Computational KIR copy number discovery reveals interaction between inhibitory receptor burden and survival.

Details

Serval ID
serval:BIB_D49E37F7812C
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Computational KIR copy number discovery reveals interaction between inhibitory receptor burden and survival.
Journal
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Author(s)
Pyke R.M., Genolet R., Harari A., Coukos G., Gfeller D., Carter H.
ISSN
2335-6936 (Electronic)
ISSN-L
2335-6928
Publication state
Published
Issued date
2019
Peer-reviewed
Oui
Volume
24
Pages
148-159
Language
english
Notes
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
Publication Status: ppublish
Abstract
Natural killer (NK) cells have increasingly become a target of interest for immunotherapies. NK cells express killer immunoglobulin-like receptors (KIRs), which play a vital role in immune response to tumors by detecting cellular abnormalities. The genomic region encoding the 16 KIR genes displays high polymorphic variability in human populations, making it difficult to resolve individual genotypes based on next generation sequencing data. As a result, the impact of polymorphic KIR variation on cancer phenotypes has been understudied. Currently, labor-intensive, experimental techniques are used to determine an individual's KIR gene copy number profile. Here, we develop an algorithm to determine the germline copy number of KIR genes from whole exome sequencing data and apply it to a cohort of nearly 5000 cancer patients. We use a k-mer based approach to capture sequences unique to specific genes, count their occurrences in the set of reads derived from an individual and compare the individual's k-mer distribution to that of the population. Copy number results demonstrate high concordance with population copy number expectations. Our method reveals that the burden of inhibitory KIR genes is associated with survival in two tumor types, highlighting the potential importance of KIR variation in understanding tumor development and response to immunotherapy.
Keywords
Algorithms, Computational Biology/methods, Databases, Genetic/statistics & numerical data, Female, Gene Dosage, Histocompatibility Antigens Class I/metabolism, Humans, Kaplan-Meier Estimate, Killer Cells, Natural/immunology, Neoplasms/genetics, Neoplasms/immunology, Neoplasms/mortality, Receptors, KIR/genetics, Uterine Cervical Neoplasms/genetics, Uterine Cervical Neoplasms/immunology, Uterine Cervical Neoplasms/mortality, Uterine Neoplasms/genetics, Uterine Neoplasms/immunology, Uterine Neoplasms/mortality, Whole Exome Sequencing
Pubmed
Create date
28/11/2019 12:10
Last modification date
29/11/2019 6:26
Usage data