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Objectives: We have recently described a predictive/prognostic model for ovarian cancer, exploiting commonly available clinico-pathological parameters and the ovarian serum biomarkers mesothelin (MSL), human epididymis protein 4 (HE4) and cancer-antigen 125 (CA125). Considering urine as a prototype non-invasive sample, we investigated whether serum levels of these biomarkers are mirrored in urine and compared their clinical relevance in matched serum vs. urine samples. Methods: MSL, HE4 and CA125 were quantified in urinary (n=172) and matched serum samples (n=188) from ovarian cancer patients (n=192) using the Lumipulse® G chemiluminescent enzyme immunoassay (Fujirebio). Results: While absolute concentrations of MSL or CA125 were higher in serum than in matched urine samples, HE4 concentrations were considerably higher in urine than in serum. Nonetheless, the levels of all three biomarkers strongly correlated between matched serum vs. urine samples and were unrelated to BRCA1/2 mutational status. Consequently, prediction of surgical outcome or relapse/death by MSL, HE4 or CA125 was similarly efficient among urinary- vs. serum-based detection. HE4 provided the highest capacity to predict surgical outcome or relapse/death among both body fluids (urine: AUC=0.854; serum: AUC=0.750, respectively). All clinically relevant findings regarding the investigated urinary biomarkers were equally reproducible among raw vs. creatinine-normalized datasets, suggesting that normalization may have subordinate priority for urine-based analysis of these biomarkers. Conclusion: We report that the capacity of MSL, HE4 and CA125 to predict surgical outcome and relapse/death is equivalent between serum vs. urine-based detection. Urinary biomarkers, in particular HE4, may provide an additional dimension for prognostic modeling in ovarian cancer.
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OBJECTIVES: We analysed whether temporal heterogeneity of ctDNA encodes 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 primary tumor biopsies vs. ctDNA, TP53 variants were the most commonly shared somatic alterations. Up to three variant clusters were detected in each tumor biopsy, 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 abdominal 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 and were undetectable at relapse. ctDNA private variants were present among both patterns, with some of them mirroring subclonal expansions after chemotherapy. CONCLUSIONS: We demonstrate that tracing the temporal heterogeneity of ctDNA, even below exome scale resolution, deciphers evolutionary trajectories in ovarian cancer. Furthermore, we describe two evolutionary patterns that may help to identify relapse seeding clones for targeted therapy.