Germline and somatic SNVS calling in NGS panel tumor samples: Approaches to optimize tumor only genomic analysis for cancer precision medicine.

Abstract

e13011 Background: Clinical NGS is often limited by tumor only profiling. Discrimination between somatic and likely germline mutations when calling from tumor patient samples is a critical step for clinical genotyping. Many algorithms have been developed for somatic single nucleotide variant (SNV) detection in matched tumor-normal whole genome and whole exome sequencing. Here, we demonstrate approaches of how a cost-effective large gene panel sequencing can be used to call somatic and germline SNVs for tumor only samples. Methods: Tumor, adjacent normal, and matched normal samples are collected from five patients. The somatic mutations were called with GATK Mutect2 in tumor only and adjacent normal. The germline mutations were called individually for all 15 samples with GATK Haplotype caller. To remove germline mutations from tumor only somatic calls, the filters ExAc pop freq, 1000G pop freq, COSMIC were applied on the tumor only somatic calls. PPV (Positive predictive value) for each filter was calculated by dividing the number of somatic mutations in the post-filtering mutation data by the total number of unfiltered mutations. TPR (True Positive Rate, representing sensitivity) was calculated by dividing the number of true somatic mutations in the tumor-only post-filter. Results: Compared with germline mutations called from matched normal, 70% germline mutations were called in RAWE somatic calls. A PPV of 0.71 and a TPR of 0.95 were optimally provided when the filter ExAc pop freq > 0.01 and COSMIC ( > 5 occurrence) applied. For germline mutations called in tumor samples, when compared with those in blood samples and in adjacent normal samples, PPV is 0.99 and TPR is 0.97. For somatic mutations called with tumor-adjacent normal pair mode in Mutect2, PPV is 0.5 and TPR is 0.99. Conclusions: Optimization of tools and parameters in NGS large panels could detect somatic and germline variants with high specificity, sensitivity and accuracy, without matched or adjacent normal. For the germline variants, when adjacent normal is available, it could replace matched normal with high accuracy.