Feng Malong, Wang Ji, Zhou Jianying
Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Department of Respiration, Fenghua District People's Hospital of Ningbo, Ningbo, China.
Front Genet. 2023 Jun 8;14:1199566. doi: 10.3389/fgene.2023.1199566. eCollection 2023.
The aim of this study was to investigate the molecular mechanisms underlying the therapeutic effects of dichloroacetic acid (DCA) in lung cancer by integrating multi-omics approaches, as the current understanding of DCA's role in cancer treatment remains insufficiently elucidated. We conducted a comprehensive analysis of publicly available RNA-seq and metabolomic datasets and established a subcutaneous xenograft model of lung cancer in BALB/c nude mice ( = 5 per group) treated with DCA (50 mg/kg, administered via intraperitoneal injection). Metabolomic profiling, gene expression analysis, and metabolite-gene interaction pathway analysis were employed to identify key pathways and molecular players involved in the response to DCA treatment. evaluation of DCA treatment on tumor growth and MIF gene expression was performed in the xenograft model. Metabolomic profiling and gene expression analysis revealed significant alterations in metabolic pathways, including the Warburg effect and citric acid cycle, and identified the MIF gene as a potential therapeutic target in lung cancer. Our analysis indicated that DCA treatment led to a decrease in MIF gene expression and an increase in citric acid levels in the treatment group. Furthermore, we observed a potential interaction between citric acid and the MIF gene, suggesting a novel mechanism underlying the therapeutic effects of DCA in lung cancer. This study underscores the importance of integrated omics approaches in deciphering the complex molecular mechanisms of DCA treatment in lung cancer. The identification of key metabolic pathways and the novel finding of citric acid elevation, together with its interaction with the MIF gene, provide promising directions for the development of targeted therapeutic strategies and improving clinical outcomes for lung cancer patients.
本研究的目的是通过整合多组学方法，探究二氯乙酸（DCA）治疗肺癌的分子机制，因为目前对DCA在癌症治疗中的作用仍未得到充分阐明。我们对公开可用的RNA测序和代谢组学数据集进行了全面分析，并在接受DCA（50mg/kg，腹腔注射）治疗的BALB/c裸鼠（每组n = 5）中建立了肺癌皮下异种移植模型。采用代谢组学分析、基因表达分析和代谢物-基因相互作用途径分析，以确定参与DCA治疗反应的关键途径和分子参与者。在异种移植模型中评估DCA治疗对肿瘤生长和MIF基因表达的影响。代谢组学分析和基因表达分析揭示了代谢途径的显著变化，包括瓦伯格效应和柠檬酸循环，并确定MIF基因为肺癌的潜在治疗靶点。我们的分析表明，DCA治疗导致治疗组中MIF基因表达降低和柠檬酸水平升高。此外，我们观察到柠檬酸与MIF基因之间存在潜在相互作用，提示DCA治疗肺癌的新机制。本研究强调了整合组学方法在解读DCA治疗肺癌复杂分子机制中的重要性。关键代谢途径的确定以及柠檬酸升高及其与MIF基因相互作用的新发现，为开发靶向治疗策略和改善肺癌患者临床结局提供了有希望的方向。
