NCI Office of Data Sharing (ODS) Data Jamboree (Abstract Submissions): Submission #26

Submission information
Submission Number: 26
Submission ID: 145168
Submission UUID: 8b1eb5cc-833f-4016-b6a6-2ed5b36957f4

Created: Mon, 06/23/2025 - 15:25
Completed: Mon, 06/23/2025 - 15:25
Changed: Mon, 06/23/2025 - 15:25

Remote IP address: 10.208.28.103
Submitted by: Anonymous
Language: English

Is draft: No





Presenter Information
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First Name: Marcin









Middle Initial: {Empty}









Last Name: Cieslik









Degree(s): Ph.D









Position/Title/Career Status: Assistant Professor









Organization: University of Michigan









Organization Address:
Ann Arbor










Email: mcieslik@med.umich.edu









Other (Please Specify): {Empty}













Abstract Information
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Abstract Category: Building specific disease cohorts, or visualization techniques









Abstract Keywords: MI-OncoSeq, immunotherapy, integrative genomics, precision oncology









Abstract Title: Integrative Genomic Analysis of Pediatric Cancer Data from Peds-MI-OncoSeq within the NCI Childhood Cancer Data Initiative (CCDI)









Abstract Summary:
Childhood cancers are rare and genomically diverse, and a lack of centralized data has hindered research progress. This project will leverage the rich genomic and transcriptomic data from the Pediatric Michigan Oncology Sequencing (Peds-MI-OncoSeq) cohort, a key contribution to the NCI's Childhood Cancer Data Initiative (CCDI). We propose a dual-aim study to first, create a comprehensive multi-omic atlas to define the molecular architecture across a range of pediatric malignancies. Second, we will conduct a focused analysis on the neuroblastoma cohort to identify robust molecular biomarkers that predict patient response to anti-GD2 immunotherapy, a standard-of-care treatment. By integrating genomic and transcriptomic data, this work seeks to uncover fundamental cancer biology and produce clinically relevant predictors to improve therapeutic strategies for children with cancer.










Upload Abstract: https://events.cancer.gov/sites/default/files/webform/nci_office_of_data_sharing_abstr/145168/CCDI_proposal.docx