Mass spectrometry MALDI imaging of colon cancer biomarkers: a new diagnostic paradigm

A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research

Clinical metabolomics emerged as a novel approach for biomarker discovery with the translational potential to guide next-generation therapeutics and precision health interventions. However, reproducibility in clinical research employing metabolomics data is challenging. Checklists are a helpful tool for promoting reproducible research. Existing checklists that promote reproducible metabolomics research primarily focused on metadata and may not be sufficient to ensure reproducible metabolomics data processing. This paper provides a checklist including actions that need to be taken by researchers to make computational steps reproducible for clinical metabolomics studies. We developed an eight-item checklist that includes criteria related to reusable data sharing and reproducible computational workflow development. We also provided recommended tools and resources to complete each item, as well as a GitHub project template to guide the process. The checklist is concise and easy to follow. Studies that follow this checklist and use recommended resources may facilitate other researchers to reproduce metabolomics results easily and efficiently.

Mass spectrometry-based metabolomics in health and medical science: a systematic review

Metabolomics is the study of the investigation of small molecules derived from cellular and organism metabolism, which reflects the outcomes of the complex network of biochemical reactions in living systems.

Unraveling local tissue changes within severely injured skeletal muscles in response to MSC-based intervention using MALDI Imaging mass spectrometry

Pre-clinical and clinical studies are now beginning to demonstrate the high potential of cell therapies in enhancing muscle regeneration. We previously demonstrated functional benefit after the transplantation of autologous bone marrow mesenchymal stromal cells (MSC-TX) into a severe muscle crush trauma model. Despite our increasing understanding of the molecular and cellular mechanisms underlying MSC's regenerative function, little is known about the local molecular alterations and their spatial distribution within the tissue after MSC-TX. Here, we used MALDI imaging mass spectrometry (MALDI-IMS) in combination with multivariate statistical strategies to uncover previously unknown peptide alterations within severely injured skeletal muscles. Our analysis revealed that very early molecular alterations in response to MSC-TX occur largely in the region adjacent to the trauma and only to a small extent in the actual trauma region. Using "bottom up" mass spectrometry, we subsequently identified the proteins corresponding to the differentially expressed peptide intensity distributions in the specific muscle regions and used immunohistochemistry to validate our results. These findings extend our current understanding about the early molecular processes of muscle healing and highlights the critical role of trauma adjacent tissue during the early therapeutic response upon treatment with MSC.

Biomarker discovery by proteomics-based approaches for early detection and personalized medicine in colorectal cancer

About one million people per year develop colorectal cancer (CRC) and approximately half of them die. The extent of the disease (i.e. local invasion at the time of diagnosis) is a key prognostic factor. The 5-year survival rate is almost 90% in the case of delimited CRC and 10% in the case of metastasized CRC. Hence, one of the great challenges in the battle against CRC is to improve early diagnosis strategies. Large-scale proteomic approaches are widely used in cancer research to search for novel biomarkers. Such biomarkers can help in improving the accuracy of the diagnosis and in the optimization of personalized therapy. Herein, we provide an overview of studies published in the last 5 years on CRC that led to the identification of protein biomarkers suitable for clinical application by using proteomic approaches. We discussed these findings according to biomarker application, including also the role of protein phosphorylation and cancer stem cells in biomarker discovery. Our review provides a cross section of scientific approaches and can furnish suggestions for future experimental strategies to be used as reference by scientists, clinicians and researchers interested in proteomics for biomarker discovery.

MALDI imaging mass spectrometry: discrimination of pathophysiological regions in traumatized skeletal muscle by characteristic peptide signatures

Due to formation of fibrosis and the loss of contractile muscle tissue, severe muscle injuries often result in insufficient healing marked by a significant reduction of muscle force and motor activity. Our previous studies demonstrated that the local transplantation of mesenchymal stromal cells into an injured skeletal muscle of the rat improves the functional outcome of the healing process. Since, due to the lack of sufficient markers, the accurate discrimination of pathophysiological regions in injured skeletal muscle is inadequate, underlying mechanisms of the beneficial effects of mesenchymal stromal cell transplantation on primary trauma and trauma adjacent muscle area remain elusive. For discrimination of these pathophysiological regions, formalin-fixed injured skeletal muscle tissue was analyzed by MALDI imaging MS. By using two computational evaluation strategies, a supervised approach (ClinProTools) and unsupervised segmentation (SCiLS Lab), characteristic m/z species could be assigned to primary trauma and trauma adjacent muscle regions. Using "bottom-up" MS for protein identification and validation of results by immunohistochemistry, we could identify two proteins, skeletal muscle alpha actin and carbonic anhydrase III, which discriminate between the secondary damage on adjacent tissue and the primary traumatized muscle area. Our results underscore the high potential of MALDI imaging MS to describe the spatial characteristics of pathophysiological changes in muscle.

MALDI MS imaging as a tool for biomarker discovery: methodological challenges in a clinical setting

MALDI MS imaging (MSI) is an analytical tool capable of providing spatial distribution and relative abundance of biomolecules directly in tissue. After 15 years of intense efforts to improve the acquisition and quality of molecular images, MSI has matured into an asset of the proteomic toolbox. The power of MSI lies in the ability to differentiate tissue regions that are not histologically distinct but are characterized by different MS profiles. Recently, MSI has been gaining momentum in biomedical research and has found applications in disease diagnosis and prognosis, biomarker discovery, and drug therapy. Although the technology holds great promise, MSI is still faced with a set of methodological challenges presented by the clinical setting. There is a growing awareness regarding this topic and efforts are being taken to develop clear and practical standards to overcome these challenges. This review presents an overview of MALDI MSI as a biomarker discovery tool and recent methodological progress in the field.

The Role of Mass Spectrometry in the "Omics" Era

Mass spectrometry (MS) is one of the key analytical technology on which the emerging ''-omics'' approaches are based. It may provide detection and quantization of thousands of proteins and biologically active metabolites from a tissue, body fluid or cell culture working in a ''global'' or ''targeted'' manner, down to ultra-trace levels. It can be expected that the high performance of MS technology, coupled to routine data handling, will soon bring fruit in the request for a better understanding of human diseases, leading to new molecular biomarkers, hence affecting drug targets and therapies. In this review, we focus on the main advances in the MS technologies, influencing genomics, transcriptomics, proteomics, lipidomics and metabolomics fields, up to the most recent MS applications to meta-omic studies.

Microscopic imaging mass spectrometry assisted by on-tissue chemical derivatization for visualizing multiple amino acids in human colon cancer xenografts

Imaging MS combined with CE/MS serves as a method to provide semi-quantitative and spatial information of small molecular metabolites in tissue slices. However, not all metabolites including amino acids have fully been visualized, because of low-ionization efficiency in MALDI MS. This study aimed to acquire semi-quantitative spatial information for multiple amino acids in frozen tissue slices. As a derivatization reagent, p-N,N,N-trimethylammonioanilyl N'-hydroxysuccinimidyl carbamate iodide (TAHS) was applied to increase their ionization efficiency and detection sensitivity. Semi-quantitative MALDI-imaging MS allowed us to visualize and quantify free amino acid pools in human colon cancer xenografts using a model of liver metastases in super-immunodeficient NOD/scid/γ(null) mice (NOG mice). Because the m/z values of several TAHS-derivatized amino acids overlap with those of the 2,5-dihydroxybenzoic acid background and other endogenous compounds, we imaged them with tandem MS. The results indicated that regional contents of glutamate, glutamine, glycine, leucine/isoleucine/hydroxyproline, phenylalanine, and alanine were significantly elevated in metastatic tumors versus parenchyma of tumor-bearing livers. On-tissue TAHS derivatization thus serves as a useful method to detect alterations in many amino acid levels in vivo, thereby enabling understanding of the spatial alterations of these metabolites under varied disease conditions including cancer.

Identification of biological tissues by rapid evaporative ionization mass spectrometry

The newly developed rapid evaporative ionization mass spectrometry (REIMS) provides the possibility of in vivo, in situ mass spectrometric tissue analysis. The experimental setup for REIMS is characterized in detail for the first time, and the description and testing of an equipment capable of in vivo analysis is presented. The spectra obtained by various standard surgical equipments were compared and found highly specific to the histological type of the tissues. The tissue analysis is based on their different phospholipid distribution; the identification algorithm uses a combination of principal component analysis (PCA) and linear discriminant analysis (LDA). The characterized method was proven to be sensitive for any perturbation such as age or diet in rats, but it was still perfectly suitable for tissue identification. Tissue identification accuracy higher than 97% was achieved with the PCA/LDA algorithm using a spectral database collected from various tissue species. In vivo, ex vivo, and post mortem REIMS studies were performed, and the method was found to be applicable for histological tissue analysis during surgical interventions, endoscopy, or after surgery in pathology.

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.

Peptide and protein imaging mass spectrometry in cancer research

MALDI mass spectrometry is able to acquire protein profiles directly from tissue that can describe the levels of hundreds of distinct proteins. MALDI imaging MS can simultaneously reveal how each of these proteins varies in heterogeneous tissues. Numerous studies have now demonstrated how MALDI imaging MS can generate different protein profiles from the different cell types in a tumor, which can act as biomarker profiles or enable specific candidate protein biomarkers to be identified. MALDI imaging MS can be directly applied to patient samples where its utility is to accomplish untargeted multiplex analysis of the tissue's protein content, enabling the different regions of the tissue to be differentiated on the basis of previously unknown protein profiles/biomarkers. The technique continues to rapidly develop and is now approaching the cusp whereby its potential to provide new diagnostic/prognostic tools for cancer patients can be routinely investigated. Here the latest methodological developments are summarized and its application to a range of tumors is reported in detail. The prospects of MALDI imaging MS are then described from the perspectives of modern pathological practice and MS-based proteomics, to ensure the outlook addresses real clinical needs and reflects the real capabilities of MS-based proteomics of complex tissue samples.

Atmospheric pressure laser desorption/ionization of plant metabolites and plant tissue using colloidal graphite

Colloidal graphite is a promising matrix for atmospheric pressure laser desorption/ionization mass spectrometry. Intact [M+H](+) and [M-H](-) ions are readily produced from a wide range of small molecule plant metabolites, particularly anthocyanins, fatty acids, lipids, glycerides, and ceramides. Compared with a more traditional organic acid matrix, colloidal graphite provides more efficient ionization for small hydrophobic molecules and has a much cleaner background spectrum, especially in negative ion mode. Some important metabolites, e.g., fatty acids and glycosylated flavonoids, can be observed from Arabidopsis thaliana leaf and flower petal tissues in situ.

Matrix-assisted laser desorption/ionization imaging mass spectrometry of oxaliplatin derivatives in heated intraoperative chemotherapy (HIPEC)-like treated rat kidney

Oxaliplatin [1,2-diaminocyclohexane (dach)-Pt complex] is a platinum anticancer drug which is mainly used in the treatment of advanced colorectal cancer, particularly in Heated Intraoperative Chemotherapy (HIPEC) for the treatment of colorectal peritoneal carcinomatosis. In order to better understand the penetration of oxaliplatin in treated tissues we performed a direct imaging of tissue sections from HIPEC-like treated rat kidney using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry. This procedure allowed the detection and localization of oxaliplatin and its metabolites, the monocysteine and monomethionine complexes, in kidney sections. Specifically, oxaliplatin and its metabolites were localized exclusively in the kidney cortex, suggesting that it did not penetrate deeply into the organ. Based on these results, an imaging analysis of human tumors collected after HIPEC is currently in progress to assess the distribution of oxaliplatin and/or metabolites with the aim of defining clinical conditions to improve drug penetration.