Abstract
Background: Novel biomarkers and molecular monitoring tools hold potential to improve outcome for patients following resection of pancreatic ductal adenocarcinoma (PDAC). We hypothesized that the combined longitudinal analysis of mutated cell-free plasma KRAS (cfKRASmut) and CA 19-9 during adjuvant treatment and follow-up might more accurately predict disease course than hitherto available parameters.
Methods: Between 07/2015 and 10/2018, we collected 134 plasma samples from 25 patients after R0/R1-resection of PDAC during adjuvant chemotherapy and post-treatment surveillance at our institution. Highly sensitive discriminatory multi-target ddPCR assays were employed to screen plasma samples for cfKRASmut. cfKRASmut and CA 19-9 dynamics were correlated with recurrence-free survival (RFS) and overall survival (OS). Patients were followed-up until 01/2020.
Results: Out of 25 enrolled patients, 76% had undergone R0 resection and 48% of resected PDACs were pN0. 17/25 (68%) of patients underwent adjuvant chemotherapy. Median follow-up was 22.0 months, with 19 out of 25 (76%) patients relapsing during study period. Median RFS was 10.0 months, median OS was 22.0 months. Out of clinicopathologic variables, only postoperative CA 19-9 levels and administration of adjuvant chemotherapy correlated with survival endpoints. cfKRASmut. was detected in 12/25 (48%) of patients, and detection of high levels inversely correlated with survival endpoint. Integration of cfKRASmut and CA 19-9 levels outperformed either individual marker. cfKRASmut outperformed CA 19-9 as dynamic marker since increase during adjuvant chemotherapy and follow-up was highly predictive of early relapse and poor OS.
Conclusions: Integrated analysis of cfKRASmut and CA 19-9 levels is a promising approach for molecular monitoring of patients following resection of PDAC. Larger prospective studies are needed to further develop this approach and dissect each marker's specific potential.
Keywords: Cell-free DNA (cfDNA); Circulating KRAS (cfKRAS mut); Droplet digital PCR (ddPCR); Liquid biopsy; Molecular monitoring; Pancreatic cancer; Prognostic biomarkers.