NCI Office of Data Sharing (ODS) Data Jamboree (Abstract Submissions): Submission #48
Submission information
Submission Number: 48
Submission ID: 145623
Submission UUID: 0b1c962c-6f95-4976-8103-9fdd9f0f2b50
Submission URI: /nci/ods-data-jamboree/abstractsubmissions
Submission Update: /nci/ods-data-jamboree/abstractsubmissions?token=8b6FqvvDxG81GQkuRMkPR0NXUd_z4xpAsIpdEJBbgeg
Created: Fri, 06/27/2025 - 12:47
Completed: Fri, 06/27/2025 - 12:47
Changed: Fri, 06/27/2025 - 14:32
Remote IP address: 10.208.28.84
Submitted by: Anonymous
Language: English
Is draft: No
Presenter Information
Sapna
{Empty}
Oberoi
MD, MSc
Assistant Professor
CancerCare Manitoba
Winnipeg, Manitoba
{Empty}
Abstract Information
Building specific disease cohorts, or visualization techniques
soft tissue sarcoma, tumor microenviornment, immune classification, pediatrics
Immune Characterization of Pediatric Soft Tissue Sarcomas
Rationale: Pediatric Soft-tissue sarcomas (STS) represent a rare and histologically diverse group of cancers with variable clinical behaviour and limited responsiveness to immune checkpoint blockade. While recent transcriptomic analyses in adult STS have led to a reproducible immune-based classification, comprising five tumor microenvironment (TME) phenotypes ranging from immune-low to immune-high and vascularized subtypes, relevance of these findings to pediatric STS remains unknown. In adult STS, immune-high, B cell–enriched phenotype (class E), characterized by the presence of tertiary lymphoid structures (TLSs), was associated with favorable survival and responsiveness to PD-1 blockade. These observations underscore the potential of immune phenotyping to guide risk stratification and immunotherapeutic decision-making in pediatric STS.
Methods: We propose to characterize the immune landscape of pediatric STS using bulk RNA sequencing data from patients enrolled in the Molecular Characterization Initiative of the National Cancer Institute and the Children’s Oncology Group. Our analytic framework will follow the approach described by Petitprez et al. (PMID: 31942077), applying a transcriptomic-based classification scheme to assess the applicability of adult-derived immune subtypes in pediatric disease. TME composition will be inferred using the MCPcounter algorithm, which estimates the relative abundance of key immune and stromal cell populations. Results will be compared with those obtained from other computational methods, including xCell, CIBERSORT and deconvolution-based algorithms such as QuanTIseq. Immune phenotypes will be correlated with clinicopathologic features, genomics data and clinical outcomes data available through the Childhood Cancer Data Initiative (CCDI). In parallel, pathologists will evaluate the H & E slides to assess relevant morphological features that may be associated with TME clustering and the presence of TLSs in these tumors.
Expected Outcome: This work aims to define the immune architecture of pediatric STS, assess the translatability of adult-derived immune subtypes, and inform the development of immune-informed therapeutic strategies for children and adolescents with sarcoma.
Methods: We propose to characterize the immune landscape of pediatric STS using bulk RNA sequencing data from patients enrolled in the Molecular Characterization Initiative of the National Cancer Institute and the Children’s Oncology Group. Our analytic framework will follow the approach described by Petitprez et al. (PMID: 31942077), applying a transcriptomic-based classification scheme to assess the applicability of adult-derived immune subtypes in pediatric disease. TME composition will be inferred using the MCPcounter algorithm, which estimates the relative abundance of key immune and stromal cell populations. Results will be compared with those obtained from other computational methods, including xCell, CIBERSORT and deconvolution-based algorithms such as QuanTIseq. Immune phenotypes will be correlated with clinicopathologic features, genomics data and clinical outcomes data available through the Childhood Cancer Data Initiative (CCDI). In parallel, pathologists will evaluate the H & E slides to assess relevant morphological features that may be associated with TME clustering and the presence of TLSs in these tumors.
Expected Outcome: This work aims to define the immune architecture of pediatric STS, assess the translatability of adult-derived immune subtypes, and inform the development of immune-informed therapeutic strategies for children and adolescents with sarcoma.