IMMU-62. The Immune Microenvironment and Antigenic Profile of Oligodendrogliomas: Insights for Next-Generation Immunotherapies

Abstract BACKGROUND Efficient immunotherapies for oligodendrogliomas require a detailed understanding of their immunologic landscape and tumor rejection antigens. METHODS To address this, we applied our in-house Open Reading Frame Antigen Network (O.R.A.N.) pipeline (Yang et al., Genome Medicine 2024) to analyze antigenic epitopes—including single nucleotide variations (SNVs), indels, gene fusions, and tumor-associated antigens (TAAs)—in oligodendrogliomas (n = 190) from the TCGA cohort. The analysis included 131 IDH-mutant, 1p/19q co-deleted oligodendrogliomas, along with molecularly defined IDHmut non-deleted gliomas (n = 47) and IDH wild-type gliomas (n = 22) from the TCGA dataset. IDHwt tumors exhibited the poorest survival outcomes, while no significant survival difference was observed between primary and recurrent cases. RESULTS Mutation burden analysis revealed a low protein-coding mutation count across all subgroups, with IDHmut tumors showing higher SNV counts (average: 20.9 in codel, 19.7 in non-codel) compared to IDHwt (13.3). Neoantigen prediction identified an average of 2.5 MHC-I- and 3.1 MHC-II-restricted neoantigens per patient, predominantly derived from SNVs. IDHmut tumors also expressed more TAAs (average: 180 MHC-I/II in codel, 170 in non-codel) than IDHwt (150). Gene fusions, though rare (average: 1 per patient), were highly immunogenic. Immune landscape analysis using cell type deconvolution and pathway enrichment revealed no significant differences in immune cell infiltration across subgroups. However, immune function scores were elevated in the non-codel and IDHwt groups, with the latter exhibiting upregulated markers of immune dysfunction (e.g., TIM-3, CD39), hinting at therapeutic opportunities through immunotherapy against tumor-specific antigens. In matched primary-recurrent tumors (n = 8), shared mutations persisted, while recurrent tumors acquired new neoantigens and fusions, albeit with reduced TAAs. These findings highlight the heterogeneity of oligodendrogliomas and the potential for combined neoantigen- and TAA-targeted immunotherapies. Future work will leverage single-cell RNA-seq to further elucidate tumor immunogenicity and refine antigen selection for clinical translation. CONCLUSIONS Our findings underscore the potential of personalized immunotherapy approaches and emphasize the need to address immune evasion in recurrent disease.

Authors

Institutions

Publication Details

Journal
Neuro-Oncology
Published
2025-11-01
DOI
https://doi.org/10.1093/neuonc/noaf201.0860
Primary Topic
Glioma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

IMMU-62. The Immune Microenvironment and Antigenic Profile of Oligodendrogliomas: Insights for Next-Generation Immunotherapies

Oleg Yegorov, Duane A. Mitchell, Changlin Yang, Kate Cadelario
Neuro-Oncology
Glioma Diagnosis and Treatment
article

IMMU-62. The Immune Microenvironment and Antigenic Profile of Oligodendrogliomas: Insights for Next-Generation Immunotherapies

Oleg Yegorov, Duane A. Mitchell, Changlin Yang, Kate Cadelario
article en

Abstract

Abstract BACKGROUND Efficient immunotherapies for oligodendrogliomas require a detailed understanding of their immunologic landscape and tumor rejection antigens. METHODS To address this, we applied our in-house Open Reading Frame Antigen Network (O.R.A.N.) pipeline (Yang et al., Genome Medicine 2024) to analyze antigenic epitopes—including single nucleotide variations (SNVs), indels, gene fusions, and tumor-associated antigens (TAAs)—in oligodendrogliomas (n = 190) from the TCGA cohort. The analysis included 131 IDH-mutant, 1p/19q co-deleted oligodendrogliomas, along with molecularly defined IDHmut non-deleted gliomas (n = 47) and IDH wild-type gliomas (n = 22) from the TCGA dataset. IDHwt tumors exhibited the poorest survival outcomes, while no significant survival difference was observed between primary and recurrent cases. RESULTS Mutation burden analysis revealed a low protein-coding mutation count across all subgroups, with IDHmut tumors showing higher SNV counts (average: 20.9 in codel, 19.7 in non-codel) compared to IDHwt (13.3). Neoantigen prediction identified an average of 2.5 MHC-I- and 3.1 MHC-II-restricted neoantigens per patient, predominantly derived from SNVs. IDHmut tumors also expressed more TAAs (average: 180 MHC-I/II in codel, 170 in non-codel) than IDHwt (150). Gene fusions, though rare (average: 1 per patient), were highly immunogenic. Immune landscape analysis using cell type deconvolution and pathway enrichment revealed no significant differences in immune cell infiltration across subgroups. However, immune function scores were elevated in the non-codel and IDHwt groups, with the latter exhibiting upregulated markers of immune dysfunction (e.g., TIM-3, CD39), hinting at therapeutic opportunities through immunotherapy against tumor-specific antigens. In matched primary-recurrent tumors (n = 8), shared mutations persisted, while recurrent tumors acquired new neoantigens and fusions, albeit with reduced TAAs. These findings highlight the heterogeneity of oligodendrogliomas and the potential for combined neoantigen- and TAA-targeted immunotherapies. Future work will leverage single-cell RNA-seq to further elucidate tumor immunogenicity and refine antigen selection for clinical translation. CONCLUSIONS Our findings underscore the potential of personalized immunotherapy approaches and emphasize the need to address immune evasion in recurrent disease.

Neuro-OncologyVol. 27(Supplement_5)
University of Florida (US)
Openalex Percentile: Top 51%
Glioma Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.