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Updated: Jul 7, 2026

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Genetic testing for cancer predisposition syndromes in pediatric cancer patients: current practices and
Anja Urbas1, Polona Usaj1, Bostjan Seruga1,2
11Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Background:
Childhood cancer is rare but remains a leading cause of disease-related mortality in children. Unlike adult malignancies, pediatric cancers often arise from inherited or de novo germline variants, with cancer predisposition syndromes (CPS) identified in approximately 7-15% of cases. Recognition of CPS is clinically important, as it affects treatment decisions, surveillance strategies, and family counseling.
Materials And Methods:
Because genetic testing practices for hereditary CPS in pediatric cancer patients vary internationally, we conducted a systematic literature review to summarize current clinical practices and the most recent guidelines for genetic testing in children with cancer. PubMed searches (1994-2025) identified 106 articles; after screening and exclusions, 15 studies were included (13 original studies, one meta-analysis, and one review).
Results:
Included studies reported cohort sizes ranging from 31 to 3,975 participants, mainly pediatric cancer patients. The number of analyzed genes varied widely (1-1,048). Testing approaches ranged from single-gene testing to multigene panel testing, with multi gene panel testing most commonly used. The prevalence of pathogenic or likely pathogenic germline variants ranged from 2.99%to 47.5%, reflecting differences in cohort composition, gene panel size, and genetic testing methodology. Most guidelines recommend genetic testing based on clinical and biological selection criteria, while universal germline testing is generally not supported, except in Sweden, where whole genome sequencing is offered to all pediatric cancer patients.
Conclusions:
Phenotype-driven genetic testing currently provides the best resource-benefit balance, although ongoing technological advances may enable broader universal testing in the future.
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