Proteomic Analysis of Colorectal Cancer Reveals Alterations in Metabolic Pathways

Alterations in fatty acid utilization and an impaired antioxidant defense mechanism are early events in podocyte injury: a proteomic analysis

Ultrastructural alterations of podocytes are closely associated with loss of glomerular filtration function. In the present study, we explored changes at the proteome level that paralleled the disturbances of podocyte architecture in the early stages of puromycin aminonucleoside (PA) nephrosis in vivo. Using two-dimensional fluorescence difference gel electrophoresis and vacuum matrix-assisted laser desorption/ionization mass spectrometry combined with postsource decay fragment ion analysis and high-energy collision-induced dissociation tandem mass spectrometry, 23 differentially expressed protein spots, corresponding to 16 glomerular proteins that are involved in various cellular functions, were unambiguously identified, and a subset was corroborated by Western blot analysis. The majority of these proteins were primarily related to fatty acid metabolism and redox regulation. Key enzymes of the mitochondrial beta-oxidation pathway and antioxidant enzymes were consistently down-regulated in PA nephrosis. These changes were paralleled by increased expression levels of CD36. PA treatment of murine podocytes in culture resembled these specific protein changes in vitro. In this cell system, the modulatory effects of albumin-bound fatty acids on the expression levels of Mn-superoxide dismutase in response to PA were demonstrated as well. Taken together, these results indicate that a disrupted fatty acid metabolism in concert with an impaired antioxidant defense mechanism in podocytes may play a role in the early stages of PA-induced lesions in podocytes.

Metabolic profiling of human colorectal cancer using high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy and gas chromatography mass spectrometry (GC/MS)

Current clinical strategy for staging and prognostication of colorectal cancer (CRC) relies mainly upon the TNM or Duke system. This clinicopathological stage is a crude prognostic guide because it reflects in part the delay in diagnosis in the case of an advanced cancer and gives little insight into the biological characteristics of the tumor. We hypothesized that global metabolic profiling (metabonomics/metabolomics) of colon mucosae would define metabolic signatures that not only discriminate malignant from normal mucosae, but also could distinguish the anatomical and clinicopathological characteristics of CRC. We applied both high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) and gas chromatography mass spectrometry (GC/MS) to analyze metabolites in biopsied colorectal tumors and their matched normal mucosae obtained from 31 CRC patients. Orthogonal partial least-squares discriminant analysis (OPLS-DA) models generated from metabolic profiles obtained by both analytical approaches could robustly discriminate normal from malignant samples (Q(2) > 0.50, Receiver Operator Characteristic (ROC) AUC >0.95, using 7-fold cross validation). A total of 31 marker metabolites were identified using the two analytical platforms. The majority of these metabolites were associated with expected metabolic perturbations in CRC including elevated tissue hypoxia, glycolysis, nucleotide biosynthesis, lipid metabolism, inflammation and steroid metabolism. OPLS-DA models showed that the metabolite profiles obtained via HR-MAS NMR could further differentiate colon from rectal cancers (Q(2)> 0.60, ROC AUC = 1.00, using 7-fold cross validation). These data suggest that metabolic profiling of CRC mucosae could provide new phenotypic biomarkers for CRC management.

Development and validation of a gas chromatography/mass spectrometry method for the metabolic profiling of human colon tissue

In this study, a gas chromatography/mass spectrometry (GC/MS) method was developed and validated for the metabolic profiling of human colon tissue. Each colon tissue sample (20 mg) was ultra-sonicated with 1 mL of a mixture of chloroform/methanol/water in the ratio of 20:50:20 (v/v/v), followed by centrifugation, collection of supernatant, drying, removal of moisture using anhydrous toluene and finally derivatization using N-methyl-N-trifluoroacetamide (MSTFA) with 1% trimethylchlorosilane (TMCS). A volume of 1 microL of the derivatized mixture was injected into the GC/MS system. A total of 53 endogenous metabolites were separated and identified in the GC/MS chromatogram, all of which were selected to evaluate the sample stability and precision of the method. Of the identified endogenous metabolites 19 belonging to diverse chemical classes and covering a wide range of the GC retention times (Rt) were selected to investigate the quantitative linearity of the method. The developed GC/MS method demonstrated good reproducibility with intra- and inter-day precision within relative standard deviation (RSD) of +/-15%. The metabolic profiles of the intact tissue were determined to be stable (100 +/- 15%) for up to 90 days at -80 degrees C. Satisfactory results were also obtained in the case of other stability-indicating studies such as freeze/thaw cycle stability, bench-top stability and autosampler stability. The developed method showed a good linear response for each of the 19 analytes tested (r(2) > 0.99). Our GC/MS metabolic profiling method was successfully applied to discriminate biopsied colorectal cancer (CRC) tissue from their matched normal tissue obtained from six CRC patients using orthogonal partial least-squares discriminant analysis [two latent variables, R(2)Y = 0.977 and Q(2) (cumulative) = 0.877].

Identification of new accessible tumor antigens in human colon cancer by ex vivo protein biotinylation and comparative mass spectrometry analysis

One of the most promising new strategies for the development of efficacious cancer therapies relies on the targeted delivery of biopharmaceutical to the tumor environment by the use of selective and specific antibodies. The identification of accessible perivascular proteins selectively overexpressed in cancer tissue may facilitate the development of antibody-based biopharmaceutical administration. This approach is potentially highly selective and specific, combining the presence of tumor biomarkers readily accessible from the blood vessels and the high rate of angiogenesis characteristic of cancer tissues. We performed ex vivo perfusions of surgically resected human colon cancer using a reactive ester derivative of biotin, thus achieving a selective covalent modification of accessible proteins in vascular structures and stroma. After extraction and purification, biotinylated proteins were digested and the resulting peptides submitted to a comparative mass spectrometry-based proteomic analysis, revealing quantitative differences between normal and cancer colon. Sixty-seven of the total 367 proteins identified were found to be preferentially expressed at the tumor site. We generated human monoclonal antibodies against 2 potential tumor targets, NGAL and GW112, and we proved their selective expression in cancer colon and not or barely in healthy tissues. This article presents the first proteomic analysis of human colorectal cancer structures readily accessible from the tumor vasculature, revealing the overexpression of novel tumor antigens which may serve as selective targets for antibody-based imaging and therapeutic biomolecular strategies.

Discovery and scoring of protein interaction subnetworks discriminative of late stage human colon cancer

We used a systems biology approach to identify and score protein interaction subnetworks whose activity patterns are discriminative of late stage human colorectal cancer (CRC) versus control in colonic tissue. We conducted two gel-based proteomics experiments to identify significantly changing proteins between normal and late stage tumor tissues obtained from an adequately sized cohort of human patients. A total of 67 proteins identified by these experiments was used to seed a search for protein-protein interaction subnetworks. A scoring scheme based on mutual information, calculated using gene expression data as a proxy for subnetwork activity, was developed to score the targets in the subnetworks. Based on this scoring, the subnetwork was pruned to identify the specific protein combinations that were significantly discriminative of late stage cancer versus control. These combinations could not be discovered using only proteomics data or by merely clustering the gene expression data. We then analyzed the resultant pruned subnetwork for biological relevance to human CRC. A number of the proteins in these smaller subnetworks have been associated with the progression (CSNK2A2, PLK1, and IGFBP3) or metastatic potential (PDGFRB) of CRC. Others have been recently identified as potential markers of CRC (IFITM1), and the role of others is largely unknown in this disease (CCT3, CCT5, CCT7, and GNA12). The functional interactions represented by these signatures provide new experimental hypotheses that merit follow-on validation for biological significance in this disease. Overall the method outlines a quantitative approach for integrating proteomics data, gene expression data, and the wealth of accumulated legacy experimental data to discover significant protein subnetworks specific to disease.

Glucose avidity of carcinomas

The cancer cell phenotype has been summarized in six hallmarks [D. Hanahan, R.A. Weinberg, The hallmarks of cancer, Cell 100 (1) (2000) 57-70]. Following the conceptual trait established in that review towards the comprehension of cancer, herein we summarize the basis of an underlying principle that is fulfilled by cancer cells and tumors: its avidity for glucose. Our purpose is to push forward that the metabolic reprogramming that operates in the cancer cell represents a seventh hallmark of the phenotype that offers a vast array of possibilities for the future treatment of the disease. We summarize the metabolic pathways that extract matter and energy from glucose, paying special attention to the concerted regulation of these pathways by the ATP mass-action ratio. The molecular and functional evidences that support the high glucose uptake and the "abnormal" aerobic glycolysis of the carcinomas are detailed discussing also the role that some oncogenes and tumor suppressors have in these pathways. We overview past and present evidences that sustain that mitochondria of the cancer cell are impaired, supporting the original Warburg's formulation that ascribed the high glucose uptake of cancer cells to a defective mitochondria. A simple proteomic approach designed to assess the metabolic phenotype of cancer, i.e., its bioenergetic signature, molecularly and functionally supports Warburg's hypothesis. Furthermore, we discuss the clinical utility that the bioenergetic signature might provide. Glycolysis is presented as the "selfish" pathway used for cellular proliferation, providing both the metabolic precursors and the energy required for biosynthetic purposes, in the context of a plethora of substrates. The glucose avidity of carcinomas is thus presented as the result of both the installment of glycolysis for cellular proliferation and of the impairment of mitochondrial activity in the cancer cell. At the end, the repression of mitochondrial activity affords the cancer cell with a cell-death resistant phenotype making them prone to malignant growth.

Causes and consequences of increased glucose metabolism of cancers

In this review we examine the mechanisms (causes) underlying the increased glucose consumption observed in tumors within a teleological context (consequences). In other words, we will ask not only "How do cancers have high glycolysis?" but also, "Why?" We believe that the insights gained from answering the latter question support the conclusion that elevated glucose consumption is a necessary component of carcinogenesis. Specifically we propose that glycolysis is elevated because it produces acid, which provides an evolutionary advantage to cancer cells vis-à-vis normal parenchyma into which they invade.

Expression of chloride intracellular channel protein 1 (CLIC1) and tumor protein D52 (TPD52) as potential biomarkers for colorectal cancer

OBJECTIVES

Unequivocal biomarkers are needed to predict susceptibility and progression of colorectal cancer.

DESIGN AND METHODS

Paired samples of tumor and normal tissue from six patients with colorectal cancer of different localization, pTNM stage and grade were employed in the present study. MS analysis was used to identify differentially regulated proteins after 2-DE separation and densitometric analysis.

RESULTS

Densitometric analysis revealed differential abundance of 55 spots in tumor as compared to normal tissues. Thirty nine out of 55 spots were unambiguously identified by MS representing 32 different proteins. CLIC1, TPD52 and FABPL were consistently overexpressed (>3-fold, P<0.05) in all tumor tissue samples, while TPM1, TPM2, TPM3, TAGL and MLRN were consistently down-regulated (>3-fold, P<0.05) compared to normal tissue.

CONCLUSIONS

CLIC1 and TPD52 were significantly (P<0.05) up-regulated in all cases of colorectal cancer investigated, irrespective of localization, pTNM stage and grade of colon cancer highlighting their potential to serve as new biomarkers.

ORF018R, a highly abundant virion protein from Singapore grouper iridovirus, is involved in serine/threonine phosphorylation and virion assembly

Iridovirus is an important pathogen causing serious diseases among wild, cultured and ornamental fish. Previous studies have shown that Singapore grouper iridovirus (SGIV) contains 162 open reading frames (ORFs) from which 51 viral proteins have been confirmed by proteomics studies. ORF018R, which is conserved among vertebrate iridoviruses, is an abundant virion protein identified from SGIV. Here, immunofluorescence staining showed that ORF018R occurred at high abundance throughout SGIV-infected cells. The function of ORF018R was explored using antisense morpholino oligonucleotides (asMOs). Knockdown of ORF018R expression resulted in a reduction in the expression of viral late genes, distortion of viral particle assembly and inhibition of SGIV infection in grouper embryonic cells. Western blotting with phosphoserine-specific antibody indicated that serine phosphorylation was significantly enhanced for proteins of molecular masss 17-32 kDa by SDS-PAGE when ORF018R expression was eliminated. These proteins were analysed further by two-dimensional gel electrophoresis, and numerous protein spots were found to shift to a lower pI and higher molecular mass as a result of the loss of ORF018R function. Five proteins with enhanced phosphorylation were identified by matrix-assisted laser desorption/ionization time-of-flight (TOF)-TOF mass spectrometry, including three viral proteins: ORF049L (dUTPase), ORF075R and ORF086R, and two host proteins: subunit 12 of eukaryotic translation factor 3 and natural killer enhancing factor. These findings suggest that ORF018R is involved in serine/threonine phosphorylation in SGIV-infected late-stage cells and plays an important role in expression of viral late genes and virion assembly.

Comparison of DIGE and post-stained gel electrophoresis with both traditional and SameSpots analysis for quantitative proteomics

2-DE is an important tool in quantitative proteomics. Here, we compare the deep purple (DP) system with DIGE using both a traditional and the SameSpots approach to gel analysis. Missing values in the traditional approach were found to be a significant issue for both systems. SameSpots attempts to address the missing value problem. SameSpots was found to increase the proportion of low volume data for DP but not for DIGE. For all the analysis methods applied in this study, the assumptions of parametric tests were met. Analysis of the same images gave significantly lower noise with SameSpots (over traditional) for DP, but no difference for DIGE. We propose that SameSpots gave lower noise with DP due to the stabilisation of the spot area by the common spot outline, but this was not seen with DIGE due to the co-detection process which stabilises the area selected. For studies where measurement of small abundance changes is required, a cost-benefit analysis highlights that DIGE was significantly cheaper regardless of the analysis methods. For studies analysing large changes, DP with SameSpots could be an effective alternative to DIGE but this will be dependent on the biological noise of the system under investigation.

Identification of collapsin response mediator protein-2 as a potential marker of colorectal carcinoma by comparative analysis of cancer cell secretomes

The cancer cell secretome may contain many potentially useful biomarkers. We therefore sought to identify proteins in the conditioned media of colorectal carcinoma (CRC) cell lines but not in those from other cancer cell lines. The secretomes of 21 cancer cell lines derived from 12 cancer types were analyzed by SDS-PAGE combined with MALDI-TOF MS. Among the 325 proteins identified, collapsin response mediator protein-2 (CRMP-2) was chosen for evaluation as a potential CRC biomarker, since it was selectively detected in the CRC cell line secretome and has never been reported as a cancer biomarker. Immunohistochemical analysis of 169 CRC specimens showed that CRMP-2 was positively detected in 58.6% of the tumors, but weakly or not detected in >90% of the adjacent nontumor epithelial cells. Moreover, the CRMP-2-positive rate was significantly increased in earlier stage tumors and lymph node metastasis. Plasma CRMP-2 levels were significantly higher in CRC patients (N = 201) versus healthy controls (N = 201) (61.3 +/- 34.6 vs. 40.2 +/- 24.3 ng/mL, p = 0.001). Our results indicate that comparative analysis of cancer cell secretome is a feasible strategy for identifying potential cancer biomarkers, and that CRMP-2 may be a novel CRC biomarker.

Mechanisms of hormone carcinogenesis: evolution of views, role of mitochondria

CumuIative and excessive exposure to estrogens is associated with increased breast cancer risk. The traditional mechanism explaining this association is that estrogens affect the rate of cell division and apoptosis and thus manifest their effect on the risk of breast cancer by affecting the growth of breast epithelial tissues. Highly proliferative cells are susceptible to genetic errors during DNA replication. The action of estrogen metabolites offers a complementary genotoxic pathway mediated by the generation of reactive estrogen quinone metabolites that can form adducts with DNA and generate reactive oxygen species through redox cycling. In this chapter, we discussed a novel mitochondrial pathway mediated by estrogens and their cognate estrogen receptors (ERs) and its potential implications in estrogen-dependent carcinogenesis. Several lines of evidence are presented to show: (1) mitochondrial localization of ERs in human breast cancer cells and other cell types; (2) a functional role for the mitochondrial ERs in regulation of the mitochondrial respiratory chain (MRC) proteins and (3) potential implications of the mitochondrial ER-mediated pathway in stimulation of cell proliferation, inhibition of apoptosis and oxidative damage to mitochondrial DNA. The possible involvement of estrogens and ERs in deregulation of mitochondrial bioenergetics, an important hallmark of cancer cells, is also described. An evolutionary view is presented to suggest that persistent stimulation by estrogens through ER signaling pathways of MRC proteins and energy metabolic pathways leads to the alterations in mitochondrial bioenergetics and contributes to the development of estrogen-related cancers.

Gene expression profiles in zebrafish (Danio rerio) liver cells exposed to a mixture of pharmaceuticals at environmentally relevant concentrations

The effects of a mixture of pharmaceuticals at environmentally relevant concentrations were studied on growth and transcriptional regulation in zebrafish liver (ZFL) cells. The mixture of 13 ingredients was assembled to mimic the association and low concentration (ng/l) of drugs as detected in the environment, and decidedly inhibited ZFL cells proliferation in vitro over a 72 h exposure time. Using an oligonucleotide DNA-microarray targeting 14,000 zebrafish transcripts, we profiled gene expression in ZFL cells treated with ecologically relevant levels of the drug mixture. Compared to unexposed controls, ZFL cells challenged with pharmaceuticals were characterised by transcriptional repression involving primary metabolism and regulation of the cell cycle. On the other hand, we observed upregulation of genes identifying protein kinase signalling pathways and DNA-repair mechanisms. Part of the identified transcripts could be associated with general toxicity, while others were possibly linked to the effects of specific pharmaceuticals. Drugs also caused overexpression of oestrogen receptor beta and the oestrogen responsive protein GREB1. The context drawn by our data highlights a similarity in the response to the drug mixture in fish and previously employed human cells, and further prioritise studies targeting the potential risks associated with the presence of pharmaceuticals in the environment.

Design and Analysis Issues in Quantitative Proteomics Studies

Quantitative proteomics is the comparison of distinct proteomes which enables the identification of protein species which exhibit changes in expression or post-translational state in response to a given stimulus. Many different quantitative techniques are being utilized and generate large datasets. Independent of the technique used, these large datasets need robust data analysis to ensure valid conclusions are drawn from such studies. Approaches to address the problems that arise with large datasets are discussed to give insight into the types of statistical analyses of data appropriate for the various experimental strategies that can be employed by quantitative proteomic studies. This review also highlights the importance of employing a robust experimental design and highlights various issues surrounding the design of experiments. The concepts and examples discussed within will show how robust design and analysis will lead to confident results that will ensure quantitative proteomics delivers.

White spot syndrome virus proteins and differentially expressed host proteins identified in shrimp epithelium by shotgun proteomics and cleavable isotope-coded affinity tag

Shrimp subcuticular epithelial cells are the initial and major targets of white spot syndrome virus (WSSV) infection. Proteomic studies of WSSV-infected subcuticular epithelium of Penaeus monodon were performed through two approaches, namely, subcellular fractionation coupled with shotgun proteomics to identify viral and host proteins and a quantitative time course proteomic analysis using cleavable isotope-coded affinity tags (cICATs) to identify differentially expressed cellular proteins. Peptides were analyzed by offline coupling of two-dimensional liquid chromatography with matrix-assisted laser desorption ionization-tandem time of flight mass spectrometry. We identified 27, 20, and 4 WSSV proteins from cytosolic, nuclear, and membrane fractions, respectively. Twenty-eight unique WSSV proteins with high confidence (total ion confidence interval percentage [CI%], >95%) were observed, 11 of which are reported here for the first time, and 3 of these novel proteins were shown to be viral nonstructural proteins by Western blotting analysis. A first shrimp protein data set containing 1,999 peptides (ion score, > or =20) and 429 proteins (total ion score CI%, >95%) was constructed via shotgun proteomics. We also identified 10 down-regulated proteins and 2 up-regulated proteins from the shrimp epithelial lysate via cICAT analysis. This is the first comprehensive study of WSSV-infected epithelia by proteomics. The 11 novel viral proteins represent the latest addition to our knowledge of the WSSV proteome. Three proteomic data sets consisting of WSSV proteins, epithelial cellular proteins, and differentially expressed cellular proteins generated in the course of WSSV infection provide a new resource for further study of WSSV-shrimp interactions.

Quantitative proteomics for identification of cancer biomarkers

Quantitative proteomics can be used for the identification of cancer biomarkers that could be used for early detection, serve as therapeutic targets, or monitor response to treatment. Several quantitative proteomics tools are currently available to study differential expression of proteins in samples ranging from cancer cell lines to tissues to body fluids. 2-DE, which was classically used for proteomic profiling, has been coupled to fluorescence labeling for differential proteomics. Isotope labeling methods such as stable isotope labeling with amino acids in cell culture (SILAC), isotope-coded affinity tagging (ICAT), isobaric tags for relative and absolute quantitation (iTRAQ), and (18) O labeling have all been used in quantitative approaches for identification of cancer biomarkers. In addition, heavy isotope labeled peptides can be used to obtain absolute quantitative data. Most recently, label-free methods for quantitative proteomics, which have the potential of replacing isotope-labeling strategies, are becoming popular. Other emerging technologies such as protein microarrays have the potential for providing additional opportunities for biomarker identification. This review highlights commonly used methods for quantitative proteomic analysis and their advantages and limitations for cancer biomarker analysis.

Contribution of oncoproteomics to cancer biomarker discovery

Oncoproteomics is the study of proteins and their interactions in a cancer cell by proteomic technologies. Proteomic research first came to the fore with the introduction of two-dimensional gel electrophoresis. At the turn of the century, proteomics has been increasingly applied to cancer research with the wide-spread introduction of mass spectrometry and proteinchip. There is an intense interest in applying proteomics to foster an improved understanding of cancer pathogenesis, develop new tumor biomarkers for diagnosis, and early detection using proteomic portrait of samples. Oncoproteomics has the potential to revolutionize clinical practice, including cancer diagnosis and screening based on proteomic platforms as a complement to histopathology, individualized selection of therapeutic combinations that target the entire cancer-specific protein network, real-time assessment of therapeutic efficacy and toxicity, and rational modulation of therapy based on changes in the cancer protein network associated with prognosis and drug resistance. Besides, oncoproteomics is also applied to the discovery of new therapeutic targets and to the study of drug effects. In pace with the successful completion of the Human Genome Project, the wave of proteomics has raised the curtain on the postgenome era. The study of oncoproteomics provides mankind with a better understanding of neoplasia. In this article, the discovery of cancer biomarkers in recent years is reviewed. The challenges ahead and perspectives of oncoproteomics for biomarkers development are also addressed. With a wealth of information that can be applied to a broad spectrum of biomarker research projects, this review serves as a reference for biomarker researchers, scientists working in proteomics and bioinformatics, oncologists, pharmaceutical scientists, biochemists, biologists, and chemists.