HLA class-I and class-II restricted neoantigen loads predict overall survival in breast cancer
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...
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doaj-f28c86fc6b8d4534a55511cd2277d5f52021-09-24T14:41:24ZengTaylor & Francis GroupOncoImmunology2162-402X2020-01-019110.1080/2162402X.2020.17449471744947HLA class-I and class-II restricted neoantigen loads predict overall survival in breast cancerYingxue Ren0Yesesri Cherukuri1Daniel P. Wickland2Vivekananda Sarangi3Shulan Tian4Jodi M. Carter5Aaron S. Mansfield6Matthew S. Block7Mark E. Sherman8Keith L. Knutson9Yi Lin10Yan W. Asmann11Mayo ClinicMayo ClinicMayo ClinicMayo ClinicMayo ClinicMayo ClinicMayo ClinicMayo ClinicMayo ClinicMayo ClinicMayo ClinicMayo ClinicTumors 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.http://dx.doi.org/10.1080/2162402X.2020.1744947breast cancerneoantigenoverall survivaltumor mutational burden |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
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 |
spellingShingle |
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 HLA class-I and class-II restricted neoantigen loads predict overall survival in breast cancer OncoImmunology breast cancer neoantigen overall survival tumor mutational burden |
author_facet |
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 |
author_sort |
Yingxue Ren |
title |
HLA class-I and class-II restricted neoantigen loads predict overall survival in breast cancer |
title_short |
HLA class-I and class-II restricted neoantigen loads predict overall survival in breast cancer |
title_full |
HLA class-I and class-II restricted neoantigen loads predict overall survival in breast cancer |
title_fullStr |
HLA class-I and class-II restricted neoantigen loads predict overall survival in breast cancer |
title_full_unstemmed |
HLA class-I and class-II restricted neoantigen loads predict overall survival in breast cancer |
title_sort |
hla class-i and class-ii restricted neoantigen loads predict overall survival in breast cancer |
publisher |
Taylor & Francis Group |
series |
OncoImmunology |
issn |
2162-402X |
publishDate |
2020-01-01 |
description |
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. |
topic |
breast cancer neoantigen overall survival tumor mutational burden |
url |
http://dx.doi.org/10.1080/2162402X.2020.1744947 |
work_keys_str_mv |
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