TY - JOUR T1 - Comprehensive Analysis of Indels in Whole-genome Microsatellite Regions and Microsatellite Instability across 21 Cancer Types JF - bioRxiv DO - 10.1101/406975 SP - 406975 AU - Akihiro Fujimoto AU - Masashi Fujita AU - Takanori Hasegawa AU - Jing Hao Wong AU - Kazuhiro Maejima AU - Aya Oku-Sasaki AU - Kaoru Nakano AU - Yuichi Shiraishi AU - Satoru Miyano AU - Seiya Imoto AU - Michael R Stratton AU - Steven G Rosen AU - Hidewaki Nakagawa AU - ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Network Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/02/22/406975.abstract N2 - Microsatellites are repeats of 1-6bp units and ∼10 million microsatellites have been identified across the human genome. Microsatellites are vulnerable to DNA mismatch errors, and have thus been used to detect cancers with mismatch repair deficiency. To reveal the mutational landscape of the microsatellite repeat regions at the genome level, we analyzed approximately 20.1 billion microsatellites in 2,717 whole genomes of pan-cancer samples across 21 tissue types. Firstly, we developed a new insertion and deletion caller (MIMcall) that takes into consideration the error patterns of different types of microsatellites. Among the 2,717 pan-cancer samples, our analysis identified 31 samples, including colorectal, uterus, and stomach cancers, with higher microsatellite mutation rate (≥ 0.03), which we defined as microsatellite instability (MSI) cancers in genome-wide level. Next, we found 20 highly-mutated microsatellites that can be used to detect MSI cancers with high sensitivity. Third, we found that replication timing and DNA shape were significantly associated with mutation rates of the microsatellites. Analysis of germline variation of the microsatellites suggested that the amount of germline variations and somatic mutation rates were correlated. Lastly, analysis of mutations in mismatch repair genes showed that somatic SNVs and short indels had larger functional impact than germline mutations and structural variations. Our analysis provides a comprehensive picture of mutations in the microsatellite regions, and reveals possible causes of mutations, as well as provides a useful marker set for MSI detection. ER -