Novel proteomic approaches for tissue analysis

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.

Proteomic profiling of H-Ras-G12V induced hypertrophic cardiomyopathy in transgenic mice using comparative LC-MS analysis of thin fresh-frozen tissue sections

Determination of disease-relevant proteomic profiles from limited tissue specimens, such as pathological biopsies and tissues from small model organisms, remains an analytical challenge and a much needed clinical goal. In this study, a transgenic mouse disease model of cardiac-specific H-Ras-G12V induced hypertrophic cardiomyopathy provided a system to explore the potential of using mass spectrometry (MS)-based proteomics to obtain a disease-relevant molecular profile from amount-limited specimens that are routinely used in pathological diagnosis. Our method employs a two-stage methanol-assisted solubilization to digest lysates prepared from 8-μm-thick fresh-frozen histological tissue sections of diseased/experimental and normal/control hearts. Coupling this approach with a nanoflow reversed-phase liquid chromatography (LC) and a hybrid linear ion trap/Fourier transform-ion cyclotron resonance MS resulted in the identification of 704 and 752 proteins in hypertrophic and wild-type (control) myocardium, respectively. The disease driving H-Ras protein along with vimentin were unambiguously identified by LC-MS in hypertrophic myocardium and cross-validated by immunohistochemistry and western blotting. The pathway analysis involving proteins identified by MS showed strong association of proteomic data with cardiovascular disease. More importantly, the MS identification and subsequent cross-validation of Wnt3a and β-catenin, in conjunction with IHC identification of phosphorylated GSK-3β and nuclear localization of β-catenin, provided evidence of Wnt/β-catenin canonical pathway activation secondary to Ras activation in the course of pathogenic myocardial hypertrophic transformation. Our method yields results indicating that the described proteomic approach permits molecular discovery and assessment of differentially expressed proteins regulating H-Ras induced hypertrophic cardiomyopathy. Selected proteins and pathways can be further investigated using immunohistochemical techniques applied to serial tissue sections of similar or different origin.

Identification of biological tissues by rapid evaporative ionization mass spectrometry

The newly developed rapid evaporative ionization mass spectrometry (REIMS) provides the possibility of in vivo, in situ mass spectrometric tissue analysis. The experimental setup for REIMS is characterized in detail for the first time, and the description and testing of an equipment capable of in vivo analysis is presented. The spectra obtained by various standard surgical equipments were compared and found highly specific to the histological type of the tissues. The tissue analysis is based on their different phospholipid distribution; the identification algorithm uses a combination of principal component analysis (PCA) and linear discriminant analysis (LDA). The characterized method was proven to be sensitive for any perturbation such as age or diet in rats, but it was still perfectly suitable for tissue identification. Tissue identification accuracy higher than 97% was achieved with the PCA/LDA algorithm using a spectral database collected from various tissue species. In vivo, ex vivo, and post mortem REIMS studies were performed, and the method was found to be applicable for histological tissue analysis during surgical interventions, endoscopy, or after surgery in pathology.

Identification of pancreatic cancer-specific cell-surface markers for development of targeting ligands

Pancreatic cancer is generally detected at later stages with a poor prognosis and a high-mortality rate. Development of theranostic imaging agents that noninvasively target pancreatic cancer by gene expression and deliver therapies directly to malignant cells could greatly improve therapeutic outcomes. Small-peptide ligands that bind cell-surface proteins and are conjugated to imaging moieties have demonstrated efficacy in cancer imaging. Identification of cancer-specific targets is a major bottleneck in the development of such agents. Herein, a method is presented that uses DNA microarray expression profiling of large sets of normal and cancer tissues to identify targets expressed in cancer but not expressed in relevant normal tissues. Identified targets are subsequently validated for protein expression using tissue microarray. Further validations are performed by quantifying expression in pancreatic cancer cells by quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR), by immunocytochemistry and immunohistochemistry, and by reviewing data and literature in public databases. Validated targets are selected for ligand development based on the existence of a known ligand or by known structure-activity relationships useful for development of novel ligands.

Gene expression profiling-based identification of cell-surface targets for developing multimeric ligands in pancreatic cancer

Multimeric ligands are ligands that contain multiple binding domains that simultaneously target multiple cell-surface proteins. Due to cooperative binding, multimeric ligands can have high avidity for cells (tumor) expressing all targeting proteins and only show minimal binding to cells (normal tissues) expressing none or only some of the targets. Identifying combinations of targets that concurrently express in tumor cells but not in normal cells is a challenging task. Here, we describe a novel approach for identifying such combinations using genome-wide gene expression profiling followed by immunohistochemistry. We first generated a database of mRNA gene expression profiles for 28 pancreatic cancer specimens and 103 normal tissue samples representing 28 unique tissue/cell types using DNA microarrays. The expression data for genes that encode proteins with cell-surface epitopes were then extracted from the database and analyzed using a novel multivariate rule-based computational approach to identify gene combinations that are expressed at an efficient binding level in tumors but not in normal tissues. These combinations were further ranked according to the proportion of tumor samples that expressed the sets at efficient levels. Protein expression of the genes contained in the top ranked combinations was confirmed using immunohistochemistry on a pancreatic tumor tissue and normal tissue microarrays. Coexpression of targets was further validated by their combined expression in pancreatic cancer cell lines using immunocytochemistry. These validated gene combinations thus encompass a list of cell-surface targets that can be used to develop multimeric ligands for the imaging and treatment of pancreatic cancer.

LC/MS identification of 12 intracellular cytoskeletal and inflammatory proteins from monocytes adherent on surface-adsorbed fibronectin-derived peptides

The extent and duration of the host response determines device efficacy, yet the mechanism is poorly understood. U937 promonocytic cells were cultured on peptide-adsorbed tissue-culture polystyrene to better understand surface-modulated intracellular events. Phosphotyrosine proteins were enriched by immunoprecipitation and analyzed by nanospray HPLC-coupled tandem mass spectrometry (LC/MS). Tyrosine-phosphorylated proteins were chosen based on physiological significance and previous densitometry results, which identified a set of proteins ranging from approximately 200 to approximately 23 kDa showing altered phosphorylation levels in response to various surface-adsorbed ligands and phosphorylation inhibitor AG18. Although LC/MS has been used for nearly a decade, its application to the field of biomaterials is relatively novel. Twelve intracellular proteins identified by nanospray LC/MS are potentially related to the host response. Eight of the twelve proteins are related to the cytoskeleton including: moesin, heat shock protein 90beta, alpha-tubulin, elongation factor 1alpha, beta actin, vimentin, plasminogen activator inhibitor 2, and heterogeneous ribonuclear protein A2. The remaining four proteins: high mobility group box 1, caspase recruitment domain 5, glycoprotein 96, and heterogeneous nuclear ribonucleoprotein D0 modulate inflammation. The specific effect each peptide has upon modulating the phosphorylation state of these proteins cannot be determined from this work; however, 12 viable targets have been identified for further investigation into the role each plays in the surface-mediated monocyte response.

Infrared-based protein detection arrays for quantitative proteomics

The advancement of efficient technologies to comply with the needs of systems biology and drug discovery has so far not received adequate attention. A substantial bottleneck for the time-resolved quantitative description of signaling networks is the limited throughput and the inadequate sensitivity of currently established methods. Here, we present an improved protein microarray-based approach towards the sensitive detection of proteins in the fg-range which is based on signal detection in the near-infrared range. The high sensitivity of the assay permits the specific quantification of proteins derived from as little as only 20,000 cells with an error rate of only 5%. The capacity is limited to the analysis of up to 500 different samples per microarray. Protein abundance is determined qualitatively, and quantitatively, if recombinant protein is available. This novel approach was called IPAQ (infrared-based protein arrays with quantitative readout). IPAQ offers a highly sensitive experimental approach superior to the established standard protein quantification technologies, and is suitable for quantitative proteomics. Employing the IPAQ approach, a detailed analysis of activated signaling networks in biopsy samples and of crosstalk between signaling modules as required in drug discovery strategies can easily be performed.

Methods for samples preparation in proteomic research

Sample preparation is one of the most crucial processes in proteomics research. The results of the experiment depend on the condition of the starting material. Therefore, the proper experimental model and careful sample preparation is vital to obtain significant and trustworthy results, particularly in comparative proteomics, where we are usually looking for minor differences between experimental-, and control samples. In this review we discuss problems associated with general strategies of samples preparation, and experimental demands for these processes.

Layered expression scanning: multiplex molecular analysis of diverse life science platforms

With the advent of the genomic era, there is an increasing use of high-throughput techniques to generate transcriptome- and proteome-based profiles of biological specimens. Each of these methodologies offers a unique window into the inner workings of cell and tissue samples. Often, these studies generate large data sets and provide investigators with a substantial number of candidate dysregulated genes and pathways. Follow-up studies are then undertaken to independently validate the original findings and to extend the study to additional samples or more quantitative measurements. Although there are several methods available for these validation efforts, they are often tedious and laborious to perform; thus, additional tools that enable this task are needed. One such approach is layered expression scanning (LES), a new technique developed via a cooperative research and development agreement (CRADA) between the National Cancer Institute and 20/20 GeneSystems, Inc. The technique is based on the movement of biomolecules from a two-dimensional life science platform (histological tissue section, electrophoresis gel, multi-well plate, etc.) through a set of analysis membranes while maintaining the original distribution pattern of the molecules. Each membrane measures one analyte and the data are then mapped back to the original specimen, permitting each component of the life science platform to be studied in detail. LES can be configured in several different ways depending on the goals of the study. In this review, we summarize the use of the LES technique for a variety of biological applications.

Effect of surface-adsorbed proteins and phosphorylation inhibitor AG18 on intracellular protein expression in adherent macrophages

Macrophages are believed to play an important role in the host inflammatory response to implanted biomaterials. However, the mechanism of macrophage adhesion to protein-adsorbed substrates and the subsequent activation and inflammation is unresolved. Previously the effect of various surface-adsorbed proteins and increasing concentrations of phosphorylation inhibitor AG18 on intracellular protein expression levels in adherent human monocytic cell line U937 was identified using SDS-PAGE and densitometry. The protein ligands and AG18 concentrations up or down regulated the expression of a set of proteins ranging from approximately 200 to approximately 23 kDa. In the present work, HPLC coupled tandem mass spectroscopy (LC/MS) was used to identify proteins in these bands. We hypothesized that key proteins in macrophage adhesion and activation could be identified by observing protein expression resulting from various surface-adsorbed ligands and AG18 concentrations. Increasing concentrations of AG18 down or up regulate protein expression in adherent U937 on PBS-adsorbed TCPS at approximately 52, approximately 42 and approximately 23 kDa. AG18 concentrations had no effect on cells on albumin (Alb)-adsorbed surfaces but regulated different protein expression in adherent U937 on fibronectin (FN)-adsorbed TCPS at 40 and 80 microm AG18. Both Alb and FN regulate distinct sets of proteins in adherent cells as surface-adsorbed ligands. Based on the data from LC/MS, both surface associated ligand and increasing concentrations of AG18 modulate shifts in intracellular signaling.