Thiol profiling in cancer cell lines by HPLC-mass spectrometry.
Ontology highlight
ABSTRACT:
SUBMITTER: Liu X
PROVIDER: S-EPMC8669100 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Abnormal lipid metabolisms are closely associated with cancers. In this study, mass spectrometry was employed to in situ investigate the associations of membrane lipid phenotypes of six human lung cancer cell lines (i.e., A549, H1650, H1975 from adenocarcinoma, H157 and H1703 from squamous cell carcinomas, and H460 from a large cell carcinoma) with cancer cell types and finally total 230 lipids were detected. Based these 230 lipids, partial least-square discriminant analysis indicated that fifteen lipids (i.e., PE 18:0_18:1, PI 18:0_20:4, SM 42:2, PE 16:0_20:4, PE 36:2, PC 36:2, SM 34:1, PA 38:3,C18:0, C22:4, PA 34:2, C20:5, C20:2, C18:2, and CerP 36:2) with variable importance in the projection (VIP) value of > 1.0 could be used to differentiate six cancer cell lines with the Predicted Residual Sum of Square (PRESS) score of 0.1974. Positive correlation between polyunsaturated fatty acids (i.e., C20:4, C22:4, C22:5, and C22:6) and polyunsaturated phospholipids (PE 16:0_20:4, PE 38:4, and PI 18:0_20:4) was observed in lung adenocarcinoma cells, especially for H1975 cells. Three adenocarcinoma cell lines (i.e., A549, H1650, and H1975) could be differentiated from other lung cancer cell lines based on the expression of C18:1, C20:1, C20:2, C20:5, and C22:6.
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Project description:The functions of the liver and the pancreas differ; however, chronic inflammation in both organs is associated with fibrosis. Evidence suggests that fibrosis in both organs is partially regulated by organ-specific stellate cells. We explore the proteome of human hepatic stellate cells (hHSC) and human pancreatic stellate cells (hPaSC) using mass spectrometry (MS)-based quantitative proteomics to investigate pathophysiologic mechanisms. Proteins were isolated from whole cell lysates of immortalized hHSC and hPaSC. These proteins were tryptically digested, labeled with tandem mass tags (TMT), fractionated by OFFGEL, and subjected to MS. Proteins significantly different in abundance (P<0.05) were classified via gene ontology (GO) analysis. We identified 1223 proteins and among them, 1222 proteins were quantifiable. Statistical analysis determined that 177 proteins were of higher abundance in hHSC, while 157 were of higher abundance in hPaSC. GO classification revealed that proteins of relatively higher abundance in hHSC were associated with protein production, while those of relatively higher abundance in hPaSC were involved in cell structure. Future studies using the methodologies established herein, but with further upstream fractionation and/or use of enhanced MS instrumentation will allow greater proteome coverage, achieving a comprehensive proteomic analysis of hHSC and hPaSC.
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Project description:BackgroundEvidences indicated that non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC) might originate from the same cell type, which however ended up to be two different subtypes of lung carcinoma, requiring different therapeutic regimens. We aimed to identify the differences between these two subtypes of lung cancer by using integrated proteome and genome approaches.Methods and materialsTwo representative cell lines for each lung cancer subtype were comparatively analysed by quantitative proteomics, and their corresponding transcriptomics data were obtained from the Gene Expression Omnibus database. The integrated analyses of proteogenomic data were performed to determine key differentially expressed proteins that were positively correlated between proteomic and transcriptomic data.ResultThe proteomics analysis revealed 147 differentially expressed proteins between SCLC and NSCLC from a total of 3,970 identified proteins. Combined with available transcriptomics data, we further confirmed 14 differentially expressed proteins including six known and eight new lung cancer related proteins that were positively correlated with their transcriptomics data. These proteins are mainly involved in cell migration, proliferation, and invasion.ConclusionThe proteogenomic data on both NSCLC and SCLC cell lines presented in this manuscript is complementary to existing genomic and proteomic data related to lung cancers and will be crucial for a systems biology-level understanding of the molecular mechanism of lung cancers. The raw mass spectrometry data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD015270.
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Project description:PurposeAdvanced testicular germ cell tumours (GCT) generally have a good prognosis owing to their unique sensitivity towards cisplatin-based chemotherapies. However, cisplatin-resistant GCT have a poor outcome. Further studies are mandatory to better understand resistance mechanisms and develop therapeutic strategies for refractory GCTs.MethodsProtein levels in cisplatin-resistant GCT cell lines of NTERA-2, NCCIT and 2102EP were analyzed by quantitative proteomic mass spectrometry (MS) in combination with stable isotope labelling by amino acids in cell culture (SILAC). Differentially abundant protein markers of acquired cisplatin resistance were validated by Western blotting. Comprehensive bioinformatical annotation using gene set enrichment analyses (GSEA) and STRING interaction analysis were performed to identify commonly affected pathways in cisplatin resistance and the data were compared to the GCT cohort of the 'The Cancer Genome Atlas'.ResultsA total of 4375 proteins were quantified by MS, 144 of which were found to be differentially abundant between isogenic resistant and sensitive cell line pairs (24 proteins for NTERA-2, 60 proteins for NCCIT, 75 proteins for 2102EP). Western blotting confirmed regulation of key resistance-associated proteins (CBS, ANXA1, LDHA, CTH, FDXR). GSEA revealed a statistically significant enrichment of DNA repair-associated proteins in all three resistant cell lines and specific additional processes for individual cell lines.ConclusionHigh resolution MS combined with SILAC is a powerful tool and 144 significantly deregulated proteins were found in cisplatin-resistant GCT cell lines. Our study provides the largest proteomic in vitro library for cisplatin resistance in GCT, yet, enabling further studies to develop new treatment options for patients with refractory GCT.
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Project description:BackgroundOnco-proteogenomics aims to understand how changes in a cancer's genome influences its proteome. One challenge in integrating these molecular data is the identification of aberrant protein products from mass-spectrometry (MS) datasets, as traditional proteomic analyses only identify proteins from a reference sequence database.MethodsWe established proteomic workflows to detect peptide variants within MS datasets. We used a combination of publicly available population variants (dbSNP and UniProt) and somatic variations in cancer (COSMIC) along with sample-specific genomic and transcriptomic data to examine proteome variation within and across 59 cancer cell-lines.ResultsWe developed a set of recommendations for the detection of variants using three search algorithms, a split target-decoy approach for FDR estimation, and multiple post-search filters. We examined 7.3 million unique variant tryptic peptides not found within any reference proteome and identified 4771 mutations corresponding to somatic and germline deviations from reference proteomes in 2200 genes among the NCI60 cell-line proteomes.ConclusionsWe discuss in detail the technical and computational challenges in identifying variant peptides by MS and show that uncovering these variants allows the identification of druggable mutations within important cancer genes.
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Project description:The use of cell lines in research can be affected by cell line misidentification. Short tandem repeat (STR) analysis is an effective method, and the gold standard, for the identification of the genetic origin of a cell line, but methods that allow the discrimination between cell lines of the same genetic origin are lacking. Here, we use intact cell MALDI-ToF mass spectrometry analysis, routinely used for the identification of bacteria in clinical diagnostic procedures, for the authentication of a set of cell lines consisting of three parental neuroblastoma cell lines (IMR-5, IMR-32 and UKF-NB-3) and eleven drug-adapted sublines. Principal component analysis (PCA) of intact-cell MALDI-ToF mass spectrometry data revealed clear differences between most, but not all, of the investigated cell lines. Mass spectrometry whole-cell fingerprints enabled the separation of IMR-32 and its clonal subline IMR-5. Sublines that had been adapted to closely related drugs, for example, the cisplatin- and oxaliplatin-resistant UKF-NB-3 sublines and the vincristine- and vinblastine-adapted IMR-5 sublines, also displayed clearly distinctive patterns. In conclusion, intact whole-cell MALDI-ToF mass spectrometry has the potential to be further developed into an authentication method for mammalian cells of a common genetic origin.
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Project description:Data Access Committee EGAC00001002236
| EGAC00001002236 | EGA
Project description:Methanococcus maripaludis is a methanogenic archaeon. Within its genome, there are two operons for membrane associated hydrogenases, eha and ehb. To investigate the regulation of ehb on the cell, an S40 mutant was constructed in such a way that a portion of the ehb operon was replaced by pac cassette in the wild type parental strain S2 (done by Whitman's group at the University of Georgia). The S40 and S2 strains were grown in 14N and 15N media with acetate separately. A biological replicate was made by switching the media. Mass spectrometry based quantitative proteomics were done on the mixtures to investigate the differences in expression patterns between S40 and S2. Keywords: isotope labeling mass spectrometry, quantitative proteomics
2005-09-20 | GSE2744 | GEO
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