ArticleScientific reports2018
Explaining cancer type specific mutations with transcriptomic and epigenomic features in normal tissues.
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 9 papers.
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Who cites it
9 citing papers in PubMed, 18 citations in OpenAlex.
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- Detection and genomic analysis of BRAF fusions in Juvenile Pilocytic Astrocytoma through the combination and integration of multi-omic data.BMC cancer · 2022Article
- Blood-Derived Extracellular Vesicle-Associated miR-3182 Detects Non-Small Cell Lung Cancer Patients.Cancers · 2022Article
- Nanocarriers as a Tool for the Treatment of Colorectal Cancer.Pharmaceutics · 2021Review
- Non-coding driver mutations in human cancer.Nature reviews. Cancer · 2021Review
- A systems genomics approach to uncover the molecular properties of cancer genes.Scientific reports · 2020Article
- Human genes differ by their UV sensitivity estimated through analysis of UV-induced silent mutations in melanoma.Human mutation · 2020Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Most cancer driver genes are involved in generic cellular processes such as DNA repair, cell proliferation and cell adhesion, yet their mutations are often confined to specific cancer types. To resolve this paradox, we explained mutation frequencies of selected genes across tumor types with four features in the corresponding normal tissues from cancer-free subjects: mRNA expression and chromatin accessibility of mutated genes, mRNA expressions of their neighbors in curated pathways and the protein-protein interaction network. Encouragingly, these transcriptomic/epigenomic features in normal tissues were closely associated with mutational/functional characteristics in tumors. First, chromatin accessibility was a necessary but not sufficient condition for frequent mutations. Second, variations of mutation frequencies in selected genes across tissue types were significantly associated with all four features. Third, the genes possessing significant associations between mutation frequency variations and pathway gene expression were enriched with documented cancer genes. We further proposed a novel bivariate gene set enrichment analysis and confirmed that the pathway gene expression was the dominant factor in cancer gene enrichment. These findings shed lights on the functional roles of genes in normal tissues in shaping the mutational landscape during tumor genome evolution.
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