Semiquantitative immunohistochemistry for mucin (MUC1, MUC2, MUC3, MUC4, MUC5AC, and MUC6) profiling of pancreatic ductal cell adenocarcinoma improves diagnostic and prognostic performance

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Abstract

Aims:

Mucin (MUC) glycoproteins are involved in various steps of the carcinogenesis and progression of human malignancies. The aim of this study was to verify whether semiquantitative evaluation of MUC staining by immunohistochemistry may help to differentiate pancreatic ductal cell adenocarcinoma (PDAC) from chronic pancreatitis and normal pancreas.

Methods and results:

Mucin expression was examined by immunohistochemistry in surgical specimens resected from 101 patients with PDAC and 33 with chronic pancreatitis, and in 40 normal pancreatic tissue specimens. A quickscore (QS, range 0–300) was calculated by multiplying staining intensity by the percentage of positive cells. A diagnostic model was developed for MUC QS (MUC1, MUC2, MUC3, MUC4, MUC5AC, and MUC6), based on a receiver operating characteristic (ROC) curve and logistic regression analysis. Median QS values for MUC1 and MUC5AC were significantly higher for PDAC, whereas patients with non-malignant tissues had higher values for MUC3 and MUC6. The area under the curve for the ROC curve derived from the diagnostic model including MUC3, MUC5AC and MUC6 was 0.96 [95% confidence interval (CI) 0.91–0.98], with 85% sensitivity and 94% specificity. Median QS values for MUC2 were significantly higher in patients with less advanced tumours, whereas venous invasion was associated with a lower QS for MUC6. Moreover, multivariate survival analysis revealed that low MUC6 expression was a negative prognostic factor, with a hazard ratio of 1.73 (95% CI 1.07–2.81).

Conclusions:

The three-MUC diagnostic model (MUC3, MUC5AC, and MUC6) showed an excellent ability to discriminate pancreatic cancer from non-malignant tissues, and yielded information that may prove useful for the development of clinical applications.

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