Histology-guided protein digestion/extraction from formalin-fixed and paraffin-embedded pressure ulcer biopsies

A Fast-Tracking Sample Preparation Protocol for Proteomics of Formalin-Fixed Paraffin-Embedded Tumor Tissues

Archived tumor specimens are routinely preserved by formalin fixation and paraffin embedding. Despite the conventional wisdom that proteomics might be ineffective due to the cross-linking and pre-analytical variables, these samples have utility for both discovery and targeted proteomics. Building on this capability, proteomics approaches can be used to maximize our understanding of cancer biology and clinical relevance by studying preserved tumor tissues annotated with the patients' medical histories. Proteomics of formalin-fixed paraffin-embedded (FFPE) tissues also integrates with histological evaluation and molecular pathology strategies, so that additional collection of research biopsies or resected tumor aliquots is not needed. The acquisition of data from the same tumor sample also overcomes concerns about biological variation between samples due to intratumoral heterogeneity. However, the protein extraction and proteomics sample preparation from FFPE samples can be onerous, particularly for small (i.e., limited or precious) samples. Therefore, we provide a protocol for a recently introduced kit-based EasyPep method with benchmarking against a modified version of the well-established filter-aided sample preparation strategy using laser-capture microdissected lung adenocarcinoma tissues from a genetically engineered mouse model. This model system allows control over the tumor preparation and pre-analytical variables while also supporting the development of methods for spatial proteomics to examine intratumoral heterogeneity. Data are posted in ProteomeXchange (PXD045879).

Hanging drop sample preparation improves sensitivity of spatial proteomics

Spatial proteomics holds great promise for revealing tissue heterogeneity in both physiological and pathological conditions. However, one significant limitation of most spatial proteomics workflows is the requirement of large sample amounts that blurs cell-type-specific or microstructure-specific information. In this study, we developed an improved sample preparation approach for spatial proteomics and integrated it with our previously-established laser capture microdissection (LCM) and microfluidics sample processing platform. Specifically, we developed a hanging drop (HD) method to improve the sample recovery by positioning a nanowell chip upside-down during protein extraction and tryptic digestion steps. Compared with the commonly-used sitting-drop method, the HD method keeps the tissue pixel away from the container surface, and thus improves the accessibility of the extraction/digestion buffer to the tissue sample. The HD method can increase the MS signal by 7 fold, leading to a 66% increase in the number of identified proteins. An average of 721, 1489, and 2521 proteins can be quantitatively profiled from laser-dissected 10 μm-thick mouse liver tissue pixels with areas of 0.0025, 0.01, and 0.04 mm², respectively. The improved system was further validated in the study of cell-type-specific proteomes of mouse uterine tissues.

Tissue Proteomic Approaches to Understand the Pathogenesis of Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) has become a global disease encompassing a group of progressive disorders characterized by recurrent chronic inflammation of the gut with variable disease courses and complications. Despite recent advances in the knowledge of IBD pathophysiology, the elucidation of its etiopathology and progression is far from fully understood, requiring complex and multiple approaches. Therefore, limited clinical progress in diagnosis, assessment of disease activity, and optimal therapeutic regimens have been made over the past few decades. This review explores recent advances and challenges in tissue proteomics with an emphasis on biomarker discovery and better understanding of the molecular mechanisms underlying IBD pathogenesis. Future multi-omic studies are required for the comprehensive molecular characterization of disease biology in real time with a future impact on early detection, disease monitoring, and prediction of the clinical outcome.

Mapping and Identification of Native Proteins of Developing Teeth in Mouse Mandibles

Mass spectrometry imaging is a powerful tool of increasing utility due to its ability to spatially resolve molecular biomarkers directly from sectioned tissues. One hindrance to its universality is that no single protocol is sufficient for every tissue type, fixation, and pretreatment. Mineralized tissues are uniquely challenging as extensive decalcification protocols are necessary to achieve thin sections. In this study, we optimized a method to image tryptic peptides by matrix-assisted laser desorption ionization mass spectrometry of decalcified, formalin-fixed paraffin-embedded mouse hemimandibles. Using a combination of on-tissue MS/MS and hydrogel extraction LC-MS/MS, peptides from the enamel, dentin, periodontal ligament, alveolar bone, pulp, and other regions are identified and mapped. This breakthrough method provides a comprehensive approach to biomarker discovery in dental and craniofacial tissues which is highly relevant given that diseases originating from this region of the body are the most prevalent across all populations.

Hierarchical Cluster and Region of Interest Analyses Based on Mass Spectrometry Imaging of Human Brain Tumours

Imaging mass spectrometry (IMS) has been rarely used to examine specimens of human brain tumours. In the current study, high quality brain tumour samples were selected by tissue observation. Further, IMS analysis was combined with a new hierarchical cluster analysis (IMS-HCA) and region of interest analysis (IMS-ROI). IMS-HCA was successful in creating groups consisting of similar signal distribution images of glial fibrillary acidic protein (GFAP) and related multiple proteins in primary brain tumours. This clustering data suggested the relation of GFAP and these identified proteins in the brain tumorigenesis. Also, high levels of histone proteins, haemoglobin subunit α, tubulins, and GFAP were identified in a metastatic brain tumour using IMS-ROI. Our results show that IMS-HCA and IMS-ROI are promising techniques for identifying biomarkers using brain tumour samples.

MicroLESA: Integrating Autofluorescence Microscopy, In Situ Micro-Digestions, and Liquid Extraction Surface Analysis for High Spatial Resolution Targeted Proteomic Studies

The ability to target discrete features within tissue using liquid surface extractions enables the identification of proteins while maintaining the spatial integrity of the sample. Here, we present a liquid extraction surface analysis (LESA) workflow, termed microLESA, that allows proteomic profiling from discrete tissue features of ∼110 μm in diameter by integrating nondestructive autofluorescence microscopy and spatially targeted liquid droplet micro-digestion. Autofluorescence microscopy provides the visualization of tissue foci without the need for chemical stains or the use of serial tissue sections. Tryptic peptides are generated from tissue foci by applying small volume droplets (∼250 pL) of enzyme onto the surface prior to LESA. The microLESA workflow reduced the diameter of the sampled area almost 5-fold compared to previous LESA approaches. Experimental parameters, such as tissue thickness, trypsin concentration, and enzyme incubation duration, were tested to maximize proteomics analysis. The microLESA workflow was applied to the study of fluorescently labeled Staphylococcus aureus infected murine kidney to identify unique proteins related to host defense and bacterial pathogenesis. Proteins related to nutritional immunity and host immune response were identified by performing microLESA at the infectious foci and surrounding abscess. These identifications were then used to annotate specific proteins observed in infected kidney tissue by MALDI FT-ICR IMS through accurate mass matching.

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.

Round robin study of formalin-fixed paraffin-embedded tissues in mass spectrometry imaging

Mass spectrometry imaging (MSI) has provided many results with translational character, which still have to be proven robust in large patient cohorts and across different centers. Although formalin-fixed paraffin-embedded (FFPE) specimens are most common in clinical practice, no MSI multicenter study has been reported for FFPE samples. Here, we report the results of the first round robin MSI study on FFPE tissues with the goal to investigate the consequences of inter- and intracenter technical variation on masking biological effects. A total of four centers were involved with similar MSI instrumentation and sample preparation equipment. A FFPE multi-organ tissue microarray containing eight different types of tissue was analyzed on a peptide and metabolite level, which enabled investigating different molecular and biological differences. Statistical analyses revealed that peptide intercenter variation was significantly lower and metabolite intercenter variation was significantly higher than the respective intracenter variations. When looking at relative univariate effects of mass signals with statistical discriminatory power, the metabolite data was more reproducible across centers compared to the peptide data. With respect to absolute effects (cross-center common intensity scale), multivariate classifiers were able to reach on average > 90% accuracy for peptides and > 80% for metabolites if trained with sufficient amount of cross-center data. Overall, our study showed that MSI data from FFPE samples could be reproduced to a high degree across centers. While metabolite data exhibited more reproducibility with respect to relative effects, peptide data-based classifiers were more directly transferable between centers and therefore more robust than expected. Graphical abstract ᅟ.

Recent advances and opportunities in proteomic analyses of tumour heterogeneity

Solid tumour malignancies comprise a highly variable admixture of tumour and non-tumour cellular populations, forming a complex cellular ecosystem and tumour microenvironment. This tumour heterogeneity is not incidental, and is known to correlate with poor patient prognosis for many cancer types. Indeed, non-malignant cell populations, such as vascular endothelial and immune cells, are known to play key roles supporting and, in some cases, driving aggressive tumour biology, and represent targets of emerging therapeutics, such as antiangiogenesis and immune checkpoint inhibitors. The biochemical interplay between these cellular populations and how they contribute to molecular tumour heterogeneity remains enigmatic, particularly from the perspective of the tumour proteome. This review focuses on recent advances in proteomic methods, namely imaging mass spectrometry, single-cell proteomic techniques, and preanalytical sample processing, that are uniquely positioned to enable detailed analysis of discrete cellular populations within tumours to improve our understanding of tumour proteomic heterogeneity. This review further emphasizes the opportunity afforded by the application of these techniques to the analysis of tumour heterogeneity in formalin-fixed paraffin-embedded archival tumour tissues, as these represent an invaluable resource for retrospective analyses that is now routinely accessible, owing to recent technological and methodological advances in tumour tissue proteomics. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

MALDI (matrix assisted laser desorption ionization) Imaging Mass Spectrometry (IMS) of skin: Aspects of sample preparation

MALDI (matrix assisted laser desorption ionization) Imaging Mass Spectrometry (IMS) allows molecular analysis of biological materials making possible the identification and localization of molecules in tissues, and has been applied to address many questions on skin pathophysiology, as well as on studies about drug absorption and metabolism. Sample preparation for MALDI IMS is the most important part of the workflow, comprising specimen collection and preservation, tissue embedding, cryosectioning, washing, and matrix application. These steps must be carefully optimized for specific analytes of interest (lipids, proteins, drugs, etc.), representing a challenge for skin analysis. In this review, critical parameters for MALDI IMS sample preparation of skin samples will be described. In addition, specific applications of MALDI IMS of skin samples will be presented including wound healing, neoplasia, and infection.

MALDI IMS and Cancer Tissue Microarrays

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) technology creates a link between the molecular assessment of numerous molecules and the morphological information about their special distribution. The application of MALDI IMS on formalin-fixed paraffin-embedded (FFPE) tissue microarrays (TMAs) is suitable for large-scale discovery analyses. Data acquired from FFPE TMA cancer samples in current research are very promising, and applications for routine diagnostics are under development. With the current rapid advances in both technology and applications, MALDI IMS technology is expected to enter into routine diagnostics soon. This chapter is intended to be comprehensive with respect to all aspects and considerations for the application of MALDI IMS on FFPE cancer TMAs with in-depth notes on technical aspects.

Imaging mass spectrometry for accessing molecular changes during burn wound healing

The spatiotemporal analysis of the proteomic profile during human wound healing is a critical investigative step that can establish the complex interplay of molecular events that comprise the local response to burn injury. Partial-thickness wound samples with adjacent "normal" skin were collected from twenty-one patients with burn wounds and examined across a time spectrum ranging from the acute injury period at 3, 6, 11 days to the later hypertrophic scar period at 7 and 15 months. The techniques used for histology-directed tissue analyses highlighted inflammatory protein markers at the early time points after injury with diminished expression as burn wounds progressed into the proliferative phase. The datasets show the usefulness of MALDI MS and imaging mass spectrometry as discovery approaches to identify and map the cutaneous molecular sequence that is activated in response to the unique systemic inflammatory response following burn trauma. This information has the potential to define the unique factors that predispose human burn victims to disfiguring hypertrophic scar formation.