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SYST-22 INTEGRATING GENE DEPENDENCY INTO A PEDIATRIC-FOCUSED CANCER DATA PORTAL FOR TARGETED THERAPY AND BIOMARKER DISCOVERY
Pediatric solid cancers, particularly those affecting the central nervous system (CNS), are the leading cause of disease-related deaths in children. Despite significant efforts to sequence pediatric solid tumors, they exhibit a "quiescent genome" with a considerably lower mutational burden...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402306/ http://dx.doi.org/10.1093/noajnl/vdad070.124 |
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author | Sun, Claire Ajith, Vikesh Panday, Monty Firestein, Ron |
author_facet | Sun, Claire Ajith, Vikesh Panday, Monty Firestein, Ron |
author_sort | Sun, Claire |
collection | PubMed |
description | Pediatric solid cancers, particularly those affecting the central nervous system (CNS), are the leading cause of disease-related deaths in children. Despite significant efforts to sequence pediatric solid tumors, they exhibit a "quiescent genome" with a considerably lower mutational burden than adult cancers. This leads to fewer actionable drug targets and poor response to cancer immunotherapy agents, including checkpoint inhibitors. As a result, it is imperative to move beyond genetic alterations and adopt a combination of functional and integrative approaches to develop novel, targeted treatments that are specifically designed for pediatric cancers. Over the past five years, the Next-Gen Precision Medicine Program team has devoted its efforts to establishing the Childhood Cancer Model Atlas (CCMA) (Sun, Daniel et al. Cancer Cell 2023). The CCMA is the largest collection of high-risk pediatric solid tumor cell lines globally, presenting a tremendous opportunity to integrate molecular features with functional dependencies using state-of-the-art computational approaches. However, the analysis of -omics level data is often limited to laboratories with specialized bioinformatics capabilities. Therefore, the establishment of the CCMA data portal with user-friendly analytical and visualization capabilities is essential to accelerate data-driven discovery and translational research in pediatric cancer on a global scale. The data portal is designed to simplify reporting, automate manual processes, and enhance the quality, usability, and longevity of the CCMA dataset. Its highlighted features concentrate on customized analysis, informative results, and user-friendly data visualization. Furthermore, by connecting the established models and their original tumor with clinical and molecular endpoints, the data portal enables clinical integration within the Australian molecular tumor board framework. This analytical data portal will enable the generation of new research hypotheses, prioritizes therapeutic opportunities, and supports international collaborative efforts in pediatric cancer. |
format | Online Article Text |
id | pubmed-10402306 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-104023062023-08-05 SYST-22 INTEGRATING GENE DEPENDENCY INTO A PEDIATRIC-FOCUSED CANCER DATA PORTAL FOR TARGETED THERAPY AND BIOMARKER DISCOVERY Sun, Claire Ajith, Vikesh Panday, Monty Firestein, Ron Neurooncol Adv Final Category: Systemic Therapeutics Pediatric solid cancers, particularly those affecting the central nervous system (CNS), are the leading cause of disease-related deaths in children. Despite significant efforts to sequence pediatric solid tumors, they exhibit a "quiescent genome" with a considerably lower mutational burden than adult cancers. This leads to fewer actionable drug targets and poor response to cancer immunotherapy agents, including checkpoint inhibitors. As a result, it is imperative to move beyond genetic alterations and adopt a combination of functional and integrative approaches to develop novel, targeted treatments that are specifically designed for pediatric cancers. Over the past five years, the Next-Gen Precision Medicine Program team has devoted its efforts to establishing the Childhood Cancer Model Atlas (CCMA) (Sun, Daniel et al. Cancer Cell 2023). The CCMA is the largest collection of high-risk pediatric solid tumor cell lines globally, presenting a tremendous opportunity to integrate molecular features with functional dependencies using state-of-the-art computational approaches. However, the analysis of -omics level data is often limited to laboratories with specialized bioinformatics capabilities. Therefore, the establishment of the CCMA data portal with user-friendly analytical and visualization capabilities is essential to accelerate data-driven discovery and translational research in pediatric cancer on a global scale. The data portal is designed to simplify reporting, automate manual processes, and enhance the quality, usability, and longevity of the CCMA dataset. Its highlighted features concentrate on customized analysis, informative results, and user-friendly data visualization. Furthermore, by connecting the established models and their original tumor with clinical and molecular endpoints, the data portal enables clinical integration within the Australian molecular tumor board framework. This analytical data portal will enable the generation of new research hypotheses, prioritizes therapeutic opportunities, and supports international collaborative efforts in pediatric cancer. Oxford University Press 2023-08-04 /pmc/articles/PMC10402306/ http://dx.doi.org/10.1093/noajnl/vdad070.124 Text en © The Author(s) 2023. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Final Category: Systemic Therapeutics Sun, Claire Ajith, Vikesh Panday, Monty Firestein, Ron SYST-22 INTEGRATING GENE DEPENDENCY INTO A PEDIATRIC-FOCUSED CANCER DATA PORTAL FOR TARGETED THERAPY AND BIOMARKER DISCOVERY |
title | SYST-22 INTEGRATING GENE DEPENDENCY INTO A PEDIATRIC-FOCUSED CANCER DATA PORTAL FOR TARGETED THERAPY AND BIOMARKER DISCOVERY |
title_full | SYST-22 INTEGRATING GENE DEPENDENCY INTO A PEDIATRIC-FOCUSED CANCER DATA PORTAL FOR TARGETED THERAPY AND BIOMARKER DISCOVERY |
title_fullStr | SYST-22 INTEGRATING GENE DEPENDENCY INTO A PEDIATRIC-FOCUSED CANCER DATA PORTAL FOR TARGETED THERAPY AND BIOMARKER DISCOVERY |
title_full_unstemmed | SYST-22 INTEGRATING GENE DEPENDENCY INTO A PEDIATRIC-FOCUSED CANCER DATA PORTAL FOR TARGETED THERAPY AND BIOMARKER DISCOVERY |
title_short | SYST-22 INTEGRATING GENE DEPENDENCY INTO A PEDIATRIC-FOCUSED CANCER DATA PORTAL FOR TARGETED THERAPY AND BIOMARKER DISCOVERY |
title_sort | syst-22 integrating gene dependency into a pediatric-focused cancer data portal for targeted therapy and biomarker discovery |
topic | Final Category: Systemic Therapeutics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402306/ http://dx.doi.org/10.1093/noajnl/vdad070.124 |
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