Rushing Blake R
Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA.
Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Biomedicines. 2023 Sep 14;11(9):2532. doi: 10.3390/biomedicines11092532.
Drug resistance continues to be a significant problem in cancer therapy, leading to relapse and associated mortality. Although substantial progress has been made in understanding drug resistance, significant knowledge gaps remain concerning the molecular underpinnings that drive drug resistance and which processes are unique to certain drug classes. The NCI-60 cell line panel program has evaluated the activity of numerous anticancer agents against many common cancer cell line models and represents a highly valuable resource to study intrinsic drug resistance. Furthermore, great efforts have been undertaken to collect high-quality omics datasets to characterize these cell lines. The current study takes these two sources of data-drug response and omics profiles-and uses a multi-omics investigation to uncover molecular networks that differentiate cancer cells that are sensitive or resistant to antifolates, which is a commonly used class of anticancer drugs. Results from a combination of univariate and multivariate analyses showed numerous metabolic processes that differentiate sensitive and resistant cells, including differences in glycolysis and gluconeogenesis, arginine and proline metabolism, beta-alanine metabolism, purine metabolism, and pyrimidine metabolism. Further analysis using multivariate and integrated pathway analysis indicated purine metabolism as the major metabolic process separating cancer cells sensitive or resistant to antifolates. Additional pathways differentiating sensitive and resistant cells included autophagy-related processes (e.g., phagosome, lysosome, autophagy, mitophagy) and adhesion/cytoskeleton-related pathways (e.g., focal adhesion, regulation of actin cytoskeleton, tight junction). Volcano plot analysis and the receiver operating characteristic (ROC) curves of top selected variables differentiating Q1 and Q4 revealed the importance of genes involved in the regulation of the cytoskeleton and extracellular matrix (ECM). These results provide novel insights toward mechanisms of intrinsic antifolate resistance as it relates to interactions between nucleotide metabolism, autophagy, and the cytoskeleton. These processes should be evaluated in future studies to potentially derive novel therapeutic strategies and personalized treatment approaches to improve antifolate response.
耐药性仍然是癌症治疗中的一个重大问题,会导致复发及相关死亡率。尽管在理解耐药性方面已取得了重大进展,但在驱动耐药性的分子基础以及某些药物类别所特有的过程方面,仍存在重大知识空白。NCI - 60细胞系面板项目评估了多种抗癌药物对许多常见癌细胞系模型的活性,是研究内在耐药性的极有价值的资源。此外,人们已付出巨大努力来收集高质量的组学数据集,以表征这些细胞系。当前的研究利用这两个数据源——药物反应和组学概况——并通过多组学研究来揭示区分对抗叶酸剂敏感或耐药的癌细胞的分子网络,抗叶酸剂是一类常用的抗癌药物。单变量和多变量分析相结合的结果显示,有许多代谢过程可区分敏感细胞和耐药细胞,包括糖酵解和糖异生、精氨酸和脯氨酸代谢、β - 丙氨酸代谢、嘌呤代谢和嘧啶代谢的差异。使用多变量和综合通路分析的进一步分析表明,嘌呤代谢是区分对抗叶酸剂敏感或耐药的癌细胞的主要代谢过程。区分敏感细胞和耐药细胞的其他通路包括自噬相关过程(如吞噬体、溶酶体、自噬、线粒体自噬)以及黏附/细胞骨架相关通路(如粘着斑、肌动蛋白细胞骨架调节、紧密连接)。火山图分析以及区分第一四分位数(Q1)和第四四分位数(Q4)的顶级选定变量的受试者工作特征(ROC)曲线揭示了参与细胞骨架和细胞外基质(ECM)调节的基因的重要性。这些结果为内在抗叶酸耐药性机制提供了新的见解,因为它与核苷酸代谢、自噬和细胞骨架之间的相互作用有关。在未来的研究中应评估这些过程,以潜在地得出新的治疗策略和个性化治疗方法,从而改善抗叶酸反应。