BackgroundThe American College of Medical Genetics and American College of Pathologists (ACMG/AMP) variant classification guidelines for clinical reporting are widely used in diagnostic laboratories for variant interpretation. The ACMG/AMP guidelines recommend complete concordance of predictions among all in silico algorithms used without specifying the number or types of algorithms. The subjective nature of this recommendation contributes to discordance of variant classification among clinical laboratories and prevents definitive classification of variants.ResultsUsing 14,819 benign or pathogenic missense variants from the ClinVar database, we compared performance of 25 algorithms across datasets differing in distinct biological and technical variables. There was wide variability in concordance among different combinations of algorithms with particularly low concordance for benign variants. We also identify a previously unreported source of error in variant interpretation where in silico predictions are opposite to the evidence provided by other sources. We identified recently developed algorithms with high predictive power and robust to variables like disease mechanism, gene constraint and mode of inheritance, although poorer performing algorithms are more frequently used based on review of the clinical genetics literature (2011-2017).ConclusionsOur analyses identify algorithms with high performance characteristics independent of underlying disease mechanisms. We describe combinations of algorithms with increased concordance that should improve in silico algorithm usage during assessment of clinically relevant variants using the ACMG/AMP guidelines.

Background Pediatric hepatocellular carcinoma (HCC) is a rare liver tumor in children with a poor prognosis. Comprehensive molecular profiling to understand the underlying genomic drivers of this tumor has not been completed, and it is unclear whether nonfibrolamellar pediatric HCC is more genomically similar to hepatoblastoma or adult HCC. Procedure To characterize the molecular landscape of these tumors, we analyzed a cohort of 15 pediatric non‐FL‐HCCs by sequencing a panel of cancer‐associated genes and conducting copy‐number and gene‐expression analyses. Results We detected multiple types of molecular alterations in Wnt signaling genes, including APC inversion, AMER1 somatic mutation, and most commonly CTNNB1 intragenic deletions. There were multiple alterations to the telomerase pathway via TERT activation or ATRX mutation. Therapeutically targetable activating mutations in MAPK/ERK signaling pathway genes, including MAPK1 and BRAF, were detected in 20% of tumors. TP53 mutations occurred far less frequently in our pediatric HCC cohort than reported in adult cohorts. Tumors arising in children with underlying liver disease were found to be molecularly distinct from the remainder and lacking detectable oncogenic drivers, as compared with those arising in patients without a history of underlying liver disease; the majority of both types were positive for glypican‐3, another potential therapeutic target. Conclusion Our study revealed pediatric HCC to be a molecularly heterogeneous group of tumors. Those non‐FL‐HCC tumors arising in the absence of underlying liver disease harbor genetic alterations affecting multiple cancer pathways, most notably Wnt signaling, and share some characteristics with adult HCC.

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