Colorectal cancer (CRC) is a leading cause of cancer-related deaths, often diagnosed at late stages when treatment options are limited. Early detection through screening significantly improves survival rates. Current screening methods, such as fecal immunochemical tests (FIT) and colonoscopy, have limitations in sensitivity, specificity, or invasiveness. Circulating tumor DNA (ctDNA), a portion of DNA released from tumor cells into the bloodstream, offers a minimally invasive approach for early cancer detection. While ctDNA has shown promise in diagnosing CRC, most studies have focused on patients at the time of diagnosis or used selected populations. This study aimed to evaluate the ability of ctDNA markers to detect CRC up to two years before clinical diagnosis in an unselected population, mimicking a real-world screening setting. The Trøndelag Health Study (HUNT), a large longitudinal population health study, provided a suitable cohort for this investigation. The study hypothesized that a panel of known methylated ctDNA markers could be used to detect CRC in this setting and potentially lead to earlier diagnosis and improved patient outcomes.

Numerous studies have explored the potential of ctDNA as a liquid biopsy for CRC diagnosis, prognosis, and monitoring. Several methylated promoter regions have been identified as potential biomarkers for CRC detection in blood or stool samples. Some commercially available tests based on these markers, such as epi proColon 2.0 and ColoSure™, have shown varying sensitivities and specificities. However, the sensitivity of these tests in average-risk individuals is often low, highlighting the need for more sensitive and specific screening tools. While some studies have reported the detection of ctDNA years before CRC diagnosis, these studies were often prospective with limited sample sizes or focused on specific populations, limiting their generalizability to broader screening scenarios. This study aimed to address these limitations by using a large, unselected population and investigating the detection of CRC up to two years prior to clinical diagnosis.

This nested case-control study utilized data from the HUNT study (HUNT3 wave). 245 individuals diagnosed with colorectal adenocarcinoma within 54 months of providing a blood sample were identified. Controls were matched 1:1 to cases by sex and age (±1 year) and had no CRC diagnosis. Plasma samples were analyzed for methylation of 20 genes, selected based on previous research. The most specific markers (specificity >70%) were BMP3, FLT1, IKZF1, SFRP1, SFRP2, NPTX2, SLCA1, and VIM. DNA was extracted using the easyMAG® platform, and methylation analysis was performed using a multiplexed PCR approach (EpiTyper). Samples were randomly split into test (70%) and validation (30%) sets. The cutoff value for methylation was determined using the Youden index in the test set, and the results were validated in the independent validation set. Statistical analyses included chi-square tests for categorical variables and t-tests for continuous variables. Logistic regression was used to assess the association between markers and CRC status, adjusting for age, sex, BMI, and smoking. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the diagnostic performance of the marker panel.

The study analyzed plasma samples from 212 individuals (106 cases and 106 controls). The test and validation sets were comparable in terms of demographics and clinical characteristics. In the test set, chi-square analysis revealed significant associations between CRC and FLI1, IKZF1, SFRP2, and WNT5A methylation. A panel comprising the eight most specific single markers (BMP3, FLT1, IKZF1, SFRP1, SFRP2, NPTX2, SLCA1, and VIM) showed a sensitivity of 43% (95% CI 42.7–43.4) and specificity of 86% (95% CI 85.7–86.2) for detecting CRC up to 2 years before clinical diagnosis. The results were reproducible in the validation set. The area under the curve (AUC) for the panel was 0.67 (95% CI 0.58–0.76), indicating a moderate discriminatory ability. Further analysis revealed that at least two positive markers out of the eight resulted in higher sensitivity and specificity.

This study demonstrates the potential of a minimally invasive ctDNA-based test for early CRC detection in a population-based screening setting. The panel of eight methylated ctDNA markers showed acceptable sensitivity and high specificity for detecting CRC up to two years before clinical diagnosis. The findings support the hypothesis that incorporating ctDNA detection into CRC screening programs could lead to earlier diagnoses in a potentially curative setting. The study's use of a large, unselected population strengthens the generalizability of the results. The moderate discriminatory ability of the panel suggests that further refinement of the marker panel or combination with other biomarkers may improve diagnostic accuracy. This would allow for more targeted follow-up investigations such as colonoscopy. Future research should focus on prospective studies to confirm these results and assess the cost-effectiveness of incorporating ctDNA testing into CRC screening protocols.

This study demonstrates the feasibility of detecting CRC using a panel of eight methylated ctDNA markers up to two years prior to clinical diagnosis in an unselected population. These results support further investigation of ctDNA as a potential screening tool for CRC. Future prospective studies with larger cohorts are needed to validate these findings and assess the clinical utility and cost-effectiveness of this approach in real-world settings.

Several limitations should be considered. The plasma samples were collected before the study was planned, potentially affecting the quality of ctDNA analysis. The relatively low sensitivity of the panel requires further optimization. A high false-positive rate was observed with increasing Ct values, and false-negative results among cases were also noted. The study used a nested case-control design, which may be subject to selection bias. Despite these limitations, the study's large, unselected population and long observation time offer a valuable contribution to the field.