Childhood Cancer Data Initiative Annual Symposium (Abstract Registration): Submission #58
Submission information
Submission Number: 58
Submission ID: 150485
Submission UUID: 23993711-100d-4651-8a73-25592ea841e0
Submission URI: /nci/ccdisymposium/abstract
Created: Mon, 09/01/2025 - 15:57
Completed: Mon, 09/01/2025 - 16:02
Changed: Mon, 09/01/2025 - 16:02
Remote IP address: 10.208.24.230
Submitted by: Anonymous
Language: English
Is draft: No
Abstract Submission for Poster Presentation
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Abstract Title:: Next-generation cancer models for pediatric solid cancer.
Abstract::
The Human Cancer Models Initiative (HCMI) is a global initiative founded by the National Cancer Institute (NCI), Cancer Research UK, Wellcome Sanger Institute, and the foundation Hubrecht Organoid Technology. The mission is to generate patient-derived Next-generation Cancer Models (NGCMs) from diverse tumor types, including rare adult and pediatric cancers, as a community resource. Unlike traditional cancer models, NGCMs are cultured under optimized conditions that better preserve the characteristics of the parental tumors. This preservation is validated through molecular and phenotypic analyses of tumor tissue and models, which are shared with the community alongside standard operating procedures (SOPs), informed consent templates, and clinical data case report forms (CRFs).
The Stanford University Cancer Model Development Center (referred to as STAN CMDCs) is one of several CMDCs that ensure the integrity and quality of this initiative. STAN CMDC is dedicated to pediatric solid tumors, emphasizing central nervous system (CNS) tumors, the leading cause of cancer-related death in children. We developed a standardized bioprocessing pipeline which yielded a functional tumor bank, achieving a 60-70% success rate in establishing NGCMs for long-term passaging. We have successfully generated and submitted 85 NGCMs along with case-associated clinical and biospecimen data, as well as internal QC data validating the derived cancer models.
These models partially capture the heterogeneity of pediatric CNS tumors, neuroblastoma, hepatoblastoma, Wilms tumor, and brain metastases from neuroblastoma and rare sarcoma-related cancers. Longitudinal biobanking has identified and characterized novel onco-fusion proteins, rare tumor entities, and recurrences, thereby enhancing therapeutic efficacy and promoting personalized treatment strategies.
Abstract:: {Empty}
Authors::
1. First Name: Emon
Last Name: Nasajpour
Organization: Stanford University
2. First Name: Dena
Last Name: Panovska
Organization: Stanford University
3. First Name: Ruolun
Last Name: Wei
Organization: Stanford University
4. First Name: Conrado
Last Name: Soria
Organization: Frederick National Laboratory for Cancer Research
5. First Name: Eva
Last Name: Tonsing-Carter
Organization: National Cancer Institute
6. First Name: Julyann
Last Name: Perez-Mayoral
Organization: National Cancer Institute
7. First Name: Louis
Last Name: Staudt
Organization: National Cancer Institute
8. First Name: Calvin
Last Name: Kuo
Organization: Stanford University
9. First Name: Daniela
Last Name: Gerhard
Organization: National Cancer Institute
10. First Name: Melissa
Last Name: Porter
Organization: National Cancer Institute
11. First Name: Rachana
Last Name: Agarwal
Organization: Frederick National Laboratory for Cancer Research
12. First Name: Claudia
Middle Initial: K
Last Name: Petritsch
Organization: Stanford University
Presenting Author:: Claudia K Petritsch
Institution:: Stanford University
Email Address:: cpetri@stanford.edu