ArticleScientific reports2018
Pan-cancer analysis of somatic mutations and transcriptomes reveals common functional gene clusters shared by multiple cancer types.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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25 citing papers in PubMed, 44 citations in OpenAlex.
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- Therapeutic Targets for Gastric Cancer: Mendelian Randomization and Colocalization Analysis.Biological procedures online · 2025Article
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- A Novel IGLC2 Gene Linked With Prognosis of Triple-Negative Breast Cancer.Frontiers in oncology · 2021Article
- Integrated Analysis of Hub Genes and Pathways In Esophageal Carcinoma Based on NCBI's Gene Expression Omnibus (GEO) Database: A Bioinformatics Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2020Article
- Factorized embeddings learns rich and biologically meaningful embedding spaces using factorized tensor decomposition.Bioinformatics (Oxford, England) · 2020Article
- Variant morphology and random chromosomal integration of BK polyomavirus in posttransplant urothelial carcinomas.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2020Article
- PRODIGY: personalized prioritization of driver genes.Bioinformatics (Oxford, England) · 2020Article
- Impact of mutations in DNA methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancer.BMC medical genomics · 2020Article
- Depicting the genetic architecture of pediatric cancers through an integrative gene network approach.Scientific reports · 2020Article
- Pathogenic mutations and overall survival in 3,084 patients with cancer: the Hellenic Cooperative Oncology Group Precision Medicine Initiative.Oncotarget · 2020Article
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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
To discover functional gene clusters across cancers, we performed a systematic pan-cancer analysis of 33 cancer types. We identified genes that were associated with somatic mutations and were the cores of a co-expression network. We found that multiple cancer types have relatively exclusive hub genes individually; however, the hub genes cooperate with each other based on their functional relationship. When we built a protein-protein interaction network of hub genes and found nine functional gene clusters across cancer types, the gene clusters divided not only the region of the network map, but also the function of the network by their distinct roles related to the development and progression of cancer. This functional relationship between the clusters and cancers was underpinned by the high expression of module genes and enrichment of programmed cell death, and known candidate cancer genes. In addition to protein-coding hub genes, non-coding hub genes had a possible relationship with cancer. Overall, our approach of investigating cancer genes enabled finding pan-cancer hub genes and common functional gene clusters shared by multiple cancer types based on the expression status of the primary tumour and the functional relationship of genes in the biological network.
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