RT Journal Article
SR Electronic
T1 Gene Polymorphisms MTHFRC677T and MTRA2756G as Predictive Factors in Adjuvant Chemotherapy for Stage III Colorectal Cancer
JF Anticancer Research
JO Anticancer Res
FD International Institute of Anticancer Research
SP 3057
OP 3062
VO 31
IS 9
A1 HELENA TAFLIN
A1 YVONNE WETTERGREN
A1 ELISABETH ODIN
A1 GĂ–RAN CARLSSON
A1 KRISTOFFER DERWINGER
YR 2011
UL http://ar.iiarjournals.org/content/31/9/3057.abstract
AB Background: The aim of this study was to explore the effect in stage III colorectal cancer of functional gene polymorphisms methylenetetrahydrofolate reductase (MTHFR C677T) and methionine synthase (A2756G), in the folate metabolism on outcome and risk of toxicity for adjuvant chemotherapy. A secondary aim was to investigate any possible interdependency between the two genes. Patients and Methods: one hundred and fifty randomly chosen patients with stage III colorectal cancer, treated with adjuvant chemotherapy, were genotyped by real-time PCR. Patient and treatment data were retrieved and assessed for demography, pathology, chemotherapy tolerability and survival after adjuvant therapy. The polymorphisms were studied separately and in combination to discover possible interactions. Results: Patients with MTHFR 677 CC genotype carried lower risks of suffering from nausea (p=0.027), parasthesia (p=0.0042) and need for dose reduction (p=0.025). The CC genotype was also associated with better survival (p<0.034). There was interdependency with MTR A2756G. Patients with MTR AG/GG in combination with MTHFR CT/TT genotypes carried the highest risk of side-effects. Conclusion: Functional polymorphisms of MTHFR C677T and MTR A2756G can affect outcome and risk of toxicity during adjuvant chemotherapy in stage III colorectal cancer. Their possible interdependence brings attention to the function of folate metabolism overall regarding its association with 5-fluoruracil related toxicity. Our results could explain some of the difficulties of obtaining reproducible and uniform results when using single polymorphisms as predictive markers.