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Jiayi Shen



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    P2.04 - Immuno-oncology (ID 167)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Immuno-oncology
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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      P2.04-13 - Interleukin-18 and Lung Cancer: A Mendelian Randomization Study (ID 336)

      10:15 - 18:15  |  Author(s): Jiayi Shen

      • Abstract
      • Slides

      Background

      Previous studies have shown that Interleukin-18 (IL-18) suppresses the growth of lung cancer. IL-18 might restore natural killer cell-mediated immunosurveillance against MHC class I-deficient tumors and enhance the therapeutic effects of cancer immunotherapy. However, whether there is a causal influence of higher IL-18 protecting against lung cancer remains unknown. We aim to explore whether genetically predicted circulating level of IL-18 is associated with lung cancer through 2-sample Mendelian randomization (MR) analysis.

      Method

      We obtained the summary data for significant single-nucleotide polymorphisms (SNPs, P<5×10–8 ) associated with serum IL-18 from a genome-wide association study of 8293 healthy adults. Their associations with lung cancer and its histological subtypes were evaluated in the International Lung Cancer Consortium (ILCCO, 11348 lung cancer cases, and 15861 controls) applying Inverse variance–weighted (IVW) meta-analysis, Weighted-median analysis, Mendelian randomization–Egger regression, Simple mode method, and Weighted mode method. We also performed several sensitivity analyses to evaluate the potential violation of MR assumptions.

      Result

      Genetically predicted IL-18 level is associated with lower risk of lung cancer (Odds ratio [OR] per 1 standard deviation (SD) increase: 0.824, 95% confidence interval (CI) 0.762-0.890, p<0.001). Similar trends were shown in the histological subtypes of lung cancer: lung adenocarcinoma (OR per 1 SD increase: 0.816, 95%CI 0.708-0.941, p=0.005) and squamous cell lung cancer (OR per 1 SD increase: 0.883, 95%CI 0.787-0.990, p=0.034). Our sensitivity analyses also showed that there was no directional pleiotropy bias and horizontal pleiotropy bias.

      Table 1. Mendelian randomization estimates of associations of genetically predicted circulating IL-18 and lung cancer and its histological subtypes using different analysis methods.

      Variants

      Outcome

      Method

      OR

      95%CI

      P value

      Heterogeneity p

      MR-Egger intercept p

      IL-18

      Lung cancer

      IVW

      0.824

      0.762-0.890

      <0.001*

      0.868

      MR Egger

      0.964

      0.750-1.239

      0.787

      0.976

      0.251

      Weighted median

      0.823

      0.748-0.906

      <0.001*

      Simple mode

      0.826

      0.714-0.955

      0.042*

      Weighted mode

      0.826

      0.727-0.938

      0.026*

      IL-18

      Lung adenocarcinoma

      IVW

      0.816

      0.708-0.941

      0.005*

      0.216

      MR Egger

      1.137

      0.752-1.720

      0.568

      0.372

      0.159

      Weighted median

      0.840

      0.713-0.989

      0.036*

      Simple mode

      0.807

      0.622-1.046

      0.156

      Weighted mode

      0.827

      0.663-1.032

      0.144

      IL-18

      Squamous cell lung cancer

      IVW

      0.883

      0.787-0.990

      0.034*

      0.809

      MR Egger

      0.791

      0.557-1.123

      0.247

      0.765

      0.545

      Weighted median

      0.927

      0.803-1.070

      0.301

      Simple mode

      0.919

      0.736-1.146

      0.480

      Weighted mode

      0.939

      0.765-1.153

      0.572

      *: P value < 0.05; IVW: inverse­variance weighted; OR: odds ratio; CI: confidence interval.

      Conclusion

      Genetically predicted higher IL-18 is causally associated with lower lung cancer risk, indicating that IL-18 might have the potential to be used clinically to protect against lung cancer. Additional work is warranted to confirm the causality and underline the potential mechanisms.

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