Thyroid cancer (TC) is the most common endocrine malignancy and its incidence continues to rise worldwide. Ionizing radiation exposure is the best established etiological factor. Heritability is high; however, despite valuable contribution from recent genome-wide association studies, the current understanding of genetic susceptibility to TC remains limited. Several studies suggest that altered function or expression of the DNA mismatch repair (MMR) system may contribute to TC pathogenesis. Therefore, the present study aimed to evaluate the potential role of a panel of MMR single nucleotide polymorphisms (SNPs) on the individual susceptibility to well-differentiated TC (DTC). A case-control study was performed involving 106 DTC patients and 212 age- and gender-matched controls, who were all Caucasian Portuguese. Six SNPs present in distinct MMR genes (MLH1 rs1799977, MSH3 rs26279, MSH4 rs5745325, PMS1 rs5742933, MLH3 rs175080 and MSH6 rs1042821) were genotyped through TaqMan® assays and genotype-associated risk estimates were calculated. An increased risk was observed in MSH6 rs1042821 variant homozygotes [adjusted odds ratio (OR)=3.42, 95% CI: 1.04-11.24, P=0.04, under the co-dominant model; adjusted OR=3.84, 95% CI: 1.18-12.44, P=0.03, under the recessive model]. The association was especially evident for the follicular histotype and female sex. The association was also apparent when MSH6 was analysed in combination with other MMR SNPs such as MSH3 rs26279. Interestingly, two other SNP combinations, both containing the MSH6 heterozygous genotype, were associated with a risk reduction, suggesting a protective effect for these genotype combinations. These data support the idea that MMR SNPs such as MSH6 rs1042821, alone or in combination, may contribute to DTC susceptibility. This is coherent with the limited evidence available. Nevertheless, further studies are needed to validate these findings and to establish the usefulness of these SNPs as genetic susceptibility biomarkers for DTC so that, in the near future, cancer prevention policies may be optimized under a personalized medicine perspective.