Molecular signatures of medullary thyroid carcinoma by matrix-assisted laser desorption/ionisation mass spectrometry imaging

Matrix-assisted laser desorption/ionization mass spectrometry imaging as a new tool for molecular histopathology in epilepsy surgery

OBJECTIVE

Epilepsy surgery is a treatment option for patients with seizures that do not respond to pharmacotherapy. The histopathological characterization of the resected tissue has an important prognostic value to define postoperative seizure outcome in these patients. However, the diagnostic classification process based on microscopic assessment remains challenging, particularly in the case of focal cortical dysplasia (FCD). Imaging mass spectrometry is a spatial omics technique that could improve tissue phenotyping and patient stratification by investigating hundreds of biomolecules within a single tissue sample, without the need for target-specific reagents.

METHODS

An in situ proteomic technique called matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is here investigated as a potential new tool to expand conventional diagnosis on standard paraffin brain tissue sections. Unsupervised and region of interest-based MALDI-MSI analyses of sections from 10 FCD type IIb (FCDIIb) cases were performed, and the results were validated by immunohistochemistry.

RESULTS

MALDI-MSI identified distinct histopathological features and the boundaries of the dysplastic lesion. The capability to visualize the spatial distribution of well-known diagnostic markers enabling multiplex measurements on single tissue sections was demonstrated. Finally, a fingerprint list of potential discriminant peptides that distinguish FCD core from peri-FCD tissue was generated.

SIGNIFICANCE

This is the first study that explores the potential application of MALDI-MSI in epilepsy postsurgery fixed tissue, by utilizing the well-characterized FCDIIb features as a model. Extending these preliminary analyses to a larger cohort of patients will generate spectral libraries of molecular signatures that discriminate tissue features and will contribute to patient phenotyping.

DropBlot: single-cell western blotting of chemically fixed cancer cells

Archived patient-derived tissue specimens play a central role in understanding disease and developing therapies. To address specificity and sensitivity shortcomings of existing single-cell resolution proteoform analysis tools, we introduce a hybrid microfluidic platform (DropBlot) designed for proteoform analyses in chemically fixed single cells. DropBlot serially integrates droplet-based encapsulation and lysis of single fixed cells, with on-chip microwell-based antigen retrieval, with single-cell western blotting of target antigens. A water-in-oil droplet formulation withstands the harsh chemical (SDS, 6 M urea) and thermal conditions (98 °C, 1-2 hr) required for effective antigen retrieval, and supports analysis of retrieved protein targets by single-cell electrophoresis. We demonstrate protein-target retrieval from unfixed, paraformaldehyde-fixed (PFA), and methanol-fixed cells. Key protein targets (HER2, GAPDH, EpCAM, Vimentin) retrieved from PFA-fixed cells were resolved and immunoreactive. Relevant to biorepositories, DropBlot profiled targets retrieved from human-derived breast tumor specimens archived for six years, offering a workflow for single-cell protein-biomarker analysis of sparing biospecimens.

Advanced progress of spatial metabolomics in head and neck cancer research

Head and neck cancer ranks as the sixth most prevalent malignancy, constituting 5 % of all cancer cases. Its inconspicuous onset often leads to advanced stage diagnoses, prompting the need for early detection to enhance patient prognosis. Currently, research into early diagnostic markers relies predominantly on genomics, proteomics, transcriptomics, and other methods, which, unfortunately, necessitate tumor tissue homogenization, resulting in the loss of temporal and spatial information. Emerging as a recent addition to the omics toolkit, spatial metabolomics stands out. This method conducts in situ mass spectrometry analyses on fresh tissue specimens while effectively preserving their spatiotemporal information. The utilization of spatial metabolomics in life science research offers distinct advantages. This article comprehensively reviews the progress of spatial metabolomics in head and neck cancer research, encompassing insights into cancer cell metabolic reprogramming. Various mass spectrometry imaging techniques, such as secondary ion mass spectrometry, stroma-assisted laser desorption/ionization, and desorption electrospray ionization, enable in situ metabolite analysis for head and neck cancer. Finally, significant emphasis is placed on the application of presently available techniques for early diagnosis, margin assessment, and prognosis of head and neck cancer.

Next-generation pathology practices with mass spectrometry imaging

Mass spectrometry imaging (MSI) is a powerful technique that reveals the spatial distribution of various molecules in biological samples, and it is widely used in pathology-related research. In this review, we summarize common MSI techniques, including matrix-assisted laser desorption/ionization and desorption electrospray ionization MSI, and their applications in pathological research, including disease diagnosis, microbiology, and drug discovery. We also describe the improvements of MSI, focusing on the accumulation of imaging data sets, expansion of chemical coverage, and identification of biological significant molecules, that have prompted the evolution of MSI to meet the requirements of pathology practices. Overall, this review details the applications and improvements of MSI techniques, demonstrating the potential of integrating MSI techniques into next-generation pathology practices.

DropBlot: single-cell western blotting of chemically fixed cancer cells

To further realize proteomics of archived tissues for translational research, we introduce a hybrid microfluidic platform for high-specificity, high-sensitivity protein detection from individual chemically fixed cells. To streamline processing-to-analysis workflows and minimize signal loss, DropBlot serially integrates sample preparation using droplet-based antigen retrieval from single fixed cells with unified analysis-on-a-chip comprising microwell-based antigen extraction followed by chip-based single-cell western blotting. A water-in-oil droplet formulation proves robust to the harsh chemical (SDS, 6M urea) and thermal conditions (98°C, 1-2 hr.) required for sufficient antigen retrieval, and the electromechanical conditions required for electrotransfer of retrieved antigen from microwell-encapsulated droplets to single-cell electrophoresis. Protein-target retrieval was demonstrated for unfixed, paraformaldehyde-(PFA), and methanol-fixed cells. We observed higher protein electrophoresis separation resolution from PFA-fixed cells with sufficient immunoreactivity confirmed for key targets (HER2, GAPDH, EpCAM, Vimentin) from both fixation chemistries. Multiple forms of EpCAM and Vimentin were detected, a hallmark strength of western-blot analysis. DropBlot of PFA-fixed human-derived breast tumor specimens (n = 5) showed antigen retrieval from cells archived frozen for 6 yrs. DropBlot could provide a precision integrated workflow for single-cell resolution protein-biomarker mining of precious biospecimen repositories.

Spatial metabolomics in head and neck tumors: a review

The joint analysis of single-cell transcriptomics, proteomics, lipidomics, metabolomics and spatial metabolomics is continually transforming our understanding of the mechanisms of metabolic reprogramming in tumor cells. Since head and neck tumor is the sixth most common tumor in the world, the study of the metabolic mechanism of its occurrence, development and prognosis is still undeveloped. In the past decade, this field has witnessed tremendous technological revolutions and considerable development that enables major breakthroughs to be made in the study of human tumor metabolism. In this review, a comprehensive comparison of traditional metabolomics and spatial metabolomics has been concluded, and the recent progress and challenges of the application of spatial metabolomics combined multi-omics in the research of metabolic reprogramming in tumors are reviewed. Furthermore, we also highlight the advances of spatial metabolomics in the study of metabolic mechanisms of head and neck tumors, and provide an outlook of its application prospects.

Paving the path toward multi-omics approaches in the diagnostic challenges faced in thyroid pathology

INTRODUCTION

Despite advancements in diagnostic methods, the classification of indeterminate thyroid nodules still poses diagnostic challenges not only in pre-surgical evaluation but even after histological evaluation of surgical specimens. Proteomics, aided by mass spectrometry and integrated with artificial intelligence and machine learning algorithms, shows great promise in identifying diagnostic markers for thyroid lesions.

AREAS COVERED

This review provides in-depth exploration of how proteomics has contributed to the understanding of thyroid pathology. It discusses the technical advancements related to immunohistochemistry, genetic and proteomic techniques, such as mass spectrometry, which have greatly improved sensitivity and spatial resolution up to single-cell level. These improvements allowed the identification of specific protein signatures associated with different types of thyroid lesions.

EXPERT COMMENTARY

Among all the proteomics approaches, spatial proteomics stands out due to its unique ability to capture the spatial context of proteins in both cytological and tissue thyroid samples. The integration of multi-layers of molecular information combining spatial proteomics, genomics, immunohistochemistry or metabolomics and the implementation of artificial intelligence and machine learning approaches, represent hugely promising steps forward toward the possibility to uncover intricate relationships and interactions among various molecular components, providing a complete picture of the biological landscape whilst fostering thyroid nodule diagnosis.

The Complex Cyto-Molecular Landscape of Thyroid Nodules in Pediatrics

Thyroid fine-needle aspiration (FNA) is a commonly used diagnostic cytological procedure in pediatric patients for the evaluation of thyroid nodules, triaging them for the detection of thyroid cancer. In recent years, greater attention has been paid to thyroid FNA in this setting, including the use of updated ultrasound score algorithms to improve accuracy and yield, especially considering the theoretically higher risk of malignancy of these lesions compared with the adult population, as well as to minimize patient discomfort. Moreover, molecular genetic testing for thyroid disease is an expanding field of research that could aid in distinguishing benign from cancerous nodules and assist in determining their clinical management. Finally, artificial intelligence tools can help in this task by performing a comprehensive analysis of all the obtained data. These advancements have led to greater reliance on FNA as a first-line diagnostic tool for pediatric thyroid disease. This review article provides an overview of these recent developments and their impact on the diagnosis and management of thyroid nodules in children.

Targeted Desorption Electrospray Ionization Mass Spectrometry Imaging for Drug Distribution, Toxicity, and Tissue Classification Studies

With increased use of mass spectrometry imaging (MSI) in support of pharmaceutical research and development, there are opportunities to develop analytical pipelines that incorporate exploratory high-performance analysis with higher capacity and faster targeted MSI. Therefore, to enable faster MSI data acquisition we present analyte-targeted desorption electrospray ionization–mass spectrometry imaging (DESI-MSI) utilizing a triple-quadrupole (TQ) mass analyzer. The evaluated platform configuration provided superior sensitivity compared to a conventional time-of-flight (TOF) mass analyzer and thus holds the potential to generate data applicable to pharmaceutical research and development. The platform was successfully operated with sampling rates up to 10 scans/s, comparing positively to the 1 scan/s commonly used on comparable DESI-TOF setups. The higher scan rate enabled investigation of the desorption/ionization processes of endogenous lipid species such as phosphatidylcholines and a co-administered cassette of four orally dosed drugs—erlotininb, moxifloxacin, olanzapine, and terfenadine. This was used to enable understanding of the impact of the desorption/ionization processes in order to optimize the operational parameters, resulting in improved compound coverage for olanzapine and the main olanzapine metabolite, hydroxy-olanzapine, in brain tissue sections compared to DESI-TOF analysis or matrix-assisted laser desorption/ionization (MALDI) platforms. The approach allowed reducing the amount of recorded information, thus reducing the size of datasets from up to 150 GB per experiment down to several hundred MB. The improved performance was demonstrated in case studies investigating the suitability of this approach for mapping drug distribution, spatially resolved profiling of drug-induced nephrotoxicity, and molecular–histological tissue classification of ovarian tumors specimens.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Applications of spatially resolved omics in the field of endocrine tumors

Endocrine tumors derive from endocrine cells with high heterogeneity in function, structure and embryology, and are characteristic of a marked diversity and tissue heterogeneity. There are still challenges in analyzing the molecular alternations within the heterogeneous microenvironment for endocrine tumors. Recently, several proteomic, lipidomic and metabolomic platforms have been applied to the analysis of endocrine tumors to explore the cellular and molecular mechanisms of tumor genesis, progression and metastasis. In this review, we provide a comprehensive overview of spatially resolved proteomics, lipidomics and metabolomics guided by mass spectrometry imaging and spatially resolved microproteomics directed by microextraction and tandem mass spectrometry. In this regard, we will discuss different mass spectrometry imaging techniques, including secondary ion mass spectrometry, matrix-assisted laser desorption/ionization and desorption electrospray ionization. Additionally, we will highlight microextraction approaches such as laser capture microdissection and liquid microjunction extraction. With these methods, proteins can be extracted precisely from specific regions of the endocrine tumor. Finally, we compare applications of proteomic, lipidomic and metabolomic platforms in the field of endocrine tumors and outline their potentials in elucidating cellular and molecular processes involved in endocrine tumors.

Spatial Multiomics of Lipids, N-Glycans, and Tryptic Peptides on a Single FFPE Tissue Section

Mass spectrometry imaging (MSI) is an emerging technology that is capable of mapping various biomolecules within their native spatial context, and performing spatial multiomics on formalin-fixed paraffin-embedded (FFPE) tissues may further increase the molecular characterization of pathological states. Here we present a novel workflow which enables the sequential MSI of lipids, N-glycans, and tryptic peptides on a single FFPE tissue section and highlight the enhanced molecular characterization that is offered by combining the multiple spatial omics data sets. In murine brain and clear cell renal cell carcinoma (ccRCC) tissue, the three molecular levels provided complementary information and characterized different histological regions. Moreover, when the spatial omics data was integrated, the different histopathological regions of the ccRCC tissue could be better discriminated with respect to the imaging data set of any single omics class. Taken together, these promising findings demonstrate the capability to more comprehensively map the molecular complexity within pathological tissue.

Advances in MALDI Mass Spectrometry Imaging Single Cell and Tissues

Compared with conventional optical microscopy techniques, mass spectrometry imaging (MSI) or imaging mass spectrometry (IMS) is a powerful, label-free analytical technique, which can sensitively and simultaneously detect, quantify, and map hundreds of biomolecules, such as peptides, proteins, lipid, and other organic compounds in cells and tissues. So far, although several soft ionization techniques, such as desorption electrospray ionization (DESI) and secondary ion mass spectrometry (SIMS) have been used for imaging biomolecules, matrix-assisted laser desorption/ionization (MALDI) is still the most widespread MSI scanning method. Here, we aim to provide a comprehensive review of MALDI-MSI with an emphasis on its advances of the instrumentation, methods, application, and future directions in single cell and biological tissues.

Lipidomic Typing of Colorectal Cancer Tissue Containing Tumour-Infiltrating Lymphocytes by MALDI Mass Spectrometry Imaging

Predicting the prognosis of colorectal cancer (CRC) patients remains challenging and a characterisation of the tumour immune environment represents one of the most crucial avenues when attempting to do so. For this reason, molecular approaches which are capable of classifying the immune environments associated with tumour infiltrating lymphocytes (TILs) are being readily investigated. In this proof of concept study, we aim to explore the feasibility of using spatial lipidomics by MALDI-MSI to distinguish CRC tissue based upon their TIL content. Formalin-fixed paraffin-embedded tissue from human thymus and tonsil was first analysed by MALDI-MSI to obtain a curated mass list from a pool of single positive T lymphocytes, whose putative identities were annotated using an LC-MS-based lipidomic approach. A CRC tissue microarray (TMA, n = 30) was then investigated to determine whether these cases could be distinguished based upon their TIL content in the tumour and its microenvironment. MALDI-MSI from the pool of mature T lymphocytes resulted in the generation of a curated mass list containing 18 annotated m/z features. Initially, subsets of T lymphocytes were then distinguished based on their state of maturation and differentiation in the human thymus and tonsil tissue. Then, when applied to a CRC TMA containing differing amounts of T lymphocyte infiltration, those cases with a high TIL content were distinguishable from those with a lower TIL content, especially within the tumour microenvironment, with three lipid signals being shown to have the greatest impact on this separation (p < 0.05). On the whole, this preliminary study represents a promising starting point and suggests that a lipidomics MALDI-MSI approach could be a promising tool for subtyping the diverse immune environments in CRC.

Elaboration Pipeline for the Management of MALDI-MS Imaging Datasets

Matrix-assisted laser desorption/ionization (MALDI)-time of flight (TOF)-mass spectrometry imaging (MSI) enables the spatial localization of proteins to be mapped directly on tissue sections, simultaneously detecting hundreds in a single analysis. However, the large data size, as well as the complexity of MALDI-MSI proteomics datasets, requires the appropriate tools and statistical approaches in order to reduce the complexity and mine the dataset in a successful manner. Here, a pipeline for the management of MALDI-MSI data is described, starting with preprocessing of the raw data, followed by statistical analysis using both supervised and unsupervised statistical approaches and, finally, annotation of those discriminatory protein signals highlighted by the data mining procedure.

Current status of the prognostic molecular markers in medullary thyroid carcinoma

Medullary thyroid cancer (MTC) is a rare thyroid malignancy, which arises from parafollicular C-cells. It occurs in the hereditary or sporadic form. Hereditary type is a consequence of activation of the RET proto-oncogene by germline mutations, whereas about 80% of sporadic MTC tumors harbor somatic, mainly RET or rarely RAS mutations. According to the current ATA guidelines, a postoperative MTC risk stratification and long-term follow-up are mainly based on histopathological data, including tumor stage, the presence of lymph node and/or distant metastases (TNM classification), and serum concentration of two biomarkers: calcitonin (Ctn) and carcinoembryonic antigen (CEA). The type of RET germline mutation also correlates with MTC clinical characteristics. The most common and the best known RET mutation in sporadic MTC, localized at codon 918, is related to a more aggressive MTC course and poorer survival. However, even if histopathological or clinical features allow to predict a long-term prognosis, they are not sufficient to select the patients showing aggressive MTC courses requiring immediate treatment or those, who are refractory to different therapeutic methods. Besides the RET gene mutations, there are currently no other reliable molecular prognostic markers. This review summarizes the present data of genomic investigation on molecular prognostic factors in medullary thyroid cancer.

Antigen Retrieval and Its Effect on the MALDI-MSI of Lipids in Formalin-Fixed Paraffin-Embedded Tissue

Formalin-fixed paraffin-embedded (FFPE) tissue represents the primary source of clinical tissue and is routinely used in MALDI-MSI studies. However, it is not particularly suitable for lipidomics imaging given that many species are depleted during tissue processing. Irrespective, a number of solvent-resistant lipids remain, but their extraction may be hindered by the cross-link between proteins. Therefore, an antigen retrieval step could enable the extraction of a greater number of lipids and may provide information that is complementary to that which can be obtained from other biomolecules, such as proteins. In this short communication, we aim to address the effect of performing antigen retrieval prior to MALDI-MSI of lipids in FFPE tissue. As a result, an increased number of lipid signals could be detected and may have derived from lipid species that are known to be implicated in the lipid-protein cross-linking that is formed as a result of formalin fixation. Human renal cancer tissue was used as a proof of concept to determine whether using these detected lipid signals were also able to highlight the histopathological regions that were present. These preliminary findings may highlight the potential to enhance the clinical relevance of the lipidomic information obtained from FFPE tissue.

LipostarMSI: Comprehensive, Vendor-Neutral Software for Visualization, Data Analysis, and Automated Molecular Identification in Mass Spectrometry Imaging

Mass Spectrometry Imaging (MSI) is an established and powerful MS technique that enables molecular mapping of tissues and cells finding widespread applications in academic, medical, and pharmaceutical industries. As both the applications and MSI technology have undergone rapid growth and improvement, the challenges associated both with analyzing large datasets and identifying the many detected molecular species have become apparent. The lack of readily available and comprehensive software covering all necessary data analysis steps has further compounded this challenge. To address this issue we developed LipostarMSI, comprehensive and vendor-neutral software for targeted and untargeted MSI data analysis. Through user-friendly implementation of image visualization and co-registration, univariate and multivariate image and spectral analysis, and for the first time, advanced lipid, metabolite, and drug metabolite (MetID) automated identification, LipostarMSI effectively streamlines biochemical interpretation of the data. Here, we introduce LipostarMSI and case studies demonstrating the versatility and many capabilities of the software.

Nanomedicines for Near-Infrared Fluorescent Lifetime-Based Bioimaging

Nanomedicines refer to the application of nanotechnology in disease diagnosis, treatment, and monitoring. Bioimaging provides crucial biological information for disease diagnosis and treatment monitoring. Fluorescent bioimaging shows the advantages of good contrast and a vast variety of signal readouts and yet suffers from imaging depth due to the background noise from the autofluorescence of tissue and light scattering. Near-infrared fluorescent lifetime bioimaging (NIR- FLTB) suppresses such background noises and significantly improves signal-to-background ratio. This article gives an overview of recent advances in NIR- FLTB using organic compounds and nanomaterials as contrast agent (CA). The advantages and disadvantages of each CA are discussed in detail. We survey relevant reports about NIR-FLTB in recent years and summarize important findings or progresses. In addition, emerging hybrid bioimaging techniques are introduced, such as ultrasound-modulated FLTB. The challenges and an outlook for NIR- FLTB development are discussed at the end, aiming to provide references and inspire new ideas for future nanomedicine development.

MALDI-MSI as a Complementary Diagnostic Tool in Cytopathology: A Pilot Study for the Characterization of Thyroid Nodules

The present study applies for the first time as Matrix-Assisted Laser Desorption/Ionization (MALDI) Mass Spectrometry Imaging (MSI) on real thyroid Fine Needle Aspirations (FNAs) to test its possible complementary role in routine cytology in the diagnosis of thyroid nodules. The primary aim is to evaluate the potential employment of MALDI-MSI in cytopathology, using challenging samples such as needle washes. Firstly, we designed a statistical model based on the analysis of Regions of Interest (ROIs), according to the morphological triage performed by the pathologist. Successively, the capability of the model to predict the classification of the FNAs was validated in a different group of patients on ROI and pixel-by-pixel approach. Results are very promising and highlight the possibility to introduce MALDI-MSI as a complementary tool for the diagnostic characterization of thyroid nodules.

Oncoproteomics: Current status and future opportunities

Oncoproteomics is the systematic study of cancer samples using omics technologies to detect changes implicated in tumorigenesis. Recent progress in oncoproteomics is already opening new avenues for the identification of novel biomarkers for early clinical stage cancer detection, targeted molecular therapies, disease monitoring, and drug development. Such information will lead to new understandings of cancer biology and impact dramatically on the future care of cancer patients. In this review, we will summarize the advantages and limitations of the key technologies used in (onco)proteogenomics, (the Omics Pipeline), explain how they can assist us in understanding the biology behind the overarching "Hallmarks of Cancer", discuss how they can advance the development of precision/personalised medicine and the future directions in the field.

Novel Prognostic Markers in Triple-Negative Breast Cancer Discovered by MALDI-Mass Spectrometry Imaging

There are no widely-accepted prognostic markers currently available to predict outcomes in patients with triple-negative breast cancer (TNBC), and no targeted therapies with confirmed benefit. We have used MALDI mass spectrometry imaging (MSI) of tryptic peptides to compare regions of cancer and benign tissue in 10 formalin-fixed, paraffin-embedded sections of TNBC tumors. Proteins were identified by reference to a peptide library constructed by LC-MALDI-MS/MS analyses of the same tissues. The prognostic significance of proteins that distinguished between cancer and benign regions was estimated by Kaplan-Meier analysis of their gene expression from public databases. Among peptides that distinguished between cancer and benign tissue in at least 3 tissues with a ROC area under the curve >0.7, 14 represented proteins identified from the reference library, including proteins not previously associated with breast cancer. Initial network analysis using the STRING database showed no obvious functional relationships except among collagen subunits COL1A1, COL1A2, and COL63A, but manual curation, including the addition of EGFR to the analysis, revealed a unique network connecting 10 of the 14 proteins. Kaplan-Meier survival analysis to examine the relationship between tumor expression of genes encoding the 14 proteins, and recurrence-free survival (RFS) in patients with basal-like TNBC showed that, compared to low expression, high expression of nine of the genes was associated with significantly worse RFS, most with hazard ratios >2. In contrast, in estrogen receptor-positive tumors, high expression of these genes showed only low, or no, association with worse RFS. These proteins are proposed as putative markers of RFS in TNBC, and some may also be considered as possible targets for future therapies.

The Reproducibility of the Immunohistochemical PD-L1 Testing in Non-Small-Cell Lung Cancer: A Multicentric Italian Experience

An important harmonization effort was produced by the scientific community to standardize both the preanalytical and interpretative phases of programmed death-ligand 1 (PD-L1) immunohistochemical (IHC) testing in non-small-cell lung cancer (NSCLC). This analysis is crucial for the selection of patients with advanced-stage tumors eligible for treatment with pembrolizumab and potentially with other anti-PD-1/PD-L1 checkpoint inhibitors. This multicentric retrospective study evaluated the reproducibility of PD-L1 testing in the Italian scenario both for closed and open platforms. In the evaluation of the well-known gold-standard combinations (Agilent 22C3 PharmDx on Dako Autostainer versus Roche's Ventana SP263 on BenchMark), the results confirmed the literature data and showed complete overlapping between the two methods. With regard to the performances by using open platforms, the combination of 22C3 with Dako Omnis or Benchmark obtained good results basically, while the 28,8 clone seemed to be associated with worse scores.

Novel methods in adrenal research: a metabolomics approach

Metabolic alterations have implications in a spectrum of tissue functions and disease. Aided by novel molecular biological and computational tools, our understanding of physiological and pathological processes underpinning endocrine and endocrine-related disease has significantly expanded over the last decade. Herein, we focus on novel metabolomics-related methodologies in adrenal research: in situ metabolomics by mass spectrometry imaging, steroid metabolomics by gas and liquid chromatography-mass spectrometry, energy pathway metabologenomics by liquid chromatography-mass spectrometry-based metabolomics of Krebs cycle intermediates, and cellular reprogramming to generate functional steroidogenic cells and hence to modulate the steroid metabolome. All four techniques to assess and/or modulate the metabolome in biological systems provide tremendous opportunities to manage neoplastic and non-neoplastic disease of the adrenal glands in the era of precision medicine. In this context, we discuss emerging clinical applications and/or promising metabolic-driven research towards diagnostic, prognostic, predictive and therapeutic biomarkers in tumours arising from the adrenal gland and extra-adrenal paraganglia as well as modern approaches to delineate and reprogram adrenal metabolism.

Proteome Imaging: From Classic to Modern Mass Spectrometry-Based Molecular Histology

In order to overcome the limitations of classic imaging in Histology during the actually era of multiomics, the multi-color "molecular microscope" by its emerging "molecular pictures" offers quantitative and spatial information about thousands of molecular profiles without labeling of potential targets. Healthy and diseased human tissues, as well as those of diverse invertebrate and vertebrate animal models, including genetically engineered species and cultured cells, can be easily analyzed by histology-directed MALDI imaging mass spectrometry. The aims of this review are to discuss a range of proteomic information emerging from MALDI mass spectrometry imaging comparative to classic histology, histochemistry and immunohistochemistry, with applications in biology and medicine, concerning the detection and distribution of structural proteins and biological active molecules, such as antimicrobial peptides and proteins, allergens, neurotransmitters and hormones, enzymes, growth factors, toxins and others. The molecular imaging is very well suited for discovery and validation of candidate protein biomarkers in neuroproteomics, oncoproteomics, aging and age-related diseases, parasitoproteomics, forensic, and ecotoxicology. Additionally, in situ proteome imaging may help to elucidate the physiological and pathological mechanisms involved in developmental biology, reproductive research, amyloidogenesis, tumorigenesis, wound healing, neural network regeneration, matrix mineralization, apoptosis and oxidative stress, pain tolerance, cell cycle and transformation under oncogenic stress, tumor heterogeneity, behavior and aggressiveness, drugs bioaccumulation and biotransformation, organism's reaction against environmental penetrating xenobiotics, immune signaling, assessment of integrity and functionality of tissue barriers, behavioral biology, and molecular origins of diseases. MALDI MSI is certainly a valuable tool for personalized medicine and "Eco-Evo-Devo" integrative biology in the current context of global environmental challenges.

Site-to-Site Reproducibility and Spatial Resolution in MALDI-MSI of Peptides from Formalin-Fixed Paraffin-Embedded Samples

PURPOSE

To facilitate the transition of MALDI-MS Imaging (MALDI-MSI) from basic science to clinical application, it is necessary to analyze formalin-fixed paraffin-embedded (FFPE) tissues. The aim is to improve in situ tryptic digestion for MALDI-MSI of FFPE samples and determine if similar results would be reproducible if obtained from different sites.

EXPERIMENTAL DESIGN

FFPE tissues (mouse intestine, human ovarian teratoma, tissue microarray of tumor entities sampled from three different sites) are prepared for MALDI-MSI. Samples are coated with trypsin using an automated sprayer then incubated using deliquescence to maintain a stable humid environment. After digestion, samples are sprayed with CHCA using the same spraying device and analyzed with a rapifleX MALDI Tissuetyper at 50 µm spatial resolution. Data are analyzed using flexImaging, SCiLS, and R.

RESULTS

Trypsin application and digestion are identified as sources of variation and loss of spatial resolution in the MALDI-MSI of FFPE samples. Using the described workflow, it is possible to discriminate discrete histological features in different tissues and enabled different sites to generate images of similar quality when assessed by spatial segmentation and PCA.

CONCLUSIONS AND CLINICAL RELEVANCE

Spatial resolution and site-to-site reproducibility can be maintained by adhering to a standardized MALDI-MSI workflow.

Metabolomics and Biomarker Discovery

Recently, metabolomics-the study of metabolite profiles within biological samples-has found a wide range of applications. This chapter describes the different techniques available for metabolomic analysis, the various samples that can be utilised for analysis and applications of both global and targeted metabolomic analysis to biomarker discovery in medicine.

Update on: proteome analysis in thyroid pathology - part II: overview of technical and clinical enhancement of proteomic investigation of the thyroid lesions

INTRODUCTION

An accurate diagnostic classification of thyroid lesions remains an important clinical aspect that needs to be addressed in order to avoid 'diagnostic' thyroidectomies. Among the several 'omics' techniques, proteomics is playing a pivotal role in the search for diagnostic markers. In recent years, different approaches have been used, taking advantage of the technical improvements related to mass spectrometry that have occurred. Areas covered: The review provides an update of the recent findings in diagnostic classification, in genetic definition and in the investigation of thyroid lesions based on different proteomics approaches and on different type of specimens: cytological, surgical and biofluid samples. A brief section will discuss how these findings can be integrated with those obtained by metabolomics investigations. Expert commentary: Among the several proteomics approaches able to deepen our knowledge of the molecular alterations of the different thyroid lesions, MALDI-MSI is strongly emerging above all. In fact, MS-imaging has also been demonstrated to be capable of distinguishing thyroid lesions, based on their different molecular signatures, using cytological specimens. The possibility to use the material obtained by the fine needle aspiration makes MALDI-MSI a highly promising technology that could be implemented into the clinical and pathological units.

MALDI mass spectrometry imaging and in situ microproteomics of Listeria monocytogenes biofilms

MALDI-TOF Mass spectrometry Imaging (MSI) is a surface-sampling technology that can determine spatial information and relative abundance of analytes directly from biological samples. Human listeriosis cases are due to the ingestion of contaminated foods with the pathogenic bacteria Listeria monocytogenes. The reduction of water availability in food workshops by decreasing the air relative humidity (RH) is one strategy to improve the control of bacterial contamination. This study aims to develop and implement an MSI approach on L. monocytogenes biofilms and proof of concept using a dehumidified stress condition. MSI allowed examining the distribution of low molecular weight proteins within the biofilms subjected to a dehumidification environment, mimicking the one present in a food workshop (10 °C, 75% RH). Furthermore, a LC-MS/MS approach was made to link the dots between MSI and protein identification. Five identified proteins were assigned to registered MSI m/z, including two cold-shock proteins and a ligase involved in cell wall biogenesis. These data demonstrate how imaging can be used to dissect the proteome of an intact bacterial biofilm giving new insights into protein expression relating to a dehumidification stress adaptation. Data are available via ProteomeXchange with identifier PXD010444.

BIOLOGICAL SIGNIFICANCE

The ready-to-eat food processing industry has the daily challenge of controlling the contamination of surfaces and machines with spoilage and pathogenic microorganisms. In some cases, it is a lost cause due to these microorganisms' capacity to withstand the cleaning treatments, like desiccation procedures. Such a case is the ubiquitous Gram-positive Bacterium Listeria monocytogenes. Its surface proteins have particular importance for the interaction with its environment, being important factors contributing to adaptation to stress conditions. There are few reproducibly techniques to obtain the surface proteins of Gram-positive cells. Here, we developed a workflow that enables the use of MALDI imaging on Gram-positive bacterium biofilms to study the impact of dehumidification on sessile cells. It will be of the most interest to test this workflow with different environmental conditions and potentially apply it to other biofilm-forming bacteria.