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.

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.

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.

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.

Tumor in Transit: Intracardiac Leiomyomatosis.

Intravenous leiomyoma is a rare condition that occurs when there is a vascular invasion of a pre-existing uterine leiomyoma. The tumor can metastasize to structures such as the heart and lungs. We discuss a case of metastasis to the heart resulting in severe tricuspid regurgitation. Surgical intervention is the primary modality; usually a staged approach involving cardiac surgery along with abdominal and/or pelvic surgery. We want to highlight the importance of fully investigating right-sided cardiac masses. While there are common etiologies for these masses, one must maintain a high degree of suspicion for an intravenous leiomyoma, especially if a female has certain risk factors such as a prior history of fibroids or a hysterectomy. We also stress the importance of a multi-disciplinary team approach when providing care to these patients, along with reviewing all modalities of imaging.

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.

Strategic self-limiting production of infectious HIV particles by CRISPR in permissive cells.

Post-translational glycosylation of the HIV-1 envelope protein involving precursor glycan trimming by mannosyl oligosaccharide glucosidase (MOGS) is critically important for morphogenesis of virions and viral entry. Strategic editing of the MOGS gene in T lymphocytes and myeloid origin cells harboring latent proviral DNA results in the production of non-infectious particles upon treatment of cells with latency reversal agents. Controlled activation of CRISPR-MOGS by rebound HIV-1 mitigates production of infectious particles that exhibit poor ability of the virus to penetrate uninfected cells. Moreover, exclusive activation of CRISPR in cells infected with HIV-1 alleviates concern for broad off-target impact of MOGS gene ablation in uninfected cells. Combination CRISPR treatment of peripheral blood lymphocytes prepared from blood of people with HIV-1 (PWH) tailored for editing the MOGS gene (CRISPR-MOGS) and proviral HIV-1 DNA (CRISPR-HIV) revealed a cooperative impact of CRISPR treatment in inhibiting the production of infectious HIV-1 particles. Our design for genetic inactivation of MOGS by CRISPR exhibits no detectable off-target effects on host cells or any deleterious impact on cell survival and proliferation. Our findings offer the development of a new combined gene editing-based cure strategy for the diminution of HIV-1 spread after cessation of antiretroviral therapy (ART) and its elimination.

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.

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.

Targeting protein tyrosine phosphatases for CDK6-induced immunotherapy resistance.

Elucidating the mechanisms of resistance to immunotherapy and developing strategies to improve its efficacy are challenging goals. Bioinformatics analysis demonstrates that high CDK6 expression in melanoma is associated with poor progression-free survival of patients receiving single-agent immunotherapy. Depletion of CDK6 or cyclin D3 (but not of CDK4, cyclin D1, or D2) in cells of the tumor microenvironment inhibits tumor growth. CDK6 depletion reshapes the tumor immune microenvironment, and the host anti-tumor effect depends on cyclin D3/CDK6-expressing CD8+ and CD4+ T cells. This occurs by CDK6 phosphorylating and increasing the activities of PTP1B and T cell protein tyrosine phosphatase (TCPTP), which, in turn, decreases tyrosine phosphorylation of CD3ζ, reducing the signal transduction for T cell activation. Administration of a PTP1B and TCPTP inhibitor prove more efficacious than using a CDK6 degrader in enhancing T cell-mediated immunotherapy. Targeting protein tyrosine phosphatases (PTPs) might be an effective strategy for cancer patients who resist immunotherapy treatment.

Beyond glyco-proteomics-Understanding the role of genetics in cancer biomarkers.

The development of robust cancer biomarkers is the most effective way to improve overall survival, as early detection and treatment leads to significantly better clinical outcomes. Many of the cancer biomarkers that have been identified and are clinically utilized are glycoproteins, oftentimes a specific glycoform. Aberrant glycosylation is a common theme in cancer, with dysregulated glycosylation driving tumor initiation and metastasis, and abnormal glycosylation can be detection both on the tissue surface and in serum. However, most cancer types are heterogeneous in regard to tumor genomics, and this heterogeneity extends to cancer glycomics. This limits the sensitivity of standalone glycan-based biomarkers, which has slowed their implementation clinically. However, if targeted biomarker development can take into account genomic tumor information, the development of complementary biomarkers that target unique cancer subgroups can be accomplished. This idea suggests the need for algorithm-based cancer biomarkers, which can utilize multiple biomarkers along with relevant demographic information. This concept has already been established in the detection of hepatocellular carcinoma with the GALAD score, and an algorithm-based approach would likely be effective in improving biomarker sensitivity for additional cancer types. In order to increase cancer diagnostic biomarker sensitivity, there must be more targeted biomarker development that considers tumor genomic, proteomic, metabolomic, and clinical data while identifying tumor biomarkers.

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.