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早期非小细胞肺癌中基因-基因相互作用的跨组学评估。

A trans-omics assessment of gene-gene interaction in early-stage NSCLC.

机构信息

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.

出版信息

Mol Oncol. 2023 Jan;17(1):173-187. doi: 10.1002/1878-0261.13345. Epub 2022 Dec 5.

Abstract

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.

摘要

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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c60/9812838/b313cb99a1e2/MOL2-17-173-g007.jpg

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