Association of CTACK, IL-2, and IL-13 with increased risk of lung cancer: A Mendelian randomization study

In recent years, relevant studies have reported that inflammatory cytokines are related to the occurrence of cancer. However, the correlation with lung cancer is not clear. This study used the Mendelian random grouping method to investigate the correlation between inflammatory factors and lung cancer in different populations.

We obtained the single nucleotide polymorphisms (SNPs) of inflammatory cytokines through the open database and the SNPs of lung cancer (European and East Asian) through the IEU OpenGWAS project. Inverse variance-weighted (IVW) MR analyses were used to determine the causalities of exposures and outcomes. Supplementary analyses were also performed using weighted median and MR-Egger regressions. Afterward, sensitivity analyses were performed to test the robustness. Search the ChEMBL database for target drugs and indications for CTACK, IL-2, and IL-13.

By IVW method, we found that CTACK, IL-2, and IL-13 were associated with an increased risk of lung cancer in the European population (CTACK, OR = 1.098, 95 % CI 1.001-1.204, P = 0.047; IL-2, OR = 1.112, 95 % CI 1.009-1.225, P = 0.032; IL-13, OR = 1.068, 95 % CI 1.007-1.132, P = 0.029), while only IL-13 was associated with an increased risk of lung cancer in the East Asian population (IL-13, OR = 1.110, 95 % CI 1.010-1.220, P = 0.030). The weighted median and MR-Egger regression methods were in the same direction as the IVW effect sizes. Furthermore, no evidence of multidirectionality was detected using the MR-Egger intercept as a sensitivity analysis. Currently, there are no approved or phase III studied indications for CTACK, IL-2, and IL-13 targets in lung cancer.

The study outcomes supported that the inflammatory cytokines CTACK, IL-2, and IL-13 increase the risk of lung cancer. There is a lack of indications for drugs in these three targets. We explored the causal relationship between inflammatory cytokines and lung cancer, providing a basis for future cancer prediction models and targets for anti-tumor therapy.