Genetic Variations in the PI3K/PTEN/AKT/mTOR Pathway Are Associated With Clinical Outcomes in Esophageal Cancer Patients Treated With Chemoradiotherapy

Abstract

Purpose The phosphoinositide-3-kinase (PI3K), phosphatase and tensin homolog (PTEN), v-akt murine thymoma viral oncogene homolog (AKT), and mammalian target of rapamycin (mTOR) signaling pathway has been implicated in resistance to several chemotherapeutic agents. In this retrospective study, we determined whether common genetic variations in this pathway are associated with clinical outcomes in esophageal cancer patients with adenocarcinoma or squamous cell carcinoma who have undergone chemoradiotherapy and surgery. Patients and Methods Sixteen tagging single nucleotide polymorphisms (SNPs) in PIK3CA, PTEN, AKT1, AKT2, and FRAP1 (encoding mTOR) were genotyped in these patients and analyzed for associations with response to therapy, survival, and recurrence. Results We observed an increased recurrence risk with genetic variations in AKT1 and AKT2 (hazard ratio [HR], 2.21; 95% CI, 1.06 to 4.60; and HR, 3.30; 95% CI, 1.64 to 6.66, respectively). This effect was magnified with an increasing number of AKT adverse genotypes. In contrast, a predictable protective effect by PTEN genetic variants on recurrence was evident. Survival tree analysis identified higher-order interactions that resulted in variation in recurrence-free survival from 12 to 42 months, depending on the combination of SNPs. Genetic variations in AKT1, AKT2, and FRAP1 were associated with survival. Patients homozygous for either of the FRAP1 SNPs assayed had a more than three-fold increased risk of death. Two genes—AKT2 and FRAP1—were associated with a poor treatment response, while a better response was associated with heterozygosity for AKT1:rs3803304 (odds ratio, 0.50; 95% CI, 0.25 to 0.99). Conclusion These results suggest that common genetic variations in this pathway modulate clinical outcomes in patients who undergo chemoradiotherapy. With further validation, these results may be used to build a model of individualized therapy for the selection of the optimal chemotherapeutic regimen.