Significance of distinct liquid biopsy compartments in evaluating somatic mutations for targeted therapy selection in cancer of unknown primary

Abstract

Abstract Cancer of unknown primary (CUP) account for 2-5% of all cancer diagnoses, wherein standard investigations fail to reveal the original tumor site. Basket trials allocate targeted therapeutics based on actionable somatic mutations, independent of tumor entity. These trials, however, mostly rely on variants identified in tissue biopsies from solid tumors. Since liquid biopsies (LB) represent the overall tumor genomic landscape, they may provide an ideal diagnostic source in patients with CUP. The most informative liquid biopsy compartment, however, remains to be identified. We aimed to compare the utility of genomic variant analysis for therapy stratification in CUP patients in two liquid biopsy compartments: circulating cell-free (cf) and extracellular vesicle (ev) DNA. CfDNA and evDNA from 23 patients with CUP were analyzed contemporaneously using a targeted gene panel covering 151 cancer-associated genes. LB revealed a total of 22 somatic mutations in evDNA and/or cfDNA in 11/23 patients. Out of the 22 identified somatic variants, 14 are classified as Tier I druggable somatic variants according to the MetaKB knowledgebase. Comparison of variants identified in evDNA and cfDNA revealed an overlap of 58% of somatic variants in both LB compartments, whereas over 40% of variants were only found in one or the other compartment. In our cohort, we observed substantial overlap between somatic variants identified in evDNA and cfDNA of CUP patients. Nonetheless, interrogation of both LB compartments can potentially increase the rate of druggable alterations, stressing the significance of liquid biopsies for possible primary-independent basket and umbrella trial inclusion. Significance Analysis of genomic variants in liquid biopsies has potential as a diagnostic tool for CUP samples. We compared cfDNA and evDNA by a targeted NGS approach and identified druggable targets that could help to stratify patients for inclusion into clinical trials.