A Cell-Surface Membrane Protein Signature for Glioblastoma

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.

The Pivotal Function of SLC16A1 and SLC16A1-AS1 in Cancer Progress: Molecular Pathogenesis and Prognosis

More than 300 membranes make up the SLC family of transporters, utilizing an ion gradient or electrochemical potential difference to move their substrates across biological membranes. The SLC16 gene family contains fourteen members. Proton-linked transportation of monocarboxylates can be promoted by the transporters MCT1, which the SLC16A1 gene family encodes. Glycolysis is constitutively up-regulated in cancer cells, and the amount of lactate produced as a result is correlated with prognosis. Further speaking, SLC16A1 plays an essential role in controlling the growth and spread of tumors, according to mounting evidence. Additionally, LncRNAs are the collective term for all genes that produce RNA transcripts longer than 200 nucleotides but do not convert into proteins. It has steadily developed into a hub for research, offering an innovative approach to tumor study as technology related to molecular biology advances. The growing study has uncovered SLC16A1-AS1, an RNA that acts as an antisense to SLC16A1, which is erroneously expressed in various types of cancers. Therefore, we compiled the most recent information on the physiological functions and underlying processes of SLC16A1 and the LncRNA SLC16A1-AS1 during tumor development to explore their impact on cancer treatment and prognosis. We compiled the most recent information on the physiological functions and underlying processes of SLC16A1 and the LncRNA SLC16A1-AS1 during tumor development to explore their impact on cancer treatment and prognosis. Relevant studies were retrieved and collected through the PubMed system. After determining SLC16A1 and SLC16A1-AS1 as the research object, we found a close relationship between SLC16A1 and tumorigenesis as well as the influencing factors through the analysis of the research articles. SLC16A1 regulates lactate chemotaxis while uncovering SLC16A1- AS1 as an antisense RNA acting through multiple pathways; they affect the metabolism of tumor cells and have an impact on the prognosis of patients with various cancers.

Tumor-suppressive function and mechanism of miR-873-5p in glioblastoma: evidence based on bioinformatics analysis and experimental validation

This study aims to clarify the mechanistic actions of microRNA-873-5p (miR-873-5p) on glioblastoma (GBM) progression. The most differentially expressed miRNAs were retrieved from the GEO database. It was established that miR-873-5p was downregulated in GBM tissues and cells. Based on in silico prediction and experimental data, HMOX1 was demonstrated to be a target gene of miR-873-5p. Further, miR-873-5p was then ectopically expressed in GBM cells to examine its effect on the malignant behaviors of GBM cells. Overexpression of miR-873-5p inhibited GBM cell proliferation and invasion by targeting HMOX1. HMOX1 promoted SPOP expression by increasing HIF1α expression, thus stimulating GBM cell malignant phenotypes. miR-873-5p suppressed the malignant phenotypes of GBM cells and tumorigenesis in vitro and in vivo by inhibiting the HMOX1/HIF1α/SPOP signaling axis. This study uncovers a novel miR-873-5p/HMOX1/HIF1α/SPOP axis in GBM, providing new insights into GBM progression and therapeutic targets for GBM treatment.

Impact of Solute Carrier Transporters in Glioma Pathology: A Comprehensive Review

Solute carriers (SLCs) are essential for brain physiology and homeostasis due to their role in transporting necessary substances across cell membranes. There is an increasing need to further unravel their pathophysiological implications since they have been proposed to play a pivotal role in brain tumor development, progression, and the formation of the tumor microenvironment (TME) through the upregulation and downregulation of various amino acid transporters. Due to their implication in malignancy and tumor progression, SLCs are currently positioned at the center of novel pharmacological targeting strategies and drug development. In this review, we discuss the key structural and functional characteristics of the main SLC family members involved in glioma pathogenesis, along with their potential targeting options to provide new opportunities for CNS drug design and more effective glioma management.

Neural Stem Cells as Potential Glioblastoma Cells of Origin

Glioblastoma multiforme (GBM) is the most malignant brain tumor in adults and it remains incurable. These tumors are very heterogeneous, resistant to cytotoxic therapies, and they show high rates of invasiveness. Therefore, patients face poor prognosis, and the survival rates remain very low. Previous research states that GBM contains a cell population with stem cell characteristics called glioma stem cells (GSCs). These cells are able to self-renew and regenerate the tumor and, therefore, they are partly responsible for the observed resistance to therapies and tumor recurrence. Recent data indicate that neural stem cells (NSCs) in the subventricular zone (SVZ) are the cells of origin of GBM, that is, the cell type acquiring the initial tumorigenic mutation. The involvement of SVZ-NSCs is also associated with GBM progression and recurrence. Identifying the cellular origin of GBM is important for the development of early detection techniques and the discovery of early disease markers. In this review, we analyze the SVZ-NSC population as a potential GBM cell of origin, and its potential role for GBM therapies.

Directional preference for glioblastoma cancer cell membrane encapsulated nanoparticle population: A probabilistic approach for cancer therapeutics

Background

Selective cancer cell recognition is the most challenging objective in the targeted delivery of anti-cancer agents. Extruded specific cancer cell membrane coated nanoparticles, exploiting the potential of homotypic binding along with certain protein-receptor interactions, have recently proven to be the method of choice for targeted delivery of anti-cancer drugs. Prediction of the selective targeting efficiency of the cancer cell membrane encapsulated nanoparticles (CCMEN) is the most critical aspect in selecting this strategy as a method of delivery.

Materials and methods

A probabilistic model based on binding scores and differential expression levels of Glioblastoma cancer cells (GCC) membrane proteins (factors and receptors) was implemented on python 3.9.1. Conditional binding efficiency (CBE) was derived for each combination of protein involved in the interactions. Selective propensities and Odds ratios in favour of cancer cells interactions were determined for all the possible combination of surface proteins for ‘k’ degree of interaction. The model was experimentally validated by two types of Test cultures.

Results

Several Glioblastoma cell surface antigens were identified from literature and databases. Those were screened based on the relevance, availability of expression levels and crystal structure in public databases. High priority eleven surface antigens were selected for probabilistic modelling. A new term, Break-even point (BEP) was defined as a characteristic of the typical cancer cell membrane encapsulated delivery agents. The model predictions lie within ±7% of the experimentally observed values for both experimental test culture types.

Conclusion

The implemented probabilistic model efficiently predicted the directional preference of the exposed nanoparticle coated with cancer cell membrane (in this case GCC membrane). This model, however, is developed and validated for glioblastoma, can be easily tailored for any type of cancer involving CCMEN as delivery agents for potential cancer immunotherapy. This probabilistic model would help in the development of future cancer immunotherapeutic with greater specificity.

Nucleic acid drug vectors for diagnosis and treatment of brain diseases

Nucleic acid drugs have the advantages of rich target selection, simple in design, good and enduring effect. They have been demonstrated to have irreplaceable superiority in brain disease treatment, while vectors are a decisive factor in therapeutic efficacy. Strict physiological barriers, such as degradation and clearance in circulation, blood-brain barrier, cellular uptake, endosome/lysosome barriers, release, obstruct the delivery of nucleic acid drugs to the brain by the vectors. Nucleic acid drugs against a single target are inefficient in treating brain diseases of complex pathogenesis. Differences between individual patients lead to severe uncertainties in brain disease treatment with nucleic acid drugs. In this Review, we briefly summarize the classification of nucleic acid drugs. Next, we discuss physiological barriers during drug delivery and universal coping strategies and introduce the application methods of these universal strategies to nucleic acid drug vectors. Subsequently, we explore nucleic acid drug-based multidrug regimens for the combination treatment of brain diseases and the construction of the corresponding vectors. In the following, we address the feasibility of patient stratification and personalized therapy through diagnostic information from medical imaging and the manner of introducing contrast agents into vectors. Finally, we take a perspective on the future feasibility and remaining challenges of vector-based integrated diagnosis and gene therapy for brain diseases.

Detection of pan-cancer surface protein biomarkers via a network-based approach on transcriptomics data

Cell surface proteins have been used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. Many of these proteins lie at the top of signaling cascades regulating cell responses and gene expression, therefore acting as ‘signaling hubs’. It has been previously demonstrated that the integrated network analysis on transcriptomic data is able to infer cell surface protein activity in breast cancer. Such an approach has been implemented in a publicly available method called ‘SURFACER’. SURFACER implements a network-based analysis of transcriptomic data focusing on the overall activity of curated surface proteins, with the final aim to identify those proteins driving major phenotypic changes at a network level, named surface signaling hubs. Here, we show the ability of SURFACER to discover relevant knowledge within and across cancer datasets. We also show how different cancers can be stratified in surface-activity-specific groups. Our strategy may identify cancer-wide markers to design targeted therapies and biomarker-based diagnostic approaches.

LRIG2 promotes glioblastoma progression by modulating innate antitumor immunity through macrophage infiltration and polarization

Background

Glioblastoma (GBM) is the most common malignant brain tumor with poor clinical outcomes. Immunotherapy has recently been an attractive and promising treatment of extracranial malignancies, however, most of clinical trials for GBM immunotherapy failed due to predominant accumulation of tumor-associated microglia/macrophages (TAMs).

Results

High level of LRIG2/soluble LRIG2 (sLRIG2) expression activates immune-related signaling pathways, which are associated with poor prognosis in GBM patients. LRIG2/sLRIGs promotes CD47 expression and facilitates TAM recruitment. Blockade of CD47–SIRPα interactions and inhibition of sLRIG2 secretion synergistically suppress GBM progression in an orthotropic murine GBM model.

Conclusions

GBM cells with high level LRIG2 escape the phagocytosis by TAM via the CD47-SIRPα axis, highlighting a necessity for an early stage of clinical trial targeting LRIG2 and CD47-SIRPα as a novel treatment for patients with GBM.

Genome-Wide Association Study Identifies Multiple Susceptibility Loci for Malignant Neoplasms of the Brain in Taiwan

Primary brain malignancy is a rare tumor with a global incidence of less than 10 per 100,000 people. Hence, there is limited power for identifying risk loci in individual studies, especially for Han Chinese. We performed a genome-wide association study (GWAS) in Taiwan, including 195 cases and 195 controls. We identified five new genes for malignant neoplasms of the brain: EDARADD (rs645507, 1p31.3, p = 7.71 × 10⁻⁵, odds ratio (OR) = 1.893), RBFOX1 (rs8044700, p = 2.35 × 10⁻⁵, OR = 2.36), LMF1 (rs3751667, p = 7.24 × 10⁻⁷, OR = 2.17), DPP6 (rs67433368, p = 8.32 × 10⁻⁵, OR = 3.94), and NDUFB9 (rs7827791, p = 9.73 × 10⁻⁶, OR = 4.42). These data support that genetic susceptibility toward GBM or non-GBM tumors is highly distinct, likely reflecting different etiologies. Combined with signaling analysis, we found that RNA modification may be related to major risk factors in primary malignant neoplasms of the brain.

Integrative analysis of cell adhesion molecules in glioblastoma identified prostaglandin F2 receptor inhibitor (PTGFRN) as an essential gene

Background

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults exhibiting infiltration into surrounding tissues, recurrence, and resistance to therapy. GBM infiltration is accomplished by many deregulated factors such as cell adhesion molecules (CAMs), which are membrane proteins that participate in cell-cell and cell-ECM interactions to regulate survival, proliferation, migration, and stemness.

Methods

A comprehensive bioinformatics analysis of CAMs (n = 518) in multiple available datasets revealed genetic and epigenetic alterations among CAMs in GBM. Univariate Cox regression analysis using TCGA dataset identified 127 CAMs to be significantly correlated with survival. The poor prognostic indicator PTGFRN was chosen to study its role in glioma. Silencing of PTGFRN in glioma cell lines was achieved by the stable expression of short hairpin RNA (shRNA) against the PTGFRN gene. PTGFRN was silenced and performed cell growth, migration, invasion, cell cycle, and apoptosis assays. Neurosphere and limiting dilution assays were also performed after silencing of PTGFRN in GSCs.

Results

Among the differentially regulated CAMs (n = 181, 34.9%), major proportion of them were found to be regulated by miRNAs (n = 95, 49.7%) followed by DNA methylation (n = 32, 16.7%), and gene copy number variation (n = 12, 6.2%). We found that PTGFRN to be upregulated in GBM tumor samples and cell lines with a significant poor prognostic correlation with patient survival. Silencing PTGFRN diminished cell growth, colony formation, anchorage-independent growth, migration, and invasion and led to cell cycle arrest and induction of apoptosis. At the mechanistic level, silencing of PTGFRN reduced pro-proliferative and promigratory signaling pathways such as ERK, AKT, and mTOR. PTGFRN upregulation was found to be due to the loss of its promoter methylation and downregulation of miR-137 in GBM. PTGFRN was also found to be higher in glioma stem-like cells (GSCs) than the matched differentiated glioma cells (DGCs) and is required for GSC growth and survival. Silencing of PTGFRN in GSCs reduced transcript levels of reprogramming factors (Olig2, Pou3f2, Sall2, and Sox2).

Conclusion

In this study, we provide a comprehensive overview of the differential regulation of CAMs and the probable causes for their deregulation in GBM. We also establish an oncogenic role of PTGFRN and its regulation by miR-137 in GBM, thus signifying it as a potential therapeutic target.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09682-2.

Heme Oxygenase-1 targeting exosomes for temozolomide resistant glioblastoma synergistic therapy

Glioblastoma (GBM) is a highly fatal and recurrent brain cancer without a complete prevailing remedy. Although the synthetic nanotechnology-based approaches exhibit excellent therapeutic potential, the associated cytotoxic effects and organ clearance failure rest major obstacles from bench to clinics. Here, we explored allogeneic bone marrow mesenchymal stem cells isolated exosomes (BMSC_Exo) decorated with heme oxygenase-1 (HMOX1) specific short peptide (HSSP) as temozolomide (TMZ) and small interfering RNA (siRNA) nanocarrier for TMZ resistant glioblastoma therapy. The BMSC_Exo had excellent TMZ and siRNA loading ability and could traverse the blood-brain barrier (BBB) by leveraging its intrinsic brain accumulation property. Notably, with HSSP decoration, the TMZ or siRNA encapsulated BMSC_Exo exhibited excellent TMZ resistant GBM targeting ability both in vitro and in vivo due to the overexpression of HMOX1 in TMZ resistant GBM cells. Further, the HSSP decorated BMSC_Exo delivered the STAT3 targeted siRNA to the TMZ resistant glioma and restore the TMZ sensitivity, consequently achieved the synergistically drug resistant GBM treatment with TMZ. Our results showed this biomimetic nanoplatform can serve as a flexible, robust and inert system for GBM treatment, especially emphasizing the drug resistant challenge.

Glucose Influences the Response of Glioblastoma Cells to Temozolomide and Dexamethasone

Objective

Current research indicates that weakness of glucose metabolism plays an important role in silencing of invasiveness and growth of hypoxic tumors such as GBM. Moreover, there are indications that DXM, frequently used in treatment, may support GBM energy metabolism and provoke its recurrence.

Methods

We carried out in vitro experiments on the commercial T98G cell line and two primary GBM lines (HROG02, HROG17) treated with TMZ and/or DXM in physiological oxygen conditions for GBM (2.5% oxygen) and for comparison, in standard laboratory conditions (20% oxygen). The influence of different glucose levels on selected malignancy features of GBM cells-cellular viability and division, dynamic of cell culture changes, colony formation and concentration of InsR have been elevated.

Results

Under 2.5% oxygen and high glucose concentration, an attenuated cytotoxic effect of TMZ and intensification of malignancy features in all glioblastoma cell lines exposed to DXM was seen. Furthermore, preliminary retrospective analysis to assess the correlation between serum glucose levels and Ki-67 expression in surgical specimens derived from patients with GBM (IV) treated with radio-chemotherapy and prophylactic DXM therapy was performed.

Conclusion

The data suggest a link between the in vitro study results and clinical data. High glucose can influence on GBM progression through the promotion of the following parameters: cell viability, dispersal, InsR expression and cell proliferation (Ki-67). However, this problem needs more studies and explain the mechanism of action studied drugs.

Quantifying protein abundance on single cells using split-pool sequencing on DNA-barcoded antibodies for diagnostic applications

Proteins play critical roles across all facets of biology, with their abundance frequently used as markers of cell identity and state. The most popular method for detecting proteins on single cells, flow cytometry, is limited by considerations of fluorescent spectral overlap. While mass cytometry (CyTOF) allows for the detection of upwards of 40 epitopes simultaneously, it requires local access to specialized instrumentation not commonly accessible to many laboratories. To overcome these limitations, we independently developed a method to quantify multiple protein targets on single cells without the need for specialty equipment other than access to widely available next generation sequencing (NGS) services. We demonstrate that this combinatorial indexing method compares favorably to traditional flow-cytometry, and allows over two dozen target proteins to be assayed at a time on single cells. To showcase the potential of the technique, we analyzed peripheral blood and bone marrow aspirates from human clinical samples, and identified pathogenic cellular subsets with high fidelity. The ease of use of this technique makes it a promising technology for high-throughput proteomics and for interrogating complex samples such as those from patients with leukemia.

Targeted Extracellular Vesicles Delivered Verrucarin A to Treat Glioblastoma

Glioblastomas, accounting for approximately 50% of gliomas, comprise the most aggressive, highly heterogeneous, and malignant brain tumors. The objective of this study was to develop and evaluate a new targeted therapy, i.e., highly potent natural compound verrucarin A (Ver-A), delivered with monoclonal antibody-directed extracellular vesicle (mAb-EV). First, the high surface expression of epidermal growth factor receptor (EGFR) in glioblastoma patient tissue and cell lines was confirmed using immunohistochemistry staining, flow cytometry, and Western blotting. mAb-EV-Ver-A was constructed by packing Ver-A and tagging anti-EGFR mAb to EV generated from HEK293F culture. Confocal microscopy and the In Vivo Imaging System demonstrated that mAb-EV could penetrate the blood-brain barrier, target intracranial glioblastoma xenografts, and deliver drug intracellularly. The in vitro cytotoxicity study showed IC50 values of 2-12 nM of Ver-A. The hematoxylin and eosin staining of major organs in the tolerated dose study indicated minimal systemic toxicity of mAb-EV-Ver-A. Finally, the in vivo anti-tumor efficacy study in intracranial xenograft models demonstrated that EGFR mAb-EV-Ver-A effectively inhibited glioblastoma growth, but the combination with VEGF mAb did not improve the therapeutic efficacy. This study suggested that mAb-EV is an effective drug delivery vehicle and natural Ver-A has great potential to treat glioblastoma.

Membrane Bound Peroxiredoxin-1 Serves as a Biomarker for In Vivo Detection of Sessile Serrated Adenomas

Aim: Sessile serrated adenomas (SSAs) are premalignant lesions driven by the BRAF^V600E mutation to give rise to colorectal cancers (CRCs). They are often missed during white light colonoscopy because of their subtle appearance. Previously, a fluorescently labeled 7mer peptide KCCFPAQ was shown to detect SSAs in vivo. We aim to identify the target of this peptide. Results: Peroxiredoxin-1 (Prdx1) was identified as the binding partner of the peptide ligand. In vitro binding assays and immunofluorescence staining of human colon specimens ex vivo supported this result. Prdx1 was overexpressed on the membrane of cells with the BRAF^V600E mutation, and this effect was dependent on oxidative stress. RKO cells harboring the BRAF^V600E mutation and human SSA specimens showed higher oxidative stress as well as elevated levels of Prdx1 on the cell membrane. Innovation and Conclusion: These results suggest that Prdx1 is overexpressed on the cell surface in the presence of oxidative stress and can serve as an imaging biomarker for in vivo detection of SSAs. Antioxid. Redox Signal. 36, 39-56.

The Cancer Surfaceome Atlas integrates genomic, functional and drug response data to identify actionable targets

Cell-surface proteins (SPs) are a rich source of immune and targeted therapies. By systematically integrating single-cell and bulk genomics, functional studies and target actionability, in the present study we comprehensively identify and annotate genes encoding SPs (GESPs) pan-cancer. We characterize GESP expression patterns, recurrent genomic alterations, essentiality, receptor-ligand interactions and therapeutic potential. We also find that mRNA expression of GESPs is cancer-type specific and positively correlates with protein expression, and that certain GESP subgroups function as common or specific essential genes for tumor cell growth. We also predict receptor-ligand interactions substantially deregulated in cancer and, using systems biology approaches, we identify cancer-specific GESPs with therapeutic potential. We have made this resource available through the Cancer Surfaceome Atlas ( http://fcgportal.org/TCSA ) within the Functional Cancer Genome data portal.

Integration of RNA-Seq and proteomics data identifies glioblastoma multiforme surfaceome signature

Background

Glioblastoma multiforme (GBM) is a highly lethal, stage IV brain tumour with a prevalence of approximately 2 per 10,000 people globally. The cell surface proteins or surfaceome serve as information gateway in many oncogenic signalling pathways and are important in modulating cancer phenotypes. Dysregulation in surfaceome expression and activity have been shown to promote tumorigenesis. The expression of GBM surfaceome is a case in point; OMICS screening in a cell-based system identified that this sub-proteome is largely perturbed in GBM. Additionally, since these cell surface proteins have ‘direct’ access to drugs, they are appealing targets for cancer therapy. However, a comprehensive GBM surfaceome landscape has not been fully defined yet. Thus, this study aimed to define GBM-associated surfaceome genes and identify key cell-surface genes that could potentially be developed as novel GBM biomarkers for therapeutic purposes.

Methods

We integrated the RNA-Seq data from TCGA GBM (n = 166) and GTEx normal brain cortex (n = 408) databases to identify the significantly dysregulated surfaceome in GBM. This was followed by an integrative analysis that combines transcriptomics, proteomics and protein-protein interaction network data to prioritize the high-confidence GBM surfaceome signature.

Results

Of the 2381 significantly dysregulated genes in GBM, 395 genes were classified as surfaceome. Via the integrative analysis, we identified 6 high-confidence GBM molecular signature, HLA-DRA, CD44, SLC1A5, EGFR, ITGB2, PTPRJ, which were significantly upregulated in GBM. The expression of these genes was validated in an independent transcriptomics database, which confirmed their upregulated expression in GBM. Importantly, high expression of CD44, PTPRJ and HLA-DRA is significantly associated with poor disease-free survival. Last, using the Drugbank database, we identified several clinically-approved drugs targeting the GBM molecular signature suggesting potential drug repurposing.

Conclusions

In summary, we identified and highlighted the key GBM surface-enriched repertoires that could be biologically relevant in supporting GBM pathogenesis. These genes could be further interrogated experimentally in future studies that could lead to efficient diagnostic/prognostic markers or potential treatment options for GBM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08591-0.

Targeted Mass Spectrometry-Based Approach for the Determination of Intrinsic Internalization Kinetics of Cell-Surface Membrane Protein Targets

Successful development of targeted therapeutics aimed at the elimination of diseased cells relies on the target properties and the therapeutics that target them. Currently, target properties have been evaluated through antibody-dependent semiquantitative approaches such as flow cytometry, Western blotting, or microscopy. Since antibodies can alter target properties following binding, antibody-dependent approaches provide at best skewed measurements for target intrinsic properties. To circumvent, here we attempted to develop an antibody-free targeted mass spectrometry-based (ATM) strategy to measure the surface densities and the intrinsic rates (K_int) of CD38 internalization in multiple myeloma cell lines. Using cell-surface biotinylation in conjunction with differential mass tagging to separate inward CD38 molecules from the outbound and nascent ones, the ATM approach revealed diversities in measured CD38 K_int values of 0.239 min^-1 S.E. ± 0.076, 0.109 min^-1 S.E. ± 0.032, and 0.058 min^-1 S.E. ± 0.001 for LP1, NCIH929, and MOLP8 cell lines, respectively. Together with CD38 surface densities, intrinsic K_int values aligned well with the tumor penetration model and supported the outcomes for tumor regression in mouse xenografts upon drug treatment. Additionally, the ATM approach can evaluate molecules with fast K_int as we determined for CTLA4 protein. We believe that the ATM approach has the potential to evaluate diverse cell-surface targets as part of the pharmacological assessment in drug discovery.

Emerging methods in biomarker identification for extracellular vesicle-based liquid biopsy

Extracellular vesicles (EVs) are released by many cell types and distributed within various biofluids. EVs have a lipid membrane-confined structure that allows for carrying unique molecular information originating from their parent cells. The species and quantity of EV cargo molecules, including nucleic acids, proteins, lipids, and metabolites, may vary largely owing to their parent cell types and the pathophysiologic status. Such heterogeneity in EV populations provides immense challenges to researchers, yet allows for the possibility to prognosticate the pathogenesis of a particular tissue from unique molecular signatures of dispersing EVs within biofluids. However, the inherent nature of EV's small size requires advanced methods for EV purification and evaluation from the complex biofluid. Recently, the interdisciplinary significance of EV research has attracted growing interests, and the EV analytical platforms for their diagnostic prospect have markedly progressed. This review summarizes the recent advances in these EV detection techniques and methods with the intention of translating an EV-based liquid biopsy into clinical practice. This article aims to present an overview of current EV assessment techniques, with a focus on their progress and limitations, as well as an outlook on the clinical translation of an EV-based liquid biopsy that may augment current paradigms for the diagnosis, prognosis, and monitoring the response to therapy in a variety of disease settings.

Carbonic Anhydrase XII is a Clinically Significant, Molecular Tumor-Subtype Specific Therapeutic Target in Glioma with the Potential to Combat Invasion of Brain Tumor Cells

Background

The metabolic enzyme carbonic anhydrase 12 (CA12/CAXII) emerges as a promising cancer therapeutic target with drug development projects underway. Previous reports proposed the relevance of CA12 in the context of glioma but are limited in patient data quantity, ignore ethnic diversity of patients or rely on semi-quantitative, thereby out of date, methodology. Moreover, little is known on the association of CA12 to brain tumor stemness or on the effect of anti-CAXII-directed monotherapies on glioma stem cells (GSCs), in particular their response regarding mesenchymal differentiation status.

Methods

We performed in silico analysis on three independent, large-scale patient datasets interrogating state of the art molecular diagnostics alongside clinical outcomes. We analyzed CAXII abundance on a collection of GSCs and functionally tested their response to exposure to CAXII blocking antibody 6A10.

Results

CA12 is highly expressed in glial tumors compared with normal tissue and predicts for poor clinical course of tumor patients. CA12 expression in glioblastoma significantly correlates with clinically established, molecular markers of IDH1^WT DNA, WHO grade IV or absence of 1p/19q chromosome arm co-deletion. Furthermore, tumors with elevated CA12 cluster into the mesenchymal transcription subclass of the disease. CAXII abundance in different GSCs ranges from almost absent to high levels and does not correlate to stem cell marker CD133/AC133 cell surface expression. Moreover, aiming to pharmacologically block CAXII in our cells with antibody 6A10 caused significant functional response only in one of the tested GSCs models, featuring suppression of cell invasion accompanied by reduction of ZEB1 protein and other stem cell markers.

Conclusion

CA12 represents a clinically relevant and molecular brain tumor-subtype specific therapeutic target. Our correlative data from experimental and clinical samples does not support CA12/CAXII to be GSC specific. 6A10 possesses promising potential to impede the invasive capacity of glioma cells and supports the emerging concept that CAXII interacts with cancer EMT programs. However, further mechanistic studies are required to comprehensively assess the therapeutic potential of 6A10 and to identify different resistance mechanisms of GSCs.

Overexpression of Cell-Surface Marker SLC16A1 Shortened Survival in Human High-Grade Gliomas

Solute carrier family 16 member 1 (SLC16A1) is a crucial transcription factor in modifying cancer progression and metastasis. However, its character in defining the clinical prognosis of human gliomas has not been illuminated. In our analysis from PREdiction of Clinical Outcomes from Genomic Profiles (PRECOG), The Cancer Genome Atlas (TCGA), and Chinese Glioma Genome Atlas (CGGA), we found that SLC16A1 mRNA expression level was significantly increased in high-grade gliomas in contrast to low-grade gliomas and non-tumor controls (P < 0.05). Kaplan-Meier analysis of four independent cohort studies from the Gene Expression Omnibus (GEO) profile, TCGA, and CGGA which consistently presented patients with high SLC16A1 mRNA expression displayed poor overall survival in high-grade glioma patients (P < 0.05 by log-rank test). Based on the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), the protein-protein interaction analysis of SLC16A1-regulated oncogenesis showed SLC16A1 as a potential hub protein. Immunohistochemical staining exhibited that SLC16A1 protein overexpressed in high-grade gliomas compared with low-grade clinical glioma samples. All these findings suggest that SLC16A1 expression has a positive correlation with WHO pathological grading and poor survival. SLC16A1 might be a potential biomarker of prognosis in human gliomas.

Glioblastoma Immunotherapy Targeting the Innate Immune Checkpoint CD47-SIRPα Axis

Glioblastoma Multiforme (GBM) is the most common and aggressive form of intracranial tumors with poor prognosis. In recent years, tumor immunotherapy has been an attractive strategy for a variety of tumors. Currently, most immunotherapies take advantage of the adaptive anti-tumor immunity, such as cytotoxic T cells. However, the predominant accumulation of tumor-associated microglia/macrophages (TAMs) results in limited success of these strategies in the glioblastoma. To improve the immunotherapeutic efficacy for GBM, it is detrimental to understand the role of TAM in glioblastoma immunosuppressive microenvironment. In this review, we will discuss the roles of CD47-SIRPα axis in TAMs infiltration and activities and the promising effects of targeting this axis on the activation of both innate and adaptive antitumor immunity in glioblastoma.

Pattern-recognition-based Sensor Arrays for Cell Characterization: From Materials and Data Analyses to Biomedical Applications

To capture a broader scope of complex biological phenomena, alternatives to conventional sensing based on specificity for cell detection and characterization are needed. Pattern-recognition-based sensing is an analytical method designed to mimic mammalian sensory systems for analyte identification based on the pattern recognition of multivariate data, which are generated using an array of multiple probes that cross-reactively interact with analytes. This sensing approach is significantly different from conventional specific cell sensing based on highly specific probes, including antibodies against biomarkers. Encouraged by the advantages of this technique, such as the simplicity, rapidity, and tunability of the systems without requiring a priori knowledge of biomarkers, numerous sensor arrays have been developed over the past decade and used in a variety of cell sensing applications; these include disease diagnosis, drug discovery, and fundamental research. This review summarizes recent progress in pattern-recognition-based cell sensing, with a particular focus on guidelines for designing materials and arrays, techniques for analyzing response patterns, and applications of sensor systems that are focused primarily for the biomedical field.

Finding the Keys to the CAR: Identifying Novel Target Antigens for T Cell Redirection Immunotherapies

Oncology immunotherapy has been a significant advancement in cancer treatment and involves harnessing and redirecting a patient’s immune response towards their own tumour. Specific recognition and elimination of tumour cells was first proposed over a century ago with Paul Erlich’s ‘magic bullet’ theory of therapy. In the past decades, targeting cancer antigens by redirecting T cells with antibodies using either bispecific T cell engagers (BiTEs) or chimeric antigen receptor (CAR) T cell therapy has achieved impressive clinical responses. Despite recent successes in haematological cancers, linked to a high and uniformly expressed CD19 antigen, the efficacy of T cell therapies in solid cancers has been disappointing, in part due to antigen escape. Targeting heterogeneous solid tumours with T cell therapies will require the identification of novel tumour specific targets. These targets can be found among a range of cell-surface expressed antigens, including proteins, glycolipids or carbohydrates. In this review, we will introduce the current tumour target antigen classification, outline existing approaches to discover novel tumour target antigens and discuss considerations for future design of antibodies with a focus on their use in CAR T cells.

A Serum Proteomic Signature Predicting Survival in Patients with Glioblastoma

Purpose

Glioblastoma (GBM) is the most common form of brain tumor and has a uniformly poor prognosis. Development of prognostic biomarkers in easily accessible serum samples have the potential to improve the outcomes of patients with GBM through personalized therapy planning.

Material/Methods

In this study pre-treatment serum samples from 30 patients newly diagnosed with GBM were evaluated using a 40-protein multiplex ELISA platform. Analysis of potentially relevant gene targets using The Cancer Genome Atlas database was done using the Glioblastoma Bio Discovery Portal (GBM-BioDP). A ten-biomarker subgroup of clinically relevant molecules was selected using a functional grouping analysis of the 40 plex genes with two genes selected from each group on the basis of degree of variance, lack of co-linearity with other biomarkers and clinical interest. A Multivariate Cox proportional hazard approach was used to analyze the relationship between overall survival (OS), gene expression, and resection status as covariates.

Results

Thirty of 40 of the MSD molecules mapped to known genes within TCGA and separated the patient cohort into two main clusters centered predominantly around a grouping of classical and proneural versus the mesenchymal subtype as classified by Verhaak. Using the values for the 30 proteins in a prognostic index (PI) demonstrated that patients in the entire cohort with a PI below the median lived longer than those patients with a PI above the median (HR 1.8, p=0.001) even when stratified by both age and MGMT status. This finding was also consistent within each Verhaak subclass and highly significant (range p=0.0001-0.011). Additionally, a subset of ten proteins including, CRP, SAA, VCAM1, VEGF, MDC, TNFA, IL7, IL8, IL10, IL16 were found to have prognostic value within the TCGA database and a positive correlation with overall survival in GBM patients who had received gross tumor resection followed by conventional radiation therapy and temozolomide treatment concurrent with the addition of valproic acid.

Conclusion

These findings demonstrate that proteomic approaches to the development of prognostic assays for treatment of GBM may hold potential clinical value.

Methods for Systematic Identification of Membrane Proteins for Specific Capture of Cancer-Derived Extracellular Vesicles

Analysis of cancer-derived extracellular vesicles (EVs) in biofluids potentially provides a source of disease biomarkers. At present there is no procedure to systematically identify which antigens should be targeted to differentiate cancer-derived from normal host cell-derived EVs. Here, we propose a computational framework that integrates information about membrane proteins in tumors and normal tissues from databases: UniProt, The Cancer Genome Atlas, the Genotype-Tissue Expression Project, and the Human Protein Atlas. We developed two methods to assess capture of EVs from specific cell types. (1) We used palmitoylated fluorescent protein (palmtdTomato) to label tumor-derived EVs. Beads displaying antibodies of interest were incubated with conditioned medium from palmtdTomato-expressing cells. Bound EVs were quantified using flow cytometry. (2) We also showed that membrane-bound Gaussia luciferase allows the detection of cancer-derived EVs in blood of tumor-bearing animals. Our analytical and validation platform should be applicable to identify antigens on EVs from any tumor type.

Deciphering the complex role of thrombospondin-1 in glioblastoma development

We undertook a systematic study focused on the matricellular protein Thrombospondin-1 (THBS1) to uncover molecular mechanisms underlying the role of THBS1 in glioblastoma (GBM) development. THBS1 was found to be increased with glioma grades. Mechanistically, we show that the TGFβ canonical pathway transcriptionally regulates THBS1, through SMAD3 binding to the THBS1 gene promoter. THBS1 silencing inhibits tumour cell invasion and growth, alone and in combination with anti-angiogenic therapy. Specific inhibition of the THBS1/CD47 interaction using an antagonist peptide decreases cell invasion. This is confirmed by CD47 knock-down experiments. RNA sequencing of patient-derived xenograft tissue from laser capture micro-dissected peripheral and central tumour areas demonstrates that THBS1 is one of the gene with the highest connectivity at the tumour borders. All in all, these data show that TGFβ1 induces THBS1 expression via Smad3 which contributes to the invasive behaviour during GBM expansion. Furthermore, tumour cell-bound CD47 is implicated in this process.

Thrombospondin-1 (THSB1) is a component of the ECM with a role in regulating cancer development and tumour vasculature. Here, the authors show that TGF-beta-induced THBS1 expression contributes to the invasive behaviour of GBM cells and promotes resistance to antiangiogenic therapy partially through interaction with CD47.

Current Challenges and Opportunities in Treating Glioblastoma

Glioblastoma multiforme (GBM), the most common and aggressive primary brain tumor, has a high mortality rate despite extensive efforts to develop new treatments. GBM exhibits both intra- and intertumor heterogeneity, lending to resistance and eventual tumor recurrence. Large-scale genomic and proteomic analysis of GBM tumors has uncovered potential drug targets. Effective and “druggable” targets must be validated to embark on a robust medicinal chemistry campaign culminating in the discovery of clinical candidates. Here, we review recent developments in GBM drug discovery and delivery. To identify GBM drug targets, we performed extensive bioinformatics analysis using data from The Cancer Genome Atlas project. We discovered 20 genes, BOC, CLEC4GP1, ELOVL6, EREG, ESR2, FDCSP, FURIN, FUT8-AS1, GZMB, IRX3, LITAF, NDEL1, NKX3-1, PODNL1, PTPRN, QSOX1, SEMA4F, TH, VEGFC, and C20orf166AS1 that are overexpressed in a subpopulation of GBM patients and correlate with poor survival outcomes. Importantly, nine of these genes exhibit higher expression in GBM versus low-grade glioma and may be involved in disease progression. In this review, we discuss these proteins in the context of GBM disease progression. We also conducted computational multi-parameter optimization to assess the blood-brain barrier (BBB) permeability of small molecules in clinical trials for GBM treatment. Drug delivery in the context of GBM is particularly challenging because the BBB hinders small molecule transport. Therefore, we discuss novel drug delivery methods, including nanoparticles and prodrugs. Given the aggressive nature of GBM and the complexity of targeting the central nervous system, effective treatment options are a major unmet medical need. Identification and validation of biomarkers and drug targets associated with GBM disease progression present an exciting opportunity to improve treatment of this devastating disease.

MSI1 associates glioblastoma radioresistance via homologous recombination repair, tumor invasion and cancer stem-like cell properties

INTRODUCTION

Glioblastoma multiforme (GBM) is the most common brain malignancy in adults, and currently available GBM treatments present several unique challenges. It is known that GBM involves cancer stem-like cells (CSCs) and tumor cells that aggressively invade normal brain tissues, and both cell types may cause resistance to radiotherapy (RT) and are thus responsible for therapeutic failure. The radioresistance of GBM cells relies on the efficient activation of the DNA damage response (DDR), but the mechanisms linking this response with stem-cell status and tumor invasion remain unclear.

MATERIALS AND METHODS

We used irradiation to treat patient-derived GBM (Par) cells and then purified radioresistant GBM (R2M2) cells through two rounds of irradiation and an invasion assay. Musashi-1 (MSI1) is a neural stem-cell marker and key oncogenic factor of GBM. We identified MSI1 expression to predict radioresistance through silencing an MSI1-high-expressing R2M2 cell line or inducing overexpression in a Par cell line with low/no MSI1 expression and assessing the subsequent DDR.

RESULT

MSI1 enhances tumor invasion via VCAM1 and modulates GBM radioresistance via the hyperactivation of the DDR through increasing homologous recombination repair and evading apoptosis. MSI1 knockdown induces DNA damage accumulation in irradiated GBM cells and promotes their depletion in vitro; MSI1 knockdown also inhibits the formation of GBMs generated by irradiated xeno-transplanted cells. MSI1 inhibition may radiosensitize tumors, prevent CSC-positive selection induced by RT, and reduce tumor invasion.

CONCLUSION

MSI1 may involve in regulating GBM radioresistance, invasion, and recurrence and could be a novel target for GBM treatment.

Detecting and treating brain cancer

A systems biology approach identifies plasma biomarkers and potential therapeutic targets for patients with glioblastoma.