Mass spectrometry imaging of endogenous metabolites in response to doxorubicin in a novel 3D osteosarcoma cell culture model

Mass spectrometry imaging methods for visualizing tumor heterogeneity

Profiling spatial distributions of lipids, metabolites, and proteins in tumors can reveal unique cellular microenvironments and provide molecular evidence for cancer cell dysfunction and proliferation. Mass spectrometry imaging (MSI) is a label-free technique that can be used to map biomolecules in tumors in situ. Here, we discuss current progress in applying MSI to uncover molecular heterogeneity in tumors. First, the analytical strategies to profile small molecules and proteins are outlined, and current methods for multimodal imaging to maximize biological information are highlighted. Second, we present and summarize biological insights obtained by MSI of tumor tissue. Finally, we discuss important considerations for designing MSI experiments and several current analytical challenges.

Integration of pan-omics technologies and three-dimensional in vitro tumor models: an approach toward drug discovery and precision medicine

Despite advancements in treatment protocols, cancer is one of the leading cause of deaths worldwide. Therefore, there is a need to identify newer and personalized therapeutic targets along with screening technologies to combat cancer. With the advent of pan-omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and lipidomics, the scientific community has witnessed an improved molecular and metabolomic understanding of various diseases, including cancer. In addition, three-dimensional (3-D) disease models have been efficiently utilized for understanding disease pathophysiology and as screening tools in drug discovery. An integrated approach utilizing pan-omics technologies and 3-D in vitro tumor models has led to improved understanding of the intricate network encompassing various signalling pathways and molecular cross-talk in solid tumors. In the present review, we underscore the current trends in omics technologies and highlight their role in understanding genotypic-phenotypic co-relation in cancer with respect to 3-D in vitro tumor models. We further discuss the challenges associated with omics technologies and provide our outlook on the future applications of these technologies in drug discovery and precision medicine for improved management of cancer.

Advancing rare cancer research by MALDI mass spectrometry imaging: Applications, challenges, and future perspectives in sarcoma

MALDI mass spectrometry imaging (MALDI imaging) uniquely advances cancer research, by measuring spatial distribution of endogenous and exogenous molecules directly from tissue sections. These molecular maps provide valuable insights into basic and translational cancer research, including tumor biology, tumor microenvironment, biomarker identification, drug treatment, and patient stratification. Despite its advantages, MALDI imaging is underutilized in studying rare cancers. Sarcomas, a group of malignant mesenchymal tumors, pose unique challenges in medical research due to their complex heterogeneity and low incidence, resulting in understudied subtypes with suboptimal management and outcomes. In this review, we explore the applicability of MALDI imaging in sarcoma research, showcasing its value in understanding this highly heterogeneous and challenging rare cancer. We summarize all MALDI imaging studies in sarcoma to date, highlight their impact on key research fields, including molecular signatures, cancer heterogeneity, and drug studies. We address specific challenges encountered when employing MALDI imaging for sarcomas, and propose solutions, such as using formalin-fixed paraffin-embedded tissues, and multiplexed experiments, and considerations for multi-site studies and digital data sharing practices. Through this review, we aim to spark collaboration between MALDI imaging researchers and clinical colleagues, to deploy the unique capabilities of MALDI imaging in the context of sarcoma.

Spatial lipidomics and metabolomics of multicellular tumor spheroids using MALDI-2 and trapped ion mobility imaging

Lipids and metabolites are small biological molecules that act major roles in cellular functions. Multicellular tumor spheroids (MCTS) are a highly beneficial three-dimensional cellular model for cancer research due to their ability to imitate numerous characteristics of tumor tissues. Increasing studies have performed spatial lipidomics and metabolomics in MCTS using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). However, these approaches often lack the sensitivity and specificity to offer a comprehensive characterization of lipids and metabolites within MCTS. In this study, we addressed this challenge by utilizing MALDI combined with laser-induced postionization (MALDI-2) and trapped ion mobility spectrometry (TIMS) imaging in H295R adrenocortical MCTS. Our results showed that MALDI-2 could detect more lipids and metabolites in MCTS than the traditional MALDI. TIMS data revealed a successful separation of many isomeric and isobaric ions of lipids and metabolites with different locations (e.g., proliferative region and necrotic region) within MCTS, suggesting an enhanced peak capacity for spatial lipidomics and metabolomics. To further identify these isomeric and isobaric ions, we performed MS/MS imaging experiments to compare the differences in signal intensities and spatial distributions of product ions. Our data highlight the strong potential of MALDI-2 and TIMS imaging for analyzing lipids and metabolites in MCTS, which may serve as valuable tools for numerous fields of biological and medical research.

Advances in Ultra-High-Resolution Mass Spectrometry for Pharmaceutical Analysis

Pharmaceutical analysis refers to an area of analytical chemistry that deals with active compounds either by themselves (drug substance) or when formulated with excipients (drug product). In a less simplistic way, it can be defined as a complex science involving various disciplines, e.g., drug development, pharmacokinetics, drug metabolism, tissue distribution studies, and environmental contamination analyses. As such, the pharmaceutical analysis covers drug development to its impact on health and the environment. Moreover, due to the need for safe and effective medications, the pharmaceutical industry is one of the most heavily regulated sectors of the global economy. For this reason, powerful analytical instrumentation and efficient methods are required. In the last decades, mass spectrometry has been increasingly used in pharmaceutical analysis both for research aims and routine quality controls. Among different instrumental setups, ultra-high-resolution mass spectrometry with Fourier transform instruments, i.e., Fourier transform ion cyclotron resonance (FTICR) and Orbitrap, gives access to valuable molecular information for pharmaceutical analysis. In fact, thanks to their high resolving power, mass accuracy, and dynamic range, reliable molecular formula assignments or trace analysis in complex mixtures can be obtained. This review summarizes the principles of the two main types of Fourier transform mass spectrometers, and it highlights applications, developments, and future perspectives in pharmaceutical analysis.

Multimodal Mass Spectrometry Imaging of an Aggregated 3D Cell Culture Model

Multimodal mass spectrometry imaging (MSI) is a leading approach for investigating the molecular processes within biological samples. The parallel detection of compounds including metabolites, lipids, proteins, and metal isotopes allows for a more holistic understanding of tissue microenvironments. Universal sample preparation is a primary enabler for samples of the same set to be run across multiple modalities. Using the same method and materials for a cohort of samples reduces any potential variability during sample preparation and allows for comparable analysis across analytical imaging techniques. Here, the MSI workflow is describing a sample preparation protocol for the analysis of three-dimensional (3D) cell culture models. The analysis of biologically relevant cultures by multimodal MSI offers a method in which models of cancer and disease can be studied for the use in early-stage drug development.

Automated Assessment of Cancer Drug Efficacy On Breast Tumor Spheroids in Aggrewell™400 Plates Using Image Cytometry

Tumor spheroid models have proven useful in the study of cancer cell responses to chemotherapeutic compounds by more closely mimicking the 3-dimensional nature of tumors in situ. Their advantages are often offset, however, by protocols that are long, complicated, and expensive. Efforts continue for the development of high-throughput assays that combine the advantages of 3D models with the convenience and simplicity of traditional 2D monolayer methods. Herein, we describe the development of a breast cancer spheroid image cytometry assay using T47D cells in Aggrewell™400 spheroid plates. Using the Celigo^® automated imaging system, we developed a method to image and individually track thousands of spheroids within the Aggrewell™400 microwell plate over time. We demonstrate the use of calcein AM and propidium iodide staining to study the effects of known anti-cancer drugs Doxorubicin, Everolimus, Gemcitabine, Metformin, Paclitaxel and Tamoxifen. We use the image cytometry results to quantify the fluorescence of calcein AM and PI as well as spheroid size in a dose dependent manner for each of the drugs. We observe a dose-dependent reduction in spheroid size and find that it correlates well with the viability obtained from the CellTiter96^® endpoint assay. The image cytometry method we demonstrate is a convenient and high-throughput drug-response assay for breast cancer spheroids under 400 μm in diameter, and may lay a foundation for investigating other three-dimensional spheroids, organoids, and tissue samples.

A new update of MALDI-TOF mass spectrometry in lipid research

Matrix-assisted laser desorption and ionization (MALDI) mass spectrometry (MS) is an indispensable tool in modern lipid research since it is fast, sensitive, tolerates sample impurities and provides spectra without major analyte fragmentation. We will discuss some methodological aspects, the related ion-forming processes and the MALDI MS characteristics of the different lipid classes (with the focus on glycerophospholipids) and the progress, which was achieved during the last ten years. Particular attention will be given to quantitative aspects of MALDI MS since this is widely considered as the most serious drawback of the method. Although the detailed role of the matrix is not yet completely understood, it will be explicitly shown that the careful choice of the matrix is crucial (besides the careful evaluation of the positive and negative ion mass spectra) in order to be able to detect all lipid classes of interest. Two developments will be highlighted: spatially resolved Imaging MS is nowadays well established and the distribution of lipids in tissues merits increasing interest because lipids are readily detectable and represent ubiquitous compounds. It will also be shown that a combination of MALDI MS with thin-layer chromatography (TLC) enables a fast spatially resolved screening of an entire TLC plate which makes the method competitive with LC/MS.

In Vitro Spatio-Temporal NMR Metabolomics of Living 3D Cell Models

Three-dimensional cell cultures are of growing importance in biochemical research as they represent tissue features more accurately than standard two-dimensional systems, but to investigate these challenging new models an adaptation of established analytical techniques is required. Spatially resolved data for living organoids are needed to gain insight into transport processes and biochemical characteristics of domains with different nutrient supply and waste product removal. Within this work, we present an NMR-based approach to obtain dynamically radial metabolite profiles for cell spheroids, one of the most frequently used 3D models. Our approach combines an easy to reproduce custom-made measurement design, maintaining physiological conditions without inhibition of the NMR experiment, with spatially selective NMR pulse sequences. To overcome the inherently low sensitivity of NMR spectroscopy we excited slices instead of smaller cube-like voxels in combination with an efficient interleaved measurement approach and employed a commercially available cryogenic NMR probe. Finally, radial metabolite profiles could be obtained via double Abel inversion of the measured one-dimensional intensity profiles. Applying this method to Ty82 cancer cell spheroids demonstrates the achieved spatial resolution, for instance confirming exceedingly high lactic acid and strongly decreased glucose concentrations in the oxygen-depleted core of the spheroid. Furthermore, our approach can be employed to investigate fast and slow metabolic changes in single spheroids simultaneously, which is shown as an example of a spheroid degrading over several days after stopping the nutrient supply.

In vitro three-dimensional cell cultures for bone sarcomas

Bone sarcomas are rare tumour entities that arise from the mesenchyme most of which are highly heterogeneous at the cellular, genetic and epigenetic levels. The three main types are osteosarcoma, Ewing sarcoma, and chondrosarcoma. These oncological entities are characterised by high morbidity and mortality and an absence of significant therapeutic improvement in the last four decades. In the field of oncology, in vitro cultures of cancer cells have been extensively used for drug screening unfortunately with limited success. Indeed, despite the massive knowledge acquired from conventional 2D culture methods, scientific community has been challenged by the loss of efficacy of drugs when moved to clinical trials. The recent explosion of new 3D culture methods is paving the way to more relevant in vitro models mimicking the in vivo tumour environment (e.g. bone structure) with biological responses close to the in vivo context. The present review gives a brief overview of the latest advances of the 3D culture methods used for studying primary bone sarcomas.

Applications of Omics Technologies for Three-Dimensional In Vitro Disease Models

Omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, multiomics, and integrated modalities, have greatly contributed to our understanding of various diseases by enabling researchers to probe the molecular wiring of cellular systems in a high-throughput and precise manner. With the development of tissue-engineered three-dimensional (3D) in vitro disease models, such as organoids and spheroids, there is potential of integrating omics technologies with 3D disease models to elucidate the complex links between genotype and phenotype. These 3D disease models have been used to model cancer, infectious disease, toxicity, neurological disorders, and others. In this review, we provide an overview of omics technologies, highlight current and emerging studies, discuss the associated experimental design considerations, barriers and challenges of omics technologies, and provide an outlook on the future applications of omics technologies with 3D models. Overall, this review aims to provide a valuable resource for tissue engineers seeking to leverage omics technologies for diving deeper into biological discovery. Impact statement With the emergence of three-dimensional (3D) in vitro disease models, tissue engineers are increasingly interested to investigate these systems to address biological questions related to disease mechanism, drug target discovery, therapy resistance, and more. Omics technologies are a powerful and high-throughput approach, but their application for 3D disease models is not maximally utilized. This review illustrates the achievements and potential of using omics technologies to leverage the full potential of 3D in vitro disease models. This will improve the quality of such models, advance our understanding of disease, and contribute to therapy development.

Probing drug delivery and mechanisms of action in 3D spheroid cells by quantitative analysis

Human tumor cells in a 3-dimensional (3D) spheroid can reflect the characteristics of solid tumors by forming cell-cell interactions and microenvironments. This makes 3D cell culture useful for preclinical stability and drug efficacy tests. In this study, the drug delivery and action mechanisms in SK-N-SH neuroblastoma cells cultured in 3D spheroids were quantitatively compared to those cultured in 2D monolayers using confocal microscopy imaging and inductively coupled plasma-mass spectrometry. In the 3D spheroids, cisplatin only accessed the surface, accumulating in the cells on the spheroid exterior. As a result, an increased cellular amount of cisplatin was required to obtain similar cytotoxicity in the 3D spheroid cells to that in 2D monolayers. The mechanisms of reduction of drug efficacy by dimethyl sulfoxide (DMSO) in the 3D spheroid cells compared to those in the 2D monolayer cells were further investigated. DMSO reduced the drug cytotoxicity by forming stable DMSO-substituted compounds that inhibited the cellular uptake of cisplatin and DNA-Pt adduct formation. The quantitative analysis used in this study is promising for understanding drug delivery and drug action mechanisms in cells in various microenvironments.

Characterization of an Aggregated Three-Dimensional Cell Culture Model by Multimodal Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) is an established analytical tool capable of defining and understanding complex tissues by determining the spatial distribution of biological molecules. Three-dimensional (3D) cell culture models mimic the pathophysiological environment of in vivo tumors and are rapidly emerging as a valuable research tool. Here, multimodal MSI techniques were employed to characterize a novel aggregated 3D lung adenocarcinoma model, developed by the group to mimic the in vivo tissue. Regions of tumor heterogeneity and the hypoxic microenvironment were observed based on the spatial distribution of a variety of endogenous molecules. Desorption electrospray ionization (DESI)-MSI defined regions of a hypoxic core and a proliferative outer layer from metabolite distribution. Targeted metabolites (e.g., lactate, glutamine, and citrate) were mapped to pathways of glycolysis and the TCA cycle demonstrating tumor metabolic behavior. The first application of imaging mass cytometry (IMC) with 3D cell culture enabled single-cell phenotyping at 1 μm spatial resolution. Protein markers of proliferation (K_i-67) and hypoxia (glucose transporter 1) defined metabolic signaling in the aggregoid model, which complemented the metabolite data. Laser ablation inductively coupled plasma (LA-ICP)-MSI analysis localized endogenous elements including magnesium and copper, further differentiating the hypoxia gradient and validating the protein expression. Obtaining a large amount of molecular information on a complementary nature enabled an in-depth understanding of the biological processes within the novel tumor model. Combining powerful imaging techniques to characterize the aggregated 3D culture highlighted a future methodology with potential applications in cancer research and drug development.

Artificial Intelligence to Decode Cancer Mechanism: Beyond Patient Stratification for Precision Oncology

The multitude of multi-omics data generated cost-effectively using advanced high-throughput technologies has imposed challenging domain for research in Artificial Intelligence (AI). Data curation poses a significant challenge as different parameters, instruments, and sample preparations approaches are employed for generating these big data sets. AI could reduce the fuzziness and randomness in data handling and build a platform for the data ecosystem, and thus serve as the primary choice for data mining and big data analysis to make informed decisions. However, AI implication remains intricate for researchers/clinicians lacking specific training in computational tools and informatics. Cancer is a major cause of death worldwide, accounting for an estimated 9.6 million deaths in 2018. Certain cancers, such as pancreatic and gastric cancers, are detected only after they have reached their advanced stages with frequent relapses. Cancer is one of the most complex diseases affecting a range of organs with diverse disease progression mechanisms and the effectors ranging from gene-epigenetics to a wide array of metabolites. Hence a comprehensive study, including genomics, epi-genomics, transcriptomics, proteomics, and metabolomics, along with the medical/mass-spectrometry imaging, patient clinical history, treatments provided, genetics, and disease endemicity, is essential. Cancer Moonshot℠ Research Initiatives by NIH National Cancer Institute aims to collect as much information as possible from different regions of the world and make a cancer data repository. AI could play an immense role in (a) analysis of complex and heterogeneous data sets (multi-omics and/or inter-omics), (b) data integration to provide a holistic disease molecular mechanism, (c) identification of diagnostic and prognostic markers, and (d) monitor patient's response to drugs/treatments and recovery. AI enables precision disease management well beyond the prevalent disease stratification patterns, such as differential expression and supervised classification. This review highlights critical advances and challenges in omics data analysis, dealing with data variability from lab-to-lab, and data integration. We also describe methods used in data mining and AI methods to obtain robust results for precision medicine from "big" data. In the future, AI could be expanded to achieve ground-breaking progress in disease management.

Developing a Drug Screening Platform: MALDI-Mass Spectrometry Imaging of Paper-Based Cultures

Many potential chemotherapeutics fail to reach patients. One of the key reasons is that compounds are tested during the drug discovery stage in two-dimensional (2D) cell cultures, which are often unable to accurately model in vivo outcomes. Three-dimensional (3D) in vitro tumor models are more predictive of chemotherapeutic effectiveness than 2D cultures, and thus, their implementation during the drug screening stage has the potential to more accurately evaluate compounds earlier, saving both time and money. Paper-based cultures (PBCs) are an emerging 3D culture platform in which cells suspended in Matrigel are seeded into paper scaffolds and cultured to generate a tissue-like environment. In this study, we demonstrate the potential of matrix-assisted laser desorption/ionization-mass spectrometry imaging with PBCs (MALDI-MSI-PBC) as a drug screening platform. This method discriminated regions of the PBCs with and without cells and/or drugs, indicating that coupling PBCs with MALDI-MSI has the potential to develop rapid, large-scale, and parallel mass spectrometric drug screens.