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Bai H, Collins LB, André MR, Breitschwerdt EB, Islam Williams T. Bottom-Up Proteomics Workflow for Studying Multi-organism Systems. Methods Mol Biol 2025; 2884:119-141. [PMID: 39716001 DOI: 10.1007/978-1-0716-4298-6_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2024]
Abstract
In recent years, discovery proteomics has emerged as a pivotal tool in biological research, especially when studying the intricate relationships among multiple organisms. To delve deeper into these interactions, we pioneered a bottom-up proteomics workflow. Using nanoLC-MS/MS and a label-free quantification method, this work specifically examines the differential protein expression in fleas (Ctenocephalides felis felis) that have been experimentally infected with Bartonella henselae, the causative agent of cat scratch disease (CSD). Our detailed methodology, from protein cleanup to data analysis using the Proteome Discoverer software, is meticulously outlined to aid other researchers in adopting and adapting this workflow for their own multi-organism studies. This versatile protocol serves as a foundational guide for examining multiple proteomes from varied taxonomic lineages, exemplified in our cat-flea-bacterium investigation.
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Sharma V, Singh SB, Bandyopadhyay S, Sikka K, Kakkar A, Hariprasad G. Label-based comparative proteomics of oral mucosal tissue to understand progression of precancerous lesions to oral squamous cell carcinoma. Biochem Biophys Rep 2024; 40:101842. [PMID: 39483176 PMCID: PMC11525462 DOI: 10.1016/j.bbrep.2024.101842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2024] [Revised: 10/07/2024] [Accepted: 10/07/2024] [Indexed: 11/03/2024] Open
Abstract
Introduction Oral squamous cell carcinomas typically arise from precancerous lesions such as leukoplakia and erythroplakia. These lesions exhibit a range of histological changes from hyperplasia to dysplasia and carcinoma in situ, during their transformation to malignancy. The molecular mechanisms driving this multistage transition remain incompletely understood. To bridge this knowledge gap, our current study utilizes label based comparative proteomics to compare protein expression profiles across different histopathological grades of leukoplakia, erythroplakia, and oral squamous cell carcinoma samples, aiming to elucidate the molecular changes underlying lesion evolution. Methodology An 8-plex iTRAQ proteomics of 4 biological replicates from 8 clinical phenotypes of leukoplakia and erythroplakia, with hyperplasia, mild dysplasia, moderate dysplasia; along with phenotypes of well differentiated squamous cell carcinoma and moderately differentiated squamous cell carcinoma was carried out using the Orbitrap Fusion Lumos mass spectrometer. Raw files were processed with Maxquant, and statistical analysis across groups was conducted using MetaboAnalyst. Statistical tools such as ANOVA, PLS-DA VIP scoring, and correlation analysis were employed to identify differentially expressed proteins that had a linear expression variation across phenotypes of hyperplasia to cancer. Validation was done using Bioinformatic tools such as ClueGO + Cluepedia plugin in Cytoscape to extract functional annotations from gene ontology and pathway databases. Results and discussion A total of 2685 protein groups and 12,397 unique peptides were identified, and 61 proteins consistently exhibited valid reporter ion corrected intensities across all samples. Of these, 6 proteins showed linear varying expression across the analysed sample phenotypes. Collagen type VI alpha 2 chain (COL6A2), Fibrinogen β chain (FGB), and Vimentin (VIM) were found to have increased linear expression across pre-cancer phenotypes of leukoplakia to cancer, while Annexin A7 (ANXA7) was seen to be having a linear decreasing expression. Collagen type VI alpha 2 chain (COL6A2) and Annexin A2 (ANXA2) had increased linear expression across precancer phenotypes of erythroplakia to cancer. The mass spectrometry proteomics data have been deposited to the ProteomeXchanger Consortium via the PRIDE partner repository with the data set identifier PXD054190. These differentially expressed proteins mediate cancer progression mainly through extracellular exosome; collagen-containing extracellular matrix, hemostasis, platelet aggregation, and cell adhesion molecule binding. Conclusion Label-based proteomics is an ideal platform to study oral cancer progression. The differentially expressed proteins provide insights into the molecular mechanisms underlying the progression of oral premalignant lesions to malignant phenotypes. The study has translational value for early detection, risk stratification, and potential therapeutic targeting of oral premalignant lesions and in its prevention to malignant forms.
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Rajan MV, Sharma V, Upadhyay N, Murali A, Bandyopadhyay S, Hariprasad G. Serum proteomics for the identification of biomarkers to flag predilection of COVID19 patients to various organ morbidities. Clin Proteomics 2024; 21:61. [PMID: 39487396 PMCID: PMC11531188 DOI: 10.1186/s12014-024-09512-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2024] [Accepted: 10/23/2024] [Indexed: 11/04/2024] Open
Abstract
BACKGROUND COVID19 is a pandemic that has affected millions around the world since March 2020. While many patients recovered completely with mild illness, many patients succumbed to various organ morbidities. This heterogeneity in the clinical presentation of COVID19 infection has posed a challenge to clinicians around the world. It is therefore crucial to identify specific organ-related morbidity for effective treatment and better patient outcomes. We have carried out serum-based proteomic experiments to identify protein biomarkers that can flag organ dysfunctions in COVID19 patients. METHODS COVID19 patients were screened and tested at various hospitals across New Delhi, India. 114 serum samples from these patients, with and without organ morbidities were collected and annotated based on clinical presentation and treatment history. Of these, 29 samples comprising of heart, lung, kidney, gastrointestinal, liver, and neurological morbidities were considered for the discovery phase of the experiment. Proteins were isolated, quantified, trypsin digested, and the peptides were subjected to liquid chromatography assisted tandem mass spectrometry analysis. Data analysis was carried out using Proteome Discoverer software. Fold change analysis was carried out on MetaboAnalyst. KEGG, Reactome, and Wiki Pathway analysis of differentially expressed proteins were carried out using the STRING database. Potential biomarker candidates for various organ morbidities were validated using ELISA. RESULTS 254 unique proteins were identified from all the samples with a subset of 12-31 differentially expressed proteins in each of the clinical phenotypes. These proteins establish complement and coagulation cascade pathways in the pathogenesis of the organ morbidities. Validation experiments along with their diagnostic parameters confirm Secreted Protein Acidic and Rich in Cysteine, Cystatin C, and Catalase as potential biomarker candidates that can flag cardiovascular disease, renal disease, and respiratory disease, respectively. CONCLUSIONS Label free serum proteomics shows differential protein expression in COVID19 patients with morbidity as compared to those without morbidity. Identified biomarker candidates hold promise to flag organ morbidities in COVID19 for efficient patient care.
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He Y, Jin H, Ju F. Toxicological effects and underlying mechanisms of chlorination-derived metformin byproducts in Escherichia coli. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 905:167281. [PMID: 37758144 DOI: 10.1016/j.scitotenv.2023.167281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 09/14/2023] [Accepted: 09/20/2023] [Indexed: 10/03/2023]
Abstract
Chlorination-derived byproducts of the emerging contaminant metformin, such as (3E)-3-(chloroimino)-N,N-dimethyl-3H-1,2,4-triazol-5-amine (3,3-CDTA) and N-cyano-N,N-dimethylcarbaminmidic chloride (NCDC), occur in global waters and are toxic to organisms, from bacteria to mice. However, the mechanisms underlying their toxicity remain unknown. Here, we explored the toxicological effects and potential molecular mechanisms of 3,3-CDTA and NCDC at milligram concentrations, using Escherichia coli as a model organism. Compared with metformin (>300 mg/L), 3,3-CDTA and NCDC exerted stronger toxicity to E. coli, with a 4-h half maximal inhibitory concentration of 2.97 mg/L and 75.7 mg/L, respectively. Both byproducts disrupted E. coli cellular structures and components, decreased membrane potential and adenosine triphosphate (ATP) biosynthesis, and led to excessive reactive oxidative species (ROS), as well as the ROS-scavenging enzymes superoxide dismutase and catalase. Proteomic analysis and molecular docking supported these biomarker responses in the byproduct-treated E. coli, and indicated potential damage to DNA/RNA processes, while also provided novel insights into the toxicological and detoxified-byproduct effects at the proteome level. The toxicity-related events of NCDC and 3,3-CDTA included membrane disruption, oxidative stress, and abnormal protein expression. This study is the first to examine the toxicological effects of chlorination-derived metformin byproducts in E. coli and the associated pathways involved; thereby broadening our understanding regarding the toxicity and transformation risks of metformin throughout its entire life process.
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Wang Z, Cao L, Wang J, Wang H, Ma T, Yin Z, Cai W, Liu L, Liu T, Ma H, Zhang Y, Shen Z, Zheng H. A novel predictive model of microvascular invasion in hepatocellular carcinoma based on differential protein expression. BMC Gastroenterol 2023; 23:89. [PMID: 36973651 PMCID: PMC10041792 DOI: 10.1186/s12876-023-02729-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Accepted: 03/13/2023] [Indexed: 03/29/2023] Open
Abstract
BACKGROUND This study aims to construct and verify a nomogram model for microvascular invasion (MVI) based on hepatocellular carcinoma (HCC) tumor characteristics and differential protein expressions, and explore the clinical application value of the prediction model. METHODS The clinicopathological data of 200 HCC patients were collected and randomly divided into training set and validation set according to the ratio of 7:3. The correlation between MVI occurrence and primary disease, age, gender, tumor size, tumor stage, and immunohistochemical characteristics of 13 proteins, including GPC3, CK19 and vimentin, were statistically analyzed. Univariate and multivariate analyzes identified risk factors and independent risk factors, respectively. A nomogram model that can be used to predict the presence of MVI was subsequently constructed. Then, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were conducted to assess the performance of the model. RESULTS Multivariate logistic regression analysis indicated that tumor size, GPC3, P53, RRM1, BRCA1, and ARG were independent risk factors for MVI. A nomogram was constructed based on the above six predictors. ROC curve, calibration, and DCA analysis demonstrated the good performance and the clinical application potential of the nomogram model. CONCLUSIONS The predictive model constructed based on the clinical characteristics of HCC tumors and differential protein expression patterns could be helpful to improve the accuracy of MVI diagnosis in HCC patients.
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Araújo MJ, Sousa ML, Fonseca E, Felpeto AB, Martins JC, Vázquez M, Mallo N, Rodriguez-Lorenzo L, Quarato M, Pinheiro I, Turkina MV, López-Mayán JJ, Peña-Vázquez E, Barciela-Alonso MC, Spuch-Calvar M, Oliveira M, Bermejo-Barrera P, Cabaleiro S, Espiña B, Vasconcelos V, Campos A. Proteomics reveals multiple effects of titanium dioxide and silver nanoparticles in the metabolism of turbot, Scophthalmus maximus. CHEMOSPHERE 2022; 308:136110. [PMID: 36007739 DOI: 10.1016/j.chemosphere.2022.136110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 08/01/2022] [Accepted: 08/16/2022] [Indexed: 06/15/2023]
Abstract
Titanium dioxide (TiO2) and silver (Ag) NPs are among the most used engineered inorganic nanoparticles (NPs); however, their potential effects to marine demersal fish species, are not fully understood. Therefore, this study aimed to assess the proteomic alterations induced by sub-lethal concentrations citrate-coated 25 nm ("P25") TiO2 or polyvinylpyrrolidone (PVP) coated 15 nm Ag NPs to turbot, Scophthalmus maximus. Juvenile fish were exposed to the NPs through daily feeding for 14 days. The tested concentrations were 0, 0.75 or 1.5 mg of each NPs per kg of fish per day. The determination of NPs, Titanium and Ag levels (sp-ICP-MS/ICP-MS) and histological alterations (Transmission Electron Microscopy) supported proteomic analysis performed in the liver and kidney. Proteomic sample preparation procedure (SP3) was followed by LC-MS/MS. Label-free MS quantification methods were employed to assess differences in protein expression. Functional analysis was performed using STRING web-tool. KEGG Gene Ontology suggested terms were discussed and potential biomarkers of exposure were proposed. Overall, data shows that liver accumulated more elements than kidney, presented more histological alterations (lipid droplets counts and size) and proteomic alterations. The Differentially Expressed Proteins (DEPs) were higher in Ag NPs trial. The functional analysis revealed that both NPs caused enrichment of proteins related to generic processes (metabolic pathways). Ag NPs also affected protein synthesis and nucleic acid transcription, among other processes. Proteins related to thyroid hormone transport (Serpina7) and calcium ion binding (FAT2) were suggested as biomarkers of TiO2 NPs in liver. For Ag NPs, in kidney (and at a lower degree in liver) proteins related with metabolic activity, metabolism of exogenous substances and oxidative stress (e.g.: NADH dehydrogenase and Cytochrome P450) were suggested as potential biomarkers. Data suggests adverse effects in turbot after medium/long-term exposures and the need for additional studies to validate specific biological applications of these NPs.
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ITRAQ-based quantitative proteomic analysis of Fusarium moniliforme (Fusarium verticillioides) in response to Phloridzin inducers. Proteome Sci 2021; 19:2. [PMID: 33446211 PMCID: PMC7807804 DOI: 10.1186/s12953-021-00170-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 01/02/2021] [Indexed: 11/13/2022] Open
Abstract
Background Apple replant disease (ARD) has been reported from all major fruit-growing regions of the world, and is often caused by biotic factors (pathogen fungi) and abiotic factors (phenolic compounds). In order to clarify the proteomic differences of Fusarium moniliforme under the action of phloridzin, and to explore the potential mechanism of F. moniliforme as the pathogen of ARD, the role of Fusarium spp. in ARD was further clarified. Methods In this paper, the quantitative proteomics method iTRAQ analysis technology was used to analyze the proteomic differences of F. moniliforme before and after phloridzin treatment. The differentially expressed protein was validated by qRT-PCR analysis. Results A total of 4535 proteins were detected, and 293 proteins were found with more than 1.2 times (P< 0.05) differences. In-depth data analysis revealed that 59 proteins were found with more than 1.5 times (P< 0.05) differences, and most proteins were consistent with the result of qRT-PCR. Differentially expressed proteins were influenced a variety of cellular processes, particularly metabolic processes. Among these metabolic pathways, a total of 8 significantly enriched KEGG pathways were identified with at least 2 affiliated proteins with different abundance in conidia and mycelium. Functional pathway analysis indicated that up-regulated proteins were mainly distributed in amino sugar, nucleotide sugar metabolism, glycolysis/ gluconeogenesis and phagosome pathways. Conclusions This study is the first to perform quantitative proteomic investigation by iTRAQ labeling and LC-MS/MS to identify differentially expressed proteins in F. moniliforme under phloridzin conditions. The results confirmed that F. moniliforme presented a unique protein profile that indicated the adaptive mechanisms of this species to phloridzin environments. The results deepened our understanding of the proteome in F. moniliforme in response to phloridzin inducers and provide a basis for further exploration for improving the efficiency of the fungi as biocontrol agents to control ARD. Supplementary Information The online version contains supplementary material available at 10.1186/s12953-021-00170-2.
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Voruganti S, Kline JT, Balch MJ, Rogers J, Matts RL, Hartson SD. Proteomic Profiling of Hsp90 Inhibitors. Methods Mol Biol 2018; 1709:139-162. [PMID: 29177657 DOI: 10.1007/978-1-4939-7477-1_11] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
Mass spectrometry assays demonstrate that Hsp90 inhibitors alter the expression of approximately one-quarter of the assayable proteome in mammalian cells. These changes are extraordinarily robust and reproducible, making "proteomics profiling" the gold standard for validating the effects of new Hsp90 inhibitors on cultured cells. Proteomics assays can also suggest novel hypotheses regarding drug mechanisms. To assist investigators in adopting this approach, this Chapter provides detailed protocols for conducting simple proteomics assays of Hsp90 inhibition. The protocols present a robust label-free approach that utilizes pre-fractionation of protein samples by SDS-PAGE, thereby providing reasonably good penetration into the proteome while addressing common issues with sample quality. The actual programming and operation of liquid chromatography-tandem mass spectrometers is not covered, but expectations for achievable performance are discussed, as are alternative approaches, common challenges, and software for data analysis.
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Wang Z, Zhou Q, Li Y, Qiao L, Pang Q, Huang B. iTRAQ-based quantitative proteomic analysis of conidia and mycelium in the filamentous fungus Metarhizium robertsii. Fungal Biol 2018; 122:651-658. [PMID: 29880200 DOI: 10.1016/j.funbio.2018.03.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2017] [Revised: 03/21/2018] [Accepted: 03/22/2018] [Indexed: 01/10/2023]
Abstract
Metarhizium robertsii is widely applied in biological control via conidia application. To clarify the proteomic differences between conidia and mycelia and explore the underlying mechanisms of conidia as a unit responsible for dispersal and environmental stress, we carried out an iTRAQ (isobaric tags for relative and absolute quantitation)-based quantitative proteomic analysis for two developmental stages from M. robertsii. A total of 2052 proteins were detected, and 90 showed differential protein abundance between the conidia and mycelia. These 90 proteins were primarily associated with stress resistance, amino acid and protein metabolism, and energy metabolism. Further bioinformatics analysis showed that these proteins could be mapped to 52 pathways, five of which were significantly enriched after mapping to KEGG pathways. Interestingly, many proteins involved in the significantly enriched pathway of peroxisome, biosynthesis of secondary metabolites and glyoxylate and dicarboxylate metabolism, including catalase, peroxisomal membrane anchor protein, formate dehydrogenase and isocitrate lyase, were identified with higher abundance in conidia. The results deepened our understanding of the conidia proteome in M. robertsii and provide a basis for further exploration for improving the efficiency of the fungi as biocontrol agents.
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Choksawangkarn W, Graham LM, Burke M, Lee SB, Ostrand-Rosenberg S, Fenselau C, Edwards NJ. Peptide-based systems analysis of inflammation induced myeloid-derived suppressor cells reveals diverse signaling pathways. Proteomics 2017; 16:1881-8. [PMID: 27193397 DOI: 10.1002/pmic.201500102] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2015] [Revised: 05/03/2016] [Accepted: 05/16/2016] [Indexed: 12/19/2022]
Abstract
A better understanding of molecular signaling between myeloid-derived suppressor cells (MDSC), tumor cells, T-cells, and inflammatory mediators is expected to contribute to more effective cancer immunotherapies. We focus on plasma membrane associated proteins, which are critical in signaling and intercellular communication, and investigate changes in their abundance in MDSC of tumor-bearing mice subject to heightened versus basal inflammatory conditions. Using spectral counting, we observed statistically significant differential abundances for 35 proteins associated with the plasma membrane, most notably the pro-inflammatory proteins S100A8 and S100A9 which induce MDSC and promote their migration. We also tested whether the peptides associated with canonical pathways showed a statistically significant increase or decrease subject to heightened versus basal inflammatory conditions. Collectively, these studies used bottom-up proteomic analysis to identify plasma membrane associated pro-inflammatory molecules and pathways that drive MDSC accumulation, migration, and suppressive potency.
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Wang H, Liu W, Cai Y, Ma L, Ma C, Luo A, Huang Y. Glutaminase 1 is a potential biomarker for chronic post-surgical pain in the rat dorsal spinal cord using differential proteomics. Amino Acids 2015; 48:337-48. [PMID: 26427714 DOI: 10.1007/s00726-015-2085-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2015] [Accepted: 08/24/2015] [Indexed: 12/30/2022]
Abstract
Chronic post-surgical pain (CPSP) is a normal and significant symptom in clinical surgery, such as breast operation, biliary tract operation, cesarean operation, uterectomy and thoracic operation. Severe chronic post-surgical pain could increase post-surgical complications, including myocardial ischemia, respiratory insufficiency, pneumonia and thromboembolism. However, the underlying mechanism is still unknown. Herein, a rat CPSP model was produced via thoracotomy. After surgery, in an initial study, 5 out of 12 rats after surgery showed a significant decrease in mechanical withdrawal threshold and/or increase in the number of acetone-evoked responses, and therefore classified as the CPSP group. The remaining seven animals were classified as non-CPSP. Subsequently, open-chest operation was performed on another 30 rats and divided into CPSP and non-CPSP groups after 21-day observation. Protein expression levels in the dorsal spinal cord tissue were determined by 12.5 % SDS-PAGE. Finally, differently expressed proteins were identified by LC MS/MS and analyzed by MASCOT software, followed by Gene Ontology cluster analysis using PANTHER software. Compared with the non-CPSP group, 24 proteins were only expressed in the CPSP group and another 23 proteins expressed differentially between CPSP and non-CPSP group. Western blot further confirmed that the expression of glutaminase 1 (GLS1) was significantly higher in the CPSP than in the non-CPSP group. This study provided a new strategy to identify the spinal proteins, which may contribute to the development of chronic pain using differential proteomics, and suggested that GLS1 may serve as a potential biomarker for CPSP.
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Identification of Differential Protein Expression in Hepatocellular Carcinoma Induced Wistar Albino Rats by 2D Electrophoresis and MALDI-TOF-MS Analysis. Indian J Clin Biochem 2015; 31:194-202. [PMID: 27069327 DOI: 10.1007/s12291-015-0510-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2015] [Accepted: 05/13/2015] [Indexed: 12/12/2022]
Abstract
Hepato cellular carcinoma (HCC) is a type of malignant tumor. To investigate the proteins in cancer molecular mechanism and its role in HCC, we have used proteomic tools such as 2DE and MALDI-TOF-MS. Our investigation ravels that, plasma α-fetoprotein and carcinoembryonic antigen levels were elevated in DEN induced rats and gradually decreased after the treatment with 1,3BPMU. 2DE and MALDI-TOF-MS tool offers to identify the up and down regulation of proteins in HCC. Proteomic study reveals that, five differentially expressed proteins were identified in DEN induced rats and 1,3BPMU treated rats i.e. three up regulated protein such as T kininogen, NDPKB, PRMT1 (DEN induced rats), RGS19 and PAF (1,3BPMU treated rats) in 3BPMU treated rats, activation of transcription of a single gene from multiple promoters provides flexibility in the controlled gene expression. The regulations of hepatocyte stimulating factor were slow down the proliferation of hepatic cell and uncontrolled hepatic cell growth and also molecular signals strongly argue for a patho-physiological role in liver metastasis to control the cell aggression. This indicates that, anti cancer property of 1,3BPMU can be used as potent anti cancer agent. The present study also shows the proteomic approach helps to elucidate the tumor maker as well as regulatory marker proteins in HCC.
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Rabilloud T, Lescuyer P. The proteomic to biology inference, a frequently overlooked concern in the interpretation of proteomic data: a plea for functional validation. Proteomics 2014; 14:157-61. [PMID: 24273051 DOI: 10.1002/pmic.201300413] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2013] [Revised: 11/11/2013] [Accepted: 11/13/2013] [Indexed: 11/08/2022]
Abstract
Proteomics will celebrate its 20th year in 2014. In this relatively short period of time, it has invaded most areas of biology and its use will probably continue to spread in the future. These two decades have seen a considerable increase in the speed and sensitivity of protein identification and characterization, even from complex samples. Indeed, what was a challenge twenty years ago is now little more than a daily routine. Although not completely over, the technological challenge now makes room to another challenge, which is the best possible appraisal and exploitation of proteomic data to draw the best possible conclusions from a biological point of view. The point developed in this paper is that proteomic data are almost always fragmentary. This means in turn that although better than an mRNA level, a protein level is often insufficient to draw a valid conclusion from a biological point of view, especially in a world where PTMs play such an important role. This means in turn that transformation of proteomic data into biological data requires an important intermediate layer of functional validation, i.e. not merely the confirmation of protein abundance changes by other methods, but a functional appraisal of the biological consequences of the protein level changes highlighted by the proteomic screens.
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Herrmann AG, Searcy JL, Le Bihan T, McCulloch J, Deighton RF. Total variance should drive data handling strategies in third generation proteomic studies. Proteomics 2013; 13:3251-5. [PMID: 24123801 DOI: 10.1002/pmic.201300056] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2013] [Revised: 08/02/2013] [Accepted: 08/21/2013] [Indexed: 12/26/2022]
Abstract
Quantitative proteomics is entering its "third generation," where intricate experimental designs aim to increase the spatial and temporal resolution of protein changes. This paper re-analyses multiple internally consistent proteomic datasets generated from whole cell homogenates and fractionated brain tissue samples providing a unique opportunity to explore the different factors influencing experimental outcomes. The results clearly indicate that improvements in data handling are required to compensate for the increased mean CV associated with complex study design and intricate upstream tissue processing. Furthermore, applying arbitrary inclusion thresholds such as fold change in protein abundance between groups can lead to unnecessary exclusion of important and biologically relevant data.
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