In matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) experimentation, dried-drop analyses are valuable for their ease of preparation and the generation of efficient results. They hold value in their ability to assess the ionizability of an analyte or determine whether it will fragment when subjected to the MALDI laser. However, this technique can be limited by the "coffee ring effect", producing heterogeneity in dried drops with "sweet spots" (areas of concentrated analyte) and "dead zones" (areas with little to no analyte). The coffee ring forms when the analyte concentrates on the edge of the MALDI spot, which leads to difficulty in finding consistent signals from a sample. We demonstrate that sequentially spotting dried drops at halved and quartered pipet solution levels reduces the spot diameter and crucially enhances the signal intensity. With this technique, these concentrated areas are less prevalent and there are fewer dead zones across the droplet. This study has its limitations in sample size; therefore, further investigations will be necessary. Although it increases the sample preparation time, sequential spotting makes the MS process more robust, reducing dead zones and obtaining higher signals in this proof-of-concept study.

Spatial context is becoming increasingly important in the omics disciplines. Spatial proteomics is a diverse field encompassing numerous techniques that provide both the location and identity of proteins in biological samples. Improving upon bulk analyses, spatial proteomics can map peptides and intact proteins within tissue. This review focuses on the application of matrix-assisted laser desorption/ionization (MALDI) in spatial proteomics. Approaches are grouped into two general categories and discussed: protein MALDI MSI and MSI-guided spatial proteomics. A discussion of the workflow for each method is presented, and challenges to each approach are discussed. Recent and technically interesting cases in the literature are presented for each category. This review aims to guide researchers interested in MALDI protein imaging through the strengths, weaknesses, and technical considerations of the many workflows available to them.

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a transformative molecular imaging technology capable of mapping diverse chemical classes, from small metabolites, neurotransmitters and lipids to N-glycans and proteins, at cellular resolution. The field has rapidly matured, offering a range of mass analysers, including axial time-of-flight, quadrupole (or orthogonal) time-of-flight, and high-resolution Orbitrap and Fourier-transform ion cyclotron resonance systems, each with distinct characteristics in terms of spatial resolution, chemical specificity and throughput. In practice, MALDI IMS involves applying a light-absorbing chemical matrix onto a tissue section, followed by automated laser irradiation at discrete coordinates (like pixels) to desorb and ionize endogenous molecules for mass analysis. This label-free approach preserves spatial context, providing a molecular map that links highly multiplexed molecular distributions to distinct anatomical regions, functional tissue units and cell types in situ. This Primer includes an overview of basic imaging MALDI IMS concepts, instrumentation, data processing approaches and advanced applications. We also address key challenges and considerations, with an eye towards optimizing instrumentation and methods to overcome issues in spatial resolution, sensitivity and specificity. Finally, we look towards the future of the technology, including its integration with other spatial omics modalities and its potential as a tool for precision medicine. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a label-free molecular imaging approach mapping diverse biomolecules at cellular resolution. In this Primer, Spraggins et al. outline MALDI IMS concepts, instrumentation, data processing and integration with spatial omics and medicine.

The advancements made in the mass spectrometry imaging (MSI) field have allowed for the generation of very large-scale data sets. These data are often interrogated by machine learning (ML), although storing and handling data sets of this size can be difficult. To aid impacted researchers, we seek to evaluate feature reduction strategies that will minimize the amount of data stored while still maintaining the ability to correctly classify the data. Two different feature selection strategies are tested on six different data sets, leveraging XGBoost as the machine learning algorithm. The study provides evidence that selecting features based on the greatest average abundance across all samples is best suited to scale down the feature set at a more modest trimming level, while selecting features based on statistical analysis via a Student’s t-test is better suited for a more aggressive trimming level. These trends were present regardless of training set size or cross-validation strategy. The results from this work provide insight into when these feature filtering steps can be used effectively and when another data reduction strategy, including not restricting the data set, should be considered.

Lynch syndrome, historically known as hereditary nonpolyposis colorectal cancer, is caused by germline mutations in the DNA mismatch repair (MMR) genes, MLH1, MSH2 (EPCAM), MSH6, and PMS2. While the genetic changes associated with Lynch Syndrome have previously been characterized, there have not been studies of the associated proteomic alterations, in part because of the limited availability of primary samples and the absence of in vitro model systems. In this study, the first large-scale tissue proteomic assessment of Lynch Syndrome samples as well as three other subtypes of colorectal cancer was completed with specimens from the Ohio Colorectal Cancer Prevention Initiative. The cohort contained three groups of microsatellite unstable (MSI-high) CRC patients (Lynch syndrome, double somatic MMR mutation, and MLH1 hypermethylation) and a group of microsatellite stable (MSS) CRC patients. A total of 122 tumor and complimentary normal mucosa samples from 61 patients were evaluated using label-free bottom-up proteomic analysis. Hierarchical clustering analysis of the global proteome showed that the MSS group was significantly different than the three MSI-high groups. Of the 1,084 proteins found to be dysregulated across all four colorectal cancer subtypes, there were age at diagnosis associated shifts in proteins correlated with tumor proliferation and immune regulation for the Lynch syndrome and Double Somatic samples. The proteins TPD52, GMDS, and DSP showed increased protein abundance correlated with older age at diagnosis. In addition, the Lynch syndrome samples showed substantial sex-based differences in immune and inflammatory pathways, for example, downregulation of ZG16, DIS3, and WDR43. This study fills a critical gap as the first proteomic characterization of Lynch syndrome samples to date. Data are available via ProteomeXchange with identifier PXD073693.

INTRODUCTION:Ovarian cancer is the most lethal gynecologic malignancy and has seen little progress in early detection and treatment. Mass spectrometry-based proteomics is a powerful technique that can be used to understand tumor biology and identify novel biomarkers that could transform diagnosis, prognosis, and treatment. AREAS COVERED:This review highlights recent applications of proteomics in ovarian cancer research. Tissue studies have defined histotype-specific pathways and spatial proteomics focuses on intratumoral heterogeneity. Biofluid studies are growing with exciting potential for minimally invasive diagnostics. Post-translational modification profiling has explored signaling alterations and mechanisms of resistance. Proteogenomic integration has improved tumor classification, revealing protein-level alterations and regulatory mechanisms not captured by genomics. Literature was drawn mostly from studies of the past five years, with emphasis on translational applications. EXPERT OPINION:Proteomics has developed into a tool capable of providing clinically relevant, valuable insight. However, translation will depend on validation and standardization. Continued integration with other omics is critical for moving discoveries from the laboratory to the clinic. Importantly, there is an unmet need for proteomic analysis of less common subtypes, as seen by the bias of this review toward HGSOC.

Colorectal cancer (CRC) development is closely associated with the accumulation of both genetic and epigenetic alterations. Many efforts have been made to investigate the role of epigenetic modifications in CRC metastasis. In this work, we present the quantitative top-down proteomics study focusing on histone proteoforms between metastatic (SW620) and nonmetastatic (SW480) CRC cells to reveal potentially critical histone proteoforms in CRC metastasis. We isolated histone proteins from CRC cells, fractionated them by sodium dodecyl-sulfate (SDS)-polyacrylamide gel electrophoresis (PAGE), and analyzed them by capillary zone electrophoresis (CZE)-tandem mass spectrometry (MS/MS). A total of 230 histone proteoforms were quantified in SW480 and SW620 cell lines, among which 34 proteoforms were significantly altered in abundance in the metastatic cells, indicating a significant transformation of histone proteoforms during metastasis. We observed a significant increase in abundance of all nine differentially expressed histone H4 proteoforms in metastatic SW620 cells compared to SW480 cells, while differentially expressed proteoforms of other histone proteins display diversified expression patterns. Additionally, two histone H2A proteoforms with a combination of N-terminal acetylation and phosphorylation were upregulated in the metastatic CRC cells. These differentially expressed histone proteoforms could be novel proteoform biomarkers of CRC metastasis.

The lipidome, encompassing the comprehensive lipid fingerprint of a biological system, includes thousands of unique isomeric and isobaric lipid species. Mass spectrometry (MS) is an effective technique for characterizing the lipidome, although the resolution of isomeric lipid species through MS typically requires specialized or modified equipment. In this study, we introduce a novel matrix derivatization technique that leverages the unique photoreactive properties of unsaturated lipids to reveal the double-bond location in conventional matrix-assisted laser desorption-ionization mass spectrometry (MALDI-MS) experiments. The principle mechanistic framework of this technique is type II photosensitization, where the MALDI matrix norharmane acts as an organic photosensitizer to generate singlet oxygen upon light exposure. The singlet oxygen then reacts with unsaturated lipid species, forming hydroperoxide derivatives at acyl group carbon double bonds, facilitating their identification. The labile nature of these hydroperoxide-functionalized lipids allows for further decomposition under normal MALDI laser exposure, enhancing the analytical resolution of isomeric lipids without additional experiments. With this approach, we were able to distinguish the 18:1 (Δ6-cis) and 18:1 (Δ9-cis) PC lipid isomers. We also demonstrated that the approach works in an imaging context, mapping lipid species in both mouse tissue and 3D cell cultures.

The use of cell culture techniques to model human disease is an indispensable tool that has helped improve the health and well-being of the world. Monolayer cultures have most often been used for biomedical research, although not accurately recapitulating an in vivo human tumor. Tumor spheroids are a form of three-dimensional cell culture that better mimics an avascularized human tumor through their cell-cell contacts in all directions, development of various chemical gradients, and distinct populations of cells found within the spheroid. In this review, we highlight how mass spectrometry has propelled the utility of the spheroid model to understand cancer biology. We discuss how mass spectrometry imaging can be utilized to determine the penetration efficiency of various chemotherapeutics, how proteomics can be used to understand the biology in the various layers of a spheroid, and how metabolomics and lipidomics are used to elucidate how various spheroids behave toward chemotherapeutics.

The FDA Modernization Act 2.0 permits data from advanced microphysiological systems, such as spheroids, to be used as a testbed for drug candidates entering phase 1 clinical trials. Despite their increasing adoption, spheroids of varying growth durations are often used interchangeably as disease models. While transcriptomic studies have been employed to monitor spheroids over time, proteomics has primarily been used to validate their utility as model systems and assess drug responses rather than for longitudinal studies. Here, we apply data independent acquisition with gas phase fractionation (DIA-GPF) proteomics to investigate temporal changes in HCT 116 spheroids every 2 days throughout 18 days of growth, identifying 6,835 proteins across all samples. Differential expression analysis reveals that day 2 spheroids more closely resemble monolayer cells than spheroids cultured for extended periods. Gene ontology (GO) term analysis of differentially expressed proteins indicates that relative to monolayer cells DNA replication is downregulated, while glycolysis is upregulated during spheroid maturation. Parallel reaction monitoring (PRM) experiments targeting thymidylate synthase and fructose-bisphosphate aldolase C validate the initial proteomic findings and corroborate the trends observed in the GO term analysis. These results highlight the importance of growth duration when spheroids are used as a model for avascular tumors.

Polo-like kinase 1 (Plk1) is a serine/threonine kinase involved in regulating the cell cycle. It is activated by aurora kinase B along with the cofactors Borealin, INCE, and survivin. Plk1 is involved in the development of resistances to chemotherapeutics such as doxorubicin, Taxol, and gemcitabine. It has been shown that patients with higher levels of Plk1 have lower survival rates. Onvansertib is a competitive ATP inhibitor for Plk1 in clinical trials for the treatment of tumors and has recently entered a trial for the treatment of KRAS mutant colorectal cancers (CRCs). In this study, we conducted an untargeted liquid chromatography-mass spectrometry (LC-MS) proteomics study as well as an untargeted lipidomics analysis of HCT 116 spheroids treated with onvansertib over a 72-h treatment time-course experiment. Mass spectrometry imaging (MSI) showed that onvansertib begins to accumulate most prominently after 12 h of treatment and continues to accumulate through 72 h. Proteomic results displayed alterations to cell cycle control proteins and an increasing abundance of aurora kinase B and Borealin. The proteomics data also showed alterations to many lipid metabolism enzymes. The MSI lipidomics data indicated alterations to phosphatidylcholine lipids, with many lipids increasing in abundance over time or increasing until 12 h of onvansertib treatment and decreasing after that time point. In summary, these results suggest that onvansertib is causing cells within the spheroid to halt at a certain phase of the cell cycle in accordance with previous literature. Our findings suggest the S phase is likely interrupted, with observed alterations in cell cycle control proteins and PC lipid abundance.

Microphysiological systems, such as multicellular spheroids, hold great promise for drug screening experiments. Spheroids may be dosed statically, where the drug is introduced to the growing chamber at one time point, or dynamically, where the drug is introduced via a fluidic component. Dynamic dosing can generate pharmacokinetic curves that more closely represent those seen in vivo than static dosing. In this work, we demonstrate the dynamic dosing of colorectal cancer spheroids in a 3D printed fluidic device with liposomal doxorubicin. Spheroids are valuable models to evaluate dynamic dosing, as they recapitulate the nutrient, oxygen, and pH gradients of solid tumors. Spheroids feature distinct cellular populations with a necrotic core, quiescent middle layer, and proliferative outer layer. Drug and liposome penetration are tracked with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) and fluorescence imaging, showing that liposomal doxorubicin is stable to fluidic dosing and penetrates spheroids after 48 h. To provide a comprehensive pharmacodynamic profile of the distinct cellular regions within spheroids, we employ spatially stable isotopic labeling by amino acids in cell culture (spatial SILAC) proteomics to isotopically label the core and outer layers. Proteomic analysis reveals 714 upregulated proteins in the core upon treatment and 30 in the outer layers, as well as 103 downregulated proteins in the core and 1276 in the outer layers. Spatial SILAC uncovers the differential regulation of proteins associated with glycolysis, the TCA cycle, and lipid synthesis upon drug treatment between the spheroid core and outer layers. Using MALDI MSI and spatial SILAC proteomics, we interrogate the effects of dynamic dosing with liposomal doxorubicin on spheroid regions that would be overlooked by bulk analysis.

In this study, we evaluate lipids and select proteins in human lung fibroblasts (hLFs) to interrogate changes occurring due to aging and senescence. To study single cell populations, a comparison of cells adhered onto slides using poly-d-lysine versus centrifugal force deposition was first analyzed to determine whether specific alterations were observed between preparations. The poly-d-lysine approach was then utilized to interrogate the lipidome of the cell populations and further evaluate potential applications of the MALDI-immunohistochemistry (IHC) platform for single-cell-level analyses. Two protein markers of senescence, vimentin and p21, were both observed within the fibroblast populations and quantified. Lipidomic analysis of the fibroblasts found 12 lipids significantly altered because of replicative senescence, including fatty acids, such as stearic acid, and ceramide phosphoethanolamine species (CerPE). Similar to previous reports, alterations were detected in putative fatty acid building blocks, ceramides, among other lipid species. Altogether, our results reveal the ability to detect lipids implicated in senescence and show alterations to protein expression between normal and senescent fibroblast populations, including differences between young and aged cells. This report is the first time that the MALDI-IHC system has been utilized at a single-cell level to analyze both protein expression and lipid profiles in cultured cells, with a particular focus on changes associated with aging and senescence.

Targeted therapy to the tumor would greatly advance precision medicine. Many drug delivery vehicles have emerged, but liposomes are cited as the most successful to date. Recent efforts to develop liposomal drug delivery systems focus on drug distribution in tissues and ignore liposomal fate. In this study, we developed a novel method to elucidate both drug and liposomal bilayer distribution in a three-dimensional cell culture model using quantitative matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI qMSI) alongside fluorescence microscopy. Imaging liposomal distribution in a cell culture model is challenging, as lipids forming the bilayer are endogenous to the model system. To resolve this issue, we functionalized the bilayer by chemically cross-linking a fluorescent tag to the alkyne-containing lipid hexynoyl phosphoethanolamine (HPE). We synthesized liposomes incorporating the tagged HPE lipid and encapsulated within them doxorubicin, yielding a theranostic liposome capable of both drug delivery and monitoring liposomal uptake. We employed an "in-tissue" MALDI qMSI approach to generate a calibration curve with R2 = 0.9687, allowing for quantification of doxorubicin within spheroid sections at multiple time points. After 72 h of treatment with the theranostic liposomes, full doxorubicin penetration was observed. The metabolites doxorubicinone and 7-deoxydoxorubicinone were also detected after 48 h. Modification of the bilayer allowed for fluorescence microscopy tracking of liposomes, while MALDI MSI simultaneously permitted the imaging of drugs and metabolites. While we demonstrated the utility of our method with doxorubicin, this system could be applied to examine the uptake, release, and metabolism of many other liposome-encapsulated drugs.

Three-dimensional (3D) organoids have been at the forefront of regenerative medicine and cancer biology fields for the past decade. However, the fragile nature of organoids makes their spatial analysis challenging due to their budding structures and composition of single layer of cells. The standard sample preparation approaches can collapse the organoid morphology. Therefore, in this study, we evaluated several approaches to optimize a method compatible with both mass spectrometry imaging (MSI) and immunohistological techniques. Murine intestinal organoids were used to evaluate embedding in gelatin, carboxymethylcellulose (CMC)-gelatin-CMC-sucrose, or hydroxypropyl methylcellulose (HPMC) and polyvinylpyrrolidone (PVP) solutions. Organoids were assessed with and without aldehyde fixation and analyzed for lipid distributions by MSI coupled with hematoxylin and eosin (H&E) staining and immunofluorescence (IF) in consecutive sections from the same sample. While chemical fixation preserves morphology for better histological outcomes, it can lead to suppression of the matrix-assisted laser desorption/ionization (MALDI) lipid signal. By contrast, leaving organoid samples unfixed enhanced MALDI lipid signal. The method that performed best for both MALDI and histological analysis was embedding unfixed samples in HPMC and PVP. This approach allowed assessment of cell proliferation by Ki67 while also identifying putative phosphatidylethanolamine (PE(18:0/18:1)), which was confirmed further by tandem MS approaches. Overall, these protocols will be amenable to multiplexing imaging mass spectrometry analysis with several histological assessments and help advance our understanding of the biological processes that take place in district subsets of cells in budding organoid structures.

Colorectal cancer (CRC) contains considerable heterogeneity; therefore, models of the disease must also reflect the multifarious components. Compared to traditional 2D models, 3D cellular models, such as tumor spheroids, have the utility to determine the drug efficacy of potential therapeutics. Monoculture spheroids are well-known to recapitulate gene expression, cell signaling, and pathophysiological gradients of avascularized tumors. However, they fail to mimic the stromal cell influence present in CRC, which is known to perturb drug efficacy and is associated with metastatic, late-stage colorectal cancer. This study seeks to develop a cocultured spheroid model using carcinoma and noncancerous fibroblast cells. We characterized the proteomic profile of cocultured spheroids in comparison to monocultured spheroids using data-independent acquisition with gas-phase fractionation. Specifically, we determined that proteomic differences related to translation and mTOR signaling are significantly increased in cocultured spheroids compared to monocultured spheroids. Proteins related to fibroblast function, such as exocytosis of coated vesicles and secretion of growth factors, were significantly differentially expressed in the cocultured spheroids. Finally, we compared the proteomic profiles of both the monocultured and cocultured spheroids against a publicly available data set derived from solid CRC tumors. We found that the proteome of the cocultured spheroids more closely resembles that of the patient samples, indicating their potential as tumor mimics.

Synthetic polymeric nanoparticles (NPs) have been proven to be essential drug delivery systems and cancer therapy tools. However, NPs derived from traditional linear polymers often fail to provide the stability, biocompatibility, and loading efficiencies needed for clinical application. The present work explores strategically designed amino acid-based NPs formed from self-assembling amphiphilic Y and H-shaped polymers consisting of a tryptophan-based hydrophobic segment coupled to a hydrophilic block of polyethylene glycol (PEG). This study employs tryptophan due to its natural availability and abilities as a cancer immunotherapeutic agent. These amphiphilic polymers (SM_Trp2P and SM_Trp4P) were synthesized via a combination of Steglich esterification and "click" chemistry (azide-alkyne cycloaddition). Their resulting NPs were characterized using electron microscopy and dynamic light scattering (DLS), by which the morphologies of the NPs were confirmed. Spherical NPs possessing a tryptophan core enabled the loading of hydrophobic cargo, such as drug molecules and near-infrared dyes, demonstrating the potential for dual imaging and delivery applications. Cytotoxicity and spectroscopic analysis of the NPs supported comparative studies between the two polymers and the biological relevancy of the nanomaterials. Employing matrix-assisted laser desorption/ionization-imaging mass spectrometry (MALDI-MSI), full penetration and metabolism of irinotecan-loaded NPs were observed in three-dimensional cell cultures. Results indicate that these strategically designed polymer frameworks and their resulting NPs are exceptional candidates for biomedical applications.

Mass spectrometry imaging (MSI) has become increasingly utilized in the analysis of biological molecules. MSI grants the ability to spatially map thousands of molecules within one experimental run in a label-free manner. While MSI is considered by most to be a qualitative method, recent advancements in instrumentation, sample preparation, and development of standards has made quantitative MSI (qMSI) more common. In this feature article, we present a tailored review of recent advancements in qMSI of therapeutics and biomolecules such as lipids and peptides/proteins. We also provide detailed experimental considerations for conducting qMSI studies on biological samples, aiming to advance the methodology. In this feature article, we discuss quantitative mass spectrometry imaging of therapeutics and biomolecules conducted by recent studies for matrix-assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI) techniques.

Colorectal cancer (CRC) is projected to become the third most diagnosed and third most fatal cancer in the United States by 2024, with early onset CRC on the rise. Research is constantly underway to discover novel therapeutics for the treatment of various cancers to improve patient outcomes and survival. Fatty acid synthase (FAS) has become a druggable target of interest for the treatment of many different cancers. One such inhibitor, TVB-2640, has gained popularity for its high specificity for FAS and has entered a phase 1 clinical trial for the treatment of solid tumors. However, the distinct molecular differences that occur upon inhibition of FAS have yet to be understood. Here, we conduct proteomics and phosphoproteomics analyses on HCT 116 and HT-29 CRC spheroids inhibited with either a generation 1 (cerulenin) or generation 2 (TVB-2640) FAS inhibitor. Proteins involved in lipid metabolism and cellular respiration were altered in abundance. It was also observed that proteins involved in ferroptosis─an iron mediated form of cell death─were altered. These results show that HT-29 spheroids exposed to cerulenin or TVB-2640 are undergoing a ferroptotic death mechanism. The data were deposited to the ProteomeXchange Consortium via the PRIDE repository with the identifier PXD050987.

<p>Supplementary Figure S1 PDF file - 1274K, Schematic presentation of the workflow of experiments and analytical procedures</p>