Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.
Department of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland.
Cancer Res. 2022 May 3;82(9):1698-1711. doi: 10.1158/0008-5472.CAN-21-3983.
Metabolic reprogramming is a hallmark of malignant transformation, and loss of isozyme diversity (LID) contributes to this process. Isozymes are distinct proteins that catalyze the same enzymatic reaction but can have different kinetic characteristics, subcellular localization, and tissue specificity. Cancer-dominant isozymes that catalyze rate-limiting reactions in critical metabolic processes represent potential therapeutic targets. Here, we examined the isozyme expression patterns of 1,319 enzymatic reactions in 14 cancer types and their matching normal tissues using The Cancer Genome Atlas mRNA expression data to identify isozymes that become cancer-dominant. Of the reactions analyzed, 357 demonstrated LID in at least one cancer type. Assessment of the expression patterns in over 600 cell lines in the Cancer Cell Line Encyclopedia showed that these reactions reflect cellular changes instead of differences in tissue composition; 50% of the LID-affected isozymes showed cancer-dominant expression in the corresponding cell lines. The functional importance of the cancer-dominant isozymes was assessed in genome-wide CRISPR and RNAi loss-of-function screens: 17% were critical for cell proliferation, indicating their potential as therapeutic targets. Lists of prioritized novel metabolic targets were developed for 14 cancer types; the most broadly shared and functionally validated target was acetyl-CoA carboxylase 1 (ACC1). Small molecule inhibition of ACC reduced breast cancer viability in vitro and suppressed tumor growth in cell line- and patient-derived xenografts in vivo. Evaluation of the effects of drug treatment revealed significant metabolic and transcriptional perturbations. Overall, this systematic analysis of isozyme expression patterns elucidates an important aspect of cancer metabolic plasticity and reveals putative metabolic vulnerabilities.
This study exploits the loss of metabolic isozyme diversity common in cancer and reveals a rich pool of potential therapeutic targets that will allow the repurposing of existing inhibitors for anticancer therapy. See related commentary by Kehinde and Parker, p. 1695.
代谢重编程是恶性转化的一个标志,同工酶多样性丧失(LID)促成了这一过程。同工酶是催化相同酶促反应但具有不同动力学特征、亚细胞定位和组织特异性的不同蛋白质。催化关键代谢过程中限速反应的癌优势同工酶代表潜在的治疗靶点。在这里,我们使用癌症基因组图谱 mRNA 表达数据检查了 14 种癌症类型及其匹配的正常组织中 1319 种酶促反应的同工酶表达模式,以鉴定成为癌优势的同工酶。在分析的反应中,至少有一种癌症类型存在 357 种 LID。在癌症细胞系百科全书(Cancer Cell Line Encyclopedia)中对超过 600 种细胞系的表达模式进行评估表明,这些反应反映了细胞变化而不是组织成分的差异;50%受 LID 影响的同工酶在相应的细胞系中表现出癌优势表达。在全基因组 CRISPR 和 RNAi 功能丧失筛选中评估了癌优势同工酶的功能重要性:17%对细胞增殖至关重要,表明它们具有作为治疗靶点的潜力。为 14 种癌症类型开发了优先考虑的新型代谢靶标清单;最广泛共享和功能验证的靶标是乙酰辅酶 A 羧化酶 1(ACC1)。小分子抑制 ACC 减少了体外乳腺癌的活力,并抑制了体内细胞系和患者来源异种移植瘤的生长。药物治疗效果的评估显示出明显的代谢和转录扰动。总的来说,这种同工酶表达模式的系统分析阐明了癌症代谢可塑性的一个重要方面,并揭示了潜在的代谢脆弱性。
这项研究利用了癌症中常见的代谢同工酶多样性丧失,并揭示了丰富的潜在治疗靶点池,这将允许重新利用现有的抑制剂用于癌症治疗。请参阅 Kehinde 和 Parker 的相关评论,第 1695 页。