Multimodal mass spectrometric imaging of small molecules reveals distinct spatio-molecular signatures in differentially metastatic breast tumor models

Discovering metabolic vulnerability using spatially resolved metabolomics for antitumor small molecule-drug conjugates development as a precise cancer therapy strategy

Against tumor-dependent metabolic vulnerability is an attractive strategy for tumor-targeted therapy. However, metabolic inhibitors are limited by the drug resistance of cancerous cells due to their metabolic plasticity and heterogeneity. Herein, choline metabolism was discovered by spatially resolved metabolomics analysis as metabolic vulnerability which is highly active in different cancer types, and a choline-modified strategy for small molecule-drug conjugates (SMDCs) design was developed to fool tumor cells into indiscriminately taking in choline-modified chemotherapy drugs for targeted cancer therapy, instead of directly inhibiting choline metabolism. As a proof-of-concept, choline-modified SMDCs were designed, screened, and investigated for their druggability in vitro and in vivo. This strategy improved tumor targeting, preserved tumor inhibition and reduced toxicity of paclitaxel, through targeted drug delivery to tumor by highly expressed choline transporters, and site-specific release by carboxylesterase. This study expands the strategy of targeting metabolic vulnerability and provides new ideas of developing SMDCs for precise cancer therapy.

A multimodal pipeline using NMR spectroscopy and MALDI-TOF mass spectrometry imaging from the same tissue sample

NMR spectroscopy and matrix assisted laser desorption ionization mass spectrometry imaging (MALDI MSI) are both commonly used to detect large numbers of metabolites and lipids in metabolomic and lipidomic studies. We have demonstrated a new workflow, highlighting the benefits of both techniques to obtain metabolomic and lipidomic data, which has realized for the first time the combination of these two complementary and powerful technologies. NMR spectroscopy is frequently used to obtain quantitative metabolite information from cells and tissues. Lipid detection is also possible with NMR spectroscopy, with changes being visible across entire classes of molecules. Meanwhile, MALDI MSI provides relative measures of metabolite and lipid concentrations, mapping spatial information of many specific metabolite and lipid molecules across cells or tissues. We have used these two complementary techniques in combination to obtain metabolomic and lipidomic measurements from triple-negative human breast cancer cells and tumor xenograft models. We have emphasized critical experimental procedures that ensured the success of achieving NMR spectroscopy and MALDI MSI in a combined workflow from the same sample. Our data show that several phospholipid metabolite species were differentially distributed in viable and necrotic regions of breast tumor xenografts. This study emphasizes the power of combined NMR spectroscopy-MALDI imaging to advance metabolomic and lipidomic studies.

Lipid Profiles Obtained from MALDI Mass Spectrometric Imaging in Liver Cancer Metastasis Model

Liver cancer metastasis is known to be a poor prognosis and a leading cause of mortality. To overcome low therapeutic efficacy, understanding the physiological properties of liver cancer metastasis is required. However, the metastatic lesion is heterogeneous and complex. We investigate the distribution of lipids using matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) in an experimental metastasis model. We obtained the differentially expressed mass peaks in comparison between normal sites and metastatic lesions. The relationship of mass to charge ratio (m/z) and intensity were measured, m/z-indicated species were analyzed by MALDI-MS/MS analysis, and identification of these mass species was confirmed using the METASPACEannotation platform and Lipid Maps®. MALDI-MSI at m/z 725.6, 734.6, 735.6, 741.6, 742.6, 744.6, 756.6, and 772.6 showed significantly higher intensity, consistent with the metastatic lesions in hematoxylin-stained tissues. Sphingomyelin SM [d18:0/16:1], phosphatidylcholine (PC) [32:0], PC [31:0], PC [31:1], and PE [36:2] were highly expressed in metastatic lesions. Our results could provide information for understanding metastatic lesions. It suggests that the found lipids could be a biomarker for the diagnosis of metastatic lesions.

Dynamic intracellular exchange of nanomaterials' protein corona perturbs proteostasis and remodels cell metabolism

SignificanceThis study analyzed the dynamic protein corona on the surface of nanoparticles as they traversed from blood to cell lysosomes and escaped from lysosomes to cytoplasm in the target cells. We found with proteomic analysis an abundance of chaperone and glycolysis coronal proteins (i.e., heat shock cognate protein 70, heat shock protein 90, and pyruvate kinase M2 [PKM2]) after escape of the nanoparticles from lysosomes to the cytosol. Alterations of the coronal proteins (e.g., PKM2 and chaperone binding) induced proteostasis collapse, which subsequently led to elevated chaperone-mediated autophagy (CMA) activity in cells. As PKM2 is a key molecule in cell metabolism, we also revealed that PKM2 depletion was causative to CMA-induced cell metabolism disruption from glycolysis to lipid metabolism.

Role of MRI-Based Functional Imaging in Improving the Therapeutic Index of Radiotherapy in Cancer Treatment

Advances in radiation technology, such as intensity-modulated radiation therapy (IMRT), have largely enabled a biological dose escalation of the target volume (TV) and reduce the dose to adjacent tissues or organs at risk (OARs). However, the risk of radiation-induced injury increases as more radiation dose utilized during radiation therapy (RT), which predominantly limits further increases in TV dose distribution and reduces the local control rate. Thus, the accurate target delineation is crucial. Recently, technological improvements for precise target delineation have obtained more attention in the field of RT. The addition of functional imaging to RT can provide a more accurate anatomy of the tumor and normal tissues (such as location and size), along with biological information that aids to optimize the therapeutic index (TI) of RT. In this review, we discuss the application of some common MRI-based functional imaging techniques in clinical practice. In addition, we summarize the main challenges and prospects of these imaging technologies, expecting more inspiring developments and more productive research paths in the near future.

Nanoscale Mass Spectrometry Multimodal Imaging via Tip-Enhanced Photothermal Desorption

Materials ranging from adhesives, pharmaceuticals, lubricants, and personal care products are traditionally studied using macroscopic characterization techniques. However, their functionality is in reality defined by details of chemical organization on often noncrystalline matter with characteristic length scales on the order of microns to nanometers. Additionally, these materials are traditionally difficult to analyze using standard vacuum-based approaches that provide nanoscale chemical characterization due to their volatile and beam-sensitive nature. Therefore, approaches that operate under ambient conditions need to be developed that allow probing of nanoscale chemical phenomena and correlated functionality. Here, we demonstrate a tool for probing and visualizing local chemical environments and correlating them to material structure and functionality using advanced multimodal chemical imaging on a combined atomic force microscopy (AFM) and mass spectrometry (MS) system using tip-enhanced photothermal desorption with atmospheric pressure chemical ionization (APCI). We demonstrate enhanced performance metrics of the technique for correlated imaging and point sampling and illustrate the applicability for the analysis of trace chemicals on a human hair, additives in adhesives on paper, and pharmaceuticals samples notoriously difficult to analyze in a vacuum environment. Overall, this approach of correlating local chemical environments to structure and functionality is key to advancing research in many fields ranging from biology, to medicine, to material science.

Pneumatically Sprayed Gold Nanoparticles for Mass Spectrometry Imaging of Neurotransmitters

Using citrate-capped gold nanoparticles (AuNPs) for laser desorption ionization mass spectrometry (LDI-MS) is an approach that has demonstrated broad applicability to ionization of different classes of molecules. Here, we show a simple AuNP-based approach for the ionization of neurotransmitters. Specifically, the detection of acetylcholine, dopamine, epinephrine, glutamine, 4-aminobutyric acid, norepinephrine, octopamine, and serotonin was achieved at physiologically relevant concentrations in serum and homogenized tissue. Additionally, pneumatic spraying of AuNPs onto tissue sections facilitated mass spectrometry imaging (MSI) of rabbit brain tissue sections, zebrafish embryos, and neuroblastoma cells for several neurotransmitters simultaneously using this quick and simple sample preparation. AuNP LDI-MS achieved mapping of neurotransmitters in fine structures of zebrafish embryos and neuroblastoma cells at a lateral spatial resolution of 5 μm. The use of AuNPs to ionize small aminergic neurotransmitters in situ provides a fast, high-spatial resolution method for simultaneous detection of a class of molecules that typically evade comprehensive detection with traditional matrixes.

Discovering New Lipidomic Features Using Cell Type Specific Fluorophore Expression to Provide Spatial and Biological Specificity in a Multimodal Workflow with MALDI Imaging Mass Spectrometry

Identifying the spatial distributions of biomolecules in tissue is crucial for understanding integrated function. Imaging mass spectrometry (IMS) allows simultaneous mapping of thousands of biosynthetic products such as lipids but has needed a means of identifying specific cell-types or functional states to correlate with molecular localization. We report, here, advances starting from identity marking with a genetically encoded fluorophore. The fluorescence emission data were integrated with IMS data through multimodal image processing with advanced registration techniques and data-driven image fusion. In an unbiased analysis of spleens, this integrated technology enabled identification of ether lipid species preferentially enriched in germinal centers. We propose that this use of genetic marking for microanatomical regions of interest can be paired with molecular information from IMS for any tissue, cell-type, or activity state for which fluorescence is driven by a gene-tracking allele and ultimately with outputs of other means of spatial mapping.

Imaging of cancer lipid metabolism in response to therapy

Lipids represent a diverse array of molecules essential to the cell's structure, defense, energy, and communication. Lipid metabolism can often become dysregulated during tumor development. During cancer therapy, targeted inhibition of cell proliferation can likewise cause widespread and drastic changes in lipid composition. Molecular imaging techniques have been developed to monitor altered lipid profiles as a biomarker for cancer diagnosis and treatment response. For decades, MRS has been the dominant non-invasive technique for studying lipid metabolite levels. Recent insights into the oncogenic transformations driving changes in lipid metabolism have revealed new mechanisms and signaling molecules that can be exploited using optical imaging, mass spectrometry imaging, and positron emission tomography. These novel imaging modalities have provided researchers with a diverse toolbox to examine changes in lipids in response to a wide array of anticancer strategies including chemotherapy, radiation therapy, signal transduction inhibitors, gene therapy, immunotherapy, or a combination of these strategies. The understanding of lipid metabolism in response to cancer therapy continues to evolve as each therapeutic method emerges, and this review seeks to summarize the current field and areas of unmet needs.

Correlated Materials Characterization via Multimodal Chemical and Functional Imaging

Multimodal chemical imaging simultaneously offers high-resolution chemical and physical information with nanoscale and, in select cases, atomic resolution. By coupling modalities that collect physical and chemical information, we can address scientific problems in biological systems, battery and fuel cell research, catalysis, pharmaceuticals, photovoltaics, medicine, and many others. The combined systems enable the local correlation of material properties with chemical makeup, making fundamental questions of how chemistry and structure drive functionality approachable. In this Review, we present recent progress and offer a perspective for chemical imaging used to characterize a variety of samples by a number of platforms. Specifically, we present cases of infrared and Raman spectroscopies combined with scanning probe microscopy; optical microscopy and mass spectrometry; nonlinear optical microscopy; and, finally, ion, electron, and probe microscopies with mass spectrometry. We also discuss the challenges associated with the use of data originated by the combinatorial hardware, analysis, and machine learning as well as processing tools necessary for the interpretation of multidimensional data acquired from multimodal studies.

Specific Lipid and Metabolic Profiles of R-CHOP-Resistant Diffuse Large B-Cell Lymphoma Elucidated by Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging and in Vivo Imaging

Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell non-Hodgkin lymphoma. To treat this aggressive disease, R-CHOP, a combination of immunotherapy (R; rituximab) and chemotherapy (CHOP; cyclophosphamide, doxorubicin, vincristine, and prednisone), remains the most commonly used regimen for newly diagnosed DLBCLs. However, up to one-third of patients ultimately becomes refractory to initial therapy or relapses after treatment, and the high mortality rate highlights the urgent need for novel therapeutic approaches based upon selective molecular targets. In order to understand the molecular mechanisms underlying relapsed DLBCL, we studied differences in the lipid and metabolic composition of nontreated and R-CHOP-resistant tumors, using a combination of in vivo DLBCL xenograft models and mass spectrometry imaging. Together, these techniques provide information regarding analyte composition and molecular distributions of therapy-resistant and sensitive areas. We found specific lipid and metabolic profiles for R-CHOP-resistant tumors, such as a higher presence of phosphatidylinositol and sphingomyelin fragments. In addition, we investigated intratumor heterogeneity and identified specific lipid markers of viable and necrotic areas. Furthermore, we could monitor metabolic changes and found reduced adenosine triphosphate and increased adenosine monophosphate in the R-CHOP-resistant tumors. This work highlights the power of combining in vivo imaging and MSI to track molecular signatures in DLBCL, which has potential application for other diseases.

Applications of Metabolomics in Cancer Studies

Since the start of metabolomics as a field of research, the number of studies related to cancer has grown to such an extent that cancer metabolomics now represents its own discipline. In this chapter, the applications of metabolomics in cancer studies are explored. Different approaches and analytical platforms can be employed for the analysis of samples depending on the goal of the study and the aspects of the cancer metabolome being investigated. Analyses have concerned a range of cancers including lung, colorectal, bladder, breast, gastric, oesophageal and thyroid, amongst others. Developments in these strategies and methodologies that have been applied are discussed, in addition to exemplifying the use of cancer metabolomics in the discovery of biomarkers and in the assessment of therapy (both pharmaceutical and nutraceutical). Finally, the application of cancer metabolomics in personalised medicine is presented.

Fine Needle Aspiration Combined With Matrix-assisted Laser Desorption Ionization Time-of-Flight/Mass Spectrometry to Characterize Lipid Biomarkers for Diagnosing Accuracy of Breast Cancer

BACKGROUND

Fine needle aspiration (FNA) cytology has been widely used for pathologic assessment of breast lesions. However, the examination suffers a risk of false-negative results owing to insufficient sample volumes, inaccurate sampling positions, nondefinitive cytologic features, or suboptimal cell preservation. One approach to improve its accuracy is using modern mass spectrometry to detect disease biomarkers, of which the tissue samples are collected through FNA.

METHODS

The biological compounds in the FNA tissue samples were extracted and characterized by matrix-assisted laser desorption ionization time-of-flight/mass spectrometry (MALDI-TOF/MS). The results were further analyzed by principal component analysis. Distribution of lipid biomarkers on tissues was explored by imaging mass spectrometry.

RESULTS

Lipid profiles of the tissue samples collected by FNA were rapidly obtained through MALDI-TOF/MS analysis. Phosphatidylcholines and triacylglycerols were detected as the predominant compounds in cancerous and normal regions, respectively. The samples were clearly classified by principal component analysis, based on the differences in their lipid profiles. Different lipid patterns were clearly viewed through the molecular imaging of normal and tumorous regions of breast tissue samples.

CONCLUSION

The FNA-MALDI-TOF/MS approach can provide complementary information for pathological examinations and improve the accuracy of breast cancer diagnoses. Owing to the ease of operation and automation, it is possible to efficiently screen the lipid biomarkers in a large number of tissue samples by means of MALDI-TOF/MS.

3D Mass Spectrometry Imaging Reveals a Very Heterogeneous Drug Distribution in Tumors

Mass Spectrometry Imaging (MSI) is a widespread technique used to qualitatively describe in two dimensions the distribution of endogenous or exogenous compounds within tissue sections. Absolute quantification of drugs using MSI is a recent challenge that just in the last years has started to be addressed. Starting from a two dimensional MSI protocol, we developed a three-dimensional pipeline to study drug penetration in tumors and to develop a new drug quantification method by MALDI MSI. Paclitaxel distribution and concentration in different tumors were measured in a 3D model of Malignant Pleural Mesothelioma (MPM), which is known to be a very heterogeneous neoplasm, highly resistant to different drugs. The 3D computational reconstruction allows an accurate description of tumor PTX penetration, adding information about the heterogeneity of tumor drug distribution due to the complex microenvironment. The use of an internal standard, homogenously sprayed on tissue slices, ensures quantitative results that are similar to those obtained using HPLC. The 3D model gives important information about the drug concentration in different tumor sub-volumes and shows that the great part of each tumor is not reached by the drug, suggesting the concept of pseudo-resistance as a further explanation for ineffective therapies and tumors relapse.

Assessment of pathological response to therapy using lipid mass spectrometry imaging

In many cancers, the establishment of a patient’s future treatment regime often relies on histopathological assessment of tumor tissue specimens in order to determine the extent of the ‘pathological response’ to a given therapy. However, histopathological assessment of pathological response remains subjective. Here we use MALDI mass spectrometry imaging to generate lipid signatures from colorectal cancer liver metastasis specimens resected from patients preoperatively treated with chemotherapy. Using these signatures we obtained a unique pathological response score that correlates with prognosis. In addition, we identify single lipid moieties that are overexpressed in different histopathological features of the tumor, which have potential as new biomarkers for assessing response to therapy. These data show that computational methods, focusing on the lipidome, can be used to determine prognostic markers for response to chemotherapy and may potentially improve risk assessment and patient care.

Myc Expression Drives Aberrant Lipid Metabolism in Lung Cancer

MYC-mediated pathogenesis in lung cancer continues to attract interest for new therapeutic strategies. In this study, we describe a transgenic mouse model of KRAS-driven lung adenocarcinoma that affords reversible activation of MYC, used here as a tool for lipidomic profiling of MYC-dependent lung tumors formed in this model. Advanced mass spectrometric imaging and surface analysis techniques were used to characterize the spatial and temporal changes in lipid composition in lung tissue. We found that normal lung tissue was characterized predominantly by saturated phosphatidylcholines and phosphatidylglycerols, which are major lipid components of pulmonary surfactant. In contrast, tumor tissues displayed an increase in phosphatidylinositols and arachidonate-containing phospholipids that can serve as signaling precursors. Deactivating MYC resulted in a rapid and dramatic decrease in arachidonic acid and its eicosanoid metabolites. In tumors with high levels of MYC, we found an increase in cytosolic phospholipase A2 (cPLA2) activity with a preferential release of membrane-bound arachidonic acid, stimulating the lipoxygenase (LOX) and COX pathways also amplified by MYC at the level of gene expression. Deactivating MYC lowered cPLA2 activity along with COX2 and 5-LOX mRNA levels. Notably, inhibiting the COX/5-LOX pathways in vivo reduced tumor burden in a manner associated with reduced cell proliferation. Taken together, our results show how MYC drives the production of specific eicosanoids critical for lung cancer cell survival and proliferation, with possible implications for the use of COX and LOX pathway inhibitors for lung cancer therapy. Cancer Res; 76(16); 4608-18. ©2016 AACR.

Multimodal Mass Spectrometry Imaging of N-Glycans and Proteins from the Same Tissue Section

On-tissue digestion matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can be used to record spatially correlated molecular information from formalin-fixed, paraffin-embedded (FFPE) tissue sections. In this work, we present the in situ multimodal analysis of N-linked glycans and proteins from the same FFPE tissue section. The robustness and applicability of the method are demonstrated for several tumors, including epithelial and mesenchymal tumor types. Major analytical aspects, such as lateral diffusion of the analyte molecules and differences in measurement sensitivity due to the additional sample preparation methods, have been investigated for both N-glycans and proteolytic peptides. By combining the MSI approach with extract analysis, we were also able to assess which mass spectral peaks generated by MALDI-MSI could be assigned to unique N-glycan and peptide identities.

Identification of Biomarkers of Necrosis in Xenografts Using Imaging Mass Spectrometry

Xenografts are commonly used to test the effect of new drugs on human cancer. However, because of their heterogeneity, analysis of the results is often controversial. Part of the problem originates in the existence of tumor cells at different metabolic stages: from metastatic to necrotic cells, as it happens in real tumors. Imaging mass spectrometry is an excellent solution for the analysis of the results as it yields detailed information not only on the composition of the tissue but also on the distribution of the biomolecules within the tissue. Here, we use imaging mass spectrometry to determine the distribution of phosphatidylcholine (PC), phosphatidylethanolamine (PE), and their plasmanyl- and plasmenylether derivatives (PC-P/O and PE-P/O) in xenografts of five different tumor cell lines: A-549, NCI-H1975, BX-PC3, HT29, and U-87 MG. The results demonstrate that the necrotic areas showed a higher abundance of Na(+) adducts and of PC-P/O species, whereas a large abundance of PE-P/O species was found in all the xenografts. Thus, the PC/PC-ether and Na(+)/K(+) ratios may highlight the necrotic areas while an increase on the number of PE-ether species may be pointing to the existence of viable tumor tissues. Furthermore, the existence of important changes in the concentration of Na(+) and K(+) adducts between different tissues has to be taken into account while interpreting the imaging mass spectrometry results. Graphical Abstract ᅟ.

Mass spectrometry imaging for plant biology: a review

Mass spectrometry imaging (MSI) is a developing technique to measure the spatio-temporal distribution of many biomolecules in tissues. Over the preceding decade, MSI has been adopted by plant biologists and applied in a broad range of areas, including primary metabolism, natural products, plant defense, plant responses to abiotic and biotic stress, plant lipids and the developing field of spatial metabolomics. This review covers recent advances in plant-based MSI, general aspects of instrumentation, analytical approaches, sample preparation and the current trends in respective plant research.

Live-cell vibrational imaging of choline metabolites by stimulated Raman scattering coupled with isotope-based metabolic labeling

Choline is a small molecule that occupies a key position in the biochemistry of all living organisms. Recent studies have strongly implicated choline metabolites in cancer, atherosclerosis and nervous system development. To detect choline and its metabolites, existing physical methods such as magnetic resonance spectroscopy and positron emission tomography are often limited by the poor spatial resolution and substantial radiation dose. Fluorescence imaging, although with submicrometer resolution, requires introduction of bulky fluorophores and thus is difficult in labeling the small choline molecule. By combining the emerging bond-selective stimulated Raman scattering microscopy with metabolic incorporation of deuterated choline, herein we have achieved high resolution imaging of choline-containing metabolites in living mammalian cell lines, primary hippocampal neurons and the multicellular organism C. elegans. Different subcellular distributions of choline metabolites are observed between cancer cells and non-cancer cells, which may reveal a functional difference in the choline metabolism and lipid-mediated signaling events. In neurons, choline incorporation is visualized within both soma and neurites, where choline metabolites are more evenly distributed compared to proteins. Furthermore, choline localization is also observed in the pharynx region of C. elegans larvae, consistent with its organogenesis mechanism. These applications demonstrate the potential of isotope-based stimulated Raman scattering microscopy for future choline-related disease detection and development monitoring in vivo.

Lipid analysis of eight human breast cancer cell lines with ToF-SIMS

In this work, four triple negative (TN) cell lines, three ER+ and PR+ receptor positive (RP) cell lines, and one ER+, PR+, and HER2+ cell line were chemically distinguished from one another using time-of-flight secondary ion mass spectrometry (ToF-SIMS) and principal component analysis (PCA). PCA scores separation was observed between the individual cell lines within a given classification (TN and RP) and there were distinctly different trends found in the fatty acid and lipid compositions of the two different classifications. These trends indicated that the RP cell lines separated out based on the carbon chain length of the lipids while the TN cell lines showed separation based on cholesterol-related peaks (in the positive ion data). Both cell types separated out by trends in fatty acid chain length and saturation in the negative ions. These chemical differences may be manifestations of unique metabolic processes within each of the different cell lines. Additionally, the HER2+ cell line was distinguished from three other RP cell types as having a unique distribution of fatty acids including anticorrelation to 18-carbon chain fatty acids. As these cell lines could not be grown in the same growth media, a combination of chemical fixation, rinsing, C60 (+) presputtering, and selection of cellular regions-of-interest is also presented as a successful method to acquire ToF-SIMS data from cell lines grown in different media.

Structural mass spectrometry of tissue extracts to distinguish cancerous and non-cancerous breast diseases

Aberrant metabolism in breast cancer tumors has been widely studied by both targeted and untargeted analyses to characterize the affected metabolic pathways. In this work, we utilize ultra-performance liquid chromatography (UPLC) in tandem with ion mobility-mass spectrometry (IM-MS), which provides chromatographic, structural, and mass information, to characterize the aberrant metabolism associated with breast diseases such as cancer. In a double-blind analysis of matched control (n = 3) and disease tissues (n = 3), samples were homogenized, polar metabolites were extracted, and the extracts were characterized by UPLC-IM-MS/MS. Principle component analysis revealed a strong separation between disease tissues, with one diseased tissue clustering with the control tissues along PC1 and two others separated along PC2. Using post-ion mobility MS/MS spectra acquired by data-independent acquisition, the features giving rise to the observed grouping were determined to be biomolecules associated with aggressive breast cancer tumors, including glutathione, oxidized glutathione, thymosins β4 and β10, and choline-containing species. Pathology reports revealed the outlier of the disease tissues to be a benign fibroadenoma, whereas the other disease tissues represented highly metabolic benign and aggressive tumors. This IM-MS-based workflow bridges the transition from untargeted metabolomic profiling to tentative identifications of key descriptive molecular features using data acquired in one analysis, with additional experiments performed only for validation. The ability to resolve cancerous and non-cancerous tissues at the biomolecular level demonstrates UPLC-IM-MS/MS as a robust and sensitive platform for metabolomic profiling of tissues.

MALDI-Mass Spectrometric Imaging Revealing Hypoxia-Driven Lipids and Proteins in a Breast Tumor Model

Hypoxic areas are a common feature of rapidly growing malignant tumors and their metastases and are typically spatially heterogeneous. Hypoxia has a strong impact on tumor cell biology and contributes to tumor progression in multiple ways. To date, only a few molecular key players in tumor hypoxia, such as hypoxia-inducible factor-1 (HIF-1), have been discovered. The distribution of biomolecules is frequently heterogeneous in the tumor volume and may be driven by hypoxia and HIF-1α. Understanding the spatially heterogeneous hypoxic response of tumors is critical. Mass spectrometric imaging (MSI) provides a unique way of imaging biomolecular distributions in tissue sections with high spectral and spatial resolution. In this paper, breast tumor xenografts grown from MDA-MB-231-HRE-tdTomato cells, with a red fluorescent tdTomato protein construct under the control of a hypoxia response element (HRE)-containing promoter driven by HIF-1α, were used to detect the spatial distribution of hypoxic regions. We elucidated the 3D spatial relationship between hypoxic regions and the localization of lipids and proteins by using principal component analysis-linear discriminant analysis (PCA-LDA) on 3D rendered MSI volume data from MDA-MB-231-HRE-tdTomato breast tumor xenografts. In this study, we identified hypoxia-regulated proteins active in several distinct pathways such as glucose metabolism, regulation of actin cytoskeleton, protein folding, translation/ribosome, splicesome, the PI3K-Akt signaling pathway, hemoglobin chaperone, protein processing in endoplasmic reticulum, detoxification of reactive oxygen species, aurora B signaling/apoptotic execution phase, the RAS signaling pathway, the FAS signaling pathway/caspase cascade in apoptosis, and telomere stress induced senescence. In parallel, we also identified colocalization of hypoxic regions and various lipid species such as PC(16:0/18:0), PC(16:0/18:1), PC(16:0/18:2), PC(16:1/18:4), PC(18:0/18:1), and PC(18:1/18:1), among others. Our findings shed light on the biomolecular composition of hypoxic tumor regions, which may be responsible for a given tumor's resistance to radiation or chemotherapy.

MALDI TOF imaging mass spectrometry in clinical pathology: a valuable tool for cancer diagnostics (review)

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) imaging mass spectrometry (IMS) is an evolving technique in cancer diagnostics and combines the advantages of mass spectrometry (proteomics), detection of numerous molecules, and spatial resolution in histological tissue sections and cytological preparations. This method allows the detection of proteins, peptides, lipids, carbohydrates or glycoconjugates and small molecules.Formalin-fixed paraffin-embedded tissue can also be investigated by IMS, thus, this method seems to be an ideal tool for cancer diagnostics and biomarker discovery. It may add information to the identification of tumor margins and tumor heterogeneity. The technique allows tumor typing, especially identification of the tumor of origin in metastatic tissue, as well as grading and may provide prognostic information. IMS is a valuable method for the identification of biomarkers and can complement histology, immunohistology and molecular pathology in various fields of histopathological diagnostics, especially with regard to identification and grading of tumors.

Analysis of the lipidome of xenografts using MALDI-IMS and UHPLC-ESI-QTOF

Human tumor xenografts in immunodeficient mice are a very popular model to study the development of cancer and to test new drug candidates. Among the parameters analyzed are the variations in the lipid composition, as they are good indicators of changes in the cellular metabolism. Here, we present a study on the distribution of lipids in xenografts of NCI-H1975 human lung cancer cells, using MALDI imaging mass spectrometry and UHPLC-ESI-QTOF. The identification of lipids directly from the tissue by MALDI was aided by the comparison with identification using ESI ionization in lipid extracts from the same xenografts. Lipids belonging to PCs, PIs, SMs, DAG, TAG, PS, PA, and PG classes were identified and their distribution over the xenograft was determined. Three areas were identified in the xenograft, corresponding to cells in different metabolic stages and to a layer of adipose tissue that covers the xenograft.

Gold sputtered fiducial markers for combined secondary ion mass spectrometry and MALDI imaging of tissue samples

Mass spectrometry imaging (MSI) is a label free technique capable of providing simultaneous identification and localization of biomolecules. A multimodal approach is required that allows for the study of the complexity of biological tissue samples to overcome the limitations of a single MSI technique. Secondary ion mass spectrometry (SIMS) allows for high spatial resolution imaging while matrix-assisted laser desorption (MALDI) offers a significantly wider mass range. The combination of coregistered SIMS and MALDI images results in detailed and unique biomolecular information. In this Technical Note, we describe how gold sputtered/implanted fiducial markers (FM) are created and can be used to ensure a proper overlay and coregistration of the two-dimensional images provided by the two MSI modalities.

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

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

Towards lipidomics of low-abundant species for exploring tumor heterogeneity guided by high-resolution mass spectrometry imaging

Many studies have evidenced the main role of lipids in physiological and also pathological processes such as cancer, diabetes or neurodegenerative diseases. The identification and the in situ localization of specific low-abundant lipid species involved in cancer biology are still challenging for both fundamental studies and lipid marker discovery. In this paper, we report the identification and the localization of specific isobaric minor phospholipids in human breast cancer xenografts by FTICR MALDI imaging supported by histochemistry. These potential candidates can be further confirmed by liquid chromatography coupled with electrospray mass spectrometry (LC-ESI-MS) after extraction from the region of interest defined by MALDI imaging. Finally, this study highlights the importance of characterizing the heterogeneous distribution of low-abundant lipid species, relevant in complex histological samples for biological purposes.

Determination of paclitaxel distribution in solid tumors by nano-particle assisted laser desorption ionization mass spectrometry imaging

A sensitive, simple and reproducible protocol for nanoparticle-assisted laser desorption/ionization mass spectrometry imaging technique is described. The use of commercially available TiO₂ nanoparticles abolishes heterogeneous crystallization, matrix background interferences and enhances signal detection, especially in the low mass range. Molecular image normalization was based on internal standard deposition on tissues, allowing direct comparison of drug penetration and distribution between different organs and tissues. The method was applied to analyze the distribution of the anticancer drug paclitaxel, inside normal and neoplastic mouse tissue sections. Spatial resolution was good, with a linear response between different in vivo treatments and molecular imaging intensity using therapeutic drug doses. This technique distinguishes the different intensity of paclitaxel distribution in control organs of mice, such as liver and kidney, in relation to the dose. Animals treated with 30 mg/kg of paclitaxel had half of the concentration of those treated with 60 mg/kg. We investigated the spatial distribution of paclitaxel in human melanoma mouse xenografts, following different dosage schedules and found a more homogeneous drug distribution in tumors of mice given repeated doses (5×8 mg/kg) plus a 60 mg/kg dose than in those assigned only a single 60 mg/kg dose. The protocol can be readily applied to investigate anticancer drug distribution in neoplastic lesions and to develop strategies to optimize and enhance drug penetration through different tumor tissues.

High-resolution imaging mass spectrometry reveals detailed spatial distribution of phosphatidylinositols in human breast cancer

High-resolution matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is an emerging application for lipid research that provides a comprehensive and detailed spatial distribution of ionized molecules. Recent lipidomic approach has identified several phospholipids and phosphatidylinositols (PIs) are accumulated in breast cancer tissues and are therefore novel biomarker candidates. Because their distribution and significance remain unclear, we investigated the precise spatial distribution of PIs in human breast cancer tissues using high-resolution MALDI IMS. We evaluated tissues from nine human breast cancers and one normal mammary gland by negative ion MALDI IMS at a resolution of 10 μm. We detected 10 PIs with different fatty acid compositions, and their proportions were remarkably variable in the malignant epithelial regions. High-resolution imaging enabled us to discriminate cancer cell clusters from the adjacent stromal tissue within epithelial regions; moreover, this technique revealed that several PIs were specifically localized to cancer cell clusters. These PIs were heterogeneously distributed within cancer cell clusters, allowing us to identify two different populations of cancer cells that predominantly expressed either PI(18:0/18:1) or PI(18:0/20:3). Tracing the expression level of PIs during cancer cell progression suggested that the latter population is associated with the invasion. Our study documents a novel model for phospholipid analysis of breast cancer tissues by using high-resolution MALDI IMS and identifies candidate PIs that can describe a specific phenotype of cancer cells.

AC1MMYR2, an inhibitor of dicer-mediated biogenesis of Oncomir miR-21, reverses epithelial-mesenchymal transition and suppresses tumor growth and progression

The extensive involvement of miRNAs in cancer pathobiology has opened avenues for drug development based on oncomir inhibition. Dicer is the core enzyme in miRNA processing that cleaves the terminal loop of precursor microRNAs (pre-miRNAs) to generate mature miRNA duplexes. Using the three-dimensional structure of the Dicer binding site on the pre-miR-21 oncomir, we conducted an in silico high-throughput screen for small molecules that block miR-21 maturation. By this method, we identified a specific small-molecule inhibitor of miR-21, termed AC1MMYR2, which blocked the ability of Dicer to process pre-miR-21 to mature miR-21. AC1MMYR2 upregulated expression of PTEN, PDCD4, and RECK and reversed epithelial-mesenchymal transition via the induction of E-cadherin expression and the downregulation of mesenchymal markers, thereby suppressing proliferation, survival, and invasion in glioblastoma, breast cancer, and gastric cancer cells. As a single agent in vivo, AC1MMYR2 repressed tumor growth, invasiveness, and metastasis, increasing overall host survival with no observable tissue cytotoxicity in orthotopic models. Our results offer a novel, high-throughput method to screen for small-molecule inhibitors of miRNA maturation, presenting AC1MMYR2 as a broadly useful candidate antitumor drug.

miR-23b regulates cytoskeletal remodeling, motility and metastasis by directly targeting multiple transcripts

Uncontrolled cell proliferation and cytoskeletal remodeling are responsible for tumor development and ultimately metastasis. A number of studies have implicated microRNAs in the regulation of cancer cell invasion and migration. Here, we show that miR-23b regulates focal adhesion, cell spreading, cell-cell junctions and the formation of lamellipodia in breast cancer (BC), implicating a central role for it in cytoskeletal dynamics. Inhibition of miR-23b, using a specific sponge construct, leads to an increase of cell migration and metastatic spread in vivo, indicating it as a metastatic suppressor microRNA. Clinically, low miR-23b expression correlates with the development of metastases in BC patients. Mechanistically, miR-23b is able to directly inhibit a number of genes implicated in cytoskeletal remodeling in BC cells. Through intracellular signal transduction, growth factors activate the transcription factor AP-1, and we show that this in turn reduces miR-23b levels by direct binding to its promoter, releasing the pro-invasive genes from translational inhibition. In aggregate, miR-23b expression invokes a sophisticated interaction network that co-ordinates a wide range of cellular responses required to alter the cytoskeleton during cancer cell motility.

Combined MR, fluorescence and histology imaging strategy in a human breast tumor xenograft model

Applications of molecular imaging in cancer and other diseases frequently require the combination of in vivo imaging modalities, such as MR and optical imaging, with ex vivo optical, fluorescence, histology and immunohistochemical imaging to investigate and relate molecular and biological processes to imaging parameters within the same region of interest. We have developed a multimodal image reconstruction and fusion framework that accurately combines in vivo MRI and MRSI, ex vivo brightfield and fluorescence microscopic imaging and ex vivo histology imaging. Ex vivo brightfield microscopic imaging was used as an intermediate modality to facilitate the ultimate link between ex vivo histology and in vivo MRI/MRSI. Tissue sectioning necessary for optical and histology imaging required the generation of a three-dimensional reconstruction module for two-dimensional ex vivo optical and histology imaging data. We developed an external fiducial marker-based three-dimensional reconstruction method, which was able to fuse optical brightfield and fluorescence with histology imaging data. The registration of the three-dimensional tumor shape was pursued to combine in vivo MRI/MRSI and ex vivo optical brightfield and fluorescence imaging data. This registration strategy was applied to in vivo MRI/MRSI, ex vivo optical brightfield/fluorescence and histology imaging datasets obtained from human breast tumor models. Three-dimensional human breast tumor datasets were successfully reconstructed and fused with this platform.

Localized hypoxia results in spatially heterogeneous metabolic signatures in breast tumor models

Tumor hypoxia triggers signaling cascades that significantly affect biologic outcomes such as resistance to radiotherapy and chemotherapy in breast cancer. Hypoxic regions in solid tumor are spatially heterogeneous. Therefore, delineating the origin and extent of hypoxia in tumors is critical. In this study, we have investigated the effect of hypoxia on different metabolic pathways, such as lipid and choline metabolism, in a human breast cancer model. Human MDA-MB-231 breast cancer cells and tumors, which were genetically engineered to express red fluorescent tdTomato protein under hypoxic conditions, were used to investigate hypoxia. Our data were obtained with a novel three-dimensional multimodal molecular imaging platform that combines magnetic resonance (MR) imaging, MR spectroscopic imaging (MRSI), and optical imaging of hypoxia and necrosis. A higher concentration of noninvasively detected total choline-containing metabolites (tCho) and lipid CH3 localized in the tdTomato-fluorescing hypoxic regions indicated that hypoxia can upregulate tCho and lipid CH3 levels in this breast tumor model. The increase in tCho under hypoxia was primarily due to elevated phosphocholine levels as shown by in vitro MR spectroscopy. Elevated lipid CH3 levels detected under hypoxia were caused by an increase in mobile MR-detectable lipid droplets, as demonstrated by Nile Red staining. Our findings demonstrate that noninvasive MRSI can help delineate hypoxic regions in solid tumors by means of detecting the metabolic outcome of tumor hypoxia, which is characterized by elevated tCho and lipid CH3.

HR-MALDI-MS imaging assisted screening of β-carboline alkaloids discovered from Mycena metata

Fruiting bodies of Mycena metata were screened for the presence of new secondary metabolites by means of HPLC-UV, LC-HR-ESIMS, and high-resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (HR-MALDI-MS imaging). Thus, a new β-carboline alkaloid, 6-hydroxymetatacarboline D (1d), was isolated from fruiting bodies of M. metata. 6-Hydroxymetatacarboline D consists of a highly substituted β-carboline skeleton, which is likely to be derived biosynthetically from l-tryptophan, 2-oxoglutaric acid, l-threonine, and l-proline. The structure of the alkaloid was established by 2D NMR spectroscopic methods and HR-ESIMS. Moreover, by extensive application of LC-HR-ESIMS, LC-HR-ESIMS/MS, and LC-HR-ESIMS(3) techniques we were able to elucidate the structures of a number of accompanying β-carboline alkaloids, 1a-1c, 1e-1i, and 2a-2g, structurally closely related to 6-hydroxymetatacarboline D, which are present in M. metata in minor amounts. The absolute configuration of the stereogenic centers of the β-carboline alkaloids was determined by GC-MS comparison with authentic synthetic samples after hydrolytic cleavage and derivatization of the resulting amino acids.

Histology-driven data mining of lipid signatures from multiple imaging mass spectrometry analyses: application to human colorectal cancer liver metastasis biopsies

Imaging mass spectrometry (IMS) represents an innovative tool in the cancer research pipeline, which is increasingly being used in clinical and pharmaceutical applications. The unique properties of the technique, especially the amount of data generated, make the handling of data from multiple IMS acquisitions challenging. This work presents a histology-driven IMS approach aiming to identify discriminant lipid signatures from the simultaneous mining of IMS data sets from multiple samples. The feasibility of the developed workflow is evaluated on a set of three human colorectal cancer liver metastasis (CRCLM) tissue sections. Lipid IMS on tissue sections was performed using MALDI-TOF/TOF MS in both negative and positive ionization modes after 1,5-diaminonaphthalene matrix deposition by sublimation. The combination of both positive and negative acquisition results was performed during data mining to simplify the process and interrogate a larger lipidome into a single analysis. To reduce the complexity of the IMS data sets, a sub data set was generated by randomly selecting a fixed number of spectra from a histologically defined region of interest, resulting in a 10-fold data reduction. Principal component analysis confirmed that the molecular selectivity of the regions of interest is maintained after data reduction. Partial least-squares and heat map analyses demonstrated a selective signature of the CRCLM, revealing lipids that are significantly up- and down-regulated in the tumor region. This comprehensive approach is thus of interest for defining disease signatures directly from IMS data sets by the use of combinatory data mining, opening novel routes of investigation for addressing the demands of the clinical setting.

MALDI imaging mass spectrometry for direct tissue analysis

MALDI (Matrix-Assisted Laser Desorption/Ionization) Imaging mass spectrometry is a powerful new method for analyzing the spatial distribution of molecules in tissues. Several different classes of cellular constituents such as proteins, peptides, lipids, and small molecules can be analyzed in situ while maintaining the morphological integrity of the tissue. This allows a correlation of the morphology with the previously acquired molecular patterns. By this, specific molecules can be clearly assigned to their cellular origin. Here, we will present a protocol for the analysis of proteins in tissues which are either native or alcohol-fixed and paraffin-embedded.

Novel methodologies in metabolic profiling with a focus on molecular diagnostic applications

The metabolome contains all the biological end points of genomic, transcriptomic and proteomic perturbations, also including the influence of gut microbiota and the environment, giving a direct picture of an organism's ongoing metabolic state. Metabolomics thus has the potential to be an effective tool for early diagnosis of disease, and also to be a predictor of treatment response and survival. In recent years, the development of instrumental systems has enabled more comprehensive coverage of the metabolome. Advances in mass spectrometry and chromatography have particularly improved both the efficiency of nontargeted metabolic profiling as well as the sensitivity and reliability of targeted analyses. Mass spectrometric techniques are also increasingly becoming accepted as a routine diagnostic tool in clinical laboratories. This review summarizes the most recent advances and current challenges in metabolomics, with a focus on mass spectrometric methods utilized in biomarker research, highlighted with selected examples.

Imaging the clear cell renal cell carcinoma proteome

PURPOSE

A key barrier to identifying tissue biomarkers of clear cell renal cell carcinoma is the heterogeneity of protein expression in tissue. However, by providing spectra for every 0.05 mm(2) area of tissue, imaging mass spectrometry reveals the spatial distribution of peptides. We determined whether this approach could be used to identify and map protein signatures of clear cell renal cell carcinoma.

MATERIALS AND METHODS

We constructed 2 tissue microarrays with 2 cores each of matched tumor and normal tissue from the nephrectomy specimens of 70 patients with clear cell renal cell carcinoma. Samples were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. In each tissue microarray peptide signatures were identified that differentiated cancer from normal tissue. The signatures were then cross validated. Mass spectrometry/mass spectrometry sequencing was performed to determine the identity of select, differentially expressed peptides. Immunohistochemistry was used for validation.

RESULTS

In each tissue microarray peptide signatures were identified that had 94.7% to 98.5% classification accuracy for each 0.05 mm(2) spot (spectrum) and 96.9% to 100% accuracy for each tissue core. Cross validation across tissue microarrays revealed a classification accuracy of 82.6% to 84.7% for each spot and 88.9% to 92.4% for each core. We identified vimentin, histone 2A.X and α-enolase as proteins with greater expression in cancer tissue. This was validated by immunohistochemistry.

CONCLUSIONS

Imaging mass spectrometry identified and mapped specific peptides that accurately distinguished malignant from normal renal tissue. This demonstrates its potential as a novel, high throughput approach to clear cell renal cell carcinoma biomarker discovery. Given the multiple pathways and known heterogeneity involved in tumors such as clear cell renal cell carcinoma, multiple peptide signatures that maintain their spatial relationships may outperform traditional protein biomarkers.

Global changes in phospholipids identified by MALDI MS in rats with focal cerebral ischemia

Neuronal membrane phospholipids are highly affected by oxidative stress caused by ischemic injury. Thus, it is necessary to identify key lipid components that show changes during ischemia to develop an effective approach to prevent brain damage from ischemic injury. The recent development of MALDI imaging MS (MALDI IMS) makes it possible to identify phospholipids that change between damaged and normal regions directly from tissues. In this study, we conducted IMS on rat brains damaged by ischemic injury and detected various phospholipids that showed unique distributions between normal and damaged areas of the brain. Among them, we confirmed changes in phospholipids such as lysophosphatidylcholine, phosphatidylcholine, phosphatidylethanolamine, and sphingomyelin by MALDI IMS followed by MS/MS analysis. These lipids were present in high concentrations in the brain and are important for maintenance of cellular structure as well as production of second messengers for cellular signal transduction. Our results emphasize the identification of phospholipid markers for ischemic injury and successfully identified several distinctly located phospholipids in ischemic brain tissue.