Abstract 1093: Sensitive detection of somatic mutations in class I HLA genes reveals enrichment for functional events in cancer
Authors: Sachet A. Shukla, Mohini Rajasagi, Philip Dixon, Grace Tiao, Michael S. Lawrence, Carrie Sougnez, Vladimir Brusic, Kristian Cibulskis, Adam Kiezun, Catherine J. Wu, Gad Getz
Journal: Cancer Research (2015)

Abstract Recent studies have revealed enhanced somatic mutation rate in HLA genes in several tumor types and has strongly implicated HLA dysfunction as a possible mediator of immune evasion. Mutation detection in this highly polymorphic and GC-rich locus, however, is complicated by suboptimal alignment to the canonical reference genome and lowered capture efficiency. To address this challenge, we developed the POLYSOLVER (POLYmorphic loci reSOLVER) algorithm for accurate inference of class I HLA-A, -B and -C alleles from whole exome sequencing (WES) data, which can then be used for more sensitive and specific mutation detection. POLYSOLVER comprises two broad steps: alignment optimization and subsequent inference of the alleles using a Bayesian classifier. When applied to 133 HapMap samples of known HLA type, POLYSOLVER outperformed other publicly available tools with an overall protein-level accuracy of 97% and was particularly more powerful at low sequencing depths with an overall accuracy of 96%. To accurately detect HLA mutations in tumor samples, we performed HLA typing by applying POLYSOLVER to the paired germline sample, re-aligned the HLA reads from both tumor and normal to the inferred HLA alleles while filtering out likely erroneous alignments, and then applied standard tools (MuTect and Strelka) to detect somatic mutations by comparing the re-aligned tumor and normal HLA reads. Based on orthogonal RNA-Seq validation, we estimate an improvement in sensitivity from 57.1% to 94.3% and specificity from 43.8% to 81.3% over standard methods. Pan-cancer analysis of TCGA data from 3,608 tumor/normal pairs by POLYSOLVER across 12 tumor types revealed 147 non-silent HLA mutations in 121 patients. We identified colon adenocarcinoma to be significantly affected by somatic mutation in class I HLA genes, further supporting HLA mutation as a common oncogenic mechanism. By contrast, HLA mutations were not detected in chronic lymphocytic leukemia (n = 129). Alterations likely to have a functional effect, including loss-of-function, were significantly enriched in HLA mutations compared to non-HLA mutations (P &amp;lt; 2.2×10-16). We also observed that 70 of the 147 total HLA mutations (47.6%) fell in 23 recurrent sites suggesting positive selection at these positions. Finally, we determined that the majority of the detected mutations mapped to regions critical for antigen presentation. In addition to enabling better detection of HLA mutations, accurate HLA typing by POLYSOLVER can also be used to study germline associations of HLA alleles in diseases, and in donor screening for organ transplantation. It may be extended to extracting typing and mutation information from whole genome or RNA sequencing data and from other polymorphic regions in the genome such as MHC class II, TAP1 and TAP2 genes, and MIC-A and MIC-B ligands. POLYSOLVER hence is a generally applicable analysis framework to address these otherwise challenging loci. Citation Format: Sachet A. Shukla, Mohini Rajasagi, Philip Dixon, Grace Tiao, Michael S. Lawrence, Carrie Sougnez, Vladimir Brusic, Kristian Cibulskis, Adam Kiezun, Catherine J. Wu, Gad Getz. Sensitive detection of somatic mutations in class I HLA genes reveals enrichment for functional events in cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1093. doi:10.1158/1538-7445.AM2015-1093