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

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