| Literature DB >> 30942618 |
Shuto Hayashi1, Takuya Moriyama1, Rui Yamaguchi1, Shinichi Mizuno2, Mitsuhiro Komura1, Satoru Miyano1, Hidewaki Nakagawa3, Seiya Imoto4.
Abstract
Human leukocyte antigen (HLA) genes provide useful information on the relationship between cancer and the immune system. Despite the ease of obtaining these data through next-generation sequencing methods, interpretation of these relationships remains challenging owing to the complexity of HLA genes. To resolve this issue, we developed a Bayesian method, ALPHLARD-NT, to identify HLA germline and somatic mutations as well as HLA genotypes from whole-exome sequencing (WES) and whole-genome sequencing (WGS) data. ALPHLARD-NT showed 99.2% accuracy for WGS-based HLA genotyping and detected five HLA somatic mutations in 25 colon cancer cases. In addition, ALPHLARD-NT identified 88 HLA somatic mutations, including recurrent mutations and a novel HLA-B type, from WES data of 343 colon adenocarcinoma cases. These results demonstrate the potential of ALPHLARD-NT for conducting an accurate analysis of HLA genes even from low-coverage data sets. This method can become an essential tool for comprehensive analyses of HLA genes from WES and WGS data, helping to advance understanding of immune regulation in cancer as well as providing guidance for novel immunotherapy strategies.Entities:
Keywords: Bayesian model; HLA genotyping; HLA mutation calling; whole-exome sequencing; whole-genome sequencing
Year: 2019 PMID: 30942618 PMCID: PMC6748403 DOI: 10.1089/cmb.2018.0224
Source DB: PubMed Journal: J Comput Biol ISSN: 1066-5277 Impact factor: 1.479