Differential expression proteomics of human colon cancer

Iron Supplementation Increases Tumor Burden and Alters Protein Expression in a Mouse Model of Human Intestinal Cancer

Iron supplements are widely consumed. However, excess iron may accelerate intestinal tumorigenesis. To determine the effect of excess iron on intestinal tumor burden and protein expression changes between tumor and normal tissues, ApcMin/+ mice were fed control (adequate) and excess iron (45 and 450 mg iron/kg diet, respectively; n = 9/group) for 10 wk. Tumor burden was measured, and two-dimensional fluorescence difference gel electrophoresis was used to identify differentially expressed proteins in tumor and normal intestinal tissues. There was a significant increase (78.3%; p ≤ 0.05) in intestinal tumor burden (mm2/cm) with excess iron at wk 10. Of 980 analyzed protein spots, 69 differentially expressed (p ≤ 0.05) protein isoforms were identified, representing 55 genes. Of the isoforms, 56 differed (p ≤ 0.05) between tumor vs. normal tissues from the adequate iron group and 23 differed (p ≤ 0.05) between tumors from the adequate vs. excess iron. Differentially expressed proteins include those involved in cell integrity and adaptive response to reactive oxygen species (including, by gene ID: ANPEP, DPP7, ITGB1, PSMA1 HSPA5). Biochemical pathway analysis found that iron supplementation modulated four highly significant (p ≤ 0.05) functional networks. These findings enhance our understanding of interplay between dietary iron and intestinal tumorigenesis and may help develop more specific dietary guidelines regarding trace element intake.

Proteins Involved in Focal Cell Adhesion and Podosome Formation Are Differentially Expressed during Colorectal Tumorigenesis in AOM-Treated Rats

Colorectal tumorigenesis involves the development of aberrant crypt foci (ACF) or preneoplastic lesions, representing the earliest morphological lesion visible in colon cancer. The purpose of this study was to determine changes in protein expression in carcinogen-induced ACF as they mature and transform into adenomas. Protein expression profiles of azoxymethane (AOM)-induced F344 rat colon ACF and adenomas were compared at four time points, 4 (control), 8, 16, and 24 weeks post AOM administration (n = 9/group), with time points correlating with induction and transformation events. At each time point, micro-dissected ACF and/or adenoma tissues were analyzed across multiple quantitative two-dimensional (2D-DIGE) gels using a Cy-dye labeling technique and a pooled internal standard to quantify expression changes with statistical confidence. Western blot and subsequent network pathway mapping were used to confirm and elucidate differentially expressed (p ≤ 0.05) proteins, including changes in vinculin (Vcl; p = 0.007), scinderin (Scin; p = 0.02), and profilin (Pfn1; p = 0.01), By determining protein expression changes in ACF as they mature and transform into adenomas, a "baseline" of altered regulatory proteins associated with adenocarcinoma development in this model has been elucidated. These data will enable future studies aimed at biomarker identification and understanding the molecular biology of intestinal tumorigenesis and adenocarcinoma maturation under varying intestinal conditions.

Proteomic analysis of low- and high-grade human colon adenocarcinoma tissues and tissue-derived primary cell lines reveals unique biological functions of tumours and new protein biomarker candidates

Background

Colon cancer is the third most common cancer and second highest cause of cancer deaths worldwide. The aim of the study was to find new biomarkers for diagnosis, prognosis and therapeutic drug targets for this disease.

Methods

Four low-grade and four high-grade human colon adenocarcinoma tumours with patient-matched normal colon tissues were analysed. Additionally, tissue-derived primary cell lines were established from each tumour tissue. The cell lines were validated using DNA sequencing to confirm that they are a suitable in vitro model for colon adenocarcinoma based on conserved gene mutations. Label-free quantitation proteomics was performed to compare the proteomes of colon adenocarcinoma samples to normal colon samples, and of colon adenocarcinoma tissues to tissue-derived cell lines to find significantly differentially abundant proteins. The functions enriched within the differentially expressed proteins were assessed using STRING. Proteomics data was validated by Western blotting.

Results

A total of 4767 proteins were identified across all tissues, and 4711 across primary tissue-derived cell lines. Of these, 3302 proteins were detected in both the tissues and the cell lines. On average, primary cell lines shared about 70% of proteins with their parent tissue, and they retained mutations to key colon adenocarcinoma-related genes and did not diverge far genetically from their parent tissues. Colon adenocarcinoma tissues displayed upregulation of RNA processing, steroid biosynthesis and detoxification, and downregulation of cytoskeletal organisation and loss of normal muscle function. Tissue-derived cell lines exhibited increased interferon-gamma signalling and aberrant ferroptosis. Overall, 318 proteins were significantly up-regulated and 362 proteins significantly down-regulated by comparisons of high-grade with low-grade tumours and low-grade tumour with normal colon tissues from both sample types.

Conclusions

The differences exhibited between tissues and cell lines highlight the additional information that can be obtained from patient-derived primary cell lines. DNA sequencing and proteomics confirmed that these cell lines can be considered suitable in vitro models of the parent tumours. Various potential biomarkers for colon adenocarcinoma initiation and progression and drug targets were identified and discussed, including seven novel markers: ACSL4, ANK2, AMER3, EXOSC1, EXOSC6, GCLM, and TFRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-022-09364-y.

Metabolic phenotyping to monitor chronic enteritis canceration

INTRODUCTION

Colorectal cancer (CRC) remains an incurable disease. Previous metabolomic studies show that metabolic signatures in plasma distinguish CRC patients from healthy controls. Chronic enteritis (CE) represents a risk factor for CRC, with a 20 fold greater incidence than in healthy individuals. However, no studies have performed metabolomic profiling to investigate CRC biomarkers in CE.

OBJECTIVE

Our aims were to identify metabolomic signatures in CRC and CE and to search for blood-derived metabolite biomarkers distinguishing CRC from CE, especially early-stage biomarkers.

METHODS

In this case-control study, 612 subjects were prospectively recruited between May 2015 and May 2016, and including 539 CRC patients (stage I, 102 cases; stage II, 259 cases; stage III, 178 cases) and 73 CE patients. Untargeted metabolomics was performed to identify CRC-related metabolic signatures in CE.

RESULTS

Five pathways were significantly enriched based on 153 differential metabolites between CRC and CE. 16 biomarkers were identified for diagnosis of CRC from CE and for guiding CRC staging. The AUC value for CRC diagnosis in the external validation set was 0.85. Good diagnostic performances were also achieved for early-stage CRC (stage I and stage II), with an AUC value of 0.84. The biomarker panel could also stage CRC patients, with an AUC of 0.72 distinguishing stage I from stage II CRC and AUC of 0.74 distinguishing stage II from stage III CRC.

CONCLUSIONS

The identified metabolic biomarkers exhibit promising properties for CRC monitoring in CE patients and are superior to commonly used clinical biomarkers (CEA and CA19-9).

Protein Expression Profiling Identifies Key Proteins and Pathways Involved in Growth Inhibitory Effects Exerted by Guggulsterone in Human Colorectal Cancer Cells

Colorectal cancer (CRC) is a leading killer cancer worldwide and one of the most common malignancies with increasing incidences of mortality. Guggulsterone (GS) is a plant sterol used for treatment of various ailments such as obesity, hyperlipidemia, diabetes, and arthritis. In the current study, anti-cancer effects of GS in human colorectal cancer cell line HCT 116 was tested, potential targets identified using mass spectrometry-based label-free shotgun proteomics approach and key pathways validated by proteome profiler antibody arrays. Comprehensive proteomic profiling identified 14 proteins as significantly dysregulated. Proteins involved in cell proliferation/migration, tumorigenesis, cell growth, metabolism, and DNA replication were downregulated while the protein with functional role in exocytosis/tumor suppression was found to be upregulated. Our study evidenced that GS treatment altered expression of Bcl-2 mediated the mitochondrial release of cytochrome c which triggered the formation of apoptosome as well as activation of caspase-3/7 leading to death of HCT 116 cells via intrinsic apoptosis pathway. GS treatment also induced expression of p53 protein while p21 expression was unaltered with no cell cycle arrest. In addition, GS was found to inhibit NF-kB signaling in colon cancer cells by quelling the expression of its regulated gene products Bcl-2, cIAP-1, and survivin.

Metabolomics Analysis in Serum from Patients with Colorectal Polyp and Colorectal Cancer by 1H-NMR Spectrometry

Colorectal cancer (CRC) is one of the leading causes of cancer-related death worldwide. Colorectal adenomatous polyps are at high risk for the development of CRC. In this report, we described the metabolic changes in the sera from patients with colorectal polyps and CRC by using the NMR-based metabolomics. 110 serum samples were collected from patients and healthy controls, including 40 CRC patients, 32 colorectal polyp patients, and 38 healthy controls. The metabolic profiles and differential metabolites of sera were analyzed by multivariate statistical analysis (MSA), including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) methods. A total of 23 differential metabolites were identified from MSA. According to the pathway analysis and multivariate ROC curve-based exploratory analysis by using the relative concentrations of differential metabolites, we found abnormal metabolic pathways and potential biomarkers involved with the colorectal polyp and CRC. The results showed that the pyruvate metabolism and glycerolipid metabolism were activated in colorectal polyps. And the glycolysis and glycine, serine, and threonine metabolism were activated in CRC. The changed metabolism may promote cellular proliferation. In addition, we found that the rates of acetate/glycerol and lactate/citrate could be the potential biomarkers in colorectal polyp and CRC, respectively. The application of ¹H-NMR metabolomics analysis in serum has interesting potential as a new detection and diagnostic tool for early diagnosis of CRC.

Metabolomics for biomarker discovery in the diagnosis, prognosis, survival and recurrence of colorectal cancer: a systematic review

Colorectal cancer (CRC) remains an incurable disease. There are no effective noninvasive techniques that have achieved colorectal cancer (CRC) diagnosis, prognosis, survival and recurrence in clinic. To investigate colorectal cancer metabolism, we perform an electronic literature search, from 1998 to January 2016, for studies evaluating the metabolomic profile of patients with CRC regarding the diagnosis, recurrence, prognosis/survival, and systematically review the twenty-three literatures included. QUADOMICS tool was used to assess the quality of them. We highlighted the metabolism perturbations based on metabolites and pathway. Metabolites related to cellular respiration, carbohydrate, lipid, protein and nucleotide metabolism were significantly altered in CRC. Altered metabolites were also related to prognosis, survival and recurrence of CRC. This review could represent the most comprehensive information and summary about CRC metabolism to date. It certificates that metabolomics had great potential on both discovering clinical biomarkers and elucidating previously unknown mechanisms of CRC pathogenesis.

Proteomic analysis shows down-regulations of cytoplasmic carbonic anhydrases, CAI and CAII, are early events of colorectal carcinogenesis but are not correlated with lymph node metastasis

Aim

The aim of the study was to screen the markedly down-regulated proteins in colorectal cancer and analyze their relationship to carcinogenesis, cancer progression and pathological aspects.

Methods

Proteomic analysis was preformed on six fresh colorectal cancer tissues and paired normal colorectal mucosa by two-dimensional differential gel electrophoresis and matrix-assisted laser desorption/ionization-time of flight mass spectrometry. Two markedly down-regulated proteins among the proteins, of which the expressions were significantly decreased in colorectal cancer compared to normal mucosa, were confirmed by Western Blot in 12 colorectal cancers. Their relationship to carcinogenesis, cancer progression and pathological aspects of colorectal cancer were analyzed in 64 colorectal cancer and paired normal mucosa, 27 benign polyps, and 20 lymph node metastases by immunohistochemistry.

Results

Two-dimensional differential gel electrophoresis analysis showed there were 2 protein spots, of which the average abundances decreased 3.62 and 3.76 fold in colorectal cancer compared to normal mucosa, respectively. They were identified by matrix-assisted laser desorption/ionization-time of flight mass spectrometry as carbonic anhydrase I and II (CAI and CAII). Validation by Western Blot in 12 colorectal cancers showed there were significantly different expressions of CAI and CAII between colorectal cancer and normal mucosa (P = 0.002 and 0.027, respectively). Immunohistochemistry analysis indicated the expression of CAI and CAII was decreased from normal mucosa to benign polyps, and to colorectal cancer stepwise significantly (P <0.05). However, there were no differences in their expressions between lymph node metastasis and colorectal cancer (P >0.05). There were decreasing trends of CAI and CAII expressions from well to poor differentiation and from stage I or II to stage III or IV, but they were not statistically significant (P >0.05).

Conclusions

CAI and CAII are necessary enzymes of the colorectum for their normal function. Down-regulations of CAI and CAII are early events of colorectum carcinogenesis. They have no correlations with lymph node metastasis.

A plasma lipidomics strategy reveals perturbed lipid metabolic pathways and potential lipid biomarkers of human colorectal cancer

To explore underlying molecular mechanisms and identify novel lipid biomarkers promising for colorectal cancer (CRC) diagnosis, a continuous-flow two dimensional liquid chromatography-quadrupole time-of-flight mass spectrometry (2D LC-QToF/MS) method was employed to comprehensively measure lipid species in human plasma of CRC patients and healthy controls. With a total of 427 annotated lipid species, we identified 64 lipid species with corrected p value less than 0.05 and fold change more than 1.5. These significantly altered lipid species were mainly involved in glycerolipids and glycerophospholipids metabolism and sphingolipids metabolism. After the diagnosis ability evaluation based on the receiver operating characteristic (ROC) curve, phosphatidylglycerol (34:0), sphingomyelin (42:2), ceramide (44:5), lysophosphatidylcholine (18:3), lysophosphatidylcholine (18:2), phosphatidylethanolamine (O-36:3), phosphatidylethanolamine (O-38:3) and sphingomyelin (38:8) were finally proposed as the potential biomarkers with the area under the curve (AUC) more than 0.900. These results suggest that this 2D LC-QToF/MS-based lipidomics profiling has great potential as a noninvasive diagnostic method in detecting CRC and hopefully provide new clues to understand its underlying mechanism.

Identifying DCN and HSPD1 as Potential Biomarkers in Colon Cancer Using 2D-LC-MS/MS Combined with iTRAQ Technology

Colon cancer is one of the most common types of gastrointestinal cancers and the fourth cause of cancer death worldwide. To discover novel diagnostic biomarkers for colon cancer and investigate potential mechanisms of oncogenesis, quantitative proteomic approach using iTRAQ-tagging and 2D-LC-MS/MS was performed to characterize proteins alterations in colon cancer and non-neoplastic colonic mucosa (NNCM) using laser capture microdissection-harvested from the two types of tissues, respectively. As a result, 188 DEPs were identified, and the differential expression of two DEPs (DCN and HSPD1) was further verified by Western blotting and immunohistochemistry. KEGG pathway analysis disclosed that the DEPs were related to signaling pathways associated with cancer; furthermore, DCN and HSPD1 are in the relative central hub position among protein-protein interaction subnetwork of the DEPs. The results not only shed light on the mechanism by the DEPs contributed to colonic carcinogenesis, but also showed that DCN and HSPD1 are novel potential biomarkers for the diagnosis of colon cancer.

Thiamine Deficiency-Mediated Brain Mitochondrial Pathology in Alaskan Huskies with Mutation in SLC19A3.1

Alaskan Husky encephalopathy (AHE(1) ) is a fatal brain disease associated with a mutation in SLC19A3.1 (c.624insTTGC, c.625C>A). This gene encodes for a thiamine transporter 2 with a predominately (CNS) central nervous system distribution. Considering that brain is particularly vulnerable to thiamine deficiency because of its reliance on thiamine pyrophosphate (TPP)-dependent metabolic pathways involved in energy metabolism and neurotransmitter synthesis, we characterized the impact of this mutation on thiamine status, brain bioenergetics and the contribution of oxidative stress to this phenotype. In silico modeling of the mutated transporter indicated a significant loss of alpha-helices resulting in a more open protein structure suggesting an impaired thiamine transport ability. The cerebral cortex and thalamus of affected dogs were severely deficient in TPP-dependent enzymes accompanied by decreases in mitochondrial mass and oxidative phosphorylation (OXPHOS) capacity, and increases in oxidative stress. These results along with the behavioral and pathological findings indicate that the phenotype associated with AHE is consistent with a brain-specific thiamine deficiency, leading to brain mitochondrial dysfunction and increased oxidative stress. While some of the biochemical deficits, neurobehavior and affected brain areas in AHE were shared by Wernicke's and Korsakoff's syndromes, several differences were noted likely arising from a tissue-specific vs. that from a whole-body thiamine deficiency.

Altered tissue metabolites correlate with microbial dysbiosis in colorectal adenomas

Several studies have linked bacterial dysbiosis with elevated risk of colorectal adenomas and cancer. However, the functional implications of gut dysbiosis remain unclear. Gut bacteria contribute to nutrient metabolism and produce small molecules termed the “metabolome”, which may contribute to the development of neoplasia in the large bowel. We assessed the metabolome in normal rectal mucosal biopsies of 15 subjects with colorectal adenomas and 15 nonadenoma controls by liquid chromatography and gas chromatography time-of-flight mass spectrometry. Quantitative real-time PCR was used to measure abundances of specific bacterial taxa. We identified a total of 274 metabolites. Discriminant analysis suggested a separation of metabolomic profiles between adenoma cases and nonadenoma controls. Twenty-three metabolites contributed to the separation, notably an increase in adenoma cases of the inflammatory metabolite prostaglandin E2 and a decrease in antioxidant-related metabolites 5-oxoproline and diketogulonic acid. Pathway analysis suggested that differential metabolites were significantly related to cancer, inflammatory response, carbohydrate metabolism, and GI disease pathways. Abundances of six bacterial taxa assayed were increased in cases. The 23 differential metabolites demonstrated correlations with bacteria that were different between cases and controls. These findings suggest that metabolic products of bacteria may be responsible for the development of colorectal adenomas and CRC.

Metabolomic profiling in colorectal cancer: opportunities for personalized medicine

Colorectal cancer (CRC) is one of the most common types of cancer in the world, with high prevalence and mortality. Understanding the alterations of cancer metabolism and identifying reliable biomarkers would facilitate the development of novel technologies of CRC screening and early diagnosis, as well as new approaches to providing personalized medicine. Metabolomics, as an emerging molecular phenotyping approach, provides a clinical platform technology with an unprecedented amount of metabolic readout information, which is ideal for theranostic biomarker discovery. Metabolic signatures can link the unique pathophysiological states of patients to personalized health monitoring and intervention strategies. This article presents an overview of the metabolomic studies of CRC with a focus on recent advances in the biomarker discovery in serum, urine, fecal water and tissue samples for cancer diagnosis. The development and application of metabolomics towards personalized medicine, including early diagnosis, cancer staging, treatment and drug discovery are also discussed.

Immunogenic cell death and DAMPs in cancer therapy

Although it was thought that apoptotic cells, when rapidly phagocytosed, underwent a silent death that did not trigger an immune response, in recent years a new concept of immunogenic cell death (ICD) has emerged. The immunogenic characteristics of ICD are mainly mediated by damage-associated molecular patterns (DAMPs), which include surface-exposed calreticulin (CRT), secreted ATP and released high mobility group protein B1 (HMGB1). Most DAMPs can be recognized by pattern recognition receptors (PRRs). In this Review, we discuss the role of endoplasmic reticulum (ER) stress and reactive oxygen species (ROS) in regulating the immunogenicity of dying cancer cells and the effect of therapy-resistant cancer microevolution on ICD.

Improving colorectal cancer management: the potential of proteomics

Colorectal cancer (CRC) is the third most common cancer worldwide. Successful treatment is heavily dependent on tumor stage at the time of detection, but unfortunately CRC is often only detected in advanced stages. New biomarkers in the form of genes or proteins that can be used for diagnosis, prognostication, follow-up, and treatment selection and monitoring could be of great benefit for the management of CRC. Furthermore, proteins could prove valuable new targets for therapy. Therefore, clinical proteomics has gained a lot of scientific interest in this regard. To get an overall insight into the extent to which this research has contributed to a better management of CRC, we give a comprehensive overview of the results of proteomics research on CRC, focusing on expression proteomics, in other words, protein profiling studies. Furthermore, we evaluate the potential of the discriminating proteins identified in this research for clinical use as biomarkers for (early) diagnosis, prognosis and follow-up of CRC or as targets for new therapeutic regimens.

Cancer cell growth and survival as a system-level property sustained by enhanced glycolysis and mitochondrial metabolic remodeling

Systems Biology holds that complex cellular functions are generated as system-level properties endowed with robustness, each involving large networks of molecular determinants, generally identified by “omics” analyses. In this paper we describe four basic cancer cell properties that can easily be investigated in vitro: enhanced proliferation, evasion from apoptosis, genomic instability, and inability to undergo oncogene-induced senescence. Focusing our analysis on a K-ras dependent transformation system, we show that enhanced proliferation and evasion from apoptosis are closely linked, and present findings that indicate how a large metabolic remodeling sustains the enhanced growth ability. Network analysis of transcriptional profiling gives the first indication on this remodeling, further supported by biochemical investigations and metabolic flux analysis (MFA). Enhanced glycolysis, down-regulation of TCA cycle, decoupling of glucose and glutamine utilization, with increased reductive carboxylation of glutamine, so to yield a sustained production of growth building blocks and glutathione, are the hallmarks of enhanced proliferation. Low glucose availability specifically induces cell death in K-ras transformed cells, while PKA activation reverts this effect, possibly through at least two mitochondrial targets. The central role of mitochondria in determining the two investigated cancer cell properties is finally discussed. Taken together the findings reported herein indicate that a system-level property is sustained by a cascade of interconnected biochemical pathways that behave differently in normal and in transformed cells.

Murine colon proteome and characterization of the protein pathways

Background

Most of the current proteomic researches focus on proteome alteration due to pathological disorders (i.e.: colorectal cancer) rather than normal healthy state when mentioning colon. As a result, there are lacks of information regarding normal whole tissue- colon proteome.

Results

We report here a detailed murine (mouse) whole tissue- colon protein reference dataset composed of 1237 confident protein (FDR < 2) with comprehensive insight on its peptide properties, cellular and subcellular localization, functional network GO annotation analysis, and its relative abundances. The presented dataset includes wide spectra of pI and Mw ranged from 3–12 and 4–600 KDa, respectively. Gravy index scoring predicted 19.5% membranous and 80.5% globularly located proteins. GO hierarchies and functional network analysis illustrated proteins function together with their relevance and implication of several candidates in malignancy such as Mitogen- activated protein kinase (Mapk8, 9) in colorectal cancer, Fibroblast growth factor receptor (Fgfr 2), Glutathione S-transferase (Gstp1) in prostate cancer, and Cell division control protein (Cdc42), Ras-related protein (Rac1,2) in pancreatic cancer. Protein abundances calculated with 3 different algorithms (NSAF, PAF and emPAI) provide a relative quantification under normal condition as guidance.

Conclusions

This highly confidence colon proteome catalogue will not only serve as a useful reference for further experiments characterizing differentially expressed proteins induced from diseased conditions, but also will aid in better understanding the ontology and functional absorptive mechanism of the colon as well.

Searching for consistently reported up- and down-regulated biomarkers in colorectal cancer: a systematic review of proteomic studies

The cumulative lifetime risk for the development of colorectal cancer in the general population is 6 %. In many cases, early detection by fecal occult blood test is limited regarding sensitivity. Therefore, there is an urgent need for improved diagnostic tests in colorectal cancer. The recent development of high-throughput molecular analytic techniques should allow the rapid evaluation of new diagnostic markers. However, researchers are faced with an overwhelming number of potential markers form numerous colorectal cancer protein expression profiling studies. To address the challenge, we have carried out a comprehensive systematic review of colorectal cancer biomarkers from 13 published studies that compared the protein expression profiles of colorectal cancer and normal tissues. A protein ranking system that considers the number of comparisons in agreement, total sample sizes, average fold-change and direction of differential expression was devised. We observed that some proteins were consistently reported by multiple studies as differentially expressed with a statistically significant frequency (P < 0.05) in cancer versus normal tissues comparison. Our systematic review method identified proteins that were consistently reported as differentially expressed. A review of the top four candidates revealed proteins described previously as having diagnostic value as well as novel candidate biomarkers. These candidates should help to develop a panel of biomarkers with sufficient sensitivity and specificity for the diagnosis of colorectal cancer in a clinical setting.

Identification and verification of heat shock protein 60 as a potential serum marker for colorectal cancer

Colorectal cancer (CRC) is a major public health issue worldwide, and novel tumor markers may contribute to its efficient management by helping in early detection, prognosis or surveillance of disease. The aim of our study was to identify new serum biomarkers for CRC, and we followed a phased biomarker discovery and validation process to obtain an accurate preliminary assessment of potential clinical utility. We compared colonic tumors and matched normal tissue from 15 CRC patients, using two-dimensional difference gel electrophoresis (2D-DIGE), and identified 17 proteins that had significant differential expression. These results were further confirmed by western blotting for heat shock protein (HSP) 60, glutathione-S-transferase Pi, α-enolase, T-complex protein 1 subunit β, and leukocyte elastase inhibitor, and by immunohistochemistry for HSP60. Using mAbs raised against HSP60, we developed a reliable (precision of 5-15%) and sensitive (0.3 ng·mL(-1)) immunoassay for the detection of HSP60 in serum. Elevated levels of HSP60 were found in serum from CRC patients in two independent cohorts; the receiver-operating characteristic curve obtained in 112 patients with CRC and 90 healthy controls had an area under the curve (AUC) of 0.70, which was identical to the AUC of carcinoembryonic antigen. Combination of serum markers improved clinical performance: the AUC of a three-marker logistic regression model combining HSP60, carcinoembryonic antigen and carbohydrate antigen 19-9 reached 0.77. Serum HSP60 appeared to be more specific for late-stage CRC; therefore, future studies should evaluate its utility for determining prognosis or monitoring therapy rather than early detection.

Heat-shock protein 27 (Hsp27) as a target of methylglyoxal in gastrointestinal cancer

The molecular mechanisms underlying the posttranslational modification of proteins in gastrointestinal cancer are still unknown. Here, we investigated the role of methylglyoxal modifications in gastrointestinal tumors. Methylglyoxal is a reactive dicarbonyl compound produced from cellular glycolytic intermediates that reacts non-enzymatically with proteins. By using a monoclonal antibody to methylglyoxal-modified proteins, we found that murine heat-shock protein 25 and human heat-shock protein 27 were the major adducted proteins in rat gastric carcinoma mucosal cell line and human colon cancer cell line, respectively. Furthermore, we found that heat-shock protein 27 was modified by methylglyoxal in ascending colon and rectum of patients with cancer. However, methylglyoxal-modified heat-shock protein 25/heat-shock protein 27 was not detected in non cancerous cell lines or in normal subject. Matrix-associated laser desorption/ionization mass spectrometry/mass spectrometry analysis of peptide fragments identified Arg-75, Arg-79, Arg-89, Arg-94, Arg-127, Arg-136, Arg-140, Arg-188, and Lys-123 as methylglyoxal modification sites in heat-shock protein 27 and in phosphorylated heat-shock protein 27. The transfer of methylglyoxal-modified heat-shock protein 27 into rat intestinal epithelial cell line RIE was even more effective in preventing apoptotic cell death than that of native control heat-shock protein 27. Furthermore, methylglyoxal modification of heat-shock protein 27 protected the cells against both the hydrogen peroxide- and cytochrome c-mediated caspase activation, and the hydrogen peroxide-induced production of intracellular reactive oxygen species. The levels of lactate converted from methylglyoxal were increased in carcinoma mucosal cell lines. Our results suggest that posttranslational modification of heat-shock protein 27 by methylglyoxal may have important implications for epithelial cell injury in gastrointestinal cancer.

Identification of biomarkers for colorectal cancer through proteomics-based approaches

The early detection of colorectal cancer is one of the great challenges in the battle against this disease. However, owing to its heterogeneous character, single markers are not likely to provide sufficient diagnostic power to be used in colorectal cancer population screens. This review provides an overview of recent studies aimed at the discovery of new diagnostic protein markers through proteomics-based approaches. It indicates that studies that start with the proteomic analysis of tumor tissue or tumor cell lines (near the source) have a high potential to yield novel and colorectal cancer-specific biomarkers. In the next step, the diagnostic accuracy of these candidate markers can be assessed by a targeted ELISA assay using serum from colorectal cancer patients and healthy controls. Instead, direct proteomic analysis of serum yields predominantly secondary markers composed of fragments of abundant serum proteins that may be associated with tumor-associated protease activity, and alternatively, immunoproteomic analysis of the serum antibody repertoire provides a valuable tool to identify the molecular imprint of colorectal cancer-associated antigens directly from patient serum samples. The latter approach also allows a relatively easy translation into targeted assays. Eventually, multimarker assays should be developed to reach a diagnostic accuracy that meets the stringent criteria for colorectal cancer screening at the population level.

Cell surface markers in colorectal cancer prognosis

The classification of colorectal cancers (CRC) is currently based largely on histologically determined tumour characteristics, such as differentiation status and tumour stage, i.e., depth of tumour invasion, involvement of regional lymph nodes and the occurrence of metastatic spread to other organs. These are the conventional prognostic factors for patient survival and often determine the requirement for adjuvant therapy after surgical resection of the primary tumour. However, patients with the same CRC stage can have very different disease-related outcomes. For some, surgical removal of early-stage tumours leads to full recovery, while for others, disease recurrence and metastasis may occur regardless of adjuvant therapy. It is therefore important to understand the molecular processes that lead to disease progression and metastasis and to find more reliable prognostic markers and novel targets for therapy. This review focuses on cell surface proteins that correlate with tumour progression, metastasis and patient outcome, and discusses some of the challenges in finding prognostic protein markers in CRC.

Linking obesity to colorectal cancer: application of nutrigenomics

Diet is one of the most affective environmental factors in cancer development. Due to complicated nature of the diet, it has been very difficult to provide clear explanations for the role of dietary components in carcinogenesis. However, as high-throughput omics techniques became available, researchers are now able to analyze large sets of gene transcripts, proteins, and metabolites to identify molecules involved in disease development. Bioinformatics uses these data to perform network analyses and suggest possible interactions between metabolic processes and environmental factors. Obesity is known as one of the most closely related risk factors of colorectal cancer (CRC). Metabolic disturbances due to a positive energy balance may trigger and accelerate CRC development. In this review, we have summarized reports on genes, proteins and metabolites that are related to either obesity or CRC, and suggested candidate molecules linking obesity and CRC based on currently available literature. Possible application of bioinformatics for a large scale network analysis in studying cause-effect relationship between dietary components and CRC are suggested.

Hypoxia-induced metabolic shifts in cancer cells: moving beyond the Warburg effect

Hypoxia has been recognized to play a role in promoting the invasive and metastatic behaviour of cancer cells. Largely via the transcription factor, hypoxia-induced factor 1, hypoxia exerts significant effects on cellular metabolism, with numerous downstream consequences. Energetically there is a significant shift away from oxidative phosphorylation in mitochondria towards glycolysis, a state also involved in the 'Warburg effect'. The proteins involved in mediating the altered metabolic pathways seen in tumour cells thus represent new targets for potential therapeutic intervention. Hypoxia has been associated with the development of aggressive phenotypes in cancer cells, and can be accompanied by changes in carbohydrate and lipid metabolism that impact tumour cell proliferation, adhesion, and angiogenesis. Herein, we examine glycolytic and other less investigated metabolic pathways in relation to cancer and hypoxia, with a focus on emerging tools for large-scale metabolite profiling ('metabolomics'). Metabolomic technologies permit the measurement of a wide range of metabolites in an untargeted manner, however, to date, this technology has been relatively under utilized for studying cellular responses to hypoxia. We detail some of the common experimental approaches employed in metabolomics experiments, including nuclear magnetic resonance and new mass spectrometry-based methods of analysis. Selected examples of the application of these technologies to the study of metabolic alterations brought about by hypoxia are provided, particularly as they relate to energy, carbohydrate, and lipid metabolism. Finally, the potential for therapeutic targeting of metabolic processes activated by hypoxia is presented.

Heat shock protein 27: a potential biomarker for colorectal carcinoma

AIM: To find specific biomarkers for colorectal carcinoma using a proteomic method to provide clues to early diagnosis, prognosis and therapy of colorectal carcinoma as well as to understanding the molecular mechanisms governing cancer progression.

METHODS: Six colorectal carcinoma patients were included in the study. High-resolution two-dimensional gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) were utilized for the identification of proteins differentially expressed between cancer and adjacent non-cancerous tissue. The differential expression of heat shock protein 27 (HSP27) was further verified by Western blot and immunohistochemistry.

RESULTS: Comparative analysis of 2-DE maps revealed 42 differentially expressed proteins between the two groups. Ten differential proteins were further identified by mass spectrometry, including HSP27, disulfide isomerase (DI), heterogeneous nuclear ribonucleoprotein A2/B1 (HnRNP A2/B1), triosephosphate isomerase (TIM), pyruvate kinase, etc. Western blot and immunohistochemistry analyses confirmed the overexpression of HSP27 in colorectal carcinoma. These results indicate that HSP27 may be a potential biomarker for colorectal cancer.

CONCLUSION: Many differential proteins are identified between cancer and adjacent non-cancerous tissue in patients with colorectal carcinoma. HSP27 might be a potential biomarker for early diagnosis, therapy and prognosis of colorectal carcinoma.

Reduced levels of hydroxylated, polyunsaturated ultra long-chain fatty acids in the serum of colorectal cancer patients: implications for early screening and detection

BACKGROUND

There are currently no accurate serum markers for detecting early risk of colorectal cancer (CRC). We therefore developed a non-targeted metabolomics technology to analyse the serum of pre-treatment CRC patients in order to discover putative metabolic markers associated with CRC. Using tandem-mass spectrometry (MS/MS) high throughput MS technology we evaluated the utility of selected markers and this technology for discriminating between CRC and healthy subjects.

METHODS

Biomarker discovery was performed using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). Comprehensive metabolic profiles of CRC patients and controls from three independent populations from different continents (USA and Japan; total n = 222) were obtained and the best inter-study biomarkers determined. The structural characterization of these and related markers was performed using liquid chromatography (LC) MS/MS and nuclear magnetic resonance technologies. Clinical utility evaluations were performed using a targeted high-throughput triple-quadrupole multiple reaction monitoring (TQ-MRM) method for three biomarkers in two further independent populations from the USA and Japan (total n = 220).

RESULTS

Comprehensive metabolomic analyses revealed significantly reduced levels of 28-36 carbon-containing hydroxylated polyunsaturated ultra long-chain fatty-acids in all three independent cohorts of CRC patient samples relative to controls. Structure elucidation studies on the C28 molecules revealed two families harbouring specifically two or three hydroxyl substitutions and varying degrees of unsaturation. The TQ-MRM method successfully validated the FTICR-MS results in two further independent studies. In total, biomarkers in five independent populations across two continental regions were evaluated (three populations by FTICR-MS and two by TQ-MRM). The resultant receiver-operator characteristic curve AUCs ranged from 0.85 to 0.98 (average = 0.91 +/- 0.04).

CONCLUSIONS

A novel comprehensive metabolomics technology was used to identify a systemic metabolic dysregulation comprising previously unknown hydroxylated polyunsaturated ultra-long chain fatty acid metabolites in CRC patients. These metabolites are easily measurable in serum and a decrease in their concentration appears to be highly sensitive and specific for the presence of CRC, regardless of ethnic or geographic background. The measurement of these metabolites may represent an additional tool for the early detection and screening of CRC.

An integrative -omics approach to identify functional sub-networks in human colorectal cancer

Emerging evidence indicates that gene products implicated in human cancers often cluster together in “hot spots” in protein-protein interaction (PPI) networks. Additionally, small sub-networks within PPI networks that demonstrate synergistic differential expression with respect to tumorigenic phenotypes were recently shown to be more accurate classifiers of disease progression when compared to single targets identified by traditional approaches. However, many of these studies rely exclusively on mRNA expression data, a useful but limited measure of cellular activity. Proteomic profiling experiments provide information at the post-translational level, yet they generally screen only a limited fraction of the proteome. Here, we demonstrate that integration of these complementary data sources with a “proteomics-first” approach can enhance the discovery of candidate sub-networks in cancer that are well-suited for mechanistic validation in disease. We propose that small changes in the mRNA expression of multiple genes in the neighborhood of a protein-hub can be synergistically associated with significant changes in the activity of that protein and its network neighbors. Further, we hypothesize that proteomic targets with significant fold change between phenotype and control may be used to “seed” a search for small PPI sub-networks that are functionally associated with these targets. To test this hypothesis, we select proteomic targets having significant expression changes in human colorectal cancer (CRC) from two independent 2-D gel-based screens. Then, we use random walk based models of network crosstalk and develop novel reference models to identify sub-networks that are statistically significant in terms of their functional association with these proteomic targets. Subsequently, using an information-theoretic measure, we evaluate synergistic changes in the activity of identified sub-networks based on genome-wide screens of mRNA expression in CRC. Cross-classification experiments to predict disease class show excellent performance using only a few sub-networks, underwriting the strength of the proposed approach in discovering relevant and reproducible sub-networks.

Intensive research on cancer has led to an understanding of many individual genes that may be important for the initiation and progression of tumors. However, since cancer is a progressive disease that results from accumulation of multiple mutations likely acting in concert, individual markers can only provide limited insights into cellular mechanisms that underlie tumorigenesis. For this reason, recent studies focus on identification of “sub-network markers”, that is, functionally associated genes that exhibit coordinate changes in molecular expression during cancer progression. However, expression of genes is most frequently interrogated at the mRNA level, which captures functional activity of genes only to a limited extent. Screening of protein expression, on the other hand, provides information on the abundance of functional gene products, but its scale is often limited compared to screening of mRNA expression. In this article, we develop a proteomics-driven computational method that searches for sub-network markers in human colorectal cancer, based on a seed of differentially expressed proteins identified by proteomic screening. Our results show that significant changes in the expression of these proteins is likely to be associated with coordinate changes in the expression of the genes whose products are functionally associated with these proteins. This analysis leads to novel insights in the synergistic processes that underlie tumorigenesis.

Application of proteomics in colorectal cancer research

Colorectal cancer is one of the most common malignant tumors in China. Its morbidity and mortality are increasing year by year. The emergence of proteomics has pushed colorectal cancer research forward. In this article, we will review the application of proteomics in the study of the diagnosis, pathogenesis and treatment of colorectal cancer.

Identification of HSP27 as a potential tumor marker for colorectal cancer by the two-dimensional polyacrylamide gel electrophoresis

The identification of specific biomarkers for colorectal cancer would provide the basis for early diagnosis, prognosis, therapy, as well as clues for understanding the molecular mechanisms governing cancer progression. This study was designed to use comparative proteomics technology to find the differentially expressed proteins between human colorectal carcinoma and the corresponding normal tumor-adjacent colorectal tissues. We have used the highly sensitive two-dimensional gel electrophoresis (2-DE) coupled with matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) for the identification of proteins differentially expressed in tumoral and neighboring normal mucosa. We have detected differences in abundance of 42 proteins with statistical variance of the tumor versus normal spot volume ratio within the 95th confidence level (Student's t-test; P < 0.05). 10 out of 42 analyzed proteins were unambiguously identified by MS coupled with database interrogation as being differentially expressed in colorectal cancer. Of the 10 newly implicated proteins, HSP27 was chosen for detailed analysis. Preliminary studies demonstrated that the differentially expressed proteins found by 2-DE could be confirmed and validated by western blotting and immunohistochemistry analyses in those few cases. The results suggest that HSP27 might be a potential biomarker for early diagnosis, prognosis, monitoring in the therapy of colorectal carcinoma.

Approaches to biomarkers in human colorectal cancer: looking back, to go forward

Like all human cancers, colorectal cancer is a complicated disease. While a mature body of research involving colorectal cancer has implicated the putative sequence of genetic alterations that trigger the disease and sustain its progression, there is a surprising paucity of well-validated, clinically useful diagnostic markers of this disease. For prognosis or guiding therapy, single gene-based markers of colorectal cancer often have limited specificity and sensitivity. Genome-wide analyses (microarrays) have been used to propose candidate patterns of gene expression that are prognostic of outcome or predict the tumor's response to a therapy regimen; however, these patterns frequently do not overlap, and this has raised questions concerning their use as biomarkers. The limitation of gene-expression approaches to marker discovery occurs because the change in mRNA expression across tumors is highly variable and, alone, accounts for a limited variability of the phenotype, such as with cancer. More robust and accurate markers of cancer will result from integrating all the information we have about the cell: genomics, proteomics and interactomics. This article will discuss traditional markers in colorectal cancer, both genomic and proteomic, including their respective approaches and limitations, then conclude with examples of systems biology-based approaches for candidate marker discovery, and discuss how this approach is reshaping our view of a biomarker.

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].

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.

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.

Proteomic expression analysis of surgical human colorectal cancer tissues: up-regulation of PSB7, PRDX1, and SRP9 and hypoxic adaptation in cancer

Colorectal adenocarcinoma is one of the worldwide leading causes of cancer deaths. Discovery of specific biomarkers for early detection of cancer progression and the identification of underlying pathogenetic mechanisms are important tasks. Global proteomic approaches have thus far been limited by the large dynamic range of molecule concentrations in tissues and the lack of selective enrichment of the low-abundance proteome. We studied paired cancerous and normal clinical tissue specimens from patients with colorectal adenocarcinomas by heparin affinity fractionation enrichment (HAFE) followed by 2-D PAGE and tandem mass spectrometric (MS/MS) identification. Fifty-six proteins were found to be differentially expressed, of which 32 low-abundance proteins were only detectable after heparin affinity enrichment. MS/MS was used to identify 5 selected differentially expressed proteins as proteasome subunit beta type 7 (PSB7), hemoglobin alpha subunit (HBA), peroxiredoxin-1 (PRDX1), argininosuccinate synthase (ASSY), and signal recognition particle 9 kDa protein (SRP9). This is the first proteomic study detecting the differential expression of these proteins in human colorectal cancer tissue. Several of the proteins are functionally related to tissue hypoxia and hypoxic adaptation. The relative specificities of PSB7, PRDX1, and SRP9 overexpression in colon cancer were investigated by Western blot analysis of patients with colon adenocarcinomas and comparison with a control cohort of patients with lung adenocarcinomas. Furthermore, immunohistochemistry on tissue sections was used to define the specific locations of PSB7, PRDX1, and SRP9 up-regulation within heterogeneous primary human tumor tissue. Overexpression of the three proteins was restricted to the neoplastic cancer cell population within the tumors, demonstrating both cytoplasmic and nuclear localization of PSB7 and predominantly cytoplasmic localization of PRDX1 and SRP9. In summary, we describe heparin affinity fractionation enrichment (HAFE) as a prefractionation tool for the study of the human primary tissue proteome and the discovery of PSB7, PRDX1, and SRP9 up-regulation as candidate biomarkers of colon cancer.

Profiling of mitochondrial associated proteins from rat colon

Mitochondrial dysfunction, damage and mutations of mitochondrial proteins give rise to a range of ill understood patterns of disease. Although there is significant general knowledge of the proteins and the functional processes of the mitochondria, there is little knowledge of difference about how mitochondria respond and how they are regulated in different organs and tissues. Proteomic profiling of mitochondria and associated proteins involved in mitochondrial regulation and trafficking within cells and tissues has the potential to provide insights into mitochondrial dysfunction associated with many human diseases. The rat colon mitoproteome analysis presented here provides a useful tool to assist in identification and interpretation of mitochondrial dysfunction implicated in colon pathogenesis. 2DPAGE followed by LC/MS/MS was used to identify 430 proteins from mitochondrial enriched fractions prepared from rat colon, resulting in 195 different proteins or approximately 50% of the resolved proteins being identified as multiple protein expression forms. Proteins associated with the colon mitoproteome were involved in calcium binding, cell cycle, energy metabolism and electron transport chain, protein folding, protein synthesis and degradation, redox regulation, structural proteins, signalling and transporter and channel proteins. The mitochondrial associated proteins identified in this study of colon tissue complement and are compared with other recently published mitoproteome analyses from other organ tissues, and will assist in revealing potentially organ specific roles of the mitochondria and organ specific disease associated with mitochondrial dysfunction.

Differential expression of mimecan and thioredoxin domain-containing protein 5 in colorectal adenoma and cancer: a proteomic study

Adenoma is the major precursor lesion of colorectal cancer, one of the most common cancers worldwide. The elucidation of the molecular mechanism underlying adenoma is essential for early detection, prevention, and intervention of colorectal cancer. Using a combination of two-dimensional gel electrophoresis and mass spectrometry, we identified 27 differentially expressed proteins in adenoma, compared with matched normal mucosa and cancer tissue. Seventeen proteins were upregulated and six downregulated in adenoma when compared with the same proteins in individual-matched normal mucosa. Four were downregulated, but none upregulated in adenoma when compared with the same proteins in matched cancer tissue. Two novel proteins, mimecan and thioredoxin domain-containing protein 5 (TXNDC5), were further validated by Western blot in 8 colorectal adenomas and 19 cancers that were matched with normal mucosa. All adenoma and cancer tissues did not express mimecan, but all normal mucosa did (P < 0.01). In contrast, TXNDC5 was significantly upregulated in colorectal adenoma and cancer tissues as compared with that in normal mucosa (P < 0.05). This study clearly demonstrated that absence of mimecan and upregulation of TXNDC5 are involved in the early development of colorectal cancer. Thus, the differentially expressed proteins might serve as potential biomarkers for colorectal cancer detection and intervention.

Hepatocellular carcinoma: epidemiology and clinical aspects

Liver cancer is one of the most frequent solid cancers that kills more than 650,000 people around the world each year. Though great improvements have been done in last 10 years on the understanding the molecular mechanisms involved in liver oncogenesis, the prognosis of patients affected by liver cancer is still poor for most of them. Even in those where a relatively early diagnosis is done, the course of the disease is often fatal due to the underlying liver cirrhosis. In this review authors report the most recent findings on the pathogenesis of liver cancer and on therapeutic approaches, included those emerging from the most recent literature.

Proteome informatics for cancer research: from molecules to clinic

Proteomics offers the most direct approach to understand disease and its molecular biomarkers. Biomarkers denote the biological states of tissues, cells, or body fluids that are useful for disease detection and classification. Clinical proteomics is used for early disease detection, molecular diagnosis of disease, identification and formulation of therapies, and disease monitoring and prognostics. Bioinformatics tools are essential for converting raw proteomics data into knowledge and subsequently into useful applications. These tools are used for the collection, processing, analysis, and interpretation of the vast amounts of proteomics data. Management, analysis, and interpretation of large quantities of raw and processed data require a combination of various informatics technologies such as databases, sequence comparison, predictive models, and statistical tools. We have demonstrated the utility of bioinformatics in clinical proteomics through the analysis of the cancer antigen survivin and its suitability as a target for cancer immunotherapy.

A controversial tumor marker: is SM22 a proper biomarker for gastric cancer cells?

SM22, a dominant protein in smooth muscle cells (SMCs), has been widely reported to be abnormally expressed in many solid tumors. However, the expression patterns of SM22 are not consistent in all tumors, not even in the same ones. Whether SM22 should be considered a tumor biomarker is still debated in different laboratories. Herein, we have carried out a systematical investigation to validate SM22 expression in the primary tissues of gastric cancer (GC). Of eight cases, seven samples were found in the elevated expression of SM22 proteins through proteomic analysis. The observation was further verified by the approaches of Western blotting and quantitative RT-PCR. Surprisingly, the results achieved from tissue microarray in 126 GC cases appeared contrary to the proteomic conclusion, in which the highly expressed SM22 was mainly found in smooth muscle layers, blood vessels, and myofibroblasts. This suggested that the increased abundance of SM22 in the cancerous regions was not caused by the presence of the GC cells. Furthermore, the expression of SM22 was measured in different GC cell lines and SMCs with Western blotting and quantitative RT-PCR. The results revealed that SM22 expression in SMCs was dramatically higher than that of the GC cells, which indicates that SM22 is unlikely to be a proper biomarker for GC. Instead, it can be considered a potential indicator for the abnormal developments of smooth muscles, blood vessels, or myofibroblasts triggered by tumorigenesis.

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.

Vascular-derived artemin: a determinant of vascular sympathetic innervation?

Vascular sympathetic innervation is an important determinant of blood pressure and blood flow. The mechanisms that determine vascular sympathetic innervation are not well understood. The present study tests the hypothesis that vascular-derived artemin promotes the development of sympathetic innervation to blood vessels by promoting sympathetic axon growth. RT-PCR and Western analyses indicate that artemin is expressed by cultured vascular smooth muscle and arteries, and artemin coreceptors, glial cell-derived neurotrophic factor family receptor alpha3 and ret, are expressed by postganglionic sympathetic neurons. The effects of artemin on axon growth were assessed on explants of neonatal rat sympathetic ganglia. In the presence, but not in the absence, of nerve growth factor, exogenous artemin stimulated neurite growth. Femoral arteries (FA) from adult rats contain artemin, and these arteries stimulated sympathetic neurite growth. Growth in the presence of FA was 92.2 +/- 11.9 mm, and that in the absence of FA was 26.3 +/- 5.4 mm (P < 0.05). FA stimulation of axon growth was reduced by an antibody that neutralized the activity of artemin (P < 0.05). These data indicate that artemin is expressed in arteries, and its receptors are expressed and functional in the postganglionic sympathetic neurons that innervate them. This suggests that artemin may be a determinant of vascular sympathetic innervation.

Building the power house: recent advances in mitochondrial studies through proteomics and systems biology

The emerging field of systems biology seeks to develop novel approaches to integrate heterogeneous data sources for effective analysis of complex living systems. Systemic studies of mitochondria have generated a large number of proteomic data sets in numerous species, including yeast, plant, mouse, rat, and human. Beyond component identification, mitochondrial proteomics is recognized as a powerful tool for diagnosing and characterizing complex diseases associated with these organelles. Various proteomic techniques for isolation and purification of proteins have been developed; each tailored to preserve protein properties relevant to study of a particular disease type. Examples of such techniques include immunocapture, which minimizes loss of posttranslational modification, 4-iodobutyltriphenylphosphonium labeling, which quantifies protein redox states, and surface-enhanced laser desorption ionization-time-of-flight mass spectrometry, which allows sequence-specific binding. With the rapidly increasing number of discovered molecular components, computational models are also being developed to facilitate the organization and analysis of such data. Computational models of mitochondria have been accomplished with top-down and bottom-up approaches and have been steadily improved in size and scope. Results from top-down methods tend to be more qualitative but are unbiased by prior knowledge about the system. Bottom-up methods often require the incorporation of a large amount of existing data but provide more rigorous and quantitative information, which can be used as hypotheses for subsequent experimental studies. Successes and limitations of the studies reviewed here provide opportunities and challenges that must be addressed to facilitate the application of systems biology to larger systems.