Mis-Splicing Derived Neoantigens and Cognate T Cell Receptors in Splicing Factor Mutant Myeloid Neoplasms
Bibliographic record
Abstract
Mutations in RNA splicing factors are the most common class of genetic alterations in MDS and are also prevalent in AML. These mutations cause recurrent splicing changes in a highly sequence-specific manner across patients and cancer types. We hypothesized that a subset of these aberrant splicing changes would generate “public” neoantigens (i.e. shared across patients) that can serve as potential targets of T cell-based immunotherapies. Here we identify a series of shared, bona fide neoantigens induced by leukemia-associated mutations in RNA splicing factors SRSF2 and ZRSR2. We validate in vitro that these neoantigens are presented on HLA class I (HLA-I) and immunogenic. We also discover T cell receptors (TCRs) reactive to identified neoantigens and demonstrate that introduction of these TCRs into primary human T cells redirects the T cells to selectively eliminate leukemic cells. To predict mis-splicing derived neoantigens, we analyzed RNA-seq datasets from five myeloid leukemia patient cohorts with SRSF2 mutations (n=107), ZRSR2 mutations (n=33), or no mutations in splicing factors (n=837). We identified mis-spliced mRNA isoforms consistently produced across SRSF2 or ZRSR2 mutant patients but minimally expressed in healthy bone marrow, PBMCs, and a panel of 14 normal tissues. We translated each tumor-specific mRNA isoform in silico, split into 8-12-mer peptides, and predicted high-affinity binders to HLA-A*02:01. In total, we selected 56 candidate mis-splicing derived neoantigens created by mutant SRSF2 and 19 by mutant ZRSR2 for further in vitro studies. We synthesized candidate peptides and validated their HLA-I binding using the T2 HLA-A2 shift assay. We then tested if the peptides are immunogenic (i.e. elicit effector CD8+ T cell responses) in PBMCs from 14 unique healthy donors. One particular peptide, derived from SRSF2 mutation-induced exon 4 skipping in CLK3 and confirmed by HLA-I immunopeptidomics, was immunogenic across multiple donors. To isolate CD8+ T cells reactive to the CLK3 neoantigen, we constructed dextramers, which are composed of ten peptide/HLA-I complexes on a dextran scaffold. We sorted CLK3 peptide-primed CD8+ T cells with dual-color CLK3 neoepitope dextramers and performed TCR-seq which identified 11 distinct TCR clonotypes from two healthy donors. Primary human T cells transduced with these TCRs demonstrated remarkably specific cytolysis of HLA-A*02:01+ leukemic cells expressing the CLK3 neoantigen as well as cells harboring SRSF2 mutations. The discovery of immunogenic neoantigens in splicing factor mutant cells begs the question of how such malignancies develop in the setting of potential immune responses to these antigens. To address this question, we synthesized a panel of DNA-barcoded dextramers against 43 SRSF2 and 12 ZRSR2 mutant-induced candidate peptides as well as one CMV and three negative control peptides. Using this dextramer panel, we isolated antigen-reactive CD8+ T cells from splicing factor mutant MDS/AML patient PBMCs and performed single-cell RNA-, TCR-, and dextramer barcode sequencing. Downstream single-cell analysis revealed that neoantigen-reactive CD8+ T cells are present in MDS and AML patient blood and are clonally expanded. However, they have a distinct gene expression profile from virus-reactive T cells with evidence of impaired T cell cytotoxic function at the time of active MDS and AML. For patients with high-risk MDS and AML, allogeneic stem cell transplantation (allo-SCT) remains the most established curative therapy and results in donor T cell-mediated graft-versus-leukemia effect. To test if donor T cells could recognize mis-splicing derived neoantigens in patient leukemia, we performed dextramer-based single-cell profiling of matched pre- and post-allo-SCT patient PBMC samples. This discovered a donor-derived TCR that is clonally expanded and cognate to a peptide derived from SRSF2 mutant-induced intron retention in RHOT2. Primary human T cells transduced with this TCR specifically recognized and lysed leukemic cells expressing the RHOT2 neoantigen. Overall, these data identify recurrent RNA mis-splicing events as sources of actionable public neoantigens in myeloid malignancies and provide proof-of-concept for genetically redirecting T cells to recognize these targets. These data have immediate therapeutic implications as the TCRs presented can be applied for transgenic TCR-T cell therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".