Prognostic impact of blood biomarkers TS and DPD in neoadjuvant-treated esophageal cancer patients.

BACKGROUND/AIM: The prognostic value of TS (thymidylate synthase) and DPD (dihydropyrimidine dehydrogenase) RNA expression in the blood of patients with esophageal cancer is not known. The aim of the present study was to evaluate the significance of these molecular alterations in the blood as a prognostic marker for patients with neoadjuvant-treated esophageal cancer. PATIENTS AND METHODS: A total of 29 patients with locally advanced esophageal cancer (cT3-T4, Nx, M0) were enrolled in this prospective study. All patients received neoadjuvant chemoradiation followed by a transthoracic resection (curative transthoracic en bloc esophagectomy, RO). Peripheral blood samples were drawn before initiation of therapy. The analysis was performed using quantitative real-time-polymerase chain reaction (RT-PCR). The histomorphological regressions grading after neoadjuvant therapy was defined as follows: major response (MaR)=less than 10% vital tumor tissue, minor response (MiR)=more than 10% vital tumor tissue. RESULTS: Nineteen out of 29 patients (65.5%) had a MiR and 10 (34.5%) had a MaR. The median survival of patients was 2.08 years (range=0.15-4.53). Among the tested genes, the RNA expression of TS was significantly associated with prognosis of patients. Patients with TS expression above 0.78 had a median survival of 1.1 years (range=0.21-3.96) compared to 2.6 years (range=0.15 to 4.53) in patients with TS expression lower than 0.78 (p=0.031, log rank test). There was no association between clinical variables (e.g., tumor stage, gender, age, etc.) and the RNA expression of TS in the serum. CONCLUSION: The RNA expression of TS in the blood is a potential prognostic marker in patients with neoadjuvant-treated esophageal cancer. The significance of these molecular alterations as non-invasive prognostic marker for esophageal cancer should be evaluated in prospective studies.

XRCC1 gene polymorphism for prediction of response and prognosis in the multimodality therapy of patients with locally advanced rectal cancer.

BACKGROUND: Neoadjuvant treatment strategies have been developed to improve survival of patients with locally advanced rectal cancer. Since mainly patients with major histopathologic response benefit from this therapy, predictive markers are needed. The gene polymorphism of the X-ray-repair-cross complementing (XRCC1-) gene (rs25487) was analyzed to predict response to neoadjuvant radiochemotherapy and prognosis in patients with locally advanced rectal cancer. PATIENTS AND METHODS: 81 patients (51 male; 30 female; median age 59 years) with locally advanced rectal cancer were included in this study. All patients received a neoadjuvant radiochemotherapy (50.4 Gy, 5-FU) followed by surgical therapy. Histomorphologic regression was defined as major response when resected specimens contained less than 10% viable tumor cells (n = 28) and minor response when more than 10% viable tumor cells (n = 53) were detected in the surgical specimen. Genomic DNA was extracted from paraffin-embedded tissues of all study patients. Allelic discrimination was performed by real-time polymerase chain reaction. Two allele-specific TaqMan probes in competition were used for amplification of the XRCC1 gene. Allelic genotyping was correlated with therapy response and prognosis. RESULTS: Single-nucleotide polymorphism XRCC1 A399G (rs25487) was predictive for therapy response (P = 0.039). Within the AG genotype group, 17 (53%) patients showed a minor response and 15 (47%) patients a major response. In contrast, 39 (78%) of the patients with homogeneous AA or GG genotype were minor responders and only 11 (22%) major responders. No prognostic value was revealed for the XRCC1 A399G (rs25487) gene polymorphism in the multimodality therapy. CONCLUSION: Our data supports the role of XRCC1 as a predictive marker for therapy response in the multimodality therapy of patients with locally advanced rectal cancer. Single-nucleotide polymorphism XRCC1 A399G (rs25487) could be applied to individualize treatment strategies.