Label-free quantitative proteomics unravels the importance of RNA processing in glioma malignancy

FBXO22 promotes HCC angiogenesis and metastasis via RPS5/AKT/HIF-1α/VEGF-A signaling axis

The gene F-box only protein 22 (FBXO22) has been discovered to promote the development of liver cancer tumors. Nevertheless, there remains considerable ambiguity regarding the involvement of FBXO22 in the processes of angiogenesis and metastasis in hepatocellular carcinoma (HCC). Our study has confirmed a significant upregulation of FBXO22 expression in both HCC samples and cellular models. The increased level of FBXO22 correlates strongly with the number of tumors, presence of vascular invasion, and poor prognosis. Experimental investigations have shown that FBXO22 significantly enhances angiogenesis and metastasis of HCC both in vitro and in vivo. Mechanistically, FBXO22 interacts with and ubiquitinates 40S ribosomal protein S5 (RPS5) on Lys85, thereby promoting its K48-linked ubiquitin-mediated degradation in the cytoplasm. Following a decrease in the expression of RPS5, activation of downstream PI3K/AKT signaling pathway occurs, leading to elevated levels of HIF-1α and vascular endothelial growth factor A (VEGF-A). Our study has shown that FBXO22 facilitates HCC angiogenesis and metastasis via the RPS5/AKT/HIF-1α/VEGF-A signaling axis. Notably, inhibition of FBXO22 enhances the efficacy of Lenvatinib both in vitro and in vivo. Therefore, FBXO22 may present itself as a potential target for therapeutic intervention in the treatment of HCC.

Expression and prognostic value of ferritinophagy-related NCOA4 gene in low-grade glioma: integration of bioinformatics and experimental validation

BACKGROUND

Low-grade glioma (LGG) is a primary brain tumor with relatively low malignancy. NCOA4 is a key regulator of ferritinophagy-related processes and is involved in the occurrence and development of many cancers. However, the role of NCOA4 in LGG remains poorly understood.

METHODS

This study comprehensively analyzed several mainstream bioinformatics databases to explore the expression, diagnostic efficacy, clinical pathological features, immune infiltration, prognostic value, and biological functions of NCOA4 in LGG. Immunohistochemistry experiments were conducted using LGG tissue samples collected from our hospital to validate the bioinformatics analysis results.

RESULTS

NCOA4 expression was significantly elevated in LGG (p < 0.05), with an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.973, suggesting it as a potential diagnostic marker. High NCOA4 expression was associated with younger age (21-40 years), lower malignancy (oligodendroglioma), and better prognosis (IDHmut-non-codel and IDHmut-codel subtypes) (all p < 0.05) in LGG. Kaplan-Meier survival curves from three databases showed that high NCOA4-expressing LGG patients had better prognosis (all p < 0.05). NCOA4 correlated weakly with B cells, CD8 + T cells, macrophages, and dendritic cells infiltration (all with correlation coefficients r < 0.3, and p < 0.05) in LGG. Multivariate Cox regression identified NCOA4, age, CD8 T cells, and macrophages as LGG independent prognostic factors (all p < 0.05). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that NCOA4's primary function in LGG is related to autophagy processes (all p < 0.05).

CONCLUSION

Our findings suggest that NCOA4 could be a potential prognostic marker and therapeutic target in LGG.

Proteomic Analysis on Sequential Samples of Cystic Fluid Obtained from Human Brain Tumors

Cystic formation in human primary brain tumors is a relatively rare event whose incidence varies widely according to the histotype of the tumor. Composition of the cystic fluid has mostly been characterized in samples collected at the time of tumor resection and no indications of the evolution of cystic content are available. We characterized the evolution of the proteome of cystic fluid using a bottom-up proteomic approach on sequential samples obtained from secretory meningioma (SM), cystic schwannoma (CS) and cystic high-grade glioma (CG). We identified 1008 different proteins; 74 of these proteins were found at least once in the cystic fluid of all tumors. The most abundant proteins common to all tumors studied derived from plasma, with the exception of prostaglandin D2 synthase, which is a marker of cerebrospinal fluid origin. Overall, the protein composition of cystic fluid obtained at different times from the same tumor remained stable. After the identification of differentially expressed proteins (DEPs) and the protein-protein interaction network analysis, we identified the presence of tumor-specific pathways that may help to characterize tumor-host interactions. Our results suggest that plasma proteins leaking from local blood-brain barrier disruption are important contributors to cyst fluid formation, but cerebrospinal fluid (CSF) and the tumor itself also contribute to the cystic fluid proteome and, in some cases, as with immunoglobulin G, shows tumor-specific variations that cannot be simply explained by differences in vessel permeability or blood contamination.

Recognition of a Novel Gene Signature for Human Glioblastoma

Glioblastoma (GBM) is one of the most common malignant and incurable brain tumors. The identification of a gene signature for GBM may be helpful for its diagnosis, treatment, prediction of prognosis and even the development of treatments. In this study, we used the GSE108474 database to perform GSEA and machine learning analysis, and identified a 33-gene signature of GBM by examining astrocytoma or non-GBM glioma differential gene expression. The 33 identified signature genes included the overexpressed genes COL6A2, ABCC3, COL8A1, FAM20A, ADM, CTHRC1, PDPN, IBSP, MIR210HG, GPX8, MYL9 and PDLIM4, as well as the underexpressed genes CHST9, CSDC2, ENHO, FERMT1, IGFN1, LINC00836, MGAT4C, SHANK2 and VIPR2. Protein functional analysis by CELLO2GO implied that these signature genes might be involved in regulating various aspects of biological function, including anatomical structure development, cell proliferation and adhesion, signaling transduction and many of the genes were annotated in response to stress. Of these 33 signature genes, 23 have previously been reported to be functionally correlated with GBM; the roles of the remaining 10 genes in glioma development remain unknown. Our results were the first to reveal that GBM exhibited the overexpressed GPX8 gene and underexpressed signature genes including CHST9, CSDC2, ENHO, FERMT1, IGFN1, LINC00836, MGAT4C and SHANK2, which might play crucial roles in the tumorigenesis of different gliomas.

The role of proteomics in the multiplexed analysis of gene alterations in human cancer

INTRODUCTION

Proteomics has played a pivotal role in identifying proteins perturbed in disease conditions when compared with healthy samples. Study of dysregulated proteins aids in identifying diagnostic markers and potential therapeutic targets. Cancer is an outcome of interplay of several such disarrayed proteins and molecular pathways which perturb cellular homeostasis, resulting in transformation. In this review, we discuss various facets of proteomic approaches, including tools and technological advancements, aiding in understanding differentially expressed molecules and signaling mechanisms.

AREAS COVERED

In this review, we have taken the approach of documenting the different methods of proteomic studies, ranging from labeling techniques, data analysis methods, and the nature of molecule detected. We summarize each technique and provide a glimpse of cancer research carried out using them, highlighting the advantages and drawbacks in comparison with others. Literature search using online resources, such as PubMed and Google Scholar were carried out for this approach.

EXPERT OPINION

Technological advancements in proteomics studies have come a long way from the study of two-dimensional mapping of proteins separated on gels in the early 1970s. Higher precision in molecular identification and quantification (high throughput), and greater number of samples analyzed have been the focus of researchers.

The Big Picture of Glioblastoma Malignancy: A Meta-Analysis of Glioblastoma Proteomics to Identify Altered Biological Pathways

Glioblastoma is a highly malignant cancer with no effective treatment. It is vital to elucidate the mechanisms which drive glioblastoma in order to identify therapeutic targets. The differences in protein expression between glioblastoma, grade I-III glioma, and normal brain tissue reflect the functional alterations driving malignancy. However, proteomic analysis of glioblastoma has been hampered by the heterogeneity of glioblastoma and the variety of methodology used in its study. To reduce these inconsistencies, we performed a meta-analysis of the literature published since 2015, including 14 datasets from eight papers comparing the whole proteome of glioblastoma to normal brain or grade I-III glioma. We found that 154 proteins were commonly upregulated and 116 proteins were commonly downregulated in glioblastoma compared to normal brain. Meanwhile, 240 proteins were commonly upregulated and 125 proteins were commonly downregulated in glioblastoma compared to grade I-III glioma. Functional enrichment analysis revealed upregulation of proteins involved in mRNA splicing and the immune system and downregulation of proteins involved in synaptic signaling and glucose and glutamine metabolism. The identification of these altered biological pathways provides a basis for deeper investigation in the pursuit of an effective treatment for glioblastoma.

Latent TGF-β Activation Is a Hallmark of the Tenascin Family

Transforming growth factor-β (TGF-β) isoforms are secreted as inactive complexes formed through non-covalent interactions between bioactive TGF-β entities and their N-terminal pro-domains called latency-associated peptides (LAP). Extracellular activation of latent TGF-β within this complex is a crucial step in the regulation of TGF-β activity for tissue homeostasis and immune cell function. We previously showed that the matrix glycoprotein Tenascin-X (TN-X) interacted with the small latent TGF-β complex and triggered the activation of the latent cytokine into a bioactive TGF-β. This activation most likely occurs through a conformational change within the latent TGF-β complex and requires the C-terminal fibrinogen-like (FBG) domain of the glycoprotein. As the FBG-like domain is highly conserved among the Tenascin family members, we hypothesized that Tenascin-C (TN-C), Tenascin-R (TN-R) and Tenascin-W (TN-W) might share with TN-X the ability to regulate TGF-β bioavailability through their C-terminal domain. Here, we demonstrate that purified recombinant full-length Tenascins associate with the small latent TGF-β complex through their FBG-like domains. This association promotes activation of the latent cytokine and subsequent TGF-β cell responses in mammary epithelial cells, such as cytostasis and epithelial-to-mesenchymal transition (EMT). Considering the pleiotropic role of TGF-β in numerous physiological and pathological contexts, our data indicate a novel common function for the Tenascin family in the regulation of tissue homeostasis under healthy and pathological conditions.

Putting Proteomics Into Immunotherapy for Glioblastoma

In glioblastoma, the most aggressive brain cancer, a complex microenvironment of heterogeneity and immunosuppression, are considerable hurdles to classify the subtypes and promote treatment progression. Treatments for glioblastoma are similar to standard therapies for many other cancers and do not effectively prolong the survival of patients, due to the unique location and heterogeneous characteristics of glioblastoma. Immunotherapy has shown a promising effect for many other tumors, but its application for glioma still has some challenges. The recent breakthrough of high-throughput liquid chromatography-mass spectrometry (LC-MS/MS) systems has allowed researchers to update their strategy for identifying and quantifying thousands of proteins in a much shorter time with lesser effort. The protein maps can contribute to generating a complete map of regulatory systems to elucidate tumor mechanisms. In particular, newly developed unicellular proteomics could be used to determine the microenvironment and heterogeneity. In addition, a large scale of differentiated proteins provides more ways to precisely classify tumor subtypes and construct a larger library for biomarkers and biotargets, especially for immunotherapy. A series of advanced proteomic studies have been devoted to the different aspects of immunotherapy for glioma, including monoclonal antibodies, oncolytic viruses, dendritic cell (DC) vaccines, and chimeric antigen receptor (CAR) T cells. Thus, the application of proteomics in immunotherapy may accelerate research on the treatment of glioblastoma. In this review, we evaluate the frontline applications of proteomics strategies for immunotherapy in glioblastoma research.

In silico molecular target prediction unveils mebendazole as a potent MAPK14 inhibitor

The concept of polypharmacology involves the interaction of drug molecules with multiple molecular targets. It provides a unique opportunity for the repurposing of already-approved drugs to target key factors involved in human diseases. Herein, we used an in silico target prediction algorithm to investigate the mechanism of action of mebendazole, an antihelminthic drug, currently repurposed in the treatment of brain tumors. First, we confirmed that mebendazole decreased the viability of glioblastoma cells in vitro (IC₅₀ values ranging from 288 nm to 2.1 µm). Our in silico approach unveiled 21 putative molecular targets for mebendazole, including 12 proteins significantly upregulated at the gene level in glioblastoma as compared to normal brain tissue (fold change > 1.5; P < 0.0001). Validation experiments were performed on three major kinases involved in cancer biology: ABL1, MAPK1/ERK2, and MAPK14/p38α. Mebendazole could inhibit the activity of these kinases in vitro in a dose-dependent manner, with a high potency against MAPK14 (IC₅₀  = 104 ± 46 nm). Its direct binding to MAPK14 was further validated in vitro, and inhibition of MAPK14 kinase activity was confirmed in live glioblastoma cells. Consistent with biophysical data, molecular modeling suggested that mebendazole was able to bind to the catalytic site of MAPK14. Finally, gene silencing demonstrated that MAPK14 is involved in glioblastoma tumor spheroid growth and response to mebendazole treatment. This study thus highlighted the role of MAPK14 in the anticancer mechanism of action of mebendazole and provides further rationale for the pharmacological targeting of MAPK14 in brain tumors. It also opens new avenues for the development of novel MAPK14/p38α inhibitors to treat human diseases.

A Panel of Synapse-Related Genes as a Biomarker for Gliomas

Gliomas are the most common primary brain cancers. In recent years, IDH mutation and 1p/19q codeletion have been suggested as biomarkers for the diagnosis, treatment, and prognosis of gliomas. However, these biomarkers are only effective for a part of glioma patients, and thus more biomarkers are still emergently needed. Recently, an electrochemical communication between normal neurons and glioma cells by neuro-glioma synapse has been reported. Moreover, it was discovered that breast-to-brain metastasis tumor cells have pseudo synapses with neurons, and these synapses were indicated to promote tumor progression and metastasis. Based on the above observations, we first curated a panel of 17 synapse-related genes and then proposed a metric, synapse score to quantify the "stemness" for each sample of 12 glioma gene expression datasets from TCGA, CGGA, and GEO. Strikingly, synapse score showed excellent predictive ability for the prognosis, diagnosis, and grading of gliomas. Moreover, being compared with the two established biomarkers, IDH mutation and 1p/19q codeletion, synapse score demonstrated independent and better predictive performance. In conclusion, this study proposed a quantitative method, synapse score, as an efficient biomarker for monitoring gliomas.

Glioma tumor proteomics: clinically useful protein biomarkers and future perspectives

Introduction: Despite being rare cancers, gliomas account for a significant number of cancer-related deaths. Identification and treatment of these tumors at an early stage would greatly improve the therapeutic outcomes. There is an urgent need for diagnostic and prognostic markers, which can identify disease early and discriminate the subtypes of these tumors thereby improving the existing treatment modalities.Areas covered: In this article, we have reviewed published literature on proteomics biomarkers for gliomas and their importance in diagnosis or prognosis. Proteomic studies for the discovery of protein, autoantibody biomarkers, and biological pathway alterations in serum, CSF and tumor biopsies have been discussed in this review.Expert opinion: The rapid development in the field of mass spectrometry and increased sensitivity and reproducibility in assays has led to the identification and quantification of large number of proteins very precisely. Though genomic markers are the prime focus in the classification of gliomas, incorporating protein markers would further improve the existing classification. In this regard, data mining and studies on large cohorts of glioma patients would help in the identification of diagnostic and prognostic markers ultimately translating to the clinics.

Proteomic Advances in Glial Tumors through Mass Spectrometry Approaches

Being the fourth leading cause of cancer-related death, glial tumors are highly diverse tumor entities characterized by important heterogeneity regarding tumor malignancy and prognosis. However, despite the identification of important alterations in the genome of the glial tumors, there remains a gap in understanding the mechanisms involved in glioma malignancy. Previous research focused on decoding the genomic alterations in these tumors, but due to intricate cellular mechanisms, the genomic findings do not correlate with the functional proteins expressed at the cellular level. The development of mass spectrometry (MS) based proteomics allowed researchers to study proteins expressed at the cellular level or in serum that may provide new insights on the proteins involved in the proliferation, invasiveness, metastasis and resistance to therapy in glial tumors. The integration of data provided by genomic and proteomic approaches into clinical practice could allow for the identification of new predictive, diagnostic and prognostic biomarkers that will improve the clinical management of patients with glial tumors. This paper aims to provide an updated review of the recent proteomic findings, possible clinical applications, and future research perspectives in diffuse astrocytic and oligodendroglial tumors, pilocytic astrocytomas, and ependymomas.

A proteomic network approach across the ALS-FTD disease spectrum resolves clinical phenotypes and genetic vulnerability in human brain

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are neurodegenerative diseases with overlap in clinical presentation, neuropathology, and genetic underpinnings. The molecular basis for the overlap of these disorders is not well established. We performed a comparative unbiased mass spectrometry‐based proteomic analysis of frontal cortical tissues from postmortem cases clinically defined as ALS, FTD, ALS and FTD (ALS/FTD), and controls. We also included a subset of patients with the C9orf72 expansion mutation, the most common genetic cause of both ALS and FTD. Our systems‐level analysis of the brain proteome integrated both differential expression and co‐expression approaches to assess the relationship of these differences to clinical and pathological phenotypes. Weighted co‐expression network analysis revealed 15 modules of co‐expressed proteins, eight of which were significantly different across the ALS‐FTD disease spectrum. These included modules associated with RNA binding proteins, synaptic transmission, and inflammation with cell‐type specificity that showed correlation with TDP‐43 pathology and cognitive dysfunction. Modules were also examined for their overlap with TDP‐43 protein–protein interactions, revealing one module enriched with RNA‐binding proteins and other causal ALS genes that increased in FTD/ALS and FTD cases. A module enriched with astrocyte and microglia proteins was significantly increased in ALS cases carrying the C9orf72 mutation compared to sporadic ALS cases, suggesting that the genetic expansion is associated with inflammation in the brain even without clinical evidence of dementia. Together, these findings highlight the utility of integrative systems‐level proteomic approaches to resolve clinical phenotypes and genetic mechanisms underlying the ALS‐FTD disease spectrum in human brain.

RNA processing as an alternative route to attack glioblastoma

Genomic analyses have become an important tool to identify new avenues for therapy. This is especially true for cancer types with extremely poor outcomes, since our lack of effective therapies offers no tangible clinical starting point to build upon. The highly malignant brain tumor glioblastoma (GBM) exemplifies such a refractory cancer, with only 15 month average patient survival. Analyses of several hundred GBM samples compiled by the TCGA (The Cancer Genome Atlas) have produced an extensive transcriptomic map, identified prevalent chromosomal alterations, and defined important driver mutations. Unfortunately, clinical trials based on these results have not yet delivered an improvement on outcome. It is, therefore, necessary to characterize other regulatory routes known for playing a role in tumor relapse and response to treatment. Alternative splicing affects more than 90% of the human coding genes and it is an important source for transcript variation and gene regulation. Mutations and alterations in splicing factors are highly prevalent in multiple cancers, demonstrating the potential for splicing to act as a tumor driver. As a result, numerous genes are expressed as cancer-specific splicing isoforms that are functionally distinct from the canonical isoforms found in normal tissue. These include genes that regulate cancer-critical pathways such as apoptosis, DNA repair, cell proliferation, and migration. Splicing defects can even induce genomic instability, a common characteristic of cancer, and a driver of tumor evolution. Importantly, components of the splicing machinery are targetable; multiple drugs can inhibit splicing factors or promote changes in splicing which could be exploited to begin improving clinical outcomes. Here, we review the current literature and present a case for exploring RNA processing as therapeutic route for the treatment of GBM.