Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
Use of circulating microRNAs to identify high-risk adenomas among FIT+ patients undergoing screening colonoscopy.
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Sutherland R Liam, Ruan Yibing, Warkentin Matthew T, O'Sullivan Dylan E, Hutchinson John M, McIntyre John B, Forbes Nauzer, Cheung Winson Y, Lix Lisa, Tinmouth Jill, Rabeneck Linda, Hilsden Robert J, Brenner Darren R
Аннотация
BACKGROUND: Colonoscopy prevents colorectal cancer (CRC) but is invasive and resource intensive. Circulating microRNAs (miRNAs) may improve risk stratification of fecal immunochemical test (FIT)-positive individuals by identifying high-risk adenomas (HRAs). We evaluated the association of circulating miRNAs with HRAs and their contribution to risk prediction models (RPMs).
METHODS: We analyzed 398 FIT-positive participants from a Canadian screening cohort (160 HRAs; 238 controls). Plasma miRNAs were quantified using NanoString nCounter. Differential expression was assessed using two-tailed t-tests with Bonferroni correction, and LASSO regression identified predictive miRNAs. Five RPMs were developed (Baseline, Bonferroni, Bonferroni+Baseline, LASSO, LASSO+Baseline) and evaluated using AUCs, DeLong's test, calibration, bootstrap validation, and decision curve analysis.
RESULTS: Eleven miRNAs were Bonferroni-significant, and LASSO retained 8 predictors. The Baseline model had an optimism-corrected AUC of 0.61, increasing to 0.80 with these miRNAs and 0.82 with baseline variables added; the LASSO+Baseline model achieved an AUC of 0.82 with good calibration. All miRNA-enhanced models outperformed Baseline (P<0.001) and showed greater net benefit on decision curve analysis. At a 20% threshold, the LASSO+Baseline model achieved 95.0% sensitivity and 56.7% PPV. Conclusions Circulating miRNAs substantially improved identification of HRAs among FIT-positive individuals with clinical utility.
IMPACT: These data support further evaluation of miRNA-informed RPMs to refine CRC screening.
METHODS: We analyzed 398 FIT-positive participants from a Canadian screening cohort (160 HRAs; 238 controls). Plasma miRNAs were quantified using NanoString nCounter. Differential expression was assessed using two-tailed t-tests with Bonferroni correction, and LASSO regression identified predictive miRNAs. Five RPMs were developed (Baseline, Bonferroni, Bonferroni+Baseline, LASSO, LASSO+Baseline) and evaluated using AUCs, DeLong's test, calibration, bootstrap validation, and decision curve analysis.
RESULTS: Eleven miRNAs were Bonferroni-significant, and LASSO retained 8 predictors. The Baseline model had an optimism-corrected AUC of 0.61, increasing to 0.80 with these miRNAs and 0.82 with baseline variables added; the LASSO+Baseline model achieved an AUC of 0.82 with good calibration. All miRNA-enhanced models outperformed Baseline (P<0.001) and showed greater net benefit on decision curve analysis. At a 20% threshold, the LASSO+Baseline model achieved 95.0% sensitivity and 56.7% PPV. Conclusions Circulating miRNAs substantially improved identification of HRAs among FIT-positive individuals with clinical utility.
IMPACT: These data support further evaluation of miRNA-informed RPMs to refine CRC screening.