Abstract 3275: Comparison of somatic variant interpretation results between human experts and automated classification using AMP/ASCO/CAP guidelines
Authors: Niroshan Nadarajah, Manja Meggendorfer, Claudia Haferlach, Wolfgang Kern, Torsten Haferlach
Journal: Cancer Research (2018)

Abstract Introduction: Evaluating the pathogenicity of a variant is challenging given the plethora of types of genetic evidence that laboratories have to consider. Deciding how to weigh each type of evidence is difficult, and standards are needed. In 2017, AMP/ASCO/CAP released a joint consensus recommendation proposing a four-tiered system to categorize somatic sequence variations based on their clinical significance in cancer diagnosis, prognosis, and/or therapeutic. Aim: Evaluate how the AMP/ASCO/CAP guidelines compare to an accredited laboratory approach to variant classification and explore the variance in the use and interpretation of the pathogenicity criteria. Identifying disease-contributory variants for various human genetic diseases will greatly improve diagnosis and facilitate development of therapies. Patients and Methods: 50 cases with myeloid malignancies were selected, analyzed either with a 26 genes myeloid panel (ThunderStorm Target Enrichment library; Raindance, Billerica, MA) or a 63 genes panel (TruSeq Custom Amplicon; Illumina, San Diego, CA). Alignment and Variant calling was performed with JSI SeqPilot (JSI Medisys, Ettenheim, Germany). Molecular geneticists in the lab annotated each variant manually in a 3-tier system (pathogenic, uncertain significance, benign) given the lab's SOP for variant classification. Each variant was checked against the following databases: COSMIC (v76), ClinVar, dbSNP (v147) and IARC TP53 (r17). Population frequency information was extracted from ExAC. Mutation impact prediction was performed using PolyPhen-2, SIFT and VEP. Results: Among the 50 cases 681 variants were classified during routine workup according to SOPs accredited by EN ISO15189, subsequent to the elimination of sequencing artefacts. 405 were classified as benign, 52 with variant of uncertain significance (VUS) and 224 as pathogenic. Using the computed classification yielded 377 Tier IV (Benign), 184 Tier III (Unknown clinical significance), 93 Tier II (Potential clinical significance) and 27 Tier I (Strong clinical significance). To be able to compare, Tier I and II were binned. In 80% (542/681) of instances both approaches are concordant. 4 variants classified diagnostically discrepant (3 VUS to Tier I/II, 1 benign variant to Tier II) (Table 1). Manual interrogation revealed these were difficult variants with scarce public data and poor concordance of prediction tools. Conclusion: Systematic evaluation of an automated classification based on AMP/ASCO/CAP with manual curated data found a concordance rate of 80%. The automated approach seems to be more cautious, thus the bias towards more VUS calls, which is preferable to miscalls. The guidelines seem to yield results sufficiently good for clinical use, especially for labs with little experience in variant classification and a big step forward regarding standardization. Citation Format: Niroshan Nadarajah, Manja Meggendorfer, Claudia Haferlach, Wolfgang Kern, Torsten Haferlach. Comparison of somatic variant interpretation results between human experts and automated classification using AMP/ASCO/CAP guidelines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3275.