Depicting the spatial distribution of proteins in human tumor tissue combining SELDI and MALDI imaging and immunohistochemistry

Nano-DESI Mass Spectrometry Imaging of Proteoforms in Biological Tissues with High Spatial Resolution

Mass spectrometry imaging (MSI) is a powerful tool for label-free mapping of the spatial distribution of proteins in biological tissues. We have previously demonstrated imaging of individual proteoforms in biological tissues using nanospray desorption electrospray ionization (nano-DESI), an ambient liquid extraction-based MSI technique. Nano-DESI MSI generates multiply charged protein ions, which is advantageous for their identification using top-down proteomics analysis. In this study, we demonstrate proteoform mapping in biological tissues with a spatial resolution down to 7 μm using nano-DESI MSI. A substantial decrease in protein signals observed in high-spatial-resolution MSI makes these experiments challenging. We have enhanced the sensitivity of nano-DESI MSI experiments by optimizing the design of the capillary-based probe and the thickness of the tissue section. In addition, we demonstrate that oversampling may be used to further improve spatial resolution at little or no expense to sensitivity. These developments represent a new step in MSI-based spatial proteomics, which complements targeted imaging modalities widely used for studying biological systems.

Imaging mass spectrometry of gold nanoparticles in a tissue section as an immunohistochemical staining mass probe

For analysis of low abundance peptides in a tissue section, immunohistochemical staining through antibody-antigen interaction is a usual technique. The antibody is conjugated with a probe moiety that aids in highly sensitive detection. Gold nanoparticles, which show excellent chemical stability and variation of surface modifications, are expected to act as a sensitive mass probe to desorb gold ions (Au⁺ , Au₂ ⁺ , Au₃ ⁺ ) that are distinguishable from fragment ions from organic molecules. Here, green fluorescent proteins (GFP) in a tissue section of a transgenic zebrafish were detected by the gold mass probe conjugated with antibodies. Due to the efficient ionization and desorption of gold ions, imaging mass spectrometry of Au₂ ⁺ ions indicated the distribution of gold nanoparticles stained in a tissue section, and the mass signal distribution was consistent with the area where the GFP-expressing cells were distributed. Conventional immunofluorescence techniques showed intense autofluorescence that come from intrinsic fluorophores in the tissue section. In contrast, the gold nanoparticles acted as an immunostaining mass probe that displayed significantly lower background signals.

Mass spectrometric imaging of cysteine rich proteins in human skin

Looking insight pathological processes, metallothioneins (MTs) are considered to be potential biomarkers for monitoring of a development of various types of diseases, such as cancer. The early identification of the MTs in biological tissues could be important tool for the estimation of appropriate clinical therapy. Therefore, here we investigated the application of matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) together with immunohistochemical analyses (IHC) using MT-1/2 antibody for MT detection in formalin-fixed paraffin-embedded (FFPE) biopsy specimens of human skin. Principal component analyses revealed differences in the peptide/protein profiles separating healthy skin from the carcinoma specimens. Statistically significant ion peaks at m/z 6038, 6300, 6676, and 7026 were more frequently detected in squamous cell carcinoma (SCC), basal cell carcinoma (BCC) and melanoma. Using IHC, we found that MT-1/2 was significantly higher in SCC and melanoma compared to healthy skin. Surprisingly, significantly low levels of MT-1/2 were found in BCC. On one side, the results indicate important role of MTs in melanoma occurrence and progression, as on the second side, there are hidden processes associated with MTs based on differences of the occurrence of the MS peaks, which could be associated with cycling of MTs isoforms.

Global Proteomics-based Identification and Validation of Thymosin Beta-4 X-Linked as a Prognostic Marker for Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) represents a major health concern worldwide. We applied the matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) to analyze paired normal (N) and tumor (T) samples from head and neck squamous cell carcinoma as well as liquid chromatography with tandem mass spectrometry (LC-MS/MS) analysis in HNSCC cell lines to identify tumor-associated biomarkers. Our results showed a number of proteins found to be over-expressed in HNSCC. We identified thymosin beta-4 X-linked (TMSB4X) is one of the most significant candidate biomarkers. Higher TMSB4X expression in the tumor was found by N/T-paired HNSCC samples at both RNA and protein level. Overexpression of TMSB4X was found significantly associated with poor prognosis of overall survival (OS, P = 0.006) and recurrence-free survival (RFS, P = 0.013) in HNSCC patients. Silencing of TMSB4X expression in HNSCC cell line reduced the proliferation and invasion ability in vitro, as well as inhibited the cervical lymph node metastasis in vivo. Altogether, our global proteomics analysis identified that TMSB4X is a newly discovered biomarker in HNSCC whose functions resulted in enhanced proliferation and metastasis in vitro and in vivo. TMSB4X may be a potential therapeutic target for treating HNSCC patients.

Spatial segmentation of MALDI FT-ICR MSI data: a powerful tool to explore the head and neck tumor in situ lipidome

Matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI MSI) is a well-established analytical technique for determining spatial localization of lipids in biological samples. The use of Fourier-transform ion cyclotron resonance (FT-ICR) mass spectrometers for the molecular imaging of endogenous compounds is gaining popularity, since the high mass accuracy and high mass resolving power enables accurate determination of exact masses and, consequently, a more confident identification of these molecules. The high mass resolution FT-ICR imaging datasets are typically large in size. In order to analyze them in an appropriate timeframe, the following approach has been employed: the FT-ICR imaging datasets were spatially segmented by clustering all spectra by their similarity. The resulted spatial segmentation maps were compared with the histologic annotation. This approach facilitates interpretation of the full datasets by providing spatial regions of interest. The application of this approach, which has originally been developed for MALDI-TOF MSI datasets, to the lipidomic analysis of head and neck tumor tissue revealed new insights into the metabolic organization of the carcinoma tissue.

Selected protein monitoring in histological sections by targeted MALDI-FTICR in-source decay imaging

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is a rapidly growing method in biomedical research allowing molecular mapping of proteins on histological sections. The images can be analyzed in terms of spectral pattern to define regions of interest. However, the identification and the differential quantitative analysis of proteins require off line or in situ proteomic methods using enzymatic digestion. The rapid identification of biomarkers holds great promise for diagnostic research, but the major obstacle is the absence of a rapid and direct method to detect and identify with a sufficient dynamic range a set of specific biomarkers. In the current work, we present a proof of concept for a method allowing one to identify simultaneously a set of selected biomarkers on histological slices with minimal sample treatment using in-source decay (ISD) MSI and MALDI-Fourier transform ion cyclotron resonance (FTICR). In the proposed method, known biomarkers are spotted next to the tissue of interest, the whole MALDI plate being coated with 1,5-diaminonaphthalene (1,5-DAN) matrix. The latter enhances MALDI radical-induced ISD, providing large tags of the amino acid sequences. Comparative analysis of ISD fragments between the reference spots and the specimen in imaging mode allows for unambiguous identification of the selected biomarker while preserving full spatial resolution. Moreover, the high resolution/high mass accuracy provided by FTICR mass spectrometry allows the identification of proteins. Well-resolved peaks and precise measurements of masses and mass differences allow the construction of reliable sequence tags for protein identification. The method will allow the use of MALDI-FTICR MSI as a method for rapid targeted biomarker detection in complement to classical histology.

MALDI-imaging segmentation is a powerful tool for spatial functional proteomic analysis of human larynx carcinoma

PURPOSE

For several decades, conventional histological staining and immunohistochemistry (IHC) have been the main tools to visualize and understand tissue morphology and structure. IHC visualizes the spatial distribution of individual protein species directly in tissue. However, a specific antibody is required for each protein, and multiplexing capabilities are extremely limited, rarely visualizing more than two proteins simultaneously. With the recent emergence of matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-imaging), it is becoming possible to study more complex proteomic patterns directly in tissue. However, the analysis and interpretation of large and complex MALDI-imaging data requires advanced computational methods. In this paper, we show how the recently introduced method of spatial segmentation can be applied to analysis and interpretation of a larynx carcinoma section and compare the spatial segmentation with the histological annotation of the same tissue section.

METHODS

Matrix-assisted laser desorption/ionization imaging is a label-free spatially resolved analytical technique, which allows detection and visualization of hundreds of proteins at once. Spatial segmentation of the MALDI-imaging data by clustering of spectra by their similarity was performed, automatically generating a spatial segmentation map of the tissue section, where regions of similar proteomic patterns were highlighted. The tissue was stained with the hematoxylin and eosin (H&E), histopathologically analyzed and annotated. The segmentation map was interpreted after its overlay with the H&E microscopy image.

RESULTS

The automatically generated segmentation map exhibits high correspondence to the detailed histological annotation of the larynx carcinoma tissue section. By superimposing, the segmentation map based on the proteomic profiles with H&E-stained microscopic images, we demonstrate precise localization of complex and histopathologically relevant tissue features in an automated way.

CONCLUSIONS

The combination of MALDI-imaging and automatic spatial segmentation is a useful approach in analyzing carcinoma tissue and provides a deeper insight into the functional proteomic organization of the respective tissue.

Application of matrix-assisted laser desorption/ionization mass spectrometric imaging to monitor surface changes of UV-irradiated poly(styrene) films

This study presents the application of matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI-MSI) to monitor changes occurring at polymer surfaces. As an example, a poly(styrene) (PS) film was irradiated with ultraviolet (UV) light at 254 nm for different time intervals, while areas of the film were protected from UV light by covering it with an aluminum mask. After the UV treatment, the polymer surface was analyzed by MALDI-MSI. Time-dependent photo-induced cross-linking of the polymer film was observed, and a correlation curve between UV radiation time and area of cross-linking was constructed. This represents the first step towards the surface analysis of polymer components of photoresists and top coatings of cars, and it will also enable a new characterization strategy for combinatorial material research.