Biomarkers for non-small cell lung cancer risk using multi-omics approaches: a nested case-control study

Abstract

Background: Lung cancer poses a major public health challenge, accounting for the highest cancer-related mortality worldwide. This study aimed to identify non-invasive biomarkers for the early detection of non-small cell lung cancer (NSCLC) risk. Methods: We randomly selected 150 incident NSCLC cases during follow-up from the Korean Cancer Prevention Study-II. Controls (n=150) were matched to cases by age, gender, and the time of blood collection. Non-targeted metabolite screening by ultra-high-performance liquid chromatography (UHPLC)/ mass spectrometry (MS) was conducted on the pre-diagnostic biological samples. The 11 reported lung cancer-associated single-nucleotide polymorphisms (SNPs) in Koreans were extracted from DNA genotyping data of the study population. Metabolite markers related to NSCLC risk were identified through clustering using hierarchical density-based spatial clustering of applications with noise. The associations between smoking, dietary factors, and NSCLC were also examined. Results: Six discriminative serum metabolites were identified as having an association with NSCLC incidence. Notably, the relationship between specific metabolite levels and NSCLC risk differed by rs7086803 genotype. Smoking status and occupational exposures appear to influence specific metabolite profiles, while dietary vegetable intake may modulate the risk of NSCLC among smokers. Conclusions: The meaningful biomarkers revealed in the current research could be used to enhance the predictive ability for NSCLC risk. Furthermore, we suggest that the protective role of dietary vegetables against NSCLC may be attenuated or absent in smokers.