This was a single-center, retrospective, real-world study conducted at the First Affiliated Hospital of Shantou University Medical College between January 2023 and December 2024. Eligible participants included patients diagnosed with CRC, patients with colorectal polyps, and healthy individuals undergoing routine physical examinations. Participants were recruited from the Departments of Gastroenterology, Oncology, and Gastrointestinal Surgery (both outpatient and inpatient), as well as from the health examination center. The study was approved by the Ethics Committee of the First Affiliated Hospital of Shantou University (approval No. II2025-048-01). Informed consent was not required as the study was retrospective, and data collected was de-identified.

Inclusion criteria: (1) CRC group: Patients aged 18–75 years with histologically confirmed CRC (via colonoscopic biopsy or surgical pathology), who had not received prior antitumor treatments (e.g., chemotherapy or radiotherapy), and with complete clinical data including imaging and laboratory results (12). (2) Polyp group: Patients aged 18–75 years with colorectal polyps detected by colonoscopy, histologically confirmed as adenomatous polyps, with a polyp diameter ≥5 mm and complete clinical data (13). (3) Healthy group: Individuals aged 18–75 years with normal results on routine physical examination, including blood tests, biochemistry, tumor markers, abdominal ultrasound, and chest CT; no history of malignancy in the past five years; no polyps or other lesions detected by colonoscopy; and complete clinical data.

Exclusion criteria: (1) Other malignancies; (2) severe cardiac, hepatic, or renal dysfunction; (3) autoimmune diseases such as systemic lupus erythematosus or rheumatoid arthritis; (4) acute infectious diseases (bacterial or viral); (5) pregnant or lactating women; (6) psychiatric disorders affecting compliance; (7) inflammatory bowel disease; (8) familial adenomatous polyposis or hereditary nonpolyposis colorectal cancer.

Peripheral venous blood (10 mL) was collected in EDTA-K2 tubes from fasting participants in the morning and gently inverted 8–10 times. Samples were processed within 2 hours. Plasma was obtained by centrifugation at 3,000 × g for 10 minutes and aliquoted (≥ 4 mL total; 0.5 mL per tube) into RNase-free tubes, then stored at −80°C to avoid repeated freeze–thaw cycles.

Before cfDNA extraction, plasma was thawed at room temperature. cfDNA was isolated using a magnetic bead-based protocol per the manufacturer’s instructions. Approximately 20 ng cfDNA (minimum ≥10 ng) was used for bisulfite conversion, and DNA was eluted in 15 µL. Purity was assessed by NanoDrop (A260/280 of 1.8–2.0). All cfDNA extraction and methylation analyses were performed at Guangzhou Huayin Medical Laboratory.

cfDNA was isolated from plasma and subjected to bisulfite conversion according to the manufacturer’s instructions. Converted DNA was used immediately or stored at 2–8°C for up to 24 h. Plasma ctDNA methylation was quantified using the ColonAiQ multi-gene methylation assay (Singlera Genomics, Shanghai, China), a commercial qPCR-based platform for colorectal cancer detection. The assay targets six CRC-associated methylation markers (SEPT9-R1, SEPT9-R2, BCAT1, IKZF1, BCAN, and VAV3).

Methylation levels were measured by multiplex real-time PCR, and ΔCt values for each marker were analyzed using a proprietary logistic-regression algorithm to generate individual marker scores. A gene was considered methylation-positive if P ≥ 6.0. For the multi-gene panel, a sample was classified as methylation-positive if at least one of the six genes was positive. All reactions were performed in triplicate and incorporated into the algorithm rather than interpreted by a single Ct threshold. The qPCR procedures and reporting follow the MIQE guidelines (14, 15). Details of the method are available in previous published study (10).

This algorithm-based strategy has been validated in large clinical cohorts and demonstrated high diagnostic performance for CRC (11). Reporting of diagnostic accuracy in this study adheres to the STARD 2015 guidelines (16). As the platform is proprietary, primer and probe sequences are not publicly disclosed; however, assay reproducibility and methodological transparency are supported by publicly available documentation and peer-reviewed validation studies (10).

Clinical information was extracted from the hospital’s electronic medical record system. Collected data included sex, age, clinical symptoms, Family History of CRC, CT/MRI findings, tumor location, cancer staging and laboratory test indicators.

Based on previously reported data, the positive rate of the multi-gene methylation assay in CRC was assumed to be approximately 85%, whereas the corresponding rate in patients with polyps or other non-CRC conditions was estimated to be around 60% (10). Using a two-sided test with a significance level of 0.05, a statistical power of 0.90, and an equal allocation ratio (1:1), the required sample size was calculated with PASS 2021 (two-independent-proportions procedure), yielding a minimum of 130 subjects in total (65 per group).

Statistical analyses were performed using SPSS version 25.0. Continuous variables were expressed as mean ± standard deviation ( x¯ ± s) and compared using independent sample t-tests or one-way ANOVA. Categorical variables were reported as counts and percentages, and comparisons were made using the χ² test or Fisher’s exact test.

Participants were randomly stratified into training and validation sets at a 7:3 ratio. Propensity score matching (PSM) was applied for pairwise comparisons (healthy vs. polyp, polyp vs. CRC) at a 1:1 ratio based on matching variables such as age and sex. An ordinal logistic regression model was constructed for multi-gene methylation diagnosis.

The diagnostic performance of individual and combined methylation markers was evaluated using receiver operating characteristic (ROC) curve analysis. Area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Internal validation was performed using the bootstrap method with 2000 resampling iterations.

The Cochran–Armitage trend test was used to assess the increasing trend of methylation positivity across the three-stage disease progression (healthy → polyp → CRC). Multivariate logistic regression models were constructed to explore potential predictive factors associated with multi-gene methylation positivity, with results presented as odds ratios (ORs) and 95% confidence intervals (CIs). A two-sided P-value < 0.05 was considered statistically significant.

A total of 180 CRC patients (CRC group), 120 colorectal polyp patients (polyp group), and 150 healthy individuals (healthy group) were enrolled. In the CRC group, there were 104 males and 76 females, with a mean age of 62.8 ± 8.5 years old. According to the TNM staging system, there were 36 patients in stage I, 52 in stage II, 62 in stage III, and 30 in stage IV. The tumor was located in the colon in 99 cases and in the rectum in 81 cases. In the polyp group, 68 were male and 52 were female, with a mean age of 58.2 ± 9.8 years old. All polyps were histologically confirmed as adenomas, including 72 tubular adenomas, 28 villous adenomas, and 20 tubulovillous adenomas. In the healthy group, there were 82 males and 68 females, with a mean age of 56.5 ± 10.2 years old. No statistically significant differences were found with respect to sex, age, and BMI (P > 0.05), whereas higher levels of CEA and CA19–9 were observed in the CRC group (P < 0.05). The study flowchart is presented in Figure 1, and the baseline characteristics of the participants are presented in Table 1.

The methylation-positive rates of the six gene loci (SEPT9-R1, SEPT9-R2, BCAT1, IKZF1, BCAN, and VAV3) across the healthy, colorectal polyp, and CRC groups are summarized in Table 2. All six loci demonstrated significant differences among the three groups (all P < 0.001), with a clear stepwise increase from healthy controls to patients with polyps and then to CRC (all trend P < 0.001). Specifically, the multi-gene positivity rate was lowest in the healthy group (9.3%), intermediate in the polyp group (56.7%), and highest in the CRC group (91.7%).

The positive rates of multi-gene methylation were further analyzed across different TNM stages of CRC. A progressive increase in methylation positivity was observed with advancing tumor stage, and the differences were statistically significant (P < 0.05 for all markers). Notably, the positivity rate of the multi-gene methylation rose from 86.1% in stage I to 96.7% in stage IV, indicating a strong positive association between methylation burden and tumor severity (Figure 2; Supplementary Table 1).

CRC patients were randomly and stratifiedly assigned to a training set and a validation set in a 7:3 ratio. Baseline characteristics for both cohorts are shown in Supplementary Table 2, with no significant differences observed between the groups. The multi-gene methylation assay demonstrated excellent overall performance for CRC detection, with a sensitivity of 91.7% and specificity of 93.3%. The AUC were 0.958 (95% CI: 0.934–0.982) in the training cohort and 0.952 (95% CI: 0.920–0.984) in the validation cohort, outperforming any single-gene marker (Figure 3). The overall diagnostic accuracy was 92.4%, with a PPV of 94.3% and an NPV of 90.3%. Detailed results are presented in Table 3.

Multivariate analysis was conducted to evaluate the association between clinical characteristics and multi-gene methylation positivity in CRC patients. The results showed that tumor size (OR = 1.974, 95% CI: 1.321–2.950, P = 0.005) and TNM stage (OR = 2.117, 95% CI: 1.452–3.087, P = 0.002) were independent predictors of multi-gene methylation positivity (Supplementary Table 3).