Background
Human Leukocyte Antigen (HLA) genes are critical for the presentation of neoantigens to the immune system by cancer cells. Deletion of HLA alleles, known as HLA loss of heterozygosity (LOH), has been highlighted as a key immune escape mechanism. Validated algorithms to detect HLA LOH from sequencing data are critical for exploring the biological impact of HLA LOH and assessing its utility as a clinical biomarker. To address this need, we developed a machine learning algorithm to detect HLA LOH, Deletion of Allele-Specific HLAs (DASH™), extensively validated it with several approaches and applied it to a large cancer cohort to understand its frequency of occurrence and biological impact.
Augmented exome capture with ImmunoID NeXT™
The ImmunoID NeXT Platform® provides joint tumor genomics and immune profiling from a single tumor/normal sample. Through augmenting coverage of the HLA locus, ImmunoID NeXT also provides the data to accurately type HLA alleles, detect somatic mutations and probe copy number deletions in this highly polymorphic region.
