Exploring evolutionary trajectories in ovarian cancer patients by longitudinal analysis of ctDNA

ABSTRACTBackground: We analysed, whether temporal heterogeneity of ctDNA mirrors evolutionary patterns in ovarian cancer.Methods: Targeted sequencing of 275 cancer-associated genes was performed in a primary tumor biopsy and in ctDNA of six longitudinal plasma samples from 15 patients, using the Illumina platform.Results: While there was low overall concordance between the mutational spectrum of the tumor biopsies vs. ctDNA, TP53 variants were the most commonly shared somatic alterations. In the tumor biopsies, up to three variant clusters per patient were detected, likely representing predominant clones of the primary tumor, most of them harbouring a TP53 variant. By tracing these clusters in ctDNA, we propose that liquid biopsy may allow to assess the contribution of ancestral clones of the tumor to relapsed pelvic masses, revealing two evolutionary patterns. In pattern#1, clusters detected in the primary tumor biopsy were likely relapse seeding clones, as they contributed a major share to ctDNA at relapse. In pattern#2, similar clusters were present in tumors and ctDNA; however, they were entirely cleared from liquid biopsy after chemotherapy. ctDNA private variants were present among both patterns with some of them possibly mirroring subclonal expansions after chemotherapy. There was a numerical trend that pattern#1 was prognostically inferior compared to pattern#2.Conclusion: We highlight that temporal heterogeneity of liquid biopsy encodes evolutionary trajectories in ovarian cancer and describe two patterns with a potential prognostic impact. Particularly for patients with pattern#1, we envision that relapse seeding clones for targeted therapy could be identified from a single tumor biopsy.