Comparing the Diagnostic Yield of Germline Exome Versus Panel Sequencing in the Diverse Population of the Texas KidsCanSeq Pediatric Cancer Study.

Abstract

To evaluate the relative diagnostic yield of clinical germline genomic tests in a diverse pediatric cancer population. The KidsCanSeq study enrolled pediatric cancer patients across six sites in Texas. Germline analysis included both exome sequencing and a therapy-focused pediatric cancer gene panel. The results were categorized by participants demographics, the presence of pathogenic or likely pathogenic (P/LP) variants, and variants of uncertain significance (VUS) in cancer predisposition genes (CPGs). Pediatric actionable CPGs were defined as those with cancer surveillance recommendations during childhood. Cancer P/LP variants were reported by at least one platform in 103 of 578 (17.8%) participants of which 76 were dominant cancer genes (13.1%) with no significant differences by self-described race or Hispanic ethnicity. However, the proportion of participants with VUS was greater in Asian and African American participants (<i>P</i> = .0029). Diagnostic yield was 16.6% for exome versus 8.5% for panel (<i>P</i> < .0001) with 42 participants with concordant germline results. Exome-only results included P/LP variants in 30 different CPGs in 54 participants, whereas panel-only results included seven participants with a copy number or structural P/LP variants in CPGs. There was no significant difference in diagnostic yield limited to pediatric actionable CPGs (<i>P</i> = .6171). Approximately 18% of a diverse pediatric cancer population had germline diagnostic findings with 50% of P/LP variants reported by only one platform because of CPGs not on the targeted panel and copy number variants (CNVs)/rearrangements not reported by exome. Although diagnostic yields were similar in this diverse population, increases in VUS results were observed in Asian and African American populations. Given the clinical significance of CNVs/rearrangements in this cohort, detection is critical to optimize germline analysis of pediatric cancer populations.