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Metabolic pathways underlying GATA6 regulating Trastuzumab resistance in Gastric Cancer cells based on untargeted metabolomics.

ABSTRACT: Trastuzumab has proven its effectiveness in gastric cancer with HER-2 gene-amplification, which has now developed resistance while the mechanism of which is not fully elucidated. Our previous studies demonstrated that the activity of GATA6 binding protein 6 (GATA6) enhanced prominently in trastuzumab resistant gastric cancer cell lines (NCI N87R and MKN45R). In the present study, we further confirmed the re-sensitization to trastuzumab and inhibition of mitochondrial functions of GATA6 knockout sublines (NCI N87R/?GATA6 and MKN45R/?GATA6). Moreover, we applied untargeted metabolomic profiling to investigate the potential roles of GATA6 in metabolism of NCI N87R and MKN45R. The UPLC system coupled with Q-Exactive Focus Orbitrap mass spectrometry, multivariate in combination with univariate analysis were performed for the screening of differential metabolites between resistant cells and GATA6 knockout sublines. A total of 68 and 59 endogenous metabolites were found to be altered significantly in NCI N87R/?GATA6 and MKN45R/?GATA6 cells compared with NCI N87R and MKN45R, respectively. Pathway analyses indicated disturbance of metabolic pathways after GATA6 knockout including tricarboxylic acid (TCA) cycle, glycolysis and energy-related amino acid pathways. An integrated proteomics-metabolomics revealed that sub-networks were closely related to TCA cycle, glycolysis, multiple amino acid and nucleotide metabolism. Western blot showed that TCA cycle and glycolysis-related molecules, including PKM, GLS, GLUL and LDHA, were downregulated in GATA6 knockout sublines. Taken together, these findings demonstrate that GATA6 is involved in metabolism reprogramming which might contribute to trastuzumab resistance in gastric cancer.

SUBMITTER: Chang J

PROVIDER: S-EPMC7646115 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Metabolic pathways underlying GATA6 regulating Trastuzumab resistance in Gastric Cancer cells based on untargeted metabolomics.

Chang Jinxia J Wang Qiang Q Bhetuwal Anup A Liu Wenhu W

International journal of medical sciences 20201023 18

Trastuzumab has proven its effectiveness in gastric cancer with HER-2 gene-amplification, which has now developed resistance while the mechanism of which is not fully elucidated. Our previous studies demonstrated that the activity of GATA6 binding protein 6 (GATA6) enhanced prominently in trastuzumab resistant gastric cancer cell lines (NCI N87R and MKN45R). In the present study, we further confirmed the re-sensitization to trastuzumab and inhibition of mitochondrial functions of GATA6 knockout ...[more]

PMID: 33173435

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Project description:PurposeGastric cancer is a common tumor of the digestive system. Identification of potential molecules associated with gastric cancer progression and validation of potential biomarkers for gastric cancer diagnosis are very important. Thus, the aim of our study was to determine the serum metabolic characteristics of the serum of patients with chronic gastritis (CG) or gastric cancer (GC) and validate candidate biomarkers for disease diagnosis.Experimental designA total of 123 human serum samples from patients with CG or GC were collected for untargeted metabolomic analysis via UHPLC-Q-TOF/MS to determine characteristics of the serum. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and heat map were used for multivariate analysis. In addition, commercial databases were used to identify the pathways of metabolites. Differential metabolites were identified based on a heat map with a t-test threshold (p < 0.05), fold-change threshold (FC > 1.5 or FC < 2/3) and variable importance in the projection (VIP >1). Then, differential metabolites were analyzed by receiver operating characteristic (ROC) curve to determine candidate biomarkers. All samples were analyzed for fasting lipid profiles.ResultsAnalysis of serum metabolomic profiles indicated that most of the altered metabolic pathways in the three groups were associated with lipid metabolism (p < 0.05) and lipids and lipid-like molecules were the predominating metabolites within the top 100 differential metabolites (p < 0.05, FC > 1.5 or FC < 2/3, and VIP >1). Moreover, differential metabolites, including hexadecasphinganine, linoleamide, and N-Hydroxy arachidonoyl amine had high diagnostic performance according to PLS-DA. In addition, fasting lipid profile analysis showed the serum levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A1 (Apo-A1) were decreased concomitant to the progression of the progression of the disease compared with those in the control group (p < 0.05).ConclusionsThus, this study demonstrated that lipid metabolism may influence the development of CG to GC. Hexadecasphinganine, linoleamide, and N-Hydroxy arachidonoyl amine were selected as candidate diagnostic markers for CG and GC.

Project description:Background: Esophageal squamous cell carcinoma (ESCC) is one of the most fatal diseases worldwide. Because early diagnosis is difficult, ESCC is mostly diagnosed at an advanced stage, leading to a poor overall prognosis. The purpose of this study was to explore the differences between plasma metabolic profiles in ESCC patients and healthy controls and to establish a diagnostic model of ESCC. Methods: In this study, a cohort of 310 subjects, containing 140 ESCC patients and 170 healthy controls (HC), was recruited. Participants were randomly separated into a training set (80 ESCCs, 80 HCs) and a validation set (60 ESCCs, 90 HCs) and their plasma metabolomics profiles were analyzed by ultra-performance liquid chromatography-tandem quadruple time-of-flight mass spectrometry (UPLC-QTOF/MS) technique. Univariate statistical analysis and multivariate analysis (MVA) methods were used to identify differential metabolites. Finally, the dysregulated pathways associated with ESCC were further explored and the diagnostic performance of the biomarker panel was evaluated. Results: Metabolic analyses identified 34 significant metabolites involved in the metabolism of amino acids, phospholipids, fatty acids, purine, and choline. Farthermore, an effective diagnostic model for ESCC was constructed based on eight metabolites. This panel of biomarkers consisted of hypoxanthine, proline betaine, indoleacrylic acid, inosine, 9-decenoylcarnitine, tetracosahexaenoic acid, LPE (20:4), and LPC (20:5). The model was verified and evaluated in the validation set. The AUC value of the ROC curve was 0.991(95% CI: 0.981-1.000, CI, Confidence interval), with a sensitivity (SE) of 98.8% and a specificity (SP) of 94.9% for the training set and 0.965(95% CI: 0.936-0.993), with a SE of 88.3% and a SP of 88.9% for the validation set. Among them, three biomarkers, indoleacrylic acid, LPC (20:5), and LPE (20:4), exhibited a trend associated with the ESCC progression. Conclusions: Our study identified a novel plasma biomarker panel, which clearly distinguishes ESCC patients and provides insight into the mechanisms of ESCC. This finding may form the basis for the development of a minimally invasive method for ESCC detection.

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Metabolic pathways underlying GATA6 regulating Trastuzumab resistance in Gastric Cancer cells based on untargeted metabolomics.

Publications

Metabolic pathways underlying GATA6 regulating Trastuzumab resistance in Gastric Cancer cells based on untargeted metabolomics.

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