IMMU-79. An Updated Analysis of PD1 and Immune Pathway Activity in Malignant Pediatric Central Nervous System (CNS) Tumors: A Pediatric Brain Tumor Consortium (PBTC) Study, PBTC-N13

Abstract BACKGROUND Responses to immunotherapy in pediatric brain cancers have thus far been disappointing. We, therefore, sought to understand the immunophenotype/immune environment in these tumors. METHODS The Pediatric Brain Tumor Consortium studied 100 patient samples from ependymomas, high-grade gliomas (HGGs), medulloblastomas, and historically-diagnosed supratentorial primitive neuroectodermal tumor [sPNET]). PD-1/PD-L1 expression were determined by immunohistochemistry as previously presented, and an updated study of immune-related gene expression was analyzed via a Nanostring immunologic codeset. Immune scores were calculated with a GSVA ssGSEA algorithm, and hierarchical clustering visualized by pheatmap and ComplexHeatmap. Tumor-type specific subgrouping was applied using the scores generated from Consensus Non-negative Matrix factorization (cNMF). RESULTS Approximately half of the tumors expressed PD-1 (52/100) or PD-L1 (44/100) at an intensity score of at least 1/5, with higher scores in HGG. Ependymoma and HGG demonstrated more robust immune cell signatures, while medulloblastoma and sPNET demonstrated decreased monocytic and myeloid cell signatures. Reclustering delineated three immune-related subgroups in each tumor with unique expression profiles. Ependymoma group E1 was enriched for Th17 cell differentiation, and E3 with EGFR tyrosine kinase inhibitor resistance. HGG G1 pathways related to IL-17 signaling, NOD-like receptor signaling, and cytokine signaling, while G3 was enriched for PI3K-Akt signaling and ECM-receptor interaction. Medulloblastoma M1 and M2 was enriched for pathways related to pro-inflammatory genes, and M3 enriched with PI3K-Akt signaling and NK cell mediated cytotoxicity. sPNET P1 and P2 was also enriched for pathways related to immune system genes, while P3 showed upregulated HSC lineage and antigen presentation pathways. CONCLUSION The addition of immune expression profiling in our study to PD-1/PD-L1 IHC scores enables better understanding of relevant immune-specific genes, with better characterization of noteworthy immune alterations that may aid in designing more effective immunotherapy for pediatric brain cancers.

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Journal
Neuro-Oncology
Published
2025-11-01
DOI
https://doi.org/10.1093/neuonc/noaf201.0877
Primary Topic
Glioma Diagnosis and Treatment
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article
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article

IMMU-79. An Updated Analysis of PD1 and Immune Pathway Activity in Malignant Pediatric Central Nervous System (CNS) Tumors: A Pediatric Brain Tumor Consortium (PBTC) Study, PBTC-N13

Jason Fangusaro, Natasha Pillay‐Smiley, Jennifer H. Yearley, Changlin Yang et al.
Neuro-Oncology
Glioma Diagnosis and Treatment
article

IMMU-79. An Updated Analysis of PD1 and Immune Pathway Activity in Malignant Pediatric Central Nervous System (CNS) Tumors: A Pediatric Brain Tumor Consortium (PBTC) Study, PBTC-N13

Jason Fangusaro, Natasha Pillay‐Smiley, Jennifer H. Yearley, Changlin Yang, Eugene Hwang, Alicia Lenzen, Sridharan Gururangan, Sonia Partap, Tong Lin, Maryam Fouladi, Ira J. Dunkel, Wendy M. Blumenschein, Scott Raskin, Duane A. Mitchell, Arzu Onar-Thomas
article en

Abstract

Abstract BACKGROUND Responses to immunotherapy in pediatric brain cancers have thus far been disappointing. We, therefore, sought to understand the immunophenotype/immune environment in these tumors. METHODS The Pediatric Brain Tumor Consortium studied 100 patient samples from ependymomas, high-grade gliomas (HGGs), medulloblastomas, and historically-diagnosed supratentorial primitive neuroectodermal tumor [sPNET]). PD-1/PD-L1 expression were determined by immunohistochemistry as previously presented, and an updated study of immune-related gene expression was analyzed via a Nanostring immunologic codeset. Immune scores were calculated with a GSVA ssGSEA algorithm, and hierarchical clustering visualized by pheatmap and ComplexHeatmap. Tumor-type specific subgrouping was applied using the scores generated from Consensus Non-negative Matrix factorization (cNMF). RESULTS Approximately half of the tumors expressed PD-1 (52/100) or PD-L1 (44/100) at an intensity score of at least 1/5, with higher scores in HGG. Ependymoma and HGG demonstrated more robust immune cell signatures, while medulloblastoma and sPNET demonstrated decreased monocytic and myeloid cell signatures. Reclustering delineated three immune-related subgroups in each tumor with unique expression profiles. Ependymoma group E1 was enriched for Th17 cell differentiation, and E3 with EGFR tyrosine kinase inhibitor resistance. HGG G1 pathways related to IL-17 signaling, NOD-like receptor signaling, and cytokine signaling, while G3 was enriched for PI3K-Akt signaling and ECM-receptor interaction. Medulloblastoma M1 and M2 was enriched for pathways related to pro-inflammatory genes, and M3 enriched with PI3K-Akt signaling and NK cell mediated cytotoxicity. sPNET P1 and P2 was also enriched for pathways related to immune system genes, while P3 showed upregulated HSC lineage and antigen presentation pathways. CONCLUSION The addition of immune expression profiling in our study to PD-1/PD-L1 IHC scores enables better understanding of relevant immune-specific genes, with better characterization of noteworthy immune alterations that may aid in designing more effective immunotherapy for pediatric brain cancers.

Neuro-OncologyVol. 27(Supplement_5)
Northwestern University (US), Cincinnati Children's Hospital Medical Center (US), Merck & Co., Inc., Rahway, NJ, USA (United States) (US), St. Jude Children's Research Hospital (US), Nationwide Children's Hospital (US), Memorial Sloan Kettering Cancer Center (US), Emory University (US), Palo Alto University (US), University of Florida (US), BeiGene (China) (CN), Center for Cancer and Blood Disorders (US), Aflac (United States) (US), Deltagen (United States) (US), Lurie Children's Hospital (US), Children's Healthcare of Atlanta (US), Robert H. Lurie Comprehensive Cancer Center of Northwestern University, University of Cincinnati Medical Center (US), Stanford University (US)
Openalex Percentile: Top 51%
Glioma Diagnosis and Treatment
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