Peptide and protein imaging mass spectrometry in cancer research

Implementation of molecular phenotyping approaches in the personalized surgical patient journey

OBJECTIVE

The present review describes commonly employed metabolic profiling platforms and discusses the current and likely future application of these technologies in surgery.

BACKGROUND

The metabolic adaptations that occur in response to surgical illness and trauma are incompletely understood. Evaluating these will be critical to the development of personalized surgical health solutions. Metabonomics is an advancing field in systems biology, which provides a means of interrogating these metabolic shifts.

METHODS

Recent literature regarding metabolic profiling technologies and their applications in surgical practice are discussed. Future strategies are proposed for the incorporation of these and next-generation technologies in the evaluation of all steps in the patient surgical pathway.

RESULTS

Metabolite-based profiling has provided valuable insights into the metabolic irregularities that occur in cancer development and progression across a variety of cancer subclasses including colorectal, breast, prostate, and lung cancers. In addition, metabolic modeling has shown considerable promise in other surgical conditions including trauma and sepsis and in the assessment of pharmacotherapeutic efficacy.

DISCUSSION

Metabonomics offers a posttranscriptional view of system activity providing functional information downstream of the genome and proteome. Information at this level will provide the surgeon with a novel means of evaluating major socioeconomic problems such as cancer and sepsis. In addition, the rapid nature of emerging next generation profiling platforms provides a viable means of "real-time" perioperative metabolic assessment and optimization.

High-resolution matrix-assisted laser desorption/ionization imaging of tryptic peptides from tissue

RATIONALE

The analysis of proteins by mass spectrometry imaging is an important biomedical application as spatial distributions can be used to identify markers for pathological processes. The direct detection and identification of proteins on tissue can be hindered by a number of factors including limited mass range and fragmentation efficiency as well as incompatibility with formalin-fixed samples.

METHODS

To overcome some of these limitations, on-tissue digestion of proteins was followed by detection of the resulting peptides. Trypsin was applied by a spraying device. Matrix-assisted laser desorption/ionization (MALDI) imaging experiments were performed with a home-built atmospheric-pressure imaging source attached to a LTQ Orbitrap mass spectrometer. The mass accuracy under imaging conditions was better than 3 ppm RMS. This allowed for confident identification of tryptic peptides by comparison with liquid chromatography/electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS) measurements of an adjacent mouse brain section.

RESULTS

A spatial resolution of 50 µm was obtained for tryptic peptides on tissue. Several tryptic peptides of myelin showed matching spatial distributions, and numerous tryptic peptides of other proteins were identified. MS images were generated with a bin size (mass range used for image generation) of Δm/z = 0.01 u. Examples demonstrate that MS images with lower selectivity can result in misleading information about the spatial distribution of tryptic peptides.

CONCLUSIONS

The presented method combines a significantly improved spatial resolution for tryptic peptides with low-ppm mass accuracy in a single experiment and thus provides highly reliable and specific information.

High speed data processing for imaging MS-based molecular histology using graphical processing units

Imaging MS enables the distributions of hundreds of biomolecular ions to be determined directly from tissue samples. The application of multivariate methods, to identify pixels possessing correlated MS profiles, is referred to as molecular histology as tissues can be annotated on the basis of the MS profiles. The application of imaging MS-based molecular histology to larger tissue series, for clinical applications, requires significantly increased computational capacity in order to efficiently analyze the very large, highly dimensional datasets. Such datasets are highly suited to processing using graphical processor units, a very cost-effective solution for high speed processing. Here we demonstrate up to 13× speed improvements for imaging MS-based molecular histology using off-the-shelf components, and demonstrate equivalence with CPU based calculations. It is then discussed how imaging MS investigations may be designed to fully exploit the high speed of graphical processor units.

Relevant phosphoproteomic and mass spectrometry: approaches useful in clinical research

Background

"It's not what we do, it's the way that we do it". Never has this maxim been truer in proteomics than now. Mass Spectrometry-based proteomics/phosphoproteomics tools are critical to understand the structure and dynamics (spatial and temporal) of signalling that engages and migrates through the entire proteome. Approaches such as affinity purification followed by Mass Spectrometry (MS) have been used to elucidate relevant biological questions disease vs. health. Thousands of proteins interact via physical and chemical association. Moreover, certain proteins can covalently modify other proteins post-translationally. These post-translational modifications (PTMs) ultimately give rise to the emergent functions of cells in sequence, space and time.

Findings

Understanding the functions of phosphorylated proteins thus requires one to study proteomes as linked-systems rather than collections of individual protein molecules. Indeed, the interacting proteome or protein-network knowledge has recently received much attention, as network-systems (signalling pathways) are effective snapshots in time, of the proteome as a whole. MS approaches are clearly essential, in spite of the difficulties of some low abundance proteins for future clinical advances.

Conclusion

Clinical proteomics-MS has come a long way in the past decade in terms of technology/platform development, protein chemistry, and together with bioinformatics and other OMICS tools to identify molecular signatures of diseases based on protein pathways and signalling cascades. Hence, there is great promise for disease diagnosis, prognosis, and prediction of therapeutic outcome on an individualized basis. However, and as a general rule, without correct study design, strategy and implementation of robust analytical methodologies, the efforts, efficiency and expectations to make biomarkers (especially phosphorylated kinases) a useful reality in the near future, can easily be hampered.

Emerging technologies in mass spectrometry imaging

Mass spectrometry imaging (MSI) as an analytical tool for bio-molecular and bio-medical research targets accurate compound localization and identification. In terms of dedicated instrumentation, this translates into the demand for more detail in the image dimension (spatial resolution) and in the spectral dimension (mass resolution and accuracy), preferably combined in one instrument. At the same time, large area biological tissue samples require fast acquisition schemes, instrument automation and a robust data infrastructure. This review discusses the analytical capabilities of an "ideal" MSI instrument for bio-molecular and bio-medical molecular imaging. The analytical attributes of such an ideal system are contrasted with technological and methodological challenges in MSI. In particular, innovative instrumentation for high spatial resolution imaging in combination with high sample throughput is discussed. Detector technology that targets various shortcomings of conventional imaging detector systems is highlighted. The benefits of accurate mass analysis, high mass resolving power, additional separation strategies and multimodal three-dimensional data reconstruction algorithms are discussed to provide the reader with an insight in the current technological advances and the potential of MSI for bio-medical research.

Recent advances in single-cell MALDI mass spectrometry imaging and potential clinical impact

Single-cell analysis is gaining popularity in the field of mass spectrometry as a method for analyzing protein and peptide content in cells. The spatial resolution of MALDI mass spectrometry (MS) imaging is by a large extent limited by the laser focal diameter and the displacement of analytes during matrix deposition. Owing to recent advancements in both laser optics and matrix deposition methods, spatial resolution on the order of a single eukaryotic cell is now achievable by MALDI MS imaging. Provided adequate instrument sensitivity, a lateral resolution of approximately 10 µm is currently attainable with commercial instruments. As a result of these advances, MALDI MS imaging is poised to become a transformative clinical technology. In this article, the crucial steps needed to obtain single-cell resolution are discussed, as well as potential applications to disease research.

Tissue analysis by imaging MS

Imaging MS (IMS) is generating tremendous interest in scientific communities because of its unparalleled capabilities to provide chemical analysis of intact tissue. Advances in analytical chemistry and MS are providing new insights into chemical and biological processes. This review will discuss various IMS platforms and their applications in biomedical and pharmaceutical research.

A gain and bandwidth enhanced transimpedance preamplifier for Fourier-transform ion cyclotron resonance mass spectrometry

The nature of the ion signal from a 12-T Fourier-transform ion cyclotron resonance mass spectrometer and the electronic noise were studied to further understand the electronic detection limit. At minimal cost, a new transimpedance preamplifier was designed, computer simulated, built, and tested. The preamplifier design pushes the electronic signal-to-noise performance at room temperature to the limit, because of its enhanced tolerance of the capacitance of the detection device, lower intrinsic noise, and larger flat mid-band gain (input current noise spectral density of around 1 pA/√Hz when the transimpedance is about 85 dBΩ). The designed preamplifier has a bandwidth of ~3 kHz to 10 MHz, which corresponds to the mass-to-charge ratio, m/z, of approximately 18 to 61 k at 12 T. The transimpedance and the bandwidth can be easily adjusted by changing the value of passive components. The feedback limitation of the circuit is discussed. With the maximum possible transimpedance of 5.3 MΩ when using an 0402 surface mount resistor, the preamplifier was estimated to be able to detect ~110 charges in a single scan.

Qualitative and quantitative MALDI imaging of the positron emission tomography ligands raclopride (a D2 dopamine antagonist) and SCH 23390 (a D1 dopamine antagonist) in rat brain tissue sections using a solvent-free dry matrix application method

The distributions of positron emission tomography (PET) ligands in rat brain tissue sections were analyzed by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI). The detection of the PET ligands was possible following the use of a solvent-free dry MALDI matrix application method employing finely ground dry α-cyano-4-hydroxycinnamic acid (CHCA). The D2 dopamine receptor antagonist 3,5-dichloro-N-{[(2S)-1-ethylpyrrolidin-2-yl]methyl}-2-hydroxy-6-methoxybenzamide (raclopride) and the D1 dopamine receptor antagonist 7-chloro-3-methyl-1-phenyl-1,2,4,5-tetrahydro-3-benzazepin-8-ol (SCH 23390) were both detected at decreasing abundance at increasing period postdosing. Confirmation of the compound identifications and distributions was achieved by a combination of mass-to-charge ratio accurate mass, isotope distribution, and MS/MS fragmentation imaging directly from tissue sections (performed using MALDI TOF/TOF, MALDI q-TOF, and 12T MALDI-FT-ICR mass spectrometers). Quantitative data was obtained by comparing signal abundances from tissues to those obtained from quantitation control spots of the target compound applied to adjacent vehicle control tissue sections (analyzed during the same experiment). Following a single intravenous dose of raclopride (7.5 mg/kg), an average tissue concentration of approximately 60 nM was detected compared to 15 nM when the drug was dosed at 2 mg/kg, indicating a linear response between dose and detected abundance. SCH 23390 was established to have an average tissue concentration of approximately 15 μM following a single intravenous dose at 5 mg/kg. Both target compounds were also detected in kidney tissue sections when employing the same MSI methodology. This study illustrates that a MSI may well be readily applied to PET ligand research development when using a solvent-free dry matrix coating.

Multiple statistical analysis techniques corroborate intratumor heterogeneity in imaging mass spectrometry datasets of myxofibrosarcoma

MALDI mass spectrometry can generate profiles that contain hundreds of biomolecular ions directly from tissue. Spatially-correlated analysis, MALDI imaging MS, can simultaneously reveal how each of these biomolecular ions varies in clinical tissue samples. The use of statistical data analysis tools to identify regions containing correlated mass spectrometry profiles is referred to as imaging MS-based molecular histology because of its ability to annotate tissues solely on the basis of the imaging MS data. Several reports have indicated that imaging MS-based molecular histology may be able to complement established histological and histochemical techniques by distinguishing between pathologies with overlapping/identical morphologies and revealing biomolecular intratumor heterogeneity. A data analysis pipeline that identifies regions of imaging MS datasets with correlated mass spectrometry profiles could lead to the development of novel methods for improved diagnosis (differentiating subgroups within distinct histological groups) and annotating the spatio-chemical makeup of tumors. Here it is demonstrated that highlighting the regions within imaging MS datasets whose mass spectrometry profiles were found to be correlated by five independent multivariate methods provides a consistently accurate summary of the spatio-chemical heterogeneity. The corroboration provided by using multiple multivariate methods, efficiently applied in an automated routine, provides assurance that the identified regions are indeed characterized by distinct mass spectrometry profiles, a crucial requirement for its development as a complementary histological tool. When simultaneously applied to imaging MS datasets from multiple patient samples of intermediate-grade myxofibrosarcoma, a heterogeneous soft tissue sarcoma, nodules with mass spectrometry profiles found to be distinct by five different multivariate methods were detected within morphologically identical regions of all patient tissue samples. To aid the further development of imaging MS based molecular histology as a complementary histological tool the Matlab code of the agreement analysis, instructions and a reduced dataset are included as supporting information.

Chemical inhibitors: the challenge of finding the right target

A paper in this issue of Chemistry & Biology shows that the diaryl oxazole compound UA62784 that targets pancreatic cancer cells interacts with tubulin near the colchicine binding site (Tcherniuk et al., 2011). These findings differ from previous observations, highlighting the challenges of identifying the biological target for chemical inhibitors.

Protein identification by accurate mass matrix-assisted laser desorption/ionization imaging of tryptic peptides

The spatial distribution of proteins in tissue sections can be used to identify potential markers for pathological processes. Tissue sections are often subjected to enzymatic digestion before matrix-assisted laser desorption/ionization (MALDI) imaging. This study is targeted at improving the on-tissue identification of tryptic peptides by accurate mass measurements and complementary off-line liquid chromatography coupled to electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS) analysis. Two adjacent mouse brain sections were analyzed in parallel. The first section was spotted with trypsin and analyzed by MALDI imaging. Direct on-tissue MS/MS experiments of this section resulted in the identification of 14 peptides (originating from 4 proteins). The second tissue section was homogenized, fractionated by ultracentrifugation and digested with trypsin prior to LC/ESI-MS/MS analysis. The number of identified peptides was increased to 153 (corresponding to 106 proteins) by matching imaged mass peaks to peptides which were identified in these LC/ESI-MS/MS experiments. All results (including MALDI imaging data) were based on accurate mass measurements (RMS <2 ppm) and allow a confident identification of tryptic peptides. Measurements based on lower accuracy would have led to ambiguous or misleading results. MS images of identified peptides were generated with a bin width (mass range used for image generation) of Δm/z = 0.01. The application of accurate mass measurements and additional LC/MS measurements increased both the quality and the number of peptide identifications. The advantages of this approach for the analysis of biological tissue sections are demonstrated and discussed in detail. Results indicate that accurate mass measurements are needed for confident identification and specific image generation of tryptic peptides in tissue sections.

MALDI imaging mass spectrometry for direct tissue analysis: technological advancements and recent applications

Matrix assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a method that allows the investigation of the molecular content of tissues within its morphological context. Since it is able to measure the distribution of hundreds of analytes at once, while being label free, this method has great potential which has been increasingly recognized in the field of tissue-based research. In the last few years, MALDI-IMS has been successfully used for the molecular assessment of tissue samples mainly in biomedical research and also in other scientific fields. The present article will give an update on the application of MALDI-IMS in clinical and preclinical research. It will also give an overview of the multitude of technical advancements of this method in recent years. This includes developments in instrumentation, sample preparation, computational data analysis and protein identification. It will also highlight a number of emerging fields for application of MALDI-IMS like drug imaging where MALDI-IMS is used for studying the spatial distribution of drugs in tissues.

MALDI imaging techniques dedicated to drug-distribution studies

Previously, MS was often used to analyze the composition and structure of biological molecules present in solutions. Today, technology developments enable the application of MS for the analysis of localized biomolecules on biological tissue surfaces. This technique is called MS imaging. MALDI imaging MS is a technique whereby thousands of compounds present in a tissue section are detected simultaneously without labeling. Although initially used for the detection of biomolecules such as peptides and proteins, this technology is also used today for drug detection. These characteristics make MS imaging an ideal technology that is perfectly adapted for ADME (absorption, distribution, metabolism and excretion) studies. In fact, this technology facilitates the tracking of one or several administered drugs, as well as the metabolites that result from their assimilations. In this article, we will present the various possibilities that MALDI imaging MS approaches have to offer for the study of drugs and their metabolites using MS, MS/MS, FAST-SRM and MRM modes. In this context, we investigate two studies: the distribution of olanzapine in the kidney and the overall distribution of BDM31343 in mouse whole-body section.

High-speed MALDI-TOF imaging mass spectrometry: rapid ion image acquisition and considerations for next generation instrumentation

A prototype matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometer has been used for high-speed ion image acquisition. The instrument incorporates a Nd:YLF solid state laser capable of pulse repetition rates up to 5 kHz and continuous laser raster sampling for high-throughput data collection. Lipid ion images of a sagittal rat brain tissue section were collected in 10 min with an effective acquisition rate of roughly 30 pixels/s. These results represent more than a 10-fold increase in throughput compared with current commercially available instrumentation. Experiments aimed at improving conditions for continuous laser raster sampling for imaging are reported, highlighting proper laser repetition rates and stage velocities to avoid signal degradation from significant oversampling. As new high spatial resolution and large sample area applications present themselves, the development of high-speed microprobe MALDI imaging mass spectrometry is essential to meet the needs of those seeking new technologies for rapid molecular imaging.

Direct analysis of biological tissue by paper spray mass spectrometry

Paper spray mass spectrometry (PS-MS) is explored as a fast and convenient way for direct analysis of molecules in tissues with minimum sample pretreatment. This technique allows direct detection of different types of compounds such as hormones, lipids, and therapeutic drugs in short total analysis times (less than 1 min) using a small volume of tissue sample (typically 1 mm(3) or less). The tissue sample could be obtained by needle aspiration biopsy, by punch biopsy, or by rubbing a thin tissue section across the paper. There exists potential for the application of paper spray mass spectrometry together with tissue biopsy for clinical diagnostics.

The evolving field of imaging mass spectrometry and its impact on future biological research

Within the past decade, imaging mass spectrometry (IMS) has been increasingly recognized as an indispensable technique for studying biological systems. Its rapid evolution has resulted in an impressive array of instrument variations and sample applications, yet the tools and data are largely confined to specialists. It is therefore important that at this junction the IMS community begin to establish IMS as a permanent fixture in life science research thereby making the technology and/or the data approachable by non-mass spectrometrists, leading to further integration into biological and clinical research. In this perspective article, we provide insight into the evolution and current state of IMS and propose some of the directions that IMS could develop in order to stay on course to become one of the most promising new tools in life science research.

Imaging mass spectrometry data reduction: automated feature identification and extraction

Imaging MS now enables the parallel analysis of hundreds of biomolecules, spanning multiple molecular classes, which allows tissues to be described by their molecular content and distribution. When combined with advanced data analysis routines, tissues can be analyzed and classified based solely on their molecular content. Such molecular histology techniques have been used to distinguish regions with differential molecular signatures that could not be distinguished using established histologic tools. However, its potential to provide an independent, complementary analysis of clinical tissues has been limited by the very large file sizes and large number of discrete variables associated with imaging MS experiments. Here we demonstrate data reduction tools, based on automated feature identification and extraction, for peptide, protein, and lipid imaging MS, using multiple imaging MS technologies, that reduce data loads and the number of variables by >100×, and that highlight highly-localized features that can be missed using standard data analysis strategies. It is then demonstrated how these capabilities enable multivariate analysis on large imaging MS datasets spanning multiple tissues.

Spatial segmentation of imaging mass spectrometry data with edge-preserving image denoising and clustering

In recent years, matrix-assisted laser desorption/ionization (MALDI)-imaging mass spectrometry has become a mature technology, allowing for reproducible high-resolution measurements to localize proteins and smaller molecules. However, despite this impressive technological advance, only a few papers have been published concerned with computational methods for MALDI-imaging data. We address this issue proposing a new procedure for spatial segmentation of MALDI-imaging data sets. This procedure clusters all spectra into different groups based on their similarity. This partition is represented by a segmentation map, which helps to understand the spatial structure of the sample. The core of our segmentation procedure is the edge-preserving denoising of images corresponding to specific masses that reduces pixel-to-pixel variability and improves the segmentation map significantly. Moreover, before applying denoising, we reduce the data set selecting peaks appearing in at least 1% of spectra. High dimensional discriminant clustering completes the procedure. We analyzed two data sets using the proposed pipeline. First, for a rat brain coronal section the calculated segmentation maps highlight the anatomical and functional structure of the brain. Second, a section of a neuroendocrine tumor invading the small intestine was interpreted where the tumor area was discriminated and functionally similar regions were indicated.

MALDI imaging and profiling MS of higher mass proteins from tissue

MALDI imaging and profiling mass spectrometry of proteins typically leads to the detection of a large number of peptides and small proteins but is much less successful for larger proteins: most ion signals correspond to proteins of m/z < 25,000. This is a severe limitation as many proteins, including cytokines, growth factors, enzymes, and receptors have molecular weights exceeding 25 kDa. The detector technology typically used for protein imaging, a microchannel plate, is not well suited to the detection of high m/z ions and is prone to detector saturation when analyzing complex mixtures. Here we report increased sensitivity for higher mass proteins by using the CovalX high mass HM1 detector (Zurich, Switzerland), which has been specifically designed for the detection of high mass ions and which is much less prone to detector saturation. The results demonstrate that a range of different sample preparation strategies enable higher mass proteins to be analyzed if the detector technology maintains high detection efficiency throughout the mass range. The detector enables proteins up to 70 kDa to be imaged, and proteins up to 110 kDa to be detected, directly from tissue, and indicates new directions by which the mass range amenable to MALDI imaging MS and MALDI profiling MS may be extended.