Abstract Background: Diffuse Glioma (DG) exhibits low tumor mutational burden and limited responsiveness to immunotherapy, suggesting that antigen sources beyond canonical mutation-derived neoantigens are required to support effective antitumor T-cell responses. Transcriptomic aberrations, such as aberrant splicing, fusion transcripts, etc., generate extensive tumor-specific sequences. However, conventional short-read RNA sequencing captures only the sequences overlapping the neojunctions (NJs), thereby substantially underrepresenting this rich source of actionable neoantigens. Methods: Nanopore long-read RNA sequencing was performed on 11 diffuse glioma tissues. Public data from 6 normal cortices was included as a control. A pipeline was composed to construct the whole-length transcriptome, identify novel transcripts with transcriptomic aberrations, translate peptides, and predict neoantigen candidates. Data-independent acquisition (DIA) proteomics was performed on 4 matched samples to verify the transcription of these novel transcripts and analyzed via DIA-NN. Immunopeptidome data were acquired from 5 matched samples and screened by NeoDisc, a computational pipeline accessing neoantigens based on the functionality of the antigen processing and presentation machinery. Results: DGs demonstrated a significantly greater burden of both a larger number and higher expression of novel transcripts with transcriptomic aberration compared to normal cortex, indicating transcriptomic aberration as a tumor-enriched source of antigenic diversity. Novel transcripts consist of 8.08% of the total transcriptome in the DG cohort compared to 7.06% in the cortex cohort. Across the 4 DG samples with matched DIA proteomics, hundreds of novel transcripts per sample were identified after filtering for expression and coding probability. Approximately 30-40% of these transcripts showed evidence of translation supported by the DIA proteomics, with ongoing refinement for the high-confidence translated set. Neoantigen prioritization further identified hundreds of high-confidence candidate peptides per tumor with strong predicted HLA binding and immunogenicity features. To verify HLA-mediated peptide presentation as a further validation, DDA and DIA immunopeptidomics spectra for HLA-I and HLA-II have been collected. Conclusions: Transcriptomic aberration neoantigens represent a biologically authentic and targetable antigen class in diffuse glioma. Integrating whole-length transcriptomics, DIA proteomics, and immunopeptidomics provides a disease-relevant and scalable framework for neoantigen discovery in low-mutation tumors. Cohort expansion and early T-cell functional validation of prioritized neoantigen candidates are undergoing to assess their therapeutic relevance. Citation Format: Kenan Zhang, Megan Benz, Kelly M. Hotchkiss, Lin Lin, Sarah Quackenbush, Aroa Elortza Payros, Mark Pieterse, Wigard Kloosterman, Jeroen Kneppers, Mustafa Khasraw. Long-read RNA sequencing and immunopeptidomics reveal transcriptomic aberrationneoantigens as targets for T cell immunotherapy in diffuse glioma abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4256.
Zhang et al. (Fri,) studied this question.