Imaging mass spectrometry of a specific fragment of mitogen-activated protein kinase/extracellular signal-regulated kinase kinase kinase 2 discriminates cancer from uninvolved prostate tissue

The glycosylation landscape of prostate cancer tissues and biofluids

An overview of the role of glycosylation in prostate cancer (PCa) development and progression is presented, focusing on recent advancements in defining the N-glycome through glycomic profiling and glycoproteomic methodologies. Glycosylation is a common post-translational modification typified by oligosaccharides attached N-linked to asparagine or O-linked to serine or threonine on carrier proteins. These attached sugars have crucial roles in protein folding and cellular recognition processes, such that altered glycosylation is a hallmark of cancer pathogenesis and progression. In the past decade, advancements in N-glycan profiling workflows using Matrix Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) technology have been applied to define the spatial distribution of glycans in PCa tissues. Multiple studies applying N-glycan MALDI-MSI to pathology-defined PCa tissues have identified significant alterations in N-glycan profiles associated with PCa progression. N-glycan compositions progressively increase in number, and structural complexity due to increased fucosylation and sialylation. Additionally, significant progress has been made in defining the glycan and glycopeptide compositions of prostatic-derived glycoproteins like prostate-specific antigen in tissues and biofluids. The glycosyltransferases involved in these changes are potential drug targets for PCa, and new approaches in this area are summarized. These advancements will be discussed in the context of the further development of clinical diagnostics and therapeutics targeting glycans and glycoproteins associated with PCa progression. Integration of large scale spatial glycomic data for PCa with other spatial-omic methodologies is now feasible at the tissue and single-cell levels.

The SMYD3-MAP3K2 signaling axis promotes tumor aggressiveness and metastasis in prostate cancer

Aberrant activation of Ras/Raf/mitogen-activated protein kinase (MAPK) signaling is frequently linked to metastatic prostate cancer (PCa); therefore, the characterization of modulators of this pathway is critical for defining therapeutic vulnerabilities for metastatic PCa. The lysine methyltransferase SET and MYND domain 3 (SMYD3) methylates MAPK kinase kinase 2 (MAP3K2) in some cancers, causing enhanced activation of MAPK signaling. In PCa, SMYD3 is frequently overexpressed and associated with disease severity; however, its molecular function in promoting tumorigenesis has not been defined. We demonstrate that SMYD3 critically regulates tumor-associated phenotypes via its methyltransferase activity in PCa cells and mouse xenograft models. SMYD3-dependent methylation of MAP3K2 promotes epithelial-mesenchymal transition associated behaviors by altering the abundance of the intermediate filament vimentin. Furthermore, activation of the SMYD3-MAP3K2 signaling axis supports a positive feedback loop continually promoting high levels of SMYD3. Our data provide insight into signaling pathways involved in metastatic PCa and enhance understanding of mechanistic functions for SMYD3 to reveal potential therapeutic opportunities for PCa.

Spatial Omics Imaging of Fresh-Frozen Tissue and Routine FFPE Histopathology of a Single Cancer Needle Core Biopsy: A Freezing Device and Multimodal Workflow

The complex molecular alterations that underlie cancer pathophysiology are studied in depth with omics methods using bulk tissue extracts. For spatially resolved tissue diagnostics using needle biopsy cores, however, histopathological analysis using stained FFPE tissue and the immunohistochemistry (IHC) of a few marker proteins is currently the main clinical focus. Today, spatial omics imaging using MSI or IRI is an emerging diagnostic technology for the identification and classification of various cancer types. However, to conserve tissue-specific metabolomic states, fast, reliable, and precise methods for the preparation of fresh-frozen (FF) tissue sections are crucial. Such methods are often incompatible with clinical practice, since spatial metabolomics and the routine histopathology of needle biopsies currently require two biopsies for FF and FFPE sampling, respectively. Therefore, we developed a device and corresponding laboratory and computational workflows for the multimodal spatial omics analysis of fresh-frozen, longitudinally sectioned needle biopsies to accompany standard FFPE histopathology of the same biopsy core. As a proof-of-concept, we analyzed surgical human liver cancer specimens using IRI and MSI with precise co-registration and, following FFPE processing, by sequential clinical pathology analysis of the same biopsy core. This workflow allowed for a spatial comparison between different spectral profiles and alterations in tissue histology, as well as a direct comparison for histological diagnosis without the need for an extra biopsy.

An optimized MALDI MSI protocol for spatial detection of tryptic peptides in fresh frozen prostate tissue

MALDI MS imaging (MSI) is a powerful analytical tool for spatial peptide detection in heterogeneous tissues. Proper sample preparation is crucial to achieve high quality, reproducible measurements. Here we developed an optimized protocol for spatially resolved proteolytic peptide detection with MALDI time-of-flight MSI of fresh frozen prostate tissue sections. The parameters tested included four different tissue washes, four methods of protein denaturation, four methods of trypsin digestion (different trypsin densities, sprayers, and incubation times), and five matrix deposition methods (different sprayers, settings, and matrix concentrations). Evaluation criteria were the number of detected and excluded peaks, percentage of high mass peaks, signal-to-noise ratio, spatial localization, and average intensities of identified peptides, all of which were integrated into a weighted quality evaluation scoring system. Based on these scores, the optimized protocol included an ice-cold EtOH+H2 O wash, a 5 min heating step at 95°C, tryptic digestion incubated for 17h at 37°C and CHCA matrix deposited at a final amount of 1.8 μg/mm2 . Including a heat-induced protein denaturation step after tissue wash is a new methodological approach that could be useful also for other tissue types. This optimized protocol for spatial peptide detection using MALDI MSI facilitates future biomarker discovery in prostate cancer and may be useful in studies of other tissue types.

Moving translational mass spectrometry imaging towards transparent and reproducible data analyses: a case study of an urothelial cancer cohort analyzed in the Galaxy framework

Background

Mass spectrometry imaging (MSI) derives spatial molecular distribution maps directly from clinical tissue specimens and thus bears great potential for assisting pathologists with diagnostic decisions or personalized treatments. Unfortunately, progress in translational MSI is often hindered by insufficient quality control and lack of reproducible data analysis. Raw data and analysis scripts are rarely publicly shared. Here, we demonstrate the application of the Galaxy MSI tool set for the reproducible analysis of a urothelial carcinoma dataset.

Methods

Tryptic peptides were imaged in a cohort of 39 formalin-fixed, paraffin-embedded human urothelial cancer tissue cores with a MALDI-TOF/TOF device. The complete data analysis was performed in a fully transparent and reproducible manner on the European Galaxy Server. Annotations of tumor and stroma were performed by a pathologist and transferred to the MSI data to allow for supervised classifications of tumor vs. stroma tissue areas as well as for muscle-infiltrating and non-muscle infiltrating urothelial carcinomas. For putative peptide identifications, m/z features were matched to the MSiMass list.

Results

Rigorous quality control in combination with careful pre-processing enabled reduction of m/z shifts and intensity batch effects. High classification accuracy was found for both, tumor vs. stroma and muscle-infiltrating vs. non-muscle infiltrating urothelial tumors. Some of the most discriminative m/z features for each condition could be assigned a putative identity: stromal tissue was characterized by collagen peptides and tumor tissue by histone peptides. Immunohistochemistry confirmed an increased histone H2A abundance in the tumor compared to the stroma tissues. The muscle-infiltration status was distinguished via MSI by peptides from intermediate filaments such as cytokeratin 7 in non-muscle infiltrating carcinomas and vimentin in muscle-infiltrating urothelial carcinomas, which was confirmed by immunohistochemistry. To make the study fully reproducible and to advocate the criteria of FAIR (findability, accessibility, interoperability, and reusability) research data, we share the raw data, spectra annotations as well as all Galaxy histories and workflows. Data are available via ProteomeXchange with identifier PXD026459 and Galaxy results via https://github.com/foellmelanie/Bladder_MSI_Manuscript_Galaxy_links.

Conclusion

Here, we show that translational MSI data analysis in a fully transparent and reproducible manner is possible and we would like to encourage the community to join our efforts.

Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning

Acquiring comprehensive knowledge about the uptake of pollutants, impact on tissue integrity and the effects at the molecular level in organisms is of increasing interest due to the environmental exposure to numerous contaminants. The analysis of tissues can be performed by histological examination, which is still time-consuming and restricted to target-specific staining methods. The histological approaches can be complemented with chemical imaging analysis. Chemical imaging of tissue sections is typically performed using a single imaging approach. However, for toxicological testing of environmental pollutants, a multimodal approach combined with improved data acquisition and evaluation is desirable, since it may allow for more rapid tissue characterization and give further information on ecotoxicological effects at the tissue level. Therefore, using the soil model organism Eisenia fetida as a model, we developed a sequential workflow combining Fourier transform infrared spectroscopy (FTIR) and matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) for chemical analysis of the same tissue sections. Data analysis of the FTIR spectra via random decision forest (RDF) classification enabled the rapid identification of target tissues (e.g., digestive tissue), which are relevant from an ecotoxicological point of view. MALDI imaging analysis provided specific lipid species which are sensitive to metabolic changes and environmental stressors. Taken together, our approach provides a fast and reproducible workflow for label-free histochemical tissue analyses in E. fetida, which can be applied to other model organisms as well.

Proteomic Landscape of Prostate Cancer: The View Provided by Quantitative Proteomics, Integrative Analyses, and Protein Interactomes

Prostate cancer is the second most frequent cancer of men worldwide. While the genetic landscapes and heterogeneity of prostate cancer are relatively well-known already, methodological developments now allow for studying basic and dynamic proteomes on a large scale and in a quantitative fashion. This aids in revealing the functional output of cancer genomes. It has become evident that not all aberrations at the genetic and transcriptional level are translated to the proteome. In addition, the proteomic level contains heterogeneity, which increases as the cancer progresses from primary prostate cancer (PCa) to metastatic and castration-resistant prostate cancer (CRPC). While multiple aspects of prostate adenocarcinoma proteomes have been studied, less is known about proteomes of neuroendocrine prostate cancer (NEPC). In this review, we summarize recent developments in prostate cancer proteomics, concentrating on the proteomic landscapes of clinical prostate cancer, cell line and mouse model proteomes interrogating prostate cancer-relevant signaling and alterations, and key prostate cancer regulator interactomes, such as those of the androgen receptor (AR). Compared to genomic and transcriptomic analyses, the view provided by proteomics brings forward changes in prostate cancer metabolism, post-transcriptional RNA regulation, and post-translational protein regulatory pathways, requiring the full attention of studies in the future.

Autophagy protects murine preputial glands against premature aging, and controls their sebum phospholipid and pheromone profile

Preputial glands are large lipid and hormone secreting sebaceous organs of mice, and present a convenient model for the investigation of biological processes in sebocytes. Suppression of ATG7-dependent macroautophagy/autophagy in epithelial cells of murine skin causes enlargement of hair follicle-associated sebaceous glands and alters the lipid profile of sebum. We have now extended these studies to the preputial glands and find that autophagy significantly delays the onset of age-related ductal ectasia, influences lipid droplet morphology and contributes to the complete dissolution of the mature sebocytes during holocrine secretion. Single cell RNA sequencing showed that many genes involved in lipid metabolism and oxidative stress response were downregulated in immature and mature epithelial cells of ATG7-deficient glands. When analyzing the lipid composition of control and mutant glands, we found that levels of all phospholipid classes, except choline plasmalogen, were decreased in the mutant glands, with a concomitant accumulation of diacyl glycerides. Mass spectrometric imaging (MSI) demonstrated that phospholipid species, specifically the dominant phosphatidylcholine (PC 34:1), were decreased in immature and mature sebocytes. In addition, we found a strong reduction in the amounts of the pheromone, palmityl acetate. Thus, autophagy in the preputial gland is not only important for homeostasis of the gland as a whole and an orderly breakdown of cells during holocrine secretion, but also regulates phospholipid and fatty acid metabolism, as well as pheromone production.AbbreviationsATG7: autophagy related 7; BODIPY: boron dipyrromethene; DAG: diacyl glycerides; DBI: diazepam binding inhibitor; GFP: green fluorescent protein; KRT14: keratin 14; HPLC-MS: high performance liquid chromatography-mass spectrometry; LD: lipid droplet; MAP1LC3/LC3: microtubule-associated protein 1 light chain 3; MSI: mass spectrometric imaging; ORO: Oil Red O; PC: phosphatidylcholine; PE: phosphatidylethanolamine; PG: preputial gland; PLIN2: perilipin 2; PtdIns: phosphatidylinositol; PL: phospholipids; POPC: 1-palmitoyl-2-oleoyl-PC; PS: phosphatidylserine; qRT-PCR: quantitative reverse transcribed PCR; SG: sebaceous gland; scRNAseq: single-cell RNA sequencing; TAG: triacylglycerides; TLC: thin layer chromatography.

Bringing Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging to the Clinics

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is an emerging analytical technique that promises to change tissue-based diagnostics. This article provides a brief introduction to MALDI MSI as well as clinical diagnostic workflows and opportunities to apply this powerful approach. It describes various MALDI MSI applications, from more clinically mature applications such as cancer to emerging applications such as infectious diseases and drug distribution. In addition, it discusses the analytical considerations that need to be considered when bringing these approaches to different diagnostic problems and settings.

Proteomics-based identification of TMED9 is linked to vascular invasion and poor prognoses in patients with hepatocellular carcinoma

BACKGROUND

Due to the difficulties in early diagnosing and treating hepatocellular carcinoma (HCC), prognoses for patients remained poor in the past decade. In this study, we established a screening model to discover novel prognostic biomarkers in HCC patients.

METHODS

Candidate biomarkers were screened by liquid chromatography with tandem mass spectrometry (LC-MS/MS) analyses of five HCC normal (N)/tumor (T) paired tissues and preliminarily verified them through several in silico database analyses. Expression levels and functional roles of candidate biomarkers were respectively evaluated by immunohistochemical staining in N/T paired tissue (n = 120) and MTS, colony formation, and transwell migration/invasion assays in HCC cell lines. Associations of clinicopathological features and prognoses with candidate biomarkers in HCC patients were analyzed from GEO and TCGA datasets and our recruited cohort.

RESULTS

We found that the transmembrane P24 trafficking protein 9 (TMED9) protein was elevated in HCC tissues according to a global proteomic analysis. Higher messenger (m)RNA and protein levels of TMED9 were observed in HCC tissues compared to normal liver tissues or pre-neoplastic lesions. The TMED9 mRNA expression level was significantly associated with an advanced stage and a poor prognosis of overall survival (OS, p = 0.00084) in HCC patients. Moreover, the TMED9 protein expression level was positively correlated with vascular invasion (p = 0.026), OS (p = 0.044), and disease-free survival (p = 0.015) in our recruited Taiwanese cohort. In vitro, manipulation of TMED9 expression in HCC cells significantly affected cell migratory, invasive, proliferative, and colony-forming abilities.

CONCLUSIONS

Ours is the first work to identify an oncogenic role of TMED9 in HCC cells and may provide insights into the application of TMED9 as a novel predictor of clinical outcomes and a potential therapeutic target in patients with HCC.

Applications of mass spectrometry imaging in virus research

Mass spectrometry imaging (MSI) is a label-free molecular imaging technique allowing an untargeted detection of a broad range of biomolecules and xenobiotics. MSI enables imaging of the spatial distribution of proteins, peptides, lipids and metabolites from a wide range of samples. To date, this technique is commonly applied to tissue sections in cancer diagnostics and biomarker development, but also molecular histology in general. Advances in the methodology and bioinformatics improved the resolution of MS images below the single cell level and increased the flexibility of the workflow. However, MSI-based research in virology is just starting to gain momentum and its full potential has not been exploited yet. In this review, we discuss the main applications of MSI in virology. We review important aspects of matrix-assisted laser desorption/ionization (MALDI) MSI, the most widely used MSI technique in virology. In addition, we summarize relevant literature on MSI studies that aim to unravel virus-host interactions and virus pathogenesis, to elucidate antiviral drug kinetics and to improve current viral disease diagnostics. Collectively, these studies strongly improve our general understanding of virus-induced changes in the proteome, metabolome and metabolite distribution in host tissues of humans, animals and plants upon infection. Furthermore, latest MSI research provided important insights into the drug distribution and distribution kinetics, especially in antiretroviral research. Finally, MSI-based investigations of oncogenic viruses greatly increased our knowledge on tumor mass signatures and facilitated the identification of cancer biomarkers.

Universal Sample Preparation Unlocking Multimodal Molecular Tissue Imaging

A new tissue sample embedding and processing method is presented that provides downstream compatibility with numerous different histological, molecular biology, and analytical techniques. The methodology is based on the low temperature embedding of fresh frozen specimens into a hydrogel matrix composed of hydroxypropyl methylcellulose (HPMC) and polyvinylpyrrolidone (PVP) and sectioning using a cryomicrotome. The hydrogel was expected not to interfere with standard tissue characterization methods, histologically or analytically. We assessed the compatibility of this protocol with various mass spectrometric imaging methods including matrix-assisted laser desorption ionization (MALDI), desorption electrospray ionization (DESI) and secondary ion mass spectrometry (SIMS). We also demonstrated the suitability of the universal protocol for extraction based molecular biology techniques such as rt-PCR. The integration of multiple analytical modalities through this universal sample preparation protocol offers the ability to study tissues at a systems biology level and directly linking results to tissue morphology and cellular phenotype.

MIR205HG acts as a ceRNA to expedite cell proliferation and progression in lung squamous cell carcinoma via targeting miR-299-3p/MAP3K2 axis

INTRODUCTION

Long noncoding RNAs (lncRNAs) have been associated with many types of cancers, but their molecular mechanisms in lung squamous cell carcinoma (LUSC) have not been fully studied. Therefore, the current study investigated the regulation role of microRNA-205 host gene (MIR205HG) in LUSC and recognized the target genes managed by this lncRNA.

METHODS

MIR205HG expression was assessed by the quantitative real-time polymerase chain reaction (qRT-PCR) analysis. The effects of silenced MIR205HG on cell biological behaviors were detected by colony formation assay, transwell assay, flow cytometry analysis and western blot analysis. Luciferase reporter assay and RNA immunoprecipitation (RIP) assay were utilized to proof the binding relationship between miR-299-3p and MIR205HG/mitogen-activated protein kinase kinase kinase 2 (MAP 3 K2).

RESULTS

The expression levels of MIR205HG in LUSC tissues and cell lines were obviously up-regulated. Down-regulation of MIR205HG expression remarkably reduced cell proliferation, migration and epithelial-to-mesenchymal transition (EMT) progression, whereas promoted cell apoptosis. MIR205HG could bind with miR-299-3p and down-regulation of MIR205HG elevated miR-299-3p expression. MAP 3 K2 acted as the target gene of miR-299-3p and was up-regulated by MIR205HG overexpression. Overexpressing MAP 3 K2 could counteract the effects of down-regulating MIR205HG on LUSC progression to some degree.

CONCLUSION

MIR205HG acts as a competing endogenous RNA (ceRNA) to expedite cell proliferation and progression via targeting miR-299-3p in LUSC.

MiRNAs differentially expressed in skeletal muscle of animals with divergent estimated breeding values for beef tenderness

Background

MicroRNAs (miRNAs) are small noncoding RNAs of approximately 22 nucleotides, highly conserved among species, which modulate gene expression by cleaving messenger RNA target or inhibiting translation. MiRNAs are involved in the regulation of many processes including cell proliferation, differentiation, neurogenesis, angiogenesis, and apoptosis. Beef tenderness is an organoleptic characteristic of great influence in the acceptance of meat by consumers. Previous studies have shown that collagen level, marbling, apoptosis and proteolysis are among the many factors that affect beef tenderness. Considering that miRNAs can modulate gene expression, this study was designed to identify differentially expressed miRNAs that could be modulating biological processes involved with beef tenderness.

Results

Deep sequence analysis of miRNA libraries from longissimus thoracis muscle allowed the identification of 42 novel and 308 known miRNAs. Among the known miRNAs, seven were specifically expressed in skeletal muscle. Differential expression analysis between animals with high (H) and low (L) estimated breeding values for shear force (EBVSF) revealed bta-mir-182 and bta-mir-183 are up-regulated (q value < 0.05) in animals with L EBVSF, and bta-mir-338 is up-regulated in animals with H EBVSF. The number of bovine predicted targets for bta-mir-182, bta-mir-183 and bta-mir-338 were 811, 281 and 222, respectively, which correspond to 1204 unique target genes. Among these, four of them, MEF2C, MAP3K2, MTDH and TNRC6B were common targets of the three differentially expressed miRNAs. The functional analysis identified important pathways related to tenderness such as apoptosis and the calpain–calpastatin system.

Conclusion

The results obtained indicate the importance of miRNAs in the regulatory mechanisms that influence muscle proteolysis and meat tenderness and contribute to our better understanding of the role of miRNAs in biological processes associated with beef tenderness.

Electronic supplementary material

The online version of this article (10.1186/s12867-018-0118-3) contains supplementary material, which is available to authorized users.

Mass spectrometry imaging for clinical research - latest developments, applications, and current limitations

Mass spectrometry is being used in many clinical research areas ranging from toxicology to personalized medicine. Of all the mass spectrometry techniques, mass spectrometry imaging (MSI), in particular, has continuously grown towards clinical acceptance. Significant technological and methodological improvements have contributed to enhance the performance of MSI recently, pushing the limits of throughput, spatial resolution, and sensitivity. This has stimulated the spread of MSI usage across various biomedical research areas such as oncology, neurological disorders, cardiology, and rheumatology, just to name a few. After highlighting the latest major developments and applications touching all aspects of translational research (i.e. from early pre-clinical to clinical research), we will discuss the present challenges in translational research performed with MSI: data management and analysis, molecular coverage and identification capabilities, and finally, reproducibility across multiple research centers, which is the largest remaining obstacle in moving MSI towards clinical routine.

Mass spectrometry imaging: How will it affect clinical research in the future?

INTRODUCTION

Mass spectrometry imaging (MSI) is a label free, multiplex imaging technology able to simultaneously record the distributions of 100's to 1000's of species, and which may be configured to study metabolites, lipids, glycans, peptides, and proteins simply by changing the tissue preparation protocol. Areas covered: The capability of MSI to complement established histopathological practice through the identification of biomarkers for differential diagnosis, patient prognosis, and response to therapy; the capability of MSI to annotate tissues on the basis of each pixel's mass spectral signature; the development of reproducible MSI through multicenter studies. Expert commentary: We discuss how MSI can be combined with microsampling/microdissection technologies in order to investigate, with more depth of coverage, the molecular changes uncovered by MSI.

Approaching cellular resolution and reliable identification in mass spectrometry imaging of tryptic peptides

On-tissue digestion has become the preferred method to identify proteins in mass spectrometry (MS) imaging. In this study, we report advances in data acquisition and protein identification for MS imaging after on-tissue digestion. Tryptic peptides in a coronal mouse brain section were measured at 50 μm pixel size and revealed detailed histological structures, e.g., the ependyma (consisting of one to two cell layers), which was confirmed by H&E staining. This demonstrates that MS imaging of tryptic peptides at or close to cellular resolution is within reach. We also describe a detailed identification workflow which resulted in the identification of 99 proteins (with 435 corresponding peptides), based on comparison with LC-MS/MS data and in silico digest. These results were obtained with stringent parameters, including high mass accuracy in imaging mode (RSME < 3 ppm) and at least two unique peptides per protein showing consistent spatial distribution. We identified almost 50% of proteins with at least four corresponding peptides. As there is no agreed approach for identification of proteins after on-tissue digestion yet, we discuss our workflow in detail and make the corresponding mass spectral data available as “open data” via ProteomeXchange (identifier PXD003172). With this, we would like to contribute to a more effective discussion and the development of new approaches for tryptic peptide identification in MS imaging. From an experimental point of view, we demonstrate the improvement due to the combination of high spatial resolution and high mass resolution/mass accuracy on a measurement at 25 μm pixel size in mouse cerebellum tissue. A whole body section of a mouse pub imaged at 50 μm pixel size (40 GB, 230,000 spectra) demonstrates the stability of our protocol. For this data set, we developed a workflow that is based on conversion to the common data format imzML and sequential application of freely available software tools. In combination, the presented results for spatial resolution, protein identification, and data processing constitute significant improvements for the field of on-tissue digestion.

Graphical abstract

Discovery and characterization of an iminocoumarin scaffold as an inhibitor of MEKK2 (MAP3K2)

The kinase MEKK2 (MAP3K2) activates the MEK5/ERK5 cell signaling pathway and may play an important role in tumor growth and metastasis. Thus, MEKK2 may represent a novel kinase target for cancer. In order to identify inhibitors of MEKK2, we screened a library of compounds using a high throughput MEKK2 intrinsic ATPase enzyme assay. We identified two hits with validated structures and confirmed activity in the primary assay (IC₅₀ values = 322 nM and 7.7 μM) and two orthogonal MEKK2 biochemical assays. Compound 1, the more potent hit, was the subject of further investigation. Limited structure-activity relationship (SAR) studies were performed on this iminocoumarin hit which resulted in ≥20-fold more potent analogs (e.g. 8 and 16 nM IC₅₀). Two analogs had improved selectivity in a 50-member kinase profiling panel compared to the hit. These studies suggested that substitutions around the phenoxy ring of this scaffold can impart improved potency and selectivity for MEKK2. Analog Compound 1s (16 nM IC₅₀) was further verified by external testing to inhibit MEKK2 and MEKK3 with similar potencies. Compound 1s displayed activity in cell-based assays in which it inhibited ERK5 pathway activation in cells and inhibited cell migration in a scratch assay. Thus, we have identified a scaffold that has promising potential to be developed into a highly selective and potent inhibitor of MEKK2. Information from these SAR studies provides specific guidance for the future design of MEKK2 inhibitor probes.

MALDI MSI of MeLiM melanoma: Searching for differences in protein profiles

Background

Treatment of advanced cutaneous melanoma remains challenging, and new data on melanoma biology are required. The most widely accepted criteria for the prognostic evaluation of melanoma are histopathological and clinical parameters, and the identification of additional tumor markers is thus of paramount importance. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI), an important tool in cancer research, is useful for unraveling the molecular profile of melanoma.

Methodology/Principal findings

In this report, we used the melanoma-bearing Libechov minipig (MeLiM), a unique animal model that allows observation of the complete spontaneous regression of invasive cutaneous melanoma, to investigate i) the differences between melanoma and healthy skin protein profiles and ii) the proteins potentially involved in spontaneous regression. The MeLiM tissues were cryosected, histologically characterized, analyzed by MALDI MSI, and immunohistologically stained. Multivariate statistical analyses of the MALDI MSI data revealed ten relevant m/z ions, of which the expression levels varied significantly among the studied MeLiM tissues. These ion peaks were used to create mass ion images/maps and visualize the differences between tumor and healthy skin specimens, as well as among histologically characterized tissue regions.

Conclusions/Significance

Protein profiles comprising ten statistically significant mass ion peaks useful for differentiating cutaneous melanoma and healthy skin tissues were determined. Peaks at m/z 3044, 6011, 6140 and 10180 were overexpressed in melanoma compared with healthy skin tissue. More specifically, m/z 6140 was expressed at significantly (p < 0.05) higher levels in normally growing melanoma regions than in regions with early and late spontaneous regression. This study demonstrates the clinical utility of MALDI MSI for the analysis of tissue cryosections at a molecular level.

Prostate cancer diagnosis and characterization with mass spectrometry imaging

Background

Prostate cancer (PCa), the most common cancer and second leading cause of cancer death in American men, presents the clinical challenge of distinguishing between indolent and aggressive tumors for proper treatment. PCa presents significant alterations in metabolic pathways that can potentially be measured using techniques like mass spectrometry (MS) or mass spectrometry imaging (MSI) and used to characterize PCa aggressiveness. MS quantifies metabolomic, proteomic, and lipidomic profiles of biological systems that can be further visualized for their spatial distributions through MSI.

Methods

PubMed was queried for all publications relating to MS and MSI in human prostate cancer from April 2007 to April 2017. With the goal of reviewing the utility of MSI in diagnosis and prognostication of human PCa, MSI articles that reported investigations of PCa-specific metabolites or metabolites indicating PCa aggressiveness were selected for inclusion. Articles were included that covered MS and MSI principles, limitations, and applications in PCa.

Results

We identified nine key studies on MSI in intact human prostate tissue specimens that determined metabolites which could either differentiate between benign and malignant prostate tissue or indicate prostate cancer aggressiveness. These MSI-detected biomarkers show promise in reliably identifying PCa and determining disease aggressiveness.

Conclusions

MSI represents an innovative technique with the ability to interrogate cancer biomarkers in relation to tissue pathologies and investigate tumor aggressiveness. We propose MSI as a powerful adjuvant histopathology imaging tool for prostate tissue evaluations, where clinical translation of this ex vivo technique could make possible the use of MSI for personalized medicine in diagnosis and prognosis of prostate cancer. Moreover, the knowledge provided from this technique can majorly contribute to the understanding of molecular pathogenesis of PCa and other malignant diseases.

High-grade sarcoma diagnosis and prognosis: Biomarker discovery by mass spectrometry imaging

The combination of high heterogeneity, both intratumoral and intertumoral, with their rarity has made diagnosis, prognosis of high-grade sarcomas difficult. There is an urgent need for more objective molecular biomarkers, to differentiate between the many different subtypes, and to also provide new treatment targets. Mass spectrometry imaging (MSI) has amply demonstrated its ability to identify potential new markers for patient diagnosis, survival, metastasis and response to therapy in cancer research. In this study, we investigated the ability of MALDI-MSI of proteins to distinguish between high-grade osteosarcoma (OS), leiomyosarcoma (LMS), myxofibrosarcoma (MFS) and undifferentiated pleomorphic sarcoma (UPS) (Ntotal = 53). We also investigated if there are individual proteins or protein signatures that are statistically associated with patient survival. Twenty diagnostic protein signals were found characteristic for specific tumors (p ≤ 0.05), amongst them acyl-CoA-binding protein (m/z 11 162), macrophage migration inhibitory factor (m/z 12 350), thioredoxin (m/z 11 608) and galectin-1 (m/z 14 633) were assigned. Another nine protein signals were found to be associated with overall survival (p ≤ 0.05), including proteasome activator complex subunit 1 (m/z 9753), indicative for non-OS patients with poor survival; and two histone H4 variants (m/z 11 314 and 11 355), indicative of poor survival for LMS patients.

LRP6 is identified as a potential prognostic marker for oral squamous cell carcinoma via MALDI-IMS

Oral squamous cell carcinoma (OSCC) is a leading cause of cancer-related deaths worldwide, with 500 000 new cases each year. However, the mechanisms underlying OSCC development are relatively unknown. In this study, matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS)-based proteomic strategy was used to profile the differentially expressed peptides/proteins between OSCC tissues and their adjacent noncancerous tissues. Sixty-seven unique peptide peaks and five distinct proteins were identified with changed expression levels. Among them, LRP6 expression was found to be upregulated in OSCC tissues, and correlated with a cluster of clinicopathologic parameters, including smoking, drinking, tumor differentiation status, lymph node metastasis and survival time. Notably, knockdown of LRP6 inhibited the proliferation ability of OSCC cells. Furthermore, we demonstrated that the expression of LRP6 in OSCC cells is positively correlated with its downstream oncogene, FGF8. The present study suggests that LRP6 could be a potential biomarker for OSCC patients, and might further assist in the therapeutic decisions in OSCC treatment.

Label-free molecular imaging of the kidney

In this review, we will highlight technologies that enable scientists to study the molecular characteristics of tissues and/or cells without the need for antibodies or other labeling techniques. Specifically, we will focus on matrix-assisted laser desorption/ionization imaging mass spectrometry, infrared spectroscopy, and Raman spectroscopy.

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.

Biophysical technologies for understanding circulating tumor cell biology and metastasis

An understanding of cancer evolution in lung cancer with its associated resistance to therapy can only be achieved with repeated sampling and analysis of the cancer. Given the high risks and costs associated with repeat physical biopsy, alternative technologies must be applied. Several modalities exist for analysis and re-analysis of cancer biology. Among them are the CellSearch platform, the CTC chip, and the high-definition CTC platform. While the former is primarily able to provide prognosticating information in the form of CTC enumeration, the latter two have the advantage of serving as a platform to study tumor biology. Techniques for analysis of single cell genomics, as well as protein expression on a single cell basis provide scientists with the capacity to understand cancer cell populations as a collection of individual cells, rather than as an average of all cells. A multimodal combination of circulating tumor DNAs (ctDNAs), CTCs, proteomics, and CTC-derived xenografts (CDXs) to create computational models useful in diagnosis, prognostication, and predictiveness to treatment is likely the future of tailoring individualized cancer care.

MALDI imaging: beyond classic diagnosis

Mass spectrometry has been the focus of technology development and application for imaging for several decades. Imaging mass spectrometry using matrix-assisted laser desorption ionization is a new and effective tool for molecular studies of complex biological samples such as tissue sections. As histological features remain intact throughout the analysis of a section, distribution maps of multiple analytes can be correlated with histological and clinical features. Spatial molecular arrangements can be assessed without the need for target-specific reagents, allowing the discovery of diagnostic and prognostic markers of different cancer types and enabling the determination of effective therapies.

Mass spectrometry imaging shows major derangements in neurogranin and in purine metabolism in the triple-knockout 3×Tg Alzheimer mouse model

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) can simultaneously measure hundreds of biomolecules directly from tissue. Using different sample preparation strategies, proteins and metabolites have been profiled to study the molecular changes in a 3×Tg mouse model of Alzheimer's disease. In comparison with wild-type (WT) control mice MALDI-MSI revealed Alzheimer's disease-specific protein profiles, highlighting dramatic reductions of a protein with m/z 7560, which was assigned to neurogranin and validated by immunohistochemistry. The analysis also revealed substantial metabolite changes, especially in metabolites related to the purine metabolic pathway, with a shift towards an increase in hypoxanthine/xanthine/uric acid in the 3×Tg AD mice accompanied by a decrease in AMP and adenine. Interestingly these changes were also associated with a decrease in ascorbic acid, consistent with oxidative stress. Furthermore, the metabolite N-arachidonyl taurine was increased in the diseased mouse brain sections, being highly abundant in the hippocampus. Overall, we describe an interesting shift towards pro-inflammatory molecules (uric acid) in the purinergic pathway associated with a decrease in anti-oxidant level (ascorbic acid). Together, these observations fit well with the increased oxidative stress and neuroinflammation commonly observed in AD. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

MALDI imaging mass spectrometry reveals multiple clinically relevant masses in colorectal cancer using large-scale tissue microarrays

For identification of clinically relevant masses to predict status, grade, relapse and prognosis of colorectal cancer, we applied Matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (IMS) to a tissue micro array containing formalin-fixed and paraffin-embedded tissue samples from 349 patients. Analysis of our MALDI-IMS data revealed 27 different m/z signals associated with epithelial structures. Comparison of these signals showed significant association with status, grade and Ki-67 labeling index. Fifteen out of 27 IMS signals revealed a significant association with survival. For seven signals (m/z 654, 776, 788, 904, 944, 975 and 1013) the absence and for eight signals (m/z 643, 678, 836, 886, 898, 1095, 1459 and 1477) the presence were associated with decreased life expectancy, including five masses (m/z 788, 836, 904, 944 and 1013) that provided prognostic information independently from the established prognosticators pT and pN. Combination of these five masses resulted in a three-step classifier that provided prognostic information superior to univariate analysis. In addition, a total of 19 masses were associated with tumor stage, grade, metastasis and cell proliferation. Our data demonstrate the suitability of combining IMS and large-scale tissue micro arrays to simultaneously identify and validate clinically useful molecular marker. Copyright © 2017 John Wiley & Sons, Ltd.

Differentiating tumor heterogeneity in formalin-fixed paraffin-embedded (FFPE) prostate adenocarcinoma tissues using principal component analysis of matrix-assisted laser desorption/ionization imaging mass spectral data

RATIONALE

Many patients with adenocarcinoma of the prostate present with advanced and metastatic cancer at the time of diagnosis. There is an urgent need to detect biomarkers that will improve the diagnosis and prognosis of this disease. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) is playing a key role in cancer research and it can be useful to unravel the molecular profile of prostate cancer biopsies.

METHODS

MALDI imaging data sets are highly complex and their interpretation requires the use of multivariate statistical methods. In this study, MALDI-IMS technology, sequential principal component analysis (PCA) and two-dimensional (2-D) peak distribution tests were employed to investigate tumor heterogeneity in formalin-fixed paraffin-embedded (FFPE) prostate cancer biopsies.

RESULTS

Multivariate statistics revealed a number of mass ion peaks obtained from different tumor regions that were distinguishable from the adjacent normal regions within a given specimen. These ion peaks have been used to generate ion images and visualize the difference between tumor and normal regions. Mass peaks at m/z 3370, 3441, 3447 and 3707 exhibited stronger ion signals in the tumor regions.

CONCLUSIONS

This study reports statistically significant mass ion peaks unique to tumor regions in adenocarcinoma of the prostate and adds to the clinical utility of MALDI-IMS for analysis of FFPE tissue at a molecular level that supersedes all other standard histopathologic techniques for diagnostic purposes used in the current clinical practice. Copyright © 2016 John Wiley & Sons, Ltd.

Clinical applications of MALDI imaging technologies in cancer and neurodegenerative diseases

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) imaging mass spectrometry (IMS) enables localization of analytes of interest along with histology. More specifically, MALDI-IMS identifies the distributions of proteins, peptides, small molecules, lipids, and drugs and their metabolites in tissues, with high spatial resolution. This unique capacity to directly analyze tissue samples without the need for lengthy sample preparation reduces technical variability and renders MALDI-IMS ideal for the identification of potential diagnostic and prognostic biomarkers and disease gradation. MALDI-IMS has evolved rapidly over the last decade and has been successfully used in both medical and basic research by scientists worldwide. In this review, we explore the clinical applications of MALDI-IMS, focusing on the major cancer types and neurodegenerative diseases. In particular, we re-emphasize the diagnostic potential of IMS and the challenges that must be confronted when conducting MALDI-IMS in clinical settings. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Applications of Mass Spectrometry Imaging to Cancer

Pathologists play an essential role in the diagnosis and prognosis of benign and cancerous tumors. Clinicians provide tissue samples, for example, from a biopsy, which are then processed and thin sections are placed onto glass slides, followed by staining of the tissue with visible dyes. Upon processing and microscopic examination, a pathology report is provided, which relies on the pathologist's interpretation of the phenotypical presentation of the tissue. Targeted analysis of single proteins provide further insight and together with clinical data these results influence clinical decision making. Recent developments in mass spectrometry facilitate the collection of molecular information about such tissue specimens. These relatively new techniques generate label-free mass spectra across tissue sections providing nonbiased, nontargeted molecular information. At each pixel with spatial coordinates (x/y) a mass spectrum is acquired. The acquired mass spectrums can be visualized as intensity maps displaying the distribution of single m/z values of interest. Based on the sample preparation, proteins, peptides, lipids, small molecules, or glycans can be analyzed. The generated intensity maps/images allow new insights into tumor tissues. The technique has the ability to detect and characterize tumor cells and their environment in a spatial context and combined with histological staining, can be used to aid pathologists and clinicians in the diagnosis and management of cancer. Moreover, such data may help classify patients to aid therapy decisions and predict outcomes. The novel complementary mass spectrometry-based methods described in this chapter will contribute to the transformation of pathology services around the world.

Pathology-Driven Comprehensive Proteomic Profiling of the Prostate Cancer Tumor Microenvironment

Prostate cancer is the second most common cancer in men worldwide. Gleason grading is an important predictor of prostate cancer outcomes and is influential in determining patient treatment options. Clinical decisions based on a Gleason score of 7 are difficult as the prognosis for individuals diagnosed with Gleason 4+3 cancer is much worse than for those diagnosed with Gleason 3+4 cancer. Laser capture microdissection (LCM) is a highly precise method to isolate specific cell populations or discrete microregions from tissues. This report undertook a detailed molecular characterization of the tumor microenvironment in prostate cancer to define the proteome in the epithelial and stromal regions from tumor foci of Gleason grades 3 and 4. Tissue regions of interest were isolated from several Gleason 3+3 and Gleason 4+4 tumors using telepathology to leverage specialized pathology expertise to support LCM. Over 2,000 proteins were identified following liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of all regions of interest. Statistical analysis revealed significant differences in protein expression (>100 proteins) between Gleason 3 and Gleason 4 regions-in both stromal and epithelial compartments. A subset of these proteins has had prior strong association with prostate cancer, thereby providing evidence for the authenticity of the approach. Finally, validation of these proteins by immunohistochemistry has been obtained using an independent cohort of prostate cancer tumor specimens.Implications: This unbiased strategy provides a strong foundation for the development of biomarker protein panels with significant diagnostic and prognostic potential. Mol Cancer Res; 15(3); 281-93. ©2017 AACR.

Polarity switching mass spectrometry imaging of healthy and cancerous hen ovarian tissue sections by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI)

Mass spectrometry imaging (MSI) is a rapidly evolving field for monitoring the spatial distribution and abundance of analytes in biological tissue sections. It allows for direct and simultaneous analysis of hundreds of different compounds in a label-free manner. In order to obtain a comprehensive metabolite and lipid data, a polarity switching MSI method using infrared matrix assisted laser desorption electrospray ionization (IR-MALDESI) was developed and optimized where the electrospray polarity was alternated from one voxel to the next. Healthy and cancerous ovarian hen tissue sections were analyzed using this method. Distribution and relative abundance of different metabolites and lipids within each tissue section were discerned, and differences between the two were revealed. Additionally, the utility of using mass spectrometry concepts such as spectral accuracy and sulfur counting for confident identification of analytes in an untargeted method are discussed.

Mass Spectrometry Imaging for the Investigation of Intratumor Heterogeneity

One of the big clinical challenges in the treatment of cancer is the different behavior of cancer patients under guideline therapy. An important determinant for this phenomenon has been identified as inter- and intratumor heterogeneity. While intertumor heterogeneity refers to the differences in cancer characteristics between patients, intratumor heterogeneity refers to the clonal and nongenetic molecular diversity within a patient. The deciphering of intratumor heterogeneity is recognized as key to the development of novel therapeutics or treatment regimens. The investigation of intratumor heterogeneity is challenging since it requires an untargeted molecular analysis technique that accounts for the spatial and temporal dynamics of the tumor. So far, next-generation sequencing has contributed most to the understanding of clonal evolution within a cancer patient. However, it falls short in accounting for the spatial dimension. Mass spectrometry imaging (MSI) is a powerful tool for the untargeted but spatially resolved molecular analysis of biological tissues such as solid tumors. As it provides multidimensional datasets by the parallel acquisition of hundreds of mass channels, multivariate data analysis methods can be applied for the automated annotation of tissues. Moreover, it integrates the histology of the sample, which enables studying the molecular information in a histopathological context. This chapter will illustrate how MSI in combination with statistical methods and histology has been used for the description and discovery of intratumor heterogeneity in different cancers. This will give evidence that MSI constitutes a unique tool for the investigation of intratumor heterogeneity, and could hence become a key technology in cancer research.

Rapid Mass Spectrometry Imaging to Assess the Biochemical Profile of Pituitary Tissue for Potential Intraoperative Usage

Pituitary adenomas are relatively common intracranial neoplasms that are frequently treated with surgical resection. Rapid visualization of pituitary tissue remains a challenge as current techniques either produce little to no information on hormone-secreting function or are too slow to practically aid in intraoperative or even perioperative decision-making. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) represents a powerful method by which molecular maps of tissue samples can be created, yielding a two-dimensional representation of the expression patterns of small molecules and proteins from biologic samples. In this chapter, we review the use of MALDI MSI, its application to the characterization of the pituitary gland, and its potential applications for guiding the management of pituitary adenomas.

Metabolomic profiling of prostate cancer by matrix assisted laser desorption/ionization-Fourier transform ion cyclotron resonance mass spectrometry imaging using Matrix Coating Assisted by an Electric Field (MCAEF)

In this work, we combined the use of two MALDI matrices (quercetin and 9-aminoacridine), a recently developed new matrix coating technique - matrix coating assisted by an electric field (MCAEF), and matrix-assisted laser desorption/ionization - Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FTICRMS) to detect and image endogenous compounds in the cancerous and non-cancerous regions of three human prostate cancer (stage II) tissue specimens. After three rounds of imaging data acquisitions (i.e., quercetin for positive and negative ion detection and 9-aminoacridine for negative ion detection), and metabolite identification, a total of 1091 metabolites including 1032 lipids and 59 other metabolites were routinely detected and successfully localized. Of these compounds, 250 and 217 were only detected in either the cancerous or the non-cancerous regions respectively, although we cannot rule out the presence of these metabolites at concentrations below the detection limit. In addition, 152 of the other 624 metabolites showed differential distributions (p<0.05, t-test) between the two regions of the tissues. Further studies on a larger number of clinical specimens will need to be carried out to confirm this large number of apparently cancer-related metabolites. The successful determination of the spatial locations and abundances of these endogenous biomolecules indicated significant metabolism abnormalities - e.g., increased energy charge and under-expression of neutral acyl glycerides, in the prostate cancer samples. To our knowledge, this work has resulted in MALDI-MS imaging of the largest group of metabolites in prostate cancer thus far and demonstrated the importance of using complementary matrices for comprehensive metabolomic imaging by MALDI-MS. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

A new classification method for MALDI imaging mass spectrometry data acquired on formalin-fixed paraffin-embedded tissue samples

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) shows a high potential for applications in histopathological diagnosis, and in particular for supporting tumor typing and subtyping. The development of such applications requires the extraction of spectral fingerprints that are relevant for the given tissue and the identification of biomarkers associated with these spectral patterns. We propose a novel data analysis method based on the extraction of characteristic spectral patterns (CSPs) that allow automated generation of classification models for spectral data. Formalin-fixed paraffin embedded (FFPE) tissue samples from N=445 patients assembled on 12 tissue microarrays were analyzed. The method was applied to discriminate primary lung and pancreatic cancer, as well as adenocarcinoma and squamous cell carcinoma of the lung. A classification accuracy of 100% and 82.8%, resp., could be achieved on core level, assessed by cross-validation. The method outperformed the more conventional classification method based on the extraction of individual m/z values in the first application, while achieving a comparable accuracy in the second. LC-MS/MS peptide identification demonstrated that the spectral features present in selected CSPs correspond to peptides relevant for the respective classification. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

MALDI imaging mass spectrometry - From bench to bedside

Today, pathologists face many challenges in defining the precise morphomolecular diagnosis and in guiding clinicians to the optimal patients' treatment. To achieve this goal, increasingly, classical histomorphological methods have to be supplemented by high throughput molecular assays. Since MALDI imaging mass spectrometry (IMS) enables the assessment of spatial molecular arrangements in tissue sections, it goes far beyond microscopy in providing hundreds of different molecular images from a single scan without the need of target-specific reagents. Thus, this technology has the potential to uncover new markers for diagnostic purposes or markers that correlate with disease severity as well as prognosis and therapeutic response. Additionally, in the future MALDI IMS based classifiers measured with this technology in real time in the diagnostic setting might be applicable in the routine diagnostic setting. In this review, recently published studies that show the usefulness, advantages, and applicability of MALDI IMS in different fields of pathology (diagnosis, prognosis and treatment response) are highlighted. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

MicroRNA-186 suppresses cell proliferation and metastasis through targeting MAP3K2 in non-small cell lung cancer

MicroRNAs are a class of small endogenous non-coding RNAs that play crucial roles in the initiation and progression of human cancers. miR-186 was found decreased in various human malignancies and function as a tumor suppressor. However, the regulating mechanism of miR-186 in growth and metastasis of human non-small cell lung cancer (NSCLC) is still poorly understood. We investigated the role of miR-186 in the growth and metastasis of human NSCLC. In the present study, we found that miR-186 was significantly decreased in lung cancer tissues and cells. Furthermore, overexpression of miR-186 suppressed lung cancer cell proliferation, migration and invasion, and induced cell apoptosis. Moreover, we found that confirmed mitogen-activated protein kinase kinase kinase 2 (MAP3K2) protein was increased in lung cancer tissues and confirmed that MAP3K2 is a target gene of miR-186. In addition, knockdown of MAP3K2 by RNA interference inhibited lung cancer cell proliferation, migration and invasion, and promoted cell apoptosis in vitro. Furthermore, we observed tthat the overexpression of MAP3K2 partially reversed the inhibitory effect of miR-186 on the proliferation and metastasis of A549 and HCC827 cell lines. Taken together, our data indicated that miR-186 regulates lung cancer growth and metastasis through suppressing MAP3K2 expression, at least partly. Therefore, miR-186-MAP3K2 may represent a new and useful potential clinical treatment and diagnosis target for NSCLC.

Visualization of sphingolipids and phospholipids in the fundic gland mucosa of human stomach using imaging mass spectrometry

AIM: To analyze the lipid distribution in gastric mucosae.

METHODS: Imaging mass spectrometry (MS) is a useful tool to survey the distribution of biomolecules in surgical specimens. Here we used the imaging MS apparatus named iMScope to identify the dominant molecules present in the human gastric mucosa near the fundic glands. Five gastric specimens were subjected to iMScope analysis. These specimens were also analyzed by immunohistochemistry using MUC5AC, H(+)-K(+)-ATPaseβ Claudin18 antibodies.

RESULTS: Three major molecules with m/z 725.5, 780.5, and 782.5 detected in the gastric mucosa were identified as sphingomyelin (SM) (d18:1/16:0), phosphatidylcholine (PC) (16:0/18:2), and PC (16:0/18:1), respectively, through MS/MS analyses. Using immunohistological staining, SM (d18:1/16:0) signals were mainly co-localized with the foveolar epithelium marker MUC5AC. In contrast, PC (16:0/18:2) signals were observed in the region testing positive for the fundic gland marker H(+)-K(+)-ATPaseβ. PC (16:0/18:1) signals were uniformly distributed throughout the mucosa.

CONCLUSION: Our basic data will contribute to the studies of lipid species in physical and pathological conditions of the human stomach.

Potential of MALDI imaging for the toxicological evaluation of environmental pollutants

Risk assessment related to the exposure of humans to chemicals released into the environment is a major concern of our modern societies. In this context, toxicology plays a crucial role to characterize the effects of this exposure on health and identify the targets of these molecules. MALDI imaging mass spectrometry (IMS) is an enabling technology for biodistribution studies of chemicals. Although the majority of published studies are presented in a pharmacological context, the concepts discussed in this review can be applied to the toxicological evaluation of chemicals released into the environment. The major asset of IMS is the simultaneous localization and identification of a parent molecule and its metabolites without labeling and without any prior knowledge. Quantification methods developed in IMS are presented with application to an environmental pollutant. IMS is effective in the localization of chemicals and endogenous species. This opens unique perspectives for the discovery of molecular alterations in metabolites and protein biomarkers that could help for a better understanding of toxicity mechanisms. Distribution studies of agrochemicals in plants by IMS can contribute to a better understanding of their mode of action and to a more effective use of these chemicals, avoiding the current concern of environmental damage.

The use of matrix coating assisted by an electric field (MCAEF) to enhance mass spectrometric imaging of human prostate cancer biomarkers

In this work, we combined a newly developed matrix coating technique - matrix coating assisted by an electric field (MCAEF) and matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) to enhance the imaging of peptides and proteins in tissue specimens of human prostate cancer. MCAEF increased the signal-to-noise ratios of the detected proteins by a factor of 2 to 5, and 232 signals were detected within the m/z 3500-37500 mass range on a time-of-flight mass spectrometer and with the sinapinic acid MALDI matrix. Among these species, three proteins (S100-A9, S100-A10, and S100-A12) were only observed in the cancerous cell region and 14 proteins, including a fragment of mitogen-activated protein kinase/extracellular signal-regulated kinase kinase kinase 2, a fragment of cAMP-regulated phosphoprotein 19, 3 apolipoproteins (C-I, A-I, and A-II), 2 S100 proteins (A6 and A8), β-microseminoprotein, tumor protein D52, α-1-acid glycoprotein 1, heat shock protein β-1, prostate-specific antigen, and 2 unidentified large peptides at m/z 5002.2 and 6704.2, showed significantly differential distributions at the p < 0.05 (t-test) level between the cancerous and the noncancerous regions of the tissue. Among these 17 species, the distributions of apolipoprotein C-I, S100-A6, and S100-A8 were verified by immunohistological staining. In summary, this study resulted in the imaging of the largest group of proteins in prostate cancer tissues by MALDI-MS reported thus far, and is the first to show a correlation between S100 proteins and prostate cancer in a MS imaging study. The successful imaging of the three proteins only found in the cancerous tissues, as well as those showing differential expressions demonstrated the potential of MCAEF-MALDI/MS for the in situ detection of potential cancer biomarkers. Copyright © 2015 John Wiley & Sons, Ltd.

Deconvolving molecular signatures of interactions between microbial colonies

Motivation: The interactions between microbial colonies through chemical signaling are not well understood. A microbial colony can use different molecules to inhibit or accelerate the growth of other colonies. A better understanding of the molecules involved in these interactions could lead to advancements in health and medicine. Imaging mass spectrometry (IMS) applied to co-cultured microbial communities aims to capture the spatial characteristics of the colonies’ molecular fingerprints. These data are high-dimensional and require computational analysis methods to interpret.

Results: Here, we present a dictionary learning method that deconvolves spectra of different molecules from IMS data. We call this method MOLecular Dictionary Learning (MOLDL). Unlike standard dictionary learning methods which assume Gaussian-distributed data, our method uses the Poisson distribution to capture the count nature of the mass spectrometry data. Also, our method incorporates universally applicable information on common ion types of molecules in MALDI mass spectrometry. This greatly reduces model parameterization and increases deconvolution accuracy by eliminating spurious solutions. Moreover, our method leverages the spatial nature of IMS data by assuming that nearby locations share similar abundances, thus avoiding overfitting to noise. Tests on simulated datasets show that this method has good performance in recovering molecule dictionaries. We also tested our method on real data measured on a microbial community composed of two species. We confirmed through follow-up validation experiments that our method recovered true and complete signatures of molecules. These results indicate that our method can discover molecules in IMS data reliably, and hence can help advance the study of interaction of microbial colonies.

Availability and implementation: The code used in this paper is available at: https://github.com/frizfealer/IMS_project.

Contact:vjojic@cs.unc.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Decreased expression of lysophosphatidylcholine (16:0/OH) in high resolution imaging mass spectrometry independently predicts biochemical recurrence after surgical treatment for prostate cancer

BACKGROUND

Human prostate cancers are highly heterogeneous, indicating a need for various novel biomarkers to predict their prognosis. Lipid metabolism affects numerous cellular processes, including cell growth, proliferation, differentiation, and motility. Direct profiling of lipids in tissue using high-resolution matrix-assisted laser desorption/ionization imaging mass spectrometry (HR-MALDI-IMS) may provide molecular details that supplement tissue morphology.

METHODS

Prostate tissue samples were obtained from 31 patients, with localized prostate cancer who underwent radical prostatectomy. The samples were assessed by HR-MALDI-IMS in positive mode, with the molecules identified by tandem mass spectrometry (MS/MS). The effect of identified molecules on prostate specific antigen recurrence free survival after radical prostatectomy was determined by Cox regression analysis and by the Kaplan-Meier method.

RESULTS

Thirteen molecules were found to be highly expressed in prostate tissue, with five being significantly lower in cancer tissue than in benign epithelium. MS/MS showed that these molecules were [lysophosphatidylcholine (LPC)(16:0/OH)+H](+), [LPC(16:0/OH)+Na](+), [LPC(16:0/OH)+K](+), [LPC(16:0/OH)+matrix+H](+), and [sphingomyelin (SM)(d18:1/16:0)+H](+). Reduced expression of LPC(16:0/OH) in cancer tissue was an independent predictor of biochemical recurrence after radical prostatectomy.

CONCLUSIONS

HR-MALDI-IMS showed that the expression of LPC(16:0/OH) and SM(d18:1/16:0) was lower in prostate cancer than in benign prostate epithelium. These differences in expression of phospholipids may predict prostate cancer aggressiveness, and provide new insights into lipid metabolism in prostate cancer.

Identification of ponatinib and other known kinase inhibitors with potent MEKK2 inhibitory activity

The kinase MEKK2 (MAP3K2) may play an important role in tumor growth and metastasis for several cancer types. Thus, targeting MEKK2 may represent a novel strategy for developing more effective therapies for cancer. In order to identify small molecules with MEKK2 inhibitory activity, we screened a collection of known kinase inhibitors using a high throughput MEKK2 intrinsic ATPase enzyme assay and confirmed activity of the most potent hits with this primary assay. We also confirmed activities of these known kinase inhibitors with an MEKK2 transphosphorylation slot blot assay using MKK6 as a substrate. We observed a good correlation in potencies between the two orthogonal MEKK2 kinase activity assay formats for this set of inhibitors. We report that ponatinib, AT9283, AZD7762, JNJ-7706621, PP121 and hesperadin had potent MEKK2 enzyme inhibitory activities ranging from 4.7 to 60 nM IC50. Ponatinib is an FDA-approved drug that potently inhibited MEKK2 enzyme activity with IC50 values of 10-16 nM. AT9283 is currently in clinical trials and produced MEKK2 IC50 values of 4.7-18 nM. This set of known kinase inhibitors represents some of the most potent in vitro MEKK2 inhibitors reported to date and may be useful as research tools. Although these compounds are not selective for MEKK2, the structures of these compounds give insight into pharmacophores that potently inhibit MEKK2 and could be used as initial leads to design highly selective inhibitors of MEKK2.

Altered glycosylation in prostate cancer

Prostate cancer is annually the most common newly diagnosed cancer in men. The prostate functions as a major secretory gland for the production of glycoproteins critical to sperm activation and reproduction. Prostate-specific antigen (PSA), produced by the prostate, is one of the most commonly assayed glycoproteins in blood, serving as a biomarker for early detection and progression of prostate cancer. The single site of N-glycosylation on PSA has been the target of multiple glycan characterization studies. In this review, the extensive number of studies that have characterized the changes in O-linked and N-linked glycosylations associated with prostate cancer development and progression will be summarized. This includes analysis of the glycosylation of PSA, and other prostate glycoproteins, in tissues, clinical biofluids, and cell line models. Other studies are summarized in the context of understanding the complexities of these glycan changes in order to address the many confounding questions associated with prostate cancer, as well as efforts to improve prostate cancer biomarker assays using targeted glycomic-based strategies.