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Circulating cell‐free DNA (cfDNA) contains circulating tumor DNA (ctDNA), which can be obtained from serial liquid biopsies to enable tumor genome analysis throughout the course of treatment. We investigated cfDNA and mutant ctDNA as potential biomarkers to predict the best outcomes of regorafenib‐treated metastatic colorectal cancer (mCRC) patients. We analyzed longitudinally collected plasma cfDNA of 43 mCRC patients prospectively enrolled in the phase II TEXCAN trial by IntPlex qPCR. Qualitative (KRAS, NRAS, BRAFV600E mutations) and quantitative (total cfDNA concentration, mutant ctDNA concentration, mutant ctDNA fraction) parameters were correlated with overall survival (OS) and progression‐free survival (PFS). When examined as classes or continuous variables, the concentrations of total cfDNA, mutant ctDNA, and, partly, mutant ctDNA fraction prior to regorafenib treatment correlated with OS. Patients with baseline cfDNA > 26 ng·mL−1 had shorter OS than those with cfDNA value below this threshold (4.0 vs 6.9 months; log‐rank P = 0.0366). Patients with baseline mutant ctDNA > 2 ng·mL−1 had shorter OS than those with mutant ctDNA below this threshold (log‐rank P = 0.0154). We show that pretreatment cfDNA and mutant ctDNA levels may identify mCRC patients that may benefit from regorafenib treatment., Circulating cell‐free DNA (cfdNA) was extracted from longitudinal blood collection of 43 mCRC patients treated by regorafenib. Qualitative (RAS, BRAFV600E mutations) and quantitative (cfDNA concentration, mutant circulating tumor DNA (ctDNA) concentration, mutant ctDNA fraction) parameters were correlated with survival. We show that pretreatment cfDNA and mutant ctDNA levels may identify mCRC patients that may benefit from regorafenib treatment.

Background Circulating DNA (cfDNA) has emerged as a potential biomarker in cancer, and is the subject of extensive studies in translational and clinical research. Our group has been interested in its implication and clinical significance in the field of oncology for many years, and is now focused on evaluating its potential for early cancer detection. Methods We recently developed a screening test (MNR: Multi Normalized Ratio), based on various cfDNA parameters determined by a specific q-PCR based method, targeting both nuclear and mitochondrial sequences. Results When applied to the supernatant of cell culture, the MNR had a discriminative potential of 100% between normal and cancer cell lines. An extensive evaluation of this test was carried out in plasma samples of 289 healthy subjects and 987 cancer patients (CRC, breast, liver, pancreatic, ovarian) of all stages. Preliminary results revealed a high potential with an AUC of 0.81 (0.78-0.84, 95% CI), a 70% sensitivity (Se) and 77% specificity (Sp). In breast cancer (N = 169), an AUC of 0.82 (0.78-0.86, 95% CI) with 72% Se and 80% Sp were observed. In all stages CRC patients (N = 795), the results showed an AUC of 0.80 (0.78-0.84, 95%, CI), 75% Se and 70% Sp; for CRC stages 0/I/II (N = 426), an AUC of 0.79 (0.75-0.82, 95% CI), 70% Se and 72% Sp; and for CRC stage IV (N = 186), a 0.86 AUC (0.82-0.89, 95% CI) with 75% Se and 80% Sp. When combining the MNR to a total cfDNA concentration threshold value (AUC = 0.81 (0.79-0.83, 95% CI), 72% Se and 76% Sp for all stage cancers (N = 987)), in a test cohort of 173 stages 0/I/II CRC patients and 132 healthy individuals, we increased the sensitivity and specificity to 74% and 95% respectively. Furthermore we recently discovered that cfDNA fragmentation, as determined by Whole Genome Sequencing using either double or single strand library, is also a parameter enabling discrimination between healthy and cancer individuals. Conclusions The implementation of a multi-parametric test combining total cfDNA quantification, MNR and fragmentation biomarkers, with help of a decision tree in machine learning, is currently on-going. Our data suggest that our strategy in targeting cfDNA structural features might be powerful for early cancer detection, and appears as an alternative or a synergistic combination to the detection of mutations. Legal entity responsible for the study Alain R. Thierry - INSERM (Institut national de la sante et de la recherche medicale). Funding MSDAvenir - Mitest / Alain R. Thierry is supported by INSERM (Institut national de la sante et de la recherche medicale). Disclosure All authors have declared no conflicts of interest.