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.

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.

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.

Integrating age, BMI, and serum N-glycans detected by MALDI mass spectrometry to classify suspicious mammogram findings as benign lesions or breast cancer.

While mammograms are the standard tool for breast cancer screening, there remains challenges for mammography to effectively distinguish benign lesions from breast cancers, leading to many unnecessary biopsy procedures. A blood-based biomarker could provide a minimally invasive supplemental assay to increase the specificity of breast cancer screening. Serum N-glycosylation alterations have associations with many cancers and several of the clinical characteristics of breast cancer. The current study utilized a high-throughput mass spectrometry workflow to identify serum N-glycans with differences in intensities between patients that had a benign lesion from patients with breast cancer. The overall N-glycan profiles of the two patient groups had no differences, but there were several individual N-glycans with significant differences in intensities between patients with benign lesions and ductal carcinoma in situ (DCIS). Many N-glycans had strong associations with age and/or body mass index, but there were several of these associations that differed between the patients with benign lesions and breast cancer. Accordingly, the samples were stratified by the patient's age and body mass index, and N-glycans with significant differences between these subsets were identified. For women aged 50-74 with a body mass index of 18.5-24.9, a model including the intensities of two N-glycans, 1850.666 m/z and 2163.743 m/z, age, and BMI were able to clearly distinguish the breast cancer patients from the patients with benign lesions with an AUROC of 0.899 and an optimal cutoff with 82% sensitivity and 84% specificity. This study indicates that serum N-glycan profiling is a promising approach for providing clarity for breast cancer screening, especially within the subset of healthy weight women in the age group recommended for mammograms.

Perspectives on pediatric congenital aortic valve stenosis: Extracellular matrix proteins, post translational modifications, and proteomic strategies.

In heart valve biology, organization of the extracellular matrix structure is directly correlated to valve function. This is especially true in cases of pediatric congenital aortic valve stenosis (pCAVS), in which extracellular matrix (ECM) dysregulation is a hallmark of the disease, eventually leading to left ventricular hypertrophy and heart failure. Therapeutic strategies are limited, especially in pediatric cases in which mechanical and tissue engineered valve replacements may not be a suitable option. By identifying mechanisms of translational and post-translational dysregulation of ECM in CAVS, potential drug targets can be identified, and better bioengineered solutions can be developed. In this review, we summarize current knowledge regarding ECM proteins and their post translational modifications (PTMs) during aortic valve development and disease and contributing factors to ECM dysregulation in CAVS. Additionally, we aim to draw parallels between other fibrotic disease and contributions to ECM post-translational modifications. Finally, we explore the current treatment options in pediatrics and identify how the field of proteomics has advanced in recent years, highlighting novel characterization methods of ECM and PTMs that may be used to identify potential therapeutic strategies relevant to pCAVS.

Racial Distribution of Neighborhood-Level Social Deprivation in a Retrospective Cohort of Prostate Cancer Survivors.

Background: A better understanding of neighborhood-level factors' contribution is needed in order to increase the precision of cancer control interventions that target geographic determinants of cancer health disparities. This study characterized the distribution of neighborhood deprivation in a racially diverse cohort of prostate cancer survivors. Methods: A retrospective cohort of 253 prostate cancer patients who were treated with radical prostatectomy from 2011 to 2019 was established at the Medical University of South Carolina. Individual-level data on clinical variables (e.g., stage, grade) and race were abstracted. Social Deprivation Index (SDI) and Healthcare Professional Shortage (HPS) status was obtained from the Robert Graham Center and assigned to participants based on their residential census tract. Data were analyzed with descriptive statistics and multivariable logistic regression. Results: The cohort of 253 men consisted of 168 white, 81 African American, 1 Hispanic and 3 multiracial men. Approximately 49% of 249 men lived in areas with high SDI (e.g., SDI score of 48 to 98). The mean for SDI was 44.5 (+27.4), and the range was 97 (1−98) for all study participants. African American men had a significantly greater likelihood of living in a socially deprived neighborhood compared to white men (OR = 3.7, 95% C.I. 2.1−6.7, p < 0.01), while men who lived in areas with higher HPS shortage status were significantly more likely to live in a neighborhood that had high SDI compared to men who lived in areas with lower HPS shortages (OR = 4.7, 95% C.I. = 2.1−10.7, p < 0.01). African Americans had a higher likelihood of developing biochemical reoccurrence (OR = 3.7, 95% C.I. = 1.7−8.0) compared with white men. There were no significant association between SDI and clinical characteristics of prostate cancer. Conclusions: This study demonstrates that SDI varies considerably by race among men with prostate cancer treated with radical prostatectomy. Using SDI to understand the social environment could be -particularly useful as part of precision medicine and precision public health approaches and could be used by cancer centers, public health providers, and other health care specialists to inform operational decisions about how to target health promotion and disease prevention efforts in catchment areas and patient populations.

Sphingomyelinases in retinas and optic nerve heads: Effects of ocular hypertension and ischemia.

Sphingomyelinases (SMase), enzymes that catalyze the hydrolysis of sphingomyelin to ceramide, are important sensors for inflammatory cytokines and apoptotic signaling. Studies have provided evidence that increased SMase activity can contribute to retinal injury. In most tissues, two major SMases are responsible for stress-induced increases in ceramide: acid sphingomyelinase (ASMase) and Mg2+-dependent neutral sphingomyelinase (NSMase). The purposes of the current study were to determine the localization of SMases and their substrates in the retina and optic nerve head and to investigate the effects of ocular hypertension and ischemia on ASMase and NSMase activities. Tissue and cellular localization of ASMase and NSMase were determined by immunofluorescence imaging. Tissue localization of sphingomyelin in retinas was further determined by Matrix-Assisted Laser Desorption/Ionization mass spectrometry imaging. Tissue levels of sphingomyelins and ceramide were determined by liquid chromatography with tandem mass spectrometry. Sphingomyelinase activities under basal conditions and following acute ischemic and ocular hypotensive stress were measured using the Amplex Red Sphingomyelinase Assay Kit. Our data show that ASMase is in the optic nerve head and the retinal ganglion cell layer. NSMase is in the optic nerve head, photoreceptor and retinal ganglion cell layers. Both ASMase and NSMase were identified in human induced pluripotent stem cell-derived retinal ganglion cells and optic nerve head astrocytes. The retina and optic nerve head each exhibited unique distribution of sphingomyelins with the abundance of very long chain species being higher in the optic nerve head than in the retina. Basal activities for ASMase in retinas and optic nerve heads were 54.98 ± 2.5 and 95.6 ± 19.5 mU/mg protein, respectively. Ocular ischemia significantly increased ASMase activity to 86.2 ± 15.3 mU/mg protein in retinas (P = 0.03) but not in optic nerve heads (81.1 ± 15.3 mU/mg protein). Ocular hypertension significantly increased ASMase activity to 121.6 ± 7.3 mU/mg protein in retinas (P < 0.001) and 267.0 ± 66.3 mU/mg protein in optic nerve heads (P = 0.03). Basal activities for NSMase in retinas and optic nerve heads were 12.3 ± 2.1 and 37.9 ± 8.7 mU/mg protein, respectively. No significant change in NSMase activity was measured following ocular ischemia or hypertension. Our results provide evidence that both ASMase and NSMase are expressed in retinas and optic nerve heads; however, basal ASMase activity is significantly higher than NSMase activity in retinas and optic nerve heads. In addition, only ASMase activity was significantly increased in ocular ischemia or hypertension. These data support a role for ASMase-mediated sphingolipid metabolism in the development of retinal ischemic and hypertensive injuries.

Metabolic Links to Socioeconomic Stresses Uniquely Affecting Ancestry in Normal Breast Tissue at Risk for Breast Cancer.

A primary difference between black women (BW) and white women (WW) diagnosed with breast cancer is aggressiveness of the tumor. Black women have higher mortalities with similar incidence of breast cancer compared to other race/ethnicities, and they are diagnosed at a younger age with more advanced tumors with double the rate of lethal, triple negative breast cancers. One hypothesis is that chronic social and economic stressors result in ancestry-dependent molecular responses that create a tumor permissive tissue microenvironment in normal breast tissue. Altered regulation of N-glycosylation of proteins, a glucose metabolism-linked post-translational modification attached to an asparagine (N) residue, has been associated with two strong independent risk factors for breast cancer: increased breast density and body mass index (BMI). Interestingly, high body mass index (BMI) levels have been reported to associate with increases of cancer-associated N-glycan signatures. In this study, we used matrix assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) to investigate molecular pattern changes of N-glycosylation in ancestry defined normal breast tissue from BW and WW with significant 5-year risk of breast cancer by Gail score. N-glycosylation was tested against social stressors including marital status, single, education, economic status (income), personal reproductive history, the risk factors BMI and age. Normal breast tissue microarrays from the Susan G. Komen tissue bank (BW=43; WW= 43) were used to evaluate glycosylation against socioeconomic stress and risk factors. One specific N-glycan (2158 m/z) appeared dependent on ancestry with high sensitivity and specificity (AUC 0.77, Brown/Wilson p-value<0.0001). Application of a linear regression model with ancestry as group variable and socioeconomic covariates as predictors identified a specific N-glycan signature associated with different socioeconomic stresses. For WW, household income was strongly associated to certain N-glycans, while for BW, marital status (married and single) was strongly associated with the same N-glycan signature. Current work focuses on understanding if combined N-glycan biosignatures can further help understand normal breast tissue at risk. This study lays the foundation for understanding the complexities linking socioeconomic stresses and molecular factors to their role in ancestry dependent breast cancer risk.

Novel Combined Enzymatic Approach to Analyze Nonsialylated N-Linked Glycans through MALDI Imaging Mass Spectrometry.

Alterations to N-glycan expression are relevant to the progression of various diseases, particularly cancer. In many cases, specific N-glycan structural features such as sialylation, fucosylation, and branching are of specific interest. A novel MALDI imaging mass spectrometry workflow has been recently developed to analyze these features of N-glycosylation through the utilization of endoglycosidase enzymes to cleave N-glycans from associated glycoproteins. Enzymes that have previously been utilized to cleave N-glycans include peptide-N-glycosidase F (PNGase F) to target N-glycans indiscriminately and endoglycosidase F3 (Endo F3) to target core fucosylated N-glycans. In addition to these endoglycosidases, additional N-glycan cleaving enzymes could be used to target specific structural features. Sialidases, also termed neuraminidases, are a family of enzymes that remove terminal sialic acids from glycoconjugates. This work aims to utilize sialidase, in conjunction with PNGase F/Endo F3, to enzymatically remove sialic acids from N-glycans in an effort to increase sensitivity for nonsialylated N-glycan MALDI-IMS peaks. Improving detection of nonsialylated N-glycans allows for a more thorough analysis of specific structural features such as fucosylation or branching, particularly of low abundant structures. Sialidase utilization in MALDI-IMS dramatically increases sensitivity and increases on-tissue endoglycosidase efficiency, making it a very useful companion technique to specifically detect nonsialylated N-glycans.

Predictive value of collagen in cancer.

Cancer is a complex disease and a significant cause of mortality worldwide. Over the course of nearly all cancer types, collagen within the tumor microenvironment influences emergence, progression, and metastasis. This review discusses collagen regulation within the tumor microenvironment, pathological involvement of collagen, and predictive values of collagen and related extracellular matrix components in main cancer types. A survey of predictive tests leveraging collagen assays using clinical cohorts is presented. A conclusion is that collagen has high predictive value in monitoring cancer processes and stratifying by outcomes. New approaches should be considered that continue to define molecular facets of collagen related to cancer.