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结合代谢表型测定、代谢组学和转录分析以揭示由羟基羧酸受体2调控的途径。

Combining metabolic phenotype determination with metabolomics and transcriptional analyses to reveal pathways regulated by hydroxycarboxylic acid receptor 2.

作者信息

Rabe Philipp, Gehmlich Mareike, Peters Anna, Krumbholz Petra, Nordström Anders, Stäubert Claudia

机构信息

Rudolf Schönheimer Institute of Biochemistry, Faculty of Medicine, Leipzig University, Johannisallee 30, 04103, Leipzig, Germany.

Swedish Metabolomics Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, Linnaeus väg 6, 901 87, Umeå, Sweden.

出版信息

Discov Oncol. 2022 Jun 13;13(1):47. doi: 10.1007/s12672-022-00503-3.

DOI:10.1007/s12672-022-00503-3
PMID:35697980
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9192902/
Abstract

BACKGROUND

The adaptation of cellular metabolism is considered a hallmark of cancer. Oncogenic signaling pathways support tumorigenesis and cancer progression through the induction of certain metabolic phenotypes associated with altered regulation of key metabolic enzymes. Hydroxycarboxylic acid receptor 2 (HCA) is a G protein-coupled receptor previously shown to act as a tumor suppressor. Here, we aimed to unveil the connection between cellular metabolism and HCA in BT-474 cells. Moreover, we intend to clarify how well this metabolic phenotype is reflected in transcriptional changes and metabolite levels as determined by global metabolomics analyses.

METHODS

We performed both, siRNA mediated knockdown of HCA and stimulation with the HCA-specific agonist monomethyl fumarate. Seahorse technology was used to determine the role of HCA in BT-474 breast cancer cell metabolism and its potential to induce a switch in the metabolic phenotype in the presence of different energy substrates. Changes in the mRNA expression of metabolic enzymes were detected with real-time quantitative PCR (RT-qPCR). Untargeted liquid chromatography-mass spectrometry (LC-MS) metabolic profiling was used to determine changes in metabolite levels.

RESULTS

Knockdown or stimulation of HCA induced changes in the metabolic phenotype of BT474 cells dependent on the availability of energy substrates. The presence of HCA was associated with increased glycolytic flux with no fatty acids available. This was reflected in the increased mRNA expression of the glycolytic enzymes PFKFB4 and PKM2, which are known to promote the Warburg effect and have been described as prognostic markers in different types of cancer. With exogenous palmitate present, HCA caused elevated fatty acid oxidation and likely lipolysis. The increase in lipolysis was also detectable at the transcriptional level of ATGL and the metabolite levels of palmitic and stearic acid.

CONCLUSIONS

We combined metabolic phenotype determination with metabolomics and transcriptional analyses and identified HCA as a regulator of glycolytic flux and fatty acid metabolism in BT-474 breast cancer cells. Thus, HCA, for which agonists are already widely used to treat diseases such as psoriasis or hyperlipidemia, may prove useful as a target in combination cancer therapy.

摘要

背景

细胞代谢的适应性被认为是癌症的一个标志。致癌信号通路通过诱导与关键代谢酶调控改变相关的某些代谢表型来支持肿瘤发生和癌症进展。羟基羧酸受体2(HCA)是一种G蛋白偶联受体,先前已被证明具有肿瘤抑制作用。在此,我们旨在揭示BT - 474细胞中细胞代谢与HCA之间的联系。此外,我们打算阐明这种代谢表型在转录变化和通过全局代谢组学分析确定的代谢物水平中得到了怎样的体现。

方法

我们进行了HCA的siRNA介导的敲低以及用HCA特异性激动剂富马酸单甲酯进行刺激。采用海马技术来确定HCA在BT - 474乳腺癌细胞代谢中的作用及其在存在不同能量底物时诱导代谢表型转变的潜力。用实时定量PCR(RT - qPCR)检测代谢酶mRNA表达的变化。非靶向液相色谱 - 质谱(LC - MS)代谢谱分析用于确定代谢物水平的变化。

结果

HCA的敲低或刺激诱导了BT474细胞代谢表型的变化,这取决于能量底物的可用性。在没有脂肪酸的情况下,HCA的存在与糖酵解通量增加有关。这反映在糖酵解酶PFKFB4和PKM2的mRNA表达增加上,已知这两种酶可促进瓦伯格效应,并已被描述为不同类型癌症的预后标志物。在外源棕榈酸存在的情况下,HCA导致脂肪酸氧化增加以及可能的脂解作用增强。在ATGL的转录水平以及棕榈酸和硬脂酸的代谢物水平上也可检测到脂解作用的增加。

结论

我们将代谢表型测定与代谢组学和转录分析相结合,确定HCA是BT - 474乳腺癌细胞中糖酵解通量和脂肪酸代谢的调节因子。因此,其激动剂已被广泛用于治疗诸如牛皮癣或高脂血症等疾病的HCA,可能被证明可作为联合癌症治疗的一个靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae9a/9192902/80356e4dbc6f/12672_2022_503_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae9a/9192902/055d4eed1963/12672_2022_503_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae9a/9192902/4d345adceaa8/12672_2022_503_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae9a/9192902/80356e4dbc6f/12672_2022_503_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae9a/9192902/055d4eed1963/12672_2022_503_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae9a/9192902/4d345adceaa8/12672_2022_503_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae9a/9192902/80356e4dbc6f/12672_2022_503_Fig4_HTML.jpg

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