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At least 127 records · Page 7Linked to original sources
PubMed2005

Proteins associated with Cisplatin resistance in ovarian cancer cells identified by quantitative proteomic technology and integrated with mRNA expression levels.

Nearly all women diagnosed with ovarian cancer receive combination chemotherapy including cis- or carboplatin. Despite high initial response rates, resistance to cisplatin develops in roughly one-third of women during primary treatment and in all women treated for recurrent disease. ICAT coupled with tandem MS is a quantitative proteomic technique for high throughput protein expression profiling of complex protein mixtures. Using ICAT/MS/MS we profiled the nuclear, cytosolic, and microsomal fractions obtained from IGROV-1 [corrected] (cisplatin-sensitive) and IGROV-1/CP [corrected] (cisplatin-resistant) ovarian cancer cell lines. The proteomes of cisplatin-sensitive and -resistant ovarian cancer cells were compared, and protein expression was correlated with mRNA expression profiles. A total of 1117 proteins were identified and quantified. The relative expression of 121 of these varied between the two cell lines. Sixty-three proteins were overexpressed in cisplatin-sensitive, and 58 were over expressed in cisplatin-resistant cells. Examples of proteins at least 5-fold overexpressed in resistant cells and with biological relevance to cancer include cell recognition molecule CASPR3 (13.3-fold), S100 protein family members (8.7-fold), junction adhesion molecule Claudin 4 (7.2-fold), and CDC42-binding protein kinase beta (5.4-fold). Examples of cancer-related proteins at least 5-fold overexpressed in sensitive cells include hepatocyte growth factor inhibitor 1B (13.3-fold) and programmed cell death 6-interacting protein (12.7-fold). The direction of changes in expression levels between proteins and mRNAs were not always in the same direction, possibly reflecting posttranscriptional control of protein expression. We identified proteins whose expression profiles correlate with cisplatin resistance in ovarian cancer cells. Several proteins may be involved in modulating response to cisplatin and have potential as markers of treatment response or treatment targets.

Cell Line, Tumor↗
PubMed2026

Integration of metabolomics and proteomics reveals the toxicological mechanisms of environmentally relevant concentrations of cadmium on juvenile rockfish (Sebastes schlegelii).

As a highly toxic heavy metal, cadmium (Cd) is widely distributed in the coastal environments of the Bohai Sea, posing significant ecological and health risks. This is of particular concern for Sebastes schlegelii, a rockfish species commonly found along the Bohai coast and consumed by local populations. In this study, juvenile S. schlegelii were randomly assigned to three groups (control, 5 and 50&#xa0;&#x3bc;g/L Cd) for a 14-day exposure period, followed by analysis of Cd bioaccumulation, as well as metabolomic and proteomic profiling. ICP-MS analysis indicated dose-dependent Cd bioaccumulation in the whole body, with 0.11&#xa0;&#xb1;&#xa0;0.07&#xa0;&#x3bc;g/g dry weight in the 5&#xa0;&#x3bc;g/L group and 0.38&#xa0;&#xb1;&#xa0;0.09&#xa0;&#x3bc;g/g dry weight in the 50&#xa0;&#x3bc;g/L group (9.5-fold higher than the control, p&#xa0;<&#xa0;0.05). An iTRAQ-based proteomic analysis determined 168 differentially expressed proteins, while 1H NMR-based metabolomic profiling identified 34 metabolites with significant alterations. Integrated analysis of the proteomic and metabolomic data provided insights into the molecular responses of juvenile rockfish to Cd exposure. Specifically, metabolomic results indicated significant alterations in key metabolites, including lactate, phosphocholine, adenosine triphosphate, alanine, and inosine in the Cd-treated groups. Proteomic analysis further suggested that Cd exposure was associated with immune and oxidative stress responses, neurotoxicity, cellular damage, and disruptions in critical metabolic pathways, such as glycolysis, the tricarboxylic acid cycle, amino acid and lipid metabolism. Overall, this study demonstrates the utility of integrating proteomics and metabolomics to characterize molecular responses to Cd stress in juvenile S. schlegelii.

Animals↗
PubMed1998

An integrated approach to proteome analysis: identification of proteins associated with cardiac hypertrophy.

Hypertrophy of cardiac myocytes is a primary response of the heart to overload, and is an independent predictor of heart failure and death. Distinct cellular phenotypes are associated with hypertrophy resulting from different causes. These phenotypes have been described by others at the molecular level by analysis of gene transcription patterns. An alternative approach is the analysis of large-scale protein expression patterns (the proteome) by two-dimensional polyacrylamide gel electrophoresis. Realization of this goal requires the ability to rigorously analyze complex 2D gel images, efficiently digest individual gel isolated proteins (especially those expressed at low levels), and analyze the resulting peptides with high sensitivity for rapid database searches. We have undertaken to improve the technology and experimental approaches to these challenges in order to effectively study a cell culture model for cardiac hypertrophy. The 2D gel patterns for cell lysates from multiple samples of cardiac myocytes with or without phenylephrine-induced hypertrophy were analyzed and spots which changed in abundance with statistical significance were located. Eleven such spots were identified using improved procedures for in-gel digestion of silver-stained proteins and high-sensitivity mass spectrometry. The incorporation of low levels of sodium dodecyl sulfate into the digestion buffer improved peptide recovery. The combination of matrix-assisted laser desorption mass spectrometry for initial measurements and capillary liquid chromatography-ion trap mass spectrometry for peptide sequence determination yielded efficient protein identification. The integration of 2D gel image analysis and routine identification of proteins present in gels at the subpicomole level represents a general model for proteome studies relating genomic sequence with protein expression patterns.

Amino Acid Sequence↗
PubMed2004

Integrated genomic and proteomic analyses of gene expression in Mammalian cells.

Using DNA microarrays together with quantitative proteomic techniques (ICAT reagents, two-dimensional DIGE, and MS), we evaluated the correlation of mRNA and protein levels in two hematopoietic cell lines representing distinct stages of myeloid differentiation, as well as in the livers of mice treated for different periods of time with three different peroxisome proliferative activated receptor agonists. We observe that the differential expression of mRNA (up or down) can capture at most 40% of the variation of protein expression. Although the overall pattern of protein expression is similar to that of mRNA expression, the incongruent expression between mRNAs and proteins emphasize the importance of posttranscriptional regulatory mechanisms in cellular development or perturbation that can be unveiled only through integrated analyses of both proteins and mRNAs.

Animals↗
PubMed2005

Proteomic analysis with integrated multiple dimensional liquid chromatography/mass spectrometry based on elution of ion exchange column using pH steps.

A novel integrated multidimensional liquid chromatography (IMDL) method is demonstrated for the separation of peptide mixtures by two-dimensional HPLC coupled with ion trap mass spectrometry. The method uses an integrated column, containing both strong cation exchange and reversed-phase sections for two-dimensional liquid chromatography. The peptide mixture was fractionated by a pH step using a series of pH buffers, followed by reversed-phase chromatography. Since no salt was used during separation, the integrated multidimensional liquid chromatography can be directly connected to mass spectrometry for peptide analysis. The pH buffers were injected from an autosampler, and the entire process can be carried out on a one-dimensional liquid chromatography system. In a single analysis, the IMDL system, coupled with linear ion trap mass spectrometry, identified more than 2000 proteins in mouse liver. The peptides were eluted according to their pI distribution. The resolution of the pH fractionation is approximately 0.5 pH unit. The method has low overlapping across pH fractions, good resolution of peptide mixture, and good correlation of peptide pIs with pH steps. This method provides a technique for large-scale protein identification using existing one-dimensional HPLC systems.

Chromatography, High Pressure Liquid↗
PubMed2004

The International Protein Index: an integrated database for proteomics experiments.

Despite the complete determination of the genome sequence of several higher eukaryotes, their proteomes remain relatively poorly defined. Information about proteins identified by different experimental and computational methods is stored in different databases, meaning that no single resource offers full coverage of known and predicted proteins. IPI (the International Protein Index) has been developed to address these issues and offers complete nonredundant data sets representing the human, mouse and rat proteomes, built from the Swiss-Prot, TrEMBL, Ensembl and RefSeq databases.

Animals↗
PubMed2026

Integrative Transcriptomic and Proteomic Profiling Identifies S100P as a Potential Functional Biomarker for Sessile Serrated Lesions.

BACKGROUND: Sessile serrated lesions (SSLs) account for 15% of colorectal cancers (CRCs) but detection remains difficult due to flat morphology, mucinous features, and subtle histology. AIMS: This study aimed to identify novel and functionally relevant biomarkers of SSLs using transcriptomic screening and multi-omics validation. METHODS: Paired SSL and normal mucosa specimens (n&#x2009;=&#x2009;6) underwent RNA sequencing. Differentially expressed genes (DEGs) were filtered for membrane or secretory proteins and validated across TCGA and adenoma transcriptomes. Functional significance was assessed using CRISPR dependency profiling, proteotranscriptomic concordance, pharmacogenomic sensitivity, and connectivity map analysis. RESULTS: We identified 216 upregulated genes in SSLs, including 68 encoding secretory/membrane proteins that better discriminated SSLs from controls and were enriched for adhesion and neuronal signaling while suppressing TNF&#x3b1;-NF&#x3ba;B inflammatory pathways. Cross-cohort comparison revealed five overlapping candidates between SSLs and TCGA CMS1 tumors. Among them, S100P emerged as the primary biomarker candidate, showing consistent upregulation in SSLs and CMS1 tumors while remaining low in normal mucosa and conventional adenomas. TFF1 also showed RNA-level upregulation but appeared more context-dependent. S100P demonstrated strong RNA-protein concordance in CRC cell-line profiling, supporting its detectability as a biomarker candidate. Pharmacogenomic profiling of LS411N cells revealed marked sensitivity to SN-38 and fluoropyrimidines, consistent with serrated CRC vulnerabilities. Connectivity map analysis identified perturbations, including MAPK1 and histone acetyltransferase suppression, that may reverse parts of the SSL transcriptional program. CONCLUSION: These findings prioritize S100P as a promising biomarker candidate for SSLs that warrants further validation in larger cohorts and clinically applicable platforms.

Humans↗
PubMedDate not supplied

Integrating a functional proteomic approach into the target discovery process.

Functional proteomics is a promising technique for the rational identification of novel therapeutic targets by elucidation of the function of newly identified proteins in disease-relevant cellular pathways. Of the recently described high-throughput approaches for analyzing protein-protein interactions, the yeast two-hybrid (Y2H) system has turned out to be one of the most suitable for genome-wide analysis. However, this system presents a challenging technical problem: the high prevalence of false positives and false negatives in datasets due to intrinsic limitations of the technology and the use of a high-throughput, genetic assay. We discuss here the different experimental strategies applied to Y2H assays, their general limitations and advantages. We also address the issue of the contribution of protein interaction mapping to functional biology, especially when combined with complementary genomic and proteomic analyses. Finally, we illustrate how the combination of protein interaction maps with relevant functional assays can provide biological support to large-scale protein interaction datasets and contribute to the identification and validation of potential therapeutic targets.

Animals↗
PubMed2026

Integrated histone and proteome analyses reveal convergent and distinct hepatotoxic mechanisms of tenuazonic acid and deoxynivalenol.

Mycotoxins are widespread dietary contaminants whose health impacts are expected to intensify under climate change. Although their mechanisms of toxicity remain incompletely understood, epigenetic dysregulation has been increasingly implicated. Here, mass spectrometry-based multi-omics was used to profile histone post-translational modifications and proteome dynamics in HepG2 cells exposed to seven mycotoxin conditions. Time-resolved analyses identified tenuazonic acid as the dominant cellular disruptor, inducing alterations in H3K27 and H1 variants, and revealing a previously unrecognized oxidative modification of the H1.0 N-terminal methionine (H1.0N-term0AcM0Ox) that retains the protein's N-terminal acetylation. An Alternaria toxin mixture induced similar H1 responses, largely driven by tenuazonic acid, while deoxynivalenol produced convergent chromatin and proteomic alterations. Proteomic remodeling was characterized by increased protein translation, reduced mitochondrial complex IV expression, and impaired cholesterol biosynthesis, whereas sterigmatocystin activated DNA replication and repair pathways. Together, these findings demonstrate that mycotoxins disrupt chromatin organization, protein synthesis, and lipid metabolism, providing toxicological insight into hepatocellular dysfunction. These findings warrant further validation and mechanistic investigation in future hypothesis-driven studies of mycotoxin exposure.

Trichothecenes↗
PubMed2002

Operomics: integrated genomic and proteomic profiling of cells and tissues.

In the post-genome era, technologies are becoming available that allow the profiling of tissues and cell populations at multiple levels including genomic (DNA and RNA), proteomic (proteins and peptides) and post-proteomic (eg metabolomic). Operomics refers to the molecular analysis of tissues and cells at the three levels that are connected through the coding process - namely, DNA, RNA and protein. The premise is that no one level or type of analysis fully captures gene expression and that functional changes at the proteome level cannot be simply predicted from analyses at the DNA or RNA levels. An important determinant that weakens a direct link between RNA and protein levels is translational control that differentially regulates mRNA translation. In this paper, the approaches for genomic and proteomic profiling and the contribution of translational control are reviewed.

DNA Methylation↗
PubMed2002

Integrated genomic and proteomic analysis of signaling pathways in dendritic cell differentiation and maturation.

Dendritic cells (DCs) are antigen-presenting cells that play a major role in initiating primary immune responses. Their phenotypic and functional characteristics are intimately linked to their stage of maturation. The specific biochemical pathways and genes whose expression mediates differentiation of progenitors to DCs and their maturation are largely undefined. We recently utilized two approaches, DNA microarrays and proteomics, to analyze the expression profile of human CD14(+) blood monocytes and their derived DCs. Approximately 4% of the genes or proteins expressed were found to be regulated during DC differentiation. Most of these genes were not previously associated with DCs and included genes highly relevant to DC functions (genes involved in antigen presentation, cell adhesion and motility, lipid metabolism). Genes involved in specific signaling pathways, including IkappaBalpha, PPAR-gamma and C/EBPalpha as well as two members of the family of transcription factors, interferon regulatory factors (IRFs), were also modified. Modulation of IRF gene expression is of particular interest because of their functional roles in innate and adaptive immune responses. IRF-family members control the expression of proteins that include type-1 interferons, interleukin-12, interleukin-15, MHC molecules and adhesion molecules. They have also been found to play an important role in lymphocyte development. In contrast to DC differentiation, very few genes were modified at the transcript level during DC maturation as determined by microarray experiments. Further analysis suggested that DC maturation is largely controlled by posttranscriptional and posttranslational modifications. The use of proteomics is therefore necessary for a full comprehension of DC maturation process.

Animals↗
PubMed2007

Virtual Expert Mass Spectrometrist v3.0: an integrated tool for proteome analysis.

The number of tools described in the literature for analysis of proteome data is growing fast. However, most tools are not able to communicate or exchange data with other tools. In Virtual Expert Mass Spectrometrist (VEMS) v3.0 an effort has been made to interface and export to already existing tools. In this chapter, an outline of how to use the VEMS program to search tandem mass spectrometry data against databases is described. Additionally, examples on how to extend the analysis with other external tools are given.

Calibration↗
PubMed2005

An integrated approach utilizing proteomics and bioinformatics to detect ovarian cancer.

OBJECTIVE: To find new potential biomarkers and establish the patterns for the detection of ovarian cancer. METHODS: Sixty one serum samples including 32 ovarian cancer patients and 29 healthy people were detected by surface-enhanced laser desorption/ionization mass spectrometry (SELDI-MS). The protein fingerprint data were analyzed by bioinformatics tools. Ten folds cross-validation support vector machine (SVM) was used to establish the diagnostic pattern. RESULTS: Five potential biomarkers were found (2085 Da, 5881 Da, 7564 Da, 9422 Da, 6044 Da), combined with which the diagnostic pattern separated the ovarian cancer from the healthy samples with a sensitivity of 96.7%, a specificity of 96.7% and a positive predictive value of 96.7%. CONCLUSIONS: The combination of SELDI with bioinformatics tools could find new biomarkers and establish patterns with high sensitivity and specificity for the detection of ovarian cancer.

Adolescent↗