Global metabolomic profiling of trastuzumab resistant gastric cancer cells reveals major metabolic pathways and metabolic signatures based on UHPLC-Q exactive-MS/MS

Abstract

Resistance mechanism exploration has become an urgent need owing to the widespread trastuzumab resistance in gastric cancer. In this study, UHPLC-Q exactive MS/MS was carried out to characterize the metabolic profiles of human gastric cancer cell lines NCI N87, MKN45 (trastuzumab-sensitive) and NCI N87/R, MKN45/R (trastuzumab-resistant), respectively. Metabolic signatures and different metabolites were identified using multivariate in combination with univariate analysis. Integrated pathway enrichment analysis was executed using MetaboAnalyst and KEGG metabolic libraries to analyze the altered metabolic pathways in trastuzumab resistant cells. A total of 79 and 75 different metabolites were positively identified by utilizing authentic standards in NCI N87/R and MKN45/R cells, respectively.Furthermore, enrichment analysis demonstrated that seven metabolic pathways in NCI N87/R cells and five in MKN45/R cells were significantly changed. These pathways are involved in amino acid, nucleotide, carbohydrate, cofactor and vitamin metabolism, of which alanine, aspartate and glutamate metabolism displayed the highest pathway impact and lower P value both in NCI N87/R and MKN45/R cells.Moreover, we constructed a metabolomics-proteomics network between substantially altered metabolites and target genes which revealed citrate being regulated by citrate synthase and ACLY, while proline regulation was due to EPRS, PYCRL and PYCR1/2, respectively. Overall, our findings disclose prominent alterations of metabolic signatures in NCI N87/R and MKN45/R cells when compared with the parent cells which are crucial for understanding of underlying mechanisms of resistance and for developing strategies to overcome trastuzumab resistance. Fig. 4 Heat map visualization of differential metabolites from significantly altered pathways in (A) NCI N87/R and NCI N87 cells, and (B) MKN45/R and MKN45 cells. Each row represents a metabolite and each column represents a sample. The increased and decreased metabolites are represented by range of red and blue intensities, respectively.41202 | RSC Adv., 2019,9,[41192][41193][41194][41195][41196][41197][41198][41199][41200][41201][41202][41203][41204][41205][41206][41207][41208] This journal is

Lipidomic Analyses Uncover Apoptotic and Inhibitory Effects of Pyrvinium Pamoate on Cholangiocarcinoma Cells via Mitochondrial Membrane Potential Dysfunction

“…In this study, we investigated the inhibitory effect of PP on apoptotic cell death in CCA cell lines. We found that PP is an effective Previous studies showed that S-acetyldihydrolipoamide is found in gastric cancer cells and is associated with trastuzumab response 22 . Methylselenopyruvate is an α-keto acid metabolite of methylselenocysteine which acts as a histone deacetylase 8 (HDAC8) inhibitor that can restore Bcl2 modifying factor (BMF) downregulation and thereby activate apoptosis in colon cancer cells 23 .…”

Serum Metabolic Profiling of Late-Pregnant Women With Antenatal Depressive Symptoms

“…The metabolites with VIP values >1.0 and Q value < 0.05 were considered to be statistically significant, whereas variables that were not significantly changed were discarded ( 32 , 33 ). The metabolites identified were mapped by MS/MS spectral similarity with score ≥0.8 based on an in-house database ( 34 ). In addition, the differential metabolites were mapped into their biochemical pathways through metabolic pathway enrichment and pathway analysis based on MetaboAnalyst 5.0 ( http://www.metaboanalyst.ca ), which uses the high-quality Kyoto Encyclopedia of Genes and Genomes metabolic pathways as the backend knowledge base ( 34 , 35 ), and a pathway with p < 0.05 was considered to be significant ( 36 ).…”

“…In addition, the differential metabolites were mapped into their biochemical pathways through metabolic pathway enrichment and pathway analysis based on MetaboAnalyst 5.0 (http://www.metaboanalyst. ca), which uses the high-quality Kyoto Encyclopedia of Genes and Genomes metabolic pathways as the backend knowledge base (34,35), and a pathway with p < 0.05 was considered to be significant (36). All data analyses were conducted using SPSS 22.0 (IBM Corp., Armonk, NY, USA) or RStudio version 1.2.1335-2009-2019 (RStudio, Inc.) software.…”

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

“…Intracellular metabolites extractions were performed according to methods that were utilized in our previous study 14 . Briefly, cells were seeded in 6-well plates for 48-72 h in complete medium after which cells were harvested and counted at a density of 1×10 7 cells/well.…”

“…Subsequent data processing and analysis was accomplished using the bioinformatics program XCMS in R package (version 3.3.0) 15 . The parameters settings were accomplished as it was in our previous study 14 . OSI-SMMS software (version 1.0, Dalian Chem Data Solution Information Technology Co. Ltd.) was further used for peak annotation after XCMS data.…”