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Identification of 33 candidate oncogenes by screening for base-specific mutations.

ABSTRACT: BACKGROUND: Genes with recurrent codon-specific somatic mutations are likely drivers of tumorigenesis and potential therapeutic targets. Hypermutable cancers may represent a sensitive system for generation and selection of oncogenic mutations. METHODS: We utilised exome-sequencing data on 25 sporadic microsatellite-instable (MSI) colorectal cancers (CRCs) and searched for base-specific somatic mutation hotspots. RESULTS: We identified novel mutation hotspots in 33 genes. Fourteen genes displayed mutations in the validation set of 254 MSI CRCs: ANTXR1, MORC2, CEP135, CRYBB1, GALNT9, KRT82, PI15, SLC36A1, CNTF, GLDC, MBTPS1, OR9Q2, R3HDM1 and TTPAL. A database search found examples of the hotspot mutations in multiple cancer types. CONCLUSIONS: This work reveals a variety of new recurrent candidate oncogene mutations to be further scrutinised as potential therapeutic targets.

SUBMITTER: Tuupanen S

PROVIDER: S-EPMC4200084 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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Identification of 33 candidate oncogenes by screening for base-specific mutations.

Tuupanen S S Hänninen U A UA Kondelin J J von Nandelstadh P P Cajuso T T Gylfe A E AE Katainen R R Tanskanen T T Ristolainen H H Böhm J J Mecklin J-P JP Järvinen H H Renkonen-Sinisalo L L Andersen C L CL Taipale M M Taipale J J Vahteristo P P Lehti K K Pitkänen E E Aaltonen L A LA

British journal of cancer 20140812 8

<h4>Background</h4>Genes with recurrent codon-specific somatic mutations are likely drivers of tumorigenesis and potential therapeutic targets. Hypermutable cancers may represent a sensitive system for generation and selection of oncogenic mutations.<h4>Methods</h4>We utilised exome-sequencing data on 25 sporadic microsatellite-instable (MSI) colorectal cancers (CRCs) and searched for base-specific somatic mutation hotspots.<h4>Results</h4>We identified novel mutation hotspots in 33 genes. Fourt ...[more]

PMID: 25117815

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Project description:Muscle tissue is involved with every stage of life activities and has roles in biological processes. For example, the blood circulation system needs the heart muscle to transport blood to all parts, and the movement cannot be separated from the participation of skeletal muscle. However, the process of muscle development and the regulatory mechanisms of muscle development are not clear at present. In this study, we used bioinformatics techniques to identify differentially expressed genes specifically expressed in multiple muscle tissues of mice as potential candidate genes for studying the regulatory mechanisms of muscle development. Mouse tissue microarray data from 18 tissue samples was selected from the GEO database for analysis. Muscle tissue as the treatment group, and the other 17 tissues as the control group. Genes expressed in the muscle tissue were different to those in the other 17 tissues and identified 272 differential genes with highly specific expression in muscle tissue, including 260 up-regulated genes and 12 down regulated genes. is the genes were associated with the myofibril, contractile fibers, and sarcomere, cytoskeletal protein binding, and actin binding. KEGG pathway analysis showed that the differentially expressed genes in muscle tissue were mainly concentrated in pathways for AMPK signaling, cGMP PKG signaling calcium signaling, glycolysis, and, arginine and proline metabolism. A PPI protein interaction network was constructed for the selected differential genes, and the MCODE module used for modular analysis. Five modules with Score > 3.0 are selected. Then the Cytoscape software was used to analyze the tissue specificity of differential genes, and the genes with high degree scores collected, and some common genes selected for quantitative PCR verification. The conclusion is that we have screened the differentially expressed gene set specific to mouse muscle to provide potential candidate genes for the study of the important mechanisms of muscle development.

Dataset Information

Identification of 33 candidate oncogenes by screening for base-specific mutations.

Publications

Identification of 33 candidate oncogenes by screening for base-specific mutations.

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