Proteins with altered levels in plasma from glioblastoma patients as revealed by iTRAQ-based quantitative proteomic analysis

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.

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.

Advances on Liquid Biopsy Analysis for Glioma Diagnosis

Gliomas comprise the most frequent primary central nervous system (CNS) tumors, characterized by remarkable genetic and epigenetic heterogeneity, difficulty in monitoring, and increased relapse and mortality rates. Tissue biopsy is an established method of tumor cell collection and analysis that enables diagnosis, classification of different tumor types, and prediction of prognosis upon confirmation of tumor's location for surgical removal. However, it is an invasive and often challenging procedure that cannot be used for frequent patient screening, detection of mutations, disease monitoring, or resistance to therapy. To this end, the minimally invasive procedure of liquid biopsy has emerged, allowing effortless tumor sampling and enabling continuous monitoring. It is considered a novel preferable way to obtain faster data on potential tumor risk, personalized diagnosis, prognosis, and recurrence evaluation. The purpose of this review is to describe the advances on liquid biopsy for glioma diagnosis and management, indicating several biomarkers that can be utilized to analyze tumor characteristics, such as cell-free DNA (cfDNA), cell-free RNA (cfRNA), circulating proteins, circulating tumor cells (CTCs), and exosomes. It further addresses the benefit of combining liquid biopsy with radiogenomics to facilitate early and accurate diagnoses, enable precise prognostic assessments, and facilitate real-time disease monitoring, aiming towards more optimal treatment decisions.

Recent advances in the detection of glioblastoma, from imaging-based methods to proteomics and biosensors: A narrative review

Glioblastoma (GBM) is an aggressive type of cancer that originates in the cells called astrocytes, which support the functioning of nerve cells. It can develop in either the brain or the spinal cord and is also known as glioblastoma multiform. GBM is a highly aggressive cancer that can occur in either the brain or spinal cord. The detection of GBM in biofluids offers potential advantages over current methods for diagnosing and treatment monitoring of glial tumors. Biofluid-based detection of GBM focuses on identifying tumor-specific biomarkers in blood and cerebrospinal fluid. To date, different methods have been used to detect biomarkers of GBM, ranging from various imaging techniques to molecular approaches. Each method has its own strengths and weaknesses. The present review aims to scrutinize multiple diagnostic methods for GBM, with a focus on proteomics methods and biosensors. In other words, this study aims to provide an overview of the most significant research findings based on proteomics and biosensors for the diagnosis of GBM.

Deoxyhypusine hydroxylase: A novel therapeutic target differentially expressed in short-term vs long-term survivors of glioblastoma

Glioblastoma (GB) is the most aggressive neoplasm of the brain. Poor prognosis is mainly attributed to tumor heterogeneity, invasiveness and drug resistance. Only a small fraction of GB patients survives longer than 24 months from the time of diagnosis (ie, long-term survivors [LTS]). In our study, we aimed to identify molecular markers associated with favorable GB prognosis as a basis to develop therapeutic applications to improve patients' outcome. We have recently assembled a proteogenomic dataset of 87 GB clinical samples of varying survival rates. Following RNA-seq and mass spectrometry (MS)-based proteomics analysis, we identified several differentially expressed genes and proteins, including some known cancer-related pathways and some less established that showed higher expression in short-term (<6 months) survivors (STS) compared to LTS. One such target found was deoxyhypusine hydroxylase (DOHH), which is known to be involved in the biosynthesis of hypusine, an unusual amino acid essential for the function of the eukaryotic translation initiation factor 5A (eIF5A), which promotes tumor growth. We consequently validated DOHH overexpression in STS samples by quantitative polymerase chain reaction (qPCR) and immunohistochemistry. We further showed robust inhibition of proliferation, migration and invasion of GB cells following silencing of DOHH with short hairpin RNA (shRNA) or inhibition of its activity with small molecules, ciclopirox and deferiprone. Moreover, DOHH silencing led to significant inhibition of tumor progression and prolonged survival in GB mouse models. Searching for a potential mechanism by which DOHH promotes tumor aggressiveness, we found that it supports the transition of GB cells to a more invasive phenotype via epithelial-mesenchymal transition (EMT)-related pathways.

Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

The Role of the S100 Protein Family in Glioma

The S100 protein family consists of 25 members and share a common structure defined in part by the Ca²⁺ binding EF-hand motif. Multiple members' dysregulated expression is associated with progression, diagnosis and prognosis in a broad range of diseases, especially in tumors. They could exert wide range of functions both in intracellular and extracellular, including cell proliferation, cell differentiation, cell motility, enzyme activities, immune responses, cytoskeleton dynamics, Ca²⁺ homeostasis and angiogenesis. Gliomas are the most prevalent primary tumors of the brain and spinal cord with multiple subtypes that are diagnosed and classified based on histopathology. Up to now the role of several S100 proteins in gliomas have been explored. S100A8, S100A9 and S100B were highly expression in serum and may present as a marker correlated with survival and prognosis of glioma patients. Individual member was confirmed as a new regulator of glioma stem cells (GSCs) and a mediator of mesenchymal transition in glioblastoma (GBM). Additionally, several members up- or downregulation have been reported to involve in the development of glioma by interacting with signaling pathways and target proteins. Here we detail S100 proteins that are associated with glioma, and discuss their potential effects on progression, diagnosis and prognosis.

Quantitative proteomic analysis of GnRH agonist treated GBM cell line LN229 revealed regulatory proteins inhibiting cancer cell proliferation

BACKGROUND

Gonadotropin-releasing hormone (GnRH) receptor, a rhodopsin-like G-protein coupled receptor (GPCR) family member involved in GnRH signaling, is reported to be expressed in several tumors including glioblastoma multiforme (GBM), one of the most malignant and aggressive forms of primary brain tumors. However, the molecular targets associated with GnRH receptor are not well studied in GBM or in other cancers. The present study aims at investigating the effect of GnRH agonist (Gosarelin acetate) on cell proliferation and associated signaling pathways in GBM cell line, LN229.

METHODS

LN229 cells were treated with different concentrations of GnRH agonist (10^-10 M to 10^-5 M) and the effect on cell proliferation was analyzed by cell count method. Further, total protein was extracted from control and GnRH agonist treated cells (with maximum reduction in cell proliferation) followed by trypsin digestion, labeling with iTRAQ reagents and LC-MS/MS analysis to identify differentially expressed proteins. Bioinformatic analysis was performed for annotation of proteins for the associated molecular function, altered pathways and network analysis using STRING database.

RESULTS

The treatment with different concentrations of GnRH agonist showed a reduction in cell proliferation with a maximum reduction of 48.2% observed at 10^-6 M. Quantitative proteomic analysis after GnRH agonist treatment (10^-6 M) led to the identification of a total of 29 differentially expressed proteins with 1.3-fold change (23 upregulated, such as, kininogen-1 (KNG1), alpha-2-HS-glycoprotein (AHSG), alpha-fetoprotein (AFP), and 6 downregulated, such as integrator complex subunit 11 (CPSF3L), protein FRG1 (FRG1). Some of them are known [KNG1, AHSG, AFP] while others such as inter-alpha-trypsin inhibitor heavy chain H2 (ITIH2), ITIH4, and LIM domain-containing protein 1 (LIMD1) are novel to GnRH signaling pathway. Protein-protein interaction analysis showed a direct interaction of KNG1, a hub molecule, with GnRH, GnRH receptor, EGFR and other interactors including ITIH2, ITIH4 and AHSG. Overexpression of KNG1 after GnRH agonist treatment was validated using Western blot analysis, while a significant inhibition of EGFR was observed after GnRH agonist treatment.

CONCLUSIONS

The study suggests a possible link of GnRH signaling with EGFR signaling pathways likely via KNG1. KNG1 inhibitors may be investigated independently or in combination with GnRH agonist for therapeutic applications.

Plasma-derived candidate biomarkers for detection of gallbladder carcinoma

Gallbladder carcinoma (GBC) is a major cancer of the gastrointestinal tract with poor prognosis. Reliable and affordable biomarker-based assays with high sensitivity and specificity for the detection of this cancer are a clinical need. With the aim of studying the potential of the plasma-derived extracellular vesicles (EVs), we carried out quantitative proteomic analysis of the EV proteins, using three types of controls and various stages of the disease, which led to the identification of 86 proteins with altered abundance. These include 29 proteins unique to early stage, 44 unique to the advanced stage and 13 proteins being common to both the stages. Many proteins are functionally relevant to the tumor condition or have been also known to be differentially expressed in GBC tissues. Several of them are also present in the plasma in free state. Clinical verification of three tumor-associated proteins with elevated levels in comparison to all the three control types—5′-nucleotidase isoform 2 (NT5E), aminopeptidase N (ANPEP) and neprilysin (MME) was carried out using individual plasma samples from early or advanced stage GBC. Sensitivity and specificity assessment based on receiver operating characteristic (ROC) analysis indicated a significant association of NT5E and ANPEP with advanced stage GBC and MME with early stage GBC. These and other proteins identified in the study may be potentially useful for developing new diagnostics for GBC.

Plasma-Derived Extracellular Vesicles Reveal Galectin-3 Binding Protein as Potential Biomarker for Early Detection of Glioma

Gliomas are the most common type of the malignant brain tumor, which arise from glial cells. They make up about 40% of all primary brain tumors and around 70% of all primary malignant brain tumors. They can occur anywhere in the central nervous system (CNS) and have a poor prognosis. The average survival of glioma patients is approximately 6-15 months with poor aspects of life. In this edge, identification of proteins secreted by cancer cells is of special interest because it may provide a better understanding of tumor progression and provide early diagnosis of the diseases. Extracellular vesicles (EVs) were isolated from pooled plasma of healthy controls (n=03) and patients with different grades of glioma (Grade I or II or III, n=03 each). Nanoparticle tracking analysis, western blot, and flow cytometry were performed to determine the size, morphology, the concentration of glioma-derived vesicles and EV marker, CD63. Further, iTRAQ-based LC-MS/MS analysis of EV protein was performed to determine the differential protein abundance in extracellular vesicles across different glioma grades. We further verified galectin-3 binding protein (LGALS3BP) by ELISA in individual blood plasma and plasma-derived vesicles from control and glioma patients (n=40 each). Analysis by Max Quant identified 123 proteins from the pooled patient exosomes, out of which 34, 21, and 14 proteins were found to be differentially abundant by more than 1.3-fold in the different grades of glioma grade I, pilocytic astrocytoma; grade II, diffuse astrocytoma; grade III, anaplastic astrocytoma, respectively, in comparison with the control samples. A total of seven proteins-namely, CRP, SAA2, SERPINA3, SAA1, C4A, LV211, and KV112-showed differential abundance in all the three grades. LGALS3BP was seen to be upregulated across the different grades, and ELISA analysis from individual blood plasma and plasma-derived extracellular vesicles confirmed the increased expression of LGALS3BP in glioma patients (p<0.001). The present study provides LGALS3BP as a potential biomarker for early detection of glioma and improve survival outcome of the patient. The present study further provides the information of progression and monitoring the tumor grades (grade 1, grade II, grade III).

Incomptine A Induces Apoptosis, ROS Production and a Differential Protein Expression on Non-Hodgkin's Lymphoma Cells

Sesquiterpene lactones are of pharmaceutical interest due their cytotoxic and antitumor properties, which are commonly found within plants of several genera from the Asteraceae family such as the Decachaeta genus. From Decachaeta incompta four heliangolide, namely incomptines A-D have been isolated. In this study, cytotoxic properties of incomptine A (IA) were evaluated on four lymphoma cancer cell lines: U-937, Farage, SU-DHL-2, and REC-1. The type of cell death induced by IA and its effects on U-937 cells were analyzed based on its capability to induce apoptosis and produce reactive oxygen species (ROS) through flow cytometry with 4′,6-diamidino-2-phenylindole staining, dual annexin V/DAPI staining, and dichlorofluorescein 2′,7′-diacetate, respectively. A differential protein expression analysis study was carried out by isobaric tags for relative and absolute quantitation (iTRAQ) through UPLC-MS/MS. Results reveal that IA exhibited cytotoxic activity against the cell line U-937 (CC₅₀ of 0.12 ± 0.02 μM) and the incubation of these cells in presence of IA significantly increased apoptotic population and intracellular ROS levels. In the proteomic approach 1548 proteins were differentially expressed, out of which 587 exhibited a fold-change ≥ 1.5 and 961 a fold-change ≤ 0.67. Most of these differentially regulated proteins are involved in apoptosis, oxidative stress, glycolytic metabolism, or cytoskeleton structuration.

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.

Integrative Analysis of Metabolomic and Transcriptomic Data Reveals Metabolic Alterations in Glioma Patients

Glioma is a malignant brain tumor. There is growing evidence that its progression involves altered metabolism. This study's objective was to understand how those metabolic perturbations were manifested in plasma and urine. Metabolic signatures in blood and urine were characterized by liquid chromatography-tandem mass spectrometry. The results were linked to gene expression using data from the Gene Expression Omnibus database. Genes and pathways associated with the disease were thus identified. Forty metabolites were identified, which were differentially expressed in the plasma of glioma patients, and 61 were identified in their urine. Twenty-two metabolites and five disturbed pathways were found both in plasma and urine. Twelve metabolites in plasma and three in urine exhibited good diagnostic potential for glioma. Transcriptomic analyses revealed specific changes in the expression of 1437 genes associated with glioma. Seventeen differentially expressed genes were found to be correlated with four of the metabolites. Enrichment analysis indicated that dysregulation of glutamatergic synapse pathway might affect the pathology of glioma. Integration of metabolomics with transcriptomics can provide both a broad picture of novel cancer signatures and preliminary information about the molecular perturbations underlying glioma. These results may suggest promising targets for developing effective therapies.

Proteogenomics of glioblastoma associates molecular patterns with survival

Glioblastoma (GBM) is the most aggressive form of glioma, with poor prognosis exhibited by most patients, and a median survival time of less than 2 years. We assemble a cohort of 87 GBM patients whose survival ranges from less than 3 months and up to 10 years and perform both high-resolution mass spectrometry proteomics and RNA sequencing (RNA-seq). Integrative analysis of protein expression, RNA expression, and patient clinical information enables us to identify specific immune, metabolic, and developmental processes associated with survival as well as determine whether they are shared between expression layers or are layer specific. Our analyses reveal a stronger association between proteomic profiles and survival and identify unique protein-based classification, distinct from the established RNA-based classification. By integrating published single-cell RNA-seq data, we find a connection between subpopulations of GBM tumors and survival. Overall, our findings establish proteomic heterogeneity in GBM as a gateway to understanding poor survival.

Influencing Factors and Effects of Treatment on Quality of Life in Patients With Gastric Cancer-A Systematic Review

Background: Gastric cancer (GC) is one of the leading causes of death worldwide. It is associated with several disease-related impairments contributing to the psycho-social burden of those patients, such as deterioration of well-being and overall quality of life (QOL). The aim of this study is to present the wide range of factors potentially impacting patients' overall well-being and possible preventive interventions. Methods: This systematic review was conducted in October 2020 with a search in the PubMed, MedLine, PsycInfo, and Google Scholar databases. We used the keywords "gastric cancer," "gastric neoplasm," and each of them combined with "quality of life," "depression," and "anxiety" to identify all relevant articles reporting about potential impact factors influencing the overall well-being of patients suffering from gastric cancer. Results: Finally, 125,490 articles were found, of which 125,431 were excluded in several steps of screening. Inclusion criteria were studies carried out on human ≥18 years of age, studies in English or German language, clinical trials, registry-based studies, cohort studies, population-based studies, and certain titles and abstracts. After screening for eligibility 35 potential factors influencing overall well-being in patients with GC were identified and classified into 9 important categories: genetic condition, treatment method, blood markers, nutritional status, daily living, state of health, mental state, supportive care, and alternative treatment. Conclusion: Since various factors are involved in the development of patients' overall well-being, timely treatment of psycho-social impairments by physicians and psychologists is of enormous importance. Preventing psycho-social burden by improving patients' QOL should be of high importance in the treatment regimen of patients with GC.

Ferritin Light Chain (FTL) competes with long noncoding RNA Linc00467 for miR-133b binding site to regulate chemoresistance and metastasis of colorectal cancer

Although the colorectal cancer (CRC) mortality rates are decreasing in virtue of CRC screening and improved therapeutic methods, CRC is still a leading cause of cancer deaths. One of the main causes is chemoresistance occurrence in CRC. Understanding of the molecular mechanisms of chemoresistance benefits to CRC diagnosis and treatment. In this study, gene expression was determined by western blot and qRT-PCR. The biological functions of genes in CRC cells were studied by knocking down or overexpressing the gene in CRC cells and then analyzing cell sensitivity to 5-Fu by the MTT assay and the flow cytometry, and analyzing cell migration and invasion by transwell assays. The luciferase reporter assay was used to examine microRNA regulation of target gene expression, and biotin pull-down assay was performed to detect interaction between RNA molecules. This study found that ferritin light chain (FTL) and long intergenic noncoding RNA Linc00467 were both upregulated in CRC tissues and cell lines, and inversely correlated to CRC patient survival. FTL and Linc00467 promoted CRC cells abilities to resistance against 5-fluor-ouracil (5-Fu), migration and invasion. These effects were compromised by miR-133b which targeted both FTL and Linc00467. miR-133b interacted with Linc00467 and miR-133b inhibitor prevented Linc00467 knockdown-induced alternations of FTL expression and biological functions. Both FTL and Linc00467 are oncogenes in CRC. FTL expression upregulated in CRC via Linc00467/ miR-133b axis, and leads to CRC cell resistance against 5-FU treatment and promotes CRC metastasis. FTL expression upregulated in CRC via Linc00467/miR-133b axis, and leads to CRC cell resistance to 5-FU treatment and promotes CRC metastasis.

The development and clinical applications of proteomics: an Indian perspective

INTRODUCTION

Proteomic research has been extensively used to identify potential biomarkers or targets for various diseases. Advances in mass spectrometry along with data analytics have led proteomics to become a powerful tool for exploring the critical molecular players associated with diseases, thereby, playing a significant role in the development of proteomic applications for the clinic.

AREAS COVERED

This review presents recent advances in the development and clinical applications of proteomics in India toward understanding various diseases including cancer, metabolic diseases, and reproductive diseases. Keywords combined with 'clinical proteomics in India' 'proteomic research in India' and 'mass spectrometry' were used to search PubMed.

EXPERT OPINION

The past decade has seen a significant increase in research in clinical proteomics in India. This approach has resulted in the development of proteomics-based marker technologies for disease management in the country. The majority of these investigations are still in the discovery phase and efforts have to be made to address the intended clinical use so that the identified potential biomarkers reach the clinic. To move toward this necessity, there is a pressing need to establish some key infrastructure requirements and meaningful collaborations between the clinicians and scientists which will enable more effective solutions to address health issues specific to India.

Principal component analysis on LC‑MS/MS and 2DE‑MALDI‑TOF in glioblastoma cell lines reveals that mitochondria act as organelle sensors of the metabolic state in glioblastoma

Glioblastoma is a difficult disease to diagnose. Proteomic techniques are commonly applied in biomedical research, and can be useful for early detection, making an accurate diagnosis and reducing mortality. The relevance of mitochondria in brain development and function is well known; therefore, mitochondria may influence the development of glioblastoma. The T98G (with oxidative metabolism) and U87MG (with glycolytic metabolism) cell lines are considered to be useful glioblastoma models for studying these tumors and the role of mitochondria in key aspects of this disease, such as prognosis, metastasis and apoptosis. In the present study, principal component analysis of protein abundance data identified by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF) from 2D gels indicated that representative mitochondrial proteins were associated with glioblastoma. The selected proteins were organized into T98G- and U87MG-specific protein-protein interaction networks to demonstrate the representativeness of both proteomic techniques. Gene Ontology overrepresentation analysis based on the relevant proteins revealed that mitochondrial processes were associated with metabolic changes, invasion and metastasis in glioblastoma, along with other non-mitochondrial processes, such as DNA translation, chaperone responses and autophagy. Despite the lower resolution of 2D electrophoresis, principal component analysis yielded information of comparable quality to that of LC-MS/MS. The present analysis pipeline described a specific and more complete metabolic status for each cell line, defined a clear mitochondrial performance for distinct glioblastoma tumors, and introduced a useful strategy to understand the heterogeneity of glioblastoma.

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.

Circulating Tumor Biomarkers in Meningiomas Reveal a Signature of Equilibrium Between Tumor Growth and Immune Modulation

Meningiomas are primary central nervous system (CNS) tumors that originate from the arachnoid cells of the meninges. Recurrence occurs in higher grade meningiomas and a small subset of Grade I meningiomas with benign histology. Currently, there are no established circulating tumor markers which can be used for diagnostic and prognostic purposes in a non-invasive way for meningiomas. Here, we aimed to identify potential biomarkers of meningioma in patient sera. For this purpose, we collected preoperative (n = 30) serum samples from the meningioma patients classified as Grade I (n = 23), Grade II (n = 4), or Grade III (n = 3). We used a high-throughput, multiplex immunoassay cancer panel comprising of 92 cancer-related protein biomarkers to explore the serum protein profiles of meningioma patients. We detected 14 differentially expressed proteins in the sera of the Grade I meningioma patients in comparison to the age- and gender-matched control subjects (n = 12). Compared to the control group, Grade I meningioma patients showed increased serum levels of amphiregulin (AREG), CCL24, CD69, prolactin, EGF, HB-EGF, caspase-3, and decreased levels of VEGFD, TGF-α, E-Selectin, BAFF, IL-12, CCL9, and GH. For validation studies, we utilized an independent set of meningioma tumor tissue samples (Grade I, n = 20; Grade II, n = 10; Grade III, n = 6), and found that the expressions of amphiregulin and Caspase3 are significantly increased in all grades of meningiomas either at the transcriptional or protein level, respectively. In contrast, the gene expression of VEGF-D was significantly lower in Grade I meningioma tissue samples. Taken together, our study identifies a meningioma-specific protein signature in blood circulation of meningioma patients and highlights the importance of equilibrium between tumor-promoting factors and anti-tumor immunity.

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.

Serum Carnosinase-1 and Albuminuria Rather than the CNDP1 Genotype Correlate with Urinary Carnosinase-1 in Diabetic and Nondiabetic Patients with Chronic Kidney Disease

BACKGROUND

Carnosinase-1 (CN-1) can be detected in 24 h urine of healthy individuals and patients with type 2 diabetes (T2DM). We aimed to assess whether urinary CN-1 is also reliably measured in spot urine and investigated its association with renal function and the albumin/creatinine ratio (ACR). We also assessed associations between the CNDP1 (CTG) _n genotype and CN-1 concentrations in serum and urine.

METHODS

Patients with T2DM (n = 85) and nondiabetic patients with chronic kidney disease (CKD) (n = 26) stratified by albuminuria (ACR ≤ 300 mg/g or ACR > 300 mg/g) recruited from the nephrology clinic and healthy subjects (n = 24) were studied.

RESULTS

Urinary CN-1 was more frequently detected and displayed higher concentrations in patients with ACR > 300 mg/g as compared to those with ACR ≤ 300 mg/g irrespective of the baseline disease (T2DM: 554 ng/ml [IQR 212-934 ng/ml] vs. 31 ng/ml [IQR 31-63 ng/ml] (p < 0.0001) and nondiabetic CKD: 197 ng/ml [IQR 112-739] vs. 31 ng/ml [IQR 31-226 ng/ml] (p = 0.015)). A positive correlation between urinary CN-1 and ACR was found (r = 0.68, p < 0.0001). Multivariate linear regression analysis revealed that ACR and serum CN-1 concentrations but not eGFR or the CNDP1 genotype are independent predictors of urinary CN-1, explaining 47% of variation of urinary CN-1 concentrations (R ² = 0.47, p < 0.0001).

CONCLUSION

These results confirm and extend previous findings on urinary CN-1 concentrations, suggesting that assessment of CN-1 in spot urine is as reliable as in 24 h urine and may indicate that urinary CN-1 in macroalbuminuric patients is primarily serum-derived and not locally produced.

Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

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).

Transferrin receptor-1 and ferritin heavy and light chains in astrocytic brain tumors: Expression and prognostic value

Astrocytic brain tumors are the most frequent primary brain tumors. Treatment with radio- and chemotherapy has increased survival making prognostic biomarkers increasingly important. The aim of the present study was to investigate the expression and prognostic value of transferrin receptor-1 (TfR1) as well as ferritin heavy (FTH) and light (FTL) chain in astrocytic brain tumors. A cohort of 111 astrocytic brain tumors (grade II-IV) was stained immunohistochemically with antibodies against TfR1, FTH, and FTL and scored semi-quantitatively. Double-immunofluorescence stainings were established to determine the phenotype of cells expressing these markers. We found that TfR1, FTH, and FTL were expressed by tumor cells in all grades. TfR1 increased with grade (p<0.001), but was not associated with prognosis in the individual grades. FTH and FTL were expressed by tumor cells and cells with microglial/macrophage morphology. Neither FTH nor FTL increased with malignancy grade, but low FTH expression by both tumor cells (p = 0.03) and microglia/macrophages (p = 0.01) correlated with shorter survival in patients anaplastic astrocytoma. FTL-positive microglia/macrophages were frequent in glioblastomas, and high FTL levels correlated with shorter survival in the whole cohort (p = 0.01) and in patients with anaplastic astrocytoma (p = 0.02). Double-immunofluorescence showed that TfR1, FTH, and FTL were co-expressed to a limited extent with the stem cell-related marker CD133. FTH and FTL were also co-expressed by IBA-1-positive microglia/macrophages. In conclusion, TfR1 was highly expressed in glioblastomas and associated with shorter survival in the whole cohort, but not in the individual malignancy grades. Low levels of FTH-positive tumor cells and microglia/macrophages were associated with poor survival in anaplastic astrocytomas, while high amounts of FTL-positive microglia/macrophages had a negative prognostic value. The results suggest that regulation of the iron metabolism in astrocytic brain tumors is complex involving both autocrine and paracrine signaling.

S100A6 protein: functional roles

S100A6 protein belongs to the A group of the S100 protein family of Ca2+-binding proteins. It is expressed in a limited number of cell types in adult normal tissues and in several tumor cell types. As an intracellular protein, S100A6 has been implicated in the regulation of several cellular functions, such as proliferation, apoptosis, the cytoskeleton dynamics, and the cellular response to different stress factors. S100A6 can be secreted/released by certain cell types which points to extracellular effects of the protein. RAGE (receptor for advanced glycation endproducts) and integrin β1 transduce some extracellular S100A6's effects. Dosage of serum S100A6 might aid in diagnosis in oncology.

iTRAQ-based quantitative proteomic analysis of Yamanaka factors reprogrammed breast cancer cells

Cancer cells had been developed to be reprogrammed into embryonic stem like cells by induced pluripotent stem cells (iPSCs) technology, however, the tumor differentiation/dedifferentiation mechanisms had not yet been analyzed on a genome-wide scale. Here, we inserted the four stem cell transcription factor genes OCT4, SOX2, C-MYC and KLF4 into MCF cells (MCFs), represented a female breast cancer cell type, and obtained iPSCs (Mcfips) in about 3 weeks. By using the LC MS/MS iTRAQ technology, we analyzed the proteomic changes between MCFs and Mcfips. Of identified 4,616 proteins totally, 247 and 142 differentially expressed (DE) proteins were found in Mcfips compared with human induce pluripotent stem cells (Hips) and MCFs, respectively. 35 co-up and 10 co-down regulated proteins were recognized in DE proteins. Above DE proteins were categorized with GO functional classification annotation and KEGG metabolic pathway analysis into biological processes. In the protein interaction network, we found 37 and 39 hubs interacted with more than one protein in Mcfips comparing to Hips, in addition, 25 and 9 hubs were identified in Mcfips comparing to MCFs. Importantly, the mitochondria, ribosome and tumor suppressor proteins were found to be core regulators of tumor reprogramming, which might contribute to understand the mechanisms in relation to the occurrences and progression of a tumor. Thus, our study provided a valuable data for exploring the possibility to normalize the malignant phenotype.

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.

Proteomics in India: the clinical aspect

Proteomics has emerged as a highly promising bioanalytical technique in various aspects of applied biological research. In Indian academia, proteomics research has grown remarkably over the last decade. It is being extensively used for both basic as well as translation research in the areas of infectious and immune disorders, reproductive disorders, cardiovascular diseases, diabetes, eye disorders, human cancers and hematological disorders. Recently, some seminal works on clinical proteomics have been reported from several laboratories across India. This review aims to shed light on the increasing use of proteomics in India in a variety of biological conditions. It also highlights that India has the expertise and infrastructure needed for pursuing proteomics research in the country and to participate in global initiatives. Research in clinical proteomics is gradually picking up pace in India and its future seems very bright.

Immune phenotypes predict survival in patients with glioblastoma multiforme

Background

Glioblastoma multiforme (GBM), a common primary malignant brain tumor, rarely disseminates beyond the central nervous system and has a very bad prognosis. The current study aimed at the analysis of immunological control in individual patients with GBM.

Methods

Immune phenotypes and plasma biomarkers of GBM patients were determined at the time of diagnosis using flow cytometry and ELISA, respectively.

Results

Using descriptive statistics, we found that immune anomalies were distinct in individual patients. Defined marker profiles proved highly relevant for survival. A remarkable relation between activated NK cells and improved survival in GBM patients was in contrast to increased CD39 and IL-10 in patients with a detrimental course and very short survival. Recursive partitioning analysis (RPA) and Cox proportional hazards models substantiated the relevance of absolute numbers of CD8 cells and low numbers of CD39 cells for better survival.

Conclusions

Defined alterations of the immune system may guide the course of disease in patients with GBM and may be prognostically valuable for longitudinal studies or can be applied for immune intervention.

Electronic supplementary material

The online version of this article (doi:10.1186/s13045-016-0272-3) contains supplementary material, which is available to authorized users.

Quantitative proteomic analysis exploring progression of colorectal cancer: Modulation of the serpin family

Colorectal cancer (CRC) remains a major cause of cancer related-death in developed countries. The mortality risk is correlated with the stage of CRC determined at the primary diagnosis and early diagnosis is associated with enhanced survival rate. Currently, only faecal occult blood tests are used to screen for CRC. Consequently, there is an incentive to identify specific markers of CRC. We used quantitative proteomic analysis of serum samples to characterize protein profiles in adenoma, CRC and healthy control samples. We identified 89 distinct proteins modulated between normal, colorectal adenoma and carcinoma patients. This list emphasizes proteins involved in enzyme regulator activities and in particular the serpin family. In serum samples, protein profiles of three members of the serpin family (SERPINA1, SERPINA3 and SERPINC1) were confirmed by ELISA assays. We obtained sensitivity/specificity values of 95%/95% for both SERPINA1 and SERPINC1, and 95%/55% for SERPINA3. This study supports the idea that serum proteins can discriminate adenoma and CRC patients from unaffected patients and reveals a panel of regulated proteins that might be useful for selecting patients for colonoscopy. By evaluating SERPINA1, SERPINA3 and SERPINC1, we highlight the potential role of the serpin family during the development and progression of CRC.

SIGNIFICANCE

Colorectal cancer (CRC) remains a major cause of cancer mortality throughout the world. However, very few CRC biomarkers have satisfactory sensitivity and specificity in clinical practice. To the best of our knowledge our study is the first to profile sera proteomes between adenoma, CRC and healthy patients. We report a comprehensive list of proteins that may be used as early diagnostic biomarkers of CRC. It is noteworthy that 17% of these modulated proteins have been previously described as candidate biomarkers in CRC. Enzyme regulator activity was found to be the main molecular function among these proteins and, in particular, there was an enrichment of members of the serpin family. The subsequent verification on a new cohort by ELISA demonstrates that these serpins could be useful to discriminate healthy from colorectal carcinoma patients with a high sensitivity and specificity. The combination of these biomarkers should increase predictive powers of CRC diagnosis. The remaining candidates form a reserve for further evaluation of additional biomarkers for CRC diagnosis.

Plasma proteomics for the assessment of acute renal transplant rejection

Renal transplant is the best treatment for patients with chronical kidney disease however acute graft rejection is the major impediment to success in renal transplantation leading to loss of the organ the first year after transplantation. The aim of this study was to identify plasma proteins that may be early biomarkers of acute rejection of renal allograft, developing a diagnostic model that avoids the loss of the transplanted organ. Shotgun proteomics (LC-MS/MS) method was used to analyze a set of thirty-one plasma samples, including 06 from patients with acute graft rejection after transplantation (rejection group/Rej-group) and twenty-five from renal transplant patients with stable renal graft function (control group/Ct-group). As results nineteen proteins were upregulated in the rejection group compared to the control group, and two proteins were downregulated; and three were present exclusively in the rejection group. After analysis, we selected four proteins that were related to the acute phase response and that were strongly associated with each other: they are alpha-1 antitrypsin (A1AT), alpha-2 antiplasmin (A2AP), serum amyloid A (SAA) and apolipoprotein CIII (APOC3). We think that simultaneous monitoring of SAA and APOC3 can provide insights into a broad profile of signaling proteins and is highly valuable for the early detection of a possible acute renal graft rejection.

STATEMENT OF SIGNIFICANCE OF THE STUDY

In this study we did plasma shotgun patients with and without acute rejection of renal allograft. In a clinical setting an acute rejection is typically suspected upon an increase in plasma creatinine and renal biopsy. But these methods are late and unspecific; sometimes the rejection process is already advanced when there is an increase in serum creatinine. Therefore, it is necessary to find proteins that can predict the allograft rejection process. In our study were able to identify changes in the concentration of plasma protein belonging to a network of protein interaction processes the acute phase response. We believe, therefore, that development of a routine diagnosis of these proteins can detect early acute rejection of renal allograft process, thus preventing its loss.

Expression of Ferritin Light Chain (FTL) Is Elevated in Glioblastoma, and FTL Silencing Inhibits Glioblastoma Cell Proliferation via the GADD45/JNK Pathway

Accumulating evidence suggests that iron-associated proteins contribute to tumor initiation and development. Ferritin light chain (FTL), a key protein in iron metabolism, is associated with the survival of glioblastoma multiforme (GBM) patients; however, the molecular mechanisms underlying this association remain largely unclear. Therefore, in the present study, we investigated the role of FTL in the pathogenesis of GBM. By using quantitative real-time RT-PCR, we found that expression of FTL was higher in patients with GBM than in those with low-grade glioma. Immunofluorescence showed that FTL was mainly localized in the nucleus of GBM cells and was closely associated with mitotic spindles. Knockdown of FTL resulted in inhibition of cell growth and activation of the GADD45A/JNK pathway in GBM cells. Immunoblotting revealed that levels of GADD45A protein decreased in GBM cells when FTL expression increased. Furthermore, transfection of GADD45A in GBM cells significantly decreased cell viability, and this effect was impeded by co-transfection of FTL. Moreover, FTL was found to localize with GADD45A in GBM cells, and a coimmunoprecipitation experiment showed that the two proteins physically interacted. Taken together, these results demonstrate a novel mechanism by which FTL regulates the growth of GBM cells via the GADD45/JNK pathway.

Proteomics Study on Nonallergic Hypersensitivity Induced by Compound 4880 and Ovalbumin

Nonallergic hypersensitivity reaction (NHR) accounts for more than 77% of all immune-mediated immediate hypersensitivity reactions and has become a serious threat to public health. Here, proteomics was used to study the NHR mechanism of two typical substances, the compound 4880 and ovalbumin. Twelve different proteins were suggested as potential biomarkers for examining the NHR mechanism, and our results revealed that the mechanism mainly encompassed 2 processes, i.e., generation and effect processes. The generation process could be classified as direct stimulation, complement (classical and alternative), coagulation, kallikrein-kinin, and integrated pathways. Thus glutathione peroxidase 1, terminal complement complex (complement factor 4d and Bb), coagulation 13, kininogen-1, and IgE could be used as candidate biomarkers for the indication of the corresponding pathways respectively, the proteins were further confirmed by ELISA. And the effect process was mainly composed of histamine as well as proteins such as DCD and MYLPF, which could be used as important indices for the symptoms of NHR. Our study differs from previous studies in that C4880 was found to not only be involved in the direct stimulation pathway, but also in the activated complement and kallikrein-kinin pathways through the coagulation pathway. We also report for the first time that ovalbumin-induced NHR could be a combination of the coagulation, classical complement, and integrated pathways.

Targeted Proteomics to Assess the Response to Anti-Angiogenic Treatment in Human Glioblastoma (GBM)

Glioblastoma (GBM) is a highly aggressive primary brain tumor with dismal outcome for affected patients. Because of the significant neo-angiogenesis exhibited by GBMs, anti-angiogenic therapies have been intensively evaluated during the past years. Recent clinical studies were however disappointing, although a subpopulation of patients may benefit from such treatment. We have previously shown that anti-angiogenic targeting in GBM increases hypoxia and leads to a metabolic adaptation toward glycolysis, suggesting that combination treatments also targeting the glycolytic phenotype may be effective in GBM patients. The aim of this study was to identify marker proteins that are altered by treatment and may serve as a short term readout of anti-angiogenic therapy. Ultimately such proteins could be tested as markers of efficacy able to identify patient subpopulations responsive to the treatment. We applied a proteomics approach based on selected reaction monitoring (SRM) to precisely quantify targeted protein candidates, selected from pathways related to metabolism, apoptosis and angiogenesis. The workflow was developed in the context of patient-derived intracranial GBM xenografts developed in rodents and ensured the specific identification of human tumor versus rodent stroma-derived proteins. Quality control experiments were applied to assess sample heterogeneity and reproducibility of SRM assays at different levels. The data demonstrate that tumor specific proteins can be precisely quantified within complex biological samples, reliably identifying small concentration differences induced by the treatment. In line with previous work, we identified decreased levels of TCA cycle enzymes, including isocitrate dehydrogenase, whereas malectin, calnexin, and lactate dehydrogenase A were augmented after treatment. We propose the most responsive proteins of our subset as potential novel biomarkers to assess treatment response after anti-angiogenic therapy that warrant future analysis in clinical GBM samples.

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.

Liquid biopsies in patients with diffuse glioma

Diffuse gliomas are the most common malignant primary tumors of the central nervous system. Like other neoplasms, these gliomas release molecular information into the circulation. Tumor-derived biomarkers include proteins, nucleic acids, and tumor-derived extracellular vesicles that accumulate in plasma, serum, blood platelets, urine and/or cerebrospinal fluid. Recently, also circulating tumor cells have been identified in the blood of glioma patients. Circulating molecules, vesicles, platelets, and cells may be useful as easily accessible diagnostic, prognostic and/or predictive biomarkers to guide patient management. Thereby, this approach may help to circumvent problems related to tumor heterogeneity and sampling error at the time of diagnosis. Also, liquid biopsies may allow for serial monitoring of treatment responses and of changes in the molecular characteristics of gliomas over time. In this review, we summarize the literature on blood-based biomarkers and their potential value for improving the management of patients with a diffuse glioma. Incorporation of the study of circulating molecular biomarkers in clinical trials is essential for further assessment of the potential of liquid biopsies in this context.

Circulating carnosine dipeptidase 1 associates with weight loss and poor prognosis in gastrointestinal cancer

BACKGROUND

Cancer cachexia (CC) is linked to poor prognosis. Although the mechanisms promoting this condition are not known, several circulating proteins have been proposed to contribute. We analyzed the plasma proteome in cancer subjects in order to identify factors associated with cachexia.

DESIGN/SUBJECTS

Plasma was obtained from a screening cohort of 59 patients, newly diagnosed with suspected gastrointestinal cancer, with (n = 32) or without (n = 27) cachexia. Samples were subjected to proteomic profiling using 760 antibodies (targeting 698 individual proteins) from the Human Protein Atlas project. The main findings were validated in a cohort of 93 patients with verified and advanced pancreas cancer.

RESULTS

Only six proteins displayed differential plasma levels in the screening cohort. Among these, Carnosine Dipeptidase 1 (CNDP1) was confirmed by sandwich immunoassay to be lower in CC (p = 0.008). In both cohorts, low CNDP1 levels were associated with markers of poor prognosis including weight loss, malnutrition, lipid breakdown, low circulating albumin/IGF1 levels and poor quality of life. Eleven of the subjects in the discovery cohort were finally diagnosed with non-malignant disease but omitting these subjects from the analyses did not have any major influence on the results.

CONCLUSIONS

In gastrointestinal cancer, reduced plasma levels of CNDP1 associate with signs of catabolism and poor outcome. These results, together with recently published data demonstrating lower circulating CNDP1 in subjects with glioblastoma and metastatic prostate cancer, suggest that CNDP1 may constitute a marker of aggressive cancer and CC.

Circulating biomarker panels for targeted therapy in brain tumors

An important goal of oncology is the development of cancer risk-identifier biomarkers that aid early detection and target therapy. High-throughput profiling represents a major concern for cancer research, including brain tumors. A promising approach for efficacious monitoring of disease progression and therapy could be circulating biomarker panels using molecular proteomic patterns. Tailoring treatment by targeting specific protein-protein interactions and signaling networks, microRNA and cancer stem cell signaling in accordance with tumor phenotype or patient clustering based on biomarker panels represents the future of personalized medicine for brain tumors. Gathering current data regarding biomarker candidates, we address the major challenges surrounding the biomarker field of this devastating tumor type, exploring potential perspectives for the development of more effective predictive biomarker panels.

Quantitative proteomic analysis of meningiomas for the identification of surrogate protein markers

Meningiomas are the most common non-glial tumors of the brain and spine. Pathophysiology and definite histological grading of meningiomas are frequently found to be deceptive due to their unusual morphological features and locations. Here for the first time we report a comprehensive serum proteomic analysis of different grades of meningiomas by using multiple quantitative proteomic and immunoassay-based approaches to obtain mechanistic insights about disease pathogenesis and identify grade specific protein signatures. In silico functional analysis revealed modulation of different vital physiological pathways including complement and coagulation cascades, metabolism of lipids and lipoproteins, immune signaling, cell growth and apoptosis and integrin signaling in meningiomas. ROC curve analysis demonstrated apolipoprotein E and A-I and hemopexin as efficient predictors for meningiomas. Identified proteins like vimentin, alpha-2-macroglobulin, apolipoprotein B and A-I and antithrombin-III, which exhibited a sequential increase in different malignancy grades of meningiomas, could serve as potential predictive markers.

Towards developing biomarkers for glioblastoma multiforme: a proteomics view

Glioblastoma multiforme (GBM) is one of the most aggressive and lethal forms of the primary brain tumors. With predominance of tumor heterogeneity and emergence of new subtypes, new approaches are needed to develop tissue-based markers for tumor typing or circulatory markers to serve as blood-based assays. Multi-omics data integration for GBM tissues would offer new insights on the molecular view of GBM pathogenesis useful to identify biomarker panels. On the other hand, mapping differentially expressed tissue proteins for their secretory potential through bioinformatics analysis or analysis of the tumor cell secretome or tumor exosomes would enhance our understanding of the tumor microenvironment and prospects for targeting circulatory biomarkers. In this review, the authors first present potential biomarker candidates for GBM that have been reported and then focus on plausible pipelines for multi-omic data integration to identify additional, high-confidence molecular panels for clinical applications in GBM.

Identification of plasma biomarker candidates in glioblastoma using an antibody-array-based proteomic approach

Background

Glioblastoma multiforme (GBM) is a brain tumour with a very high patient mortality rate, with a median survival of 47 weeks. This might be improved by the identification of novel diagnostic, prognostic and predictive therapy-response biomarkers, preferentially through the monitoring of the patient blood. The aim of this study was to define the impact of GBM in terms of alterations of the plasma protein levels in these patients.

Materials and methods.

We used a commercially available antibody array that includes 656 antibodies to analyse blood plasma samples from 17 healthy volunteers in comparison with 17 blood plasma samples from patients with GBM.

Results

We identified 11 plasma proteins that are statistically most strongly associated with the presence of GBM. These proteins belong to three functional signalling pathways: T-cell signalling and immune responses; cell adhesion and migration; and cell-cycle control and apoptosis. Thus, we can consider this identified set of proteins as potential diagnostic biomarker candidates for GBM. In addition, a set of 16 plasma proteins were significantly associated with the overall survival of these patients with GBM. Guanine nucleotide binding protein alpha (GNAO1) was associated with both GBM presence and survival of patients with GBM.

Conclusions

Antibody array analysis represents a useful tool for the screening of plasma samples for potential cancer biomarker candidates in small-scale exploratory experiments; however, clinical validation of these candidates requires their further evaluation in a larger study on an independent cohort of patients.

Insulin-like growth factor 1 receptor signaling induced by supraphysiological doses of IGF-1 in human peripheral blood lymphocytes

Insulin-like growth factor-1 (IGF-1) mediates some of growth hormone anabolic functions through its receptor, IGF-1R. Following ligand binding, intracellular signaling pathways are activated favouring proliferation, cell survival, tissue growth, development, and differentiation. IGF-1 is included in the World Anti-Doping Agency Prohibited List. While the evidence for IGF-1 as performance-enhancing substrate in healthy humans is still weak, clinical studies demonstrated that the endogenous growth hormone/IGF-1 excess is associated with cardiovascular implications. Previously, we demonstrated that human peripheral blood lymphocytes represent a suitable system to identify a gene signature, related to dihydrotestosterone or IGF-1 abuse, independent from the type of sport. In addition, in a proteomic study, we demonstrated that dihydrotestosterone hyperdosage affects cell motility and apoptosis. Here, we investigate the doping action of IGF-1 by means of a differential proteomic approach and specific protein arrays, revealing an active cytoskeletal reorganization mediated by Stat-1; moreover, IGF-1 stimulation produces a sustained activation of different signaling pathways as well as an overproduction of cytokines positively related to immune response and inflammation. In conclusion, these data indicate that, following IGF-1 hyperdosage, circulating peripheral blood lymphocytes could be more prone to transendothelial migration.