부산대학교 도서관

PurposeTumor levels of thymidylate synthase (TS), a target of 5-fluorouracil (5-FU)-based chemotherapy for colorectal cancer, have been studied as a predictive or prognostic biomarker with mixed results.Patients and methodsTumor TS levels were prospectively evaluated in two adjuvant therapy trials for patients with resected stage II or III colon cancer. TS expression was determined by standard immunohistochemistry and by automated quantitative analysis. Tumor mismatch repair deficiency (MMR-D) and BRAF c.1799T > A (p.V600E) mutation status were also examined. Relationships between tumor TS, MMR-D, and BRAF mutation status, overall survival (OS), and disease-free survival (DFS) were investigated in the subset of stage III patients.ResultsPatients whose tumors demonstrated high TS expression experienced better treatment outcomes, with DFS hazard ratio (HR) = 0.67, 95% confidence interval (CI) = 0.53, 0.84; and OS HR = 0.68, 95% CI = 0.53, 0.88, for high versus low TS expression, respectively. No significant interaction between TS expression and stage was observed (DFS: interaction HR = 0.94; OS: interaction HR = 0.94). Tumors with high TS expression were more likely to demonstrate MMR-D (22.2% vs. 12.8%; p =  .0003). Patients whose tumors demonstrated both high TS and MMR-D had a 7-year DFS of 77%, compared with 58% for those whose tumors had low TS and were non-MMR-D (log-rank p =  .0006). Tumor TS expression did not predict benefit of a particular therapeutic regimen.ConclusionThis large prospective analysis showed that high tumor TS levels were associated with improved DFS and OS following adjuvant therapy for colon cancer, although tumor TS expression did not predict benefit of 5-FU-based chemotherapy. The Oncologist 2017;22:107-114Implications for Practice: This study finds that measurement of tumor levels of thymidylate synthase is not helpful in assigning specific adjuvant treatment for colorectal cancer. It also highlights the importance of using prospective analyses within treatment clinical trials as the optimal method of determining biomarker utility.