시간: 11월 21일(수), 오전 11시

장소: 220동 세미나실

TITLE: Cancer Genomics Study using Public Big Data

Recently, many cancer researchers and clinicians are interesting to study a multi-level omics data analysis using cancer big data such as The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO). We’ll introduce our papers published on Nature Biotechnology (2013) and Nature Genetics (2015) using public data. First, to raise awareness of the dangers of the common filtering approach, we systematically investigate non-silent somatic point mutations in SNP database to characterize their frequency and clinical impact. A considerable number of mutation hot-spots in cancer-associated genes were present in SNP database. Some filtered cancer-associated somatic SNPs in example articles exhibited known mutually exclusive alteration patterns and some had clinical significance in survival analysis. Next, we analyzed RNA-Seq and exome data from 1,812 cancer patients from TCGA data portal and CGHub, and identified ~900 somatic exonic SNVs that disrupt splicing. At least 163 SNVs including 31 synonymous ones were shown to cause intron retention or exon skipping in an allele-specific manner, with ~70% of the SNVs occurring on the last base of exons. Importantly, SNVs causing intron retention were enriched in tumor suppressors, and 97% of these SNVs generated a premature termination codon (PTC), leading to loss of function through nonsense-mediated decay or truncated proteins. This work demonstrates that intron retention is a common mechanism of tumor suppressor inactivation.