目的:研究目的是探索丙酮酸代谢与乳腺癌(BC)之间的因果关系。以及关键代谢基因的分子作用,通过使用生物信息学和孟德尔随机化(MR)分析。
方法:我们从GEO数据库中检索并检查了不同的数据集,以通过差异表达分析确定BC中的差异作用基因(DAG)。在此之后,我们进行了功能和途径富集分析,以确定BC中值得注意的分子功能和代谢途径.采用MR分析,我们建立了丙酮酸代谢与BC易感性之间的因果关系。此外,利用DGIdb数据库,我们确定了作用于与丙酮酸代谢途径有关的基因的潜在靶向药物,并在BC中构建了竞争性内源性RNA(ceRNA)调控网络.
结果:我们收集了数据集GSE54002、GSE70947和GSE22820,在BC组和NC组之间确定了总共1127个DEG。GO和KEGG富集分析表明,这些DEGs的分子功能主要包括有丝分裂核分裂,细胞外基质,信号受体激活剂活性,等。代谢通路主要集中在PI3K-Akt信号通路,细胞因子-细胞因子受体结合和丙酮酸,酪氨酸,丙酸和苯丙氨酸代谢,等。此外,MR分析显示丙酮酸代谢与BC风险之间存在因果关系。最后,我们构建了一个通路基因之间的调控网络(ADH1B,ACSS2、ACACB、ADH1A,ALDH2和ADH1C)和靶向药物,以及BC的CERNA(IncRNA-miRNA-mRNA)调控网络,进一步揭示它们的相互作用。
结论:我们的研究揭示了丙酮酸代谢与BC风险之间的因果关系,发现ADH1B,ACSS2、ACACB、ADH1A,ALDH2和ADH1C在与丙酮酸代谢相关的分子机制中在BC的发展中起重要作用,并确定了一些潜在的靶向小分子药物。
OBJECTIVE: The study purpose was to explore the causal association between pyruvate metabolism and breast cancer (BC), as well as the molecular role of key metabolic genes, by using bioinformatics and Mendelian randomization (MR) analysis.
METHODS: We retrieved and examined diverse datasets from the GEO database to ascertain differentially acting genes (DAGs) in BC via differential expression analysis. Following this, we performed functional and pathway enrichment analyses to ascertain noteworthy molecular functions and metabolic pathways in BC. Employing MR analysis, we established a causal association between pyruvate metabolism and the susceptibility to BC. Additionally, utilizing the DGIdb database, we identified potential targeted medications that act on genes implicated in the pyruvate metabolic pathway and formulated a competing endogenous RNA (ceRNA) regulatory network in BC.
RESULTS: We collected the datasets GSE54002, GSE70947, and GSE22820, and identified a total of 1127 DEGs between the BC and NC groups. GO and KEGG enrichment analysis showed that the molecular functions of these DEGs mainly included mitotic nuclear division, extracellular matrix, signaling receptor activator activity, etc. Metabolic pathways were mainly concentrated in PI3K-Akt signaling pathway, Cytokine-cytokine receptor binding and Pyruvate, Tyrosine, Propanoate and Phenylalanine metabolism, etc. In addition, MR analysis demonstrated a causal relationship between pyruvate metabolism and BC risk. Finally, we constructed a regulatory network between pathway genes (ADH1B, ACSS2, ACACB, ADH1A, ALDH2, and ADH1C) and targeted drugs, as well as a ceRNA (lncRNA-miRNA-mRNA) regulatory network for BC, further revealing their interactions.
CONCLUSIONS: Our research revealed a causal association between pyruvate metabolism and BC risk, found that ADH1B, ACSS2, ACACB, ADH1A, ALDH2, and ADH1C takes place an important part in the development of BC in the molecular mechanisms related to pyruvate metabolism, and identified some potential targeted small molecule drugs.