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首页> 外文期刊>Cell cycle >Ketones and lactate increase cancer cell 'stemness,' driving recurrence, metastasis and poor clinical outcome in breast cancer: achieving personalized medicine via Metabolo-Genomics.
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Ketones and lactate increase cancer cell 'stemness,' driving recurrence, metastasis and poor clinical outcome in breast cancer: achieving personalized medicine via Metabolo-Genomics.

机译:酮和乳酸会增加癌细胞的“干性”,导致乳腺癌的复发,转移和不良的临床预后:通过Metabolo-Genomics实现个性化药物。

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摘要

Previously, we showed that high-energy metabolites (lactate and ketones) "fuel" tumor growth and experimental metastasis in an in vivo xenograft model, most likely by driving oxidative mitochondrial metabolism in breast cancer cells. To mechanistically understand how these metabolites affect tumor cell behavior, here we used genome-wide transcriptional profiling. Briefly, human breast cancer cells (MCF7) were cultured with lactate or ketones, and then subjected to transcriptional analysis (exon-array). Interestingly, our results show that treatment with these high-energy metabolites increases the transcriptional expression of gene profiles normally associated with "stemness," including genes upregulated in embryonic stem (ES) cells. Similarly, we observe that lactate and ketones promote the growth of bonafide ES cells, providing functional validation. The lactate- and ketone-induced "gene signatures" were able to predict poor clinical outcome (including recurrence and metastasis) in a cohort of human breast cancer patients. Taken together, our results are consistent with the idea that lactate and ketone utilization in cancer cells promotes the "cancer stem cell" phenotype, resulting in significant decreases in patient survival. One possible mechanism by which these high-energy metabolites might induce stemness is by increasing the pool of Acetyl-CoA, leading to increased histone acetylation, and elevated gene expression. Thus, our results mechanistically imply that clinical outcome in breast cancer could simply be determined by epigenetics and energy metabolism, rather than by the accumulation of specific classical (identified by the lactate/ketone gene signatures) could be treated with new therapeutics that target oxidative mitochondrial metabolism, such as the anti-oxidant and "mitochondrial poison" metformin. Finally, we propose that this new approach to personalized cancer medicine be termed "Metabolo-Genomics," which incorporates features of both 1) cell metabolism and 2) gene transcriptional profiling. Importantly, this powerful new approach directly links cancer cell metabolism with clinical outcome, and new therapeutic strategies for inhibiting the TCA cycle and mitochondrial oxidative phosphorylation in cancer cells.
机译:先前,我们显示了体内异种移植模型中的高能代谢物(乳酸和酮)“助长”肿瘤的生长和实验性转移,最有可能通过在乳腺癌细胞中驱动氧化线粒体代谢来实现。为了机械地理解这些代谢物如何影响肿瘤细胞的行为,在这里我们使用了全基因组转录谱。简而言之,将人乳腺癌细胞(MCF7)与乳酸或酮一起培养,然后进行转录分析(外显子阵列)。有趣的是,我们的结果表明,用这些高能代谢物进行治疗可增加通常与“干性”相关的基因谱的转录表达,包括在胚胎干(ES)细胞中上调的基因。同样,我们观察到乳酸和酮促进纯正ES细胞的生长,提供功能验证。乳酸和酮诱导的“基因特征”能够预测一组人类乳腺癌患者的不良临床结果(包括复发和转移)。两者合计,我们的结果与这样的想法是一致的,即癌细胞中乳酸和酮的利用促进了“癌症干细胞”表型,从而导致患者存活率显着下降。这些高能代谢物诱导干性的一种可能机制是增加乙酰辅酶A的库,导致组蛋白乙酰化增加和基因表达升高。因此,我们的研究结果从机械上暗示,乳腺癌的临床结果可以简单地由表观遗传学和能量代谢来确定,而不是可以通过针对氧化性线粒体的新疗法来治疗特定经典药物(通过乳酸/酮基因签名确定)的积累。代谢,例如抗氧化剂和“线粒体毒物”二甲双胍。最后,我们建议将这种用于个性化癌症医学的新方法称为“ Metabolo-Genomics”,该方法结合了1)细胞代谢和2)基因转录谱的特征。重要的是,这种功能强大的新方法将癌细胞的代谢与临床结果以及抑制癌细胞中TCA周期和线粒体氧化磷酸化的新治疗策略直接联系在一起。

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