Sex Differences in the Ventral Tegmental Area and Nucleus Accumbens Proteome at Baseline and Following Nicotine Exposure

Sex differences in behaviors relevant to nicotine addiction have been observed in rodent models and human subjects. Behavioral, imaging, and epidemiological studies also suggest underlying sex differences in mesolimbic dopamine signaling pathways. In this study we evaluated the proteome in the ventral tegmental area (VTA) and nucleus accumbens (NAc) shell in male and female mice. Experimental groups included two mouse strains (C3H/HeJ and C57BL/6J) at baseline, a sub-chronic, rewarding regimen of nicotine in C3H/HeJ mice, and chronic nicotine administration and withdrawal in C57BL/6J mice. Isobaric labeling with a TMT 10-plex system, sample fractionation, and tandem mass spectrometry were used to quantify changes in protein abundance. In C3H/HeJ mice, similar numbers of proteins were differentially regulated between sexes at baseline compared with within each sex after sub-chronic nicotine administration. In C57BL/6J mice, there were significantly greater numbers of proteins differentially regulated between sexes at baseline compared with within each sex after chronic nicotine administration and withdrawal. Despite differences by sex, strain, and nicotine exposure parameters, glial fibrillary acidic protein (GFAP) and dopamine and cAMP-regulated phosphoprotein of 32 kDa (DARPP-32, Ppp1r1b) were repeatedly identified as significantly altered proteins, especially in the VTA. Further, network analyses showed sex- and nicotine-dependent regulation of a number of signaling pathways, including dopaminergic signaling. Sub-chronic nicotine exposure in female mice increased proteins related to dopaminergic signaling in the NAc shell but decreased them in the VTA, whereas the opposite pattern was observed in male mice. In contrast, dopaminergic signaling pathways were similarly upregulated in both male and female VTA after chronic nicotine and withdrawal. Overall, this study identifies significant sex differences in the proteome of the mesolimbic system, at baseline and after nicotine reward or withdrawal, which may help explain differential trajectories and susceptibility to nicotine addiction in males and females.

Proteomics of Colorectal Cancer: Tumors, Organoids, and Cell Cultures-A Minireview

Proteomics, the study of the complete protein composition of a sample, is an important field for cancer research. Changes in the proteome can serve as a biomarker of cancer or lead to the development of a targeted therapy. This minireview will focus on mass spectrometry-based proteomics studies applied specifically to colorectal cancer, particularly the variety of cancer model systems used, including tumor samples, two-dimensional (2D) and three-dimensional (3D) cell cultures such as spheroids and organoids. A thorough discussion of the application of these systems will accompany the review of the literature, as each provides distinct advantages and disadvantages for colorectal cancer research. Finally, we provide conclusions and future perspectives for the application of these model systems to cancer research as a whole.

Phenanthrene-triggered tricarboxylic acid cycle response in wheat leaf

Tricarboxylic acid cycle (TCA cycle) is the most effective energy metabolism pathway in higher plants and animals. However, there is no information about its response in plants under environmental stress, especially under polycyclic aromatic hydrocarbons (PAHs) pollution. Here, this study is the first to discuss the intermediate and related enzyme changes in TCA cycle in plants. We applied high performance liquid chromatography (HPLC) and isobaric tags for relative and absolute quantitation (iTRAQ) proteomics to analyze the intermediate concentration and related protein response in wheat leaf cells, respectively. The concentrations of citrate and malate (0.37 and 0.57 mg kg^-1) in the treatment with 1.0 mg L^-1 phenanthrene were higher than those in the control, and the concentrations of the other five intermediates (i.e., α-ketoglutarate, fumarate, oxaloacetate, pyruvate and succinate) in the treatment were lower than those in the control. Three detected proteins (pyruvate dehydrogenase, dihydrolipoyllysine-residue succinyltransferase and fumarate hydratase) involved in TCA cycle were up-regulated when phenanthrene was accumulated in wheat leaf cells. Meanwhile, real-time PCR results of seven key TCA cycle enzymes genes further confirmed the aforementioned enzyme results. The gene expressions of ketoglutarate dehydrogenase, fumarase and pyruvate dehydrogenase were promoted when phenanthrene was accumulated, while the other four genes were suppressed. In general, pyruvate decrease is the key reason for TCA cycle inactivation under exposure to phenanthrene. Meanwhile, malate concentration increases significantly (P < 0.05), and all the three conversion enzymes turn active. Our results offer helpful information for understanding TCA cycle energy metabolism response to PAH exposure.

Butyrate decreases its own oxidation in colorectal cancer cells through inhibition of histone deacetylases

Colorectal cancer is characterized by an increase in the utilization of glucose and a diminishment in the oxidation of butyrate, which is a short chain fatty acid. In colorectal cancer cells, butyrate inhibits histone deacetylases to increase the expression of genes that slow the cell cycle and induce apoptosis. Understanding the mechanisms that contribute to the metabolic shift away from butyrate oxidation in cancer cells is important in in understanding the beneficial effects of the molecule toward colorectal cancer. Here, we demonstrate that butyrate decreased its own oxidation in cancerous colonocytes. Butyrate lowered the expression of short chain acyl-CoA dehydrogenase, an enzyme that mediates the oxidation of short-chain fatty acids. Butyrate does not alter short chain acyl-CoA dehydrogenase levels in non-cancerous colonocytes. Trichostatin A, a structurally unrelated inhibitor of histone deacetylases, and propionate also decreased the level of short chain acyl-CoA dehydrogenase, which alluded to inhibition of histone deacetylases as a part of the mechanism. Knockdown of histone deacetylase isoform 1, but not isoform 2 or 3, inhibited the ability of butyrate to decrease short chain acyl-CoA dehydrogenase expression. This work identifies a mechanism by which butyrate selective targets colorectal cancer cells to reduce its own metabolism.

Quantitative mass spectrometry analysis reveals a panel of nine proteins as diagnostic markers for colon adenocarcinomas

Adenocarcinomas are cancers originating from the gland forming cells of the colon and rectal lining, and are known to be the most common type of colorectal cancers. The current diagnosis strategies for colorectal cancers include biopsy, laboratory tests, and colonoscopy which are time consuming. Identification of protein biomarkers could aid in the detection of colon adenocarcinomas (CACs). In this study, tissue proteome of colon adenocarcinomas (n = 11) was compared with the matched control specimens (n = 11) using isobaric tags for relative and absolute quantitation (iTRAQ) based liquid chromatography-mass spectrometry (LC-MS/MS) approach. A list of 285 significantly altered proteins was identified in colon adenocarcinomas as compared to its matched controls, which are associated with growth and malignancy of the tumors. Protein interaction analysis revealed the association of altered proteins in colon adenocarcinomas with various transcription factors and their targets. A panel of nine proteins was validated using multiple reaction monitoring (MRM). Additionally, S100A9 was also validated using immunoblotting. The identified panel of proteins may serve as potential biomarkers and thereby aid in the detection of colon adenocarcinomas.

Chemical composition and the potential for proteomic transformation in cancer, hypoxia, and hyperosmotic stress

The changes of protein expression that are monitored in proteomic experiments are a type of biological transformation that also involves changes in chemical composition. Accompanying the myriad molecular-level interactions that underlie any proteomic transformation, there is an overall thermodynamic potential that is sensitive to microenvironmental conditions, including local oxidation and hydration potential. Here, up- and down-expressed proteins identified in 71 comparative proteomics studies were analyzed using the average oxidation state of carbon (Z_C) and water demand per residue (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O), calculated using elemental abundances and stoichiometric reactions to form proteins from basis species. Experimental lowering of oxygen availability (hypoxia) or water activity (hyperosmotic stress) generally results in decreased Z_C or \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O of up-expressed compared to down-expressed proteins. This correspondence of chemical composition with experimental conditions provides evidence for attraction of the proteomes to a low-energy state. An opposite compositional change, toward higher average oxidation or hydration state, is found for proteomic transformations in colorectal and pancreatic cancer, and in two experiments for adipose-derived stem cells. Calculations of chemical affinity were used to estimate the thermodynamic potentials for proteomic transformations as a function of fugacity of O₂ and activity of H₂O, which serve as scales of oxidation and hydration potential. Diagrams summarizing the relative potential for formation of up- and down-expressed proteins have predicted equipotential lines that cluster around particular values of oxygen fugacity and water activity for similar datasets. The changes in chemical composition of proteomes are likely linked with reactions among other cellular molecules. A redox balance calculation indicates that an increase in the lipid to protein ratio in cancer cells by 20% over hypoxic cells would generate a large enough electron sink for oxidation of the cancer proteomes. The datasets and computer code used here are made available in a new R package, canprot.

Proteomic indicators of oxidation and hydration state in colorectal cancer

New integrative approaches are needed to harness the potential of rapidly growing datasets of protein expression and microbial community composition in colorectal cancer. Chemical and thermodynamic models offer theoretical tools to describe populations of biomacromolecules and their relative potential for formation in different microenvironmental conditions. The average oxidation state of carbon (Z_C) can be calculated as an elemental ratio from the chemical formulas of proteins, and water demand per residue (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O) is computed by writing the overall formation reactions of proteins from basis species. Using results reported in proteomic studies of clinical samples, many datasets exhibit higher mean Z_C or \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O of proteins in carcinoma or adenoma compared to normal tissue. In contrast, average protein compositions in bacterial genomes often have lower Z_C for bacteria enriched in fecal samples from cancer patients compared to healthy donors. In thermodynamic calculations, the potential for formation of the cancer-related proteins is energetically favored by changes in the chemical activity of H₂O and fugacity of O₂ that reflect the compositional differences. The compositional analysis suggests that a systematic change in chemical composition is an essential feature of cancer proteomes, and the thermodynamic descriptions show that the observed proteomic transformations in host tissue could be promoted by relatively high microenvironmental oxidation and hydration states.

A proteomics-based approach identifies secreted protein acidic and rich in cysteine as a prognostic biomarker in malignant pleural mesothelioma

Background:

We aimed to identify prognostic blood biomarkers using proteomics-based approaches in malignant pleural mesothelioma (MPM).

Methods:

Plasma samples from 12 MPM patients were used for exploratory mass spectrometry and ELISA analyses. The significance of secreted protein acidic and rich in cysteine (SPARC) was examined in sera from a Dutch series (n=97). To determine the source of the circulating SPARC, we investigated SPARC expression in MPM tumours and healthy controls, as well as the expression and secretion from cell lines and xenografts.

Results:

Secreted protein acidic and rich in cysteine was identified as a putative prognostic marker in plasma. Validation in the Dutch series showed that the median survival was higher in patients with low SPARC compared with those with high SPARC (19.0 vs 8.8 months; P=0.01). In multivariate analyses, serum SPARC remained as an independent predictor (HR 1.55; P=0.05). In MPM tumour samples, SPARC was present in the tumour cells and stromal fibroblasts. Cellular SPARC expression was higher in 5 out of 7 cell lines compared with two immortalized mesothelial lines. Neither cell lines nor xenograft tumours secreted detectable SPARC.

Conclusions:

Low circulating SPARC was associated with favourable prognosis. Secreted protein acidic and rich in cysteine was present in both tumour cells and stromal fibroblasts; and our in vitro and in vivo experiments suggest that stromal fibroblasts are a potential source of circulating SPARC.

Mass spectrometry based translational proteomics for biomarker discovery and application in colorectal cancer

Colorectal cancer (CRC) is a leading cause of cancer-related death in the world. Clinically, early detection of the disease is the most effective approach to tackle this tough challenge. Discovery and development of reliable and effective diagnostic tools for the assessment of prognosis and prediction of response to drug therapy are urgently needed for personalized therapies and better treatment outcomes. Among many ongoing efforts in search for potential CRC biomarkers, MS-based translational proteomics provides a unique opportunity for the discovery and application of protein biomarkers toward better CRC early detection and treatment. This review updates most recent studies that use preclinical models and clinical materials for the identification of CRC-related protein markers. Some new advances in the development of CRC protein markers such as CRC stem cell related protein markers, SRM/MRM-MS and MS cytometry approaches are also discussed in order to address future directions and challenges from bench translational research to bedside clinical application of CRC biomarkers.

Glycomics expression analysis of sulfated glycosaminoglycans of human colorectal cancer tissues and non-neoplastic mucosa by electrospray ionization mass spectrometry

OBJECTIVE

To determine the presence of glycosaminoglycans in the extracellular matrix of connective tissue from neoplastic and non-neoplastic colorectal tissues, since it has a central role in tumor development and progression.

METHODS

Tissue samples from neoplastic and non-neoplastic colorectal tissues were obtained from 64 operated patients who had colorectal carcinoma with no distant metastases. Expressions of heparan sulphate, chondroitin sulphate, dermatan sulphate and their fragments were analyzed by electrospray ionization mass spectrometry, with the technique for extraction and quantification of glycosaminoglycans after proteolysis and electrophoresis. The statistical analysis included mean, standard deviation, and Student'st test.

RESULTS

The glycosaminoglycans extracted from colorectal tissue showed three electrophoretic bands in agarose gel. Electrospray ionization mass spectrometry showed characteristic disaccharide fragments from glycosaminoglycans, indicating their structural characterization in the tissues analyzed. Some peaks in the electrospray ionization mass spectrometry were not characterized as fragments of sugars, indicating the presence of fragments of the protein structure of proteoglycans generated during the glycosaminoglycan purification. The average amount of chondroitin and dermatan increased in the neoplastic tissue compared to normal tissue (p=0.01). On the other hand, the average amount of heparan decreased in the neoplastic tissue compared to normal tissue (p= 0.03).

CONCLUSION

The method allowed the determination of the glycosaminoglycans structural profile in colorectal tissue from neoplastic and non-neoplastic colorectal tissue. Neoplastic tissues showed greater amounts of chondroitin sulphate and dermatan sulphate compared to non-neoplastic tissues, while heparan sulphate was decreased in neoplastic tissues.

Detecting Significant Changes in Protein Abundance

We review and demonstrate how an empirical Bayes method, shrinking a protein's sample variance towards a pooled estimate, leads to far more powerful and stable inference to detect significant changes in protein abundance compared to ordinary t-tests. Using examples from isobaric mass labeled proteomic experiments we show how to analyze data from multiple experiments simultaneously, and discuss the effects of missing data on the inference. We also present easy to use open source software for normalization of mass spectrometry data and inference based on moderated test statistics.

Linking patient outcome to high throughput protein expression data identifies novel regulators of colorectal adenocarcinoma aggressiveness

A key question in cancer systems biology is how to use molecular data to predict the biological behavior of tumors from individual patients. While genomics data have been heavily used, protein signaling data are more directly connected to biological phenotype and might predict cancer phenotypes such as invasion, metastasis, and patient survival. In this study, we mined publicly available data for colorectal adenocarcinoma from the Cancer Genome Atlas and identified protein expression and signaling changes that are statistically associated with patient outcome. Our analysis identified a number of known and potentially new regulators of colorectal cancer. High levels of insulin growth factor binding protein 2 (IGFBP2) were associated with both recurrence and death, and this was validated by immunohistochemical staining of a tissue microarray for a secondary patient dataset. Interestingly, GATA binding protein 3 (GATA3) was the protein most frequently associated with death in our analysis, and GATA3 expression was significantly decreased in tumor samples from stage I-II deceased patients. Experimental studies using engineered colon cancer cell lines show that exogenous expression of GATA3 decreases three-dimensional colony growth and invasiveness of colon cancer cells but does not affect two-dimensional proliferation. These findings suggest that protein data are useful for biomarker discovery and identify GATA3 as a regulator of colorectal cancer  aggressiveness.

EPMA position paper in cancer: current overview and future perspectives

At present, a radical shift in cancer treatment is occurring in terms of predictive, preventive, and personalized medicine (PPPM). Individual patients will participate in more aspects of their healthcare. During the development of PPPM, many rapid, specific, and sensitive new methods for earlier detection of cancer will result in more efficient management of the patient and hence a better quality of life. Coordination of the various activities among different healthcare professionals in primary, secondary, and tertiary care requires well-defined competencies, implementation of training and educational programs, sharing of data, and harmonized guidelines. In this position paper, the current knowledge to understand cancer predisposition and risk factors, the cellular biology of cancer, predictive markers and treatment outcome, the improvement in technologies in screening and diagnosis, and provision of better drug development solutions are discussed in the context of a better implementation of personalized medicine. Recognition of the major risk factors for cancer initiation is the key for preventive strategies (EPMA J. 4(1):6, 2013). Of interest, cancer predisposing syndromes in particular the monogenic subtypes that lead to cancer progression are well defined and one should focus on implementation strategies to identify individuals at risk to allow preventive measures and early screening/diagnosis. Implementation of such measures is disturbed by improper use of the data, with breach of data protection as one of the risks to be heavily controlled. Population screening requires in depth cost-benefit analysis to justify healthcare costs, and the parameters screened should provide information that allow an actionable and deliverable solution, for better healthcare provision.

Comprehensive glycomics comparison between colon cancer cell cultures and tumours: implications for biomarker studies

Altered glycosylation is commonly observed in colorectal cancer. In vitro models are frequently used to study this cancer but little is known about the differences that may exist between these model cell systems and tumour tissue. We have compared the membrane protein glycosylation of five colorectal cancer cell lines (SW1116, SW480, SW620, SW837, LS174T) with epithelial cells from colorectal tumours using liquid chromatography tandem mass spectrometry. Remarkably, there were five abundant O-glycans in the tumour cells that were undetected in the low-mucin producing cell lines, although two were found in the mucinous LS174T cells. The O-glycans included the well-known glycan cancer marker, sialyl-Tn, which has been associated with mucins. Using qRT-PCR, sialyl-Tn expression was found to be associated with an increase in α2,6-sialyltransferase gene (ST6GALNAC1) and a decrease in core 1 synthase gene (C1GALT1) in LS174T cells. The expression of a subset of mucins (MUC2, MUC6, MUC5B) was also correlated with sialyl-Tn expression in LS174T cells. Overall, the membrane protein glycosylation of the model cell lines was found to differ from each other and from the epithelial cells of tumour tissue. These findings should be noted in the design of biomarker discovery experiments particularly when cell surface targets are being investigated.

BIOLOGICAL SIGNIFICANCE

The extent of protein glycosylation differences between in vitro cell lines and ex vivo tumours in colorectal cancer research is unknown. Our study expands current knowledge by characterising the membrane protein glycosylation profiles of five different colorectal cancer cell lines and of epithelial cells derived from resected colorectal cancer tumour tissue, using liquid chromatography tandem mass spectrometry. The detailed structural differences found in both N- and O-linked glycan structures on the membrane glycoproteins were determined and correlated with the mRNA expression of the relevant proteins in the cell lines. The glycosylation differences found between cultured cancer cell lines and epithelial cells from tumour tissue have important implications for glycan biomarker discovery.

The role of von Willebrand factor as a biomarker of tumor development in hepatitis B virus-associated human hepatocellular carcinoma: a quantitative proteomic based study

Chronic hepatitis B virus (HBV) infection is a major risk factor for hepatocellular carcinoma (HCC), the sixth most common cancer worldwide. To explore potential biomarkers for HCC, iTRAQ coupled with mass spectrometry was used to analyze proteins in plasma from individuals with HBV-associated HCC, nonmalignant cirrhosis, chronic hepatitis B, and healthy individuals. Twenty-one aberrantly expressed proteins were identified from HCC patients as compared with nontumor controls. Overexpression of von Willebrand factor (vWF) was confirmed by Western blotting, and immunohistochemical analysis from liver biopsies and ELISA from plasma samples revealed a correlation between vWF expression and HCC clinicopathologic staging. Furthermore, siRNA-induced vWF silencing reduced HBV replication by over two-fold via the interferon-signaling pathway and impaired the invasion and migration of HCC cells in vitro. These results indicate that vWF can serve as a biomarker, and perhaps an alternative target for therapeutic intervention of HCC progression and HBV viral infection.

BIOLOGICAL SIGNIFICANCE

We report comparative plasma proteome profiles of HBV-associated HCC and nonmalignant chronic liver diseases, including chronic hepatitis B and cirrhosis. The quantification of these datasets showed altered abundance of 21 proteins in HBV-related HCC and provides a reference point for future applied and basic research. In addition, we have demonstrated that the candidate protein vWF is involved in the pathogenesis of HBV infection and replication, and also associated with clinicopathologic staging of HCC patients with HBV infection. Overall these findings provide information on the mechanism of HCC development, which may assist in the development of novel cancer and HBV therapeutic drugs.

Sorbitol dehydrogenase overexpression and other aspects of dysregulated protein expression in human precancerous colorectal neoplasms: a quantitative proteomics study

Colorectal adenomas are cancer precursor lesions of the large bowel. A multitude of genomic and epigenomic changes have been documented in these preinvasive lesions, but their impact on the protein effectors of biological function has not been comprehensively explored. Using shotgun quantitative MS, we exhaustively investigated the proteome of 30 colorectal adenomas and paired samples of normal mucosa. Total protein extracts were prepared from these tissues (prospectively collected during colonoscopy) and from normal (HCEC) and cancerous (SW480, SW620, Caco2, HT29, CX1) colon epithelial cell lines. Peptides were labeled with isobaric tags (iTRAQ 8-plex), separated via OFFGEL electrophoresis, and analyzed by means of LC-MS/MS. Nonredundant protein families (4325 in tissues, 2017 in cell lines) were identified and quantified. Principal component analysis of the results clearly distinguished adenomas from normal mucosal samples and cancer cell lines from HCEC cells. Two hundred and twelve proteins displayed significant adenoma-related expression changes (q-value < 0.02, mean fold change versus normal mucosa ±1.4), which correlated (r = 0.74) with similar changes previously identified by our group at the transcriptome level. Fifty-one (∼25%) proteins displayed directionally similar expression changes in colorectal cancer cells (versus HCEC cells) and were therefore attributed to the epithelial component of adenomas. Although benign, adenomas already exhibited cancer-associated proteomic changes: 69 (91%) of the 76 protein up-regulations identified in these lesions have already been reported in cancers. One of the most striking changes involved sorbitol dehydrogenase, a key enzyme in the polyol pathway. Validation studies revealed dramatically increased sorbitol dehydrogenase concentrations and activity in adenomas and cancer cell lines, along with important changes in the expression of other enzymes in the same (AKR1B1) and related (KHK) pathways. Dysregulated polyol metabolism might represent a novel facet of metabolome remodeling associated with tumorigenesis.

Quantitative mass spectrometry for colorectal cancer proteomics

This review documents the uses of quantitative MS applied to colorectal cancer (CRC) proteomics for biomarker discovery and molecular pathway profiling. Investigators are adopting various labeling and label-free MS approaches to quantitate differential protein levels in cells, tumors, and plasma/serum. We comprehensively review recent uses of this technology to examine mouse models of CRC, CRC cell lines, their secretomes and subcellular fractions, CRC tumors, CRC patient plasma/serum, and stool samples. For biomarker discovery these approaches are uncovering proteins with potential diagnostic and prognostic utility, while in vitro cell culture experiments are characterizing proteomic and phosphoproteomic responses to disrupted signaling pathways due to mutations or to inhibition of drugable enzymes.

Proteome profiling of cancer-associated fibroblasts identifies novel proinflammatory signatures and prognostic markers for colorectal cancer

PURPOSE

Cancer-associated fibroblasts (CAF) are essential components of the stroma that play a critical role in cancer progression. This study aimed to identify novel CAFs markers that might contribute to the invasion and the prognosis of colorectal cancer.

EXPERIMENTAL DESIGN

The azoxymethane/dextran sodium sulfate mouse model of sporadic colon cancer represents an adequate source for the isolation of CAFs and normal fibroblasts. By using the explants technique, we purified CAFs and normal fibroblasts from colon tissues. Whole-cell extracts and supernatants were subjected to in-depth quantitative proteomic analysis by tandem mass spectrometry. Further validations of upregulated proteins in CAFs were carried out by chemokine microarray and immunohistochemical analyses of mouse and human tissues.

RESULTS

Using a fold-change of 1.4 or more, we found 132 and 125 differentially expressed proteins in whole-cell extracts and supernatants, respectively. We found CAFs-associated proinflammatory and desmoplastic signatures. The proinflammatory signature was composed of several cytokines. Among them, CCL2 and CCL8 caused an increase in migration and invasion of colorectal cancer KM12 cells. The desmoplastic signature was composed of 30 secreted proteins. In mouse and human samples, expression of LTBP2, CDH11, OLFML3, and, particularly, FSTL1 was significantly increased in the tumoral stroma, without significant expression in the cancer epithelial cells. The combination of CALU and CDH11 stromal expression showed a significant association with disease-free survival and poor prognosis.

CONCLUSION

We have identified LTBP2, CDH11, OLFML3, and FSTL1 as selective biomarkers of cancer stroma, and CALU and CDH11 as candidate stromal biomarkers of prognostic significance in colon cancer.

Label-free selected reaction monitoring enables multiplexed quantitation of S100 protein isoforms in cancer cells

In humans, the S100 protein family is composed of 21 highly related low molecular weight (∼10 kDa) proteins. These proteins are known to have diagnostic, prognostic, and predictive value in a variety of cancers, but their small size and high sequence homology present a challenging scenario for quantitative bioanalytical procedures. Here, we developed a multiplexed, label-free selected reaction monitoring (SRM) assay to specifically measure the S100 protein isoform family in cancer cells. Several normalization parameters associated with label-free SRM quantitation were investigated to derive a method with optimal precision. We detected 11 S100 isoforms across a panel of 9 colon and breast cancer cell lines. The quantitative potential of the S100 assays for biomarker discovery was demonstrated by studying the isogenic cell lines SW480 and SW620, a cellular model of colon cancer progression. Our findings were shown to be in agreement with previously published polysomal mRNA level quantitation for S100 genes in these cell lines. Comparison of the quantitation results using label-free SRM with those obtained using stable-isotope labeled peptide standards demonstrated reliability of the method. These data support the use of SRM to quantitate S100 protein isoforms as these are important players in a broad range of human diseases.

Multi-parameter systematic strategies for predictive, preventive and personalised medicine in cancer

Cancer is a complex disease that causes the alterations in the levels of gene, RNA, protein and metabolite. With the development of genomics, transcriptomics, proteomics and metabolomic techniques, the characterisation of key mutations and molecular pathways responsible for tumour progression has led to the identification of a large number of potential targets. The increasing understanding of molecular carcinogenesis has begun to change paradigms in oncology from traditional single-factor strategy to multi-parameter systematic strategy. The therapeutic model of cancer has changed from adopting the general radiotherapy and chemotherapy to personalised strategy. The development of predictive, preventive and personalised medicine (PPPM) will allow prediction of response with substantially increased accuracy, stratification of particular patient groups and eventual personalisation of medicine. The PPPM will change the approach to tumour diseases from a systematic and comprehensive point of view in the future. Patients will be treated according to the specific molecular profiles that are found in the individual tumour tissue and preferentially with targeted substances, if available.

Recent advances on multidimensional liquid chromatography-mass spectrometry for proteomics: from qualitative to quantitative analysis--a review

With the acceleration of proteome research, increasing attention has been paid to multidimensional liquid chromatography-mass spectrometry (MDLC-MS) due to its high peak capacity and separation efficiency. Recently, many efforts have been put to improve MDLC-based strategies including "top-down" and "bottom-up" to enable highly sensitive qualitative and quantitative analysis of proteins, as well as accelerate the whole analytical procedure. Integrated platforms with combination of sample pretreatment, multidimensional separations and identification were also developed to achieve high throughput and sensitive detection of proteomes, facilitating highly accurate and reproducible quantification. This review summarized the recent advances of such techniques and their applications in qualitative and quantitative analysis of proteomes.

An insight into iTRAQ: where do we stand now?

The iTRAQ (isobaric tags for relative and absolute quantification) technique is widely employed in proteomic workflows requiring relative quantification. Here, we review the iTRAQ literature; in particular, we focus on iTRAQ usage in relation to other commonly used quantitative techniques e.g. stable isotope labelling in culture (SILAC), label-free methods and selected reaction monitoring (SRM). As a result, we identify several issues arising with respect to iTRAQ. Perhaps frustratingly, iTRAQ's attractiveness has been undermined by a number of technical and analytical limitations: it may not be truly quantitative, as the changes in abundance reported will generally be underestimated. We discuss weaknesses and strengths of iTRAQ as a methodology for relative quantification in the light of this and other technical issues. We focus on technical developments targeted at iTRAQ accuracy and precision, use of 4-plex over 8-plex reagents and application of iTRAQ to post-translational modification (PTM) workflows. We also discuss iTRAQ in relation to label-free approaches, to which iTRAQ is losing ground.

Proteomics approaches in the identification of molecular signatures of mesenchymal stem cells

Mesenchymal stem cells (MSCs) are undifferentiated, multi-potent stem cells with the ability to renew. They can differentiate into many types of terminal cells, such as osteoblasts, chondrocytes, adipocytes, myocytes, and neurons. These cells have been applied in tissue engineering as the main cell type to regenerate new tissues. However, a number of issues remain concerning the use of MSCs, such as cell surface markers, the determining factors responsible for their differentiation to terminal cells, and the mechanisms whereby growth factors stimulate MSCs. In this chapter, we will discuss how proteomic techniques have contributed to our current knowledge and how they can be used to address issues currently facing MSC research. The application of proteomics has led to the identification of a special pattern of cell surface protein expression of MSCs. The technique has also contributed to the study of a regulatory network of MSC differentiation to terminal differentiated cells, including osteocytes, chondrocytes, adipocytes, neurons, cardiomyocytes, hepatocytes, and pancreatic islet cells. It has also helped elucidate mechanisms for growth factor-stimulated differentiation of MSCs. Proteomics can, however, not reveal the accurate role of a special pathway and must therefore be combined with other approaches for this purpose. A new generation of proteomic techniques have recently been developed, which will enable a more comprehensive study of MSCs.