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Distinct sets of molecular characteristics define tumor-rejecting neoantigens
Open accessPreprint — published as 10.1136/jitc-2025-013148 · Paper page
Abstract
Challenges in identifying tumor-rejecting neoantigens limit the efficacy of neoantigen vaccines to treat cancers, including cutaneous squamous cell carcinoma (cSCC). A minority of human cSCC tumors shared neoantigens, supporting the need for personalized vaccines. Using a UV-induced mouse cSCC model which recapitulated the mutational signature and driver mutations found in human disease, we found that CD8 T cells constrain cSCC. Two MHC class I neoantigens were identified that constrained cSCC growth. Compared to the wild-type peptides, one tumor-rejecting neoantigen exhibited improved MHC binding and the other had increased solvent accessibility of the mutated residue. Across known neoantigens that do not impact MHC binding, structural modeling of the peptide/MHC complexes indicated that increased solvent accessibility, which will facilitate TCR recognition of the neoantigen, distinguished tumor-rejecting from non-immunogenic neoantigens. This work reveals characteristics of tumor-rejecting neoantigens that may be of considerable importance in identifying optimal vaccine candidates in cSCC and other cancers.
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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
Flagged first, then by citations
Research works printed but not linked: 71
- 10.1126/science.aaa4971 · DOI · Paper page
- 10.1038/s41586-023-06063-y · DOI · Paper page
- 10.1038/nature23003 · DOI · Paper page
- 10.1038/nature22991 · DOI · Paper page
- 10.1038/s41586-018-0810-y · DOI · Paper page
- Katsikis, P.D. , Ishii, K.J. & Schliehe, C . Challenges in developing personalized neoantigen cancer vaccines. Nature Reviews Immunology (2023). · DOI
- 10.1126/science.aaa3828 · DOI · Paper page
- 10.1038/nature13988 · DOI · Paper page
- 10.1158/0008-5472.CAN-11-3722 · DOI
- 10.1084/jem.20141308 · DOI
- Dolina, J.S. et al. Linked CD4+/CD8+ T cell neoantigen vaccination overcomes immune checkpoint blockade resistance and enables tumor regression. J Clin Invest 133 (2023). · DOI
- 10.1038/nature14001 · DOI · Paper page
- 10.1038/s41586-019-1671-8 · DOI · Paper page
- 2020, Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction, Cell, 183, 818, 10.1016/j.cell.2020.09.015 · DOI · Paper page
- Borden, E.S. et al. NeoScore Integrates Characteristics of the Neoantigen:MHC Class I Interaction and Expression to Accurately Prioritize Immunogenic Neoantigens. J Immunol (2022). · DOI
- Ebrahimi-Nik, H. , et al. Mass spectrometry driven exploration reveals nuances of neoepitope-driven tumor rejection. JCI Insight 5 (2019). · DOI
- 2021, The landscape of driver mutations in cutaneous squamous cell carcinoma, npj Genomic Medicine, 6, 61, 10.1038/s41525-021-00226-4 · DOI
- Adams, A.C. et al. Solar simulated light induces cutaneous squamous cell carcinoma in inbred mice: a clinically relevant model to investigate T cell responses. J Invest Dermatol (2021). · DOI
- Nassir, S. et al. Whole exome and transcriptome sequencing of stage-matched, outcome-differentiated cutaneous squamous cell carcinoma identifies gene expression patterns associated with metastasis and poor outcomes. medRxiv, 2024.2002.2005.24302298 (2024). · DOI
- 10.1038/nature12912 · DOI · Paper page
- 10.1038/s41586-022-04696-z · DOI
- Jorgenson, E. et al. Genetic ancestry, skin pigmentation, and the risk of cutaneous squamous cell carcinoma in Hispanic/Latino and non-Hispanic white populations. Communications Biology 3, 765 (2020). · DOI
- 10.1158/1541-7786.MCR-11-0351 · DOI
- 10.4049/jimmunol.1700893 · DOI
- 2020, NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data, Nucleic Acids Research, 48, W449, 10.1093/nar/gkaa379 · DOI · Paper page
- Brennick, C.A. et al. An unbiased approach to defining bona fide cancer neoepitopes that elicit immune-mediated cancer rejection. The Journal of Clinical Investigation 131 (2021). · DOI
- Mikhaylov, V. et al. Accurate modeling of peptide-MHC structures with AlphaFold. Structure (2023). · DOI · Paper page
- 2023, Structural and physical features that distinguish tumor-controlling from inactive cancer neoepitopes, Proc Natl Acad Sci U S A, 120, e2312057120, 10.1073/pnas.2312057120 · DOI
- 2021, Prediction of neo-epitope immunogenicity reveals TCR recognition determinants and provides insight into immunoediting, Cell Rep Med, 2, 100194, 10.1016/j.xcrm.2021.100194 · DOI
- 10.1073/pnas.1500973112 · DOI · Paper page
- 2013, Properties of MHC Class I Presented Peptides That Enhance Immunogenicity, PLOS Computational Biology, 9, e1003266, 10.1371/journal.pcbi.1003266 · DOI
- 2023, Immune checkpoint inhibitors in advanced cutaneous squamous cell carcinoma: A systemic review and meta-analysis, Skin Res Technol, 29, e13229, 10.1111/srt.13229 · DOI
- 10.1016/j.jaad.2017.08.059 · DOI
- 2023, Immunotherapy for keratinocyte cancers. Part II: Identification and management of cutaneous side effects of immunotherapy treatments, Journal of the American Academy of Dermatology, 88, 1243, 10.1016/j.jaad.2022.07.062 · DOI
- 10.1158/0008-5472.CAN-20-1072 · DOI
- Li, F. et al. Neoantigen vaccination induces clinical and immunologic responses in non-small cell lung cancer patients harboring EGFR mutations. J Immunother Cancer 9 (2021). · DOI
- 2021, Solar Simulated Light Induces Cutaneous Squamous Cell Carcinoma in Inbred Mice: A Clinically Relevant Model to Investigate T-Cell Responses, J Invest Dermatol, 141, 2990, 10.1016/j.jid.2021.06.005 · DOI
- 10.1371/journal.pone.0110928 · DOI
- Zeng, Z. et al. IFN-γ Critically Enables the Intratumoural Infiltration of CXCR3(+) CD8(+) T Cells to Drive Squamous Cell Carcinoma Regression. Cancers (Basel) 13 (2021). · DOI
- 10.1111/j.1751-1097.2010.00859.x · DOI
- 10.1158/0008-5472.CAN-07-3059 · DOI
- Dodagatta-Marri, E. et al. α-PD-1 therapy elevates Treg/Th balance and increases tumor cell pSmad3 that are both targeted by α-TGFβ antibody to promote durable rejection and immunity in squamous cell carcinomas. J Immunother Cancer 7, 62 (2019). · DOI · Paper page
- 10.1172/JCI82416 · DOI
- 10.1126/science.aaf2288 · DOI
- Capietto, A.H. et al. Mutation position is an important determinant for predicting cancer neoantigens. J Exp Med 217 (2020). · DOI
- 2021, Reversion analysis reveals the in vivo immunogenicity of a poorly MHC I-binding cancer neoepitope, Nat Commun, 12, 6423, 10.1038/s41467-021-26646-5 · DOI
- 2020, Structural dissimilarity from self drives neoepitope escape from immune tolerance, Nat Chem Biol, 16, 1269, 10.1038/s41589-020-0610-1 · DOI
- 10.1016/j.jmb.2007.07.025 · DOI
- 1993, Intracellular transport of class I MHC molecules in antigen processing mutant cell lines, J Immunol, 151, 3407, 10.4049/jimmunol.151.7.3407 · DOI
- 10.1093/bioinformatics/btr612 · DOI
- 2023, Analysis and Visualization of Longitudinal Genomic and Clinical Data from the AACR Project GENIE Biopharma Collaborative in cBioPortal, Cancer Res, 83, 3861, 10.1158/0008-5472.CAN-23-0816 · DOI · Paper page
- 10.1038/nbt.3344 · DOI
- 10.1016/j.humimm.2007.04.005 · DOI
- Ye, J. et al. Primer-BLAST: a tool to design target-specific primers for polymerase chain reaction. BMC Bioinformatics 13, 134 (2012). · DOI
- 2020, Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma, Cell, 182, 497, 10.1016/j.cell.2020.05.039 · DOI · Paper page
- Chitsazzadeh, V. et al. Cross-species identification of genomic drivers of squamous cell carcinoma development across preneoplastic intermediates. Nat Commun 7, 12601 (2016). · DOI
- 10.1038/nature15393 · DOI · Paper page
- Li, H . Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv: Genomics (2013).
- 10.1093/bioinformatics/btp352 · DOI · Paper page
- Van der Auwera, G.A. & O’Connor, B.D. Genomics in the cloud : using Docker, GATK, and WDL in Terra, First edition. edn. O’Reilly Media: Sebastopol, CA, 2020.
- 10.1093/bioinformatics/bts271 · DOI
- McLaren, W. et al. The Ensembl Variant Effect Predictor. Genome Biol 17, 122 (2016). · DOI · Paper page
- Hundal, J. et al. pVAC-Seq: A genome-guided in silico approach to identifying tumor neoantigens. Genome Med 8, 11 (2016). · DOI
- 2020, The International Genome Sample Resource (IGSR) collection of open human genomic variation resources, Nucleic Acids Res, 48, D941, 10.1093/nar/gkz836 · DOI
- 10.1126/science.8023157 · DOI · Paper page
- 10.1093/nar/gkab314 · DOI · Paper page
- 10.1007/s001090050095 · DOI
- 10.1007/BF00300234 · DOI · Paper page
- 10.1038/nmeth.4197 · DOI · Paper page
- Ye, J. et al. Primer-BLAST: A tool to design target-specific primers for polymerase chain reaction. BMC Bioinformatics 13, 134 (2012). · DOI
- 10.1002/eji.201242379 · DOI
Metadata
- Authors
- Adams, A. C., Macy, A. M., Borden, E. S., Herrmann, L. M., Brambley, C. A., Ma, T., Li, X., Hughes, A., Roe, D. J., Mangold, A. R., Buetow, K. H., Wilson, M. A., Baker, B. M., & Hastings, K. T.
- Affiliations
- Phoenix VA Health Care System (US)
- University of Notre Dame (US)
- Mayo Clinic (US)
- Mayo Clinic in Arizona (US)
- University of Arizona (US)
- Arizona State University (US)
- Corresponding author
- Hastings, Karen Taraszka
- ORCID
- Venue
- Journal for ImmunoTherapy of Cancer
- Publisher
- openRxiv
- Published
- 2024-02-16
- Volume
- 13
- Issue
- 10
- Pages
- e013148-e013148
- ISSN
- 2051-1426 (ISSN-L)
- PMC
- PMC12548620
- OpenAlex
- W4415451524
- Cited by
- 4
- References
- 1
- Citations by year
- 2026: 3 · 2025: 1
- FWCI
- 1.48
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc
- Locations
- Journal for ImmunoTherapy of Cancer (publishedVersion, cc-by-nc)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- U.S. Department of Veterans Affairs (I01BX005336)
- Mayo Clinic
- Dermatology Foundation
- American Skin Association
- Arizona State University
- University of Arizona
- National Institutes of Health (75N93020D00005, 75N99020D00005)
- National Heart, Lung, and Blood Institute (75N92020D00005)
- National Institute on Drug Abuse (75N95020D00005)
- National Cancer Institute (T32CA009213, P01CA229112, F30CA281056, F30CA257622, P30CA023074)
- National Institute of General Medical Sciences (R35GM118166)
- National Institute of Allergy and Infectious Diseases (75N93023D00005, 75N93022D00005)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Keywords
- cutaneous squamous cell carcinoma, neoantigen vaccines, personalized cancer vaccines, MHC class I binding, T cell receptor recognition, mutational signatures, driver mutations, CD8+ T cells
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