ArticleScientific reports2017
Differential co-expression analysis reveals a novel prognostic gene module 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 29 papers, 3 of them syntheses that pooled it.
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Who cites it
29 citing papers in PubMed, 3 syntheses or guidelines pooled it, 72 citations in OpenAlex.
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- Network medicine approaches for identification of novel prognostic systems biomarkers and drug candidates for papillary thyroid carcinoma.Journal of cellular and molecular medicine · 2023Pooled it
- Updating genome annotation for the microbial cell factory Aspergillus niger using gene co-expression networks.Nucleic acids research · 2019Pooled it
- Differential co-expression network analysis elucidated genes associated with sensitivity to farnesyltransferase inhibitor and prognosis of acute myeloid leukemia.Cancer medicine · 2023Article
- Inference of differential key regulatory networks and mechanistic drug repurposing candidates from scRNA-seq data with SCANet.Bioinformatics (Oxford, England) · 2023Article
- Expression Profile and Gene Regulation Network of NUSAP1 in Pan Cancers Based on Integrated Bioinformatics Analysis.International journal of general medicine · 2023Article
- RCFGL: Rapid Condition adaptive Fused Graphical Lasso and application to modeling brain region co-expression networks.PLoS computational biology · 2023Article
- Comparative Analysis of Gene Correlation Networks of Breast Cancer Patients Based on Mutations in TP53.Biomolecules · 2022Article
- Identifying network biomarkers of cancer by sample-specific differential network.BMC bioinformatics · 2022Article
- Identification of potential autophagy-related genes in steroid-induced osteonecrosis of the femoral head via bioinformatics analysis and experimental verification.Journal of orthopaedic surgery and research · 2022Article
- Re-wiring and gene expression changes of AC025034.1 and ATP2B1 play complex roles in early-to-late breast cancer progression.BMC genomic data · 2022Article
- Gene co-expression network analysis revealed novel biomarkers for ovarian cancer.Frontiers in genetics · 2022Article
- GWENA: gene co-expression networks analysis and extended modules characterization in a single Bioconductor package.BMC bioinformatics · 2021Article
- Deciphering microRNA-mRNA regulatory network in adult T-cell leukemia/lymphoma; the battle between oncogenes and anti-oncogenes.PloS one · 2021Article
- Differential Interactome Based Drug Repositioning Unraveled Abacavir, Exemestane, Nortriptyline Hydrochloride, and Tolcapone as Potential Therapeutics for Colorectal Cancers.Frontiers in bioinformatics · 2021Article
- Development of cancer prognostic signature based on pan-cancer proteomics.Bioengineered · 2020Article
- Article
- Finding disease modules for cancer and COVID-19 in gene co-expression networks with the Core&Peel method.Scientific reports · 2020Article
- Constructing cancer patient-specific and group-specific gene networks with multi-omics data.BMC medical genomics · 2020Article
- Systemic lipid dysregulation is a risk factor for macular neurodegenerative disease.Scientific reports · 2020Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer is one of the most significant disease among gynecological disorders that women suffered from over the centuries. However, disease-specific and effective biomarkers were still not available, since studies have focused on individual genes associated with ovarian cancer, ignoring the interactions and associations among the gene products. Here, ovarian cancer differential co-expression networks were reconstructed via meta-analysis of gene expression data and co-expressed gene modules were identified in epithelial cells from ovarian tumor and healthy ovarian surface epithelial samples to propose ovarian cancer associated genes and their interactions. We propose a novel, highly interconnected, differentially co-expressed, and co-regulated gene module in ovarian cancer consisting of 84 prognostic genes. Furthermore, the specificity of the module to ovarian cancer was shown through analyses of datasets in nine other cancers. These observations underscore the importance of transcriptome based systems biomarkers research in deciphering the elusive pathophysiology of ovarian cancer, and here, we present reciprocal interplay between candidate ovarian cancer genes and their transcriptional regulatory dynamics. The corresponding gene module might provide new insights on ovarian cancer prognosis and treatment strategies that continue to place a significant burden on global health.
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