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  • Title: Predicting ulcerative colitis-associated colorectal cancer using reverse-transcription polymerase chain reaction analysis.
    Author: Watanabe T, Kobunai T, Yamamoto Y, Ikeuchi H, Matsuda K, Ishihara S, Nozawa K, Iinuma H, Kanazawa T, Tanaka T, Yokoyama T, Konishi T, Eshima K, Ajioka Y, Hibi T, Watanabe M, Muto T, Nagawa H.
    Journal: Clin Colorectal Cancer; 2011 Jun; 10(2):134-41. PubMed ID: 21859567.
    Abstract:
    BACKGROUND: Widespread genetic alterations are present not only in ulcerative colitis (UC)-associated neoplastic lesions but also in the adjacent normal colonic mucosa. This suggests that genetic changes in nonneoplastic mucosa might be effective markers for predicting the development of UC-associated cancer (UC-Ca). This study aimed to build a predictive model for the development of UC-Ca based on gene expression levels measured by reverse-transcription polymerase chain reaction (RT-PCR) analysis in nonneoplastic rectal mucosa. PATIENTS AND METHODS: Fifty-three UC patients were examined, of which 10 had UC-Ca and 43 did not (UC-NonCa). In addition to the 40 genes and transcripts previously shown to be predictive for developing UC-Ca in our microarray studies, 149 new genes, reported to be important in carcinogenesis, were selected for low density array (LDA) analysis. The expression of a total of 189 genes was examined by RT-PCR in nonneoplastic rectal mucosa. RESULTS: We identified 20 genes showing differential expression in UC-Ca and UC-NonCa patients, including cancer-related genes such as CYP27B1, RUNX3, SAMSN1, EDIL3, NOL3, CXCL9, ITGB2, and LYN. Using these 20 genes, we were able to build a predictive model that distinguished patients with and without UC-Ca with a high accuracy rate of 83% and a negative predictive value of 100%. CONCLUSION: This predictive model suggests that it is possible to identify UC patients at a high risk of developing cancer. These results have important implications for improving the efficacy of surveillance by colonoscopy and suggest directions for future research into the molecular mechanisms of UC-associated cancer.
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