genomic Instability, Tumor Microenvironment and Immune Response in High-Grade Serous Ovarian Cancer.Geburtshilfe und Frauenheilkunde · 2025Article
- Predictive modeling for metastasis in oncology: current methods and future directions.Annals of medicine and surgery (2012) · 2025Review
- The impact of the COVID-19 pandemic on the diagnosis, treatment, and prognosis of ovarian cancer in the United States: a retrospective cohort study based on the SEER database.Discover oncology · 2025Article
- Efficient Computation of High-Dimensional Penalized Piecewise Constant Hazard Random Effects Models.Statistics in medicine · 2025Article
- A comparative analysis of gene expression profiling by statistical and machine learning approaches.Bioinformatics advances · 2025Article
- Gene signatures for cancer research: A 25-year retrospective and future avenues.PLoS computational biology · 2024Article
- Urinary-based detection of MSL, HE4 and CA125 as an additional dimension for predictive and prognostic modelling in ovarian cancer.Frontiers in oncology · 2024Article
- Personalization of Therapy in High-Grade Serous Tubo-Ovarian Cancer-The Possibility or the Necessity?Journal of personalized medicine · 2023Review
15 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
14 authors.
Levi WaldronAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB).
Benjamin Haibe-KainsAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB).
Aedín C CulhaneAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB).
Markus RiesterAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB).
Jie DingAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB).
Xin Victoria WangAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB).
Mahnaz AhmadifarAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB).
Svitlana TyekuchevaAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB).
Christoph BernauAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB).
Thomas RischAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB).
Benjamin Frederick GanzfriedAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB).
Curtis HuttenhowerAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB).
Michael BirrerAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB).
Giovanni ParmigianiAffiliations of authors: City University of New York School of Public Health, Hunter College, New York, NY (LW); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA (LW, AC, MR, JD, XVW, ST, TR, BG, GP); Department of Biostatistics, Harvard School of Public Health, Boston, MA (LW, AC, CH, GP); Center for Cancer Research, Massachusetts General Hospital, Boston, MA (MB); Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada (BH); Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada (BH);Institute for Medical Information Sciences, Biometry, and Epidemiology, LMU Munich, Munich, Germany (CB). gp@jimmy.harvard.edu.
Funding
VectorP30CA006516 · NCI · DANA-FARBER CANCER INSTITUTE · PI JENNIFER W MACK · 1985 to 2026
$330.6MGenomic Stratification of Ovarian Cancer PatientsRC4CA156551 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI BIRRER, MICHAEL · 2010 to 2010
$3.7MNCI NIH HHS 1RC4CA156551-01NCI NIH HHS 5P30 CA006516-46NCI NIH HHS P30 CA006516NCI NIH HHS RC4 CA156551
Abstract
backgroundOvarian cancer is the fifth most common cause of cancer deaths in women in the United States. Numerous gene signatures of patient prognosis have been proposed, but diverse data and methods make these difficult to compare or use in a clinically meaningful way. We sought to identify successful published prognostic gene signatures through systematic validation using public data.
methodsA systematic review identified 14 prognostic models for late-stage ovarian cancer. For each, we evaluated its 1) reimplementation as described by the original study, 2) performance for prognosis of overall survival in independent data, and 3) performance compared with random gene signatures. We compared and ranked models by validation in 10 published datasets comprising 1251 primarily high-grade, late-stage serous ovarian cancer patients. All tests of statistical significance were two-sided.
resultsTwelve published models had 95% confidence intervals of the C-index that did not include the null value of 0.5; eight outperformed 97.5% of signatures including the same number of randomly selected genes and trained on the same data. The four top-ranked models achieved overall validation C-indices of 0.56 to 0.60 and shared anticorrelation with expression of immune response pathways. Most models demonstrated lower accuracy in new datasets than in validation sets presented in their publication.
conclusionsThis analysis provides definitive support for a handful of prognostic models but also confirms that these require improvement to be of clinical value. This work addresses outstanding controversies in the ovarian cancer literature and provides a reproducible framework for meta-analytic evaluation of gene signatures.
Indexed as
FemaleHumansNeoplasm StagingOvarian NeoplasmsPrognosisTranscriptome
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