Abstract LB105: Integrated molecular profiling of pediatric brain tumors: Insights into subtypes and biomarker discovery

Abstract Introduction: Medulloblastoma and ependymoma are common pediatric brain tumors, characterized by considerable molecular and clinical diversity. To create a comprehensive reference for these tumors, we gathered bulk RNA sequencing data from 888 medulloblastoma and 370 ependymoma samples. Approach: After correcting for batch effects, normalizing the data, and performing dimensionality reduction and clustering, we developed a unified landscape to analyze gene expression, signaling pathways, gene fusions, and copy number alterations. The observed UMAP clusters were validated with known gene expression, known copy number alterations, and known gene fusions from the literature for each subtype. Results: Our findings revealed distinct clustering patterns, such as two major ependymoma subgroups, EPN-E1 and EPN-E2, each with unique molecular features and gene fusions. In medulloblastoma, we achieved precise categorization of Group 3/4 tumors by subtype, and of SHH tumors based on patient age. Both known gene expression patterns and novel pathways identified by our bulk RNA-seq landscape were validated using single-cell transcriptomics in medulloblastoma patients. Additionally, we developed a pipeline that lands uncharacterized tumor samples onto the landscape, enabling the prediction of their subtype. Conclusion: This landscape offers a critical resource for discovering biomarkers, enhancing diagnoses, and allows the mapping of new patient RNA-seq data onto the reference framework to ensure accurate subtype classification. The landscape is available on Oncoscape, an interactive platform, which supports global access and exploration. Citation Format: Sonali Arora, Nicholas Nuechterlein, Matt Jensen, Gregory Glatzer, Srinidhi Varadharajan, Stephen Mack, Philipp Sievers, Andrey Korshunov, Felix Sahm, Michael Taylor, Eric Holland. Integrated molecular profiling of pediatric brain tumors: Insights into subtypes and biomarker discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB105.

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Publication Details

Journal
Cancer Research
Published
2025-04-25
DOI
https://doi.org/10.1158/1538-7445.am2025-lb105
Primary Topic
RNA modifications and cancer
Type
article
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article

Abstract LB105: Integrated molecular profiling of pediatric brain tumors: Insights into subtypes and biomarker discovery

Eric C. Holland, Andrey Korshunov, Srinidhi Varadharajan, Philipp Sievers et al.
1 links
Cancer Research
RNA modifications and cancer
article

Abstract LB105: Integrated molecular profiling of pediatric brain tumors: Insights into subtypes and biomarker discovery

Eric C. Holland, Andrey Korshunov, Srinidhi Varadharajan, Philipp Sievers, Stephen C. Mack, Matt Jensen, Felix Sahm, Nicholas Nuechterlein, Sonali Arora, Michael D. Taylor, Gregory Glatzer
article en

Abstract

Abstract Introduction: Medulloblastoma and ependymoma are common pediatric brain tumors, characterized by considerable molecular and clinical diversity. To create a comprehensive reference for these tumors, we gathered bulk RNA sequencing data from 888 medulloblastoma and 370 ependymoma samples. Approach: After correcting for batch effects, normalizing the data, and performing dimensionality reduction and clustering, we developed a unified landscape to analyze gene expression, signaling pathways, gene fusions, and copy number alterations. The observed UMAP clusters were validated with known gene expression, known copy number alterations, and known gene fusions from the literature for each subtype. Results: Our findings revealed distinct clustering patterns, such as two major ependymoma subgroups, EPN-E1 and EPN-E2, each with unique molecular features and gene fusions. In medulloblastoma, we achieved precise categorization of Group 3/4 tumors by subtype, and of SHH tumors based on patient age. Both known gene expression patterns and novel pathways identified by our bulk RNA-seq landscape were validated using single-cell transcriptomics in medulloblastoma patients. Additionally, we developed a pipeline that lands uncharacterized tumor samples onto the landscape, enabling the prediction of their subtype. Conclusion: This landscape offers a critical resource for discovering biomarkers, enhancing diagnoses, and allows the mapping of new patient RNA-seq data onto the reference framework to ensure accurate subtype classification. The landscape is available on Oncoscape, an interactive platform, which supports global access and exploration. Citation Format: Sonali Arora, Nicholas Nuechterlein, Matt Jensen, Gregory Glatzer, Srinidhi Varadharajan, Stephen Mack, Philipp Sievers, Andrey Korshunov, Felix Sahm, Michael Taylor, Eric Holland. Integrated molecular profiling of pediatric brain tumors: Insights into subtypes and biomarker discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB105.

Cancer ResearchVol. 85(8_Supplement_2)
National Institutes of Health (US), German Cancer Research Center (DE), Heidelberg University (DE), Fred Hutch Cancer Center (US)
Openalex Percentile: Top 92%
RNA modifications and cancer
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