ArticleClinical cancer research : an official journal of the American Association for Cancer Research2020
Dilution of Molecular-Pathologic Gene Signatures by Medically Associated Factors Might Prevent Prediction of Resection Status After Debulking Surgery in Patients With Advanced Ovarian Cancer.
Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 17 citations in OpenAlex.
- A pioneering artificial intelligence tool to predict treatment outcomes in ovarian cancer via diagnostic laparoscopy.Scientific reports · 2025Article
- Prediction of response to promising first-line chemotherapy in ovarian cancer patients with residual peritoneal tumors: practical biomarkers and robust multiplex models.International journal of clinical oncology · 2024Article
- Genome-wide association analyses of ovarian cancer patients undergoing primary debulking surgery identify candidate genes for residual disease.NPJ genomic medicine · 2024Article
- Molecular and phenotypic characteristics influencing the degree of cytoreduction in high-grade serous ovarian carcinomas.Cancer medicine · 2023Article
- Spatial and temporal intra-tumoral heterogeneity in advanced HGSOC: Implications for surgical and clinical outcomes.Cell reports. Medicine · 2023Article
- Predictors of residual disease after debulking surgery in advanced stage ovarian cancer.Frontiers in oncology · 2023Article
- Integrated Clinical and Genomic Models to Predict Optimal Cytoreduction in High-Grade Serous Ovarian Cancer.Cancers · 2022Article
- Chondroitin Sulfate Disaccharides, a Serum Marker for Primary Serous Epithelial Ovarian Cancer.Diagnostics (Basel, Switzerland) · 2021Article
- Clinical Phenotypes of Tumors Invading the Rectosigmoid Colon Affecting the Extent of Debulking Surgery and Survival in Advanced Ovarian Cancer.Frontiers in oncology · 2021Article
- A Solution to the Dilution: The Role for Biomarkers in Advanced Ovarian Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2020Article
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27 authors at 14 institutions in 4 countries.
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Abstract
purposePredicting surgical outcome could improve individualizing treatment strategies for patients with advanced ovarian cancer. It has been suggested earlier that gene expression signatures (GES) might harbor the potential to predict surgical outcome. EXPERIMENTAL
designData derived from high-grade serous tumor tissue of FIGO stage IIIC/IV patients of AGO-OVAR11 trial were used to generate a transcriptome profiling. Previously identified molecular signatures were tested. A theoretical model was implemented to evaluate the impact of medically associated factors for residual disease (RD) on the performance of GES that predicts RD status.
resultsA total of 266 patients met inclusion criteria, of those, 39.1% underwent complete resection. Previously reported GES did not predict RD in this cohort. Similarly, The Cancer Genome Atlas molecular subtypes, an independent
conclusionsPreviously identified GES cannot be generalized. Medically associated factors for RD may be the main obstacle to predict surgical outcome in an all-comer population of patients with advanced ovarian cancer. If biomarkers derived from tumor tissue are used to predict outcome of patients with cancer, selection bias should be focused on to prevent overestimation of the power of such a biomarker.
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