A genome-wide association study identifies single nucleotide polymorphisms associated with time-to-metastasis in colorectal cancer.

BACKGROUND: Differentiating between cancer patients who will experience metastasis within a short time and who will be long-term survivors without metastasis is a critical aim in healthcare. The microsatellite instability (MSI)-high tumor phenotype is such a differentiator in colorectal cancer, as patients with these tumors are unlikely to experience metastasis. Our aim in this study was to determine if germline genetic variations could further differentiate colorectal cancer patients based on the long-term risk and timing of metastasis.

METHODS: The patient cohort consisted of 379 stage I-III Caucasian colorectal cancer patients with microsatellite stable or MSI-low tumors. We performed univariable analysis on 810,622 common single nucleotide polymorphisms (SNPs) under different genetic models. Depending on the long-term metastasis-free survival probability estimates, we applied a mixture cure model, Cox proportional hazards regression model, or log-rank test. For SNPs reaching Bonferroni-corrected significance (p < 6.2 × 10- 8 ) having valid genetic models, multivariable analysis adjusting for significant baseline characteristics was conducted.

RESULTS: After adjusting for significant baseline characteristics, specific genotypes of ten polymorphisms were significantly associated with time-to-metastasis. These polymorphisms are three intergenic SNPs, rs5749032 (p = 1.28 × 10- 10 ), rs2327990 (p = 9.59 × 10- 10 ), rs1145724 (p = 3 × 10- 8 ), and seven SNPs within the non-coding sequences of three genes: FHIT (p = 2.59 × 10- 9 ), EPHB1 (p = 8.23 × 10- 9 ), and MIR7515 (p = 4.87 × 10- 8 ).

CONCLUSIONS: Our results suggest novel associations of specific genotypes of SNPs with early metastasis in Caucasian colorectal cancer patients. These associations, once replicated in other patient cohorts, could assist in the development of personalized treatment strategies for colorectal cancer patients.