In Vivo Optical Metabolic Imaging of Long-Chain Fatty Acid Uptake in Orthotopic Models of Triple-Negative Breast Cancer.
In Vivo Optical Metabolic Imaging of Long-Chain Fatty Acid Uptake in Orthotopic Models of Triple-Negative Breast Cancer.
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DOI：
10.3390/cancers13010148
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发表时间：
2021-01-05
期刊：
影响因子：
5.2
通讯作者：
Ramanujam N
中科院分区：
文献类型：
--
作者：
Madonna MC;Duer JE;Lee JV;Williams J;Avsaroglu B;Zhu C;Deutsch R;Wang R;Crouch BT;Hirschey MD;Goga A;Ramanujam N
新陈代谢失调是癌症的一个标志。一旦了解，肿瘤代谢重编程可以导致可靶向的脆弱性，刺激新的治疗策略的发展。除了普遍观察到肿瘤严重依赖葡萄糖之外，越来越多的证据表明，一部分肿瘤使用脂质来维持其增殖或转移表型。本研究开发了一种使用荧光标记棕榈酸酯分子Bodipy FL c16的活体显微法来定量乳腺癌小鼠模型的脂质摄取。这项工作强调了光学成像在非破坏性和重复性测量代谢终点方面的能力，以及在单独的乳腺癌体内光学成像之外为小动物代谢表型提供信息的能力。针对肿瘤的代谢依赖性是一种临床可行的治疗方法；然而，确定可能有反应的肿瘤亚型仍然很困难。使用脂质作为营养来源是特别重要的，特别是在乳腺癌中。成像技术提供了在临床前肿瘤模型中量化营养素使用的机会，以指导限制这些营养素摄取或利用的新药的开发。我们描述了一种快速动态的方法来成像体内脂肪酸摄取，并证明了它与直接研究肿瘤代谢重编程以及针对脂质代谢的药物有效性的相关性。具体来说，我们开发了一种定量光学方法，利用荧光标记的棕榈酸酯分子Bodipy FL c16，在空间和纵向上绘制了乳腺癌小鼠体内模型中长链脂肪酸摄取的动力学。我们选择乳腺肿瘤窗口的活体显微镜来验证我们的方法在两个原位乳腺癌模型中：myc过表达的转基因三阴性乳腺癌（TNBC）模型和4T1家族的小鼠模型。注射后，Bodipy FL c16荧光增强，约30 min后达到最大，注射后30 - 80 min信号保持稳定。我们以高原地区中点60 min （Bodipy60）的荧光作为总结参数，在后续实验中量化Bodipy FL c16荧光。使用我们的成像平台，我们观察到脂肪酸摄取量减少2 - 4倍，以响应MYC致癌基因的下调，这与体外代谢分析的结果一致。相比之下，我们的影像学研究报告了脂肪酸摄取随着肿瘤侵袭性（6NR， 4T07和4T1）的增加，并且在正常乳腺垫和最具侵袭性的4T1肿瘤模型中，使用脂肪酸运输抑制剂perphenazine治疗后，摄取显著减少。我们的方法填补了在静态时间点提供丰富代谢信息的体外分析和在降低分辨率下可视化整个器官代谢的成像方法之间的重要空白。
A dysregulated metabolism is a hallmark of cancer. Once understood, tumor metabolic reprogramming can lead to targetable vulnerabilities, spurring the development of novel treatment strategies. Beyond the common observation that tumors rely heavily on glucose, building evidence indicates that a subset of tumors use lipids to maintain their proliferative or metastatic phenotype. This study developed an intra-vital microscopy method to quantify lipid uptake in breast cancer murine models using a fluorescently labeled palmitate molecule, Bodipy FL c16. This work highlights optical imaging’s ability to both measure metabolic endpoints non-destructively and repeatedly, as well as inform small animal metabolic phenotyping beyond in vivo optical imaging of breast cancer alone. Targeting a tumor’s metabolic dependencies is a clinically actionable therapeutic approach; however, identifying subtypes of tumors likely to respond remains difficult. The use of lipids as a nutrient source is of particular importance, especially in breast cancer. Imaging techniques offer the opportunity to quantify nutrient use in preclinical tumor models to guide development of new drugs that restrict uptake or utilization of these nutrients. We describe a fast and dynamic approach to image fatty acid uptake in vivo and demonstrate its relevance to study both tumor metabolic reprogramming directly, as well as the effectiveness of drugs targeting lipid metabolism. Specifically, we developed a quantitative optical approach to spatially and longitudinally map the kinetics of long-chain fatty acid uptake in in vivo murine models of breast cancer using a fluorescently labeled palmitate molecule, Bodipy FL c16. We chose intra-vital microscopy of mammary tumor windows to validate our approach in two orthotopic breast cancer models: a MYC-overexpressing, transgenic, triple-negative breast cancer (TNBC) model and a murine model of the 4T1 family. Following injection, Bodipy FL c16 fluorescence increased and reached its maximum after approximately 30 min, with the signal remaining stable during the 30–80 min post-injection period. We used the fluorescence at 60 min (Bodipy60), the mid-point in the plateau region, as a summary parameter to quantify Bodipy FL c16 fluorescence in subsequent experiments. Using our imaging platform, we observed a two- to four-fold decrease in fatty acid uptake in response to the downregulation of the MYC oncogene, consistent with findings from in vitro metabolic assays. In contrast, our imaging studies report an increase in fatty acid uptake with tumor aggressiveness (6NR, 4T07, and 4T1), and uptake was significantly decreased after treatment with a fatty acid transport inhibitor, perphenazine, in both normal mammary pads and in the most aggressive 4T1 tumor model. Our approach fills an important gap between in vitro assays providing rich metabolic information at static time points and imaging approaches visualizing metabolism in whole organs at a reduced resolution.
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影响因子：
8.8
作者：
Feng, William W.;Wilkins, Owen;Kurokawa, Manabu
通讯作者：
Kurokawa, Manabu
影响因子：
29
作者：
Corbet, Cyril;Pinto, Adan;Feron, Olivier
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Feron, Olivier
影响因子：
28.2
作者：
Cantor JR;Sabatini DM
通讯作者：
Sabatini DM
影响因子：
3.7
作者：
Ahler E;Sullivan WJ;Cass A;Braas D;York AG;Bensinger SJ;Graeber TG;Christofk HR
通讯作者：
Christofk HR
影响因子：
5.5
作者：
Camarda R;Williams J;Goga A
通讯作者：
Goga A