Methods and biomarkers for early detection, prediction, and diagnosis of colorectal cancer

Colorectal cancer (CRC) is one of the most common digestive diseases worldwide. It has steadily ascended to the top three cancers in terms of incidence and mortality. The primary cause is the inability to diagnose it at an early stage. Therefore, early detection and diagnosis are essential for colorectal cancer prevention. Although there are now various methods for CRC early detection, in addition to recent developments in surgical and multimodal therapy, the poor prognosis and late detection of CRC still remain significant. Thus, it is important to investigate novel technologies and biomarkers to improve the sensitization and specification of CRC diagnosis. Here, we present some common methods and biomarkers for early detection and diagnosis of CRC, we hope this review will encourage the adoption of screening programs and the clinical use of these potential molecules as biomarkers for CRC early detection and prognosis.

Butyrate Alters Pyruvate Flux and Induces Lipid Accumulation in Cultured Colonocytes

Butyrate is considered the primary energy source of colonocytes and has received wide attention due to its unique health benefits. Insight into the mechanistic effects of butyrate on cellular and metabolic function relies mainly on research in in-vitro-cultured cells. However, cells in culture differ from those in vivo in terms of metabolic phenotype and nutrient availability. For translation, it is therefore important to understand the impact of different nutrients on the effects of butyrate. We investigated the metabolic consequences of butyrate exposure under various culturing conditions, with a focus on the interaction between butyrate and glucose. To investigate whether the effects of butyrate were different between cells with high and low mitochondrial capacity, we cultured HT29 cells under either low- (0.5 mM) or high- (25 mM) glucose conditions. Low-glucose culturing increased the mitochondrial capacity of HT29 cells compared to high-glucose (25 mM) cultured HT29 cells. Long-term exposure to butyrate did not alter mitochondrial bioenergetics, but it decreased glycolytic function, regardless of glucose availability. In addition, both high- and low-glucose-grown HT29 cells showed increased lipid droplet accumulation following long-term butyrate exposure. Acute exposure of cultured cells (HT29 and Caco-2) to butyrate increased their oxygen consumption rate (OCR). A simultaneous decrease in extracellular acidification rate (ECAR) was observed. Furthermore, in the absence of glucose, OCR did not increase in response to butyrate. These results lead us to believe that butyrate itself was not responsible for the observed increase in OCR, but, instead, butyrate stimulated pyruvate flux into mitochondria. Indeed, blocking of the mitochondrial pyruvate carrier prevented a butyrate-induced increase in oxygen consumption. Taken together, our results indicate that butyrate itself is not oxidized in cultured cells but instead alters pyruvate flux and induces lipid accumulation.

Butyrate enhances the efficacy of radiotherapy via FOXO3A in colorectal cancer patient‑derived organoids

Enhancing the radioresponsiveness of colorectal cancer (CRC) is essential for local control and prognosis. However, consequent damage to surrounding healthy cells can lead to treatment failure. We hypothesized that short‑chain fatty acids (SCFAs) could act as radiosensitizers for cancer cells, allowing the administration of a lower and safer dose of radiation. To test this hypothesis, the responses of three‑dimensional‑cultured organoids, derived from CRC patients, to radiotherapy, as well as the effects of combined radiotherapy with the SCFAs butyrate, propionate and acetate as candidate radiosensitizers, were evaluated via reverse transcription‑quantitative polymerase chain reaction, immunohistochemistry and organoid viability assay. Of the three SCFAs tested, only butyrate suppressed the proliferation of the organoids. Moreover, butyrate significantly enhanced radiation‑induced cell death and enhanced treatment effects compared with administration of radiation alone. The radiation‑butyrate combination reduced the proportion of Ki‑67 (proliferation marker)‑positive cells and decreased the number of S phase cells via FOXO3A. Meanwhile, 3/8 CRC organoids were found to be non‑responsive to butyrate with lower expression levels of FOXO3A compared with the responsive cases. Notably, butyrate did not increase radiation‑induced cell death and improved regeneration capacity after irradiation in normal organoids. These results suggest that butyrate could enhance the efficacy of radiotherapy while protecting the normal mucosa, thus highlighting a potential strategy for minimizing the associated toxicity of radiotherapy.

Redifferentiation therapeutic strategies in cancer

The widely recognized problems of pharmacological strategies based on killing cancer cells demand a rethink of therapeutic approaches. Tumor reversion strategies that aim to shift cancer cells to a healthy differentiated state are a promising alternative. Although many studies have firmly demonstrated the possibility of reverting cancer to a normal differentiated state, we are still unable (with the exception of retinoic acid in a form of leukemia) to revert cancer cells to a stable differentiated healthy state. Here, we review the main biological bases of redifferentiation strategies and provide a description of the most promising research avenues.

Clinical Proteomics in Colorectal Cancer, a Promising Tool for Improving Personalised Medicine

Colorectal cancer is the third most common and the fourth most lethal cancer worldwide. In most of cases, patients are diagnosed at an advanced or even metastatic stage, thus explaining the high mortality. The lack of proper clinical tests and the complicated procedures currently used for detecting this cancer, as well as for predicting the response to treatment and the outcome of a patient's resistance in guiding clinical practice, are key elements driving the search for biomarkers. In the present overview, the different biomarkers (diagnostic, prognostic, treatment resistance) discovered through proteomics studies in various colorectal cancer study models (blood, stool, biopsies), including the different proteomic techniques used for the discovery of these biomarkers, are reviewed, as well as the various tests used in clinical practice and those currently in clinical phase. These studies define the limits and perspectives related to proteomic biomarker research for personalised medicine in colorectal cancer.

Analytical techniques for characterization of biological molecules - proteins and aptamers/oligonucleotides

With the advent of the high-throughput technologies and exciting times for biology, the discipline of analytical methodology is experiencing a surge in the growth and the scope. Over the years, multitude of analytical techniques have evolved from a work-intensive, low sensitivity and high volume of reagent and sample consumption endeavor to automated, better selectivity, lower limit of quantification and cost-effective techniques for biological research. In this review, we give an overview of the currently available wide range of cell-based and noncell based and structural based analytical techniques, their principle and biological applications. The analytical techniques discussed in this paper includes surface plasmon resonance, electrophoresis, enzyme linked immunosorbent assay, Western blotting, flow cytometry, fluorescence activated cell sorting, mass spectrometry, nuclear magnetic resonance and x-ray crystallography.

Butyrate Suppresses the Proliferation of Colorectal Cancer Cells via Targeting Pyruvate Kinase M2 and Metabolic Reprogramming

Butyrate is a short chain fatty acid present in a high concentration in the gut lumen. It has been well documented that butyrate, by serving as an energetic metabolite, promotes the proliferation of normal colonocytes while, by serving as a histone deacetylase inhibitor, epigenetically suppressing the proliferation of cancerous counterparts undergoing the Warburg effect. However, how butyrate interrupts the metabolism of colorectal cancer cells and ultimately leads to the suppression of cell proliferation remains unclear. Here, we employed a metabolomics-proteomics combined approach to explore the link between butyrate-mediated proliferation arrest and cell metabolism. A metabolomics study revealed a remodeled metabolic profile with pronounced accumulation of pyruvate, decreased glycolytic intermediates upstream of pyruvate and reduced levels of nucleotides in butyrate-treated HCT-116 cells. Supplementation of key metabolite intermediates directly affected cancer-cell metabolism and modulated the suppressive effect of butyrate in HCT-116 cells. By a Drug Affinity Responsive Target Stability (DARTS)-based quantitative proteomics approach, we revealed the M2 isoform of a pyruvate kinase, PKM2, as a direct binding target of butyrate. Butyrate activates PKM2 via promoting its dephosphorylation and tetramerization and thereby reprograms the metabolism of colorectal cancer cells, inhibiting the Warburg effect while favoring energetic metabolism. Our study thus provides a mechanistic link between PKM2-induced metabolic remodeling and the antitumorigenic function of butyrate and demonstrates a widely applicable approach to uncovering unknown protein targets for small molecules with biological functions.

Both the intratumoral immune and microbial microenvironment are linked to recurrence in human colon cancer: results from a prospective, multicenter nodal ultrastaging trial

Colon cancer (CC) is the third most common cancer diagnosed in the United States and the incidence has been rising among young adults. We and others have shown a relationship between the immune infiltrate and prognosis, with improved disease-free survival (DFS) being associated with a higher expression of CD8⁺ T cells. We hypothesized that a microbial signature might be associated with intratumoral immune cells as well as DFS. We found that the relative abundance of one Operational Taxonomic Unit (OTU), OTU_104, was significantly associated with recurrence even after applying false discovery correction (HR 1.21, CI 1.08 to 1.36). The final multivariable model showed that DFS was influenced by three parameters: N-stage, CD8⁺ labeling, as well as this OTU_104 belonging to the order Clostridiales. Not only were CD8⁺ labeling and OTU_104 significant contributors in the final DFS model, but they were also inversely correlated to each other (p=0.022). Interestingly, CD8⁺ was also significantly associated with the microbiota composition in the tumor: CD8⁺ T cells was inversely correlated with alpha diversity (p=0.027) and significantly associated with the beta diversity. This study is the first to demonstrate an association among the intratumoral microbiome, CD8⁺ T cells, and recurrence in CC. An increased relative abundance of a specific OTU_104 was inversely associated with CD8⁺ T cells and directly associated with CC recurrence. The link between this microbe, CD8⁺ T cells, and DFS has not been previously shown.

Detection of Nuclear Protein Profile Changes by Human Metapneumovirus M2-2 Protein Using Quantitative Differential Proteomics

Human metapneumovirus (hMPV) is a leading cause of lower respiratory infection in pediatric populations globally. This study examined proteomic profile changes in A549 cells infected with hMPV and two attenuated mutants with deleted PDZ domain-binding motif(s) in the M2-2 protein. These motifs are involved in the interruption of antiviral signaling, namely the interaction between the TNF receptor associated factor (TRAF) and mitochondrial antiviral-signaling (MAVS) proteins. The aim of this study was to provide insight into the overall and novel impact of M2-2 motifs on cellular responses via an unbiased comparison. Tandem mass tagging, stable isotope labeling, and high-resolution mass spectrometry were used for quantitative proteomic analysis. Using quantitative proteomics and Venn analysis, 1248 common proteins were detected in all infected samples of both technical sets. Hierarchical clustering of the differentiated proteome displayed distinct proteomic signatures that were controlled by the motif(s). Bioinformatics and experimental analysis confirmed the differentiated proteomes, revealed novel cellular biological events, and implicated key pathways controlled by hMPV M2-2 PDZ domain-binding motif(s). This provides further insight for evaluating M2-2 mutants as potent vaccine candidates.

An insight into the complex roles of metallothioneins in malignant diseases with emphasis on (sub)isoforms/isoforms and epigenetics phenomena

Metallothioneins (MTs) belong to a group of small cysteine-rich proteins that are ubiquitous throughout all kingdoms. The main function of MTs is scavenging of free radicals and detoxification and homeostating of heavy metals. In humans, 16 genes localized on chromosome 16 have been identified to encode four MT isoforms labelled by numbers (MT-1-MT-4). MT-2, MT-3 and MT-4 proteins are encoded by a single gene. MT-1 comprises many (sub)isoforms. The known active MT-1 genes are MT-1A, -1B, -1E, -1F, -1G, -1H, -1M and -1X. The rest of the MT-1 genes (MT-1C, -1D, -1I, -1J and -1L) are pseudogenes. The expression and localization of individual MT (sub)isoforms and pseudogenes vary at intra-cellular level and in individual tissues. Changes in MT expression are associated with the process of carcinogenesis of various types of human malignancies, or with a more aggressive phenotype and therapeutic resistance. Hence, MT (sub)isoform profiling status could be utilized for diagnostics and therapy of tumour diseases. This review aims on a comprehensive summary of methods for analysis of MTs at (sub)isoforms levels, their expression in single tumour diseases and strategies how this knowledge can be utilized in anticancer therapy.

Proteomic discovery and verification of serum amyloid A as a predictor marker of patients at risk of post-stroke infection: a pilot study

Background

Post-stroke infections occur in 20–36% of stroke patients and are associated with high morbidity and mortality rates. Early identification of patients at risk of developing an infection could improve care via an earlier treatment leading to a better outcome. We used proteomic tools in order to discover biomarkers able to stratify patients at risk of post-stroke infection.

Methods

The post hoc analysis of a prospective cohort study including 40 ischemic stroke patients included 21 infected and 19 non-infected participants. A quantitative, isobaric labeling, proteomic strategy was applied to the plasma samples of 5 infected and 5 non-infected patients in order to highlight any significantly modulated proteins. A parallel reaction monitoring (PRM) assay was applied to 20 additional patients (10 infected and 10 non-infected) to verify discovery results. The most promising protein was pre-validated using an ELISA immunoassay on 40 patients and at different time points after stroke onset.

Results

Tandem mass analysis identified 266 proteins, of which only serum amyloid A (SAA1/2) was significantly (p = 0.007) regulated between the two groups of patients. This acute-phase protein appeared to be 2.2 times more abundant in infected patients than in non-infected ones. These results were verified and validated using PRM and ELISA immunoassays, which showed that infected patients had significantly higher concentrations of SAA1/2 than non-infected patients at hospital admission, but also at 1, 3, and 5 days after admission.

Conclusions

The present study demonstrated that SAA1/2 is a promising predictor, at hospital admission, of stroke patients at risk of developing an infection. Further large, multicenter validation studies are needed to confirm these results. If confirmed, SAA1/2 concentrations could be used to identify the patients most at risk of post-stroke infections and therefore implement treatments more rapidly, thus reducing mortality.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-017-9162-0) contains supplementary material, which is available to authorized users.

Biomarker discovery by proteomics-based approaches for early detection and personalized medicine in colorectal cancer

About one million people per year develop colorectal cancer (CRC) and approximately half of them die. The extent of the disease (i.e. local invasion at the time of diagnosis) is a key prognostic factor. The 5-year survival rate is almost 90% in the case of delimited CRC and 10% in the case of metastasized CRC. Hence, one of the great challenges in the battle against CRC is to improve early diagnosis strategies. Large-scale proteomic approaches are widely used in cancer research to search for novel biomarkers. Such biomarkers can help in improving the accuracy of the diagnosis and in the optimization of personalized therapy. Herein, we provide an overview of studies published in the last 5 years on CRC that led to the identification of protein biomarkers suitable for clinical application by using proteomic approaches. We discussed these findings according to biomarker application, including also the role of protein phosphorylation and cancer stem cells in biomarker discovery. Our review provides a cross section of scientific approaches and can furnish suggestions for future experimental strategies to be used as reference by scientists, clinicians and researchers interested in proteomics for biomarker discovery.

Proteomic Profiling of De Novo Protein Synthesis in Starvation-Induced Autophagy Using Bioorthogonal Noncanonical Amino Acid Tagging

Autophagy is an intracellular degradation process activated by stress factors such as nutrient starvation to maintain cellular homeostasis. There is emerging evidence demonstrating that de novo protein synthesis is involved in the autophagic process. However, up-to-date characterizing of these de novo proteins is technically difficult. In this chapter, we describe a novel method to identify newly synthesized proteins during starvation-mediated autophagy by bioorthogonal noncanonical amino acid tagging (BONCAT), in conjunction with isobaric tagging for relative and absolute quantification (iTRAQ)-based quantitative proteomics. l-azidohomoalanine (AHA) is an analog of methionine, and it can be readily incorporated into the newly synthesized proteins. The AHA-containing proteins can be enriched with avidin beads after a "click" reaction between alkyne-bearing biotin and the azide moiety of AHA. The enriched proteins are then subjected to iTRAQ™ labeling for protein identification and quantification using liquid chromatography-tandem mass spectrometry (LC-MS/MS). By using this technique, we have successfully profiled more than 700 proteins that are synthesized during starvation-induced autophagy. We believe that this approach is effective in identification of newly synthesized proteins in the process of autophagy and provides useful insights to the molecular mechanisms and biological functions of autophagy.

Quantitative chemical proteomics profiling of de novo protein synthesis during starvation-mediated autophagy

Autophagy is an intracellular degradation mechanism in response to nutrient starvation. Via autophagy, some nonessential cellular constituents are degraded in a lysosome-dependent manner to generate biomolecules that can be utilized for maintaining the metabolic homeostasis. Although it is known that under starvation the global protein synthesis is significantly reduced mainly due to suppression of MTOR (mechanistic target of rapamycin serine/threonine kinase), emerging evidence demonstrates that de novo protein synthesis is involved in the autophagic process. However, characterizing these de novo proteins has been an issue with current techniques. Here, we developed a novel method to identify newly synthesized proteins during starvation-mediated autophagy by combining bio-orthogonal noncanonical amino acid tagging (BONCAT) and isobaric tags for relative and absolute quantitation (iTRAQ^TM). Using bio-orthogonal metabolic tagging, L-azidohomoalanine (AHA) was incorporated into newly synthesized proteins which were then enriched with avidin beads after a click reaction between alkyne-bearing biotin and AHA's bio-orthogonal azide moiety. The enriched proteins were subjected to iTRAQ labeling for protein identification and quantification using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Via the above approach, we identified and quantified a total of 1176 proteins and among them 711 proteins were found to meet our defined criteria as de novo synthesized proteins during starvation-mediated autophagy. The characterized functional profiles of the 711 newly synthesized proteins by bioinformatics analysis suggest their roles in ensuring the prosurvival outcome of autophagy. Finally, we performed validation assays for some selected proteins and found that knockdown of some genes has a significant impact on starvation-induced autophagy. Thus, we think that the BONCAT-iTRAQ approach is effective in the identification of newly synthesized proteins and provides useful insights to the molecular mechanisms and biological functions of autophagy.

Measuring Serum Amyloid A for Infection Prediction in Aneurysmal Subarachnoid Hemorrhage

Aneurysmal subarachnoid hemorrhage (aSAH) is associated with high rates of mortality and morbidity. Nosocomial infections, such as pneumonia or urinary tract infections, are among the main causes of worsening outcomes and death. The aim of this study was to discover a biomarker to predict infection in aSAH patients. For this purpose, the plasma of infected and noninfected patients was compared using quantitative mass spectrometry. The most interesting differentially expressed proteins were selected for validation by immunoassays on plasma samples taken from patients (n = 81) over 10 days of hospitalization. Predictive performances were established using Mann-Whitney U tests and receiver operating characteristic curves. Quantitative proteomics identified 17 significantly regulated proteins. Of these, levels of serum amyloid A (SAA) were significantly higher in infected patients (p < 0.007). ELISA confirmed that the concentrations were significantly higher (p < 0.002) already at hospital admission in patients who subsequently developed an infection during their hospitalization, (AUC of 76%) for a cutoff value of 90.9 μg/mL. Our data suggested that measuring SAA could be an efficient means of detecting patients susceptible of developing an infection during hospitalization after an aSAH. Its predictive capacity could lead to earlier antibiotherapy, improved patient management, and potentially better long-term outcomes.

Data from proteomic characterization of the role of Snail1 in murine mesenchymal stem cells and 3T3-L1 fibroblasts differentiation

The transcription factor (TF) Snail1 is a major inducer of the epithelial–mesenchymal transition (EMT) during embryonic development and cancer progression. Ectopic expression of Snail in murine mesenchymal stem cells (mMSC) abrogated their differentiation to osteoblasts or adipocytes. We used either stable isotopic metabolic labeling (SILAC) for 3T3-L1 cells or isobaric labeling with tandem mass tags (TMT) for mMSC stably transfected cells with Snail1 or control. We carried out a proteomic analysis on the nuclear fraction since Snail is a nuclear TF that mediates its effects mainly through the regulation of other TFs. Proteomics data have been deposited in ProteomeXchange via the PRIDE partner repository with the dataset identifiers PXD001529 and PXD002157 (Vizcaino et al., 2014) [1]. Data are associated with a research article published in Molecular and Cellular Proteomics (Pelaez-Garcia et al., 2015) [2].

A proteomic analysis of transplanted liver in a rat model of chronic rejection

BACKGROUND

Chronic rejection (CR) is an important cause of liver allograft failure. In the latter condition, re-transplantation of the liver (ReLT) is the only option for survival. Unfortunately, with the current state of knowledge, it is difficult to diagnose and treat early CR.

OBJECTIVE

To explore the biomarkers of the chronic rejection in orthotopic liver transplantation (OLT).

METHODS

A rat model of chronic liver allograft rejection was established, and the differential protein expression in chronic allograft rejection (CR) was analyzed by iTRAQ-MALDI-TOF/TOF.

RESULTS

Expression of sixty-two proteins was found to be significantly changed in CR rats. In the present study, CLU, Lcn2 and Krt19 were identified and quantified as early and reliable biomarkers for chronic rejection.

CONCLUSION

Analysis of differential protein expression by iTRAQ-MALDI-TOF/TOF is a potentially effective method to help understand the mechanism of CR in orthotopic liver transplantation. The proteins CLU, Lcn2 and Krt19 might be potential prognostic markers for predicting chronic rejection after liver transplantation.

Genistein exerts anti-leukemic effects on genetically different acute myeloid leukemia cell lines by inhibiting protein synthesis and cell proliferation while inducing apoptosis - molecular insights from an iTRAQ™ quantitative proteomics study

Acute myeloid leukemia (AML) is a form of cancer that affects the hematopoietic precursor cells with lethal effects. We investigated the prospect of using genistein as an effective alternate therapy for AML. A two-cell line model, one possessing the FLT3 gene with the ITD mutation (MV4−11) and the other with the wildtype FLT3 gene (HL−60) has been employed. Our 8−plexed iTRAQ™−based quantitative proteomics analysis together with various functional studies demonstrated that genistein exerts anti-leukemic effects on both the AML cell lines. Genistein treatment on the AML cells showed that the drug arrested the mTOR pathway leading to down−regulation of protein synthesis. Additionally, genistein treatment is found to induce cell death via apoptosis. Contrasting regulatory effects of genistein on the cell cycle of the two cell lines were also identified, with the induction of G2/M phase arrest in HL-60 cells but not in MV4−11 cells. Hence, our study highlights the potent anti-leukemic effect of genistein on AML cells irrespective of their genetic status. This suggests the potential use of genistein as an effective general drug therapy for AML patients.

De Novo proteome analysis of genetically modified tumor cells by a metabolic labeling/azide-alkyne cycloaddition approach

Activin receptor type II (ACVR2) is a member of the transforming growth factor type II receptor family and controls cell growth and differentiation, thereby acting as a tumor suppressor. ACVR2 inactivation is known to drive colorectal tumorigenesis. We used an ACVR2-deficient microsatellite unstable colon cancer cell line (HCT116) to set up a novel experimental design for comprehensive analysis of proteomic changes associated with such functional loss of a tumor suppressor. To this end we combined two existing technologies. First, the ACVR2 gene was reconstituted in an ACVR2-deficient colorectal cancer (CRC) cell line by means of recombinase-mediated cassette exchange, resulting in the generation of an inducible expression system that allowed the regulation of ACVR2 gene expression in a doxycycline-dependent manner. Functional expression in the induced cells was explicitly proven. Second, we used the methionine analog azidohomoalanine for metabolic labeling of newly synthesized proteins in our cell line model. Labeled proteins were tagged with biotin via a Click-iT chemistry approach enabling specific extraction of labeled proteins by streptavidin-coated beads. Tryptic on-bead digestion of captured proteins and subsequent ultra-high-performance LC coupled to LTQ Orbitrap XL mass spectrometry identified 513 proteins, with 25 of them differentially expressed between ACVR2-deficient and -proficient cells. Among these, several candidates that had already been linked to colorectal cancer or were known to play a key role in cell growth or apoptosis control were identified, proving the utility of the presented experimental approach. In principle, this strategy can be adapted to analyze any gene of interest and its effect on the cellular de novo proteome.

Highly multiplexed and reproducible ion-current-based strategy for large-scale quantitative proteomics and the application to protein expression dynamics induced by methylprednisolone in 60 rats

A proteome-level time-series study of drug effects (i.e., pharmacodynamics) is critical for understanding mechanisms of action and systems pharmacology, but is challenging, because of the requirement of a proteomics method for reliable quantification of many biological samples. Here, we describe a highly reproducible strategy, enabling a global, large-scale investigation of the expression dynamics of corticosteroid-regulated proteins in livers from adrenalectomized rats over 11 time points after drug dosing (0.5–66 h, N = 5/point). The analytical advances include (i) exhaustive tissue extraction with a Polytron/sonication procedure in a detergent cocktail buffer, and a cleanup/digestion procedure providing very consistent protein yields (relative standard deviation (RSD%) of 2.7%–6.4%) and peptide recoveries (4.1–9.0%) across the 60 animals; (ii) an ultrahigh-pressure nano-LC setup with substantially improved temperature stabilization, pump-noise suppression, and programmed interface cleaning, enabling excellent reproducibility for continuous analyses of numerous samples; (iii) separation on a 100-cm-long column (2-μm particles) with high reproducibility for days to enable both in-depth profiling and accurate peptide ion-current match; and (iv) well-controlled ion-current-based quantification. To obtain high-quality quantitative data necessary to describe the 11 time-points protein expression temporal profiles, strict criteria were used to define “quantifiable proteins”. A total of 323 drug-responsive proteins were revealed with confidence, and the time profiles of these proteins provided new insights into the diverse temporal changes of biological cascades associated with hepatic metabolism, response to hormone stimuli, gluconeogenesis, inflammatory responses, and protein translation processes. Most profile changes persisted well after the drug was eliminated. The developed strategy can also be broadly applied in preclinical and clinical research, where the analysis of numerous biological replicates is crucial.

Butyrate decreases risk of colonic cancer: Potential mechanisms

There is an increasing trend for the incidence of bowel diseases around the world. Besides the influence from family background and environment, dietary structure plays important roles in the rising rates of bowel diseases. Results from epidemiological studies and molecular biological studies showed that the concentration of short-chain fatty acids, in particular butyrate, is a key factor for maintaining a healthy colon environment. Although the primary mechanism for butyrate to depress the growth of cancer cells is acting as an inhibitor of histone deacetylases (HDACs), some studies demonstrated that butyrate is also involved in cell metabolism and induction of the death of cancer cells. This article reviews the mechanisms of action of butyrate on colon cells.

LC-MS based cleavage site profiling of the proteases ADAM10 and ADAM17 using proteome-derived peptide libraries

A Disintegrin and Metalloproteinase 10 (ADAM10) and ADAM17 catalyze ectodomain shedding of a number of cell surface proteins important for embryonic development and tissue homeostasis. Changes in the expression levels or dysregulated proteolytic activity of ADAM10 and ADAM17 have been shown to play important roles in multiple diseases such as inflammation, cancer, and neurodegenerative disorders. Despite the well documented substrate repertoire of ADAM10 and ADAM17, little is known about their cleavage site specificity. We optimized Q-PICS (Quantitative Proteomics for the Identification of Cleavage Sites) to elucidate the cleavage site specificity of recombinant murine ADAM10 and ADAM17. Two different yeast proteome-derived peptide libraries were used and samples were analyzed by LC-MALDI and LC-ESI MS in parallel. We show that the largest difference in the cleavage site specificities of ADAM10 and ADAM17 is at the P1' site: while both enzymes cleave N-terminal of leucine, only ADAM10 shows additional preference toward aromatic amino acids, whereas ADAM17 exhibits the highest preference for valine. Together with further amino acid preferences more adjacent to the scissile bond, our data is in good agreement with ADAM10/17 cleavage sites previously identified in native substrates. Overall, the precise identification of ADAM10 and ADAM17 cleavage site specificity provides the basis for better substrate identification in vivo and the generation of specific inhibitors or activity based probes.

Proteomics, genomics and transcriptomics: their emerging roles in the discovery and validation of colorectal cancer biomarkers

Colorectal cancer (CRC) is the second most common cancer in females and the third in males. Since CRC is often diagnosed at an advanced stage when prognosis is poor, identification of biomarkers for early diagnosis is urgently required. Recent advances in proteomics, genomics and transcriptomics have facilitated high-throughput profiling of data generated from CRC-related genes and proteins, providing a window of information for biomarker discovery and validation. However, transfer of candidate biomarkers from bench to bedside remains a dilemma. In this review, we will discuss emerging proteomic technologies and highlight various sample types utilized for proteomics-based identification of CRC biomarkers. Moreover, recent breakthroughs in genomics and transcriptomics for the identification of CRC biomarkers, with particular emphasis on the merits of emerging methylomic and miRNAomic strategies, will be discussed. Integration of proteomics, genomics and transcriptomics will facilitate the discovery and validation of CRC biomarkers leading to the emergence of personalized medicine.

Exploring the human tear fluid: discovery of new biomarkers in multiple sclerosis

PURPOSE

Multiple sclerosis is the first cause of progressive neurological disability among young adults living in Western countries. Its diagnosis is mostly based on clinical evaluation, neuroimaging, and in some cases cerebrospinal fluid (CSF) analysis, but no definitive diagnostic test exists. We proposed here that the exploration of tears from multiple sclerosis patients could lead to the discovery of new biomarkers.

EXPERIMENTAL DESIGN

Thirty multiple sclerosis patients (20% men) recruited to the Geneva University Hospitals were included in our study (mean age ± SD [years]: 42.4 ± 15.9). Twenty-five control patients (32% men) were also enrolled (mean age ± SD [years]: 42.7±15.1). Tears, CSF or blood was collected for each patient. Three independent quantitative (tandem mass tag) experiments were carried out between tears from multiple sclerosis and control patients. Protein verification was performed by Western blot on tears and CSF and by ELISA on serum samples.

RESULTS

Combined proteomics analyses provided 185 identified tear proteins. Among the differential proteins, alpha-1 antichymotrypsin was the only one to be significantly increased in the three experiments with similar ratios (ratios 1.6 to 2.5, p < 0.05). Its tear, CSF and serum elevation were further confirmed by Western blot and ELISA, respectively.

CONCLUSIONS AND CLINICAL RELEVANCE

This study supports the concept that modifications of the tear proteome can reflect biological abnormalities associated with multiple sclerosis and perhaps other inflammatory conditions affecting the CNS. In addition, alpha-1 antichymotrypsin elevation in tear fluid emerges as a promising biomarker for the diagnosis of multiple sclerosis.

Enhancing gold recovery from electronic waste via lixiviant metabolic engineering in Chromobacterium violaceum

Conventional leaching (extraction) methods for gold recovery from electronic waste involve the use of strong acids and pose considerable threat to the environment. The alternative use of bioleaching microbes for gold recovery is non-pollutive and relies on the secretion of a lixiviant or (bio)chemical such as cyanide for extraction of gold from electronic waste. However, widespread industrial use of bioleaching microbes has been constrained by the limited cyanogenic capabilities of lixiviant-producing microorganisms such as Chromobacterium violaceum. Here we show the construction of a metabolically-engineered strain of Chromobacterium violaceum that produces more (70%) cyanide lixiviant and recovers more than twice as much gold from electronic waste compared to wild-type bacteria. Comparative proteome analyses suggested the possibility of further enhancement in cyanogenesis through subsequent metabolic engineering. Our results demonstrated the utility of lixiviant metabolic engineering in the construction of enhanced bioleaching microbes for the bioleaching of precious metals from electronic waste.

Quantitative mass spectrometry for colorectal cancer proteomics

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

A quantitative chemical proteomics approach to profile the specific cellular targets of andrographolide, a promising anticancer agent that suppresses tumor metastasis

Drug target identification is a critical step toward understanding the mechanism of action of a drug, which can help one improve the drug's current therapeutic regime and expand the drug's therapeutic potential. However, current in vitro affinity-chromatography-based and in vivo activity-based protein profiling approaches generally face difficulties in discriminating specific drug targets from nonspecific ones. Here we describe a novel approach combining isobaric tags for relative and absolute quantitation with clickable activity-based protein profiling to specifically and comprehensively identify the protein targets of andrographolide (Andro), a natural product with known anti-inflammation and anti-cancer effects, in live cancer cells. We identified a spectrum of specific targets of Andro, which furthered our understanding of the mechanism of action of the drug. Our findings, validated through cell migration and invasion assays, showed that Andro has a potential novel application as a tumor metastasis inhibitor. Moreover, we have unveiled the target binding mechanism of Andro with a combination of drug analog synthesis, protein engineering, and mass-spectrometry-based approaches and determined the drug-binding sites of two protein targets, NF-κB and actin.

Proteomic signatures of acquired letrozole resistance in breast cancer: suppressed estrogen signaling and increased cell motility and invasiveness

Aromatase inhibitors, such as letrozole, have become the first-line treatment for postmenopausal women with estrogen-dependent breast cancer. However, acquired resistance remains a major clinical obstacle. Previous studies demonstrated constitutive activation of the MAPK signaling, overexpression of HER2, and down-regulation of aromatase and ERα in letrozole-resistant breast cancer cells. Given the complex signaling network involved in letrozole-refractory breast cancer and the lack of effective treatment for hormone resistance, further investigation of aromatase inhibitor resistance by a novel systems biology approach may reveal previously unconsidered molecular changes that could be utilized as therapeutic targets. This study was undertaken to characterize for the first time global proteomic alterations occurring in a letrozole-resistant cell line. A quantitative proteomic analysis of the whole cell lysates of LTLT-Ca (resistant) versus AC-1 cells (sensitive) was performed to identify significant protein expression changes. A total of 1743 proteins were identified and quantified, of which 411 were significantly up-regulated and 452 significantly down-regulated (p < 0.05, fold change > 1.20). Bioinformatics analysis revealed that acquired letrozole resistance is associated with a hormone-independent, more aggressive phenotype. LTLT-Ca cells exhibited 84% and 138% increase in migration and invasion compared with the control cells. The ROCK inhibitor partially abrogated the enhanced migration and invasion of the letrozole-resistant cells. Flow cytometric analyses also demonstrated an increase in vimentin and twist expression in letrozole-resistance cells, suggesting an onset of epithelial to mesenchymal transition (EMT). Moreover, targeted gene expression arrays confirmed a 28-fold and sixfold up-regulation of EGFR and HER2, respectively, whereas ERα and pS2 were dramatically reduced by 28-fold and 1100-fold, respectively. Taken together, our study revealed global proteomic signatures of a letrozole-resistant cell line associated with hormone independence, enhanced cell motility, EMT and the potential values of several altered proteins as novel prognostic markers or therapeutic targets for letrozole resistant breast cancer.

Quantitative protein analysis using (13)C7-labeled iodoacetanilide and d5-labeled N-ethylmaleimide by nano liquid chromatography/nanoelectrospray ionization ion trap mass spectrometry

We have developed a methodology for quantitative analysis and concurrent identification of proteins by the modification of cysteine residues with a combination of iodoacetanilide (IAA, 1) and (13)C7-labeled iodoacetanilide ((13)C7-IAA, 2), or N-ethylmaleimide (NEM, 3) and d5-labeled N-ethylmaleimide (d5-NEM, 4), followed by mass spectrometric analysis using nano liquid chromatography/nanoelectrospray ionization ion trap mass spectrometry (nano LC/nano-ESI-IT-MS). The combinations of these stable isotope-labeled and unlabeled modifiers coupled with LC separation and ESI mass spectrometric analysis allow accurate quantitative analysis and identification of proteins, and therefore are expected to be a useful tool for proteomics research.

Efficacy of aerosolized celecoxib encapsulated nanostructured lipid carrier in non-small cell lung cancer in combination with docetaxel

PURPOSE

Evaluation of in-vivo anticancer activity of aerosolized Celecoxib encapsulated Nanolipidcarriers (Cxb-NLC) as a single therapeutic agent and combined with intravenously administered Docetaxel (Doc) against non-small cell lung cancer.

METHODS

Cxb-NLC were prepared by high-pressure homogenization and were characterized for its physicochemical characteristics. Metastatic A549 tumor model in Nu/Nu mice was used to evaluate response of aerosolized Cxb-NLC & Doc. Isolated lung tumor samples were analyzed for: a) DNA fragmentation and cleaved caspase-3 by immunohistochemistry, b) apoptotic and angiogenic protein markers by western blot, c) global proteomic alterations by an isobaric labeling quantitative proteomic method and d) toxicity studies of NLC.

RESULTS

The particle size of Cxb-NLC was 217 ± 20 nm, while entrapment efficiency was more than 90%. Cxb-NLC and Doc alone and in combination showed 25 ± 4%, 37 ± 5%, and 67 ± 4% reduction in tumor size respectively compared to control. Proteomic analysis with combination treatment further revealed significantly decreased expression of multiple pro-survival and pro-metastasis proteins as well as tumor invasion markers and the expression of S100 family proteins, such as S100A6 and S100P were decreased by 2.5 and 1.6 fold.

CONCLUSIONS

Combination therapy with Cxb-NLC and Doc showed significant reduction in tumor growth which was further confirmed by proteomic analysis.

Identification and functional validation of caldesmon as a potential gastric cancer metastasis-associated protein

In this study, we aim to identify biomarkers for gastric cancer metastasis using a quantitative proteomics approach. The proteins extracted from a panel of 4 gastric cancer cell lines, two derived from primary cancer (AGS, FU97) and two from lymph node metastasis (AZ521, MKN7), were labeled with iTRAQ (8-plex) reagents and analyzed by 2D-LC-MALDI-TOF/TOF MS. In total, 641 proteins were identified with at least a 95% confidence. Using cutoff values of >1.5 and <0.67, 19 proteins were found to be up-regulated and 34 were down-regulated in the metastatic versus primary gastric cancer cell lines respectively. Several of these dysregulated proteins, including caldesmon, were verified using Western blotting. It was found that caldesmon expression was decreased in the two metastasis-derived cell lines, and this was confirmed by further analysis of 7 gastric cancer cell lines. Furthermore, immunohistochemical staining of 9 pairs of primary gastric cancer and the matched lymph node metastasis tissue also corroborated this observation. Finally, knockdown of caldesmon using siRNA in AGS and FU97 gastric cancer cells resulted in an increase in cell migration and invasion, while the overexpression of caldesmon in AZ521 cells led to a decrease in cell migration and invasion. This study has thus established the potential role of caldesmon in gastric cancer metastasis, and further functional studies are underway to delineate the underlying mechanism of action of this protein.

STAT6 promotes bi-directional modulation of PKM2 in liver and adipose inflammatory cells in rosiglitazone-treated mice

STAT6 interacts with PPARγ to elicit macrophage polarization towards an anti-inflammatory, insulin-sensitizing phenotype. Mice deficient in STAT6 display liver lipid accumulation (hepatosteatosis). Rosiglitazone (RSG), a PPARγ agonist, ameliorates hepatosteatosis and enhances insulin sensitivity. To elucidate the role of STAT6 in PPARγ action on hepatosteatosis we compared liver proteomes of RSG-treated wild type and STAT6-deficient mice and we identified pyruvate kinase M2 (PKM2), a glycolysis and proliferation-regulating enzyme that displayed STAT6-dependent expression. RSG induced PKM2 within inflammatory cells in liver but suppressed its expression in adipose tissue. RSG diminished hepatosteatosis and oxidative stress, enhanced fat accumulation and improved insulin sensitivity in STAT6-deficient mice. Our data reveal a complex interaction between STAT6 and PPARγ in the regulation of liver and adipose tissue lipid depot distribution and design STAT6 as a novel link between inflammatory cell metabolism and adipocyte and hepatocyte function.

Improved reporter ion assignment of raw isobaric stable isotope labeled liquid chromatography/matrix-assisted laser desorption/ionization tandem time-of-flight mass spectral data for quantitative proteomics

RATIONALE

Isobaric labeling strategies (e.g. iTRAQ or TMT) are commonly applied in tandem mass spectrometric (MS/MS) level quantitative proteomics. However, we frequently observed missing isotope reporter ion signals in a large-scale liquid chromatography/matrix-assisted laser desorption/ionization tandem time-of-flight mass spectrometric (LC/MALDI-TOF/TOF) quantitative proteomics experiment. To understand this issue, we systematically investigated the processing of MS/MS spectra into peak lists prior to peptide identification and quantification.

METHODS

A 15-protein standard, with six proteins in different concentrations, was labeled with iTRAQ 4-plex, iTRAQ 8-plex or TMT 6-plex, tryptic digested and measured using LC/MALDI-TOF/TOF. Three commercially and open-source available peak list generation software tools were compared based on missing reporter ions, peptide identification and quantification.

RESULTS

We found that each tool discarded lower-intensity reporter ions, when they followed a higher intensity reporter ion, due to the implemented de-isotoping algorithms. By using the non-de-isotoping setting within TS2Mascot, we found that all reporter ions are exported, yet less peptides were identified with Mascot. Therefore, we developed a strategy merging the de-isotoped and non-de-isotoped outputs from TS2Mascot using the Perl script RICmerge.pl.

CONCLUSIONS

With this approach, we correctly quantified all labeled peptides that were identified within the 15-protein standard. This strategy allows improved annotation of isobaric tag labeled peptide MS/MS spectra and improves downstream peptide and protein quantification in proteomics studies.

Cancer proteomics

Cancer presents high mortality and morbidity globally, largely due to its complex and heterogenous nature, and lack of biomarkers for early diagnosis. A proteomics study of cancer aims to identify and characterize functional proteins that drive the transformation of malignancy, and to discover biomarkers to detect early-stage cancer, predict prognosis, determine therapy efficacy, identify novel drug targets, and ultimately develop personalized medicine. The various sources of human samples such as cell lines, tissues, and plasma/serum are probed by a plethora of proteomics tools to discover novel biomarkers and elucidate mechanisms of tumorigenesis. Innovative proteomics technologies and strategies have been designed for protein identification, quantitation, fractionation, and enrichment to delve deeper into the oncoproteome. In addition, there is the need for high-throughput methods for biomarker validation, and integration of the various platforms of oncoproteome data to fully comprehend cancer biology.

S100A9, GIF and AAT as potential combinatorial biomarkers in gastric cancer diagnosis and prognosis

PURPOSE

We have mined the gastric fluid proteome for potential gastric cancer (GC) biomarkers that may enhance disease detection and facilitate prognostic monitoring.

EXPERIMENTAL DESIGN

In biomarker discovery, a total of 12 patient gastric fluid samples (stages I, III, IV and gastritis) were analysed by 2DE for expression changes that correlated with GC status or disease progression. Gastric fluid proteins showing differential expression with GC were identified by MALDI-TOF/TOF MS as putative biomarkers. Levels of these potential biomarker candidates were independently validated by Western blotting in further 60 gastritis and GC patients. A targeted approach that recruits biomarker candidates for panel consideration was adopted to test if two or more biomarkers in combination improved diagnostic power.

RESULTS

From the 15 differentially regulated proteins identified, expression levels of S100A9, GIF and AAT in the gastric fluid clearly correlated with GC status. S100A9/AAT (AUC = 0.81) and S100A9/GIF (AUC = 0.92) were revealed as promising biomarker pairs for early GC diagnosis and disease monitoring, respectively.

CONCLUSION AND CLINICAL RELEVANCE

Early diagnosis, accurate staging and constant disease monitoring remain the prerequisites for effective treatment against GC. As current biomarkers like CA19-9 and carcinoembryonic antigen (CEA) lack sensitivity and specificity, there is a pressing need for novel GC detection and monitoring methods. To this end, S100A9, GIF and AAT from the gastric fluid may significantly augment existing methods of GC detection and monitoring, and eliminate the need for invasive tissue biopsies.

A review of the potential mechanisms for the lowering of colorectal oncogenesis by butyrate

Colorectal cancer (CRC) is a leading cause of preventable cancer deaths worldwide, with dietary factors being recognised as key risk modifiers. Foods containing dietary fibre are protective to a degree that the World Cancer Research Fund classifies the evidence supporting their consumption as ‘convincing’. The mechanisms by which fibre components protect against CRC remain poorly understood, especially their interactions with the gut microbiome. Fibre is a composite of indigestible plant polysaccharides and it is emerging that fermentable fibres, including resistant starch (RS), are particularly important. RS fermentation induces SCFA production, in particular, relatively high butyrate levels, and in vitro studies have shown that this acid has strong anti-tumorigenic properties. Butyrate inhibits proliferation and induces apoptosis of CRC cell lines at physiological concentrations. These effects are attributed to butyrate's ability to alter gene transcription by inhibiting histone deacetylase activity. However, the more recent discovery of G-protein coupled receptors that bind butyrate and other SCFA and data obtained from proteomic and genomic experiments suggest that alternative pathways are involved. Here, we review the mechanisms involved in butyrate-induced apoptosis in CRC cells and, additionally, the potential role this SCFA may play in mediating key processes in tumorigenesis including genomic instability, inflammation and cell energy metabolism. This discussion may help to inform the development of strategies to lower CRC risk at the individual and population levels.

Opportunities and challenges for nutritional proteomics in cancer prevention

Knowledge gaps persist about the efficacy of cancer prevention strategies based on dietary food components. Adaptations to nutrient supply are executed through tuning of multiple protein networks that include transcription factors, histones, modifying enzymes, translation factors, membrane and nuclear receptors, and secreted proteins. However, the simultaneous quantitative and qualitative measurement of all proteins that regulate cancer processes is not practical using traditional protein methodologies. Proteomics offers an attractive opportunity to fill this knowledge gap and unravel the effects of dietary components on protein networks that impinge on cancer. The articles presented in this supplement are from talks proffered in the "Nutrition Proteomics and Cancer Prevention" session at the American Institute for Cancer Research Annual Research Conference on Food, Nutrition, Physical Activity and Cancer held in Washington, DC on October 21 and 22, 2010. Recent advances in MS technologies suggest that studies in nutrition and cancer prevention may benefit from the adoption of proteomic tools to elucidate the impact on biological processes that govern the transition from normal to malignant phenotype; to identify protein changes that determine both positive and negative responses to food components; to assess how protein networks mediate dose-, time-, and tissue-dependent responses to food components; and, finally, for predicting responders and nonresponders. However, both the limited accessibility to proteomic technologies and research funding appear to be hampering the routine adoption of proteomic tools in nutrition and cancer prevention research.

Proteomic analysis of acquired tamoxifen resistance in MCF-7 cells reveals expression signatures associated with enhanced migration

Introduction

Acquired tamoxifen resistance involves complex signaling events that are not yet fully understood. Successful therapeutic intervention to delay the onset of hormone resistance depends critically on mechanistic elucidation of viable molecular targets associated with hormone resistance. This study was undertaken to investigate the global proteomic alterations in a tamoxifen resistant MCF-7 breast cancer cell line obtained by long term treatment of the wild type MCF-7 cell line with 4-hydroxytamoxifen (4-OH Tam).

Methods

We cultured MCF-7 cells with 4-OH Tam over a period of 12 months to obtain the resistant cell line. A gel-free, quantitative proteomic method was used to identify and quantify the proteome of the resistant cell line. Nano-flow high-performance liquid chromatography coupled to high resolution Fourier transform mass spectrometry was used to analyze fractionated peptide mixtures that were isobarically labeled from the resistant and control cell lysates. Real time quantitative PCR and Western blots were used to verify selected proteomic changes. Lentiviral vector transduction was used to generate MCF-7 cells stably expressing S100P. Online pathway analysis was performed to assess proteomic signatures in tamoxifen resistance. Survival analysis was done to evaluate clinical relevance of altered proteomic expressions.

Results

Quantitative proteomic analysis revealed a wide breadth of signaling events during transition to acquired tamoxifen resistance. A total of 629 proteins were found significantly changed with 364 up-regulated and 265 down-regulated. Collectively, these changes demonstrated the suppressed state of estrogen receptor (ER) and ER-regulated genes, activated survival signaling and increased migratory capacity of the resistant cell line. The protein S100P was found to play a critical role in conferring tamoxifen resistance and enhanced cell motility.

Conclusions

Our data demonstrate that the adaptive changes in the proteome of tamoxifen resistant breast cancer cells are characterized by down-regulated ER signaling, activation of alternative survival pathways, and enhanced cell motility through regulation of the actin cytoskeleton dynamics. Evidence also emerged that S100P mediates acquired tamoxifen resistance and migration capacity.

Proteomics signature profiling (PSP): a novel contextualization approach for cancer proteomics

Traditional proteomics analysis is plagued by the use of arbitrary thresholds resulting in large loss of information. We propose here a novel method in proteomics that utilizes all detected proteins. We demonstrate its efficacy in a proteomics screen of 5 and 7 liver cancer patients in the moderate and late stage, respectively. Utilizing biological complexes as a cluster vector, and augmenting it with submodules obtained from partitioning an integrated and cleaned protein–protein interaction network, we calculate a Proteomics Signature Profile (PSP) for each patient based on the hit rates of their reported proteins, in the absence of fold change thresholds, against the cluster vector. Using this, we demonstrated that moderate- and late-stage patients segregate with high confidence. We also discovered a moderate-stage patient who displayed a proteomics profile similar to other poor-stage patients. We identified significant clusters using a modified version of the SNet approach. Comparing our results against the Proteomics Expansion Pipeline (PEP) on which the same patient data was analyzed, we found good correlation. Building on this finding, we report significantly more clusters (176 clusters here compared to 70 in PEP), demonstrating the sensitivity of this approach. Gene Ontology (GO) terms analysis also reveals that the significant clusters are functionally congruent with the liver cancer phenotype. PSP is a powerful and sensitive method for analyzing proteomics profiles even when sample sizes are small. It does not rely on the ratio scores but, rather, whether a protein is detected or not. Although consistency of individual proteins between patients is low, we found the reported proteins tend to hit clusters in a meaningful and informative manner. By extracting this information in the form of a Proteomics Signature Profile, we confirm that this information is conserved and can be used for (1) clustering of patient samples, (2) identification of significant clusters based on real biological complexes, and (3) overcoming consistency and coverage issues prevalent in proteomics data sets.

Relative protein quantification by MS/MS using the tandem mass tag technology

The determination of protein changes related to stimuli such as pathological conditions is the core task of many proteomic studies. In the past decade, concomitantly to the increasing role of mass spectrometry (MS), several strategies have been implemented for the relative quantification of proteins with MS. Stable isotopic labels are introduced via metabolic, enzymatic, or chemical routes in different samples for their distinction during MS detection. Relative quantification is achieved by comparison of MS or tandem MS (MS/MS) signals of the differentially labeled moieties. Isobaric tagging is an elegant chemical isotope incorporation based on tags with an identical chemical structure and same total mass but with labile parts under collision-activated dissociation, the so-called reporter ions. The reporter ions are characteristic of each tag form and detected at distinct m/z. The TMT, iTRAQ, and ExacTag are examples of such technology. Experimental design, sample preparation and separation, MS acquisition parameters, and data analysis are the key steps to achieve accurate and precise quantitative measurements. We describe herein an isoelectric focusing shotgun proteomics workflow for the relative quantification of proteins in complex mixtures by MS/MS using tandem mass tags.

A network-based maximum link approach towards MS identifies potentially important roles for undetected ARRB1/2 and ACTB in liver cancer progression

Hepatocellular Carcinoma (HCC) ranks among the deadliest of cancers and has a complex etiology. Proteomics analysis using iTRAQ provides a direct way to analyse perturbations in protein expression during HCC progression from early- to late-stage but suffers from consistency and coverage issues. Appropriate use of network-based analytical methods can help to overcome these issues. We built an integrated and comprehensive Protein-Protein Interaction Network (PPIN) by merging several major databases. Additionally, the network was filtered for GO coherent edges. Significantly differential genes (seeds) were selected from iTRAQ data and mapped onto this network. Undetected proteins linked to seeds (linked proteins) were identified and functionally characterised. The process of network cleaning provides a list of higher quality linked proteins, which are highly enriched for similar biological process gene ontology terms. Linked proteins are also enriched for known cancer genes and are linked to many well-established cancer processes such as apoptosis and immune response. We found that there is an increased propensity for known cancer genes to be found in highly linked proteins. Three highly-linked proteins were identified that may play an important role in driving HCC progression - the G-protein coupled receptor signalling proteins, ARRB1/2 and the structural protein beta-actin, ACTB. Interestingly, both ARRB proteins evaded detection in the iTRAQ screen. ACTB was not detected in the original dataset derived from Mascot but was found to be strongly supported when we re-ran analysis using another protein detection database (Paragon). Identification of linked proteins helps to partially overcome the coverage issue in shotgun proteomics analysis. The set of linked proteins are found to be enriched for cancer-specific processes, and more likely so if they are more highly linked. Additionally, a higher quality linked set is derived if network-cleaning is performed prior. This form of network-based analysis complements the cluster-based approach, and can provide a larger list of proteins on which to perform functional analysis, as well as for biomarker identification.