NCI Office of Data Sharing (ODS) Data Jamboree (Abstract Submissions): Submission #35
Submission information
Submission Number: 35
Submission ID: 145195
Submission UUID: 4ad22263-b9e9-4db7-b969-63474ef113d7
Submission URI: /nci/ods-data-jamboree/abstractsubmissions
Submission Update: /nci/ods-data-jamboree/abstractsubmissions?token=Q326L5-bBgGYEG3I3rgHtN3geyNT0WaobvTRPtE9yhU
Created: Mon, 06/23/2025 - 18:50
Completed: Mon, 06/23/2025 - 18:50
Changed: Mon, 06/23/2025 - 18:50
Remote IP address: 10.208.28.103
Submitted by: Anonymous
Language: English
Is draft: No
Presenter Information
Nicole
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Tignor
Ph.D.
Assistant Professor
Icahn School of Medicine at Mount Sinai
New York
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Abstract Information
Employment of statistical methods or existing computational, mathematical, or informatics tools
Pediatric high-grade glioma, Glycoproteomics, Prognostic biomarkers, Tumor heterogeneity
Cross-Population Survival Analysis (CPSA) to Investigate Glycoproteomic Prognostic Markers in Pediatric High-Grade Glioma
Glycosylation is a critical post-translational modification that influences tumor cell adhesion, migration, and immune evasion, yet its role in pediatric high-grade glioma (HGG) remains poorly understood. Progress in this area is limited by small sample sizes in HGG glycoproteomics and the methodological challenge of disentangling developmental variation from tumor-intrinsic heterogeneity.
We recently developed a computational framework—Cross-Population Survival Analysis (CPSA)—that models molecular abundance as a continuous function of age. This enables interpolation of abundance values across cohorts, providing a bridge between datasets and supporting survival association analysis even when direct abundance measurements are missing or limited.
At this data jamboree, we propose to apply CPSA to characterize the prognostic relevance of glycoproteomic features in pediatric HGG. We will analyze 29 HGG tumors from the Kids First Pediatric Brain Tumor Study and 79 HGG tumors from a separate CBTN-CPTAC pediatric study, jointly profiling 465 glycoproteins and 2,508 glycopeptides. Using a harmonized preprocessing pipeline and sex-stratified Cox regression models, adjusted for age, mutation status, and global protein levels, we will test whether previously identified survival-associated glycopeptides replicate in this independent cohort. In parallel, we will assess whether 539 newly detected glycoproteins and 11,622 glycopeptides expand the repertoire of prognostic markers in pediatric HGG.
This effort will evaluate the reproducibility and generalizability of glycosylation-based survival signals and clarify the role of post-translational regulation in pediatric glioma risk stratification. More broadly, it illustrates how harmonized proteomic profiling and age- and sex-aware modeling via CPSA can advance biomarker discovery in rare pediatric cancers.
We recently developed a computational framework—Cross-Population Survival Analysis (CPSA)—that models molecular abundance as a continuous function of age. This enables interpolation of abundance values across cohorts, providing a bridge between datasets and supporting survival association analysis even when direct abundance measurements are missing or limited.
At this data jamboree, we propose to apply CPSA to characterize the prognostic relevance of glycoproteomic features in pediatric HGG. We will analyze 29 HGG tumors from the Kids First Pediatric Brain Tumor Study and 79 HGG tumors from a separate CBTN-CPTAC pediatric study, jointly profiling 465 glycoproteins and 2,508 glycopeptides. Using a harmonized preprocessing pipeline and sex-stratified Cox regression models, adjusted for age, mutation status, and global protein levels, we will test whether previously identified survival-associated glycopeptides replicate in this independent cohort. In parallel, we will assess whether 539 newly detected glycoproteins and 11,622 glycopeptides expand the repertoire of prognostic markers in pediatric HGG.
This effort will evaluate the reproducibility and generalizability of glycosylation-based survival signals and clarify the role of post-translational regulation in pediatric glioma risk stratification. More broadly, it illustrates how harmonized proteomic profiling and age- and sex-aware modeling via CPSA can advance biomarker discovery in rare pediatric cancers.
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