Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
Mol Oncol. 2023 Jan;17(1):173-187. doi: 10.1002/1878-0261.13345. Epub 2022 Dec 5.
Epigenome-wide gene-gene (G × G) interactions associated with non-small-cell lung cancer (NSCLC) survival may provide insights into molecular mechanisms and therapeutic targets. Hence, we proposed a three-step analytic strategy to identify significant and robust G × G interactions that are relevant to NSCLC survival. In the first step, among 49 billion pairs of DNA methylation probes, we identified 175 775 G × G interactions with P ≤ 0.05 in the discovery phase of epigenomic analysis; among them, 15 534 were confirmed with P ≤ 0.05 in the validation phase. In the second step, we further performed a functional validation for these G × G interactions at the gene expression level by way of a two-phase (discovery and validation) transcriptomic analysis, and confirmed 25 significant G × G interactions enriched in the 6p21.33 and 6p22.1 regions. In the third step, we identified two G × G interactions using the trans-omics analysis, which had significant (P ≤ 0.05) epigenetic cis-regulation of transcription and robust G × G interactions at both the epigenetic and transcriptional levels. These interactions were cg14391855 × cg23937960 (β = 0.018, P = 1.87 × 10 ), which mapped to RELA × HLA-G (β = 0.218, P = 8.82 × 10 ) and cg08872738 × cg27077312 (β = -0.010, P = 1.16 × 10 ), which mapped to TUBA1B × TOMM40 (β =-0.250, P = 3.83 × 10 ). A trans-omics mediation analysis revealed that 20.3% of epigenetic effects on NSCLC survival were significantly (P = 0.034) mediated through transcriptional expression. These statistically significant trans-omics G × G interactions can also discriminate patients with high risk of mortality. In summary, we identified two G × G interactions at both the epigenetic and transcriptional levels, and our findings may provide potential clues for precision treatment of NSCLC.
全基因组范围内基因-基因(G×G)相互作用与非小细胞肺癌(NSCLC)的生存相关,可能为分子机制和治疗靶点提供深入了解。因此,我们提出了一种三步分析策略,以识别与 NSCLC 生存相关的具有统计学意义和稳健性的 G×G 相互作用。在表观基因组分析的发现阶段,在 490 亿对 DNA 甲基化探针中,我们确定了 175775 对 P≤0.05 的 G×G 相互作用;其中,15534 对在验证阶段 P≤0.05 得到了确认。在第二步中,我们通过转录组学的两阶段(发现和验证)分析,进一步在基因表达水平上对这些 G×G 相互作用进行了功能验证,并在 6p21.33 和 6p22.1 区域富集的 25 个显著 G×G 相互作用中得到了证实。在第三步中,我们使用跨组学分析发现了两个 G×G 相互作用,它们在表观遗传和转录水平上都具有显著的(P≤0.05)表观遗传顺式调控转录和稳健的 G×G 相互作用。这两个相互作用分别是 cg14391855×cg23937960(β=0.018,P=1.87×10-3),映射到 RELA×HLA-G(β=0.218,P=8.82×10-3)和 cg08872738×cg27077312(β=-0.010,P=1.16×10-3),映射到 TUBA1B×TOMM40(β=-0.250,P=3.83×10-3)。跨组学中介分析显示,20.3%的 NSCLC 生存的表观遗传效应通过转录表达显著(P=0.034)介导。这些具有统计学意义的跨组学 G×G 相互作用也可以区分高死亡率风险的患者。综上所述,我们在表观遗传和转录水平上鉴定了两个 G×G 相互作用,我们的发现可能为 NSCLC 的精准治疗提供潜在线索。