# Monitoring levels of circulating cell-free DNA in patients with metastatic colorectal cancer as a potential biomarker of responses to regorafenib treatment

Brice Pastor, André Thierry, Julie Henriques, Isabelle Trouilloud, Christophe Tournigand, Jary Marine, Thibault Mazard, Christophe Louvet, Simon Azan, Audrey Bauer, et al.

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## To cite this version:

Brice Pastor, André Thierry, Julie Henriques, Isabelle Trouilloud, Christophe Tournigand, et al. Monitoring levels of circulating cell-free DNA in patients with metastatic colorectal cancer as a potential biomarker of responses to regorafenib treatment. Molecular Oncology, 2021, 15 (9), pp.2401-2411. 10.1002/1878-0261.12972. hal-03216431

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Submitted on 4 May 2021

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DR. ALAIN R THIERRY (Orcid ID: 0000-0002-4632-5404)

PROF. ANTOINE ADENIS (Orcid ID: 0000-0003-3123-9746)

Received Date: 29-Oct-2020

Revised Date: 09-Mar-2021

Accepted Date: 20-Apr-2021

Article type: Research Article

Monitoring levels of circulating cell-free DNA in patients with metastatic colorectal cancer as a potential biomarker of responses to regorafenib treatment

Pastor Brice, André Thierry, Henriques Julie, Trouilloud Isabelle, Tournigand Christophe, Jary Marine, Mazard Thibault, Louvet Christophe, Azan Simon, Bauer Audrey, Roch Benoit, Sanchez Cynthia, Vernerey Dewi, Thierry Alain R, Adenis Antoine

1 Institut de Recherche en Cancérologie de Montpellier (IRCM), INSERM, Université de Montpellier, Montpellier Cancer Institute (ICM), Montpellier, France

2 Sorbonne University and Department of Medical Oncology, Saint-Antoine University Hospital, Paris, France

3 Oncology Multidisciplinary Research Group (GERCOR), Paris, France

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/1878-0261.12972

Molecular Oncology (2020) © 2020 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Accepted Article
4 Methodology and Quality of Life Unit in Oncology, Besançon University Hospital, Besançon, France

5 Medical Oncology Service, Henri Mondor Hospital, AP-HP, Université Paris Est Créteil Créteil, France

6 Bourgogne Franche-Comté University, INSERM, Etablissement Français du Sang Bourgogne Franche-Comté, UMR1098, Interactions Hôte-Greffon-Tumeur/Ingénierie Cellulaire et Génique, Besançon, France

7 Department of Medical Oncology, Besançon University Hospital, Besançon, France

8 Department of Medical Oncology, Montpellier Cancer Institute (ICM), Montpellier, France

9 Department of Medical Oncology, Institut Monsouris, Paris, France

10 Department of Thoracic Oncology, Montpellier University Hospital, Université de Montpellier, Montpellier, France

**Corresponding authors:**

Prof Antoine Adenis, Department of Medical Oncology, Institut régional du Cancer de Montpellier, 208 avenue des Apothicaires, 34000, Montpellier, France; Tel : + 33 4 67 61 47 01; Email: antoine.adenis@icm.unicancer.fr

Alain R. THIERRY, Institut de Recherche en Cancérologie de Montpellier, Inserm U1194, Campus Val d'Aurelle, 208 rue des Apothicaires, 34298 Montpellier Cedex 5, France; Tel: +33 6 63 82 19 94; Email: alain.thierry@inserm.fr

**Running title:** cfDNA in regorafenib-treated mCRC patients

**Keywords:** Colorectal cancer, cfDNA, mutant ctDNA, predictive biomarker, tumor response, regorafenib

**ABBREVIATIONS**

**95% CI:** 95% confidence interval

**C1:** cycle 1

**C2:** cycle 2

**cfDNA:** circulating cell-free DNA
CRC: colorectal cancer

ctDNA: circulating tumor DNA

ECOG PS: eastern cooperative oncology group performance status

EDTA: ethylenediaminetetraacetic acid

EGFR: epidermal growth factor receptor

EOT: end of treatment

EU: european union

HR: hazard ratio

IQR: interquartile range

mCRC: metastatic colorectal cancer

OS: overall survival

PFS: progression-free survival

RECIST: response evaluation criteria in solid tumors

VEGF: vascular endothelial factor

WT: wild type

ABSTRACT

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, BRAF V600E 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 had shorter OS than those with cfDNA value below this threshold (4.0 vs 6.9 months; logrank P=0.0366). Patients with baseline mutant ctDNA >2 ng/mL had
shorter OS than those with mutant ctDNA below this threshold (logrank *P*=0.0154). We show that pre-treatment cfDNA and mutant ctDNA levels may identify mCRC patients that may benefit from regorafenib treatment.
# 1. INTRODUCTION

Colorectal cancer (CRC) is a major cause of morbidity and mortality globally [1]. In 2018, there were nearly 2 million newly diagnosed patients and almost 880 792 deaths. Approximately 50% of patients develop metastasis and most of them require palliative treatment. In that setting, patients with metastatic CRC (mCRC) are treated, concomitantly or sequentially, with different cytotoxic agents such as fluoropyrimidines, oxaliplatin, and irinotecan that may be combined with monoclonal antibodies against vascular endothelial growth factor (VEGF) or epidermal growth factor receptor (EGFR) [2]. The latter combination is restricted to patients with *KRAS* and *NRAS* (RAS) wild-type tumors. In otherwise standard therapies-refractory mCRC patients, oral agents such as trifluridine/tipiracil or regorafenib could be considered [2].

Regorafenib is a multi-tyrosine-kinase inhibitor that induces *in vitro* and *in vivo* anti-angiogenic and cytotoxic activities [3]. It was approved in the European Union (EU) for refractory mCRC based on the report of its activity versus placebo plus best supportive care in the CORRECT and CONCUR phase III clinical trials [4,5]. In these two studies, regorafenib demonstrated a significant improvement in overall survival (OS) in patients with mCRC who progressed on standard therapies [4,5]. However, half of the treated patients experienced tumor progression 2 months after starting treatment, which unnecessarily exposed them to treatment-related adverse events. That toxicity risk could be reduced by adopting a dose-escalation strategy for optimizing regorafenib dosing with comparable activity [6]. In an exploratory study of the pivotal CORRECT trial [4], Tabernero and colleagues (2015) showed a trend towards a better survival for patients treated with regorafenib who presented *KRAS* or *PIK3CA* wild-type genotypes, assessed using tissue DNA or circulating cell-free DNA (cfDNA). Interestingly, they also observed an association between high-baseline cfDNA and reduced median OS [7]. Subsequently, in a retrospective study of 654 patients with mCRC who received regorafenib in a compassionate use program reported by Adenis et al. [8] OS was independently and unfavorably affected by poor performance status, short time from initial diagnosis of metastasis to the start of regorafenib treatment, low initial regorafenib dose, >3 metastatic sites, the presence of the liver metastasis, and tissue *KRAS* mutations. However, there are currently no widely accepted criteria predicting benefits from regorafenib.

Circulating cell-free DNA is a plasma biomarker widely used in oncology [9], notably for detecting *RAS/BRAF* point mutations before the initiation of anti-EGFR agents in mCRC patients [10–15]. Moreover, longitudinally analysis of cfDNA were used to address the temporal and spatial clonal heterogeneity of mCRC patients [16–21].
Phase II TEXCAN trial aimed to evaluate tumor response in refractory, progressing mCRC patients after 2 months of treatment with regorafenib [22]. In the present study, we investigated the clinical activity of regorafenib in those patients according to analysis of circulating cfDNA.

## 2. MATERIAL AND METHOD

### 2.1 *Patients and study design*

TEXCAN (NCT02699073) was a multicenter, prospective, open-label, single-arm phase II trial of patients with mCRC refractory to standard therapy. The study aimed to evaluate the 2-month tumor response to treatment with regorafenib (160 mg once daily for 3 weeks, followed by 1 week off therapy) using different measurement methods. Inclusion/exclusion criteria, study design, study objectives/endpoints, and clinical results have been previously reported [22]. Briefly, 55 patients (the intent-to-treat population) received at least one regorafenib tablet (1 tablet = 40 mg). According to Response Evaluation criteria in Solid Tumors (RECIST) 1.1, no partial and complete responses were observed. The best overall response observed was stable disease in 20/35 patients evaluable for the primary endpoint (i.e. a 2-month clinical response). The median OS was 5.3 months (95% confidence interval [CI] 3.7-8.6). Unlike RECIST, other measurement methods, specifically Choi and modified Choi criteria, did not identify any survival benefit for mCRC patients [22].

The trial was submitted and approved by French regulatory authorities (Agence Nationale de Sécurité du Médicament et des Produits de Santé and the Comité de Protection des Personnes Ile de France VI [French Ethics Committee]; it complies with the Declaration of Helsinki and local regulations, and follows the standards of Good Clinical Practice (ICH-E6 R2). All patients provided a written informed consent. An exploratory analysis included (i) to determine whether a correlation exists between baseline cfDNA levels and survival outcomes, (ii) to evaluate the dynamic of total cfDNA during treatment, and (iii) to determine the RAS/BRAF mutational status in plasma samples, at baseline and at the end of treatment. Of 55 included patients, 12 were excluded because their baseline samples failed to comply with our preanalytical requirements (n = 9) [23,24] or lost during transportation (n = 3), leaving 43 eligible patients for cfDNA analysis (the cfDNA population; Fig. 1).

### 2.2 *Sample preparation*

Blood samples were collected between march 2016 and july 2017 in Ethylenediaminetetraacetic acid (EDTA) tubes and centrifuged at 1,200 x g for 10 minutes at 4°C, within 4 hours after collection. Blood draws for cfDNA analysis were scheduled at baseline (before regorafenib therapy), during treatment (day 15 of Cycles 1 and 2), and at the end of treatment. Plasma samples were immediately stored at 80°C and
transferred on dry ice from the recruiting institutions to our laboratory. Plasma were stored few months (4 months to 24 months) and plasma was centrifuged at 16,000 x g for 10 minutes at 4°C. Total cfDNA was extracted from 1 mL of plasma using the QIAamp DNA Mini Blood Kit (Qiagen) in accordance with the previously published pre-analytic guidelines [23,24] in an elution volume of 130 µL. DNA extracts were kept few days (1 to 3 days) at -20°C until use if not used immediately. Circulating cfDNA was also extracted from 1 mL plasma (Maxwell® RSC instrument) using the cfDNA plasma kit (Promega Corporation) in an elution volume of 130 µL. In total, 136 serial plasma samples from 43 patients were analyzed. We strictly followed the pre-analytical requirements to quantify cfDNA under the best conditions (plasma isolation, plasma storage at -80°C; [23,24]). No significant variation of cfDNA concentration as determined by the wild-type sequence of the *KRAS* (67 bp-length) was found upon storage at -80°C [23–25] for up to three years. We performed analysis of all preanalytical factors such as storage.

## 2.3 IntPlex® analysis of cfDNA

Analysis of cfDNA were done by IntPlex®, an allele-specific blocker quantitative PCR (ASB Q-PCR), which we previously described [10,21,26], according to the MIQE guidelines [27,28]. Q-PCR amplifications were carried out at least in two replicates in a total volume of 25 µL on a CFX96 instrument using the CFX manager software (Bio-Rad). Each PCR reaction was composed of 12.5 µL of IQ Supermix Sybr Green (Bio-Rad), 2.5 µL of DNase-free water (Qiagen) or specific oligoblocker, 2.5 µL of forward and reverse primers (0.3 pmol/mL), and 5 µL of template. Thermal cycling comprised three repeated steps: a hot-start activation step at 95°C for 3 minutes, followed by 40 cycles of denaturation-amplification at 95°C for 10 seconds, then at 60°C for 30 seconds. Melting curves were investigated by increasing the temperature from 60°C to 90°C with a plate reading every 0.2°C. Standard curves were performed for each run with a genomic extract of the DiFi cell line at 1.8 ng/µL of DNA. Each PCR run was carried out with no template control and positive control for each primer set. Positive controls were extracted from cell lines bearing *KRAS/BRAF* or *NRAS* point mutations, or synthetic DNA (Horizon dx). In each single run, negative and positive controls for each tested mutation were included and one standard curve was prepared. Validation of qPCR amplification was performed/span>by melt curve differentiation. CfDNA mutation testing was done without any sensitivity cutoff. When point mutation was found in only one of the two replicates, it was confirmed in triplicate.

## 2.4 Design of cfDNA analyses
Changes of the total level of circulating cfDNA were analyzed in all serial plasma samples (n = 136). Quantification of cfDNA was obtained by amplifying a 67 bp-length wild-type sequence of the *KRAS* gene. Pre and after-treatment plasma mutational analysis was performed (total number of plasma samples, *n* = 70). Point mutations analysis by IntPlex® ASB Q-PCR method included *KRAS* codons 12, 13, 61, 117, and 146, *NRAS* codons 12, 13, and 61, and *BRAF*-mut. Detection and quantification of *KRAS*, *NRAS* or *BRAF* point mutations were done by targeting a short specific mutant sequence (<100 bp length). In this analysis, mutant ctDNA referred to all ctDNA point mutation-bearing sequences within one or more of the analyzed *RAS/BRAF* loci. Mutant ctDNA could be referred to as *RAS*-mutant ctDNA where analysis focused solely on the quantification of *KRAS* and *NRAS* mutated ctDNA sequences. The mutation load corresponded to the proportion of mutant ctDNA fragments bearing a targeted mutation among all cfDNA fragments extracted from plasma. Likewise, the *RAS*-mutation load was expressed as the proportion of *RAS*-mutant ctDNA fragments bearing a targeted mutation in the *KRAS* and *NRAS* genes among all cfDNA fragments in a plasma extract.

## 2.5 Statistical analyses

Qualitative variables were described as percentages and quantitative variables as medians and interquartile ranges (IQR). Tumor response was defined according to RECIST 1.1 criteria. Progression-free survival (PFS) was measured from the start of treatment to the date of progression or death from any cause. Overall survival was defined as the time between the start of the treatment to death from any cause. Patients alive were censored at the last date they were known to be alive. The survival curves for OS were estimated using the Kaplan-Meier method, described with median and 95% CI, and compared using the log-rank test. The associations between patient characteristics and outcomes were estimated using the Cox proportional hazard model and hazard ratio (HR) were provided with their 95% CI. Proportional hazards assumptions were examined graphically by plotting the log-minus-log of survival. Restricted cubic spline methodology was used to estimate the association between continuous variables and OS in order to identify the best transformation to apply in Cox proportional hazard models and cut-off of interest. All analyses were performed using SAS version 9.4 (SAS Institute, Cary NC) and R software version 2.15.2 (R Development Core Team, Vienna, Austria; http://www.r-project.org). P values of less than 0.05 were considered statistically significant and all tests were two-sided. Due to the exploratory setting of the study, P values were not corrected for multiple tests.
## 3. RESULTS

Patient and treatment characteristics are summarized in Table 1. In populations of patients with and without cfDNA measurements, clinical characteristics, treatments and outcomes were similar. Of the 43 patients, 23 were male. The median age was 62.1 years. A total of 39 patients (90.7%) had their primary tumor located on the left side of the colon or rectum. All patients were refractory (or intolerant) to available standard cytotoxic agents. The majority of patients (97.7%) were previously treated with an anti-angiogenic agent (bevacizumab or aflibercept), while over 50% (22/43) received prior anti-EGFR monoclonal antibody (cetuximab or panitumumab) therapy. The available tumor genotyping data showed: mutation of *KRAS* for 16/43, mutation of *NRAS* for 3/29, *NRAS* unknown status for 14/43, mutation of *BRAF* for 5/35, and *BRAF* unknown status for 8/43. Tumor genotyping data were obtained either from resections (*n* = 27) or biopsies (*n* = 13) of primary tumors (*n* = 18) or metastases (*n* = 7). Corresponding cfDNA genotypes are shown in Appendix Table S1. Median treatment duration was 8.29 weeks (IQR, 4.14-15.14). Median OS for all patients was 5.3 months (3.7-8.6). The actual regorafenib median-dose of the prescribed dose was 82.5%. The median cfDNA concentration at baseline (the cfDNA population) was 21.18 ng/mL (IQR, 7.81-62.80).

### 3.1 Relationship between circulating DNA markers and outcomes

Among patients evaluable for tumor response (*n* = 41), those with tumor control as the best response (*n* = 33) had a median baseline cfDNA concentration of 19.4 ng/mL compared to 48.77 ng/mL for those with tumor progression (*n* = 8; *P* = 0.0784; Fig. 2A). To assess the association between survival outcomes and total baseline cfDNA, we tested three different cut-off values. The 26 ng/mL threshold was chosen based on our previous observation that mCRC patients with cfDNA concentration >26 ng/mL had a lower OS than those with a cfDNA concentration below this threshold [29]. Figure 3A shows that patients with baseline cfDNA level of >26 ng/mL had shorter OS than patients with higher cfDNA cutoff level (the median OS 4.0 vs 6.9 months, respectively; logrank *P* = 0.0366). Similar findings were observed with the 65 ng/mL threshold (i.e. third IQR of the cfDNA concentration distributions of the analysis) and 100 ng/mL threshold (Table 2, Fig. 3B). Interestingly, we found that the probability of being alive at 3 months (a key inclusion criteria in mCRC clinical trials) was 83.3% (95% CI 66.61-92.14) and 28.6% (95% CI 4.11-61.15) in patients with the cfDNA level of <100 and ≥100, respectively. Given any association between OS and cfDNA concentrations in its continuous form, we evidenced a positive correlation between these two, the higher the baseline cfDNA concentration, the higher the risk of death (Appendix Fig. S1).
When assessing the RAS-mutant ctDNA concentrations, we observed that mCRC patients with baseline RAS-mutant ctDNA concentration of >2 ng/mL (the threshold established from the relationship between RAS-mutant ctDNA concentrations and the risk of death using the restricted cubic spline regression analysis; data not shown) had shorter OS than those with below the threshold (logrank *P* = 0.0154; Fig. 4). To a lesser extent, patients with a RAS-mutation load of >6% had shorter OS than the rest of patients (logrank *P* = 0.0200; Appendix Fig. S2). No relationship was detected between PFS and any of the circulating DNA markers studied (Table 2).

## 3.2 Changes of cfDNA concentration during treatment

We did not observe any meaningful variation of cfDNA along treatment duration, but an early increase of total cfDNA concentration from baseline to day 15 of cycle 1 (paired analysis, Wilcoxon signed rank test, *P* = 0.0004; Appendix Fig. S3). Moreover, patients without disease control had significantly higher cfDNA concentrations at the end of treatment than those who had stable disease as the best response (*P* = 0.0076; Fig. 2B). In fact, at baseline, on day 15 of Cycle 1, on day 15 of Cycle 2, and at end of treatment, patients with tumor control as best response had the following median cfDNA concentrations: 19.4 ng/mL, 39.29 ng/mL, 40.76 ng/mL, and 36.67 ng/mL, respectively. Also, patients who progressed had the following median cfDNA concentrations: 48.77 ng/mL, 119.73 ng/mL, 65.59 ng/mL and 239.2 ng/mL, respectively (Fig. 2B).

## 3.3 Mutational analysis

At baseline, 33/43 patients (76.7%) showed RAS/BRAF mutations, of whom 30 had only RAS point mutations, two had BRAF<sub>mut</sub> point mutations, and one had both KRAS and BRAF mutations (Appendix Table S1). At the end of treatment, mutation analysis of ctDNA of 27 patients showed RAS and/or BRAF mutations in 25 of theme (92.6%). Plasma analysis showed a high clonal heterogeneity of these patients' tumors with 10/33 and 12/25 mutated patients showing multiple concurrent RAS/BRAF mutations prior and after regorafenib treatment, respectively. Paired analysis revealed that for 23 patients whose ctDNA was mutated at baseline, ctDNA remained mutated at the end of treatment (including five patients with one or more newly point mutations detected during treatment that were not detectable at baseline). Two patients with wild-type tumors acquired mutations by the end of treatment (Appendix Table S1). Only for two
patients the *RAS/BRAF* status remained wild-type at the end of regorafenib treatment. Overall, we found that the mutational status changed from baseline to the end of treatment in 8/27 (29.6%). These changes did not translate into different outcomes from those identified at the baseline (data not shown). The *RAS/BRAF* mutation analysis performed on archival tumor-tissue (gold standard) showed 13 false negatives and 4 false positives when compared to plasma analysis performed prior to the initiation of treatment (Appendix Table S1). The accuracy rate (*RAS/BRAF* mutant vs *RAS/BRAF* non-mutant patients) for the *RAS/BRAF* mutational status between the two assays was 60.5%, with a sensitivity of 83.3% and a specificity of 32%. These comparative values are similar to those previously reported [15], confirming the high sensitivity of the IntPlex detection test. The high number of false negative samples can be due to several reasons: (i) the intra and inter-tumoral heterogeneity of tumors, (ii) the clonal evolution of tumors over time, which may be accentuated by the different types of treatment given to patients, or (iii) the lack of analytical sensitivity of the sequencing techniques used on the tumor tissue.

DISCUSSION

Here we present the ancillary analysis of the phase II TEXCAN study population of regorafenib-treated mCRC patients. In this small, but prospective series, we found that the total cfDNA, RAS-mutant ctDNA, and to a lesser extent the mutational load were correlated with OS, regardless whether this relationship was studied as classes or as continuous variables. For example, patients with total baseline cfDNA ≥26 ng/mL have double risk of death compared with those patients who has baseline cfDNA lower than 26 ng/mL. Although preanalytical requirements are becoming increasingly stringent with time [24], this threshold dichotomizes nicely the outcome of mCRC patients treated with regorafenib. This observation is similar to that of our earlier study [29]. Such inverse correlation between circulating DNA biomarkers and outcome in patients treated with regorafenib has also been reported by others using different methods and various data sets [7,30–33]. We could not however define whether this relationship is driven by the regorafenib use due to the design of our trial, which lacks a control group of patients not treated with regorafenib. Conversely to what has been previously reported [31,34], we were unable to find a clear relationship between circulating DNA biomarkers and PFS. Similarly, although we did not identify any clear relationship between the total cfDNA level at baseline and disease control as the best response, a trend was observed. This could be explained by a weak impact of regorafenib on the tumor due to brevity
of treatment duration related to adverse events and/or lack of the efficacy in this population of heavily
pretreated patients for whom the best response is often tumor stabilization.

In line with other reports [30,31], we found the cfDNA level to be increased 2 weeks after regorafenib onset. It has been suggested that this may be related to the release of cfDNA into the bloodstream secondary to the toxic effects of regorafenib on normal tissues [30]. Vandeputte et al., in their study of 20 mCRC patients treated with regorafenib suggested that cfDNA and mutant ctDNA evolve independently with different patterns of dynamics [30]. Although it is always difficult to do cross-studies comparison using different assays, conditions, and sets of patients, we hypothesize that this discrepancy could be related to the inter-study variability in the number of patients being sensitive to treatment (toxicity on normal tissues and/or an anti-tumor effect) to regorafenib.

As anticipated, we identified several mutational changes in circulating cfDNA (Appendix Table S1) within 8 weeks from the starting dose of regorafenib (i.e. the median duration of regorafenib treatment). Although these changes did not translate into different outcomes, their unprecedented rapid nature in our series is impressive. Based on this observation and of that from our previous report in a similar group of patients undergoing other experimental therapies [21], we suggest that these mutational changes are more likely related to the clinical characteristics of this heavily pretreated mCRC patients rather than to the regorafenib itself.

This study is exploratory and has some limitations and the data should be interpreted carefully. Given the exploratory nature of this analysis, *P* values were not corrected for multiple testing. The sample size for this analysis was small could not counterbalance the lack of power due to the loss of 12 patients (22%) of the native TEXCAN population. Moreover, as regorafenib is more likely to be cytostatic than cytotoxic and as the treatment duration is very short, it would be unreasonable to expect meaningful tumor shrinkage with a sharp decrease in circulating DNA biomarkers in the setting of heavily pretreated mCRC patients.

5. CONCLUSION

In this ancillary study of the prospective TEXCAN phase II trial, we confirmed the potential benefit of cfDNA analysis prior to regorafenib treatment as a suitable method to identify mCRC patients more likely to have the best outcomes. Given our setting and inclusion of heavily pretreated mCRC patients, further investigation involving a larger validation cohort is needed to determine whether or not the 26 ng/mL cutoff for cfDNA analysis is the most optimal to discriminate between patients with poor, good, and the best prognoses.

Acknowledgments
This study is supported by unrestricted research grants from the Fondation ARCAD (Aide et Recherche en Cancérologie Digestive) and Bayer Healthcare Pharmaceutical. Funders have no role in study design, management, analysis, or interpretation of data, nor do they have any role in the writing of the final report. The authors acknowledge the editorial assistance of Magdalena Benetkiewicz (Sc.D; GERCOR).

## Conflict of Interest

AT has served in a consulting/advisory role and/or received honoraria from Amgen, Bristol-Myers Squibb, Chugai, Clovis, Gritstone Oncology, Haliodx, MSD Oncology, Pierre Fabre, Roche/Ventana, Sanofi, Servier and Tesaro/GSK, and has received travel, accommodation, and expenses from Roche/Genentech, MSD Oncology, and Bristol-Myers Squibb. JM has received travel, accommodation, and expenses from Roche/Genentech, and Pfizer. VD has reported a consulting role for GERCOR, HalioDX, Incyte, OSE immunotherapeutics, Janssen Cilag, Pfizer, and Cellprothera. TC has received travel expenses from Roche, Servier, Bayer, and BMS, has received research funding from Bayer, and has reported advisory board fees from Bayer, Roche, and Amgen. LC has reported a consulting/advisory role and receiving honoraria from MSD, Halozyme, Roche, Celgene, Amgen, and Servier; has received travel accommodation from MSD and Roche. TA is a DiaDx stockholder. MT has disclosed research funding from Roche and Amgen; has received honoraria from Amgen, Sanofi, Bristol-Myers Squibb, Sandoz; has reported travel, accommodation and expenses from Amgen, Merck. AA has reported a consulting/advisory role and/or receiving honoraria from Bristol-Myers Squibb, MSD Oncology, and Servier; has received research funding from Bayer Pharmaceuticals. All remaining authors have declared no conflicts of interest.

## Authors' contributions

AT and TA designed the study. PB and TA developed the methodology. PB, AS, BA, RB, and SC did the experiments under the supervision of TA. AT, TI, TC, JM, MT, and LC contributed to the blood and clinical collections. HJ and VD did the statistical analyses. PB, TA, and AA analyzed the data and prepared the manuscript. All of the authors (PB, AT, HJ, TI, TC, JM, MT, LC, AS, BA, RB, SC, VD, TA, and AA) discussed the results and approved the manuscript.

## Data accessibility

The data are not available in a public database or repository. The datasets generated and analyzed in this study are available from the corresponding author on reasonable request.

## REFERENCES

[1] Ferlay, J., Colombet, M., Soerjomataram, I., Mathers, C., Parkin, D. M., Piñeros, M., Znaor, A., and Bray, F., (2019), "Estimating the Global Cancer Incidence and Mortality in 2018: GLOBOCAN Sources and Methods," Int. J. Cancer, **144**(8), pp. 1941–1953.
[2] Van Cutsem, E., Cervantes, A., Adam, R., Sobrero, A., Van Krieken, J. H., Aderka, D., Aranda Aguilar, E., Bardelli, A., Benson, A., Bodoky, G., Ciardiello, F., D'Hoore, A., Diaz-Rubio, E., Douillard, J.-Y., Ducreux, M., Falcone, A., Grothey, A., Gruenberger, T., Haustermans, K., Heinemann, V., Hoff, P., Köhne, C.-H., Labianca, R., Laurent-Puig, P., Ma, B., Maughan, T., Muro, K., Normanno, N., Österlund, P., Oyen, W. J. G., Papamichael, D., Pentheroudakis, G., Pfeiffer, P., Price, T. J., Punt, C., Ricke, J., Roth, A., Salazar, R., Scheithauer, W., Schmoll, H. J., Tabernero, J., Taïeb, J., Tejpar, S., Wasan, H., Yoshino, T., Zaanan, A., and Arnold, D., (2016), "ESMO Consensus Guidelines for the Management of Patients with Metastatic Colorectal Cancer," Ann. Oncol. Off. J. Eur. Soc. Med. Oncol., **27**(8), pp. 1386-1422.

[3] Schmieder, R., Hoffmann, J., Becker, M., Bhargava, A., Müller, T., Kahmann, N., Ellinghaus, P., Adams, R., Rosenthal, A., Thierauch, K.-H., Scholz, A., Wilhelm, S. M., and Zopf, D., (2014), "Regorafenib (BAY 73-4506): Antitumor and Antimetastatic Activities in Preclinical Models of Colorectal Cancer," Int. J. Cancer, **135**(6), pp. 1487-1496.

[4] Grothey, A., Van Cutsem, E., Sobrero, A., Siena, S., Falcone, A., Ychou, M., Humblet, Y., Bouché, O., Mineur, L., Barone, C., Adenis, A., Tabernero, J., Yoshino, T., Lenz, H.-J., Goldberg, R. M., Sargent, D. J., Cihon, F., Cupit, L., Wagner, A., Laurent, D., and CORRECT Study Group, (2013), "Regorafenib Monotherapy for Previously Treated Metastatic Colorectal Cancer (CORRECT): An International, Multicentre, Randomised, Placebo-Controlled, Phase 3 Trial," Lancet Lond. Engl., **381**(9863), pp. 303-312.

[5] Li, J., Qin, S., Xu, R., Yau, T. C. C., Ma, B., Pan, H., Xu, J., Bai, Y., Chi, Y., Wang, L., Yeh, K.-H., Bi, F., Cheng, Y., Le, A. T., Lin, J.-K., Liu, T., Ma, D., Kappeler, C., Kalmus, J., Kim, T. W., and CONCUR Investigators, (2015), "Regorafenib plus Best Supportive Care versus Placebo plus Best Supportive Care in Asian Patients with Previously Treated Metastatic Colorectal Cancer (CONCUR): A Randomised, Double-Blind, Placebo-Controlled, Phase 3 Trial," Lancet Oncol., **16**(6), pp. 619-629.

[6] Bekaii-Saab, T. S., Ou, F.-S., Ahn, D. H., Boland, P. M., Ciombor, K. K., Heying, E. N., Dockter, T. J., Jacobs, N. L., Pasche, B. C., Cleary, J. M., Meyers, J. P., Desnoyers, R. J., McCune, J. S., Pedersen, K., Barzi, A., Chiorean, E. G., Sloan, J., Lacouture, M. E., Lenz, H.-J., and Grothey, A., (2019), "Regorafenib Dose-Optimisation in Patients with Refractory Metastatic Colorectal Cancer (ReDOS): A Randomised, Multicentre, Open-Label, Phase 2 Study," Lancet Oncol., **20**(8), pp. 1070-1082.

[7] Tabernero, J., Lenz, H.-J., Siena, S., Sobrero, A., Falcone, A., Ychou, M., Humblet, Y., Bouché, O., Mineur, L., Barone, C., Adenis, A., Yoshino, T., Goldberg, R. M., Sargent, D. J., Wagner, A., Laurent, D., Teufel, M., Jeffers, M., Grothey, A., and Van Cutsem, E., (2015), "Analysis of Circulating DNA and Protein Biomarkers to Predict the Clinical Activity of Regorafenib and Assess Prognosis in Patients
with Metastatic Colorectal Cancer: A Retrospective, Exploratory Analysis of the CORRECT Trial,” Lancet Oncol., **16**(8), pp. 937–948.

[8] Adenis, A., de la Fouchardiere, C., Paule, B., Burtin, P., Tougeron, D., Wallet, J., Dourthe, L.-M., Etienne, P.-L., Mineur, L., Clisant, S., Phelip, J.-M., Kramar, A., and Andre, T., (2016), “Survival, Safety, and Prognostic Factors for Outcome with Regorafenib in Patients with Metastatic Colorectal Cancer Refractory to Standard Therapies: Results from a Multicenter Study (REBECCA) Nested within a Compassionate Use Program,” BMC Cancer, **16**, p. 412.

[9] Otandault, A., Anker, P., Al Amir Dache, Z., Guillaumon, V., Meddeb, R., Pastor, B., Pisareva, E., Sanchez, C., Tanos, R., Tousch, G., Schwarzenbach, H., and Thierry, A. R., (2019), “Recent Advances in Circulating Nucleic Acids in Oncology,” Ann. Oncol. Off. J. Eur. Soc. Med. Oncol., **30**(3), pp. 374–384.

[10] Thierry, A. R., Mouliere, F., El Messaoudi, S., Mollevi, C., Lopez-Crapez, E., Rolet, F., Gillet, B., Gongora, C., Dechelotte, P., Robert, B., Del Rio, M., Lamy, P.-J., Bibeau, F., Nouaille, M., Loriot, V., Jarrousse, A.-S., Molina, F., Mathonnet, M., Pezet, D., and Ychou, M., (2014), “Clinical Validation of the Detection of KRAS and BRAF Mutations from Circulating Tumor DNA,” Nat. Med., **20**(4), pp. 430–435.

[11] Bettegowda, C., Sausen, M., Leary, R. J., Kinde, I., Wang, Y., Agrawal, N., Bartlett, B. R., Wang, H., Luber, B., Alani, R. M., Antonarakis, E. S., Azad, N. S., Bardelli, A., Brem, H., Cameron, J. L., Lee, C. C., Fecher, L. A., Gallia, G. L., Gibbs, P., Le, D., Giuntoli, R. L., Goggins, M., Hogarty, M. D., Holdhoff, M., Hong, S.-M., Jiao, Y., Juhl, H. H., Kim, J. J., Siravegna, G., Laheru, D. A., Lauricella, C., Lim, M., Lipson, E. J., Marie, S. K. N., Netto, G. J., Oliner, K. S., Olivi, A., Olsson, L., Riggins, G. J., Sartore-Bianchi, A., Schmidt, K., Shih, Ie-M., Oba-Shinjo, S. M., Siena, S., Theodorescu, D., Tie, J., Harkins, T. T., Veronese, S., Wang, T.-L., Weingart, J. D., Wolfgang, C. L., Wood, L. D., Xing, D., Hraban, R. H., Wu, J., Allen, P. J., Schmidt, C. M., Choti, M. A., Velculescu, V. E., Kinzler, K. W., Vogelstein, B., Papadopoulos, N., and Diaz, L. A., (2014), “Detection of Circulating Tumor DNA in Early- and Late-Stage Human Malignancies,” Sci. Transl. Med., **6**(224), p. 224ra24.

[12] Vitiello, P. P., De Falco, V., Giunta, E. F., Ciardiello, D., Cardone, C., Vitale, P., Zanaletti, N., Borrelli, C., Poliero, L., Terminiello, M., Arrichiello, G., Caputo, V., Famiglietti, V., Mattera Iacono, V., Marrone, F., Di Liello, A., Martini, G., Napolitano, S., Caraglia, M., Lombardi, A., Franco, R., De Vita, F., Morgillo, F., Troiani, T., Ciardiello, F., and Martinelli, E., (2019), “Clinical Practice Use of Liquid Biopsy to Identify RAS/BRAF Mutations in Patients with Metastatic Colorectal Cancer (MCRC): A Single Institution Experience,” Cancers, **11**(10).
[13] Yao, J., Zang, W., Ge, Y., Weygant, N., Yu, P., Li, L., Rao, G., Jiang, Z., Yan, R., He, L., Yu, Y., Jin, M., Cheng, G., and An, G., (2018), "RAS/BRAF Circulating Tumor DNA Mutations as a Predictor of Response to First-Line Chemotherapy in Metastatic Colorectal Cancer Patients," Can. J. Gastroenterol. Hepatol., **2018**, p. 4248971.

[14] van Helden, E. J., Angus, L., Menke-van der Houven van Oordt, C. W., Heideman, D. A. M., Boon, E., van Es, S. C., Radema, S. A., van Herpen, C. M. L., de Groot, D. J. A., de Vries, E. G. E., Jansen, M. P. H. M., Sleijfer, S., and Verheul, H. M. W., (2019), "RAS and BRAF Mutations in Cell-Free DNA Are Predictive for Outcome of Cetuximab Monotherapy in Patients with Tissue-Tested RAS Wild-Type Advanced Colorectal Cancer," Mol. Oncol., **13**(11), pp. 2361-2374.

[15] Thierry, A. R., El Messaoudi, S., Mollevi, C., Raoul, J. L., Guimbaud, R., Pezet, D., Artru, P., Assenat, E., Borg, C., Mathonnet, M., De La Fouchardière, C., Bouché, O., Gavoille, C., Fiess, C., Auzemery, B., Meddeb, R., Lopez-Crapez, E., Sanchez, C., Pastor, B., and Ychou, M., (2017), "Clinical Utility of Circulating DNA Analysis for Rapid Detection of Actionable Mutations to Select Metastatic Colorectal Patients for Anti-EGFR Treatment," Ann. Oncol. Off. J. Eur. Soc. Med. Oncol., **28**(9), pp. 2149-2159.

[16] Diehl, F., Schmidt, K., Choti, M. A., Romans, K., Goodman, S., Li, M., Thornton, K., Agrawal, N., Sokoll, L., Szabo, S. A., Kinzler, K. W., Vogelstein, B., and Diaz, L. A., (2008), "Circulating Mutant DNA to Assess Tumor Dynamics," Nat. Med., **14**(9), pp. 985-990.

[17] Misale, S., Yaeger, R., Hobor, S., Scala, E., Janakiraman, M., Liska, D., Valtorta, E., Schiavo, R., Buscarino, M., Siravegna, G., Bencardino, K., Cercek, A., Chen, C.-T., Veronese, S., Zanon, C., Sartore-Bianchi, A., Gambacorta, M., Gallicchio, M., Vakiani, E., Boscaro, V., Medico, E., Weiser, M., Siena, S., Di Nicolantonio, F., Solit, D., and Bardelli, A., (2012), "Emergence of KRAS Mutations and Acquired Resistance to Anti-EGFR Therapy in Colorectal Cancer," Nature, **486**(7404), pp. 532-536.

[18] Siravegna, G., Mussolin, B., Buscarino, M., Corti, G., Cassingena, A., Crisafulli, G., Ponzetti, A., Cremolini, C., Amatu, A., Lauricella, C., Lamba, S., Hobor, S., Avallone, A., Valtorta, E., Rospo, G., Medico, E., Motta, V., Antoniotti, C., Tatangelo, F., Bellosillo, B., Veronese, S., Budillon, A., Montagut, C., Racca, P., Marsoni, S., Falcone, A., Corcoran, R. B., Di Nicolantonio, F., Loupakis, F., Siena, S., Sartore-Bianchi, A., and Bardelli, A., (2015), "Clonal Evolution and Resistance to EGFR Blockade in the Blood of Colorectal Cancer Patients," Nat. Med., **21**(7), p. 827.

[19] Danese, E., Minicozzi, A. M., Benati, M., Montagnana, M., Paviati, E., Salvagno, G. L., Lima-Oliveira, G., Gusella, M., Pasini, F., Lippi, G., and Guidi, G. C., (2015), "Comparison of Genetic and Epigenetic Alterations of Primary Tumors and Matched Plasma Samples in Patients with Colorectal Cancer," PloS One, **10**(5), p. e0126417.
[20] Gao, J., Wang, H., Zang, W., Li, B., Rao, G., Li, L., Yu, Y., Li, Z., Dong, B., Lu, Z., Jiang, Z., and Shen, L., (2017), "Circulating Tumor DNA Functions as an Alternative for Tissue to Overcome Tumor Heterogeneity in Advanced Gastric Cancer," Cancer Sci., **108**(9), pp. 1881-1887.

[21] Thierry, A. R., Pastor, B., Jiang, Z.-Q., Katsiampoura, A. D., Parseghian, C., Loree, J. M., Overman, M. J., Sanchez, C., Messaoudi, S. E., Ychou, M., and Kopetz, S., (2017), "Circulating DNA Demonstrates Convergent Evolution and Common Resistance Mechanisms during Treatment of Colorectal Cancer," Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res., **23**(16), pp. 4578-4591.

[22] Lucidarme, O., Wagner, M., Gillard, P., Kim, S., Bachet, J.-B., Rousseau, B., Mazard, T., Louvet, C., Chibaudel, B., Cohen, R., Garcia-Larnicol, M.-L., Gobert, A., Henriques, J., and André, T., (2019), "RECIST and CHOI Criteria in the Evaluation of Tumor Response in Patients with Metastatic Colorectal Cancer Treated with Regorafenib, a Prospective Multicenter Study," Cancer Imaging Off. Publ. Int. Cancer Imaging Soc., **19**(1), p. 85.

[23] El Messaoudi, S., Rolet, F., Mouliere, F., and Thierry, A. R., (2013), "Circulating Cell Free DNA: Preanalytical Considerations," Clin. Chim. Acta Int. J. Clin. Chem., **424**, pp. 222-230.

[24] Meddeb, R., Pisareva, E., and Thierry, A. R., (2019), "Guidelines for the Preanalytical Conditions for Analyzing Circulating Cell-Free DNA," Clin. Chem., **65**(5), pp. 623-633.

[25] Tanos, R., Tosato, G., Otandault, A., Al Amir Dache, Z., Pique Lasorsa, L., Tousch, G., El Messaoudi, S., Meddeb, R., Diab Assaf, M., Ychou, M., Du Manoir, S., Pezet, D., Gagnière, J., Colombo, P.-E., Jacot, W., Assénat, E., Dupuy, M., Adenis, A., Mazard, T., Mollevi, C., Sayagués, J. M., Colinge, J., and Thierry, A. R., (2020), "Machine Learning-Assisted Evaluation of Circulating DNA Quantitative Analysis for Cancer Screening," Adv. Sci. Weinh. Baden-Wurtt. Ger., **7**(18), p. 2000486.

[26] Mouliere, F., El Messaoudi, S., Pang, D., Dritschilo, A., and Thierry, A. R., (2014), "Multi-Marker Analysis of Circulating Cell-Free DNA toward Personalized Medicine for Colorectal Cancer," Mol. Oncol., **8**(5), pp. 927-941.

[27] Bustin, S. A., (2010), "Why the Need for QPCR Publication Guidelines?--The Case for MIQE," Methods San Diego Calif., **50**(4), pp. 217-226.

[28] Bustin, S. A., Benes, V., Garson, J. A., Hellemans, J., Huggett, J., Kubista, M., Mueller, R., Nolan, T., Pfaffl, M. W., Shipley, G. L., Vandesompele, J., and Wittwer, C. T., (2009), "The MIQE Guidelines: Minimum Information for Publication of Quantitative Real-Time PCR Experiments," Clin. Chem., **55**(4), pp. 611-622.

[29] El Messaoudi, S., Mouliere, F., Du Manoir, S., Bascoul-Mollevi, C., Gillet, B., Nouaille, M., Fiess, C., Crapez, E., Bibeau, F., Theillet, C., Mazard, T., Pezet, D., Mathonnet, M., Ychou, M., and Thierry, A. R., (2016), "Circulating DNA as a Strong Multimarker Prognostic Tool for Metastatic Colorectal
Cancer Patient Management Care," Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res., **22**(12), pp. 3067-3077.

[30] Vandeputte, C., Kehagias, P., El Housni, H., Ameye, L., Laes, J.-F., Desmedt, C., Sotiriou, C., Deleporte, A., Puleo, F., Geboes, K., Delaunoit, T., Demolin, G., Peeters, M., D'Hondt, L., Janssens, J., Carrasco, J., Marechal, R., Galdon, M. G., Heimann, P., Paesmans, M., Flamen, P., and Hendlisz, A., (2018), "Circulating Tumor DNA in Early Response Assessment and Monitoring of Advanced Colorectal Cancer Treated with a Multi-Kinase Inhibitor," Oncotarget, **9**(25), pp. 17756-17769.

[31] Amatu, A., Schirripa, M., Tosi, F., Lonardi, S., Bencardino, K., Bonazzina, E., Palmeri, L., Patanè, D. A., Pizzutilo, E. G., Mussolin, B., Bergamo, F., Alberti, G., Intini, R., Procaccio, L., Arese, M., Marsoni, S., Nichelatti, M., Zagonel, V., Siena, S., Bardelli, A., Loupakis, F., Di Nicolantonio, F., Sartore-Bianchi, A., and Barault, L., (2019), "High Circulating Methylated DNA Is a Negative Predictive and Prognostic Marker in Metastatic Colorectal Cancer Patients Treated With Regorafenib," Front. Oncol., **9**, p. 622.

[32] Khan, K., Rata, M., Cunningham, D., Koh, D.-M., Tunariu, N., Hahne, J. C., Vlachogiannis, G., Hedayat, S., Marchetti, S., Lampis, A., Damavandi, M. D., Lote, H., Rana, I., Williams, A., Eccles, S. A., Fontana, E., Collins, D., Eltahir, Z., Rao, S., Watkins, D., Starling, N., Thomas, J., Kalaitzaki, E., Fotiadis, N., Begum, R., Bali, M., Rugge, M., Temple, E., Fassan, M., Chau, I., Braconi, C., and Valeri, N., (2018), "Functional Imaging and Circulating Biomarkers of Response to Regorafenib in Treatment-Refractory Metastatic Colorectal Cancer Patients in a Prospective Phase II Study," Gut, **67**(8), pp. 1484-1492.

[33] Jensen, L. H., Olesen, R., Petersen, L. N., Boysen, A. K., Andersen, R. F., Lindebjerg, J., Nottelmann, L., Thomsen, C. E. B., Havelund, B. M., Jakobsen, A., and Hansen, T. F., (2019), "NPY Gene Methylation as a Universal, Longitudinal Plasma Marker for Evaluating the Clinical Benefit from Last-Line Treatment with Regorafenib in Metastatic Colorectal Cancer," Cancers, **11**(11).

[34] Wong, A. L. A., Lim, J. S. J., Sinha, A., Gopinathan, A., Lim, R., Tan, C.-S., Soh, T., Venkatesh, S., Titin, C., Sapari, N. S., Lee, S.-C., Yong, W.-P., Tan, D. S. P., Pang, B., Wang, T.-T., Zee, Y.-K., Soong, R., Trnkova, Z., Lathia, C., Thiery, J.-P., Wilhelm, S., Jeffers, M., and Goh, B.-C., (2015), "Tumour Pharmacodynamics and Circulating Cell Free DNA in Patients with Refractory Colorectal Carcinoma Treated with Regorafenib," J. Transl. Med., **13**(1), p. 57.
## Figure Legends

<caption>**Fig. 1.** Flow-chart</caption>

55 patients (the intent-to-treat population) received at least one regorafenib tablet. 43 out of 55 patients had survival data and 41 out of 55 had tumour response data. Patients with survival and tumour response data had also circulating cell-free DNA data.

**Fig. 2.** Circulating cell-free DNA (cfDNA) and tumor response. (A) Baseline cfDNA and tumor control. (B) Dynamic changes of cfDNA concentrations throughout treatment duration. The Boxplot shows medians with interquartile range (IQR: Q1-Q3) and whiskers represents the range within the 1.5 IQR. Test for comparison of median between groups is done by the Wilcoxon test.
C1, cycle 1; C2, cycle 2; EOT, End Of Treatment

**Fig. 3.** Overall survival (OS) according to the baseline circulating cell-free (cfDNA) concentrations. (A) Baseline cfDNA at 26 ng/mL cutoff threshold. (B) Baseline cfDNA at 26 ng/mL, 26-110 ng/mL, and ≥100 ng/mL cutoff thresholds. Survival curves are represented according to thresholds of the total cfDNA concentration (ng/mL of plasma) determined at baseline. OS were estimated using the Kaplan-Meir method, described with median and 95% CI, and compared using the logrank test.

**Fig. 4.** Overall survival according to ctDNA concentrations (threshold 2 ng/mL) in patients with RAS-mutated tumors OS were estimated using the Kaplan-Meir method, described with median and 95% CI, and compared using the logrank test.
**Supplementary information**

**Fig S1. Risk of death according to baseline cfDNA concentrations**

The dotted lines represents the 95% confidence interval for the risk of death according to cfDNA concentration at baseline (continuous line).

**Fig S2. Overall survival according to mutation load (threshold 6%)**

**Fig. S3. Changes of cfDNA concentrations during treatment**

Serial concentration of circulating cfDNA (ng/mL of plasma) was determined using the IntPlex ASB Q-PCR method targeting a 67 bp-length wild-type sequence of the *KRAS* gene. A significant increase of cfDNA concentrations from baseline to day 15 of cycle 1 was observed; test for comparison of cfDNA medians between baseline and cycle 1 with paired data (Wilcoxon signed rank test, *P* = 0.0004).

EOT, End Of Treatment

**Table S1. Tumor genotyping analysis**

Comparison of *KRAS*, *BRAF*, and *NRAS* genotypes in archival tissues and blood samples taken prior and at the end of regorafenib treatment.
<table><caption>**Table 1.** Patient and treatment characteristics</caption><thead><tr><th></th><th>TEXCAN<br>population<br>N = 55</th><th>Population<br>without cfDNA<br>analysis<br>n = 12</th><th>Population with<br>cfDNA analysis<br>n = 43</th></tr></thead><tbody><tr><td>Median age, years (IQR)</td><td>62.7 (52.6-68.9)</td><td>67.7 (59.7-70)</td><td>62.1 (50.5-68.3)</td></tr><tr><td>Gender</td><td></td><td></td><td></td></tr><tr><td>Male</td><td>30 (55.5%)</td><td>7 (58.3%)</td><td>23 (53.5%)</td></tr><tr><td>Female</td><td>25 (45.5%)</td><td>5 (41.7%)</td><td>20 (46.5%)</td></tr><tr><td>ECOG PS</td><td></td><td></td><td></td></tr><tr><td>0</td><td>17 (30.9%)</td><td>4 (33.3%)</td><td>13 (30.2%)</td></tr><tr><td>1</td><td>38 (69.1%)</td><td>8 (66.7%)</td><td>30 (69.8%)</td></tr><tr><td>Primary site of disease</td><td></td><td></td><td></td></tr><tr><td>Right colon</td><td>6 (10.9%)</td><td>2 (16.6%)</td><td>4 (9.3%)</td></tr><tr><td>Left colon</td><td>49 (89.1%)</td><td>10 (83.4%)</td><td>39 (90.7%)</td></tr><tr><td>Archival tumor-genotype status</td><td></td><td></td><td></td></tr><tr><td>KRAS wild-type</td><td>34</td><td>7</td><td>27</td></tr><tr><td>KRAS mutant</td><td>21</td><td>5</td><td>16</td></tr><tr><td>NRAS wild-type</td><td>34</td><td>8</td><td>26</td></tr><tr><td>NRAS mutant</td><td>3</td><td>0</td><td>3</td></tr><tr><td>Missing</td><td>18</td><td>4</td><td>15</td></tr><tr><td>BRAF wild-type</td><td>37</td><td>7</td><td>30</td></tr><tr><td>BRAF mutant</td><td>6</td><td>1</td><td>5</td></tr></tbody></table>
<table><thead><tr><th>Missing</th><th>12</th><th>4</th><th>8</th></tr></thead><tbody><tr><td>Time from diagnosis of metastases &lt; 18 months</td><td>12 (21.8%)</td><td>3 (25%)</td><td>9 (20.9%)</td></tr><tr><td>Previous anti-EGFR treatment</td><td>28 (50.9%)</td><td>6 (50%)</td><td>22 (54.1%)</td></tr><tr><td>Previous anti-angiogenic treatment</td><td>54 (98.2%)</td><td>12 (100%)</td><td>42 (97.7%)</td></tr><tr><td>Regorafenib treatment</td><td></td><td></td><td></td></tr><tr><td>Treatment duration, weeks (IQR)</td><td>8.29 (4.14-16.29)</td><td>12.14 (4-21.79)</td><td>8.29 (4.14-15.14)</td></tr><tr><td>Actual dose / planned dose</td><td>84.5%</td><td>100%</td><td>82.5%</td></tr><tr><td>Median OS, months (95% CI)</td><td>5.32 (3.7-8.6)</td><td>3.9 (1.7-17.1)</td><td>5.3 (3.7-8.6)</td></tr></tbody></table>

IQR, interquartile range; ECOG PS, Eastern Cooperative Oncology Group performance status; OS, overall survival
<table><caption>**Table 2.** Univariate Cox regression analysis for survival according to baseline cfDNA</caption><thead><tr><th></th><th>Baseline cfDNA (ng/mL)</th><th>N (events)</th><th>HR</th><th>95% CI</th><th>P value</th></tr></thead><tbody><tr><td rowspan="10">OS</td><td>&lt;100</td><td>36 (29)</td><td>1</td><td></td><td>0.0355</td></tr><tr><td>≥100</td><td>7 (7)</td><td>2.48</td><td>1.06-5.77</td><td></td></tr><tr><td>&lt;26</td><td>24 (18)</td><td>1</td><td></td><td>0.0407</td></tr><tr><td>≥26</td><td>19 (18)</td><td>2.02</td><td>1.03-3.95</td><td></td></tr><tr><td>&lt;65</td><td>33 (26)</td><td>1</td><td></td><td>0.0458</td></tr><tr><td>≥65</td><td>10 (10)</td><td>2.12</td><td>1.01-4.45</td><td></td></tr><tr><td>&lt;26</td><td>24 (18)</td><td>1</td><td></td><td>0.0534</td></tr><tr><td>26-100</td><td>12 (11)</td><td>1.67</td><td>0.78-3.62</td><td>0.19</td></tr><tr><td>≥100</td><td>7 (7)</td><td>2.93</td><td>1.20-7.17</td><td>0.0188</td></tr><tr><td>log</td><td>43 (36)</td><td>1.26</td><td>1.01-1.56</td><td>0.0371</td></tr><tr><td rowspan="10">PFS</td><td>&lt;26</td><td>24 (22)</td><td>1</td><td></td><td>0.1947</td></tr><tr><td>≥26</td><td>19 (19)</td><td>1.51</td><td>0.81-2.83</td><td></td></tr><tr><td>&lt;65</td><td>33 (31)</td><td>1</td><td></td><td>0.4507</td></tr><tr><td>≥65</td><td>10 (10)</td><td>1.32</td><td>0.64-2.71</td><td></td></tr><tr><td>&lt;100</td><td>36 (4)</td><td>1</td><td></td><td>0.3683</td></tr><tr><td>≥100</td><td>7 (7)</td><td>1.47</td><td>0.64-3.40</td><td></td></tr><tr><td>&lt;26</td><td>24 (22)</td><td>1</td><td></td><td>0.4115</td></tr><tr><td>26-100</td><td>12 (12)</td><td>1.45</td><td>0.71-2.94</td><td>0.311</td></tr><tr><td>≥100</td><td>7 (7)</td><td>1.66</td><td>0.69-4.00</td><td>0.2589</td></tr><tr><td>log</td><td>43 (41)</td><td>1.2</td><td>0.97-1.49</td><td>0.0946</td></tr></tbody></table>

OS, overall survival; PFS, progression-free survival
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