MALDI-imaging reveals thymosin beta-4 as an independent prognostic marker for colorectal cancer

Use of tryptic peptide MALDI mass spectrometry imaging to identify the spatial proteomic landscape of colorectal cancer liver metastases

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide. CRC liver metastases (CRLM) are often resistant to conventional treatments, with high rates of recurrence. Therefore, it is crucial to identify biomarkers for CRLM patients that predict cancer progression. This study utilised matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to spatially map the CRLM tumour proteome. CRLM tissue microarrays (TMAs) of 84 patients were analysed using tryptic peptide MALDI-MSI to spatially monitor peptide abundances across CRLM tissues. Abundance of peptides was compared between tumour vs stroma, male vs female and across three groups of patients based on overall survival (0-3 years, 4-6 years, and 7+ years). Peptides were then characterised and matched using LC-MS/MS. A total of 471 potential peptides were identified by MALDI-MSI. Our results show that two unidentified m/z values (1589.876 and 1092.727) had significantly higher intensities in tumours compared to stroma. Ten m/z values were identified to have correlation with biological sex. Survival analysis identified three peptides (Histone H4, Haemoglobin subunit alpha, and Inosine-5'-monophosphate dehydrogenase 2) and two unidentified m/z values (1305.840 and 1661.060) that were significantly higher in patients with shorter survival (0-3 years relative to 4-6 years and 7+ years). This is the first study using MALDI-MSI, combined with LC-MS/MS, on a large cohort of CRLM patients to identify the spatial proteome in this malignancy. Further, we identify several protein candidates that may be suitable for drug targeting or for future prognostic biomarker development.

Prospective on Imaging Mass Spectrometry in Clinical Diagnostics

Imaging mass spectrometry (IMS) is a molecular technology utilized for spatially driven research, providing molecular maps from tissue sections. This article reviews matrix-assisted laser desorption ionization (MALDI) IMS and its progress as a primary tool in the clinical laboratory. MALDI mass spectrometry has been used to classify bacteria and perform other bulk analyses for plate-based assays for many years. However, the clinical application of spatial data within a tissue biopsy for diagnoses and prognoses is still an emerging opportunity in molecular diagnostics. This work considers spatially driven mass spectrometry approaches for clinical diagnostics and addresses aspects of new imaging-based assays that include analyte selection, quality control/assurance metrics, data reproducibility, data classification, and data scoring. It is necessary to implement these tasks for the rigorous translation of IMS to the clinical laboratory; however, this requires detailed standardized protocols for introducing IMS into the clinical laboratory to deliver reliable and reproducible results that inform and guide patient care.

Proteomic characterisation of prostate cancer intercellular communication reveals cell type-selective signalling and TMSB4X-dependent fibroblast reprogramming

BACKGROUND

In prostate cancer, the tumour microenvironment (TME) represents an important regulator of disease progression and response to treatment. In the TME, cancer-associated fibroblasts (CAFs) play a key role in tumour progression, however the mechanisms underpinning fibroblast-cancer cell interactions are incompletely resolved. Here, we address this by applying cell type-specific labelling with amino acid precursors (CTAP) and mass spectrometry (MS)-based (phospho)proteomics to prostate cancer for the first time.

METHODS

Reciprocal interactions between PC3 prostate cancer cells co-cultured with WPMY-1 prostatic fibroblasts were characterised using CTAP-MS. Signalling network changes were determined using Metascape and Enrichr and visualised using Cytoscape. Thymosin β4 (TMSB4X) overexpression was achieved via retroviral transduction and assayed by ELISA. Cell motility was determined using Transwell and random cell migration assays and expression of CAF markers by indirect immunofluorescence.

RESULTS

WPMY-1 cells co-cultured with PC3s demonstrated a CAF-like phenotype, characterised by enhanced PDGFRB expression and alterations in signalling pathways regulating epithelial-mesenchymal transition, cytoskeletal organisation and cell polarisation. In contrast, co-cultured PC3 cells exhibited more modest network changes, with alterations in mTORC1 signalling and regulation of the actin cytoskeleton. The expression of the actin binding protein TMSB4X was significantly decreased in co-cultured WPMY-1 fibroblasts, and overexpression of TMSB4X in fibroblasts decreased migration of co-cultured PC3 cells, reduced fibroblast motility, and protected the fibroblasts from being educated to a CAF-like phenotype by prostate cancer cells.

CONCLUSIONS

This study highlights the potential of CTAP-MS to characterise intercellular communication within the prostate TME and identify regulators of cellular crosstalk such as TMSB4X.

Proteomic and functional characterization of intra-tumor heterogeneity in human endometrial cancer

Endometrial cancer is one of the most frequently diagnosed gynecological cancers worldwide, and its prevalence has increased by more than 50% over the last two decades. Despite the understanding of the major signaling pathways driving the growth and metastasis of endometrial cancer, clinical trials targeting these signals have reported poor outcomes. The heterogeneous nature of endometrial cancer is suspected to be one of the key reasons for the failure of targeted therapies. In this study, we perform a sequential window acquisition of all theoretical fragment ion spectra (SWATH)-based comparative proteomic analysis of 63 tumor biopsies collected from 20 patients and define differences in protein signature in multiple regions of the same tumor. We develop organoids from multiple biopsies collected from the same tumor and show that organoids capture heterogeneity in endometrial cancer growth. Overall, using quantitative proteomics and patient-derived organoids, we define the heterogeneous nature of endometrial cancer within a patient’s tumor.

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Proteomic analysis of endometrial cancer intra-tumor heterogeneity

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Identification of potential biomarkers of tumor volume and invasion

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Protein signatures correlate with pre-and postmenopausal cancers

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Patient-derived organoids capture endometrial cancer heterogeneity

A Transcriptomic Analysis of Head and Neck Squamous Cell Carcinomas for Prognostic Indications

Survival analysis of the Cancer Genome Atlas (TCGA) dataset is a well-known method for discovering gene expression-based prognostic biomarkers of head and neck squamous cell carcinoma (HNSCC). A cutoff point is usually used in survival analysis for patient dichotomization when using continuous gene expression values. There is some optimization software for cutoff determination. However, the software's predetermined cutoffs are usually set at the medians or quantiles of gene expression values. There are also few clinicopathological features available in pre-processed datasets. We applied an in-house workflow, including data retrieving and pre-processing, feature selection, sliding-window cutoff selection, Kaplan-Meier survival analysis, and Cox proportional hazard modeling for biomarker discovery. In our approach for the TCGA HNSCC cohort, we scanned human protein-coding genes to find optimal cutoff values. After adjustments with confounders, clinical tumor stage and surgical margin involvement were found to be independent risk factors for prognosis. According to the results tables that show hazard ratios with Bonferroni-adjusted p values under the optimal cutoff, three biomarker candidates, CAMK2N1, CALML5, and FCGBP, are significantly associated with overall survival. We validated this discovery by using the another independent HNSCC dataset (GSE65858). Thus, we suggest that transcriptomic analysis could help with biomarker discovery. Moreover, the robustness of the biomarkers we identified should be ensured through several additional tests with independent datasets.

Status quo and future prospects of artificial neural network from the perspective of gastroenterologists

Artificial neural networks (ANNs) are one of the primary types of artificial intelligence and have been rapidly developed and used in many fields. In recent years, there has been a sharp increase in research concerning ANNs in gastrointestinal (GI) diseases. This state-of-the-art technique exhibits excellent performance in diagnosis, prognostic prediction, and treatment. Competitions between ANNs and GI experts suggest that efficiency and accuracy might be compatible in virtue of technique advancements. However, the shortcomings of ANNs are not negligible and may induce alterations in many aspects of medical practice. In this review, we introduce basic knowledge about ANNs and summarize the current achievements of ANNs in GI diseases from the perspective of gastroenterologists. Existing limitations and future directions are also proposed to optimize ANN’s clinical potential. In consideration of barriers to interdisciplinary knowledge, sophisticated concepts are discussed using plain words and metaphors to make this review more easily understood by medical practitioners and the general public.

Adamantinomatous craniopharyngioma: advances in proteomic research

BACKGROUND

Many efforts have been performed in the last decade to accomplish the genomic and proteomic characterization of pediatric adamantinomatous craniopharyngioma with the purpose to elucidate the molecular mechanisms underlying the onset and development of this pediatric brain tumor, its high recurrence rate, and, although classified as a histologically benign neoplasm, its aggressive behavior.

METHODS

The focus of this review is to perform the new comparison of the proteomic profiles of the solid component and the intracystic fluid of adamantinomatous craniopharyngioma based on our previous results, obtained by both the top-down and the bottom-up proteomic approaches, to disclose differences and similarities, and to discuss the results in the context of the most recent literature.

RESULTS AND CONCLUSIONS

Proteins and peptides identified in the cyst fluid and in the solid component of adamantinomatous craniopharyngioma (AC) include beyond markers of inflammation (i.e., alpha-defensins), proteins involved in cell migration and protein degradation (i.e., beta-thymosin and ubiquitin peptides), whose main role might be in tumor growth and infiltration of the surrounding neural structures. These last appeared different in the solid components compared with the cyst fluid, missing their terminal part in the solid tissue, a feature generally associated to malignancies, which might represent a distinct molecular site for an aggressive behavior of AC.

Mass Spectrometric (MS) Analysis of Proteins and Peptides

The human genome is sequenced and comprised of ~30,000 genes, making humans just a little bit more complicated than worms or flies. However, complexity of humans is given by proteins that these genes code for because one gene can produce many proteins mostly through alternative splicing and tissue-dependent expression of particular proteins. In addition, post-translational modifications (PTMs) in proteins greatly increase the number of gene products or protein isoforms. Furthermore, stable and transient interactions between proteins, protein isoforms/proteoforms and PTM-ed proteins (protein-protein interactions, PPI) add yet another level of complexity in humans and other organisms. In the past, all of these proteins were analyzed one at the time. Currently, they are analyzed by a less tedious method: mass spectrometry (MS) for two reasons: 1) because of the complexity of proteins, protein PTMs and PPIs and 2) because MS is the only method that can keep up with such a complex array of features. Here, we discuss the applications of mass spectrometry in protein analysis.

Thymosin β4 promotes autophagy and repair via HIF-1α stabilization in chronic granulomatous disease

This study demonstrates that thymosin β4 stabilizes HIF-1a to promote autophagy and up-regulate genes involved in tissue and mucosal barrier protection in chronic granulomatous disease.

Chronic granulomatous disease (CGD) is a genetic disorder of the NADPH oxidase characterized by increased susceptibility to infections and hyperinflammation associated with defective autophagy and increased inflammasome activation. Herein, we demonstrate that thymosin β4 (Tβ4), a g-actin sequestering peptide with multiple and diverse intracellular and extracellular activities affecting inflammation, wound healing, fibrosis, and tissue regeneration, promoted in human and murine cells noncanonical autophagy, a form of autophagy associated with phagocytosis and limited inflammation via the death-associated protein kinase 1. We further show that the hypoxia inducible factor-1 (HIF-1)α was underexpressed in CGD but normalized by Tβ4 to promote autophagy and up-regulate genes involved in mucosal barrier protection. Accordingly, inflammation and granuloma formation were impaired and survival increased in CGD mice with colitis or aspergillosis upon Tβ4 treatment or HIF-1α stabilization. Thus, the promotion of endogenous pathways of inflammation resolution through HIF-1α stabilization is druggable in CGD by Tβ4.

Spatial UBE2N protein expression indicates genomic instability in colorectal cancers

BACKGROUND

One major hallmark of colorectal cancers (CRC) is genomic instability with its contribution to tumor heterogeneity and therapy resistance. To facilitate the investigation of intra-sample phenotypes and the de novo identification of tumor sub-populations, imaging mass spectrometry (IMS) provides a powerful technique to elucidate the spatial distribution patterns of peptides and proteins in tissue sections.

METHODS

In the present study, we analyzed an in-house compiled tissue microarray (n = 60) comprising CRCs and control tissues by IMS. After obtaining protein profiles through direct analysis of tissue sections, two validation sets were used for immunohistochemical evaluation.

RESULTS

A total of 28 m/z values in the mass range 800-3500 Da distinguished euploid from aneuploid CRCs (p < 0.001, ROC AUC values < 0.385 or > 0.635). After liquid chromatograph-mass spectrometry identification, UBE2N could be successfully validated by immunohistochemistry in the initial sample cohort (p = 0.0274, ROC AUC = 0.7937) and in an independent sample set of 90 clinical specimens (p = 0.0070, ROC AUC = 0.6957).

CONCLUSIONS

The results showed that FFPE protein expression profiling of surgically resected CRC tissue extracts by MALDI-TOF MS has potential value for improved molecular classification. Particularly, the protein expression of UBE2N was validated in an independent clinical cohort to distinguish euploid from aneuploid CRCs.

Extracellular Matrix Imaging of Breast Tissue Pathologies by MALDI-Imaging Mass Spectrometry

PURPOSE

A new method accessing proteins from extracellular matrix by imaging mass spectrometry (ECM IMS) has been recently reported. ECM IMS is evaluated for use in exploring breast tissue pathologies.

EXPERIMENTAL DESIGN

A tissue microarray (TMA) is analyzed that has 176 cores of biopsies and lumpectomies spanning breast pathologies of inflammation, hyperplasia, fibroadenoma, invasive ductal carcinoma, and invasive lobular carcinoma and normal adjacent to tumor (NAT). NAT is compared to subtypes by area under the receiver operating curve (ROC) >0.7. A lumpectomy is also characterized for collagen organization by microscopy and stromal protein distribution by IMS. LC-based high-resolution accurate mass (HRAM) proteomics is used to identify proteins from the lumpectomy.

RESULTS

TMA analysis shows distinct spectral signatures reflecting a heterogeneous tissue microenvironment. Ninety-four peaks show an ROC > 0.7 compared to NAT; NAT has overall higher intensities. Lumpectomy analysis by IMS visualizes a complex central tumor region with distal tumor regions. A total of 39 stromal proteins are identified by HRAM LC-based proteomics. Accurate mass matches between image data and LC-based proteomics demonstrate a heterogeneous collagen type environment in the central tumor.

CONCLUSIONS

Data portray the heterogeneous stromal microenvironment of breast pathologies, including alteration of multiple collagen-type patterns. ECM IMS is a promising new tool for investigating the stromal microenvironment of breast tissue including cancer.

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.

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.

Cyclooxygenase-1 (COX-1) and COX-1 Inhibitors in Cancer: A Review of Oncology and Medicinal Chemistry Literature

Prostaglandins and thromboxane are lipid signaling molecules deriving from arachidonic acid by the action of the cyclooxygenase isoenzymes COX-1 and COX-2. The role of cyclooxygenases (particularly COX-2) and prostaglandins (particularly PGE₂) in cancer-related inflammation has been extensively investigated. In contrast, COX-1 has received less attention, although its expression increases in several human cancers and a pathogenetic role emerges from experimental models. COX-1 and COX-2 isoforms seem to operate in a coordinate manner in cancer pathophysiology, especially in the tumorigenesis process. However, in some cases, exemplified by the serous ovarian carcinoma, COX-1 plays a pivotal role, suggesting that other histopathological and molecular subtypes of cancer disease could share this feature. Importantly, the analysis of functional implications of COX-1-signaling, as well as of pharmacological action of COX-1-selective inhibitors, should not be restricted to the COX pathway and to the effects of prostaglandins already known for their ability of affecting the tumor phenotype. A knowledge-based choice of the most appropriate tumor cell models, and a major effort in investigating the COX-1 issue in the more general context of arachidonic acid metabolic network by using the systems biology approaches, should be strongly encouraged.

Proteome Heterogeneity in Colorectal Cancer

Tumor heterogeneity is an important feature of colorectal cancer (CRC) manifested by dynamic changes in gene expression, protein expression, and availability of different tumor subtypes. Recent publications in the past 10 years have revealed proteome heterogeneity between different colorectal tumors and within the same tumor site. This paper reviews recent research works on the proteome heterogeneity in CRC, which includes the heterogeneity within a single tumor (intratumor heterogeneity), between different anatomical sites at the same organ, and between primary and metastatic sites (intertumor heterogeneity). The potential use of proteome heterogeneity in precision medicine and its implications in biomarker discovery and therapeutic outcomes will be discussed. Identification of the unique proteome landscape between and within individual tumors is imperative for understanding cancer biology and the management of CRC patients.

Functional imaging in combination with mutation status aids prediction of response to inhibiting B-cell receptor signaling in lymphoma

Aberrant B-cell receptor (BCR) signaling is known to contribute to malignant transformation. Two small molecule inhibitors targeting BCR pathway signaling include ibrutinib, a Bruton’s tyrosine kinase (BTK) inhibitor, and idelalisib, a specific Phosphatidylinositol-4,5-bisphosphate 3-kinase delta (PI3Kδ) inhibitor, both of which have been approved for use in haematological malignancies. Despite the identification of various diffuse large B-cell lymphoma (DLBCL) subtypes, mutation status alone is not sufficient to predict patient response and therapeutic resistance can arise. Herein we apply early molecular imaging across alternative activated B-cell (ABC) and germinal center B-cell (GCB) DLBCL subtypes to investigate the effects of BCR pathway inhibition. Treatment with both inhibitors adversely affected cell growth and viability. These effects were partially predictable based upon mutation status. Accordingly, very early 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography (¹⁸F-FDG-PET) and 3’-deoxy-3’[18F]-fluorothymidine positron emission tomography (¹⁸F-FLT-PET) reported tumour regression and reductions in tumour metabolism and proliferation upon treatment. Furthermore, matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS) identified alterations in the proteome of a model of ABC DLBCL upon treatment with ibrutinib or idelalisib. In conclusion we demonstrate that very early molecular imaging adds predictive value in addition to mutational status of DLBCL that may be useful in directing patient therapy.

"Stealth dissemination" of macrophage-tumor cell fusions cultured from blood of patients with pancreatic ductal adenocarcinoma

Here we describe isolation and characterization of macrophage-tumor cell fusions (MTFs) from the blood of pancreatic ductal adenocarcinoma (PDAC) patients. The MTFs were generally aneuploidy, and immunophenotypic characterizations showed that the MTFs express markers characteristic of PDAC and stem cells, as well as M2-polarized macrophages. Single cell RNASeq analyses showed that the MTFs express many transcripts implicated in cancer progression, LINE1 retrotransposons, and very high levels of several long non-coding transcripts involved in metastasis (such as MALAT1). When cultured MTFs were transplanted orthotopically into mouse pancreas, they grew as obvious well-differentiated islands of cells, but they also disseminated widely throughout multiple tissues in "stealth" fashion. They were found distributed throughout multiple organs at 4, 8, or 12 weeks after transplantation (including liver, spleen, lung), occurring as single cells or small groups of cells, without formation of obvious tumors or any apparent progression over the 4 to 12 week period. We suggest that MTFs form continually during PDAC development, and that they disseminate early in cancer progression, forming "niches" at distant sites for subsequent colonization by metastasis-initiating cells.

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.

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.

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.

Typing of colon and lung adenocarcinoma by high throughput imaging mass spectrometry

In advanced tumor stages, diagnosis is frequently made from metastatic tumor tissue. In some cases, the identification of the tumor of origin may be difficult by histology alone. In this setting, immunohistochemical and molecular biological methods are often required. In a subset of tumors definite diagnosis cannot be achieved. Thus, additional new diagnostic methods are required for precise tumor subtyping. Mass spectrometric methods are of special interest for the discrimination of different tumor types. We investigated whether it is possible to discern adenocarcinomas of colon and lung using high-throughput imaging mass spectrometry on formalin-fixed paraffin-embedded tissue microarrays. 101 primary adenocarcinoma of the colon and 91 primary adenocarcinoma of the lung were used to train a Linear Discriminant Analysis model. Results were validated on an independent set of 116 colonic and 75 lung adenocarcinomas. In the validation cohort 109 of 116 patients with colonic and 67 of 75 patients with lung adenocarcinomas were correctly classified. The ability to define proteomic profiles capable to discern different tumor types promises a valuable tool in cancer diagnostics and might complement current approaches. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.