Potential serum biomarkers for glioblastoma diagnostic assessed by proteomic approaches

Diagnostic Accuracy of Ambient Mass Spectrometry with Blood Plasma in a Murine Glioma Model Using Machine Learning

OBJECTIVE

Malignant glioma progresses rapidly and shows poor prognosis, but clinically applicable blood plasma-based biochemical tumor markers remain lacking. This study aimed to develop a diagnostic system using probe electrospray ionization mass spectrometry (PESI-MS) and a machine-learning logistic regression model to detect plasma changes at various time points in a murine glioma model.

METHODS

We used a syngeneic intracranial orthotopic murine model with GL261 glioma cells. Blood plasmas were collected before and 3, 7, and 14 days after intracranial transplantation of glioma cells (tumor group, n = 7) or injection of phosphate-buffered saline (control group, n = 8). Mass spectra from those samples were obtained using PESI-MS and compared between control and tumor groups. We explored changes in mass spectra at the 3 time points (3, 7, and 14 days) after transplantation. The performance of machine-learning logistic regression-based diagnosis algorithm was evaluated to clarify the potential utility for early diagnosis.

RESULTS

Sixteen significant mass spectrum peaks were identified between the tumor and control groups. Multiple logistic regression analysis revealed 5 key mass spectra, achieving sensitivity of 0.875 and specificity of 0.943 for tumor discrimination. The area under the receiver operating characteristic curve was 0.981, outperforming analyses of individual spectra.

CONCLUSIONS

These results indicate that PESI-MS combined with machine learning-based diagnostics in blood plasma could be a promising approach to accurate detection of malignant glioma.

Proteomics of tumor and serum samples from isocitrate dehydrogenase-wildtype glioblastoma patients: is the detoxification of reactive oxygen species associated with shorter survival?

Proteomics has been little used for the identification of novel prognostic and/or therapeutic markers in isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GB). In this study, we analyzed 50 tumor and 30 serum samples from short- and long-term survivors of IDH-wildtype GB (STS and LTS, respectively) by data-independent acquisition mass spectrometry (DIA-MS)-based proteomics, with the aim of identifying such markers. DIA-MS identified 5422 and 826 normalized proteins in tumor and serum samples, respectively, with only three tumor proteins and 26 serum proteins displaying significant differential expression between the STS and LTS groups. These dysregulated proteins were principally associated with the detoxification of reactive oxygen species (ROS). In particular, GB patients in the STS group had high serum levels of malate dehydrogenase 1 (MDH1) and ribonuclease inhibitor 1 (RNH1) and low tumor levels of fatty acid-binding protein 7 (FABP7), which may have enabled them to maintain low ROS levels, counteracting the effects of the first-line treatment with radiotherapy plus concomitant and adjuvant temozolomide. A blood score built on the levels of MDH1 and RNH1 expression was found to be an independent prognostic factor for survival based on the serum proteome data for a cohort of 96 IDH-wildtype GB patients. This study highlights the utility of circulating MDH1 and RNH1 biomarkers for determining the prognosis of patients with IDH-wildtype GB. Furthermore, the pathways driven by these biomarkers, and the tumor FABP7 pathway, may constitute promising therapeutic targets for blocking ROS detoxification to overcome resistance to chemoradiotherapy in potential GB STS.

Serum CD133-Associated Proteins Identified by Machine Learning Are Connected to Neural Development, Cancer Pathways, and 12-Month Survival in Glioblastoma

Glioma is the most prevalent type of primary central nervous system cancer, while glioblastoma (GBM) is its most aggressive variant, with a median survival of only 15 months when treated with maximal surgical resection followed by chemoradiation therapy (CRT). CD133 is a potentially significant GBM biomarker. However, current clinical biomarker studies rely on invasive tissue samples. These make prolonged data acquisition impossible, resulting in increased interest in the use of liquid biopsies. Our study, analyzed 7289 serum proteins from 109 patients with pathology-proven GBM obtained prior to CRT using the aptamer-based SOMAScan® proteomic assay technology. We developed a novel methodology that identified 24 proteins linked to both serum CD133 and 12-month overall survival (OS) through a multi-step machine learning (ML) analysis. These identified proteins were subsequently subjected to survival and clustering evaluations, categorizing patients into five risk groups that accurately predicted 12-month OS based on their protein profiles. Most of these proteins are involved in brain function, neural development, and/or cancer biology signaling, highlighting their significance and potential predictive value. Identifying these proteins provides a valuable foundation for future serum investigations as validation of clinically applicable GBM biomarkers can unlock immense potential for diagnostics and treatment monitoring.

Platelet factor 4(PF4) and its multiple roles in diseases

Platelet factor 4 (PF4) combines with heparin to form an antigen that could produce IgG antibodies and participate in heparin-induced thrombocytopenia (HIT). PF4 has attracted wide attention due to its role in novel coronavirus vaccine-19 (COVID-9)-induced immune thrombotic thrombocytopenia (VITT) and cognitive impairments. The electrostatic interaction between PF4 and negatively charged molecules is vital in the progression of VITT, which is similar to HIT. Emerging evidence suggests its multiple roles in hematopoietic and angiogenic inhibition, platelet coagulation interference, host inflammatory response promotion, vascular inhibition, and antitumor properties. The emerging pharmacological effects of PF4 may help deepen the exploration of its mechanism, thus accelerating the development of targeted therapies. However, due to its pleiotropic properties, the development of drugs targeting PF4 is at an early stage and faces many challenges. Herein, we discussed the characteristics and biological functions of PF4, summarized PF4-mediated signaling pathways, and discussed its multiple roles in diseases to inform novel approaches for successful clinical translational research.

The duality of CXCR3 in glioblastoma: unveiling autocrine and paracrine mechanisms for novel therapeutic approaches

Glioblastoma (GBM) is a highly aggressive brain tumor associated with limited therapeutic options and a poor prognosis. CXCR3, a chemokine receptor, serves dual autocrine-paracrine functions in cancer. Despite gaps in our understanding of the functional role of the CXCR3 receptor in GBM, it has been shown to hold promise as a therapeutic target for the treatment of GBM. Existing clinical therapeutics and vaccines targeting CXCR3 ligand expression associated with the CXCR3 axes have also shown anti-tumorigenic effects in GBM. This review summarizes existing evidence on the oncogenic function of CXCR3 and its ligands CXCL9, CXCL10, and CXCL11, in GBM, and examines the controversies concerning the immunomodulatory functions of the CXCR3 receptor, including immune T cell recruitment, polarization, and positioning. The mechanisms underlying monotherpies and combination therapies targeting the CXCR3 pathways are discussed. A better understanding of the CXCR3 axes may lead to the development of strategies for overcoming the limitations of existing immunotherapies for GBM.

Comparative Analysis of Amino Acid Profiles in Patients with Glioblastoma and Meningioma Using Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometry (LC-ESI-MS/MS)

Brain tumors account for 1% of all cancers diagnosed de novo. Due to the specificity of the anatomical area in which they grow, they can cause significant neurological disorders and lead to poor functional status and disability. Regardless of the results of biochemical markers of intracranial neoplasms, they are currently of no diagnostic significance. The aim of the study was to use LC-ESI-MS/MS in conjunction with multivariate statistical analyses to examine changes in amino acid metabolic profiles between patients with glioblastoma, meningioma, and a group of patients treated for osteoarthritis of the spine as a control group. Comparative analysis of amino acids between patients with glioblastoma, meningioma, and the control group allowed for the identification of statistically significant differences in the amino acid profile, including both exogenous and endogenous amino acids. The amino acids that showed statistically significant differences (lysine, histidine, α-aminoadipic acid, phenylalanine) were evaluated for diagnostic usefulness based on the ROC curve. The best results were obtained for phenylalanine. Classification trees were used to build a model allowing for the correct classification of patients into the study group (patients with glioblastoma multiforme) and the control group, in which cysteine turned out to be the most important amino acid in the decision-making algorithm. Our results indicate amino acids that may prove valuable, used alone or in combination, toward improving the diagnosis of patients with glioma and meningioma. To better assess the potential utility of these markers, their performance requires further validation in a larger cohort of samples.

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 overview of glioblastoma multiforme and temozolomide resistance: can LC-MS-based proteomics reveal the fundamental mechanism of temozolomide resistance?

Glioblastoma multiforme (GBM) is a primary type of lethal brain tumor. Over the last two decades, temozolomide (TMZ) has remained the primary chemotherapy for GBM. However, TMZ resistance in GBM constitutes an underlying factor contributing to high rates of mortality. Despite intense efforts to understand the mechanisms of therapeutic resistance, there is currently a poor understanding of the molecular processes of drug resistance. For TMZ, several mechanisms linked to therapeutic resistance have been proposed. In the past decade, significant progress in the field of mass spectrometry-based proteomics has been made. This review article discusses the molecular drivers of GBM, within the context of TMZ resistance with a particular emphasis on the potential benefits and insights of using global proteomic techniques.

Pro-inflammatory megakaryocyte gene expression in murine models of breast cancer

Despite abundant research demonstrating that platelets can promote tumor cell metastasis, whether primary tumors affect platelet-producing megakaryocytes remains understudied. In this study, we used a spontaneous murine model of breast cancer to show that tumor burden reduced megakaryocyte number and size and disrupted polyploidization. Single-cell RNA sequencing demonstrated that megakaryocytes from tumor-bearing mice exhibit a pro-inflammatory phenotype, epitomized by increased Ctsg, Lcn2, S100a8, and S100a9 transcripts. Protein S100A8/A9 and lipocalin-2 levels were also increased in platelets, suggesting that tumor-induced alterations to megakaryocytes are passed on to their platelet progeny, which promoted in vitro tumor cell invasion and tumor cell lung colonization to a greater extent than platelets from wild-type animals. Our study is the first to demonstrate breast cancer-induced alterations in megakaryocytes, leading to qualitative changes in platelet content that may feedback to promote tumor metastasis.

A review of gliomas-related proteins. Characteristics of potential biomarkers

Brain tumors are one of the most commonly diagnosed cancers of the central nervous system. Of all diagnosed malignant tumors, 80% are gliomas. An unequivocal diagnosis of gliomas is not always simple, and there is a great need for research to find new treatment options and diagnostic approaches. This paper is focused on the glioma-related protein profiles as compared to healthy brain tissue, which is reflected in multiple correlations between biological aspects that influence proliferation, apoptosis evasion and the invasiveness of neoplastic cells. The work presents the possibilities of facilitating clinical practice with proteomic biomarkers, which offer a wider diagnostic spectrum and reduce the margin of mistake in histopathological or imaging diagnostic methods. In fact, many changes in the body's homeostasis can be overlooked due to the lack of symptoms or their non-specificity. Nevertheless, a single marker has limited reliability in distinguishing a particular tumor subtype, since the increased or decreased level of the protein of interest may differ between the stages or locations of the tumor. Moreover, the correlations between proposed proteins - presented in this paper - may help clinicians to choose the most optimal therapy, and estimate its effectiveness, or indicate new therapeutic targets affecting disrupted biochemical pathways.

Blood-Based Biomarkers for Glioma in the Context of Gliomagenesis: A Systematic Review

BACKGROUND

Gliomas are the most common and aggressive tumors of the central nervous system. A robust and widely used blood-based biomarker for glioma has not yet been identified. In recent years, a plethora of new research on blood-based biomarkers for glial tumors has been published. In this review, we question which molecules, including proteins, nucleic acids, circulating cells, and metabolomics, are most promising blood-based biomarkers for glioma diagnosis, prognosis, monitoring and other purposes, and align them to the seminal processes of cancer.

METHODS

The Pubmed and Embase databases were systematically searched. Biomarkers were categorized in the identified biomolecules and biosources. Biomarker characteristics were assessed using the area under the curve (AUC), accuracy, sensitivity and/or specificity values and the degree of statistical significance among the assessed clinical groups was reported.

RESULTS

7,919 references were identified: 3,596 in PubMed and 4,323 in Embase. Following screening of titles, abstracts and availability of full-text, 262 articles were included in the final systematic review. Panels of multiple biomarkers together consistently reached AUCs >0.8 and accuracies >80% for various purposes but especially for diagnostics. The accuracy of single biomarkers, consisting of only one measurement, was far more variable, but single microRNAs and proteins are generally more promising as compared to other biomarker types.

CONCLUSION

Panels of microRNAs and proteins are most promising biomarkers, while single biomarkers such as GFAP, IL-10 and individual miRNAs also hold promise. It is possible that panels are more accurate once these are involved in different, complementary cancer-related molecular pathways, because not all pathways may be dysregulated in cancer patients. As biomarkers seem to be increasingly dysregulated in patients with short survival, higher tumor grades and more pathological tumor types, it can be hypothesized that more pathways are dysregulated as the degree of malignancy of the glial tumor increases. Despite, none of the biomarkers found in the literature search seem to be currently ready for clinical implementation, and most of the studies report only preliminary application of the identified biomarkers. Hence, large-scale validation of currently identified and potential novel biomarkers to show clinical utility is warranted.

Circulating Biomarkers for Glioma: A Review

Accurate circulating biomarkers have potential clinical applications in population screening, tumor subclassification, monitoring tumor status, and the delivery of individualized treatments resulting from tumor genotyping. Recently, significant progress has been made within this field in several cancer types, but despite the many potential benefits, currently there is no validated circulating biomarker test for patients with glioma. A number of circulating factors have been examined, including circulating tumor cells, cell-free DNA, microRNA, exosomes, and proteins from both peripheral blood and cerebrospinal fluid with variable results. In the following article, we provide a narrative review of the current evidence pertaining to circulating biomarkers in patients with glioma, including discussion of the advantages and challenges encountered with the current methods used for discovery. Additionally, the potential clinical applications are described with reference to the literature.

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.

Role of RAGE and Its Ligands on Inflammatory Responses to Brain Tumors

Gliomas, the most common form of brain cancer, can range from relatively slow-growing low-grade to highly aggressive glioblastoma that has a median overall survival of only 15 months despite multimodal standard therapy. Although immunotherapy with checkpoint inhibitors has significantly improved patient survival for some cancers, to date, these agents have not shown consistent efficacy against malignant gliomas. Therefore, there is a pressing need to better understand the impact of host inflammatory responses on the efficacy of emerging immunotherapy approaches for these resistant tumors. RAGE is a multi-ligand pattern recognition receptor that is activated in various inflammatory states such as diabetes, Alzheimer's disease, cystic fibrosis, and cancer. Low levels of RAGE can be found under normal physiological conditions in neurons, immune cells, activated endothelial, and vascular smooth muscle cells, but it is over-expressed under chronic inflammation due to the accumulation of its ligands. RAGE binds to a range of damage-associated molecular pattern molecules (DAMPs) including AGEs, HMGB1, S100s, and DNA which mediate downstream cellular responses that promote tumor growth, angiogenesis, and invasion. Both in vitro and in vivo studies have shown that inhibition of RAGE signaling can disrupt inflammation and cancer progression and metastasis. Here, we will review our current understanding of the role of RAGE pathway on glioma progression and how it could be exploited to improve the efficacy of immunotherapy approaches.

Long Noncoding RNA WEE2-AS1 Plays an Oncogenic Role in Glioblastoma by Functioning as a Molecular Sponge for MicroRNA-520f-3p

The long noncoding RNA WEE2 antisense RNA 1 (WEE2-AS1) plays an oncogenic role in hepatocellular carcinoma and triple negative breast cancer progression. In this study, we investigated the expression and roles of WEE2-AS1 in glioblastoma (GBM). Furthermore, the molecular mechanisms behind the oncogenic actions of WEE2-AS1 in GBM cells were explored in detail. WEE2-AS1 expression was detected using quantitative real-time polymerase chain reaction. The roles of WEE2-AS1 in GBM cells were evaluated by the cell counting kit-8 assay, flow cytometric analysis, Transwell cell migration and invasion assays, and tumor xenograft experiments. WEE2-AS1 expression was evidently enhanced in GBM tissues and cell lines compared with their normal counterparts. An increased level of WEE2-AS1 was correlated with the average tumor diameter, Karnofsky Performance Scale score, and shorter overall survival among GBM patients. Functionally, depleted WEE2-AS1 attenuated GBM cell proliferation, migration, and invasion in vitro, promoted cell apoptosis, and impaired tumor growth in vivo. Mechanistically, WEE2-AS1 functioned as a molecular sponge for microRNA-520f-3p (miR-520f-3p) and consequently increased specificity protein 1 (SP1) expression in GBM cells. A series of recovery experiments revealed that the inhibition of miR-520f-3p and upregulation of SP1 could partially abrogate the influences of WEE2-AS1 downregulation on GBM cells. In conclusion, WEE2-AS1 can adsorb miR-520f-3p to increase endogenous SP1 expression, thereby facilitating the malignancy of GBM. Therefore, targeting the WEE2-AS1–miR-520f-3p–SP1 pathway might be a promising therapy for the management of GBM in the future.

Glioblastoma: Is There Any Blood Biomarker with True Clinical Relevance?

Glioblastoma (GBM) is the most frequent malignant primary brain tumor in adults, characterized by a highly aggressive, inflammatory and angiogenic phenotype. It is a remarkably heterogeneous tumor at several levels, including histopathologically, radiographically and genetically. The 2016 update of the WHO Classification of Tumours of the Central Nervous System highlighted molecular parameters as paramount features for the diagnosis, namely IDH1/2 mutations that distinguish primary and secondary GBM. An ideal biomarker is a molecule that can be detected/quantified through simple non- or minimally invasive methods with the potential to assess cancer risk; promote early diagnosis; increase grading accuracy; and monitor disease evolution and treatment response, as well as fundamentally being restricted to one aspect. Blood-based biomarkers are particularly attractive due to their easy access and have been widely used for various cancer types. A number of serum biomarkers with multiple utilities for glioma have been reported that could classify glioma grades more precisely and provide prognostic value among these patients. At present, screening for gliomas has no clinical relevance. This is because of the low incidence, the lack of sensitive biomarkers in plasma, and the observation that gliomas may develop apparently de novo within few weeks or months. To the best of our knowledge, there is no routine use of a serum biomarker for clinical follow-up. The purpose of this paper is to review the serum biomarkers described in the literature related to glioblastoma and their possible relationship with clinical features.

The Role of Selected Chemokines and Their Receptors in the Development of Gliomas

Among heterogeneous primary tumors of the central nervous system (CNS), gliomas are the most frequent type, with glioblastoma multiforme (GBM) characterized with the worst prognosis. In their development, certain chemokine/receptor axes play important roles and promote proliferation, survival, metastasis, and neoangiogenesis. However, little is known about the significance of atypical receptors for chemokines (ACKRs) in these tumors. The objective of the study was to present the role of chemokines and their conventional and atypical receptors in CNS tumors. Therefore, we performed a thorough search for literature concerning our investigation via the PubMed database. We describe biological functions of chemokines/chemokine receptors from various groups and their significance in carcinogenesis, cancer-related inflammation, neo-angiogenesis, tumor growth, and metastasis. Furthermore, we discuss the role of chemokines in glioma development, with particular regard to their function in the transition from low-grade to high-grade tumors and angiogenic switch. We also depict various chemokine/receptor axes, such as CXCL8-CXCR1/2, CXCL12-CXCR4, CXCL16-CXCR6, CX3CL1-CX3CR1, CCL2-CCR2, and CCL5-CCR5 of special importance in gliomas, as well as atypical chemokine receptors ACKR1-4, CCRL2, and PITPMN3. Additionally, the diagnostic significance and usefulness of the measurement of some chemokines and their receptors in the blood and cerebrospinal fluid (CSF) of glioma patients is also presented.

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.

Serum biomarkers identification by iTRAQ and verification by MRM: S100A8/S100A9 levels predict tumor-stroma involvement and prognosis in Glioblastoma

Despite advances in biology and treatment modalities, the prognosis of glioblastoma (GBM) remains poor. Serum reflects disease macroenvironment and thus provides a less invasive means to diagnose and monitor a diseased condition. By employing 4-plex iTRAQ methodology, we identified 40 proteins with differential abundance in GBM sera. The high abundance of serum S100A8/S100A9 was verified by multiple reaction monitoring (MRM). ELISA and MRM-based quantitation showed a significant positive correlation. Further, an integrated investigation using stromal, tumor purity and cell type scores demonstrated an enrichment of myeloid cell lineage in the GBM tumor microenvironment. Transcript levels of S100A8/S100A9 were found to be independent poor prognostic indicators in GBM. Medium levels of pre-operative and three-month post-operative follow-up serum S100A8 levels predicted poor prognosis in GBM patients who lived beyond median survival. In vitro experiments showed that recombinant S100A8/S100A9 proteins promoted integrin signalling dependent glioma cell migration and invasion up to a threshold level of concentrations. Thus, we have discovered GBM serum marker by iTRAQ and verified by MRM. We also demonstrate interplay between tumor micro and macroenvironment and identified S100A8 as a potential marker with diagnostic and prognostic value in GBM.

Multiplex assay for multiomics advances in personalized-precision medicine

Building the future of precision medicine is the main focus in cancer domain. Clinical trials are moving toward an array of studies that are more adapted to precision medicine. In this domain, there is an enhanced need for biomarkers, monitoring devices, and data-analysis methods. Omics profiling using whole genome, epigenome, transcriptome, proteome, and metabolome can offer detailed information of the human body in an integrative manner. Omes profiles reflect more accurately real-time physiological status. Personalized omics analyses both disease as a whole and the main disease processes, for a better understanding of the individualized health. Through this, multi-omic approaches for health monitoring, preventative medicine, and personalized treatment can be targeted simultaneously and can lead clinicians to have a comprehensive view on the diseasome.

Long noncoding RNA FOXD2-AS1 promotes glioma malignancy and tumorigenesis via targeting miR-185-5p/CCND2 axis

Glioma is the most aggressive malignant tumor in the adult central nervous system. Abnormal long noncoding RNA (lncRNA) FOXD2-AS1 expression was associated with tumor development. However, the possible role of FOXD2-AS1 in the progression of glioma is not known. In the present study, we used in vitro and in vivo assays to investigate the effect of abnormal expression of FOXD2-AS1 on glioma progression and to explore the mechanisms. FOXD2-AS1 was upregulated in glioma tissue, cells, and sphere subpopulation. Upregulation of FOXD2-AS1 was correlated with poor prognosis of glioma. Downregulation of FOXD2-AS1 decreased cell proliferation, migration, invasion, stemness, and epithelial-mesenchymal transition (EMT) in glioma cells and inhibited tumor growth in transplanted tumor. We also revealed that FOXD2-AS1 was mainly located in cytoplasm and microRNA (miR)-185-5p both targeted FOXD2-AS1 and CCND2 messenger RNA (mRNA) 3'-untranslated region (3'-UTR). miR-185-5p was downregulated in glioma tissue, cells, and sphere subpopulation. Downregulation of miR-185-5p was closely correlated with poor prognosis of glioma patients. In addition, miR-185-5p mimics decreased cell proliferation, migration, invasion, stemness, and EMT in glioma cells. CCND2 was upregulated in glioma tissue, cells, and sphere subpopulation. Upregulation of CCND2 was closely correlated with poor prognosis of glioma patients. CCND2 knockdown decreased cell proliferation, migration, invasion, and EMT in glioma cells. In glioma tissues, CCND2 expression was negatively associated with miR-185-5p, but positively correlated with FOXD2-AS1. FOXD2-AS1 knockdown and miR-185-5p mimics decreased CCND2 expression. Inhibition of miR-185-5p suppressed FOXD2-AS1 knockdown-induced decrease of CCND2 expression. Overexpression of CCND2 suppressed FOXD2-AS1 knockdown-induced inhibition of glioma malignancy. Taken together, our findings highlight the FOXD2-AS1/miR-185-5p/CCND2 axis in the glioma development.

Transcriptome profiling reveals PDZ binding kinase as a novel biomarker in peritumoral brain zone of glioblastoma

PURPOSE

Peritumoural brain zone (PT) of glioblastoma (GBM) is the area where tumour recurrence is often observed. We aimed to identify differentially regulated genes between tumour core (TC) and PT to understand the underlying molecular characteristics of infiltrating tumour cells in PT.

METHODS

17 each histologically characterised TC and PT tissues of GBM along with eight control tissues were subjected to cDNA Microarray. PT tissues contained 25-30% infiltrating tumour cells. Data was analysed using R Bioconductor software. Shortlisted genes were validated using qRT-PCR. Expression of one selected candidate gene, PDZ Binding Kinase (PBK) was correlated with patient survival, tumour recurrence and functionally characterized in vitro using gene knock-down approach.

RESULTS

Unsupervised hierarchical clustering showed that TC and PT have distinct gene expression profiles compared to controls. Further, comparing TC with PT, we observed a significant overlap in gene expression profile in both, despite PT having fewer infiltrating tumour cells. qRT-PCR for 13 selected genes validated the microarray data. Expression of PBK was higher in PT as compared to TC and recurrent when compared to newly diagnosed GBM tumours. PBK knock-down showed a significant reduction in cell proliferation, migration and invasion with increase in sensitivity to radiation and Temozolomide treatment.

CONCLUSIONS

We show that several genes of TC are expressed even in PT contributing to the vulnerability of PT for tumour recurrence. PBK is identified as a novel gene up-regulated in PT of GBM with a strong role in conferring aggressiveness, including radio-chemoresistance, thus contributing to recurrence in GBM tumours.

LncRNA MALAT1/miR-129 axis promotes glioma tumorigenesis by targeting SOX2

We aimed to explore the interaction among lncRNA MALAT1, miR‐129 and SOX2. Besides, we would investigate the effect of MALAT1 on the proliferation of glioma stem cells and glioma tumorigenesis. Differentially expressed lncRNAs in glioma cells and glioma stem cells were screened out with microarray analysis. The targeting relationship between miR‐129 and MALAT1 or SOX2 was validated by dual‐luciferase reporter assay. The expressions of MALAT1, miR‐129 and SOX2mRNA in both glioma non‐stem cells and glioma stem cells were examined by qRT‐PCR assay. The impact of MALAT1 and miR‐129 on glioma stem cell proliferation was observed by CCK‐8 assay, EdU assay and sphere formation assay. The protein expression of SOX2 was determined by western blot. The effects of MALAT1 and miR‐129 on glioma tumour growth were further confirmed using xenograft mouse model. The mRNA expression of MALAT1 was significantly up‐regulated in glioma stem cells compared with non‐stem cells, while miR‐129 was significantly down‐regulated in glioma stem cells. MALAT1 knockdown inhibited glioma stem cell proliferation via miR‐129 enhancement. Meanwhile, miR‐129 directly targeted at SOX2 and suppressed cell viability and proliferation of glioma stem cells by suppressing SOX2 expression. The down‐regulation of MALAT1 and miR‐129 overexpression both suppressed glioma tumour growth via SOX2 expression promotion in vivo. MALAT1 enhanced glioma stem cell viability and proliferation abilities and promoted glioma tumorigenesis through suppressing miR‐129 and facilitating SOX2 expressions.

Serum amyloid A1 in combination with integrin αVβ3 increases glioblastoma cells mobility and progression

Glioblastoma multiforme (GBM) is a highly malignant type of brain tumor found in humans. GBM cells reproduce quickly, and the median survival time for patients after therapy is approximately 1 year with a high relapse rate. Current therapies and diagnostic tools for GBM are limited; therefore, we searched for a more favorable therapeutic target or marker protein for both therapy and diagnosis. We used mass spectrometry (MS) analysis to identify GBM-associated marker proteins from human plasma and GBM cell cultures. Additional plasma and 52 brain tissues obtained from patients with gliomas were used to validate the association rate of serum amyloid A1 (SAA1) in different grades of gliomas and its distribution in tumors. Microarray database analysis further validated the coefficient of SAA1 levels in gliomas. The cellular mechanisms of SAA1 in GBM proliferation and infiltration were investigated in vitro. We analyzed the correlation between SAA1 and patients' medication requirement to demonstrate the clinical effects of SAA1 in GBM. SAA1 was identified from MS analysis, and its level was revealed to be correlated with the disease grade, clinical severity, and survival rate of patients with gliomas. In vitro cultures, including GBM cells and normal astrocytes, revealed that SAA1 promotes cell migration and invasion through integrin αVβ3 to activate the Erk signaling pathway. Magnetic resonance imaging and tumor region-specific microarray analysis identified a correlation between SAA1 and GBM cell infiltration in patients. In summary, our results demonstrate that SAA1 in combination with integrin αV and β3 can serve as an indicator of high glioblastoma risk. We also identified the cellular mechanisms of SAA1 contributing to GBM progression, which can serve as the basis for future GBM therapy.

Identification of blood biomarkers in glioblastoma by SWATH mass spectrometry and quantitative targeted absolute proteomics

Molecular biomarkers in blood are needed to aid the early diagnosis and clinical assessment of glioblastoma (GBM). Here, in order to identify biomarker candidates in plasma of GBM patients, we performed quantitative comparisons of the plasma proteomes of GBM patients (n = 14) and healthy controls (n = 15) using SWATH mass spectrometry analysis. The results were validated by means of quantitative targeted absolute proteomics analysis. As a result, we identified eight biomarker candidates for GBM (leucine-rich alpha-2-glycoprotein (LRG1), complement component C9 (C9), C-reactive protein (CRP), alpha-1-antichymotrypsin (SERPINA3), apolipoprotein B-100 (APOB), gelsolin (GSN), Ig alpha-1 chain C region (IGHA1), and apolipoprotein A-IV (APOA4)). Among them, LRG1, C9, CRP, GSN, IGHA1, and APOA4 gave values of the area under the receiver operating characteristics curve of greater than 0.80. To investigate the relationships between the biomarker candidates and GBM biology, we examined correlations between plasma concentrations of biomarker candidates and clinical presentation (tumor size, progression-free survival time, or overall survival time) in GBM patients. The plasma concentrations of LRG1, CRP, and C9 showed significant positive correlations with tumor size (R² = 0.534, 0.495, and 0.452, respectively).

Exploration of the platelet proteome in patients with early-stage cancer

Platelets play an important role in tumor growth and, at the same time, platelet characteristics are affected by cancer presence. Therefore, we investigated whether the platelet proteome harbors differentially expressed proteins associated with early-stage cancer. For this proof-of-concept study, patients with early-stage lung (n = 8) or head of pancreas cancer (n = 4) were included, as were healthy sex- and age-matched controls for both subgroups. Blood samples were collected from controls and from patients before surgery. Furthermore, from six of the patients, a second sample was collected two months after surgery. NanoLC-MS/MS-based proteomics of gel-fractionated platelet proteins was used for comparative spectral count analyses of patients to controls and before to after surgery samples. The total platelet proteome dataset included 4384 unique proteins of which 85 were significantly (criteria Fc > 1.5 and p < 0.05) changed in early-stage cancer compared to controls. In addition, the levels of 81 platelet proteins normalized after tumor resection. When filtering for the most discriminatory proteins, we identified seven promising platelet proteins associated with early-stage cancer. In conclusion, this pioneering study on the platelet proteome in cancer patients clearly identifies platelets as a new source of candidate protein biomarkers of early-stage cancer.

BIOLOGICAL SIGNIFICANCE

Currently, most blood-based diagnostics/biomarker research is performed in serum or plasma, while the content of blood cells is usually neglected. It is known that especially blood platelets, which are the main circulating pool of many bioactive proteins, such as growth factors, chemokines, and cytokines, are a potentially rich source of biomarkers. The current study is the first to measure the effect of early-stage cancer on the platelet proteome of patients. Our study demonstrates that the platelet proteome of patients with early-stage lung or head of pancreas cancer differs considerably compared to that of healthy individuals of matched sex and age. In addition, the platelet proteome of cancer patients normalized after surgical resection of the tumor. Exploiting platelet proteome differences linked to both tumor presence and disease status, we were able to demonstrate that the platelet proteome can be mined for potential biomarkers of cancer.

The Effect of MCM3AP-AS1/miR-211/KLF5/AGGF1 Axis Regulating Glioblastoma Angiogenesis

Glioblastoma (GBM) is the most aggressive and malignant primary tumor. Angiogenesis plays a critical role in the progression of GBM. Previous studies have indicated that long non-coding RNAs (lncRNAs) are abnormally expressed in various cancers and participate in the regulation of the malignant behaviors of tumors. The present study demonstrated that lncRNA antisense 1 to Micro-chromosome maintenance protein 3-associated protein (MCM3AP-AS1) was upregulated whereas miR-211 was downregulated in glioma-associated endothelial cells (GECs). Knockdown of MCM3AP-AS1 suppressed the cell viability, migration, and tube formation of GECs and played a role in inhibiting angiogenesis of GBM in vitro. Furthermore, knockdown of MCM3AP-AS1 increased the expression of miR-211. Luciferase reporter assay implicated that miR-211 targeted KLF5 3'-UTR and consequently inhibited KLF5 expression. Besides, in this study we found that MCM3AP-AS1 knockdown decreased KLF5 and AGGF1 expression by upregulating miR-211. In addition, KLF5 was associated with the promoter region of AGGF1. Knockdown of KLF5 decreased AGGF1 expression by transcriptional repression, and also inhibited the activation of PI3K/AKT and ERK1/2 signaling pathways. Overall, this study reveals that MCM3AP-AS1/miR-211/KLF5/AGGF1 axis plays a prominent role in the regulation of GBM angiogenesis and also serves as new therapeutic target for the anti-angiogenic therapy of glioma.

Cerebrospinal fluid and serum IL-8, CCL2, and ICAM-1 concentrations in astrocytic brain tumor patients

BACKGROUND

The aim of the study was the evaluation of serum and CSF concentrations of CCL2, IL-8, and sICAM-1 in patients with astrocytic tumors as compared to a group of non-tumoral patients.

METHODS

Chemokine concentrations were measured using the ELISA method.

RESULTS

Regardless of the parameter tested and the patient group (brain tumor or non-tumoral patients), statistical differences (P < 0.05) were found between concentrations obtained in CSF compared to values obtained in serum for all proteins tested. CSF IL-8 concentrations were significantly elevated in CNS tumor patients as compared to non-tumoral individuals (P = 0.000); serum CCL2 and sICAM-1 concentrations were significantly decreased in CNS tumors in comparison with the comparative group (P = 0.002 and P = 0.026, respectively). Among proteins tested in the serum, a higher area under the ROC curve (AUC) revealed CCL2 compared to sICAM-1 in differentiating subjects with CNS brain tumors from non-tumoral subjects. AUC for CSF IL-8 was higher than for its index (CSF IL-8/serum IL-8).

CONCLUSIONS

For individual biomarkers (IL-8 and CCL2, sICAM-1), measured in CNS brain tumor patients, the appropriate material, respectively CSF or serum, should be chosen and quantitatively tested. Increased cerebrospinal fluid IL-8 with decreased serum CCL2 create a pattern of biomarkers, which may be helpful in the management of CNS astrocytic brain tumors.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed.

Circulating LOXL2 Levels Reflect Severity of Intestinal Fibrosis and GALT CD4+ T Lymphocyte Depletion in Treated HIV Infection

BACKGROUND

Incomplete immune reconstitution may occur despite successful antiretroviral therapy (ART). Gut-associated lymphoid tissue (GALT) fibrosis may contribute via local CD4+ T lymphocyte depletion, intestinal barrier disruption, microbial translocation, and immune activation.

METHODS

In a cross-sectional analysis, we measured circulating fibrosis biomarker levels on cryopreserved plasma from adult HIV-infected (HIV+) SCOPE study participants on suppressive ART who also had fibrosis quantification on recto-sigmoid biopsies. Relationships among biomarker levels, clinical and demographic variables, GALT lymphoid aggregate (LA) collagen deposition, and LA CD4+ T lymphocyte density were analyzed using simple regression. Biomarker levels were also compared to levels in HIV+ viremic SCOPE participants and a convenience sample of HIV-uninfected (HIV-) samples.

RESULTS

HIV+ aviremic participants (n = 39) were 92% male and 41% non-white, with median age 48 years, CD4+ T lymphocyte count 277 cells/mm3, and 17 years since HIV diagnosis. Most biomarkers were lower in HIV- (n = 36) vs HIV+ aviremic individuals, although CXCL4 levels were higher. HIV+ viremic individuals (N = 18) had higher median TGF-β3, CIC-C1Q, and TIMP-1 (P < 0.05) and lower LOXL2 levels (P = 0.08) than HIV+ aviremic individuals. Only higher LOXL2 levels correlated with more GALT collagen deposition (R = 0.44, P= 0.008) and lower LA CD4+ T lymphocyte density (R = -0.32, P = 0.05) among aviremic individuals.

CONCLUSIONS

Circulating LOXL2 levels may be a noninvasive measure of intestinal fibrosis and GALT CD4+ T lymphocyte depletion in treated HIV infection. LOXL2 crosslinks elastin and collagen, and elevated LOXL2 levels occur in pathologic states, making LOXL2 inhibition a potential interventional target for intestinal fibrosis and its sequelae.

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

Glioma, one of the most common cancers in human, is classified to different grades according to the degrees of malignancy. Glioblastoma (GBM) is known to be the most malignant (Grade IV) whereas low-grade astrocytoma (LGA, Grade II) is relatively benign. The mechanism underlying the pathogenesis and progression of glioma malignancy remains unclear. Here we report a quantitative proteomic study to elucidate the differences between GBM and LGA using liquid chromatography and tandem mass spectrometry followed by label-free quantification. A total of 136 proteins were differentially expressed in GBM for at least five folds in comparison with LGA. Ontological analysis revealed a close correlation between GBM-associated proteins and RNA processing. Interaction network analysis indicated that the GBM-associated proteins in the RNA processing were linked to crucial signaling transduction modulators including epidermal growth factor receptor (EGFR), signal transducer and activator of transcription 1 (STAT1), and mitogen-activated protein kinase 1 (MAPK1), which were further connected to the proteins important for neuronal structural integrity, development and functions. Upregulation of 40S ribosomal protein S5 (RPS5), Ferritin Heavy chain (FTH1) and STAT1, and downregulation of tenascin R (TNR) were validated as representatives by immune assays. In summary, we revealed a panel of GBM-associated proteins and the important modulators centered at the RNA-processing network in glioma malignancy that may become novel biomarkers and help elucidate the underlying mechanism.

Prostate cancer proteomics: Current trends and future perspectives for biomarker discovery

The clinical and fundamental research in prostate cancer - the most common urological cancer in men - is currently entering the proteomic and genomic era. The focus has switched from one single marker (PSA) to panels of biomarkers (including proteins involved in ribosomal function and heat shock proteins). Novel genetic markers (such as Transmembrane protease serine 2 (TMPRSS2)-ERG fusion gene mRNA) or prostate cancer gene 3 (PCA3) had already entered the clinical practice, raising the question whether subsequent protein changes impact the evolution of the disease and the response to treatment. Proteomic technologies such as MALDI-MS, SELDI-MS, i-TRAQ allow a qualitative/quantitative analysis of the proteome variations, in both serum and tumor tissue. A new trend in prostate cancer research is proteomic analysis of prostasomes (prostate-specific exosomes), for the discovery of new biomarkers. This paper provides an update of novel clinical tests used in research and clinical diagnostic, as well as of potential tissue or fluid biomarkers provided by extensive proteomic research data.

Evaluation of non-supervised MALDI mass spectrometry imaging combined with microproteomics for glioma grade III classification

An integrated diagnosis using molecular features is recommended in the 2016 World Health Organization (WHO) classification. Our aim was to explore non-targeted molecular classification using MALDI mass spectrometry imaging (MALDI MSI) associated to microproteomics in order to classify anaplastic glioma by integration of clinical data. We used fresh-frozen tissue sections to perform MALDI MSI of proteins based on their digestion peptides after in-situ trypsin digestion of the tissue sections and matrix deposition by micro-spraying. The generated 70μm spatial resolution image datasets were further processed by individual or global segmentation in order to cluster the tissues according to their molecular protein signature. The clustering gives 3 main distinct groups. Within the tissues the ROIs (regions of interest) defined by these groups were used for microproteomics by micro-extraction of the tryptic peptides after on-tissue enzymatic digestion. More than 2500 proteins including 22 alternative proteins (AltProt) are identified by the Shotgun microproteomics. Statistical analysis on the basis of the label free quantification of the proteins shows a similar classification to the MALDI MSI segmentation into 3 groups. Functional analysis performed on each group reveals sub-networks related to neoplasia for group 1, glioma with inflammation for group 2 and neurogenesis for group 3. This demonstrates the interest on these new non-targeted large molecular data combining both MALDI MSI and microproteomics data, for tumor classification. This analysis provides new insights into grade III glioma organization. This specific information could allow a more accurate classification of the biopsies according to the prognosis and the identification of potential new targeted therapeutic options. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

A review of novel analytical diagnostics for liquid biopsies: spectroscopic and spectrometric serum profiling of primary and secondary brain tumors

INTRODUCTION

Spectroscopic and spectrometric analysis of biological samples is regarded as quick, cost effective, easy to operate, and spectroscopic sample preparation involves minimal sample preparation.

RESULTS

Techniques like infrared (IR) spectroscopy, surface-enhanced laser desorption/ionization (SELDI)-mass spectroscopy (MS), and matrix-assisted laser desorption/ionization (MALDI) -MS could enable early diagnosis of cancer, disease monitoring, and assessment of treatment responses allowing refinement, if required.

DISCUSSION

Carrying out analytical testing within outpatient clinics would dramatically cut the time spent by patients attending different appointments, at different locations, save hospital time and resources but importantly would theoretically enable a reduction in mortality and morbidity. While the advantages of such a prospect seem obvious, this review aims to evaluate the use of human serum spectroscopic and spectrometric analysis as a diagnostic tool for brain cancers, creating a platform for the future of cancer diagnostics.

Inflammatory Biomarkers Profile as Microenvironmental Expression in Keratoconus

Keratoconus is a degenerative disorder with progressive stromal thinning and transformation of the normal corneal architecture towards ectasia that results in decreased vision due to irregular astigmatism and irreversible tissue scarring. The pathogenesis of keratoconus still remains unclear. Hypotheses that this condition has an inflammatory etiopathogenetic component apart from the genetic and environmental factors are beginning to escalate in the research domain. This paper covers the most relevant and recent published papers regarding the biomarkers of inflammation, their signaling pathway, and the potentially new therapeutic options in keratoconus.

Proteomic Biomarkers Panel: New Insights in Chronic Kidney Disease

Chronic kidney disease, despite being a "silent epidemic" disease, represents one of the main causes of mortality in general population, along with cardiovascular disease, which is the leading cause of poor prognosis for these patients. The specific objective of our study was to characterize the relationship between the inflammatory status, the bone disorders markers, and kidney failure in chronic kidney disease patient stages 2-4, in order to design a novel biomarker panel that improves early disease diagnosis and therapeutic response, thus being further integrated into clinical applications. A panel of proteomic biomarkers, assessed by xMAP array, which includes mediators of inflammation (IL-6, TNF-α) and mineral and bone disorder biomarkers (OPG, OPN, OCN, FGF-23, and Fetuin-A), was found to be more relevant than a single biomarker to detect early CKD stages. The association between inflammatory cytokines and bone disorders markers, IL-6, TNF-α, OPN, OPG, and FGF-23, reflects the severity of vascular changes in CKD and predicts disease progression. Proteomic xMAP analyses shed light on a new approach to clinical evaluation for CKD staging and prognosis.

Proteomic Approaches for Biomarker Panels in Cancer

Proteomic technologies remain the main backbone of biomarkers discovery in cancer. The continuous development of proteomic technologies also enlarges the bioinformatics domain, thus founding the main pillars of cancer therapy. The main source for diagnostic/prognostic/therapy monitoring biomarker panels are molecules that have a dual role, being both indicators of disease development and therapy targets. Proteomic technologies, such as mass-spectrometry approaches and protein array technologies, represent the main technologies that can depict these biomarkers. Herein, we will illustrate some of the most recent strategies for biomarker discovery in cancer, including the development of immune-markers and the use of cancer stem cells as target therapy. The challenges of proteomic biomarker discovery need new forms of cross-disciplinary conglomerates that will result in increased and tailored access to treatments for patients; diagnostic companies would benefit from the enhanced co-development of companion diagnostics and pharmaceutical companies. In the technology optimization in biomarkers, immune assays are the leaders of discovery machinery.

Myeloid derived suppressor cells in inflammatory conditions of the central nervous system

The knowledge of the immune system elements and their relationship with other tissues, organs and systems are key approximations for the resolution of many immune-related disorders. The control of the immune response and/or its modulation from the pro-inflammatory to the anti-inflammatory response is being deeply studied in the field. In the last years, the study of myeloid-derived suppressor cells (MDSCs), a group of immature myeloid cells with a high suppressive activity on T cells has been extensively addressed in cancer. In contrast, their role in neuroimmune diseases is far from being totally understood. In this review, we will summarize data about MDSCs coming from the study of neuroinflammatory diseases in general and their potential role in multiple sclerosis, in order to introduce the putative use of this extraordinary promising cell type for future cell-based therapies. This article is part of a Special Issue entitled: Neuro Inflammation edited by Helga E. de Vries and Markus Schwaninger.

Circulating biomarkers for gliomas

Currently, gliomas are diagnosed by neuroimaging, and refined diagnosis requires resection or biopsy to obtain tumour tissue for histopathological classification and grading. Blood-derived biomarkers, therefore, would be useful as minimally invasive markers that could support diagnosis and enable monitoring of tumour growth and response to treatment. Such circulating biomarkers could distinguish true progression from therapy-associated changes such as radiation necrosis, and help evaluate the persistence or disappearance of a therapeutic target, such as an oncoprotein or a targetable gene mutation, after targeted therapy. Unlike for other tumours, circulating biomarkers for gliomas are still being defined and are not yet in use in clinical practice. Circulating tumour DNA (ctDNA) isolated from plasma has been shown to reflect the mutational status of glioblastoma, and extracellular vesicles (EVs) containing ctDNA, microRNA and proteins function as rapidly adapting reservoirs for glioma biomarkers such as typical DNA mutations, regulatory microRNAs and oncoproteins. Ideally, circulating tumour cells could enable profiling of the whole-tumour genome, but they are difficult to detect and can reflect only a single cell type of the heterogeneous tumour composition, whereas EVs reflect the complex heterogeneity of the whole tumour, as well as its adaptations to therapy. Although all categories of potential blood-derived biomarkers need to be developed further, findings from other tumour types suggest that EVs are the most promising biomarkers.

Definition of a serum marker panel for glioblastoma discrimination and identification of Interleukin 1β in the microglial secretome as a novel mediator of endothelial cell survival induced by C-reactive protein

Glioblastoma (GBM) is the most common malignant adult primary brain tumor. We profiled 724 cancer-associated proteins in sera of healthy individuals (n=27) and GBM (n=28) using antibody microarray. While 69 proteins exhibited differential abundance in GBM sera, a three-marker panel (LYAM1, BHE40 and CRP) could discriminate GBM sera from that of healthy donors with an accuracy of 89.7% and p<0.0001. The high abundance of C-reactive protein (CRP) in GBM sera was confirmed in 264 independent samples. High levels of CRP protein was seen in GBM but without a change in transcript levels suggesting a non-tumoral origin. Glioma-secreted Interleukin 6 (IL6) was found to induce hepatocytes to secrete CRP, involving JAK-STAT pathway. The culture supernatant from CRP-treated microglial cells induced endothelial cell survival under nutrient-deprivation condition involving CRP-FcγRIII signaling cascade. Transcript profiling of CRP-treated microglial cells identified Interleukin 1β (IL1β) present in the microglial secretome as the key mediator of CRP-induced endothelial cell survival. IL1β neutralization by antibody-binding or siRNA-mediated silencing in microglial cells reduced the ability of the supernatant from CRP-treated microglial cells to induce endothelial cell survival. Thus our study identifies a serum based three-marker panel for GBM diagnosis and provides leads for developing targeted therapies. Biological significance A complex antibody microarray based serum marker profiling identified a three-marker panel - LYAM1, BHE40 and CRP as an accurate discriminator of glioblastoma sera from that of healthy individuals. CRP protein is seen in high levels without a concomitant increase of CRP transcripts in glioblastoma. Glioma-secreted IL6 induced hepatocytes to produce CRP in a JAK-STAT signaling dependent manner. CRP induced microglial cells to release IL1β which in turn promoted endothelial cell survival. This study, besides defining a serum panel for glioblastoma discrimination, identified IL1β as a potential candidate for developing targeted therapy.