Predicting ulcerative colitis-associated colorectal cancer using reverse-transcription polymerase chain reaction analysis

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.