Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin‐1β pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation‐focused lung cancer therapies at the genetic level. While numerous genome‐wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome‐wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow‐up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor‐κB signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow‐up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome‐wide annotation data in analysis of genetic association studies.

中文翻译：

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整合多组学注释数据来确定鳞状细胞肺癌炎症和免疫相关风险变异的优先顺序和特征

最近的临床试验结果表明，通过靶向白细胞介素-1β途径抑制炎症可以显着降低肺癌的发病率和死亡率，这凸显了在基因水平上了解以炎症为重点的肺癌疗法的益处的迫切且尚未得到满足的需求。尽管大量全基因组关联研究（GWAS）已经探索了肺癌的遗传病因，但从关联研究中收集的信息类型与解释和推动转化研究结果所需的理解深度之间仍然存在很大差距。因此，在这项研究中，我们联合建模和整合广泛的多组学数据源，利用总共 40 个全基因组功能注释，增强了国际肺癌联盟 (ILCCO) GWAS 先前发布的结果，以优先考虑和表征单核苷酸多态性 (SNP) ）通过炎症和免疫反应增加鳞状细胞肺癌的风险。我们的工作弥合了相关分析和转化后续研究之间的差距，以可解释和系统的方式完善了 GWAS 关联测量。特别是，对 ILCCO 数据的重新分析强调了核因子-κB 信号通路基因高度相关的 SNP 以及主要组织相容性复合物介导的免疫反应变化的影响。优先考虑可能的功能性 SNP 的一个后果是，将可能被选择用于后续工作的变体修剪掉一个数量级以上，从可能数万到数百个。我们引入的策略提供了信息丰富且可解释的方法，用于将广泛的全基因组注释数据纳入遗传关联研究的分析中。