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

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.

Deep learning-assisted mass spectrometry imaging for preliminary screening and pre-classification of psychoactive substances

Currently, it is of great urgency to develop a rapid pre-classification and screening method for suspected drugs as the constantly springing up of new psychoactive substances. In most researches, psychoactive substances classification approaches depended on the similar chemical structures and pharmacological action with known drugs. Such approaches could not face the complicated circumstance of emerging new psychoactive substances. Herein, mass spectrometry imaging and convolutional neural networks (CNN) were used for preliminary screening and pre-classification of suspected psychoactive substances. Mass spectrometry imaging was performed simultaneously on two brain slices as one was from blank group and another one was from psychoactive substance-induced group. Then, fused neurotransmitter variation mass spectrometry images (Nv-MSIs) reflecting the difference of neurotransmitters between two slices were achieved through two homemade programs. A CNN model was developed to classify the Nv-MSIs. Compared with traditional classification methods, CNN achieved better estimation accuracy and required minimal data preprocessing. Also, the specific region on Nv-MSIs and weight of each neurotransmitter that affected the classification most could be unraveled by CNN. Finally, the method was successfully applied to assist the identification of a new psychoactive substance seized recently. This sample was identified as cannabinoids, which greatly promoted the screening process.

Imaging with mass spectrometry: Which ionization technique is best?

The use of mass spectrometry (MS) to acquire molecular images of biological tissues and other substrates has developed into an indispensable analytical tool over the past 25 years. Imaging mass spectrometry technologies are widely used today to study the in situ spatial distributions for a variety of analytes. Early MS images were acquired using secondary ion mass spectrometry and matrix-assisted laser desorption/ionization. Researchers have also designed and developed other ionization techniques in recent years to probe surfaces and generate MS images, including desorption electrospray ionization (DESI), nanoDESI, laser ablation electrospray ionization, and infrared matrix-assisted laser desorption electrospray ionization. Investigators now have a plethora of ionization techniques to select from when performing imaging mass spectrometry experiments. This brief perspective will highlight the utility and relative figures of merit of these techniques within the context of their use in imaging mass spectrometry.

Microfluidics in High-Throughput Drug Screening: Organ-on-a-Chip and C. elegans-Based Innovations

The development of therapeutic interventions for diseases necessitates a crucial step known as drug screening, wherein potential substances with medicinal properties are rigorously evaluated. This process has undergone a transformative evolution, driven by the imperative need for more efficient, rapid, and high-throughput screening platforms. Among these, microfluidic systems have emerged as the epitome of efficiency, enabling the screening of drug candidates with unprecedented speed and minimal sample consumption. This review paper explores the cutting-edge landscape of microfluidic-based drug screening platforms, with a specific emphasis on two pioneering approaches: organ-on-a-chip and C. elegans-based chips. Organ-on-a-chip technology harnesses human-derived cells to recreate the physiological functions of human organs, offering an invaluable tool for assessing drug efficacy and toxicity. In parallel, C. elegans-based chips, boasting up to 60% genetic homology with humans and a remarkable affinity for microfluidic systems, have proven to be robust models for drug screening. Our comprehensive review endeavors to provide readers with a profound understanding of the fundamental principles, advantages, and challenges associated with these innovative drug screening platforms. We delve into the latest breakthroughs and practical applications in this burgeoning field, illuminating the pivotal role these platforms play in expediting drug discovery and development. Furthermore, we engage in a forward-looking discussion to delineate the future directions and untapped potential inherent in these transformative technologies. Through this review, we aim to contribute to the collective knowledge base in the realm of drug screening, providing valuable insights to researchers, clinicians, and stakeholders alike. We invite readers to embark on a journey into the realm of microfluidic-based drug screening platforms, fostering a deeper appreciation for their significance and promising avenues yet to be explored.

Promise of spatially resolved omics for tumor research

Tumors are spatially heterogeneous tissues that comprise numerous cell types with intricate structures. By interacting with the microenvironment, tumor cells undergo dynamic changes in gene expression and metabolism, resulting in spatiotemporal variations in their capacity for proliferation and metastasis. In recent years, the rapid development of histological techniques has enabled efficient and high-throughput biomolecule analysis. By preserving location information while obtaining a large number of gene and molecular data, spatially resolved metabolomics (SRM) and spatially resolved transcriptomics (SRT) approaches can offer new ideas and reliable tools for the in-depth study of tumors. This review provides a comprehensive introduction and summary of the fundamental principles and research methods used for SRM and SRT techniques, as well as a review of their applications in cancer-related fields.

Quantification of Irinotecan in Single Spheroids Using Internal Standards by MALDI Mass Spectrometry Imaging

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been used to visualize molecular distributions in various biological samples. While it has succeeded in localizing molecules ranging from metabolites to peptides, quantitative MSI (qMSI) has remained challenging, especially in small biological samples like spheroids. Spheroids are a three-dimensional cellular model system that replicate the chemical microenvironments of tumors. This cellular model has played an important role in evaluating the penetration of drugs to better understand the efficacy of clinical chemotherapy. Therefore, we aim to optimize a method to quantify the distribution of therapeutics in a single spheroid using MALDI-MSI. Studies were performed with the therapeutic irinotecan (IR). The calibration curve showed a linear relationship with a limit of detection (LOD) of 0.058 ng/mm2 and R2 value at 0.9643. Spheroids treated with IR for different lengths of time were imaged using the optimized method to quantify the drug concentration during the penetration process. With a dosing concentration of 20.6 μM, the concentration of IR at 48 h of treatment was 16.90 μM within a single spheroid. Furthermore, spheroids were divided into different layers by spatial segmentation to be quantified separately. This MALDI-qMSI method is amenable to a wide range of drugs as well as their metabolites. The quantification results show great potential to extend this method to other small biological samples such as organoids for patient derived therapies.

MALDI mass Spectrometry based proteomics for drug discovery & development

Matrix-assisted laser desorption/ ionization (MALDI) is a soft ionization technique for introducing wide range of analytes into a mass spectrometer (MS). MALDI MS is a powerful tool in drug discovery research and development, providing a high-throughput molecular analysis technique in both preclinical and clinical systems. In particular, MALDI MS is invaluable in the study of peptides and proteins that drive all biological functions. This technology is label-free, provides high specificity in molecular identification, and is high-throughput. MALDI MS has been used in biomarker discovery and quantitation in virtually all tissues, serum, plasma, CSF, and urine for diagnostics, patient stratification, and monitoring drug efficacy. Other applications include characterization of biological drugs, spatial mapping of biomarkers and drugs in tissues, drug screening, and toxicological assessment.

A Hybrid Nanofiber/Paper Cell Culture Platform for Building a 3D Blood-brain Barrier Model

The blood brain barrier (BBB) protects the central nervous system from toxins and pathogens in the blood by regulating permeation of molecules through the barrier interface. In vitro BBB models described to date reproduce some aspects of BBB functionality, but also suffer from incomplete phenotypic expression of brain endothelial traits, difficulty in reproducibility and fabrication, or overall cost. To address these limitations, we describe a three-dimensional (3D) BBB model based on a hybrid paper/nanofiber scaffold. The cell culture platform utilizes lens paper as a framework to accommodate 3D culture of astrocytes. An electrospun nanofiber layer is coated onto one face of the paper to mimic the basement membrane and support growth of an organized two-dimensional layer of endothelial cells (ECs). Human induced pluripotent stem cell-derived ECs and astrocytes are co-cultured to develop a human BBB model. Morphological and spatial organization of model are validated with confocal microscopy. Measurements of transendothelial resistance and permeability demonstrate the BBB model develops a high-quality barrier and responds to hyperosmolar treatments. RNA-sequencing shows introduction of astrocytes both regulates EC tight junction proteins and improves endothelial phenotypes related to vasculogenesis. This model shows promise as a model platform for future in vitro studies of the BBB.

MS imaging of multicellular tumor spheroids and organoids as an emerging tool for personalized medicine and drug discovery

MS imaging (MSI) is a powerful tool in drug discovery because of its ability to interrogate a wide range of endogenous and exogenous molecules in a broad variety of samples. The impressive versatility of the approach, where almost any ionizable biomolecule can be analyzed, including peptides, proteins, lipids, carbohydrates, and nucleic acids, has been applied to numerous types of complex biological samples. While originally demonstrated with harvested organs from animal models and biopsies from humans, these models are time consuming and expensive, which makes it necessary to extend the approach to 3D cell culture systems. These systems, which include spheroid models, prepared from immortalized cell lines, and organoid cultures, grown from patient biopsies, can provide insight on the intersection of molecular information on a spatial scale. In particular, the investigation of drug compounds, their metabolism, and the subsequent distribution of their metabolites in 3D cell culture systems by MSI has been a promising area of study. This review summarizes the different ionization methods, sample preparation steps, and data analysis methods of MSI and focuses on several of the latest applications of MALDI-MSI for drug studies in spheroids and organoids. Finally, the application of this approach in patient-derived organoids to evaluate personalized medicine options is discussed.

Simultaneous and sensitive detection of multiple small biological molecules by microfluidic paper-based analytical device integrated with zinc oxide nanorods

In this work, ZnO nanorods (ZnO NRs) with different sizes were hydrothermally grown on the surface of Whatman filter paper for the fabrication of a microfluidic paper-based device (μPAD) for the simultaneous detection of glucose and uric acid. As dual enzymatic reaction was employed for the colorimetric detection in this μPAD, the presence of ZnO NRs promoted the enzyme immobilization thus significantly enhancing the colorimetric signal. The coffee ring effect was effectively conquered by the uniform distribution of ZnO NR as well as a specialized double-layered μPAD design. Meanwhile, two color indicators with distinct colors were used to provide complementary results to better quantify the concentration of the analytes by naked eye. As a result, two linear calibration curves were obtained for the detection of glucose (0.01-10 mmol L^-1) and uric acid (0.01-5 mmol L^-1), along with a LOD of 3 μmol L^-1 for glucose and 4 μmol L^-1 for uric acid, respectively. The practical usefulness of the proposed μPAD was further validated by the simultaneous analysis of glucose and uric acid in serum samples and urine samples.

Fast Nanoliter-Scale Cell Assays Using Droplet Microarray-Mass Spectrometry Imaging

In pharmaceutical research and development, cell-based assays are primarily used with readout that rely on fluorescence-based and other label-dependent techniques for analysis of different cellular processes. Superhydrophobic-hydrophilic droplet microarrays (DMA) and matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) have recently emerged as key technologies for miniaturized high-throughput cell assays and for label-free molecular high-content drug profiling, respectively. Here, nanoliter-scale cell assays are integrated on DMAs with MALDI-MS imaging (MALDI-MSI) approaches to a droplet microarray-mass spectrometry imaging (DMA-MSI) platform. Using A549 lung cancer cells, concentration-response profiling of a pharmaceutical compound, the fatty acid synthase inhibitor GSK2194069, are demonstrated. Direct cell culture on DMAs enables combination of microscopy and high speed, high molecular content analysis using MALDI-MSI. Miniaturization of array spots down to 0.5 mm confining 40 nL droplets allows for MALDI imaging analysis of as few as ten cells per spot. Partial automation ensures a fast sample preparation workflow. Taken together, the integrated DMA-MSI platform that combines MALDI-MSI, as a label-free analytical readout, with the miniaturized droplet microarray platform is a valuable complement to high throughput cell-based assays technologies.

A versatile deep learning architecture for classification and label-free prediction of hyperspectral images

Hyperspectral imaging is a technique that provides rich chemical or compositional information not regularly available to traditional imaging modalities such as intensity imaging or color imaging based on the reflection, transmission, or emission of light. Analysis of hyperspectral imaging often relies on machine learning methods to extract information. Here, we present a new flexible architecture, the U-within-U-Net, that can perform classification, segmentation, and prediction of orthogonal imaging modalities on a variety of hyperspectral imaging techniques. Specifically, we demonstrate feature segmentation and classification on the Indian Pines hyperspectral dataset and simultaneous location prediction of multiple drugs in mass spectrometry imaging of rat liver tissue. We further demonstrate label-free fluorescence image prediction from hyperspectral stimulated Raman scattering microscopy images. The applicability of the U-within-U-Net architecture on diverse datasets with widely varying input and output dimensions and data sources suggest that it has great potential in advancing the use of hyperspectral imaging across many different application areas ranging from remote sensing, to medical imaging, to microscopy.

Integrated paper-based 3D platform for long-term cell culture and in situ cell viability monitoring of Alzheimer's disease cell model

Reactive oxygen species including superoxide anion, hydrogen peroxide (H₂O₂) and hydroxyl radicals, as a conflicting class of biological metabolites in living organism, act crucial effect on Alzheimer's disease (AD). In this work, a facile integrated platform composed of a paper-based three-dimension (3D) cell culture system and an electrochemical sensor was developed for the construction of AD cell model in third dimensional structure and in situ cell viability monitoring by H₂O₂ released from PC12 cells cultured on paper scaffold were divided into three groups containing control group, amyloid beta peptide 25-35 (Aβ_25-35) group and Aβ_25-35+curcumin (Aβ_25-35+cur) group, respectively. In addition, the paper-based 3D platform displayed excellent properties, such as sensitivity, selectivity, reproducibility and stability. The levels of H₂O₂ expressed in PC12 cells of the three groups were monitored through a paper-based 3D platform. The viability of cells cultured on the 96-well plate was measured by 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (MTT) assay. Results of this paper-based platform are consistent with those of MTT, both displaying improved cell viability and decreased H₂O₂ production in Aβ_25-35+cur group compared to Aβ_25-35 group, which indicates that curcumin has effective cytoprotection. The paper-based 3D platform provides a convenient, economic and universal platform for in situ cell activity monitoring by key small molecules released from living cells.

Considerations for MALDI-Based Quantitative Mass Spectrometry Imaging Studies

Significant advances in mass spectrometry imaging (MSI) have pushed the boundaries in obtaining spatial information and quantification in biological samples. Quantitative MSI (qMSI) has typically been challenging to achieve because of matrix and tissue heterogeneity, inefficient analyte extraction, and ion suppression effects, but recent studies have demonstrated approaches to obtain highly robust methods and reproducible results. In this perspective, we share our insights into sample preparation, how the choice of matrix influences sensitivity, construction of calibration curves, signal normalization, and visualization of MSI data. We hope that by articulating these guidelines that qMSI can be routinely conducted while retaining the analytical merits of other mass spectrometry modalities.