PURPOSE: Relapsed/refractory pediatric cancers show poor prognosis; however, their genomic patterns remain unknown. To investigate the genetic mechanisms of tumor relapse and therapy resistance, we characterized genomic alterations in diagnostic and relapsed lesions in patients with relapsed/refractory pediatric solid tumors using targeted deep sequencing. PATIENTS AND METHODS: A targeted sequencing panel covering the exons of 381 cancer genes was used to characterize 19 paired diagnostic and relapsed samples from patients with relapsed/refractory pediatric solid tumors. RESULTS: The mean coverage for all samples was 930.6× (SD = 213.8). Among the 381 genes, 173 single nucleotide variations (SNVs)/insertion-deletions (InDels), 100 copy number alterations, and 1 structural variation were detected. A total of 72.6% of SNVs in primary tumors were also found in recurrent lesions, and 27.2% of SNVs in recurrent tumors had newly occurred. Among SNVs/InDels detected only in recurrent lesions, 71% had a low variant allele fraction (<10%). Patients were classified into three categories based on the mutation patterns after cancer treatment. A significant association between the major mutation patterns and clinical outcome was observed. Patients whose relapsed tumor had fewer mutations than the diagnostic sample tended to be older, had longer progression-free survival, and achieved complete remission after relapse. Contrastingly, patients whose genetic profile only had concordant mutations without any change had the worst outcome. CONCLUSIONS: We characterized genomic changes in recurrent pediatric solid tumors. These findings could help to understand the biology of relapsed childhood cancer and to develop personalized treatment based on their genetic profile.
Clinical Relevance of Genomic Changes in Recurrent Pediatric Solid Tumors
Boram Lee,Ji Won Lee,J. Shim,Je-Gun Joung,J. Yun,J. Bae,Hyun-Tae Shin,K. Sung,W. Park
Published 2018 in Translational Oncology
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- Publication year
2018
- Venue
Translational Oncology
- Publication date
2018-09-11
- Fields of study
Medicine
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- External record
- Source metadata
Semantic Scholar, PubMed
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