Comprehensive Characterization of Cancer Driver Genes and Mutations
Комплексная характеристика генов и мутаций — драйверов рака
2018-04-01
SCID: 54.1/z9r2ybq9
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PanCancer analysiscancer driver genesclinically actionable eventsdriver mutationsprecision oncology
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Abstract (AI)
Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%-85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors.
Key Findings
1
A PanCancer and PanSoftware analysis of 9,423 tumor exomes across all 33 TCGA projects used 26 computational tools to identify cancer drivers.
2
Experimental validation indicated that 60%–85% of predicted mutations were likely cancer drivers.
3
More than 300 microsatellite-instability tumors showed high PD-1/PD-L1 levels, and 57% of analyzed tumors harbored putative clinically actionable events.
4
Sequence- and structure-based analyses uncovered more than 3,400 putative missense driver mutations supported by multiple lines of evidence.
5
The study identified 299 driver genes and characterized their associations with anatomical sites and cancer or cell types.
Research Object
Cancer driver genes and mutations across tumors from all 33 The Cancer Genome Atlas projects
Research Subject
The identification, characterization, and clinical relevance of driver genes and putative driver mutations, including their cancer-type, anatomical-site, molecular, and actionable associations
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2018-04-01
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