Abstract

Biomarkers based on germline DNA variations could have translational implications by identifying prognostic factors and sub-classifying patients to tailored, patient-specific treatment. To investigate the association between germline variations in interleukin (IL) genes and lung cancer outcomes, we genotyped 251 single nucleotide polymorphisms (SNPs) from 33 different IL genes in 651 non-small cell lung cancer (NSCLC) patients. Analyses were performed to investigate overall survival, disease-free survival, and recurrence. Our analyses revealed 24 different IL SNPs significantly associated with one or more of the lung cancer outcomes of interest. The GG genotype of IL16:rs7170924 was significantly associated with disease-free survival (HR = 0.65; 95% CI 0.50-0.83) and was the only SNP that produced a false discovery rate (FDR) of modest confidence that the association is unlikely to represent a false-positive result (FDR = 0.142). Classification and regression tree (CART) analyses were used to identify potential higher-order interactions. We restricted the CART analyses to the five SNPs that were significantly associated with multiple endpoints (IL1A:rs1800587, IL1B:rs1143634, IL8:s12506479, IL12A:rs662959, and IL13:rs1881457) and IL16:rs7170924 which had the lowest FDR. CART analyses did not yield a tree structure for overall survival; separate CART tree structures were identified for recurrence, based on three SNPs (IL13:rs1881457, IL1B:rs1143634, and IL12A:rs662959), and for disease-free survival, based on two SNPs (IL12A:rs662959 and IL16:rs7170924), which may suggest that these candidate IL SNPs have a specific impact on lung cancer progression and recurrence. These data suggest that germline variations in IL genes are associated with clinical outcomes in NSCLC patients.

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