SynthesisScientific reports2016
A VEGF-dependent gene signature enriched in mesenchymal ovarian cancer predicts patient prognosis.
Synthesis in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 20 citations in OpenAlex.
- Detecting vascular normalization in epithelial ovarian cancer.Medical oncology (Northwood, London, England) · 2025Review
- Histopathological subtyping of high-grade serous ovarian cancer using whole slide imaging.Journal of gynecologic oncology · 2023Article
- Circulating Angiogenic Markers in Gastroenteropancreatic Neuroendocrine Neoplasms: A Systematic Review.Current issues in molecular biology · 2022Review
- Identification ofOncology letters · 2021Article
- Antiangiogenesis Efficacy of Ethanol Extract fromEvidence-based complementary and alternative medicine : eCAM · 2020Article
- Research Progresses in Cancer Stem Cells of Three Common Fertility-Related Female Malignancies.Pathology oncology research : POR · 2019Review
- Article
- Vascular endothelial growth factor receptor 2 (VEGFR2) correlates with long-term survival in patients with advanced high-grade serous ovarian cancer (HGSOC): a study from the Tumor Bank Ovarian Cancer (TOC) Consortium.Journal of cancer research and clinical oncology · 2019Article
- Characterisation of tumour microvessel density during progression of high-grade serous ovarian cancer: clinico-pathological impact (an OCTIPS Consortium study).British journal of cancer · 2018Article
- FSH receptor binding inhibitor impacts K-Ras and c-Myc of ovarian cancer and signal pathway.Oncotarget · 2018Article
- Recommendations for biomarker testing in epithelial ovarian cancer: a National Consensus Statement by the Spanish Society of Pathology and the Spanish Society of Medical Oncology.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2018Article
- The Prognostic 97 Chemoresponse Gene Signature in Ovarian Cancer.Scientific reports · 2017Article
- Identification of Pharmacologically Tractable Protein Complexes in Cancer Using the R-Based Network Clustering and Visualization Program MCODER.BioMed research international · 2017Article
Corrections and comments
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Authors and funding
13 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We have previously reported surrogate biomarkers of VEGF pathway activities with the potential to provide predictive information for anti-VEGF therapies. The aim of this study was to systematically evaluate a new VEGF-dependent gene signature (VDGs) in relation to molecular subtypes of ovarian cancer and patient prognosis. Using microarray profiling and cross-species analysis, we identified 140-gene mouse VDGs and corresponding 139-gene human VDGs, which displayed enrichment of vasculature and basement membrane genes. In patients who received bevacizumab therapy and showed partial response, the expressions of VDGs (summarized to yield VDGs scores) were markedly decreased in post-treatment biopsies compared with pre-treatment baselines. In contrast, VDGs scores were not significantly altered following bevacizumab treatment in patients with stable or progressive disease. Analysis of VDGs in ovarian cancer showed that VDGs as a prognostic signature was able to predict patient outcome. Correlation estimation of VDGs scores and molecular features revealed that VDGs was overrepresented in mesenchymal subtype and BRCA mutation carriers. These findings highlighted the prognostic role of VEGF-mediated angiogenesis in ovarian cancer, and proposed a VEGF-dependent gene signature as a molecular basis for developing novel diagnostic strategies to aid patient selection for VEGF-targeted agents.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.