Cited by 89Cancer Immunotherapy and BiomarkersImmunotherapy and Immune ResponsesT-cell and B-cell Immunology

Endogenous CD4+ T Cells Recognize Neoantigens in Lung Cancer Patients, Including Recurrent Oncogenic KRAS and ERBB2 ( Her2 ) Driver Mutations

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Veatch, Joshua R., Jesernig, Brenda L., Kargl, Julia, Fitzgibbon, Matthew, Lee, Sylvia M., Baik, Christina, Martins, Renato, Houghton, A. McGarry +1 more·2019·Cancer Immunology Research

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Abstract

T cells specific for neoantigens encoded by mutated genes in cancers are increasingly recognized as mediators of tumor destruction after immune-checkpoint inhibitor therapy or adoptive cell transfer. Much of the focus has been on identifying epitopes presented to CD8+ T cells by class I MHC. However, CD4+ class II MHC-restricted T cells have been shown to have an important role in antitumor immunity. Unfortunately, the vast majority of neoantigens recognized by CD8+ or CD4+ T cells in cancer patients result from random mutations and are patient-specific. Here, we screened the blood of 5 non–small cell lung cancer (NSCLC) patients for T-cell responses to candidate mutation-encoded neoepitopes. T-cell responses were detected to 8.8% of screened antigens, with 1 to 7 antigens identified per patient. A majority of responses were to random, patient-specific mutations. However, CD4+ T cells that recognized the recurrent KRASG12V and the ERBB2 (Her2) internal tandem duplication (ITD) oncogenic driver mutations, but not the corresponding wild-type sequences, were identified in two patients. Two different T-cell receptors (TCR) specific for KRASG12V and one T-cell receptor specific for Her2-ITD were isolated and conferred antigen specificity when transfected into T cells. Deep sequencing identified the Her2-ITD–specific TCR in the tumor but not nonadjacent lung. Our results showed that CD4+ T-cell responses to neoantigens, including recurrent driver mutations, can be derived from the blood of NSCLC patients. These data support the use of adoptive transfer or vaccination to augment CD4+ neoantigen-specific T cells and elucidate their role in human antitumor immunity.

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  1. [35]McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome research 2010; 20(9): 1297– 303. 20644199 PMC2928508

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Authors
Veatch, J. R., Jesernig, B. L., Kargl, J., Fitzgibbon, M., Lee, S. M., Baik, C., Martins, R., Houghton, A. M., & Riddell, S. R.
Affiliations
  • Fred Hutch Cancer Center (US)
  • Medical University of Graz (AT)
  • University of Washington (US)
Corresponding author
Veatch, Joshua R.
Venue
Cancer Immunology Research
Published
2019-06-01
Volume
7
Issue
6
Pages
910-922
ISSN
  • 2326-6066 (ISSN-L)
  • 2326-6074
OpenAlex
W2943013004
Cited by
89
References
49
Citations by year
2026: 6 · 2025: 9 · 2024: 10 · 2023: 12 · 2022: 15 · 2021: 22 · 2020: 10 · 2019: 5
FWCI
5.43
Type
journal article
Language
en
Open access
Locations
  • Cancer Immunology Research (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
HHS | National Institutes of HealthHHS | National Institutes of Health (NIH) (T32 T32CA009515, K12 CA076930-16A1)
Topics
  • Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
  • Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
  • Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
Keywords
CD4+ T cells, neoantigens, non-small cell lung cancer, KRAS G12V mutation, driver mutations, T cell receptor, tumor-specific T cell responses, antitumor immunity, adoptive cell transfer, cancer vaccination, tumor-infiltrating T cells
MeSH terms
Aged, Antigens, Neoplasm, Carcinoma, Non-Small-Cell Lung, Female, Humans, Lung Neoplasms, Lymphocyte Activation, Male, Middle Aged, Mutation, Neoplasm Staging, RNA, Messenger, CD4-Positive T-Lymphocytes, Gene Expression, Lymphocytes, Tumor-Infiltrating, Proto-Oncogene Proteins p21(ras), Receptor, ErbB-2, Erb-b2 Receptor Tyrosine Kinases, Computational Biology, Cell Line, Tumor, Transcriptome

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