重编程
癌症
计算生物学
癌细胞
癌症研究
化学
生物
生物化学
细胞
遗传学
作者
Kelly Osayi Otakhor,Elizabeth Soladoye
标识
DOI:10.30574/wjarr.2024.23.1.2038
摘要
Metabolic reprogramming is a hallmark of cancer, enabling tumor cells to sustain rapid proliferation, resist cell death, and adapt to varying microenvironmental conditions. This review elucidates the key mechanisms underlying metabolic reprogramming in cancer cells, including alterations in glucose metabolism, glutamine addiction, and lipid biosynthesis. A central feature of cancer metabolism is the Warburg effect, where cancer cells preferentially utilize aerobic glycolysis over oxidative phosphorylation, even in the presence of oxygen. This metabolic shift is driven by oncogenes and tumor suppressor genes, such as MYC and TP53, which modulate the expression and activity of enzymes involved in glycolysis and mitochondrial function. Additionally, cancer cells exhibit increased glutaminolysis, relying on glutamine as a carbon and nitrogen source to support anabolic processes and redox balance. Lipid metabolism is also reprogrammed, with enhanced de novo lipogenesis supplying membrane components and signaling molecules critical for tumor growth and survival. Understanding these metabolic alterations provides a basis for developing targeted therapies. Several therapeutic strategies have emerged, including inhibitors of key metabolic enzymes, such as hexokinase 2 (HK2), pyruvate kinase M2 (PKM2), and glutaminase. Metabolic interventions can disrupt the metabolic flexibility of cancer cells, sensitizing them to conventional therapies and overcoming resistance mechanisms. This review highlights the potential of metabolic targets in cancer treatment and emphasizes the need for personalized approaches considering tumor-specific metabolic profiles. Future research should focus on identifying biomarkers of metabolic vulnerabilities and developing combination therapies that exploit the intricate metabolic dependencies of cancer cells. Ultimately, targeting metabolic reprogramming holds promise for improving cancer prognosis and achieving more effective and durable therapeutic outcomes.
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