Tissue Imaging Mass Spectrometry Research Articles

Enzymatically Amplified Mass Tags for Tissue Mass Spectrometry Imaging

Tissue mass spectrometry imaging (MSI) is a rapidly developing technology which promises to provide biomarker molecular information within tissue context, which is an unmet medical need in the era of personalized medicine. However, challenges associated with tissue specimens as well as the MSI technical limitations have hindered the practical applications of this technology. We report here a mass tag based MSI method that combines the strength of signal amplification by immuno-enzymatic reactions with the superior detection characteristics of mass spectrometry to enable matrix-free MSI of protein biomarkers in formalin fixed paraffin embedded (FFPE) tissues. The method involves binding of the target protein with a primary antibody with high affinity and specificity, followed by binding with a secondary antibody-enzyme conjugate. Enzyme substrates suitable for mass spectrometry detection are locally deposited at the site of the target through enzymatically catalyzed transformation. The precipitates thus serve as mass tags to be detected in mass spectrometry to represent the target biomolecule in tissue. Two enzymes and various substrates have been identified and successfully used to demonstrate the feasibility of this novel MSI method to image protein targets in FFPE tissue samples.

Imaging mass spectrometry in papillary thyroid carcinoma for the identification and validation of biomarker proteins.

Direct tissue imaging mass spectrometry (IMS) by matrix-assisted laser desorption ionization and time-of-flight (MALDI-TOF) mass spectrometry has become increasingly important in biology and medicine, because this technology can detect the relative abundance and spatial distribution of interesting proteins in tissues. Five thyroid cancer samples, along with normal tissue, were sliced and transferred onto conductive glass slides. After laser scanning by MALDI-TOF equipped with a smart beam laser, images were created for individual masses and proteins were classified at 200-µm spatial resolution. Based on the spatial distribution, region-specific proteins on a tumor lesion could be identified by protein extraction from tumor tissue and analysis using liquid chromatography with tandem mass spectrometry (LC-MS/MS). Using all the spectral data at each spot, various intensities of a specific peak were detected in the tumor and normal regions of the thyroid. Differences in the molecular weights of expressed proteins between tumor and normal regions were analyzed using unsupervised and supervised clustering. To verify the presence of discovered proteins through IMS, we identified ribosomal protein P2, which is specific for cancer. We have demonstrated the feasibility of IMS as a useful tool for the analysis of tissue sections, and identified the tumor-specific protein ribosomal protein P2.Graphical

A Statistical Modeling Approach for Tumor-Type Identification in Surgical Neuropathology Using Tissue Mass Spectrometry Imaging

Current clinical practice involves classification of biopsied or resected tumor tissue based on a histopathological evaluation by a neuropathologist. In this paper, we propose a method for computer-aided histopathological evaluation using mass spectrometry imaging. Specifically, mass spectrometry imaging can be used to acquire the chemical composition of a tissue section and, hence, provides a framework to study the molecular composition of the sample while preserving the morphological features in the tissue. The proposed classification framework uses statistical modeling to identify the tumor type associated with a given sample. In addition, if the tumor type for a given tissue sample is unknown or there is a great degree of uncertainty associated with assigning the tumor type to one of the known tumor models, then the algorithm rejects the given sample without classification. Due to the modular nature of the proposed framework, new tumor models can be added without the need to retrain the algorithm on all existing tumor models.

Matrix-Assisted Laser Desorption/Ionization Imaging Mass Spectrometry: A Promising Technique for Reproductive Research1

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.

Hypergeometric Similarity Measure for Spatial Analysis in Tissue Imaging Mass Spectrometry.

Tissue imaging mass spectrometry (TIMS) is a data-intensive technique for spatial biochemical analysis. TIMS contributes both molecular and spatial information to tissue analysis. We propose and evaluate a similarity measure, based on the hypergeometric distribution, for comparing m/z images from TIMS datasets, with the goal of identifying m/z values with similar spatial distributions. We compare the formulation and properties of the proposed method with those of other similarity measures, and examine the performance of each measure on synthetic and biological data. This study demonstrates that the proposed hypergeometric similarity measure is effective in identifying similar m/z images, and may be a useful addition to current methods in TIMS data analysis.

Synergistic Effect of Graphene Oxide/MWCNT Films in Laser Desorption/Ionization Mass Spectrometry of Small Molecules and Tissue Imaging

Matrix-assisted laser desorption/ionization mass spectrometry has been considered an important tool for various biochemical analyses and proteomics research. Although addition of conventional matrix efficiently supports laser desorption/ionization of analytes with minimal fragmentation, it often results in high background interference and misinterpretation of the spatial distribution of biomolecules especially in low-mass regions. Here, we show design, systematic characterization, and application of graphene oxide/multiwalled carbon nanotube-based films fabricated on solid substrates as a new matrix-free laser desorption/ionization platform. We demonstrate that the graphene oxide/multiwalled carbon nanotube double layer provides many advantages as a laser desorption/ionization substrate, such as efficient desorption/ionization of analytes with minimum fragmentation, high salt tolerance, no sweet-spots for mass signal, excellent durability against mechanical and photoagitation and prolonged exposure to ambient conditions, and applicability to tissue imaging mass spectrometry. This platform will be widely used as an important tool for mass spectrometry-based biochemical analyses because of its outstanding performance, long-term stability, and cost effectiveness.

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.

Utility of imaging mass spectrometry (IMS) by matrix-assisted laser desorption ionization (MALDI) on an ion trap mass spectrometer in the analysis of drugs and metabolites in biological tissues

Introduction The properties and potential liabilities of drug candidate are investigated in detailed ADME assays and in toxicity studies, where findings are placed in context of exposure to dosed drug and metabolites. The complex nature of biological samples may necessitate work-up procedures prior to high performance liquid chromatography-mass spectrometric (HPLC-MS) analysis of endogenous or xenobiotic compounds. This concept can readily be applied to biological fluids such as blood or urine, but in localized samples such as organs and tissues potentially important spatial, thus anatomical, information is lost during sample preparation as the result of homogenization and extraction procedures. However, the localization of test article or spatial identification of metabolites may be critical to the understanding of the mechanism of target-organ toxicity and its relevance to clinical safety. Methods Tissue imaging mass spectrometry (IMS) by matrix-assisted laser desorption ionization (MALDI) and ion trap mass spectrometry (MS) with higher order mass spectrometric scanning functions was utilized for localization of dosed drug or metabolite in tissue. Laser capture microscopy (LCM) was used to obtain related samples from tissue for analyses by standard MALDI-MS and HPLC-MS. Results In a toxicology study, rats were administered with a high dosage of a prodrug for 2 weeks. Birefringent microcrystalline material (10–25 μm) was observed in histopathologic formalin-fixed tissue samples. Direct analysis by IMS provided the identity of material in the microcrystals as circulating active drug while maintaining spatial orientation. Complementary data from visual cross-polarized light microscopy as well as standard MALDI-MS and HPLC-MS experiments on LCM samples validated the qualitative results obtained by IMS. Furthermore, the HPLC-MS analysis on the LCM samples afforded a semi-quantitative assessment of the crystalline material in the tissue samples. Discussion IMS by MALDI ion trap MS proved sensitive, specific, and highly amenable to the image analysis of traditional small molecule drug candidates directly in tissue.