A Large-Scale Genome-Wide Gene-Gene Interaction Study of Lung Cancer Susceptibility in Europeans With a Trans-Ethnic...

Although genome-wide association studies have been conducted to investigate genetic variation of lung tumorigenesis, little is known about gene-gene (G × G) interactions that may influence the risk of non-small cell lung cancer (NSCLC).

Leveraging a total of 445,221 European-descent participants from the International Lung Cancer Consortium OncoArray project, Transdisciplinary Research in Cancer of the Lung and UK Biobank, we performed a large-scale genome-wide G × G interaction study on European NSCLC risk by a series of analyses. First, we used BiForce to evaluate and rank more than 58 billion G × G interactions from 340,958 single-nucleotide polymorphisms (SNPs). Then, the top interactions were further tested by demographically adjusted logistic regression models. Finally, we used the selected interactions to build lung cancer screening models of NSCLC, separately, for never and ever smokers.

With the Bonferroni correction, we identified eight statistically significant pairs of SNPs, which predominantly appeared in the 6p21.32 and 5p15.33 regions (e.g., rs521828_C6orf10 and rs204999_PRRT1, OR_interaction = 1.17, p = 6.57 × 10^-13; rs3135369_BTNL2 and rs2858859_HLA-DQA1, OR_interaction = 1.17, p = 2.43 × 10^-13; rs2858859_HLA-DQA1 and rs9275572_HLA-DQA2, OR_interaction = 1.15, p = 2.84 × 10^-13; rs2853668_TERT and rs62329694_CLPTM1L, OR_interaction = 0.73, p = 2.70 × 10^-13). Notably, even with much genetic heterogeneity across ethnicities, three pairs of SNPs in the 6p21.32 region identified from the European-ancestry population remained significant among an Asian population from the Nanjing Medical University Global Screening Array project (rs521828_C6orf10 and rs204999_PRRT1, OR_interaction = 1.13, p = 0.008; rs3135369_BTNL2 and rs2858859_HLA-DQA1, OR_interaction = 1.11, p = 5.23 × 10^-4; rs3135369_BTNL2 and rs9271300_HLA-DQA1, OR_interaction = 0.89, p = 0.006). The interaction-empowered polygenetic risk score that integrated classical polygenetic risk score and G × G information score was remarkable in lung cancer risk stratification.

Important G × G interactions were identified and enriched in the 5p15.33 and 6p21.32 regions, which may enhance lung cancer screening models.