Tissue proteomics for cancer biomarker development: laser microdissection and 2D-DIGE

Establishment of combined analytical method to extract the genes of interest from transcriptome data

Techniques for analyzing genome-wide expression profiles, such as the microarray technique and next-generation sequencers, have been developed. While these techniques can provide a lot of information about gene expression, selection of genes of interest is complicated because of excessive gene expression data. Thus, many researchers use statistical methods or fold change as screening tools for finding gene sets whose expression is altered between groups, which may result in the loss of important information. In the present study, we aimed to establish a combined method for selecting genes of interest with a small magnitude of alteration in gene expression by coupling with proteome analysis. We used hypercholesterolemic rats to examine the effects of a crude herbal drug on gene expression and proteome profiles. We could not select genes of interest by using standard methods. However, by coupling with proteome analysis, we found several effects of the crude herbal drug on gene expression. Our results suggest that this method would be useful in selecting gene sets with expressions that do not show a large magnitude of alteration.

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Herbal crude drug SJG had mild effects on the gene expression profile.

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It was difficult to select genes altered by SJG with conventional methods.

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We established analytical method for transcriptome by using proteome experiments.

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We identified genes of interest that could not be selected by conventional methods.

Identification and validation of potential new biomarkers for prostate cancer diagnosis and prognosis using 2D-DIGE and MS

This study was designed to identify and validate potential new biomarkers for prostate cancer and to distinguish patients with and without biochemical relapse. Prostate tissue samples analyzed by 2D-DIGE (two-dimensional difference in gel electrophoresis) and mass spectrometry (MS) revealed downregulation of secernin-1 (P < 0.044) in prostate cancer, while vinculin showed significant upregulation (P < 0.001). Secernin-1 overexpression in prostate tissue was validated using Western blot and immunohistochemistry while vinculin expression was validated using immunohistochemistry. These findings indicate that secernin-1 and vinculin are potential new tissue biomarkers for prostate cancer diagnosis and prognosis, respectively. For validation, protein levels in urine were also examined by Western blot analysis. Urinary vinculin levels in prostate cancer patients were significantly higher than in urine from nontumor patients (P = 0.006). Using multiple reaction monitoring-MS (MRM-MS) analysis, prostatic acid phosphatase (PAP) showed significant higher levels in the urine of prostate cancer patients compared to controls (P = 0.012), while galectin-3 showed significant lower levels in the urine of prostate cancer patients with biochemical relapse, compared to those without relapse (P = 0.017). Three proteins were successfully differentiated between patients with and without prostate cancer and patients with and without relapse by using MRM. Thus, this technique shows promise for implementation as a noninvasive clinical diagnostic technique.

Discovery and validation of graft-versus-host disease biomarkers

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is the most effective tumor immunotherapy available. Although allo-HSCT provides beneficial graft-versus-tumor effects, acute GVHD (aGVHD) is the primary source of morbidity and mortality after HSCT. Diagnosis of aGVHD is typically based on clinical symptoms in one or more of the main target organs (skin, liver, gastrointestinal tract) and confirmed by biopsy. However, currently available diagnostic and staging tools often fail to identify patients at higher risk of GVHD progression, unresponsiveness to therapy, or death. In addition, there are shortcomings in the prediction of GVHD before clinical signs develop, indicating the urgent need for noninvasive and reliable laboratory tests. Through the continuing evolution of proteomics technologies seen in recent years, plasma biomarkers have been identified and validated as promising diagnostic tools for GVHD and prognostic tools for nonrelapse mortality. These biomarkers may facilitate timely and selective therapeutic intervention but should be more widely validated and incorporated into a new grading system for risk stratification of patients and better-customized treatment. This review identifies biomarkers for detecting GVHD, summarizes current information on aGVHD biomarkers, proposes future prospects for the blinded evaluation of these biomarkers, and discusses the need for biomarkers of chronic GVHD.

Heterogeneous nuclear ribonucleoprotein K (hnRNP K) is a tissue biomarker for detection of early hepatocellular carcinoma in patients with cirrhosis

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors occurring mainly in patients with chronic liver disease. Detection of early HCC is critically important for treatment of these patients.

Methods

We employed a proteomic profiling approach to identify potential biomarker for early HCC detection. Based on Barcelona Clinic Liver Cancer (BCLC) staging classification, 15 early HCC and 25 late HCC tissue samples from post-operative HCC patients and their clinicopathological data were used for the discovery of biomarkers specific for the detection of early HCC. Differential proteins among cirrhotic, early, and late tissue samples were separated by two-dimensional gel electrophoresis (2-DE) and subsequently identified by mass spectrometry (MS). Receiver operating characteristic (ROC) curves analysis were performed to find potential biomarkers associated with early HCC. Diagnosis performance of the biomarker was obtained from diagnosis test.

Results

Protein spot SSP2215 was found to be significantly overexpressed in HCC, particularly in early HCC, and identified as heterogeneous nuclear ribonucleoprotein K (hnRNP K) by tandem mass spectrometry (MALDI TOF/TOF). The overexpression in HCC was subsequently validated by western blot and immunohistochemistry. ROC curve analysis showed that hnRNP K intensity could detect early HCC at 66.67 % sensitivity and 84 % specificity, which was superior to serum α-fetoprotein (AFP) in detection of early HCC. Furthermore, the diagnosis test demonstrated, when combined with hnRNP K and serum AFP as biomarker panel to detect early HCC at different cut-off value, the sensitivity and specificity could be enhanced to 93.33 % and 96 %, respectively.

Conclusions

hnRNP K is a potential tissue biomarker, either alone or in combination with serum AFP, for detection of early HCC. High expression of hnRNP K could be helpful to discriminate early HCC from a nonmalignant nodule, especially for patients with liver cirrhosis.

Protein analysis through Western blot of cells excised individually from human brain and muscle tissue

Comparing protein levels from single cells in tissue has not been achieved through Western blot. Laser capture microdissection allows for the ability to excise single cells from sectioned tissue and compile an aggregate of cells in lysis buffer. In this study we analyzed proteins from cells excised individually from brain and muscle tissue through Western blot. After we excised individual neurons from the substantia nigra of the brain, the accumulated surface area of the individual cells was 120,000, 24,000, 360,000, 480,000, 600,000 μm2. We used an optimized Western blot protocol to probe for tyrosine hydroxylase in this cell pool. We also took 360,000 μm2 of astrocytes (1700 cells) and analyzed the specificity of the method. In muscle we were able to analyze the proteins of the five complexes of the electron transport chain through Western blot from 200 human cells. With this method, we demonstrate the ability to compare cell-specific protein levels in the brain and muscle and describe for the first time how to visualize proteins through Western blot from cells captured individually.

Identification and Characterization of Cell Wall Proteins of a Toxic Dinoflagellate Alexandrium catenella Using 2-D DIGE and MALDI TOF-TOF Mass Spectrometry

The cell wall is an important subcellular component of dinoflagellate cells with regard to various aspects of cell surface-associated ecophysiology, but the full range of cell wall proteins (CWPs) and their functions remain to be elucidated. This study identified and characterized CWPs of a toxic dinoflagellate, Alexandrium catenella, using a combination of 2D fluorescence difference gel electrophoresis (DIGE) and MALDI TOF-TOF mass spectrometry approaches. Using sequential extraction and temperature shock methods, sequentially extracted CWPs and protoplast proteins, respectively, were separated from A. catenella. From the comparison between sequentially extracted CWPs labeled with Cy3 and protoplast proteins labeled with Cy5, 120 CWPs were confidently identified in the 2D DIGE gel. These proteins gave positive identification of protein orthologues in the protein database using de novo sequence analysis and homology-based search. The majority of the prominent CWPs identified were hypothetical or putative proteins with unknown function or no annotation, while cell wall modification enzymes, cell wall structural proteins, transporter/binding proteins, and signaling and defense proteins were tentatively identified in agreement with the expected role of the extracellular matrix in cell physiology. This work represents the first attempt to investigate dinoflagellate CWPs and provides a potential tool for future comprehensive characterization of dinoflagellate CWPs and elucidation of their physiological functions.

Quantitative proteomic analyses of crop seedlings subjected to stress conditions; a commentary

Quantitative proteomics is one of the analytical approaches used to clarify crop responses to stress conditions. Recent remarkable advances in proteomics technologies allow for the identification of a wider range of proteins than was previously possible. Current proteomic methods fall into roughly two categories: gel-based quantification methods, including conventional two-dimensional gel electrophoresis and two-dimensional fluorescence difference gel electrophoresis, and MS-based quantification methods consists of label-based and label-free protein quantification approaches. Although MS-based quantification methods have become mainstream in recent years, gel-based quantification methods are still useful for proteomic analyses. Previous studies examining crop responses to stress conditions reveal that each method has both advantages and disadvantages in regard to protein quantification in comparative proteomic analyses. Furthermore, one proteomics approach cannot be fully substituted by another technique. In this review, we discuss and highlight the basis and applications of quantitative proteomic analysis approaches in crop seedlings in response to flooding and osmotic stress as two environmental stresses.

Proteomic analysis of pancreatic intraepithelial neoplasia and pancreatic carcinoma in rat models

AIM

To detect the proteomic variabilities of pancreatic intraepithelial neoplasia (PanIN) and pancreatic carcinoma (PC) induced by 7,12-dimethylbenzanthracene (DMBA) in rat models and to identify potential biomarkers.

METHODS

Sixty adult male Sprague Dawley rats were randomized into three groups. The rats had DMBA implanted into their pancreas for one (n = 20) or two months (n = 20) or assigned to the normal group (n = 20). The rats were killed after one or two months, and were evaluated histopathologically. Three tissue samples from each group of rats with either normal pancreas, PanIN (PanIN-2) or PC were examined by 2D-DIGE. The different expression spot features were analyzed by matrix-assisted laser desorption/ionization-time of flight/time of flight (MALDI-TOF/TOF) tandem mass spectrometry. The expression of enolase 1, a differentially expressed protein, was identified by immunohistochemistry.

RESULTS

There was significant difference in the proportions of neoplastic changes between the 1- and 2-mogroups (P = 0.0488). There was an increase in the frequency of adenocarcinomas in the 2-mo group compared with the 1-mo group (P = 0.0309). No neoplastic changes were observed in any of the animals in the normal group. Enolase 1, pancreatic ELA3B, necdin, Hbp23, CHD3, hnRNP A2/B1, Rap80, and Gnb2l1 were up-regulated in the PanIN and PC tissues, and CEL, TPT1, NME2, PCK2, an unnamed protein product, and glycine C-acetyltransferase were down-regulated in the PanIN and PC tissues. The immunohistochemical results showed that enolase 1 expression was up-regulated in the pancreatic cancer tissues of rats and humans.

CONCLUSION

The pancreatic protein expression changes induced by DMBA suggest potential molecular targets for the early diagnosis and treatment of PC.

Mass spectrometric characterization of protein structure details refines the proteome signature for invasive ductal breast carcinoma

Early diagnosis as well as individualized therapies are necessary to reduce the mortality of breast cancer, and personalized patient care strategies rely on novel prognostic or predictive factors. In this study, with six breast cancer patients, 2D gel analysis was applied for studying protein expression differences in order to distinguish invasive ductal breast carcinoma, the most frequent breast tumor subtype, from control samples. In total, 1203 protein spots were assembled in a 2D reference gel. Differentially abundant spots were subjected to peptide mass fingerprinting for protein identification. Twenty proteins with their corresponding 38 differentially expressed 2D gel spots were contained in our previously reported proteome signature, suggesting that distinct protein forms were contributing. In-depth MS/MS measurements enabled analyses of protein structure details of selected proteins. In protein spots that significantly contributed to our signature, we found that glyceraldehyde-3-phosphate dehydrogenase was N-terminally truncated, pyruvate kinase M2 and nucleoside diphosphate kinase A but not other isoforms of these proteins were of importance, and nucleophosmin phosphorylation at serine residues 106 and 125 were clearly identified. Principle component analysis and hierarchical clustering with normalized quantitative data from the 38 spots resulted in accurate separation of tumor from control samples. Thus, separation of tissue samples as in our initial proteome signature could be confirmed even with a different proteome analysis platform. In addition, detailed protein structure investigations enabled refining our proteome signature for invasive ductal breast carcinoma, opening the way to structure-/function studies with respect to disease processes and/or therapeutic intervention.

Omic approaches in environmental issues

Biomonitoring requires the application of batteries of different biomarkers, as environmental contaminants induce multiple responses in organisms that are not necessarily correlated. Omic technologies were proposed as an alternative to conventional biomarkers since these techniques quantitatively monitor many biological molecules in a high-throughput manner and thus provide a general appraisal of biological responses altered by exposure to contaminants. As the studies using omic technologies increase, it is becoming clear that any single omic approach may not be sufficient to characterize the complexity of ecosystems. This work aims to provide a preliminary working scheme for the use of combined transcriptomic and proteomic methodologies in environmental biomonitoring. There are difficulties in working with nonmodel organisms as bioindicators when combining several omic approaches. As a whole, our results with heterologous microarrays in M. spretus and suppressive subtractive hybridization (SSH) in P. clarkii indicated that animals sustaining a heavy pollution burden exhibited an enhanced immune response and/or cell apoptosis. The proteomic studies, although preliminary, provide a holistic insight regarding the manner by which pollution shifts protein intensity in two-dimensional gel electrophoresis (2-DE), completing the transcriptomic approach. In our study, the sediment element concentration was in agreement with the intensity of protein expression changes in C. maenas crabs. In conclusion, omics are useful technologies in addressing environmental issues and the determination of contamination threats.

Mass spectrometry-based clinical proteomics: head-and-neck cancer biomarkers and drug-targets discovery

Mass spectrometry (MS)-based proteomics is a rapidly developing technology for both qualitative and quantitative analyses of proteins, and investigations into protein posttranslational modifications, subcellular localization, and interactions. Recent advancements in MS have made tremendous impact on the throughput and comprehensiveness of cancer proteomics, paving the way to unraveling deregulated cellular pathway networks in human malignancies. In turn, this knowledge is rapidly being translated into the discovery of novel potential cancer markers (PCMs) and targets for molecular therapeutics. Head-and-neck cancer is one of the most morbid human malignancies with an overall poor prognosis and severely compromised quality of life. Early detection and novel therapeutic strategies are urgently needed for more effective disease management. The characterizations of protein profiles of head-and-neck cancers and non-malignant tissues, with unprecedented sensitivity and precision, are providing technology platforms for identification of novel PCMs and drug targets. Importantly, low-abundance proteins are being identified and characterized, not only from the tumor tissues, but also from bodily fluids (plasma, saliva, and urine) in a high-throughput and unbiased manner. This review is a critical appraisal of recent advances in MS-based proteomic technologies and platforms for facilitating the discovery of biomarkers and novel drug targets in head-and-neck cancer. A major challenge in the discovery and verification of these cancer biomarkers is the typically limited availability of well-characterized and adequately stored clinical samples in tumor and sera banks, collected using recommended procedures, and with detailed information on clinical, pathological parameters, and follow-up. Most biomarker discovery studies use limited number of clinical samples and verification of cancer markers in large number of samples is beyond the scope of a single laboratory. The validation of these potential markers in large sample cohorts in multicentric studies is needed for their translation from the bench to the bedside.

Integrating high-throughput technologies in the quest for effective biomarkers for ovarian cancer

Despite widespread interest, few serum biomarkers have been introduced to the clinic over the past 20 years. Each approach to ovarian cancer biomarker discovery has its own advantages and disadvantages and it seems likely that a global biomarker discovery platform that mines all possible sources for biomarkers might be more useful. Such data could be combined with information from relevant microarray data, bioinformatic analyses and literature searches. This proposed integrated systems biology approach has the potential to yield promising ovarian cancer markers for diagnosis, prognosis and monitoring of patients during therapy.

Current advances in tumor proteomics and candidate biomarkers for hepatic cancer

Tumor proteomics apply proteomics techniques to tumor biological research, mainly by screening candidate biomarkers for early tumor diagnosis, prognosis and treatment. Hepatocellular carcinoma (HCC) is a type of malignant tumor with one of the highest death rates in the world. With the advent of the post-genomic age, tumor biological research developing the technology of proteomics has become a major focus of researchers. The discovery of novel candidate biomarkers is one of crucial problems for the early diagnosis of HCC. In general, there are three distinct types of candidate biomarkers for HCC based on different areas: biochemical biomarkers, antigenic biomarkers and epigenetic biomarkers. This review mainly discusses current advances in the problems and prospects of candidate biomarker for the early diagnosis of HCC, discovered by technologies of tumor proteomics.

Mass spectrometry-based label-free quantitative proteomics

In order to study the differential protein expression in complex biological samples, strategies for rapid, highly reproducible and accurate quantification are necessary. Isotope labeling and fluorescent labeling techniques have been widely used in quantitative proteomics research. However, researchers are increasingly turning to label-free shotgun proteomics techniques for faster, cleaner, and simpler results. Mass spectrometry-based label-free quantitative proteomics falls into two general categories. In the first are the measurements of changes in chromatographic ion intensity such as peptide peak areas or peak heights. The second is based on the spectral counting of identified proteins. In this paper, we will discuss the technologies of these label-free quantitative methods, statistics, available computational software, and their applications in complex proteomics studies.

Towards a proteome signature for invasive ductal breast carcinoma derived from label-free nanoscale LC-MS protein expression profiling of tumorous and glandular tissue

As more and more alternative treatments become available for breast carcinoma, there is a need to stratify patients and individual molecular information seems to be suitable for this purpose. In this study, we applied label-free protein quantitation by nanoscale LC-MS and investigated whether this approach could be used for defining a proteome signature for invasive ductal breast carcinoma. Tissue samples from healthy breast and tumor were collected from three patients. Protein identifications were based on LC-MS peptide fragmentation data which were obtained simultaneously to the quantitative information. Hereby, an invasive ductal breast carcinoma proteome signature was generated which contains 60 protein entries. The on-column concentrations for osteoinductive factor, vimentin, GAP-DH, and NDKA are provided as examples. These proteins represent distinctive gene ontology groups of differentially expressed proteins and are discussed as risk markers for primary tumor pathogenesis. The developed methodology has been found well applicable in a clinical environment in which standard operating procedures can be kept; a prerequisite for the definition of molecular parameter sets that shall be capable for stratification of patients.

Cell-based proteome analysis: the first stage in the pipeline for biomarker discovery

The early detection of a distinct disease is crucial for a successful treatment and depends on a sensitive as well as specific diagnosis. In last years tremendous attempts were undertaken to identify new biomarker applying proteomics, but no relevant candidate has been identified for clinical application. Although proteomics is enabling quantitative and qualitative analysis of proteins within complex mixtures it could not significantly contribute to this field. Therefore, different proteomics approaches have been established focusing on the direct analysis of cell populations involved in pathogenic processes to identify candidate biomarkers even for in vitro diagnosis. Here, we will outline approaches applying cell- and tissue based proteome analysis as the first decisive step in the pipeline for the discovery of new diagnostic biomarkers. We will show examples for analysing precursor lesions of the pancreatic ductal adenocarcinoma (PDAC), nephron glomeruli and fibrotic and non-fibrotic liver tissue. This article provides also an overview about currently available techniques in the field of cell enrichment and quantitative proteome analysis of lowest amounts of sample.

N-linked glycoproteomic analysis of formalin-fixed and paraffin-embedded tissues

Formalin-fixed, paraffin-embedded (FFPE) tissues have been used to discover disease-associated protein changes using mass spectrometry. Protein post-translational modifications such as glycosylation are known to associate with disease development. In this study, we investigated whether FFPE tissues preserve such modifications and therefore can be used as specimen of choice to identify the disease-associated modifications. We isolated the glycopeptides from the tryptic digest of frozen and FFPE lung tissues using solid-phase extraction of glycopeptides and analyzed them using mass spectrometry. The glycopeptides identified from FFPE lung tissue were compared to the ones from frozen lung tissue regarding their relative abundance, unique glycosylation sites, and subcellular locations. The results from our study confirmed that glycosylation in FFPE tissues are preserved and FFPE tissues can be used for discovery of new disease associated changes in protein modifications. Furthermore, we demonstrated the feasibility of applying the strategy of glycopeptide isolation from tryptic peptides of FFPE tissue to other tissues such as liver and heart.