Common genetic variation in the germline influences where and how tumors develop

Identification of host variants associated with overall survival of esophageal cancer patients receiving platinum-based therapy

Aim: Clinical features of esophageal cancer (EC) patients have poor prognostic power. Thus, it is paramount to discover biomarkers that can allow a more accurate survival prediction. Methods: To detect genetic variants associated with survival, DNA from 120 patients treated with cisplatin-based neoadjuvant therapy were genotyped using drug metabolism enzymes and transporters array. Results: We identified two variants: the rs2038067 in PPARD (p = 0.0004) and the rs683369 (F160L) in SLC22A1 (p = 0.001). Their prognostic power was greater than that of clinical stage alone (p = 0.017) and comparable to that of response to neoadjuvant therapy (p = 0.71). Interestingly, the prognostic accuracy of response models increased significantly when genetic variables were included (p = 0.003). Conclusion: Our data, though preliminary, strengthen the potential utility of germline variants for a better-tailored management of EC patients.

Functional germline variants as potential co-oncogenes

Germline variants that affect the expression or function of proteins contribute to phenotypic variation in humans and likely determine individual characteristics and susceptibility to diseases including cancer. A number of high penetrance germline variants that increase cancer risk have been identified and studied, but germline functional polymorphisms are not typically considered in the context of cancer biology, where the focus is primarily on somatic mutations. Yet, there is evidence from familial cancers indicating that specific cancer subtypes tend to arise in carriers of high-risk germline variants (e.g., triple negative breast cancers in mutated BRCA carriers), which suggests that pre-existing germline variants may determine which complementary somatic driver mutations are needed to drive tumorigenesis. Recent genome sequencing studies of large breast cancer cohorts reported only a handful of highly recurrent driver mutations, suggesting that different oncogenic events drive individual cancers. Here, we propose that germline polymorphisms can function as oncogenic modifiers, or co-oncogenes, and these determine what complementary subsequent somatic events are required for full malignant transformation. Therefore, we propose that germline aberrations should be considered together with somatic mutations to determine what genes drive cancer and how they may be targeted.