Inference of Germline Mutational Status and Evaluation of Loss of Heterozygosity in High-Depth, Tumor-Only Sequencing Data

Abstract

Purpose Inherited germline defects are implicated in up to 10% of human tumors, with particularly well-known roles in breast and ovarian cancers that harbor BRCA1/2-mutated genes. There is also increasing evidence for the role of germline alterations in other malignancies such as colon and pancreatic cancers. Mutations in familial cancer genes can be detected by high-throughput sequencing, when applied to formalin-fixed paraffin-embedded tumor specimens. However, because of the frequent lack of patient-matched control normal DNA and/or low tumor purity, there is limited ability to determine the genomic status of these alterations (germline v somatic) and to assess the presence of loss of heterozygosity (LOH). These analyses, especially when applied to genes such as BRCA1/2, can have significant clinical implications for patient care. Materials and Methods LOHGIC (LOH-germline inference calculator) is a statistical model selection method to determine somatic versus germline status and predict LOH for mutations identified via clinical grade, high-depth, hybrid capture, tumor-only sequencing. LOHGIC incorporates statistical uncertainties inherent to high-throughput sequencing as well as specimen biases in tumor purity estimates, which we used to assess BRCA1/2 mutations in 1,636 specimens sequenced at Rutgers Cancer Institute of New Jersey. Results Evaluation of LOHGIC with available germline sequencing from BRCA1/2 testing demonstrates 93% accuracy, 100% precision, and 96% recall. This analysis highlights a differential tumor spectrum associated with BRCA1/2 mutations. Conclusion LOHGIC can assess LOH status for both germline and somatic mutations. It also can be applied to any gene with candidate, inherited mutations. This approach demonstrates the clinical utility of targeted sequencing in both identifying patients with potential germline alterations in tumor suppressor genes as well as estimating LOH occurrence in cancer cells, which may confer therapeutic relevance.