Mass Spectrometry Imaging of the Subchondral Bone in Osteoarthritis Reveals Tissue Remodeling of Extracellular Matrix Proteins that Precede Cartilage Loss.

Osteoarthritis (OA) of the knee is a degenerative condition of the skeletal extracellular matrix (ECM) marked by the loss of articular cartilage and subchondral bone homeostasis. Treatments for OA in the knee beyond full joint replacement are lacking primarily due to gaps in molecular knowledge of the biological drivers of disease. Here, Mass Spectrometry Imaging (MSI) enabled molecular spatial mapping of the proteomic landscape of human knee tissues. Histologic sections of human tibial plateaus from OA patients and cadaveric controls were treated with collagenase III to target ECM proteins prior to imaging using a timsTOF fleX mass spectrometer (Bruker) for matrix-assisted laser desorption ionization (MALDI)-MSI of bone and cartilage proteins in human knees. Spatial MSI data of the knee, using sections of the tibial plateau from non-arthritic, cadaveric donors or from knee replacement patients with medial OA were processed and automatically segmented identifying distinct areas of joint damage. ECM peptide markers compared either OA to cadaveric tissues or OA medial to OA lateral. Not only did candidate peptides distinguish OA relative to intact cartilage, but also emphasized a significant spatial difference between OA and intact subchondral bone (AUROC >0.85). Overall, 31 peptide candidates from ECM proteins, including COL1A1, COL3A1, and unanticipated detection of collagens COL6A1 and COL6A3 in adult bone, exhibited significantly elevated abundance in diseased tissue. Highly specific hydroxyproline-containing collagens dominated OA subchondral bone directly under regions of lost cartilage revealing dramatic tissue remodeling providing molecular details on the progression of joint degeneration in OA. The identification of specific spatial markers for the progression of subchondral bone degeneration in OA advances our molecular understanding of coupled deterioration of joint tissues.

The glycosylation landscape of prostate cancer tissues and biofluids.

An overview of the role of glycosylation in prostate cancer (PCa) development and progression is presented, focusing on recent advancements in defining the N-glycome through glycomic profiling and glycoproteomic methodologies. Glycosylation is a common post-translational modification typified by oligosaccharides attached N-linked to asparagine or O-linked to serine or threonine on carrier proteins. These attached sugars have crucial roles in protein folding and cellular recognition processes, such that altered glycosylation is a hallmark of cancer pathogenesis and progression. In the past decade, advancements in N-glycan profiling workflows using Matrix Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) technology have been applied to define the spatial distribution of glycans in PCa tissues. Multiple studies applying N-glycan MALDI-MSI to pathology-defined PCa tissues have identified significant alterations in N-glycan profiles associated with PCa progression. N-glycan compositions progressively increase in number, and structural complexity due to increased fucosylation and sialylation. Additionally, significant progress has been made in defining the glycan and glycopeptide compositions of prostatic-derived glycoproteins like prostate-specific antigen in tissues and biofluids. The glycosyltransferases involved in these changes are potential drug targets for PCa, and new approaches in this area are summarized. These advancements will be discussed in the context of the further development of clinical diagnostics and therapeutics targeting glycans and glycoproteins associated with PCa progression. Integration of large scale spatial glycomic data for PCa with other spatial-omic methodologies is now feasible at the tissue and single-cell levels.

The Spatial Extracellular Proteomic Tumor Microenvironment Distinguishes Molecular Subtypes of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) mortality rates continue to increase faster than those of other cancer types due to high heterogeneity, which limits diagnosis and treatment. Pathological and molecular subtyping have identified that HCC tumors with poor outcomes are characterized by intratumoral collagenous accumulation. However, the translational and post-translational regulation of tumor collagen, which is critical to the outcome, remains largely unknown. Here, we investigate the spatial extracellular proteome to understand the differences associated with HCC tumors defined by Hoshida transcriptomic subtypes of poor outcome (Subtype 1; S1; n = 12) and better outcome (Subtype 3; S3; n = 24) that show differential stroma-regulated pathways. Collagen-targeted mass spectrometry imaging (MSI) with the same-tissue reference libraries, built from untargeted and targeted LC-MS/MS was used to spatially define the extracellular microenvironment from clinically-characterized, formalin-fixed, paraffin-embedded tissue sections. Collagen α-1(I) chain domains for discoidin-domain receptor and integrin binding showed distinctive spatial distribution within the tumor microenvironment. Hydroxylated proline (HYP)-containing peptides from the triple helical regions of fibrillar collagens distinguished S1 from S3 tumors. Exploratory machine learning on multiple peptides extracted from the tumor regions could distinguish S1 and S3 tumors (with an area under the receiver operating curve of ≥0.98; 95% confidence intervals between 0.976 and 1.00; and accuracies above 94%). An overall finding was that the extracellular microenvironment has a high potential to predict clinically relevant outcomes in HCC.

A highly potent bi-thiazole inhibitor of LOX rewires collagen architecture and enhances chemoresponse in triple-negative breast cancer.

Lysyl oxidase (LOX) is upregulated in highly stiff aggressive tumors, correlating with metastasis, resistance, and worse survival; however, there are currently no potent, safe, and orally bioavailable small molecule LOX inhibitors to treat these aggressive desmoplastic solid tumors in clinics. Here we discovered bi-thiazole derivatives as potent LOX inhibitors by robust screening of drug-like molecules combined with cell/recombinant protein-based assays. Structure-activity relationship analysis identified a potent lead compound (LXG6403) with ∼3.5-fold specificity for LOX compared to LOXL2 while not inhibiting LOXL1 with a competitive, time- and concentration-dependent irreversible mode of inhibition. LXG6403 shows favorable pharmacokinetic properties, globally changes ECM/collagen architecture, and reduces tumor stiffness. This leads to better drug penetration, inhibits FAK signaling, and induces ROS/DNA damage, G1 arrest, and apoptosis in chemoresistant triple-negative breast cancer (TNBC) cell lines, PDX organoids, and in vivo. Overall, our potent and tolerable bi-thiazole LOX inhibitor enhances chemoresponse in TNBC, the deadliest breast cancer subtype.

Extracellular Microenvironment Alterations in Ductal Carcinoma In Situ and Invasive Breast Cancer Pathologies by Multiplexed Spatial Proteomics.

Ductal carcinoma in situ (DCIS) is a heterogeneous breast disease that remains challenging to treat due to its unpredictable progression to invasive breast cancer (IBC). Contemporary literature has become increasingly focused on extracellular matrix (ECM) alterations with breast cancer progression. However, the spatial regulation of the ECM proteome in DCIS has yet to be investigated in relation to IBC. We hypothesized that DCIS and IBC present distinct ECM proteomes that could discriminate between these pathologies. Tissue sections of pure DCIS, mixed DCIS-IBC, or pure IBC (n = 22) with detailed pathological annotations were investigated by multiplexed spatial proteomics. Across tissues, 1,005 ECM peptides were detected in pathologically annotated regions and their surrounding extracellular microenvironments. A comparison of DCIS to IBC pathologies demonstrated 43 significantly altered ECM peptides. Notably, eight fibrillar collagen peptides could distinguish with high specificity and sensitivity between DCIS and IBC. Lesion-targeted proteomic imaging revealed heterogeneity of the ECM proteome surrounding individual DCIS lesions. Multiplexed spatial proteomics reported an invasive cancer field effect, in which DCIS lesions in closer proximity to IBC shared a more similar ECM profile to IBC than distal counterparts. Defining the ECM proteomic microenvironment provides novel molecular insights relating to DCIS and IBC.

Spatial N-glycomics of the normal breast microenvironment reveals fucosylated and high-mannose N-glycan signatures related to BI-RADS density and ancestry.

Higher breast cancer mortality rates continue to disproportionally affect black women (BW) compared to white women (WW). This disparity is largely due to differences in tumor aggressiveness that can be related to distinct ancestry-associated breast tumor microenvironments (TMEs). Yet, characterization of the normal microenvironment (NME) in breast tissue and how they associate with breast cancer risk factors remains unknown. N-glycans, a glucose metabolism-linked post-translational modification, has not been characterized in normal breast tissue. We hypothesized that normal female breast tissue with distinct Breast Imaging and Reporting Data Systems (BI-RADS) categories have unique microenvironments based on N-glycan signatures that varies with genetic ancestries. Profiles of N-glycans were characterized in normal breast tissue from BW (n = 20) and WW (n = 20) at risk for breast cancer using matrix assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI). A total of 176 N-glycans (32 core-fucosylated and 144 noncore-fucosylated) were identified in the NME. We found that certain core-fucosylated, outer-arm fucosylated and high-mannose N-glycan structures had specific intensity patterns and histological distributions in the breast NME dependent on BI-RADS densities and ancestry. Normal breast tissue from BW, and not WW, with heterogeneously dense breast densities followed high-mannose patterns as seen in invasive ductal and lobular carcinomas. Lastly, lifestyles factors (e.g. age, menopausal status, Gail score, BMI, BI-RADS) differentially associated with fucosylated and high-mannose N-glycans based on ancestry. This study aims to decipher the molecular signatures in the breast NME from distinct ancestries towards improving the overall disparities in breast cancer burden.

Molecular analysis of the extracellular microenvironment: from form to function.

The extracellular matrix (ECM) proteome represents an important component of the tissue microenvironment that controls chemical flux and induces cell signaling through encoded structure. The analysis of the ECM represents an analytical challenge through high levels of post-translational modifications, protease-resistant structures, and crosslinked, insoluble proteins. This review provides a comprehensive overview of the analytical challenges involved in addressing the complexities of spatially profiling the extracellular matrix proteome. A synopsis of the process of synthesizing the ECM structure, detailing inherent chemical complexity, is included to present the scope of the analytical challenge. Current chromatographic and spatial techniques addressing these challenges are detailed. Capabilities for multimodal multiplexing with cellular populations are discussed with a perspective on developing a holistic view of disease processes that includes both the cellular and extracellular microenvironment.

Differential Protease Specificity by Collagenase as a Novel Approach to Serum Proteomics That Includes Identification of Extracellular Matrix Proteins without Enrichment.

Circulating extracellular matrix (ECM) proteins are serological biomarkers of interest due to their association with pathologies involving disease processes such as fibrosis and cancers. In this study, we investigate the potential for serum biomarker research using differential protease specificity (DPS), leveraging alternate protease specificity as a targeting mechanism to selectively digest circulating ECM protein serum proteins. A proof-of-concept study is presented using serum from patients with cirrhotic liver or hepatocellular carcinoma. The approach uses collagenase DPS for digestion of deglycosylated serum and liquid-chromatography-trapped ion mobility-tandem mass spectrometry (LC-TIMS-MS/MS) to enhance the detection of ECM proteins in serum. It requires no sample enrichment and minimizes the albumin average precursor intensity readout to less than 1.2%. We further demonstrate the capabilities for using the method as a high-throughput matrix-assisted laser/desorption ionization mass spectrometry (MALDI-MS) assay coupled with reference library searching. A goal is to improve the depth and breadth of biofluid proteomics for noninvasive assays.

SpaceANOVA: Spatial Co-occurrence Analysis of Cell Types in Multiplex Imaging Data Using Point Process and Functional ANOVA.

Multiplex imaging platforms have enabled the identification of the spatial organization of different types of cells in complex tissue or the tumor microenvironment. Exploring the potential variations in the spatial co-occurrence or colocalization of different cell types across distinct tissue or disease classes can provide significant pathological insights, paving the way for intervention strategies. However, the existing methods in this context either rely on stringent statistical assumptions or suffer from a lack of generalizability. We present a highly powerful method to study differential spatial co-occurrence of cell types across multiple tissue or disease groups, based on the theories of the Poisson point process and functional analysis of variance. Notably, the method accommodates multiple images per subject and addresses the problem of missing tissue regions, commonly encountered due to data-collection complexities. We demonstrate the superior statistical power and robustness of the method in comparison with existing approaches through realistic simulation studies. Furthermore, we apply the method to three real data sets on different diseases collected using different imaging platforms. In particular, one of these data sets reveals novel insights into the spatial characteristics of various types of colorectal adenoma.

Spatial Omics Reveals that Cancer-Associated Glycan Changes Occur Early in Liver Disease Development in a Western Diet Mouse Model of MASLD.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a progressive disease and comprises different stages of liver damage; it is significantly associated with obese and overweight patients. Untreated MASLD can progress to life-threatening end-stage conditions, such as cirrhosis and liver cancer. N-Linked glycosylation is one of the most common post-translational modifications in the cell surface and secreted proteins. N-Linked glycan alterations have been established to be signatures of liver diseases. However, the N-linked glycan changes during the progression of MASLD to liver cancer are still unknown. Here, we induced different stages of MASLD in mice and liver-cancer-related phenotypes and elucidated the N-glycome profile during the progression of MASLD by quantitative and qualitative profiling in situ using matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (IMS). Importantly, we identified specific N-glycan structures including fucosylated and highly branched N-linked glycans at very early stages of liver injury (steatosis), which in humans are associated with cancer development, establishing the importance of these modifications with disease progression. Finally, we report that N-linked glycan alterations can be observed in our models by MALDI-IMS before liver injury is identified by histological analysis. Overall, we propose these findings as promising biomarkers for the early diagnosis of liver injury in MASLD.

An N-glycome tissue atlas of 15 human normal and cancer tissue types determined by MALDI-imaging mass spectrometry.

N-glycosylation is an abundant post-translational modification of most cell-surface proteins. N-glycans play a crucial role in cellular functions like protein folding, protein localization, cell-cell signaling, and immune detection. As different tissue types display different N-glycan profiles, changes in N-glycan compositions occur in tissue-specific ways with development of disease, like cancer. However, no comparative atlas resource exists for documenting N-glycome alterations across various human tissue types, particularly comparing normal and cancerous tissues. In order to study a broad range of human tissue N-glycomes, N-glycan targeted MALDI imaging mass spectrometry was applied to custom formalin-fixed paraffin-embedded tissue microarrays. These encompassed fifteen human tissue types including bladder, breast, cervix, colon, esophagus, gastric, kidney, liver, lung, pancreas, prostate, sarcoma, skin, thyroid, and uterus. Each array contained both normal and tumor cores from the same pathology block, selected by a pathologist, allowing more in-depth comparisons of the N-glycome differences between tumor and normal and across tissue types. Using established MALDI-IMS workflows and existing N-glycan databases, the N-glycans present in each tissue core were spatially profiled and peak intensity data compiled for comparative analyses. Further structural information was determined for core fucosylation using endoglycosidase F3, and differentiation of sialic acid linkages through stabilization chemistry. Glycan structural differences across the tissue types were compared for oligomannose levels, branching complexity, presence of bisecting N-acetylglucosamine, fucosylation, and sialylation. Collectively, our research identified the N-glycans that were significantly increased and/or decreased in relative abundance in cancer for each tissue type. This study offers valuable information on a wide scale for both normal and cancerous tissues, serving as a reference for future studies and potential diagnostic applications of MALDI-IMS.

Imaging of N-Linked Glycans in Biological Tissue Sections Using Nanospray Desorption Electrospray Ionization (nano-DESI) Mass Spectrometry.

N-linked glycans are complex biomolecules vital to cellular functions that have been linked to a wide range of pathological conditions. Mass spectrometry imaging (MSI) has been used to study the localization of N-linked glycans in cells and tissues. However, their structural diversity presents a challenge for MSI techniques, which stimulates the development of new approaches. In this study, we demonstrate for the first time spatial mapping of N-linked glycans in biological tissues using nanospray desorption electrospray ionization mass spectrometry imaging (nano-DESI MSI). Nano-DESI MSI is an ambient ionization technique that has been previously used for imaging of metabolites, lipids, and proteins in biological tissue samples without special sample pretreatment. N-linked glycans are released from glycoproteins using an established enzymatic digestion with peptide N-glycosidase F, and their spatial localization is examined using nano-DESI MSI. We demonstrate imaging of N-linked glycans in formalin-fixed paraffin-embedded human hepatocellular carcinoma and human prostate tissues in both positive and negative ionization modes. We examine the localization of 38 N-linked glycans consisting of high mannose, hybrid fucosylated, and sialyated glycans. We demonstrate that negative mode nano-DESI MSI is well-suited for imaging of underivatized sialylated N-linked glycans. On-tissue MS/MS of different adducts of N-linked glycans proves advantageous for elucidation of the glycan sequence. This study demonstrates the applicability of liquid extraction techniques for spatial mapping of N-linked glycans in biological samples, providing an additional tool for glycobiology research.

Evaluation of antibody-based single cell type imaging techniques coupled to multiplexed imaging of N-glycans and collagen peptides by matrix-assisted laser desorption/ionization mass spectrometry imaging.

The integration of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) with single cell spatial omics methods allows for a comprehensive investigation of single cell spatial information and matrisomal N-glycan and extracellular matrix protein imaging. Here, the performance of the antibody-directed single cell workflows coupled with MALDI-MSI are evaluated. Miralys™ photocleavable mass-tagged antibody probes (MALDI-IHC, AmberGen, Inc.), GeoMx DSP® (NanoString, Inc.), and Imaging Mass Cytometry (IMC, Standard BioTools Inc.) were used in series with MALDI-MSI of N-glycans and extracellular matrix peptides on formalin-fixed paraffin-embedded tissues. Single cell omics protocols were performed before and after MALDI-MSI. The data suggests that for each modality combination, there is an optimal order for performing both techniques on the same tissue section. An overall conclusion is that MALDI-MSI studies may be completed on the same tissue section as used for antibody-directed single cell modalities. This work increases access to combined cellular and extracellular information within the tissue microenvironment to enhance research on the pathological origins of disease.

SpaceANOVA: Spatial co-occurrence analysis of cell types in multiplex imaging data using point process and functional ANOVA.

Motivation: Multiplex imaging platforms have enabled the identification of the spatial organization of different types of cells in complex tissue or tumor microenvironment (TME). Exploring the potential variations in the spatial co-occurrence or co-localization of different cell types across distinct tissue or disease classes can provide significant pathological insights, paving the way for intervention strategies. However, the existing methods in this context either rely on stringent statistical assumptions or suffer from a lack of generalizability. Results: We present a highly powerful method to study differential spatial co-occurrence of cell types across multiple tissue or disease groups, based on the theories of the Poisson point process (PPP) and functional analysis of variance (FANOVA). Notably, the method accommodates multiple images per subject and addresses the problem of missing tissue regions, commonly encountered in such a context due to the complex nature of the data-collection procedure. We demonstrate the superior statistical power and robustness of the method in comparison to existing approaches through realistic simulation studies. Furthermore, we apply the method to three real datasets on different diseases collected using different imaging platforms. In particular, one of these datasets reveals novel insights into the spatial characteristics of various types of precursor lesions associated with colorectal cancer. Availability: The associated R package can be found here, https://github.com/sealx017/SpaceANOVA.

Development of an Antibody-Based Platform for the Analysis of Immune Cell-Specific N-linked Glycosylation.

N-linked glycosylation plays an important role in both the innate and adaptive immune response through the modulation of cell surface receptors as well as general cell-to-cell interactions. The study of immune cell N-glycosylation is gaining interest but is hindered by the complexity of cell-type-specific N-glycan analysis. Analytical techniques such as chromatography, LC-MS/MS, and the use of lectins are all currently used to analyze cellular glycosylation. Issues with these analytical techniques include poor throughput, which is often limited to a single sample at a time, lack of structural information, the need for a large amount of starting materials, and the requirement for cell purification, thereby reducing their feasibility for N-glycan study. Here, we report the development of a rapid antibody array-based approach for the capture of specific nonadherent immune cells coupled with MALDI-IMS to analyze cellular N-glycosylation. This workflow is adaptable to multiple N-glycan imaging approaches such as the removal or stabilization and derivatization of terminal sialic acid residues providing unique avenues of analysis that have otherwise not been explored in immune cell populations. The reproducibility, sensitivity, and versatility of this assay provide an invaluable tool for researchers and clinical applications, significantly expanding the field of glycoimmunology.

Bioorthogonal Chemical Labeling Probes Targeting Sialic Acid Isomers for N-Glycan MALDI Imaging Mass Spectrometry of Tissues, Cells, and Biofluids.

Sialic acid isomers attached in either α2,3 or α2,6 linkage to glycan termini confer distinct chemical, biological, and pathological properties, but they cannot be distinguished by mass differences in traditional mass spectrometry experiments. Multiple derivatization strategies have been developed to stabilize and facilitate the analysis of sialic acid isomers and their glycoconjugate carriers by high-performance liquid chromatography, capillary electrophoresis, and mass spectrometry workflows. Herein, a set of novel derivatization schemes are described that result in the introduction of bioorthogonal click chemistry alkyne or azide groups into α2,3- and α2,8-linked sialic acids. These chemical modifications were validated and structurally characterized using model isomeric sialic acid conjugates and model protein carriers. Use of an alkyne-amine, propargylamine, as the second amidation reagent effectively introduces an alkyne functional group into α2,3-linked sialic acid glycoproteins. In tissues, serum, and cultured cells, this allows for the detection and visualization of N-linked glycan sialic acid isomers by imaging mass spectrometry approaches. Formalin-fixed paraffin-embedded prostate cancer tissues and pancreatic cancer cell lines were used to characterize the numbers and distribution of alkyne-modified α2,3-linked sialic acid N-glycans. An azide-amine compound with a poly(ethylene glycol) linker was evaluated for use in histochemical staining. Formalin-fixed pancreatic cancer tissues were amidated with the azide amine, reacted with biotin-alkyne and copper catalyst, and sialic acid isomers detected by streptavidin-peroxidase staining. The direct chemical introduction of bioorthogonal click chemistry reagents into sialic acid-containing glycans and glycoproteins provides a new glycomic tool set to expand approaches for their detection, labeling, visualization, and enrichment.

Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis.

Matrix assisted laser desorption/ionization imaging has greatly improved our understanding of spatial biology, however a robust bioinformatic pipeline for data analysis is lacking. Here, we demonstrate the application of high-dimensionality reduction/spatial clustering and histopathological annotation of matrix assisted laser desorption/ionization imaging datasets to assess tissue metabolic heterogeneity in human lung diseases. Using metabolic features identified from this pipeline, we hypothesize that metabolic channeling between glycogen and N-linked glycans is a critical metabolic process favoring pulmonary fibrosis progression. To test our hypothesis, we induced pulmonary fibrosis in two different mouse models with lysosomal glycogen utilization deficiency. Both mouse models displayed blunted N-linked glycan levels and nearly 90% reduction in endpoint fibrosis when compared to WT animals. Collectively, we provide conclusive evidence that lysosomal utilization of glycogen is required for pulmonary fibrosis progression. In summary, our study provides a roadmap to leverage spatial metabolomics to understand foundational biology in pulmonary diseases.

Analysis of N-linked Glycan Alterations in Tissue and Serum Reveals Promising Biomarkers for Intrahepatic Cholangiocarcinoma.

There is an urgent need for the identification of reliable prognostic biomarkers for patients with intrahepatic cholangiocarcinoma (iCCA) and alterations in N-glycosylation have demonstrated an immense potential to be used as diagnostic strategies for many cancers, including hepatocellular carcinoma (HCC). N-glycosylation is one of the most common post-translational modifications known to be altered based on the status of the cell. N-glycan structures on glycoproteins can be modified based on the addition or removal of specific N-glycan residues, some of which have been linked to liver diseases. However, little is known concerning the N-glycan alterations that are associated with iCCA. We characterized the N-glycan modifications quantitatively and qualitatively in three cohorts, consisting of two tissue cohorts: a discovery cohort (n = 104 cases) and a validation cohort (n = 75), and one independent serum cohort consisting of patients with iCCA, HCC, or benign chronic liver disease (n = 67). N-glycan analysis in situ was correlated to tumor regions annotated on histopathology and revealed that bisected fucosylated N-glycan structures were specific to iCCA tumor regions. These same N-glycan modifications were significantly upregulated in iCCA tissue and serum relative to HCC and bile duct disease, including primary sclerosing cholangitis (PSC) (P < 0.0001). N-glycan modifications identified in iCCA tissue and serum were used to generate an algorithm that could be used as a biomarker of iCCA. We demonstrate that this biomarker algorithm quadrupled the sensitivity (at 90% specificity) of iCCA detection as compared with carbohydrate antigen 19-9, the current "gold standard" biomarker of CCA. Significance: This work elucidates the N-glycan alterations that occur directly in iCCA tissue and utilizes this information to discover serum biomarkers that can be used for the noninvasive detection of iCCA.

Applications and continued evolution of glycan imaging mass spectrometry.

Glycosylation is an important posttranslational modifier of proteins and lipid conjugates critical for the stability and function of these macromolecules. Particularly important are N-linked glycans attached to asparagine residues in proteins. N-glycans have well-defined roles in protein folding, cellular trafficking and signal transduction, and alterations to them are implicated in a variety of diseases. However, the non-template driven biosynthesis of these N-glycans leads to significant structural diversity, making it challenging to identify the most biologically and clinically relevant species using conventional analyses. Advances in mass spectrometry instrumentation and data acquisition, as well as in enzymatic and chemical sample preparation strategies, have positioned mass spectrometry approaches as powerful analytical tools for the characterization of glycosylation in health and disease. Imaging mass spectrometry expands upon these strategies by capturing the spatial component of a glycan's distribution in-situ, lending additional insight into the organization and function of these molecules. Herein we review the ongoing evolution of glycan imaging mass spectrometry beginning with widely adopted tissue imaging approaches and expanding to other matrices and sample types with potential research and clinical implications. Adaptations of these techniques, along with their applications to various states of disease, are discussed. Collectively, glycan imaging mass spectrometry analyses broaden our understanding of the biological and clinical relevance of N-glycosylation to human disease.

Utilizing multimodal mass spectrometry imaging for profiling immune cell composition and N-glycosylation across colorectal carcinoma disease progression.

Colorectal cancer (CRC) stands as a leading cause of death worldwide, often arising from specific genetic mutations, progressing from pre-cancerous adenomas to adenocarcinomas. Early detection through regular screening can result in a 90% 5-year survival rate for patients. However, unfortunately, only a fraction of CRC cases are identified at pre-invasive stages, allowing progression to occur silently over 10-15 years. The intricate interplay between the immune system and tumor cells within the tumor microenvironment plays a pivotal role in the progression of CRC. Immune cell clusters can either inhibit or facilitate tumor initiation, growth, and metastasis. To gain a better understanding of this relationship, we conducted N-glycomic profiling using matrix-assisted laser desorption-ionization mass spectrometry imaging (MALDI-MSI). We detected nearly 100 N-glycan species across all samples, revealing a shift in N-glycome profiles from normal to cancerous tissues, marked by a decrease in high mannose N-glycans. Further analysis of precancerous to invasive carcinomas showed an increase in pauci-mannose biantennary, and tetraantennary N-glycans with disease progression. Moreover, a distinct stratification in the N-glycome profile was observed between non-mucinous and mucinous CRC tissues, driven by pauci-mannose, high mannose, and bisecting N-glycans. Notably, we identified immune clusters of CD20+ B cells and CD3/CD44+ T cells distinctive and predictive with signature profiles of bisecting and branched N-glycans. These spatial N-glycan profiles offer potential biomarkers and therapeutic targets throughout the progression of CRC.