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HLA class-I and class-II restricted neoantigen loads predict overall survival in breast cancer

Authors :
Yingxue Ren
Yesesri Cherukuri
Daniel P. Wickland
Vivekananda Sarangi
Shulan Tian
Jodi M. Carter
Aaron S. Mansfield
Matthew S. Block
Mark E. Sherman
Keith L. Knutson
Yi Lin
Yan W. Asmann
Source :
OncoImmunology, Vol 9, Iss 1 (2020)
Publication Year :
2020
Publisher :
Taylor & Francis Group, 2020.

Abstract

Tumors acquire numerous mutations during development and progression. When translated into proteins, these mutations give rise to neoantigens that can be recognized by T cells and generate antibodies, representing an exciting direction of cancer immunotherapy. While neoantigens have been reported in many cancer types, the profiling of neoantigens often focused on the class-I subtype that are presented to CD8 + T cells, and the relationship between neoantigen load and clinical outcomes was often inconsistent among cancer types. In this study, we described an informatics workflow, REAL-neo, for identification, quality control (QC), and prioritization of both class-I and class-II human leukocyte antigen (HLA) bound neoantigens that arise from somatic single nucleotide mutations (SNM), small insertions and deletions (INDEL), and gene fusions. We applied REAL-neo to 835 primary breast tumors in the Cancer Genome Atlas (TCGA) and performed comprehensive profiling and characterization of the detected neoantigens. We found recurrent HLA class-I and class-II restricted neoantigens across breast cancer cases, and uncovered associations between neoantigen load and clinical traits. Both class-I and class-II neoantigen loads from SNM and INDEL were found to predict overall survival independent of tumor mutational burden (TMB), breast cancer subtypes, tumor-infiltrating lymphocyte (TIL) levels, tumor stage, and age at diagnosis. Our study highlighted the importance of accurate and comprehensive neoantigen profiling and QC, and is the first to report the predictive value of neoantigen load for overall survival in breast cancer.

Details

Language :
English
ISSN :
2162402X
Volume :
9
Issue :
1
Database :
Directory of Open Access Journals
Journal :
OncoImmunology
Publication Type :
Academic Journal
Accession number :
edsdoj.f28c86fc6b8d4534a55511cd2277d5f5
Document Type :
article
Full Text :
https://doi.org/10.1080/2162402X.2020.1744947