Landscape of surfaceome and endocytome in human glioma is divergent and depends on cellular spatial organization

Tumor suppressor role of the complement inhibitor CSMD1 and its role in TNF-induced neuroinflammation in gliomas

BACKGROUND

The complement inhibitor CSMD1 acts as a tumor suppressor in various types of solid cancers. Despite its high level of expression in the brain, its function in gliomas, malignant brain tumors originating from glial cells, has not been investigated.

METHODS

Three cohorts of glioma patients comprising 1500 patients were analyzed in our study along with their clinical data. H4, U-118 and U-87 cell lines were used to investigate the tumor suppressor function of CSMD1 in gliomas. PDGFB-induced brain tumor model was utilized for the validation of in vitro data.

RESULTS

The downregulation of CSMD1 expression correlated with reduced overall and disease-free survival, elevated tumor grade, wild-type IDH genotype, and intact 1p/19q status. Moreover, enhanced activity was noted in the neuroinflammation pathway. Importantly, ectopic expression of CSMD1 in glioma cell lines led to decreased aggressiveness in vitro. Mechanically, CSMD1 obstructed the TNF-induced NF-kB and STAT3 signaling pathways, effectively suppressing the secretion of IL-6 and IL-8. There was also reduced survival in PDGFB-induced brain tumors in mice when Csmd1 was downregulated.

CONCLUSIONS

Our study has identified CSMD1 as a tumor suppressor in gliomas and elucidated its role in TNF-induced neuroinflammation, contributing to a deeper understanding of glioma pathogenesis.

APOBEC3C is a novel target for the immune treatment of lower-grade gliomas

BACKGROUND

Apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) type 3C (A3C) has been identified as a cancer molecular biomarker in the past decade. However, the practical role of A3C in lower-grade gliomas (LGGs) in improving the clinical outcome remains unclear. This study aims to discuss the function of A3C in immunotherapy in LGGs.

METHODS

The RNA-Sequencing (RNA-seq) and corresponding clinical data were extracted from UCSC Xena and the results were verified in the Chinese Glioma Genome Atlas (CGGA). Weighted gene co-expression network analysis (WGCNA) was used for screening A3C-related genes. Comprehensive bioinformation analyses were performed and multiple levels of expression, survival rate, and biological functions were assessed to explore the functions of A3C.

RESULTS

A3C expression was significantly higher in LGGs than in normal tissues but lower than in glioblastoma (GBM), indicating its role as an independent prognosis predictor for LGGs. Twenty-eight A3C-related genes were found with WGCNA for unsupervised clustering analysis and three modification patterns with different outcomes and immune cell infiltration were identified. A3C and the A3C score were also correlated with immune cell infiltration and the expression of immune checkpoints. In addition, the A3C score was correlated with increased sensitivity to chemotherapy. Single-cell RNA (scRNA) analysis indicated that A3C most probably expresses on immune cells, such as T cells, B cells and macrophage.

CONCLUSIONS

A3C is an immune-related prognostic biomarker in LGGs. Developing drugs to block A3C could enhance the efficiency of immunotherapy and improve disease survival.Abbreviation: A3C: Apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) type 3C; LGGs: lower-grade gliomas; CGGA: Chinese Glioma Genome Atlas; WGCNA: Weighted gene co-expression network analysis; scRNA: Single-cell RNA; HGG: higher-grade glioma; OS: overall survival; TME: tumor microenvironment; KM: Kaplan-Meier; PFI: progression-free interval; IDH: isocitrate dehydrogenase; ROC: receiver operating characteristic; GS: gene significance; MM: module membership; TIMER: Tumor IMmune Estimation Resource; GSVA: gene set variation analysis; ssGSEA: single-sample gene-set enrichment analysis; PCA: principal component analysis; AUC: area under ROC curve; HAVCR2: hepatitis A virus cellular receptor 2; PDCD1: programmed cell death 1; PDCD1LG2: PDCD1 ligand 2; PTPRC: protein tyrosine phosphatase receptor type C; ACC: Adrenocortical carcinoma; BLCA: Bladder Urothelial Carcinoma;BRCA: Breast invasive carcinoma; CESC: Cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOLCholangiocarcinoma; COADColon adenocarcinoma; DLBC: Lymphoid Neoplasm Diffuse Large B-cell Lymphoma; ESCA: Esophageal carcinoma; GBM: Glioblastoma multiforme; HNSC: Head and Neck squamous cell carcinoma; KICH: Kidney Chromophobe; KIRC: Kidney renal clear cell carcinoma; KIRP: Kidney renal papillary cell carcinoma; LAML: Acute Myeloid Leukemia; LGG: Brain Lower Grade Glioma; LIHC: Liver hepatocellular carcinoma; LUAD: Lung adenocarcinoma; LUSC: Lung squamous cell carcinoma; MESO: Mesothelioma; OV: Ovarian serous cystadenocarcinoma; PAAD: Pancreatic adenocarcinoma; PCPG: Pheochromocytoma and Paraganglioma; PRAD: Prostate adenocarcinoma; READ: Rectum adenocarcinoma; SARC: Sarcoma; SKCM: Skin Cutaneous Melanoma; STAD: Stomach adenocarcinoma; TGCT: Testicular Germ Cell Tumors; THCA: Thyroid carcinoma; THYM: Thymoma; UCEC: Uterine Corpus Endometrial Carcinoma; UCS: Uterine Carcinosarcoma; UVM: Uveal Melanoma.

Decoding of the surfaceome and endocytome in primary glioblastoma cells identifies potential target antigens in the hypoxic tumor niche

Immunotherapies with antibody-drug-conjugates (ADC) and CAR-T cells, targeted at tumor surface antigens (surfaceome), currently revolutionize clinical oncology. However, target identification warrants a better understanding of the surfaceome and how it is modulated by the tumor microenvironment. Here, we decode the surfaceome and endocytome and its remodeling by hypoxic stress in glioblastoma (GBM), the most common and aggressive brain tumor in adults. We employed a comprehensive approach for global and dynamic profiling of the surfaceome and endocytosed (endocytome) proteins and their regulation by hypoxia in patient-derived GBM cultures. We found a heterogeneous surface-endocytome profile and a divergent response to hypoxia across GBM cultures. We provide a quantitative ranking of more than 600 surface resident and endocytosed proteins, and their regulation by hypoxia, serving as a resource to the cancer research community. As proof-of-concept, the established target antigen CD44 was identified as a commonly and abundantly expressed surface protein with high endocytic activity. Among hypoxia induced proteins, we reveal CXADR, CD47, CD81, BSG, and FXYD6 as potential targets of the stressed GBM niche. We could validate these findings by immunofluorescence analyses in patient tumors and by increased expression in the hypoxic core of GBM spheroids. Selected candidates were finally confronted by treatment studies, showing their high capacity for internalization and ADC delivery. Importantly, we highlight the limited correlation between transcriptomics and proteomics, emphasizing the critical role of membrane protein enrichment strategies and quantitative mass spectrometry. Our findings provide a comprehensive understanding of the surface-endocytome and its remodeling by hypoxia in GBM as a resource for exploration of targets for immunotherapeutic approaches in GBM.

Mass spectrometry-based methods for investigating the dynamics and organization of the surfaceome: exploring potential clinical implications

INTRODUCTION

Cell-surface proteins are extremely important for many cellular events, such as regulating cell-cell communication and cell-matrix interactions. Aberrant alterations in surface protein expression, modification (especially glycosylation), and interactions are directly related to human diseases. Systematic investigation of surface proteins advances our understanding of protein functions, cellular activities, and disease mechanisms, which will lead to identifying surface proteins as disease biomarkers and drug targets.

AREAS COVERED

In this review, we summarize mass spectrometry (MS)-based proteomics methods for global analysis of cell-surface proteins. Then, investigations of the dynamics of surface proteins are discussed. Furthermore, we summarize the studies for the surfaceome interaction networks. Additionally, biological applications of MS-based surfaceome analysis are included, particularly highlighting the significance in biomarker identification, drug development, and immunotherapies.

EXPERT OPINION

Modern MS-based proteomics provides an opportunity to systematically characterize proteins. However, due to the complexity of cell-surface proteins, the labor-intensive workflow, and the limit of clinical samples, comprehensive characterization of the surfaceome remains extraordinarily challenging, especially in clinical studies. Developing and optimizing surfaceome enrichment methods and utilizing automated sample preparation workflow can expand the applications of surfaceome analysis and deepen our understanding of the functions of cell-surface proteins.

sBioSITe enables sensitive identification of the cell surface proteome through direct enrichment of biotinylated peptides

BACKGROUND

Cell surface proteins perform critical functions related to immune response, signal transduction, cell-cell interactions, and cell migration. Expression of specific cell surface proteins can determine cell-type identity, and can be altered in diseases including infections, cancer and genetic disorders. Identification of the cell surface proteome remains a challenge despite several enrichment methods exploiting their biochemical and biophysical properties.

METHODS

Here, we report a novel method for enrichment of proteins localized to cell surface. We developed this new approach designated surface Biotinylation Site Identification Technology (sBioSITe) by adapting our previously published method for direct identification of biotinylated peptides. In this strategy, the primary amine groups of lysines on proteins on the surface of live cells are first labeled with biotin, and subsequently, biotinylated peptides are enriched by anti-biotin antibodies and analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS).

RESULTS

By direct detection of biotinylated lysines from PC-3, a prostate cancer cell line, using sBioSITe, we identified 5851 peptides biotinylated on the cell surface that were derived from 1409 proteins. Of these proteins, 533 were previously shown or predicted to be localized to the cell surface or secreted extracellularly. Several of the identified cell surface markers have known associations with prostate cancer and metastasis including CD59, 4F2 cell-surface antigen heavy chain (SLC3A2) and adhesion G protein-coupled receptor E5 (CD97). Importantly, we identified several biotinylated peptides derived from plectin and nucleolin, both of which are not annotated in surface proteome databases but have been shown to have aberrant surface localization in certain cancers highlighting the utility of this method.

CONCLUSIONS

Detection of biotinylation sites on cell surface proteins using sBioSITe provides a reliable method for identifying cell surface proteins. This strategy complements existing methods for detection of cell surface expressed proteins especially in discovery-based proteomics approaches.

Glioblastoma survival is associated with distinct proteomic alteration signatures post chemoirradiation in a large-scale proteomic panel

Background

Glioblastomas (GBM) are rapidly progressive, nearly uniformly fatal brain tumors. Proteomic analysis represents an opportunity for noninvasive GBM classification and biological understanding of treatment response.

Purpose

We analyzed differential proteomic expression pre vs. post completion of concurrent chemoirradiation (CRT) in patient serum samples to explore proteomic alterations and classify GBM by integrating clinical and proteomic parameters.

Materials and methods

82 patients with GBM were clinically annotated and serum samples obtained pre- and post-CRT. Serum samples were then screened using the aptamer-based SOMAScan® proteomic assay. Significant traits from uni- and multivariate Cox models for overall survival (OS) were designated independent prognostic factors and principal component analysis (PCA) was carried out. Differential expression of protein signals was calculated using paired t-tests, with KOBAS used to identify associated KEGG pathways. GSEA pre-ranked analysis was employed on the overall list of differentially expressed proteins (DEPs) against the MSigDB Hallmark, GO Biological Process, and Reactome databases with weighted gene correlation network analysis (WGCNA) and Enrichr used to validate pathway hits internally.

Results

3 clinical clusters of patients with differential survival were identified. 389 significantly DEPs pre vs. post-treatment were identified, including 284 upregulated and 105 downregulated, representing several pathways relevant to cancer metabolism and progression. The lowest survival group (median OS 13.2 months) was associated with DEPs affiliated with proliferative pathways and exhibiting distinct oppositional response including with respect to radiation therapy related pathways, as compared to better-performing groups (intermediate, median OS 22.4 months; highest, median OS 28.7 months). Opposite signaling patterns across multiple analyses in several pathways (notably fatty acid metabolism, NOTCH, TNFα via NF-κB, Myc target V1 signaling, UV response, unfolded protein response, peroxisome, and interferon response) were distinct between clinical survival groups and supported by WGCNA. 23 proteins were statistically signficant for OS with 5 (NETO2, CST7, SEMA6D, CBLN4, NPS) supported by KM.

Conclusion

Distinct proteomic alterations with hallmarks of cancer, including progression, resistance, stemness, and invasion, were identified in serum samples obtained from GBM patients pre vs. post CRT and corresponded with clinical survival. The proteome can potentially be employed for glioma classification and biological interrogation of cancer pathways.

An Assessment of the Penile Squamous Cell Carcinoma Surfaceome for Biomarker and Therapeutic Target Discovery

Penile squamous cell carcinoma (PSCC) is a rare malignancy in most parts of the world and the underlying mechanisms of this disease have not been fully investigated. About 30-50% of cases are associated with high-risk human papillomavirus (HPV) infection, which may have prognostic value. When PSCC becomes resistant to upfront therapies there are limited options, thus further research is needed in this venue. The extracellular domain-facing protein profile on the cell surface (i.e., the surfaceome) is a key area for biomarker and drug target discovery. This research employs computational methods combined with cell line translatomic (n = 5) and RNA-seq transcriptomic data from patient-derived tumors (n = 18) to characterize the PSCC surfaceome, evaluate the composition dependency on HPV infection, and explore the prognostic impact of identified surfaceome candidates. Immunohistochemistry (IHC) was used to validate the localization of select surfaceome markers. This analysis characterized a diverse surfaceome within patient tumors with 25% and 18% of the surfaceome represented by the functional classes of receptors and transporters, respectively. Significant differences in protein classes were noted by HPV status, with the most change being seen in transporter proteins (25%). IHC confirmed the robust surface expression of select surfaceome targets in the top 85% of expression and a superfamily immunoglobulin protein called BSG/CD147 was prognostic of survival. This study provides the first description of the PSCC surfaceome and its relation to HPV infection and sets a foundation for novel biomarker and drug target discovery in this rare cancer.

Mechanisms of a Mycobacterium tuberculosis Active Peptide

Multidrug-resistant tuberculosis (MDR) continues to pose a threat to public health. Previously, we identified a cationic host defense peptide with activity against Mycobacterium tuberculosis in vivo and with a bactericidal effect against MDR M. tuberculosis at therapeutic concentrations. To understand the mechanisms of this peptide, we investigated its interactions with live M. tuberculosis and liposomes as a model. Peptide interactions with M. tuberculosis inner membranes induced tube-shaped membranous structures and massive vesicle formation, thus leading to bubbling cell death and ghost cell formation. Liposomal studies revealed that peptide insertion into inner membranes induced changes in the peptides' secondary structure and that the membranes were pulled such that they aggregated without permeabilization, suggesting that the peptide has a strong inner membrane affinity. Finally, the peptide targeted essential proteins in M. tuberculosis, such as 60 kDa chaperonins and elongation factor Tu, that are involved in mycolic acid synthesis and protein folding, which had an impact on bacterial proliferation. The observed multifaceted targeting provides additional support for the therapeutic potential of this peptide.

Proteoglycans: a common portal for SARS-CoV-2 and extracellular vesicle uptake

As structural components of the glycocalyx, heparan sulfate proteoglycans (HSPGs) are involved in multiple pathophysiological processes at the apex of cell signaling cascades, and as endocytosis receptors for particle structures, such as lipoproteins, extracellular vesicles, and enveloped viruses, including SARS-CoV-2. Given their diversity and complex biogenesis regulation, HSPGs remain understudied. Here we compile some of the latest studies focusing on HSPGs as internalizing receptors of extracellular vesicles ("endogenous virus") and SARS-CoV-2 lipid-enclosed particles and highlight similarities in their biophysical and structural characteristics. Specifically, the similarities in their biogenesis, size, and lipid composition may explain a common dependence on HSPGs for efficient cell-surface attachment and uptake. We further discuss the relative complexity of extracellular vesicle composition and the viral mechanisms that evolve towards increased infectivity that complicate therapeutic strategies addressing blockade of their uptake.