ArticleScientific reports2019
A CATH domain functional family based approach to identify putative cancer driver genes and driver mutations.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 23 citations in OpenAlex.
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- Eph receptors and ephrins in cancer progression.Nature reviews. Cancer · 2024Review
- ZNF714 Supports Pro-Oncogenic Features in Lung Cancer Cells.International journal of molecular sciences · 2023Article
- A New View of Activating Mutations in Cancer.Cancer research · 2022Article
- Characterizing and explaining the impact of disease-associated mutations in proteins without known structures or structural homologs.Briefings in bioinformatics · 2022Article
- Exploiting protein family and protein network data to identify novel drug targets for bladder cancer.Oncotarget · 2022Article
- Pathogenic missense protein variants affect different functional pathways and proteomic features than healthy population variants.PLoS biology · 2021Article
- Biological impact of mutually exclusive exon switching.PLoS computational biology · 2021Article
- CATH: increased structural coverage of functional space.Nucleic acids research · 2021Article
- Representative cancer-associated U2AF2 mutations alter RNA interactions and splicing.The Journal of biological chemistry · 2020Article
- Understanding oncogenicity of cancer driver genes and mutations in the cancer genomics era.FEBS letters · 2020Review
- PDBe-KB: a community-driven resource for structural and functional annotations.Nucleic acids research · 2020Article
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Authors and funding
5 authors at 1 institution in 2 countries.
Funding
Abstract
Tumour sequencing identifies highly recurrent point mutations in cancer driver genes, but rare functional mutations are hard to distinguish from large numbers of passengers. We developed a novel computational platform applying a multi-modal approach to filter out passengers and more robustly identify putative driver genes. The primary filter identifies enrichment of cancer mutations in CATH functional families (CATH-FunFams) - structurally and functionally coherent sets of evolutionary related domains. Using structural representatives from CATH-FunFams, we subsequently seek enrichment of mutations in 3D and show that these mutation clusters have a very significant tendency to lie close to known functional sites or conserved sites predicted using CATH-FunFams. Our third filter identifies enrichment of putative driver genes in functionally coherent protein network modules confirmed by literature analysis to be cancer associated. Our approach is complementary to other domain enrichment approaches exploiting Pfam families, but benefits from more functionally coherent groupings of domains. Using a set of mutations from 22 cancers we detect 151 putative cancer drivers, of which 79 are not listed in cancer resources and include recently validated cancer associated genes EPHA7, DCC netrin-1 receptor and zinc-finger protein ZNF479.
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