Reprogramming of creatine metabolism in breast cancer metastasis

代谢重编程是癌症的一个标志，使癌细胞能够迅速增殖，侵入， 转移已经确定了几种调节癌症代谢的关键酶。这些包括 葡萄糖、氨基酸、核酸和脂质代谢中的酶，包括乳酸脱氢酶A， 转氨酶1、胸苷酸合成酶和胆碱激酶α，仅举几例。普遍存在的线粒体 肌酸激酶1（CKMT 1）是癌症肌酸代谢的一种新的关键酶。很少有研究 迄今为止，已经研究了CKMT 1在癌症中的作用，以及CKMT 1在乳腺癌中的特定作用 迁移、侵袭和转移仍然是未知的。为了缩小这一知识差距，我们寻求 研究乳腺癌中肌酸代谢重编程。我们的初步数据显示，CKMT 1 驱动细胞肌酸（Cr）和磷酸肌酸（PCr）浓度，并激活乳腺中的糖酵解 癌细胞我们在细胞系、小鼠模型和患者中一致显示， 沿着CKMT 1在转移性乳腺癌细胞和转移性肿瘤中表达下调 组织中转移性乳腺癌细胞中CKMT 1的过表达减少了迁移、侵袭和转移。 转移，同时增加增殖和原发性肿瘤生长。CKMT 1在非转移性乳腺癌中的沉默 乳腺癌细胞通过产生活性氧增加迁移和侵袭 上调粘附和降解因子的活性氧（ROS），上皮细胞向间充质细胞转化（EMT）， 和信号通路。在目标1中，我们将严格调查以下因素之间的因果关系： 肌酸代谢、相关分子通路和转移驱动癌细胞的重编程 特性.在目标2中，我们将评估基因/酶和相关分子通路是否负责 重编程肌酸代谢驱动乳腺癌小鼠模型中的原发性肿瘤生长和转移 癌我们的初步数据显示，CKMT 1表达在临床乳腺癌中显著降低， 与原发性乳腺肿瘤相比，在目标3中，我们将进一步研究独特的单一患者 组织微阵列（TMAs）从我们的快速尸检程序如何肌酸代谢酶的表达水平 和肌酸代谢物，以及相关的分子途径，受到影响时，乳腺癌 转移到病人身上。在我们的三个目标中，我们将测试我们的总体假设，即肌酸的重编程 代谢参与驱动乳腺癌转移。我们的初步发现提供了证据， 肌酸代谢，特别是CKMT 1，有望作为预后指标和潜在的治疗 转移性乳腺癌的靶点。我们的建议将大大促进我们对 肌酸代谢在肿瘤进展和转移中的重编程。我们将发展综合 多重基质辅助激光解吸/电离成像和免疫组织化学方法检测 乳腺癌标本中的肌酸酶和代谢物，以供将来在病理学工作流程中使用。

Metabolic reprogramming is a hallmark of cancer, enabling cancer cells to rapidly proliferate, invade, and metastasize. Several key enzymes have been identified that modulate cancer metabolism. These include enzymes in glucose, amino acid, nucleic acid, and lipid metabolism, including lactate dehydrogenase A, glutaminase 1, thymidylate synthase, and choline kinase alpha, to name just a few. Ubiquitous mitochondrial creatine kinase 1 (CKMT1) is emerging as a novel key enzyme in creatine metabolism of cancer. Few studies to date have investigated the role of CKMT1 in cancer, and the specific role of CKMT1 in breast cancer migration, invasion and metastasis remains largely unknown. To close this knowledge gap, we seek to investigate reprogramming of creatine metabolism in breast cancer. Our preliminary data show that CKMT1 drives cellular creatine (Cr) and phosphocreatine (PCr) concentrations and activates glycolysis in breast cancer cells. We consistently show in cell lines, mouse models, and patients that creatine metabolite levels along with CKMT1 expression are downregulated in metastatic breast cancer cells and metastatic tumor tissues. Overexpression of CKMT1 in metastatic breast cancer cells reduces migration, invasion, and metastasis, while increasing proliferation and primary tumor growth. Silencing of CKMT1 in nonmetastatic breast cancer cells increases migration and invasion, which occurs through generation of reactive oxygen species (ROS) that upregulate adhesion and degradative factors, epithelial-to-mesenchymal transition (EMT), and signaling pathways. In Aim 1, we will rigorously investigate the cause-and-effect relationships between reprogramming of creatine metabolism, related molecular pathways, and metastasis-driving cancer cell properties. In Aim 2, we will assess if genes/enzymes and related molecular pathways responsible for reprogramming creatine metabolism drive primary tumor growths and metastasis in mouse models of breast cancer. Our preliminary data show that CKMT1 expression was significantly decreased in clinical breast cancer metastases as compared to primary breast tumors. In Aim 3, we will further investigate in unique single-patient tissue microarrays (TMAs) from our rapid autopsy program how creatine metabolic enzyme expression levels and creatine metabolites, as well as related molecular pathways, are affected when breast cancers metastasize in patients. In our three Aims, we will test our overall hypothesis that reprogramming of creatine metabolism participates in driving breast cancer metastasis. Our preliminary findings provide evidence that creatine metabolism, and in particular CKMT1, holds promise as prognostic indicator and potential therapeutic target for metastatic breast cancer. Our proposal will significantly advance our understanding of reprogramming of creatine metabolism in tumor progression and metastasis. We will develop integrated multiplex matrix-assisted laser desorption/ionization imaging and immunohistochemistry approaches to detect creatine enzymes and metabolites in breast cancer specimens for future use in pathology workflows.