Laboratory of Oncobiology and Hematology (LOH) and University Clinic of Hematology, Faculty of Medicine (FMUC), University of Coimbra, Coimbra, Portugal; Coimbra Institute for Clinical and Biomedical Research (iCBR) - Group of Environment Genetics and Oncobiology (CIMAGO), FMUC, University of Coimbra, Portugal; Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra, Portugal.
Pole of Pharmacology and Therapeutics (FATH), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Belgium.
Drug Resist Updat. 2021 Dec;59:100797. doi: 10.1016/j.drup.2021.100797. Epub 2021 Dec 16.
Despite an increasing arsenal of anticancer therapies, many patients continue to have poor outcomes due to the therapeutic failures and tumor relapses. Indeed, the clinical efficacy of anticancer therapies is markedly limited by intrinsic and/or acquired resistance mechanisms that can occur in any tumor type and with any treatment. Thus, there is an urgent clinical need to implement fundamental changes in the tumor treatment paradigm by the development of new experimental strategies that can help to predict the occurrence of clinical drug resistance and to identify alternative therapeutic options. Apart from mutation-driven resistance mechanisms, tumor microenvironment (TME) conditions generate an intratumoral phenotypic heterogeneity that supports disease progression and dismal outcomes. Tumor cell metabolism is a prototypical example of dynamic, heterogeneous, and adaptive phenotypic trait, resulting from the combination of intrinsic [(epi)genetic changes, tissue of origin and differentiation dependency] and extrinsic (oxygen and nutrient availability, metabolic interactions within the TME) factors, enabling cancer cells to survive, metastasize and develop resistance to anticancer therapies. In this review, we summarize the current knowledge regarding metabolism-based mechanisms conferring adaptive resistance to chemo-, radio-and immunotherapies as well as targeted therapies. Furthermore, we report the role of TME-mediated intratumoral metabolic heterogeneity in therapy resistance and how adaptations in amino acid, glucose, and lipid metabolism support the growth of therapy-resistant cancers and/or cellular subpopulations. We also report the intricate interplay between tumor signaling and metabolic pathways in cancer cells and discuss how manipulating key metabolic enzymes and/or providing dietary changes may help to eradicate relapse-sustaining cancer cells. Finally, in the current era of personalized medicine, we describe the strategies that may be applied to implement metabolic profiling for tumor imaging, biomarker identification, selection of tailored treatments and monitoring therapy response during the clinical management of cancer patients.
尽管抗癌疗法的武器库不断增加，但许多患者由于治疗失败和肿瘤复发，仍预后不良。事实上，抗癌疗法的临床疗效受到内在和/或获得性耐药机制的显著限制，这些机制可能发生在任何肿瘤类型和任何治疗中。因此，迫切需要通过开发新的实验策略来改变肿瘤治疗模式，这些策略可以帮助预测临床药物耐药的发生，并确定替代治疗选择。除了突变驱动的耐药机制外，肿瘤微环境 (TME) 条件还会产生支持疾病进展和预后不良的肿瘤内表型异质性。肿瘤细胞代谢是动态、异质和适应性表型特征的典型例子，是内在因素 [(遗传改变、组织起源和分化依赖性] 和外在因素 (氧气和营养可用性、TME 内的代谢相互作用) 的组合的结果，使癌细胞能够存活、转移和对化疗、放疗和免疫治疗以及靶向治疗产生耐药性。在这篇综述中，我们总结了关于代谢相关机制赋予化疗、放疗和免疫治疗以及靶向治疗适应性耐药的最新知识。此外，我们报告了 TME 介导的肿瘤内代谢异质性在治疗耐药中的作用，以及氨基酸、葡萄糖和脂质代谢的适应性如何支持治疗耐药性癌症和/或细胞亚群的生长。我们还报告了肿瘤信号和代谢途径在癌细胞中的复杂相互作用，并讨论了如何操纵关键代谢酶和/或提供饮食改变可能有助于根除维持复发的癌细胞。最后，在个性化医疗的当前时代，我们描述了可能应用于肿瘤成像、生物标志物识别、个性化治疗选择和监测癌症患者治疗反应的代谢谱分析策略。
