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Published on: April 17, 2026
CT-Derived Radiomic Signature of MUC6 Expression Improves Guideline-Based Risk Stratification in Intraductal
Evan W Davis1,2, Margaret A Park2,3, Toni L Basinski2
1Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
Background And Aims:
Accurate pre-operative identification of high-risk intraductal papillary mucinous neoplasms (IPMNs) remains a major clinical challenge, particularly for branch-duct (BD) lesions where guideline-based criteria incompletely capture biologic aggressiveness. We investigated whether tumoral mucin expression identifies high-risk IPMN pathology (i.e., high-grade dysplasia or invasive carcinoma) and whether computed tomography (CT)-derived radiomic features can serve as non-invasive biomarkers to enhance pre-operative risk assessment beyond international consensus guidelines (ICG) criteria.
Methods:
Multiplex immunofluorescence quantified MUC1, MUC2, MUC5AC, and MUC6 expression in tissue microarrays from 101 surgically resected IPMNs classified as low-risk (low-grade dysplasia) or high-risk (high-grade dysplasia or invasive carcinoma). Associations were evaluated using Wilcoxon rank-sum tests, and their discriminatory capability evaluated using receiver operating characteristic curves. For mucins predictive of high-risk pathology, a CT-based 'radiomic' signature was developed. Incremental value beyond ICG criteria was evaluated using discrimination metrics and decision curve analysis.
Results:
Reduced MUC6 expression was significantly associated with high-risk pathology (p = 0.001) and had the highest discriminatory performance (AUC = 0.72). A CT-derived radiomic signature predictive of low MUC6 expression achieved an AUC of 0.75 and, when integrated with ICG high-risk stigmata (HRS), demonstrated improved discrimination and favorable decision-curve characteristics compared with HRS alone, including among BD-IPMNs.
Conclusions:
Loss of tumoral MUC6 expression is associated with high-risk IPMN pathology and may be approximated using CT-derived radiomic features, supporting the feasibility of non-invasive molecular phenotyping. These findings suggest that integration of molecular and imaging biomarkers with guideline-based criteria may enhance pre-operative IPMN risk stratification; however, prospective external validation in broader surveillance populations and multi-institutional cohorts is warranted prior to clinical implementation.