ArticleScientific reports2017
Driver pattern identification over the gene co-expression of drug response in ovarian cancer by integrating high throughput genomics data.
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 16 papers.
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Who cites it
16 citing papers in PubMed, 29 citations in OpenAlex.
- Pathology and Therapeutic Significance of Fibroblast Growth Factors.Targets (Basel) · 2025Article
- GNA15 predicts poor outcomes as a novel biomarker related to M2 macrophage infiltration in ovarian cancer.Frontiers in immunology · 2025Article
- Decoding FGF/FGFR Signaling: Insights into Biological Functions and Disease Relevance.Biomolecules · 2024Review
- Comprehensive in silico analysis of prognostic and immune infiltrates for FGFs in human ovarian cancer.Journal of ovarian research · 2024Article
- Histaminergic System and Inflammation-Related Genes in Normal Large Intestine andInternational journal of molecular sciences · 2023Article
- A novel method to identify gene interaction patterns.BMC genomics · 2021Article
- Identification of Potential Bisphenol A (BPA) Exposure Biomarkers in Ovarian Cancer.Journal of clinical medicine · 2021Article
- Downregulation of GNA15 Inhibits Cell ProliferationFrontiers in oncology · 2021Article
- GADD45B Facilitates Metastasis of Ovarian Cancer Through Epithelial-Mesenchymal Transition.OncoTargets and therapy · 2021Article
- CCL23 in Balancing the Act of Endoplasmic Reticulum Stress and Antitumor Immunity in Hepatocellular Carcinoma.Frontiers in oncology · 2021Review
- Integrated WGCNA and PPI Network to Screen Hub Genes Signatures for Infantile Hemangioma.Frontiers in genetics · 2020Article
- Identification of prognostic markers of lung cancer through bioinformatics analysis and in vitro experiments.International journal of oncology · 2020Article
- TNF-α Differentially Regulates Cell Cycle Genes in Promyelocytic and Granulocytic HL-60/S4 Cells.G3 (Bethesda, Md.) · 2019Article
- Integrated Analysis of Transcriptome and Prognosis Data Identifies FGF22 as a Prognostic Marker of Lung Adenocarcinoma.Technology in cancer research & treatment · 2019Article
- Identification of gene signatures from RNA-seq data using Pareto-optimal cluster algorithm.BMC systems biology · 2018Article
- The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes.Molecules (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multiple types of high throughput genomics data create a potential opportunity to identify driver patterns in ovarian cancer, which will acquire some novel and clinical biomarkers for appropriate diagnosis and treatment to cancer patients. To identify candidate driver genes and the corresponding driving patterns for resistant and sensitive tumors from the heterogeneous data, we combined gene co-expression modules with mutation modulators and proposed the method to identify driver patterns. Firstly, co-expression network analysis is applied to explore gene modules for gene expression profiles through weighted correlation network analysis (WGCNA). Secondly, mutation matrix is generated by integrating the CNV data and somatic mutation data, and a mutation network is constructed from the mutation matrix. Thirdly, candidate modulators are selected from significant genes by clustering vertexs of the mutation network. Finally, a regression tree model is utilized for module network learning, in which the obtained gene modules and candidate modulators are trained for the driving pattern identification and modulators regulatory exploration. Many identified candidate modulators are known to be involved in biological meaningful processes associated with ovarian cancer, such as CCL11, CCL16, CCL18, CCL23, CCL8, CCL5, APOB, BRCA1, SLC18A1, FGF22, GADD45B, GNA15, GNA11, and so on.
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