Tissue profiling by mass spectrometry: a review of methodology and applications

Matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) has become a valuable tool to address a broad range of questions in many areas of biomedical research. One such application allows spectra to be obtained directly from intact tissues, termed "profiling" (low resolution) and "imaging" (high resolution). In light of the fact that MALDI tissue profiling allows over a thousand peptides and proteins to be rapidly detected from a variety of tissues, its application to disease processes is of special interest. For example, protein profiles from tumors may allow accurate prediction of tumor behavior, diagnosis, and prognosis and uncover etiologies underlying idiopathic diseases. MALDI MS, in conjunction with laser capture microdissection, is able to produce protein expression profiles from a relatively small number of cells from specific regions of heterogeneous tissue architectures. Imaging mass spectrometry enables the investigator to assess the spatial distribution of proteins, drugs, and their metabolites in intact tissues. This article provides an overview of several tissue profiling and imaging applications performed by MALDI MS, including sample preparation, matrix selection and application, histological staining prior to MALDI analysis, tissue profiling, imaging, and data analysis. Several applications represent direct translation of this technology to clinically relevant problems.     

Matrix-assisted laser desorption/ionization imaging mass spectrometry: a promising technique for reproductive research

Matrix-assisted laser desorption/ionization (MALDI) tissue imaging mass spectrometry is particularly promising among the numerous applications of mass spectrometry. It is used for probing and analyzing the spatial arrangement of a wide range of molecules, including proteins, peptides, lipids, drugs, and metabolites, directly in thin slices of tissue. In the field of proteomics, the technology avoids tedious and time-consuming extraction and fractionation steps classically required for sample analysis. MALDI imaging mass spectrometry is increasingly recognized as a powerful method for clinical proteomics, particularly in cancer research. The technology has particular potential for the discovery of new tissue biomarker candidates, classification of tumors, early diagnosis or prognosis, elucidating pathogenesis pathways, and therapy monitoring. Over recent years, MALDI imaging mass spectrometry has been used for molecular profiling and imaging directly in male and female reproductive tissues. This review will consider some of the recent publications in the field, addressing a range of issues covering embryo development, gene expression product profiling during gametogenesis, and seeking and identifying biomarkers of reproductive cancers. The wealth of advances in mass spectrometry imaging will inevitably attract biologists and clinicians as the advantages and power of this technology become more widely known. This review will also discuss bottlenecks and the many technical issues that remain to be resolved before laboratories in the field can adopt the technology. We foresee that MALDI imaging mass spectrometry will have a major impact in reproductive research by opening new avenues to the understanding of various molecular mechanisms and the diagnosis of reproductive pathologies.     

Mass spectrometry-based expression profiling of clinical prostate cancer

The maturation of MS technologies has provided a rich opportunity to interrogate protein expression patterns in normal and disease states by applying expression protein profiling methods. Major goals of this research strategy include the identification of protein biomarkers that demarcate normal and disease populations, and the identification of therapeutic biomarkers for the treatment of diseases such as cancer (Celis, J. E., and Gromov, P. (2003) Proteomics in translational cancer research: Toward an integrated approach. Cancer Cell 3, 9-151). Prostate cancer is one disease that would greatly benefit from implementing MS-based expression profiling methods because of the need to stratify the disease based on molecular markers. In this review, we will summarize the current MS-based methods to identify and validate biomarkers in human prostate cancer. Lastly, we propose a reverse proteomic approach implementing a quantitative MS research strategy to identify and quantify biomarkers implicated in prostate cancer development. With this approach, the absolute levels of prostate cancer biomarkers will be identified and quantified in normal and diseased samples by measuring the levels of native peptide biomarkers in relation to a chemically identical but isotopically labeled reference peptide. Ultimately, a centralized prostate cancer peptide biomarker expression database could function as a repository for the identification, quantification, and validation of protein biomarker(s) during prostate cancer progression in men.     

Lectin capture strategies combined with mass spectrometry for the discovery of serum glycoprotein biomarkers

The application of mass spectrometry to identify disease biomarkers in clinical fluids like serum using high throughput protein expression profiling continues to evolve as technology development, clinical study design, and bioinformatics improve. Previous protein expression profiling studies have offered needed insight into issues of technical reproducibility, instrument calibration, sample preparation, study design, and supervised bioinformatic data analysis. In this overview, new strategies to increase the utility of protein expression profiling for clinical biomarker assay development are discussed with an emphasis on utilizing differential lectin-based glycoprotein capture and targeted immunoassays. The carbohydrate binding specificities of different lectins offer a biological affinity approach that complements existing mass spectrometer capabilities and retains automated throughput options. Specific examples using serum samples from prostate cancer and hepatocellular carcinoma subjects are provided along with suggested experimental strategies for integration of lectin-based methods into clinical fluid expression profiling strategies. Our example workflow incorporates the necessity of early validation in biomarker discovery using an immunoaffinity-based targeted analytical approach that integrates well with upstream discovery technologies.     

Approaching MALDI molecular imaging for clinical proteomic research: current state and fields of application

MALDI imaging mass spectrometry (‘MALDI imaging’) is an increasingly recognized technique for biomarker research. After years of method development in the scientific community, the technique is now increasingly applied in clinical research. In this article, we discuss the use of MALDI imaging in clinical proteomics and put it in context with classical proteomics techniques. We also highlight a number of upcoming challenges for personalized medicine, development of targeted therapies and diagnostic molecular pathology where MALDI imaging could help.     

MALDI imaging of formalin-fixed paraffin-embedded tissues: application to model animals of Parkinson disease for biomarker hunting

A common technique for the long-term storage of tissues in hospitals and clinical laboratories is preservation in formalin-fixed paraffin-embedded (FFPE) blocks. Such tissues stored for more than five years have not been useful for proteomic studies focused on biomarker discovery. Recently, MS-based proteomic analyses of FFPE showed positive results on blocks stored for less than 2 days. However, most samples are stored for more than one year, and thus our objective was to establish a novel strategy using as a model system 6-hydroxydopamine (6-OHDA) treated rat brain tissues stored in FFPE blocks for more than 9 years. We examined MALDI tissue profiling combining the use of automatic spotting of the MALDI matrix with in situ tissue enzymatic digestion. On adjacent sections, the identification of compounds is carried out by tissue digestion followed by nanoLC/MS-MS analysis. The combination of these approaches provides MALDI direct analysis, MALDI/MS imaging, as well as the localization of a large number of proteins. This method is validated since the analyses confirmed that ubiquitin, trans-elongation factor 1, hexokinase, and the Neurofilament M are down-regulated as previously shown in human or Parkinson animal models. In contrast, peroxidoredoxin 6, F1 ATPase, and alpha-enolase are up-regulated. In addition, we uncovered three novel putative biomarkers, the trans-elongation factor 1 (eEF1) and the collapsin response mediator 1 and 2 from protein libraries. Finally, we validate the CRMP-2 protein using immunocytochemistry and MALDI imaging based on the different ions from trypsic digestion of the protein. The access to archived FFPE tissue using MALDI profiling and imaging opens a whole new area in clinical studies and biomarker discovery from hospital biopsy libraries.     

Inconvenient truth: Cancer biomarker development by using proteomics

A biomarker is a crucial tool for measuring the progress of disease and the effects of treatment for better clinical outcomes in cancer patients. Diagnostic, predictive, and prognostic biomarkers are required in various clinical settings. The proteome, a functional translation of the genome, is considered a rich source of biomarkers; therefore, sizable time and funding have been spent in proteomics to develop biomarkers. Although significant progress has been made in technologies toward comprehensive protein expression profiling, and many biomarker candidates published, none of the reported biomarkers have proven to be beneficial for cancer patients. The present deceleration in biomarker research can be attributed to technical limitations. Additional efforts are required to further technical progress; however, there are many examples demonstrating that problems in biomarker research are not so much with the technology but in the study design. In the study of biomarkers for early diagnosis, candidates are screened and validated by comparing cases and controls of similar sample size, and the low prevalence of disease is often ignored. Although it is reasonable to take advantage of multiple rather than single biomarkers when studying diverse disease mechanisms, the annotation of individual components of reported multiple biomarkers does not often explain the variety of molecular events underlying the clinical observations. In tissue biomarker studies, the heterogeneity of disease tissues and pathological observations are often not considered, and tissues are homogenized as a whole for protein extraction. In addition to the challenge of technical limitations, the fundamental aspects of biomarker development in a disease study need to be addressed. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.     

Approaching MALDI molecular imaging for clinical proteomic research: current state and fields of application

MALDI imaging mass spectrometry ('MALDI imaging') is an increasingly recognized technique for biomarker research. After years of method development in the scientific community, the technique is now increasingly applied in clinical research. In this article, we discuss the use of MALDI imaging in clinical proteomics and put it in context with classical proteomics techniques. We also highlight a number of upcoming challenges for personalized medicine, development of targeted therapies and diagnostic molecular pathology where MALDI imaging could help.     

MALDI mass spectrometry in prostate cancer biomarker discovery

Matrix-assisted laser desorption/ionisation (MALDI) mass spectrometry (MS) is a highly versatile and sensitive analytical technique, which is known for its soft ionisation of biomolecules such as peptides and proteins. Generally, MALDI MS analysis requires little sample preparation, and in some cases like MS profiling it can be automated through the use of robotic liquid-handling systems. For more than a decade now, MALDI MS has been extensively utilised in the search for biomarkers that could aid clinicians in diagnosis, prognosis, and treatment decision making. This review examines the various MALDI-based MS techniques like MS imaging, MS profiling and proteomics in-depth analysis where MALDI MS follows fractionation and separation methods such as gel electrophoresis, and how these have contributed to prostate cancer biomarker research. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.     

MALDI-TOFMS compared with other polyphasic taxonomy approaches for the identification and classification of Bacillus pumilus spores

To verify the efficacy of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) protein profiling for identifying and differentiating bacterial species, several strains of Bacillus pumilus were examined in a thorough taxonomic study incorporating a polyphasic approach. Sixteen isolates of putative B. pumilus isolated from spacecraft assembly facilities, the Mars Odyssey spacecraft, and the International Space Station, were characterized for their biochemical and molecular profiles using the Biolog system, DNA techniques, and MALDI-TOFMS protein profiling. MALDI-TOFMS protein profiling was more accurate than Biolog metabolic profiling, more discriminating than 16S rDNA sequence analysis, and complemented the results of gyrB sequence analysis and DNA-DNA hybridization for the identification of the B. pumilus spores. This is the first report whereby MALDI-TOFMS generated protein profiles from a set of microbes is compared directly with DNA-DNA hybridization yielding a positive correlation. Unique, cluster-specific biomarker peaks have been identified in the spores of the B. pumilus examined in this study. MALDI-TOFMS protein profiling is a rapid and simple analysis and has been demonstrated as a useful taxonomic tool for differentiating spores of the genus Bacillus. For practical purposes, it would be ideal (and necessary) to have a publicly available, standardized MALDI profile database, to facilitate the use of the technique as a diagnostic method to differentiate bacterial species.     

Intact protein profiling in breast cancer biomarker discovery: Protein identification issue and the solutions based on 3D protein separation,bottom‐up and top‐down mass spectrometry

Proteomics profiling of intact proteins based on MALDI‐TOF MS and derived platforms has been used in cancer biomarker discovery studies. This approach suffers from a number of limitations such as low resolution, low sensitivity, and that no knowledge is available on the identity of the respective proteins in the discovery mode. Nevertheless, it remains the most high‐throughput, untargeted mode of clinical proteomics studies to date. Here we compare key protein separation and MS techniques available for protein biomarker identification in this type of studies and define reasons of uncertainty in protein peak identity. As a result of critical data analysis, we consider 3D protein separation and identification workflows as optimal procedures. Subsequently, we present a new protocol based on 3D LC‐MS/MS with top‐down at high resolution that enabled the identification of HNRNP A2/B1 intact peptide as correlating with the estrogen receptor expression in breast cancer tissues. Additional development of this general concept toward next generation, top‐down based protein profiling at high resolution is discussed.     

A new versatile peptide-based size exclusion chromatography platform for global profiling and quantitation of candidate biomarkers in hepatocellular carcinoma specimens

Disease biomarkers are predicted to be in low abundance; thus, the most crucial step of biomarker discovery is the efficient fractionation of clinical samples into protein sets that define disease stages and/or predict disease development. For this purpose, we developed a new platform that uses peptide-based size exclusion chromatography (pep-SEC) to quantify disease biomarker candidates. This new platform has many advantages over previously described biomarker profiling platforms, including short run time, high resolution, and good reproducibility, which make it suitable for large-scale analysis. We combined this platform with isotope labeling and label-free methods to identify and quantitate differentially expressed proteins in hepatocellular carcinoma (HCC) tissues. When we combined pep-SEC with a gas phase fractionation method, which broadens precursor ion selection, the protein coverage was significantly increased, which is critical for the global profiling of HCC specimens. Furthermore, pep-SEC-LC-MS/MS analysis enhanced the detection of low-abundance proteins (e.g. insulin receptor substrate 2 and carboxylesterase 1) and glycopeptides in HCC plasma. Thus, our pep-SEC platform is an efficient and versatile pre-fractionation system for the large-scale profiling and quantitation of candidate biomarkers in complex disease proteomes.     

Antibody microarrays: current status and key technological advances

Antibody-based microarrays are among the novel classes of rapidly evolving proteomic technologies that holds great promise in biomedicine. Miniaturized microarrays (< 1 cm2) can be printed with thousands of individual antibodies carrying the desired specificities, and with biological sample (e.g., an entire proteome) added, virtually any specifically bound analytes can be detected. While consuming only minute amounts (< microL scale) of reagents, ultra- sensitive assays (zeptomol range) can readily be performed in a highly multiplexed manner. The microarray patterns generated can then be transformed into proteomic maps, or detailed molecular fingerprints, revealing the composition of the proteome. Thus, protein expression profiling and global proteome analysis using this tool will offer new opportunities for drug target and biomarker discovery, disease diagnostics, and insights into disease biology. Adopting the antibody microarray technology platform, several biomedical applications, ranging from focused assays to proteome-scale analysis will be rapidly emerging in the coming years. This review will discuss the current status of the antibody microarray technology focusing on recent technological advances and key issues in the process of evolving the methodology into a high-performing proteomic research tool.     

Proteomic data analysis workflow for discovery of candidate biomarker peaks predictive of clinical outcome for patients with acute myeloid leukemia

Our goal in this paper is to show an analytical workflow for selecting protein biomarker candidates from SELDI-MS data. The clinical question at issue is to enable prediction of the complete remission (CR) duration for acute myeloid leukemia (AML) patients. This would facilitate disease prognosis and make individual therapy possible. SELDI-mass spectrometry proteomics analyses were performed on blast cell samples collected from AML patients pre-chemotherapy. Although the biobank available included approximately 200 samples, only 58 were available for analysis. The presented workflow includes sample selection, experimental optimization, repeatability estimation, data preprocessing, data fusion, and feature selection. Specific difficulties have been the small number of samples and the skew distribution of the CR duration among the patients. Further, we had to deal with both noisy SELDI-MS data and a diverse patient cohort. This has been handled by sample selection and several methods for data preprocessing and feature detection in the analysis workflow. Four conceptually different methods for peak detection and alignment were considered, as well as two diverse methods for feature selection. The peak detection and alignment methods included the recently developed annotated regions of significance (ARS) method, the SELDI-MS software Ciphergen Express which was regarded as the standard method, segment-wise spectral alignment by a genetic algorithm (PAGA) followed by binning, and, finally, binning of raw data. In the feature selection, the "standard" Mann-Whitney t test was compared with a hierarchical orthogonal partial least-squares (O-PLS) analysis approach. The combined information from all these analyses gave a collection of 21 protein peaks. These were regarded as the most potential and robust biomarker candidates since they were picked out as significant features in several of the models. The chosen peaks will now be our first choice for the continuing work on protein identification and biological validation. The identification will be performed by chromatographic purification and MALDI MS/MS. Thus, we have shown that the use of several data handling methods can improve a protein profiling workflow from experimental optimization to a predictive model. The framework of this methodology should be seen as general and could be used with other one-dimensional spectral omics data than SELDI MS including an adequate number of samples.     

Analytical glycobiology at high sensitivity: current approaches and directions

This review summarizes the analytical advances made during the last several years in the structural and quantitative determinations of glycoproteins in complex biological mixtures. The main analytical techniques used in the fields of glycomics and glycoproteomics involve different modes of mass spectrometry and their combinations with capillary separation methods such as microcolumn liquid chromatography and capillary electrophoresis. The need for high-sensitivity measurements have been emphasized in the oligosaccharide profiling used in the field of biomarker discovery through MALDI mass spectrometry. High-sensitivity profiling of both glycans and glycopeptides from biological fluids and tissue extracts has been aided significantly through lectin preconcentration and the uses of affinity chromatography.     

Challenges to developing proteomic-based breast cancer diagnostics

Over the past decade, multiple genetic and histological approaches have accelerated development of new breast cancer diagnostics and treatment paradigms. Multiple distinct genetic subtypes of breast cancers have been defined, and this has progressively led toward more personalized medicine in regard to treatment options. There still remains a deficiency in the development of molecular diagnostic assays that can be used for breast cancer detection and pretherapy clinical decisions. In particular, the type of cancer-specific biomarker typified by a serum or tissue-derived protein. Progress in this regard has been minimal, especially in comparison to the rapid advancements in genetic and histological assays for breast cancers. In this review, some potential reasons for this large gap in developing protein biomarkers will be discussed, as well as new strategies for improving these approaches. Improvements in the study design of protein biomarker discovery strategies in relation to the genetic subtypes and histology of breast cancers is also emphasized. The current successes in use of genetic and histological assays for breast cancer diagnostics are summarized, and in that context, the current limitations of the types of breast cancer-related clinical samples available for protein biomarker assay development are discussed. Based on these limitations, research strategies emphasizing identification of glycoprotein biomarkers in blood and MALDI mass spectrometry imaging of tissues are described.     

Direct analysis and MALDI imaging of formalin-fixed, paraffin-embedded tissue sections

Formalin fixation, generally followed by paraffin embedding, is the standard and well-established processing method employed by pathologist. This treatment conserves and stabilizes biopsy samples for years. Analysis of FFPE tissues from biopsy libraries has been, so far, a challenge for proteomics biomarker studies. Herein, we present two methods for the direct analysis of formalin-fixed, paraffin-embedded (FFPE) tissues by MALDI-MS. The first is based on the use of a reactive matrix, 2,4-dinitrophenylhydrazine, useful for FFPE tissues stored less than 1 year. The second approach is applicable for all FFPE tissues regardless of conservation time. The strategy is based on in situ enzymatic digestion of the tissue section after paraffin removal. In situ digestion can be performed on a specific area of the tissue as well as on a very small area (microdigestion). Combining automated microdigestion of a predefined tissue array with either in situ extraction prior to classical nanoLC/MS-MS analysis or automated microspotting of MALDI matrix according to the same array allows the identification of both proteins by nanoLC-nanoESI and MALDI imaging. When adjacent tissue sections are used, it is, thus, possible to correlate protein identification and molecular imaging. These combined approaches, along with FFPE tissue analysis provide access to massive amounts of archived samples in the clinical pathology setting.     

Exploring proteins in Anopheles gambiae male and female antennae through MALDI mass spectrometry profiling

MALDI profiling and imaging mass spectrometry (IMS) are novel techniques for direct analysis of peptides and small proteins in biological tissues. In this work we applied them to the study of Anopheles gambiae antennae, with the aim of analysing expression of soluble proteins involved in olfaction perireceptor events. MALDI spectra obtained by direct profiling on single antennae and by the analysis of extracts, showed similar profiles, although spectra obtained through profiling had a richer ion population and higher signal to noise ratio. Male and female antennae showed distinct protein profiles. MALDI imaging experiments were also performed and differences were observed in the localization of some proteins. Two proteins were identified through high resolution measurement and top-down MS/MS experiments. A 8 kDa protein only present in the male antennae matched with an unannotated sequence of the An. gambiae genome, while the presence of odorant binding protein 9 (OBP-9) was confirmed through experiments of 2-DE, followed by MS and MS/MS analysis of digested spots. This work shows that MALDI MS profiling is a technique suitable for the analysis of proteins of small and medium MW in insect appendices, and allows obtaining data for several specimens which can be investigated for differences between groups. Proteins of interest can be identified through other complementary MS approaches.