Beyond basics: Key mutation selection features for successful tumor-informed ctDNA detection.

Tumor-informed mutation-based approaches are frequently used for detection of circulating tumor DNA (ctDNA). Not all mutations make equally effective ctDNA markers. The objective was to explore if prioritizing mutations using mutational features-such as cancer cell fraction (CCF), multiplicity, and error rate-would improve the success rate of tumor-informed ctDNA analysis. Additionally, we aimed to develop a practical and easily implementable analysis pipeline for identifying and prioritizing candidate mutations from whole-exome sequencing (WES) data. We analyzed WES and ctDNA data from three tumor-informed ctDNA studies, one on bladder cancer (Cohort A) and two on colorectal cancer (Cohorts I and N). The studies included 390 patients. For each patient, a unique set of mutations (median mutations/patient: 6, interquartile 13, range: 1-46, total n = 4023) were used as markers of ctDNA. The tool PureCN was used to assess the CCF and multiplicity of each mutation. High-CCF mutations were detected more frequently than low-CCF mutations (Cohort A: odds ratio [OR] 20.6, 95% confidence interval [CI] 5.72-173, p = 1.73e-12; Cohort I: OR 2.24, 95% CI 1.44-3.52, p = 1.66e-04; and Cohort N: OR 1.78, 95% CI 1.14-2.79, p = 7.86e-03). The detection-likelihood was additionally improved by selecting mutations with multiplicity of two or above (Cohort A: OR 1.55, 95% CI 1. 14-2.11, p = 3.85e-03; Cohort I: OR 1.78, 95% CI 1.23-2.56, p = 1.34e-03; and Cohort N: OR 1.94, 95% CI 1.63-2.31, p = 2.83e-14). Furthermore, selecting the mutations for which the ctDNA detection method had the lowest error rates, additionally improved the detection-likelihood, particularly evident when plasma cell-free DNA tumor fractions were below 0.1% (p = 2.1e-07). Selecting mutational markers with high CCF, high multiplicity, and low error rate significantly improve ctDNA detection likelihood. We provide free access to the analysis pipeline enabling others to perform qualified prioritization of mutations for tumor-informed ctDNA analysis.

DREAMS: deep read-level error model for sequencing data applied to low-frequency variant calling and circulating tumor DNA detection.

Circulating tumor DNA detection using next-generation sequencing (NGS) data of plasma DNA is promising for cancer identification and characterization. However, the tumor signal in the blood is often low and difficult to distinguish from errors. We present DREAMS (Deep Read-level Modelling of Sequencing-errors) for estimating error rates of individual read positions. Using DREAMS, we develop statistical methods for variant calling (DREAMS-vc) and cancer detection (DREAMS-cc). For evaluation, we generate deep targeted NGS data of matching tumor and plasma DNA from 85 colorectal cancer patients. The DREAMS approach performs better than state-of-the-art methods for variant calling and cancer detection.

ctDNA-guided adjuvant chemotherapy for colorectal cancer-ready for prime time?

In stage II colorectal cancer, adjuvant chemotherapy is controversial, and overtreatment is substantial due to suboptimal risk stratification. In a recent New England Journal of Medicine article reporting from a prospective randomized phase II trial, Tie and colleagues demonstrate how ctDNA-guided risk-stratification reduces the use of adjuvant chemotherapy without compromising recurrence risk.

Error Characterization and Statistical Modeling Improves Circulating Tumor DNA Detection by Droplet Digital PCR.

BACKGROUND: Droplet digital PCR (ddPCR) is a widely used and sensitive application for circulating tumor DNA (ctDNA) detection. As ctDNA is often found in low abundance, methods to separate low-signal readouts from noise are necessary. We aimed to characterize the ddPCR-generated noise and, informed by this, create a sensitive and specific ctDNA caller. METHODS: We built 2 novel complimentary ctDNA calling methods: dynamic limit of blank and concentration and assay-specific tumor load estimator (CASTLE). Both methods are informed by empirically established assay-specific noise profiles. Here, we characterized noise for 70 mutation-detecting ddPCR assays by applying each assay to 95 nonmutated samples. Using these profiles, the performance of the 2 new methods was assessed in a total of 9447 negative/positive reference samples and in 1311 real-life plasma samples from colorectal cancer patients. Lastly, performances were compared to 7 literature-established calling methods. RESULTS: For many assays, noise increased proportionally with the DNA input amount. Assays targeting transition base changes were more error-prone than transversion-targeting assays. Both our calling methods successfully accounted for the additional noise in transition assays and showed consistently high performance regardless of DNA input amount. Calling methods that were not noise-informed performed less well than noise-informed methods. CASTLE was the only calling method providing a statistical estimate of the noise-corrected mutation level and call certainty. CONCLUSIONS: Accurate error modeling is necessary for sensitive and specific ctDNA detection by ddPCR. Accounting for DNA input amounts ensures specific detection regardless of the sample-specific DNA concentration. Our results demonstrate CASTLE as a powerful tool for ctDNA calling using ddPCR.

Tumour-agnostic circulating tumour DNA analysis for improved recurrence surveillance after resection of colorectal liver metastases: A prospective cohort study.

PURPOSE: Nearly 50% of patients recur within two years after curatively intended resection of colorectal cancer liver metastasis (CRLM). The optimal surveillance strategy is unknown due to the lack of evidence. Here, we explored the potential for improving postoperative CRLM surveillance by performing serial circulating tumour DNA (ctDNA) assessments parallel to standard-of-care surveillance. EXPERIMENTAL DESIGN: 499 prospectively collected serial plasma samples from 96 patients undergoing CRLM resection were analysed using the tumour-agnostic methylation multiplex droplet-digital PCR test 'TriMeth'. RESULTS: Patients with ctDNA postoperatively or post adjuvant chemotherapy experienced a significant lower recurrence-free survival than patients without ctDNA (hazard ratio (HR) 4.5; P < 0.0001 and HR 8.4, P < 0.0001). ctDNA status was a stronger predictor of recurrence than standard clinical risk factors and carcinoembryonic antigen. Serial TriMeth analysis detected ctDNA before radiological recurrence in 55.6% of ctDNA-positive patients, with up to 10.6 months lead-time (median 3.1 months). During surveillance, 24% of patients had inconclusive CT scans, which was associated with a significant delay in recurrence diagnosis (median 3.5 months versus 1.0 month, P < 0.0001). Uniquely, ctDNA status at the time of inconclusive CT scans predicted recurrence with positive and negative predictive values of 100%, and 75% (P = 0.0003). Serial TriMeth analysis allowed ctDNA growth rate assessment and revealed that fast ctDNA growth was associated with poor overall survival (HR: 1.6, P = 0.0052). CONCLUSIONS: Serial postoperative ctDNA analysis has a strong prognostic value and is more sensitive for recurrence detection than standard-of-care CRLM surveillance tools. Altogether, TriMeth provides several opportunities for improving postoperative surveillance of CRLM patients.

MethCORR infers gene expression from DNA methylation and allows molecular analysis of ten common cancer types using fresh-frozen and formalin-fixed paraffin-embedded tumor samples.

BACKGROUND: Transcriptional analysis is widely used to study the molecular biology of cancer and hold great biomarker potential for clinical patient stratification. Yet, accurate transcriptional profiling requires RNA of a high quality, which often cannot be retrieved from formalin-fixed, paraffin-embedded (FFPE) tumor tissue that is routinely collected and archived in clinical departments. To overcome this roadblock to clinical testing, we previously developed MethCORR, a method that infers gene expression from DNA methylation data, which is robustly retrieved from FFPE tissue. MethCORR was originally developed for colorectal cancer and with this study, we aim to: (1) extend the MethCORR method to 10 additional cancer types and (2) to illustrate that the inferred gene expression is accurate and clinically informative. RESULTS: Regression models to infer gene expression information from DNA methylation were developed for ten common cancer types using matched RNA sequencing and DNA methylation profiles (HumanMethylation450 BeadChip) from The Cancer Genome Atlas Project. Robust and accurate gene expression profiles were inferred for all cancer types: on average, the expression of 11,000 genes was modeled with good accuracy and an intra-sample correlation of R2 = 0.90 between inferred and measured gene expression was observed. Molecular pathway analysis and transcriptional subtyping were performed for breast, prostate, and lung cancer samples to illustrate the general usability of the inferred gene expression profiles: overall, a high correlation of r = 0.96 (Pearson) in pathway enrichment scores and a 76% correspondence in molecular subtype calls were observed when using measured and inferred gene expression as input. Finally, inferred expression from FFPE tissue correlated better with RNA sequencing data from matched fresh-frozen tissue than did RNA sequencing data from FFPE tissue (P < 0.0001; Wilcoxon rank-sum test). CONCLUSIONS: In all cancers investigated, MethCORR enabled DNA methylation-based transcriptional analysis, thus enabling future analysis of cancer in situations where high-quality DNA, but not RNA, is available. Here, we provide the framework and resources for MethCORR modeling of ten common cancer types, thereby widely expanding the possibilities for transcriptional studies of archival FFPE material.

Publisher Correction: MethCORR modelling of methylomes from formalin-fixed paraffin-embedded tissue enables characterization and prognostication of colorectal cancer.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The effect of surgical trauma on circulating free DNA levels in cancer patients-implications for studies of circulating tumor DNA.

Detection of circulating tumor DNA (ctDNA) post-treatment is an emerging marker of residual disease. ctDNA constitutes only a minor fraction of the cell-free DNA (cfDNA) circulating in cancer patients, complicating ctDNA detection. This is exacerbated by trauma-induced cfDNA. To guide optimal blood sample timing, we investigated the duration and magnitude of surgical trauma-induced cfDNA in patients with colorectal or bladder cancer. DNA levels were quantified in paired plasma samples collected before and up to 6 weeks after surgery from 436 patients with colorectal cancer and 47 patients with muscle-invasive bladder cancer. To assess whether trauma-induced cfDNA fragments are longer than ordinary cfDNA fragments, the concentration of short (< 1 kb) and long (> 1 kb) fragments was determined for 91 patients. Previously reported ctDNA data from 91 patients with colorectal cancer and 47 patients with bladder cancer were used to assess how trauma-induced DNA affects ctDNA detection. The total cfDNA level increased postoperatively-both in patients with colorectal cancer (mean threefold) and bladder cancer (mean eightfold). The DNA levels were significantly increased up to 4 weeks after surgery in both patient cohorts (P = 0.0005 and P ≤ 0.0001). The concentration of short, but not long, cfDNA fragments increased postoperatively. Of 25 patients with radiological relapse, eight were ctDNA-positive and 17 were ctDNA-negative in the period with trauma-induced DNA. Analysis of longitudinal samples revealed that five of the negative patients became positive shortly after the release of trauma-induced cfDNA had ceased. In conclusion, surgery was associated with elevated cfDNA levels, persisting up to 4 weeks, which may have masked ctDNA in relapse patients. Trauma-induced cfDNA was of similar size to ordinary cfDNA. To mitigate the impact of trauma-induced cfDNA on ctDNA detection, it is recommended that a second blood sample collected after week 4 is analyzed for patients initially ctDNA negative.

Enhanced Performance of DNA Methylation Markers by Simultaneous Measurement of Sense and Antisense DNA Strands after Cytosine Conversion.

BACKGROUND: Most existing DNA methylation-based methods for detection of circulating tumor DNA (ctDNA) are based on conversion of unmethylated cytosines to uracil. After conversion, the 2 DNA strands are no longer complementary; therefore, targeting only 1 DNA strand merely utilizes half of the available input DNA. We investigated whether the sensitivity of methylation-based ctDNA detection strategies could be increased by targeting both DNA strands after bisulfite conversion. METHODS: Dual-strand digital PCR assays were designed for the 3 colorectal cancer (CRC)-specific methylation markers KCNQ5, C9orf50, and CLIP4 and compared with previously reported single-strand assays. Performance was tested in tumor and leukocyte DNA, and the ability to detect ctDNA was investigated in plasma from 43 patients with CRC stages I to IV and 42 colonoscopy-confirmed healthy controls. RESULTS: Dual-strand assays quantified close to 100% of methylated control DNA input, whereas single-strand assays quantified approximately 50%. Furthermore, dual-strand assays showed a 2-fold increase in the number of methylated DNA copies detected when applied to DNA purified from tumor tissue and plasma from CRC patients. When the results of the 3 DNA methylation markers were combined into a ctDNA detection test and applied to plasma, the dual-strand assay format detected 86% of the cancers compared with 74% for the single-strand assay format. The specificity was 100% for both the dual- and single-strand test formats. CONCLUSION: Dual-strand assays enabled more sensitive detection of methylated ctDNA than single-strand assays.

Development of blood-based biomarker tests for early detection of colorectal neoplasia: Influence of blood collection timing and handling procedures.

INTRODUCTION: Blood-based, cancer-associated biomarkers are susceptible to a variety of well-known preanalytical factors. The influence of bowel preparation before a diagnostic colonoscopy on biomarker levels is, however, poorly investigated. The present study assessed the influence of bowel preparation on colorectal cancer-associated biomarkers. In addition, the effect of single versus double centrifugation of plasma biomarkers was assessed. METHODS: Blood samples were collected pre- and post-bowel preparation from 125 subjects scheduled for first time diagnostic colonoscopy due to symptoms attributable to CRC. The samples were separated into serum and EDTA plasma, and analyzed by four independent collaborators for: 1) the proteins AFP, CA19-9, CEA, hs-CRP, CyFra21-1, Ferritin, Galectin-3 and TIMP-1, 2) the proteins BAG4, IL6ST, vWF, CD44 and EGFR, 3) the glycoprotein Galectin-3 ligand, and 4) cell-free DNA (cfDNA). Statistical analysis of biomarker data has been performed using mixed modelling, including repeated measures. RESULTS: The biomarkers generally showed negligible variation between pre- and post-bowel preparation except for CyFra21-1, Ferritin, BAG4 and cfDNA. CyFra21-1 levels were systematically reduced with 29% (95% CI 21-36%) by bowel preparation (p ≤ 0.0001). Ferritin was not significantly different between pre- and post-bowel preparation (p = 0.07), however the estimated difference (increase) was 18%. BAG4 was systematically reduced by 12% (95% CI 1-22%, p = 0.04), while cfDNA showed a significant increase of 28% (95% CI 17-39%, p < 0.0001). Double centrifugation compared to single centrifugation showed reduced vWF (ratio 0.86, p ≤ 0.0001) and CD44 (ratio 0.85, p = 0.016), but increased IL6ST levels (ratio 1.18, p = 0.014). CONCLUSIONS: Results of the present study demonstrated systematic, statistically significant differences between pre-bowel and post-bowel preparation levels for three independent blood-based biomarkers (BAG4, CyFra21-1, cfDNA), illustrating the importance of timing of sample collection for biomarker analyses.

MethCORR modelling of methylomes from formalin-fixed paraffin-embedded tissue enables characterization and prognostication of colorectal cancer.

Transcriptional characterization and classification has potential to resolve the inter-tumor heterogeneity of colorectal cancer and improve patient management. Yet, robust transcriptional profiling is difficult using formalin-fixed, paraffin-embedded (FFPE) samples, which complicates testing in clinical and archival material. We present MethCORR, an approach that allows uniform molecular characterization and classification of fresh-frozen and FFPE samples. MethCORR identifies genome-wide correlations between RNA expression and DNA methylation in fresh-frozen samples. This information is used to infer gene expression information in FFPE samples from their methylation profiles. MethCORR is here applied to methylation profiles from 877 fresh-frozen/FFPE samples and comparative analysis identifies the same two subtypes in four independent cohorts. Furthermore, subtype-specific prognostic biomarkers that better predicts relapse-free survival (HR = 2.66, 95%CI [1.67-4.22], P value < 0.001 (log-rank test)) than UICC tumor, node, metastasis (TNM) staging and microsatellite instability status are identified and validated using DNA methylation-specific PCR. The MethCORR approach is general, and may be similarly successful for other cancer types.

Gel-Based Proteomics of Clinical Samples Identifies Potential Serological Biomarkers for Early Detection of Colorectal Cancer.

The burden of colorectal cancer (CRC) is considerable-approximately 1.8 million people are diagnosed each year with CRC and of these about half will succumb to the disease. In the case of CRC, there is strong evidence that an early diagnosis leads to a better prognosis, with metastatic CRC having a 5-year survival that is only slightly greater than 10% compared with up to 90% for stage I CRC. Clearly, biomarkers for the early detection of CRC would have a major clinical impact. We implemented a coherent gel-based proteomics biomarker discovery platform for the identification of clinically useful biomarkers for the early detection of CRC. Potential protein biomarkers were identified by a 2D gel-based analysis of a cohort composed of 128 CRC and site-matched normal tissue biopsies. Potential biomarkers were prioritized and assays to quantitatively measure plasma expression of the candidate biomarkers were developed. Those biomarkers that fulfilled the preset criteria for technical validity were validated in a case-control set of plasma samples, including 70 patients with CRC, adenomas, or non-cancer diseases and healthy individuals in each group. We identified 63 consistently upregulated polypeptides (factor of four-fold or more) in our proteomics analysis. We selected 10 out of these 63 upregulated polypeptides, and established assays to measure the concentration of each one of the ten biomarkers in plasma samples. Biomarker levels were analyzed in plasma samples from healthy individuals, individuals with adenomas, CRC patients, and patients with non-cancer diseases and we identified one protein, tropomyosin 3 (Tpm3) that could discriminate CRC at a significant level (p = 0.0146). Our results suggest that at least one of the identified proteins, Tpm3, could be used as a biomarker in the early detection of CRC, and further studies should provide unequivocal evidence for the real-life clinical validity and usefulness of Tpm3.

A genetically inducible porcine model of intestinal cancer.

Transgenic porcine cancer models bring novel possibilities for research. Their physical similarities with humans enable the use of surgical procedures and treatment approaches used for patients, which facilitates clinical translation. Here, we aimed to develop an inducible oncopig model of intestinal cancer. Transgenic (TG) minipigs were generated using somatic cell nuclear transfer by handmade cloning. The pigs encode two TG cassettes: (a) an Flp recombinase-inducible oncogene cassette containing KRAS-G12D, cMYC, SV40LT - which inhibits p53 - and pRB and (b) a 4-hydroxytamoxifen (4-OHT)-inducible Flp recombinase activator cassette controlled by the intestinal epithelium-specific villin promoter. Thirteen viable transgenic minipigs were born. The ability of 4-OHT to activate the oncogene cassette was confirmed in vitro in TG colonic organoids and ex vivo in tissue biopsies obtained by colonoscopy. In order to provide proof of principle that the oncogene cassette could also successfully be activated in vivo, three pigs were perorally treated with 400 mg tamoxifen for 2 × 5 days. After two months, one pig developed a duodenal neuroendocrine carcinoma with a lymph node metastasis. Molecular analysis of the carcinoma and metastasis confirmed activation of the oncogene cassette. No tumor formation was observed in untreated TG pigs or in the remaining two treated pigs. The latter indicates that tamoxifen delivery can probably be improved. In summary, we have generated a novel inducible oncopig model of intestinal cancer, which has the ability to form metastatic disease already two months after induction. The model may be helpful in bridging the gap between basic research and clinical usage. It opens new venues for longitudinal studies of tumor development and evolution, for preclinical assessment of new anticancer regimens, for pharmacology and toxicology assessments, as well as for studies into biological mechanisms of tumor formation and metastasis.

Clinical Implications of Monitoring Circulating Tumor DNA in Patients with Colorectal Cancer.

Purpose: We investigated whether detection of ctDNA after resection of colorectal cancer identifies the patients with the highest risk of relapse and, furthermore, whether longitudinal ctDNA analysis allows early detection of relapse and informs about response to intervention.Experimental Design: In this longitudinal cohort study, we used massively parallel sequencing to identify somatic mutations and used these as ctDNA markers to detect minimal residual disease and to monitor changes in tumor burden during a 3-year follow-up period.Results: A total of 45 patients and 371 plasma samples were included. Longitudinal samples from 27 patients revealed ctDNA postoperatively in all relapsing patients (n = 14), but not in any of the nonrelapsing patients. ctDNA detected relapse with an average lead time of 9.4 months compared with CT imaging. Of 21 patients treated for localized disease, six had ctDNA detected within 3 months after surgery. All six later relapsed compared with four of the remaining patients [HR, 37.7; 95% confidence interval (CI), 4.2-335.5; P < 0.001]. The ability of a 3-month ctDNA analysis to predict relapse was confirmed in 23 liver metastasis patients (HR 4.9; 95% CI, 1.5-15.7; P = 0.007). Changes in ctDNA levels induced by relapse intervention (n = 19) showed good agreement with changes in tumor volume (κ = 0.41; Spearman ρ = 0.4).Conclusions: Postoperative ctDNA detection provides evidence of residual disease and identifies patients at very high risk of relapse. Longitudinal surveillance enables early detection of relapse and informs about response to intervention. These observations have implications for the postoperative management of colorectal cancer patients. Clin Cancer Res; 23(18); 5437-45. ©2017 AACR.

An Optimized Shotgun Strategy for the Rapid Generation of Comprehensive Human Proteomes.

This study investigates the challenge of comprehensively cataloging the complete human proteome from a single-cell type using mass spectrometry (MS)-based shotgun proteomics. We modify a classical two-dimensional high-resolution reversed-phase peptide fractionation scheme and optimize a protocol that provides sufficient peak capacity to saturate the sequencing speed of modern MS instruments. This strategy enables the deepest proteome of a human single-cell type to date, with the HeLa proteome sequenced to a depth of ∼584,000 unique peptide sequences and ∼14,200 protein isoforms (∼12,200 protein-coding genes). This depth is comparable with next-generation RNA sequencing and enables the identification of post-translational modifications, including ∼7,000 N-acetylation sites and ∼10,000 phosphorylation sites, without the need for enrichment. We further demonstrate the general applicability and clinical potential of this proteomics strategy by comprehensively quantifying global proteome expression in several different human cancer cell lines and patient tissue samples.

The non-coding variant rs1800734 enhances DCLK3 expression through long-range interaction and promotes colorectal cancer progression.

Genome-wide association studies have identified a great number of non-coding risk variants for colorectal cancer (CRC). To date, the majority of these variants have not been functionally studied. Identification of allele-specific transcription factor (TF) binding is of great importance to understand regulatory consequences of such variants. A recently developed proteome-wide analysis of disease-associated SNPs (PWAS) enables identification of TF-DNA interactions in an unbiased manner. Here we perform a large-scale PWAS study to comprehensively characterize TF-binding landscape that is associated with CRC, which identifies 731 allele-specific TF binding at 116 CRC risk loci. This screen identifies the A-allele of rs1800734 within the promoter region of MLH1 as perturbing the binding of TFAP4 and consequently increasing DCLK3 expression through a long-range interaction, which promotes cancer malignancy through enhancing expression of the genes related to epithelial-to-mesenchymal transition.

SNHG16 is regulated by the Wnt pathway in colorectal cancer and affects genes involved in lipid metabolism.

It is well established that lncRNAs are aberrantly expressed in cancer where they have been shown to act as oncogenes or tumor suppressors. RNA profiling of 314 colorectal adenomas/adenocarcinomas and 292 adjacent normal colon mucosa samples using RNA-sequencing demonstrated that the snoRNA host gene 16 (SNHG16) is significantly up-regulated in adenomas and all stages of CRC. SNHG16 expression was positively correlated to the expression of Wnt-regulated transcription factors, including ASCL2, ETS2, and c-Myc. In vitro abrogation of Wnt signaling in CRC cells reduced the expression of SNHG16 indicating that SNHG16 is regulated by the Wnt pathway. Silencing of SNHG16 resulted in reduced viability, increased apoptotic cell death and impaired cell migration. The SNHG16 silencing particularly affected expression of genes involved in lipid metabolism. A connection between SNHG16 and genes involved in lipid metabolism was also observed in clinical tumors. Argonaute CrossLinking and ImmunoPrecipitation (AGO-CLIP) demonstrated that SNHG16 heavily binds AGO and has 27 AGO/miRNA target sites along its length, indicating that SNHG16 may act as a competing endogenous RNA (ceRNA) "sponging" miRNAs off their cognate targets. Most interestingly, half of the miRNA families with high confidence targets on SNHG16 also target the 3'UTR of Stearoyl-CoA Desaturase (SCD). SCD is involved in lipid metabolism and is down-regulated upon SNHG16 silencing. In conclusion, up-regulation of SNHG16 is a frequent event in CRC, likely caused by deregulated Wnt signaling. In vitro analyses demonstrate that SNHG16 may play an oncogenic role in CRC and that it affects genes involved in lipid metabolism, possible through ceRNA related mechanisms.

Analysis of circulating tumour DNA to monitor disease burden following colorectal cancer surgery.

OBJECTIVE: To develop an affordable and robust pipeline for selection of patient-specific somatic structural variants (SSVs) being informative about radicality of the primary resection, response to adjuvant therapy, incipient recurrence and response to treatment performed in relation to diagnosis of recurrence. DESIGN: We have established efficient procedures for identification of SSVs by next-generation sequencing and subsequent quantification of 3-6 SSVs in plasma. The consequence of intratumour heterogeneity on our approach was assessed. The level of circulating tumour DNA (ctDNA) was quantified in 151 serial plasma samples from six relapsing and five non-relapsing colorectal cancer (CRC) patients by droplet digital PCR, and correlated to clinical findings. RESULTS: Up to six personalised assays were designed for each patient. Our approach enabled efficient temporal assessment of disease status, response to surgical and oncological intervention, and early detection of incipient recurrence. Our approach provided 2-15 (mean 10) months' lead time on detection of metastatic recurrence compared to conventional follow-up. The sensitivity and specificity of the SSVs in terms of detecting postsurgery relapse were 100%. CONCLUSIONS: We show that assessment of ctDNA is a non-invasive, exquisitely specific and highly sensitive approach for monitoring disease load, which has the potential to provide clinically relevant lead times compared with conventional methods. Furthermore, we provide a low-coverage protocol optimised for identifying SSVs with excellent correlation between SSVs identified in tumours and matched metastases. Application of ctDNA analysis has the potential to change clinical practice in the management of CRC.