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Updated: May 1, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Published on: October 18, 2013
Next generation sequencing identifies novel gene alterations with potential prognostic relevance in pediatric cancer:
Yuhan Ma1, Mingwei Su2, Xiaoshan Liu1
1Pediatric Hematology/Oncology, Children's Medical Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Background:
Next generation sequencing (NGS) has driven the development of precision oncology. While adult cancer genomics has been extensively studied, pediatric cancer, particularly among Asian populations, has received less attention.
Methods:
We screened gene alteration profiles of 99 pediatric cancer patients using the targeted NGS panel and compared the results with those from Western cohorts. The relationship between genes and clinical characteristics was also analyzed.
Results:
The most frequently mutated gene was KMT2D (18.2%), followed by TP53 (11.1%) and DICER1 (9.1%). The frequency of KMT2D mutations in our cohort is significantly higher than in Western cohorts, whereas TP53 mutations showed no significant difference. Pathogenic or likely pathogenic (P/LP) germline mutations were identified in only 3.5% of the patients. Notably, 69%-75% of patients had at least one genomic alteration with potential clinical significance. In neuroblastoma (NB), the most commonly altered genes were MYCN (7/48), DICER1 (6/48), ARID1B, EGFR, KMT2D, and TCF3 (5/48). In a subset of intermediate-/high-risk NB patients (n = 33), MYCN amplification was associated with disease progression during induction chemotherapy, and gene alterations in the MAPK pathway were associated with poor survival. We also identified novel alterations in specific tumor types, including SFPQ-TACC1 fusion in NB.
Conclusions:
Our findings enhance understanding of the genomic landscape of Chinese pediatric cancer populations. Further research is required to validate these findings and fully explore the potential of genomic data to improve outcomes for pediatric cancer patients.
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