In-Depth Matrisome and Glycoproteomic Analysis of Human Brain Glioblastoma Versus Control Tissue

Unique Glycans in Synaptic Glycoproteins in Mouse Brain

The synapse is an essential connection between neuronal cells in which the membrane and secreted glycoproteins regulate neurotransmission. The post-translational modifications of glycoproteins with carbohydrates, although essential for their functions as well as their specific localization, are not well understood. Oddly, whereas galactose addition to glycoproteins is required for neuronal functions, galactosylation is severely restricted for Asn-linked on N-glycans in the brain, and genetic evidence highlights the important roles of galactose in brain functions and development. To explore this novel glycosylation, we exploited an orthogonal technology in which a biotinylated sialic acid derivative (CMP-biotin-Sia) is transferred to terminally galactosylated proteins by a recombinant sialyltransferase (rST6Gal1). This approach allowed us to identify the carrier proteins as well as their localization on brain sections. Immunohistochemical analysis of the biotinylated glycoproteins in brain sections demonstrates that they are largely positioned in the pre- and postsynaptic membranes. Consistent with this positioning, glycoproteomic analyses of the labeled glycoproteins identified a number of them that are involved in synaptic function, cell adhesion, and extracellular matrix interactions. The discovery of these galactosylated N-glycoproteins and their relative confinement to synapses provide novel insights into the unusual and specific nature of protein glycosylation in the brain.

Soluble Proteoglycans and Proteoglycan Fragments as Biomarkers of Pathological Extracellular Matrix Remodeling

Proteoglycans and their proteolytic fragments diffuse into biological fluids such as plasma, serum, urine, or synovial fluid, where they can be detected by antibodies or mass-spectrometry. Neopeptides generated by the proteolysis of proteoglycans are recognized by specific neoepitope antibodies and can act as a proxy for the activity of certain proteases. Proteoglycan and proteoglycan fragments can be potentially used as prognostic, diagnostic, or theragnostic biomarkers for several diseases characterized by dysregulated extracellular matrix remodeling such as osteoarthritis, rheumatoid arthritis, atherosclerosis, thoracic aortic aneurysms, central nervous system disorders, viral infections, and cancer. Here, we review the main mechanisms accounting for the presence of soluble proteoglycans and their fragments in biological fluids, their potential application as diagnostic, prognostic, or theragnostic biomarkers, and highlight challenges and opportunities ahead of their clinical translation.

Elevated α-1,2-mannosidase MAN1C1 in glioma stem cells and its implications for immunological changes and prognosis in glioma patients

Glioblastoma multiforme (GBM) is the most aggressive type of primary brain tumor, and the presence of glioma stem cells (GSCs) has been linked to its resistance to treatments and recurrence. Additionally, aberrant glycosylation has been implicated in the aggressiveness of cancers. However, the influence and underlying mechanism of N-glycosylation on the GSC phenotype and GBM malignancy remain elusive. Here, we performed an in-silico analysis approach on publicly available datasets to examine the function of N-glycosylation-related genes in GSCs and gliomas, accompanied by a qRT-PCR validation experiment. We found that high α-1,2-mannosidase MAN1C1 is associated with immunological functions and worse survival of glioma patients. Differential gene expression analysis and qRT-PCR validation revealed that MAN1C1 is highly expressed in GSCs. Furthermore, higher MAN1C1 expression predicts worse outcomes in glioma patients. Also, MAN1C1 expression is increased in the perinecrotic region of GBM and is associated with immunological and inflammatory functions, a hallmark of the GBM mesenchymal subtype. Further analysis confirmed that MAN1C1 expression is closely associated with infiltrating immune cells and disrupted immune response in the GBM microenvironment. These suggest that MAN1C1 is a potential biomarker for gliomas and may be important as an immunotherapeutic target for GBM.

Collagen VI deposition primes the glioblastoma microenvironment for invasion through mechanostimulation of β-catenin signaling

While glioblastoma (GBM) progression is associated with extensive extracellular matrix (ECM) secretion, the causal contributions of ECM secretion to invasion remain unclear. Here we investigate these contributions by combining engineered materials, proteomics, analysis of patient data, and a model of bevacizumab-resistant GBM. We find that GBM cells cultured in engineered 3D hyaluronic acid hydrogels secrete ECM prior to invasion, particularly in the absence of exogenous ECM ligands. Proteomic measurements reveal extensive secretion of collagen VI, and collagen VI-associated transcripts are correspondingly enriched in microvascular proliferation regions of human GBMs. We further show that bevacizumab-resistant GBM cells deposit more collagen VI than their responsive counterparts, which is associated with marked cell-ECM stiffening. COL6A3 deletion in GBM cells reduces invasion, β-catenin signaling, and expression of mesenchymal markers, and these effects are amplified in hypoxia. Our studies strongly implicate GBM cell-derived collagen VI in microenvironmental remodeling to facilitate invasion.

Identification of established and novel extracellular matrix components in glioblastoma as targets for angiogenesis and prognosis

Glioblastomas (GBM) are aggressive tumors known for their heterogeneity, rapid proliferation, treatment resistance, and extensive vasculature. Angiogenesis, the formation of new vessels, involves endothelial cell (EC) migration and proliferation. Various extracellular matrix (ECM) molecules regulate EC survival, migration, and proliferation. Culturing human brain EC (HBMEC) on GBM-derived ECM revealed a decrease in EC numbers compared to controls. Through in silico analysis, we explored ECM gene expression differences between GBM and brain normal glia cells and the impact of GBM microenvironment on EC ECM transcripts. ECM molecules such as collagen alpha chains (COL4A1, COL4A2, p < 0.0001); laminin alpha (LAMA4), beta (LAMB2), and gamma (LAMC1) chains (p < 0.0005); neurocan (NCAN), brevican (BCAN) and versican (VCAN) (p < 0.0005); hyaluronan synthase (HAS) 2 and metalloprotease (MMP) 2 (p < 0.005); MMP inhibitors (TIMP1-4, p < 0.0005), transforming growth factor beta-1 (TGFB1) and integrin alpha (ITGA3/5) (p < 0.05) and beta (ITGB1, p < 0.0005) chains showed increased expression in GBM. Additionally, GBM-influenced EC exhibited elevated expression of COL5A3, COL6A1, COL22A1 and COL27A1 (p < 0.01); LAMA1, LAMB1 (p < 0.001); fibulins (FBLN1/2, p < 0.01); MMP9, HAS1, ITGA3, TGFB1, and wingless-related integration site 9B (WNT9B) (p < 0.01) compared to normal EC. Some of these molecules: COL5A1/3, COL6A1, COL22/27A1, FBLN1/2, ITGA3/5, ITGB1 and LAMA1/B1 (p < 0.01); NCAN, HAS1, MMP2/9, TIMP1/2 and TGFB1 (p < 0.05) correlated with GBM patient survival. In conclusion, this study identified both established and novel ECM molecules regulating GBM angiogenesis, suggesting NCAN and COL27A1 are new potential prognostic biomarkers for GBM.

A prognostic matrix gene expression signature defines functional glioblastoma phenotypes and niches

Background

Interactions among tumor, immune, and vascular niches play major roles in driving glioblastoma (GBM) malignancy and treatment responses. The composition, heterogeneity, and localization of extracellular core matrix proteins (CMPs) that mediate such interactions, however, are not well understood.

Methods

Here, through computational genomics and proteomics approaches, we analyzed the functional and clinical relevance of CMP expression in GBM at bulk, single cell, and spatial anatomical resolution.

Results

We identified genes encoding CMPs whose expression levels categorize GBM tumors into CMP expression-high (M-H) and CMP expression-low (M-L) groups. CMP enrichment is associated with worse patient survival, specific driver oncogenic alterations, mesenchymal state, infiltration of pro-tumor immune cells, and immune checkpoint gene expression. Anatomical and single-cell transcriptome analyses indicate that matrisome gene expression is enriched in vascular and leading edge/infiltrative niches that are known to harbor glioma stem cells driving GBM progression. Finally, we identified a 17-gene CMP expression signature, termed Matrisome 17 (M17) signature that further refines the prognostic value of CMP genes. The M17 signature is a significantly stronger prognostic factor compared to MGMT promoter methylation status as well as canonical subtypes, and importantly, potentially predicts responses to PD1 blockade.

Conclusion

The matrisome gene expression signature provides a robust stratification of GBM patients by survival and potential biomarkers of functionally relevant GBM niches that can mediate mesenchymal-immune cross talk. Patient stratification based on matrisome profiles can contribute to selection and optimization of treatment strategies.

RAMZIS: a bioinformatic toolkit for rigorous assessment of the alterations to glycoprotein composition that occur during biological processes

Motivation

Glycosylation elaborates the structures and functions of glycoproteins; glycoproteins are common post-translationally modified proteins and are heterogeneous and non-deterministically synthesized as an evolutionarily driven mechanism that elaborates the functions of glycosylated gene products. Glycoproteins, accounting for approximately half of all proteins, require specialized proteomics data analysis methods due to micro- and macro-heterogeneities as a given glycosite can be divided into several glycosylated forms, each of which must be quantified. Sampling of heterogeneous glycopeptides is limited by mass spectrometer speed and sensitivity, resulting in missing values. In conjunction with the low sample size inherent to glycoproteomics, a specialized toolset is needed to determine if observed changes in glycopeptide abundances are biologically significant or due to data quality limitations.

Results

We developed an R package, Relative Assessment of m/z Identifications by Similarity (RAMZIS), that uses similarity metrics to guide researchers to a more rigorous interpretation of glycoproteomics data. RAMZIS uses a permutation test to generate contextual similarity, which assesses the quality of mass spectral data and outputs a graphical demonstration of the likelihood of finding biologically significant differences in glycosylation abundance datasets. Investigators can assess dataset quality, holistically differentiate glycosites, and identify which glycopeptides are responsible for glycosylation pattern change. RAMZIS is validated by theoretical cases and a proof-of-concept application. RAMZIS enables comparison between datasets too stochastic, small, or sparse for interpolation while acknowledging these issues in its assessment. Using this tool, researchers will be able to rigorously define the role of glycosylation and the changes that occur during biological processes.

Availability and implementation

https://github.com/WillHackett22/RAMZIS.

Role of the Microenvironment in Glioma Pathogenesis

Gliomas are a diverse group of primary central nervous system tumors that affect both children and adults. Recent studies have revealed a dynamic cross talk that occurs between glioma cells and components of their microenvironment, including neurons, astrocytes, immune cells, and the extracellular matrix. This cross talk regulates fundamental aspects of glioma development and growth. In this review, we discuss recent discoveries about the impact of these interactions on gliomas and highlight how tumor cells actively remodel their microenvironment to promote disease. These studies provide a better understanding of the interactions in the microenvironment that are important in gliomas, offer insight into the cross talk that occurs, and identify potential therapeutic vulnerabilities that can be utilized to improve clinical outcomes.

Glioma Cells Secrete Collagen VI to Facilitate Invasion

While glioblastoma (GBM) progression is associated with extensive extracellular matrix (ECM) secretion, the causal contributions of ECM secretion to invasion remain unclear. Here we investigate these contributions by combining engineered materials, proteomics, analysis of patient data, and a model of bevacizumab-resistant GBM. We find that GBM cells cultured in engineered 3D hyaluronic acid hydrogels secrete ECM prior to invasion, particularly in the absence of exogenous ECM ligands. Proteomic measurements reveal extensive secretion of collagen VI, and collagen VI-associated transcripts are correspondingly enriched in microvascular proliferation regions of human GBMs. We further show that bevacizumab-resistant GBM cells deposit more collagen VI than their responsive counterparts, which is associated with marked cell-ECM stiffening. COL6A3 deletion in GBM cells reduces invasion, β-catenin signaling, and expression of mesenchymal markers, and these effects are amplified in hypoxia. Our studies strongly implicate GBM cell-derived collagen VI in microenvironmental remodeling to facilitate invasion.

Agrin is a novel oncogenic protein in thyroid cancer

Agrin (AGRN) is a matricellular glycoprotein involved in extracellular signal transduction. AGRN is involved in tumorigenesis and cancer progression; however, the role of AGRN in thyroid cancer (TC) remains unclear. In the present study, using cell lines derived from various subtypes of TC including CGTH, FTC-133 and BcPAP and transcriptomic data from patients with TC, the role of AGRN in TC was analyzed by migration, invasion, viability and proliferation assays as well as Western blot with EMT markers. AGRN expression was significantly increased in thyroid tumors and cell lines derived from various TC subtypes. The highest AGRN expression was found in follicular and papillary thyroid carcinoma subtypes. Immunocytochemistry revealed nuclear AGRN localization in normal (NTHY) and TC cells. Silencing of AGRN decreased viability, proliferation, migration and invasion of TC cell lines by upregulating vimentin and downregulating N-cadherin and E-cadherin. Furthermore, the expression of AGRN was associated with neutrophil infiltration in thyroid tumors. In conclusion, the present results indicated that increased AGRN expression promoted tumorigenic phenotypes of TC cells, while AGRN expression was associated with immune infiltration in thyroid tumors. AGRN may represent a target for future cancer therapy and requires further evaluation.

Analysis of complex proteoglycans using serial proteolysis and EThcD provides deep N- and O-glycoproteomic coverage

Proteoglycans are a small but diverse family of proteins that play a wide variety of roles at the cell surface and in the extracellular matrix. In addition to their glycosaminoglycan (GAG) chains, they are N- and O-glycosylated. All of these types of glycosylation are crucial to their function but present a considerable analytical challenge. We describe the combination of serial proteolysis followed by the application of higher-energy collisional dissociation (HCD) and electron transfer/higher-energy collisional dissociation (EThcD) to optimize protein sequence coverage and glycopeptide identification from proteoglycans. In many cases, the use of HCD alone allows the identification of more glycopeptides. However, the localization of glycoforms on multiply glycosylated peptides has remained elusive. We demonstrate the use of EThcD for the confident assignment of glycan compositions on multiply glycosylated peptides. Dense glycosylation on proteoglycans is key to their biological function; thus, developing tools to identify and quantify doubly glycosylated peptides is of interest. Additionally, glycoproteomics searches identify glycopeptides in otherwise poorly covered regions of proteoglycans. The development of these and other analytical tools may permit glycoproteomic similarity comparisons in biological samples.

The entanglement of extracellular matrix molecules and immune checkpoint inhibitors in cancer: a systematic review of the literature

Introduction

Immune-checkpoint inhibitors (ICIs) have emerged as a core pillar of cancer therapy as single agents or in combination regimens both in adults and children. Unfortunately, ICIs provide a long-lasting therapeutic effect in only one third of the patients. Thus, the search for predictive biomarkers of responsiveness to ICIs remains an urgent clinical need. The efficacy of ICIs treatments is strongly affected not only by the specific characteristics of cancer cells and the levels of immune checkpoint ligands, but also by other components of the tumor microenvironment, among which the extracellular matrix (ECM) is emerging as key player. With the aim to comprehensively describe the relation between ECM and ICIs' efficacy in cancer patients, the present review systematically evaluated the current literature regarding ECM remodeling in association with immunotherapeutic approaches.

Methods

This review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines and was registered at the International Prospective Register of Systematic Reviews (PROSPERO, CRD42022351180). PubMed, Web of Science, and Scopus databases were comprehensively searched from inception to January 2023. Titles, abstracts and full text screening was performed to exclude non eligible articles. The risk of bias was assessed using the QUADAS-2 tool.

Results

After employing relevant MeSH and key terms, we identified a total of 5070 studies. Among them, 2540 duplicates, 1521 reviews or commentaries were found and excluded. Following title and abstract screening, the full text was analyzed, and 47 studies meeting the eligibility criteria were retained. The studies included in this systematic review comprehensively recapitulate the latest observations associating changes of the ECM composition following remodeling with the traits of the tumor immune cell infiltration. The present study provides for the first time a broad view of the tight association between ECM molecules and ICIs efficacy in different tumor types, highlighting the importance of ECM-derived proteolytic products as promising liquid biopsy-based biomarkers to predict the efficacy of ICIs.

Conclusion

ECM remodeling has an important impact on the immune traits of different tumor types. Increasing evidence pinpoint at ECM-derived molecules as putative biomarkers to identify the patients that would most likely benefit from ICIs treatments.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022351180, identifier CRD42022351180.

A prognostic matrix code defines functional glioblastoma phenotypes and niches

Interactions among tumor, immune and vascular niches play major roles in driving glioblastoma (GBM) malignancy and treatment responses. The composition, heterogeneity, and localization of extracellular core matrix proteins (CMPs) that mediate such interactions, however, are not well understood. Here, we characterize functional and clinical relevance of genes encoding CMPs in GBM at bulk, single cell, and spatial anatomical resolution. We identify a "matrix code" for genes encoding CMPs whose expression levels categorize GBM tumors into matrisome-high and matrisome-low groups that correlate with worse and better patient survival, respectively. The matrisome enrichment is associated with specific driver oncogenic alterations, mesenchymal state, infiltration of pro-tumor immune cells and immune checkpoint gene expression. Anatomical and single cell transcriptome analyses indicate that matrisome gene expression is enriched in vascular and leading edge/infiltrative anatomic structures that are known to harbor glioma stem cells driving GBM progression. Finally, we identified a 17-gene matrisome signature that retains and further refines the prognostic value of genes encoding CMPs and, importantly, potentially predicts responses to PD1 blockade in clinical trials for GBM. The matrisome gene expression profiles provide potential biomarkers of functionally relevant GBM niches that contribute to mesenchymal-immune cross talk and patient stratification which could be applied to optimize treatment responses.

Correlation of the tumor escape phenotype with loss of PRELP expression in melanoma

BACKGROUND

Despite immunotherapies having revolutionized the treatment of advanced cutaneous melanoma, effective and durable responses were only reported in a few patients. A better understanding of the interaction of melanoma cells with the microenvironment, including extracellular matrix (ECM) components, might provide novel therapeutic options. Although the ECM has been linked to several hallmarks of cancer, little information is available regarding the expression and function of the ECM protein purine-arginine-rich and leucine-rich protein (PRELP) in cancer, including melanoma.

METHODS

The structural integrity, expression and function of PRELP, its correlation with the expression of immune modulatory molecules, immune cell infiltration and clinical parameters were determined using standard methods and/or bioinformatics.

RESULTS

Bioinformatics analysis revealed a heterogeneous, but statistically significant reduced PRELP expression in available datasets of skin cutaneous melanoma when compared to adjacent normal tissues, which was associated with reduced patients' survival, low expression levels of components of the MHC class I antigen processing machinery (APM) and interferon (IFN)-γ signal transduction pathway, but increased expression of the transforming growth factor (TGF)-β isoform 1 (TFGB1) and TGF-β receptor 1 (TGFBR1). In addition, a high frequency of intra-tumoral T cells directly correlated with the expression of MHC class I and PRELP as well as the T cell attractant CCL5 in melanoma lesions. Marginal to low PRELP expression levels were found in the 47/49 human melanoma cell lines analysis. Transfection of PRELP into melanoma cell lines restored MHC class I surface expression due to transcriptional upregulation of major MHC class I APM and IFN-γ pathway components. In addition, PRELP overexpression is accompanied by high CCL5 secretion levels in cell supernatant, an impaired TGF-β signaling as well as a reduced cell proliferation, migration and invasion of melanoma cells.

CONCLUSIONS

Our findings suggest that PRELP induces the expression of MHC class I and CCL5 in melanoma, which might be involved in an enhanced T cell recruitment and immunogenicity associated with an improved patients' outcome. Therefore, PRELP might serve as a marker for predicting disease progression and its recovery could revert the tumorigenic phenotype, which represents a novel therapeutic option for melanoma.

Mass spectrometry methods for analysis of extracellular matrix components in neurological diseases

The brain extracellular matrix (ECM) is a highly glycosylated environment and plays important roles in many processes including cell communication, growth factor binding, and scaffolding. The formation of structures such as perineuronal nets (PNNs) is critical in neuroprotection and neural plasticity, and the formation of molecular networks is dependent in part on glycans. The ECM is also implicated in the neuropathophysiology of disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and Schizophrenia (SZ). As such, it is of interest to understand both the proteomic and glycomic makeup of healthy and diseased brain ECM. Further, there is a growing need for site-specific glycoproteomic information. Over the past decade, sample preparation, mass spectrometry, and bioinformatic methods have been developed and refined to provide comprehensive information about the glycoproteome. Core ECM molecules including versican, hyaluronan and proteoglycan link proteins, and tenascin are dysregulated in AD, PD, and SZ. Glycomic changes such as differential sialylation, sulfation, and branching are also associated with neurodegeneration. A more thorough understanding of the ECM and its proteomic, glycomic, and glycoproteomic changes in brain diseases may provide pathways to new therapeutic options.

A proteome-level view of brain tumors for a better understanding of novel diagnosis, prognosis, and therapy

INTRODUCTION

Brain tumors are complex and heterogeneous malignancies with significant challenges in diagnosis, prognosis, and therapy. Proteomics, the large-scale study of proteins and their functions, has emerged as a powerful tool to comprehensively investigate the molecular mechanisms underlying brain tumor regulation.

AREAS COVERED

This review explores brain tumors from a proteomic standpoint, highlighting recent progress and insights gained through proteomic methods. It delves into the proteomic techniques employed and underscores potential biomarkers for early detection, prognosis, and treatment planning. Recent PubMed Central proteomic studies (2017-present) are discussed, summarizing findings on altered protein expression, post-translational changes, and protein interactions. This sheds light on brain tumor signaling pathways and their significance in innovative therapeutic approaches.

EXPERT OPINION

Proteomics offers immense potential for revolutionizing brain tumor diagnosis and therapy. To unlock its full benefits, further translational research is crucial. Combining proteomics with other omics data enhances our grasp of brain tumors. Validating and translating proteomic biomarkers are vital for better patient results. Challenges include tumor complexity, lack of curated proteomic databases, and the need for collaboration between researchers and clinicians. Overcoming these challenges requires investment in technology, data sharing, and translational research.

Dexamethasone Inhibits Heparan Sulfate Biosynthetic System and Decreases Heparan Sulfate Content in Orthotopic Glioblastoma Tumors in Mice

Glioblastoma (GB) is an aggressive cancer with a high probability of recurrence, despite active chemoradiotherapy with temozolomide (TMZ) and dexamethasone (DXM). These systemic drugs affect the glycosylated components of brain tissue involved in GB development; however, their effects on heparan sulfate (HS) remain unknown. Here, we used an animal model of GB relapse in which SCID mice first received TMZ and/or DXM (simulating postoperative treatment) with a subsequent inoculation of U87 human GB cells. Control, peritumor and U87 xenograft tissues were investigated for HS content, HS biosynthetic system and glucocorticoid receptor (GR, Nr3c1). In normal and peritumor brain tissues, TMZ/DXM administration decreased HS content (5-6-fold) but did not affect HS biosynthetic system or GR expression. However, the xenograft GB tumors grown in the pre-treated animals demonstrated a number of molecular changes, despite the fact that they were not directly exposed to TMZ/DXM. The tumors from DXM pre-treated animals possessed decreased HS content (1.5-2-fold), the inhibition of HS biosynthetic system mainly due to the -3-3.5-fold down-regulation of N-deacetylase/N-sulfotransferases (Ndst1 and Ndst2) and sulfatase 2 (Sulf2) expression and a tendency toward a decreased expression of the GRalpha but not the GRbeta isoform. The GRalpha expression levels in tumors from DXM or TMZ pre-treated mice were positively correlated with the expression of a number of HS biosynthesis-involved genes (Ext1/2, Ndst1/2, Glce, Hs2st1, Hs6st1/2), unlike tumors that have grown in intact SCID mice. The obtained data show that DXM affects HS content in mouse brain tissues, and GB xenografts grown in DXM pre-treated animals demonstrate attenuated HS biosynthesis and decreased HS content.

A prognostic matrix code defines functional glioblastoma phenotypes and niches

Interactions among tumor, immune and vascular niches play major roles in driving glioblastoma (GBM) malignancy and treatment responses. The composition, heterogeneity, and localization of extracellular core matrix proteins (CMPs) that mediate such interactions, however, are not well understood. Here, we characterize functional and clinical relevance of genes encoding CMPs in GBM at bulk, single cell, and spatial anatomical resolution. We identify a "matrix code" for genes encoding CMPs whose expression levels categorize GBM tumors into matrisome-high and matrisome-low groups that correlate with worse and better survival, respectively, of patients. The matrisome enrichment is associated with specific driver oncogenic alterations, mesenchymal state, infiltration of pro-tumor immune cells and immune checkpoint gene expression. Anatomical and single cell transcriptome analyses indicate that matrisome gene expression is enriched in vascular and leading edge/infiltrative anatomic structures that are known to harbor glioma stem cells driving GBM progression. Finally, we identified a 17-gene matrisome signature that retains and further refines the prognostic value of genes encoding CMPs and, importantly, potentially predicts responses to PD1 blockade in clinical trials for GBM. The matrisome gene expression profiles may provide biomarkers of functionally relevant GBM niches that contribute to mesenchymal-immune cross talk and patient stratification to optimize treatment responses.

Abnormal glycosylation in glioma: related changes in biology, biomarkers and targeted therapy

Glioma is a rapidly growing and aggressive primary malignant tumor of the central nervous system that can diffusely invade the brain tissue around, and the prognosis of patients is not significantly improved by traditional treatments. One of the most general posttranslational modifications of proteins is glycosylation, and the abnormal distribution of this modification in gliomas may shed light on how it affects biological behaviors of glioma cells, including proliferation, migration, and invasion, which may be produced by regulating protein function, cell-matrix and cell‒cell interactions, and affecting receptor downstream pathways. In this paper, from the perspective of regulating protein glycosylation changes and abnormal expression of glycosylation-related proteins (such as glycosyltransferases in gliomas), we summarize how glycosylation may play a crucial role in the discovery of novel biomarkers and new targeted treatment options for gliomas. Overall, the mechanistic basis of abnormal glycosylation affecting glioma progression remains to be more widely and deeply explored, which not only helps to inspire researchers to further explore related diagnostic and prognostic markers but also provides ideas for discovering effective treatment strategies and improving glioma patient survival and prognosis.

RadWise: A Rank-Based Hybrid Feature Weighting and Selection Method for Proteomic Categorization of Chemoirradiation in Patients with Glioblastoma

Glioblastomas (GBM) are rapidly growing, aggressive, nearly uniformly fatal, and the most common primary type of brain cancer. They exhibit significant heterogeneity and resistance to treatment, limiting the ability to analyze dynamic biological behavior that drives response and resistance, which are central to advancing outcomes in glioblastoma. Analysis of the proteome aimed at signal change over time provides a potential opportunity for non-invasive classification and examination of the response to treatment by identifying protein biomarkers associated with interventions. However, data acquired using large proteomic panels must be more intuitively interpretable, requiring computational analysis to identify trends. Machine learning is increasingly employed, however, it requires feature selection which has a critical and considerable effect on machine learning problems when applied to large-scale data to reduce the number of parameters, improve generalization, and find essential predictors. In this study, using 7k proteomic data generated from the analysis of serum obtained from 82 patients with GBM pre- and post-completion of concurrent chemoirradiation (CRT), we aimed to select the most discriminative proteomic features that define proteomic alteration that is the result of administering CRT. Thus, we present a novel rank-based feature weighting method (RadWise) to identify relevant proteomic parameters using two popular feature selection methods, least absolute shrinkage and selection operator (LASSO) and the minimum redundancy maximum relevance (mRMR). The computational results show that the proposed method yields outstanding results with very few selected proteomic features, with higher accuracy rate performance than methods that do not employ a feature selection process. While the computational method identified several proteomic signals identical to the clinical intuitive (heuristic approach), several heuristically identified proteomic signals were not selected while other novel proteomic biomarkers not selected with the heuristic approach that carry biological prognostic relevance in GBM only emerged with the novel method. The computational results show that the proposed method yields promising results, reducing 7k proteomic data to 8 selected proteomic features with a performance value of 96.364%, comparing favorably with techniques that do not employ feature selection.

10 years of extracellular matrix proteomics: Accomplishments, challenges, and future perspectives

The extracellular matrix (ECM) is a complex assembly of hundreds of proteins forming the architectural scaffold of multicellular organisms. In addition to its structural role, the ECM conveys signals orchestrating cellular phenotypes. Alterations of ECM composition, abundance, structure, or mechanics, have been linked to diseases and disorders affecting all physiological systems, including fibrosis and cancer. Deciphering the protein composition of the ECM and how it changes in pathophysiological contexts is thus the first step toward understanding the roles of the ECM in health and disease and toward the development of therapeutic strategies to correct disease-causing ECM alterations. Potentially, the ECM also represents a vast, yet untapped reservoir of disease biomarkers. ECM proteins are characterized by unique biochemical properties that have hindered their study: they are large, heavily and uniquely post-translationally modified, and highly insoluble. Overcoming these challenges, we and others have devised mass-spectrometry-based proteomic approaches to define the ECM composition, or "matrisome", of tissues. This review provides a historical overview of ECM proteomics research and presents the latest advances that now allow the profiling of the ECM of healthy and diseased tissues. The second part highlights recent examples illustrating how ECM proteomics has emerged as a powerful discovery pipeline to identify prognostic cancer biomarkers. The third part discusses remaining challenges limiting our ability to translate findings to clinical application and proposes approaches to overcome them. Last, the review introduces readers to resources available to facilitate the interpretation of ECM proteomics datasets. The ECM was once thought to be impenetrable. MS-based proteomics has proven to be a powerful tool to decode the ECM. In light of the progress made over the past decade, there are reasons to believe that the in-depth exploration of the matrisome is within reach and that we may soon witness the first translational application of ECM proteomics.

Glycomics-Assisted Glycoproteomics Enables Deep and Unbiased N-Glycoproteome Profiling of Complex Biological Specimens

Mass spectrometry-driven glycomics and glycoproteomics, the system-wide profiling of detached glycans and intact glycopeptides from biological samples, respectively, are powerful approaches to interrogate the heterogenous glycoproteome. Efforts to develop integrated workflows employing both glycomics and glycoproteomics have been invested since the concerted application of these complementary approaches enables a deeper exploration of the glycoproteome. This protocol paper outlines, step-by-step, an integrated -omics technology, the "glycomics-assisted glycoproteomics" method, that first establishes the N-glycan fine structures and their quantitative distribution pattern of protein extracts via porous graphitized carbon-LC-MS/MS. The N-glycome information is then used to augment and guide the challenging reversed-phase LC-MS/MS-based profiling of intact N-glycopeptides from the same protein samples. Experimental details and considerations relating to the sample preparation and the N-glycomics and N-glycoproteomics data collection, analysis, and integration are discussed. Benefits of the glycomics-assisted glycoproteomics method, which can be readily applied to both simple and complex biological specimens such as protein extracts from cells, tissues, and bodily fluids (e.g., serum), include quantitative information of the protein carriers and site(s) of glycosylation, site occupancy, and the site-specific glycan structures directly from biological samples. The glycomics-assisted glycoproteomics method therefore facilitates a comprehensive view of the complexity and dynamics of the heterogenous glycoproteome.

Peptide location fingerprinting identifies species- and tissue-conserved structural remodelling of proteins as a consequence of ageing and disease

Extracellular matrices (ECMs) in the intervertebral disc (IVD), lung and artery are thought to undergo age-dependant accumulation of damage by chronic exposure to mechanisms such as reactive oxygen species, proteases and glycation. It is unknown whether this damage accumulation is species-dependant (via differing lifespans and hence cumulative exposures) or whether it can influence the progression of age-related diseases such as atherosclerosis. Peptide location fingerprinting (PLF) is a new proteomic analysis method, capable of the non-targeted identification of structure-associated changes within proteins. Here we applied PLF to publicly available ageing human IVD (outer annulus fibrosus), ageing mouse lung and human arterial atherosclerosis datasets and bioinformatically identified novel target proteins alongside common age-associated differences within protein structures which were conserved between three ECM-rich organs, two species, three IVD tissue regions, sexes and in an age-related disease. We identify peptide yield differences across protein structures which coincide with biological regions, potentially reflecting the functional consequences of ageing or atherosclerosis for macromolecular assemblies (collagen VI), enzyme/inhibitor activity (alpha-2 macroglobulin), activation states (complement C3) and interaction states (laminins, perlecan, fibronectin, filamin-A, collagen XIV and apolipoprotein-B). Furthermore, we show that alpha-2 macroglobulin and collagen XIV exhibit possible shared structural consequences in IVD ageing and arterial atherosclerosis, providing novel links between an age-related disease and intrinsic ageing. Crucially, we also demonstrate that fibronectin, laminin beta chains and filamin-A all exhibit conserved age-associated structural differences between mouse lung and human IVD, providing evidence that ECM, and their associating proteins, may be subjected to potentially similar mechanisms or consequences of ageing across both species, irrespective of differences in lifespan and tissue function.

Improving Statistical Certainty of Glycosylation Similarity between Influenza A Virus Variants Using Data-Independent Acquisition Mass Spectrometry

Amino acid sequences of immunodominant domains of hemagglutinin (HA) on the surface of influenza A virus (IAV) evolve rapidly, producing viral variants. HA mediates receptor recognition, binding and cell entry, and serves as the target for IAV vaccines. Glycosylation, a post-translational modification that places large branched polysaccharide molecules on proteins, can modulate the function of HA and shield antigenic regions allowing for viral evasion from immune responses. Our previous work showed that subtle changes in the HA protein sequence can have a measurable change in glycosylation. Thus, being able to quantitatively measure glycosylation changes in variants is critical for understanding how HA function may change throughout viral evolution. Moreover, understanding quantitatively how the choice of viral expression systems affects glycosylation can help in the process of vaccine design and manufacture. Although IAV vaccines are most commonly expressed in chicken eggs, cell-based vaccines have many advantages, and the adoption of more cell-based vaccines would be an important step in mitigating seasonal influenza and protecting against future pandemics. Here, we have investigated the use of data-independent acquisition (DIA) mass spectrometry for quantitative glycoproteomics. We found that DIA improved the sensitivity of glycopeptide detection for four variants of A/Switzerland/9715293/2013 (H3N2): WT and mutant, each expressed in embryonated chicken eggs and Madin-Darby canine kidney cells. We used the Tanimoto similarity metric to quantify changes in glycosylation between WT and mutant and between egg-expressed and cell-expressed virus. Our DIA site-specific glycosylation similarity comparison of WT and mutant expressed in eggs confirmed our previous analysis while achieving greater depth of coverage. We found that sequence variations and changing viral expression systems affected distinct glycosylation sites of HA. Our methods can be applied to track glycosylation changes in circulating IAV variants to bolster genomic surveillance already being done, for a more complete understanding of IAV evolution.

Glycan-Lectin Interactions as Novel Immunosuppression Drivers in Glioblastoma

Despite diagnostic and therapeutic improvements, glioblastoma (GB) remains one of the most threatening brain tumor in adults, underlining the urgent need of new therapeutic targets. Lectins are glycan-binding proteins that regulate several biological processes through the recognition of specific sugar motifs. Lectins and their ligands are found on immune cells, endothelial cells and, also, tumor cells, pointing out a strong correlation among immunity, tumor microenvironment and vascularization. In GB, altered glycans and lectins contribute to tumor progression and immune evasion, shaping the tumor-immune landscape promoting immunosuppressive cell subsets, such as myeloid-derived suppressor cells (MDSCs) and M2-macrophages, and affecting immunoeffector populations, such as CD8⁺ T cells and dendritic cells (DCs). Here, we discuss the latest knowledge on the immune cells, immune related lectin receptors (C-type lectins, Siglecs, galectins) and changes in glycosylation that are involved in immunosuppressive mechanisms in GB, highlighting their interest as possible novel therapeutical targets.