Genomic Determinants of Clinical Outcomes in Rhabdomyosarcoma
Increased availability of next-generation sequencing has allowed for the genomic characterization of a variety of pediatric tumors, although genomic determinants of response to treatment remain largely unknown. We sought to evaluate the genomic landscape and genomic determinants of clinical outcomes...
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Veröffentlicht in: | Clinical cancer research 2020-03, Vol.26 (5), p.1135-1140 |
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Sprache: | eng |
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Zusammenfassung: | Increased availability of next-generation sequencing has allowed for the genomic characterization of a variety of pediatric tumors, although genomic determinants of response to treatment remain largely unknown. We sought to evaluate the genomic landscape and genomic determinants of clinical outcomes in rhabdomyosarcoma (RMS).
Of 29,067 patients who underwent genomic profiling at our institution using a 468-gene oncopanel with complete records, 87 had RMS, of whom 22 were fusion positive. The 10 most common genetic alterations were associated with locoregional control (LC), disease-free survival (DFS), and overall survival (OS). Tumor mutational burden (TMB), defined as the total number of somatic nonsynonymous mutations normalized to the number of sequenced megabases, was also associated with clinical outcomes.
Median age at diagnosis was 16.4 years and median follow-up, 2.1 years. Patients with fusion-negative RMS had more genomic alterations and a higher TMB than those with fusion-positive RMS (mean number of genomic alterations, 6.0 vs. 2.9;
= 0.007 and mean TMB, 2.6 vs. 1.0;
= 0.01). Genetic alterations in
were associated with worse OS (
= 0.03). High TMB (defined as the top quartile ≥ 2.8) was associated with worse LC (
= 0.05), DFS (
= 0.04), and OS (
= 0.01), with significance retained on multivariable analysis after controlling for risk group, fusion status, and receipt of chemotherapy as per pediatric protocols.
High TMB was associated with worse clinical outcomes in patients with RMS. With further validation, TMB and other genomic classifiers may be combined with traditional clinicopathologic risk factors to guide risk stratification and ultimately treatment decisions. |
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ISSN: | 1078-0432 1557-3265 |
DOI: | 10.1158/1078-0432.ccr-19-2631 |