Clinical Relevance of Genomic Changes in Recurrent Pediatric Solid Tumors

• Main Authors: Boram Lee, Ji Won Lee, Joon Ho Shim, Je-Gun Joung, Jae Won Yun, Joon Seol Bae, Hyun-Tae Shin, Ki Woong Sung, Woong-Yang Park
• Format: Article
• Language: English
• Published: Elsevier 2018-12-01
• Series: Translational Oncology
• Online Access: http://www.sciencedirect.com/science/article/pii/S1936523318303140

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.