Concurrently expressed tumor neoantigens drive phenotypically distinct CD8 T cell responses
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA689431 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13347507.fastq.gz | Fastqsanger.gz | |||
| SRR13347508_1.fastq.gz | Fastqsanger.gz | |||
| SRR13347508_2.fastq.gz | Fastqsanger.gz | |||
| SRR13347509_1.fastq.gz | Fastqsanger.gz | |||
| SRR13347509_2.fastq.gz | Fastqsanger.gz |
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Project description:Mutations in RNA splicing factors are prevalent across cancers and generate recurrently mis-spliced mRNA isoforms. Here we identified a series of bona fide neoantigens translated from highly stereotyped splicing alterations promoted by neomorphic, leukemia-associated somatic mutations in the splicing machinery. We utilized feature-barcoded peptide-MHC dextramers to isolate neoantigen-specific T cell receptors (TCR) from both healthy donors and patients with leukemia. While circulating neoantigen-specific CD8+ T cells were identified in patients with active disease, they were dysfunctional with reduced inflammatory response gene signatures. In contrast, donor CD8+ T cells with tumor-reactive TCRs were present following curative allogeneic hematopoietic cell transplant. T cells engineered with TCRs recognizing an SRSF2 mutant-induced neoantigen in CLK3 resulted in specific recognition and cytotoxicity of SRSF2 mutant leukemia. These data identify RNA mis-splicing derived neoantigens and neoantigen-specific TCRs across patients and provide proof-of-concept to genetically redirect T cells to public mis-splicing derived neoantigens in myeloid leukemias.
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Project description:Intratumoral heterogeneity (ITH) arises from distinct subclonal expansion following genetic or epigenetic alterations, and profoundly influences how tumors response to their immune microenvironment. Tumor progression trees based on single-cell mutational profiles have made it possible to trace subclonal evolution; however, conventional tree-building methods can incorporate only a limited number of cells and mutations, restricting their application to larger single-cell data. To investigate the effect of ITH on the therapeutic response of melanoma, we have developed Trisicell (https://trisicell.rtfd.io), a computational toolkit for scalable inference of mutational ITH through assessment of single-cell genomic variant data. By applying Trisicell to genetically matched mouse melanoma datasets, we found that expressed mutations are sufficient to effectively drive subclonal evolution. On single-cell, full-length RNA sequencing data of mouse melanoma from preclinical immune checkpoint blockade (ICB) studies, the analysis showed that the subtree-seeding mutations in the trees identified distinct subclones associated with a specific developmental state and neural crest lineage markers. Using the tree to trace cell lineages, we found that neoantigens depleted by ICB were predominantly expressed in minor subclones, suggesting that post-treatment recurrence is driven by immunoediting. Moreover, these neoantigens were enriched with those derived from frameshift mutations and mutated nuclear genes. Importantly, recurrently mutated genes in ICB-responding human melanoma exhibited the same features. We next used Trisicell to analyze single-cell, full-length RNA data of brain metastases (BM) from melanoma patients treated with ICB, and discovered that relapsing BM from ICB-responding patients exhibited subclones that also expressed a higher fraction of frameshift mutations and were associated with elevated levels of infiltrated T cells. Notably, they also exhibited more mutated HLA genes and expressed high level of the novel immune checkpoint HLA-G, a putative local immunosuppressive mechanism. In summary, applying Trisicell to single-cell transcriptomic analyses allowed us to identify novel features of ICB-responding melanoma neoantigens and distinct mechanisms for adapting to immunotherapy at different sites. These results have important implications for both melanoma evolution and target identification for immunotherapies, including ICB and cancer vaccines. This is the first study to trace subclonal evolution of neoantigens at single-cell resolution, demonstrating that Trisicell and our datasets represent important resources for the field.
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| S-EPMC7919731 | biostudies-literature