Alterations in cerebrospinal fluid proteins in a presymptomatic primary glioma model

Liquid Biomarkers for Improved Diagnosis and Classification of CNS Tumors

Liquid biopsy, as a non-invasive technique for cancer diagnosis, has emerged as a major step forward in conquering tumors. Current practice in diagnosis of central nervous system (CNS) tumors involves invasive acquisition of tumor biopsy upon detection of tumor on neuroimaging. Liquid biopsy enables non-invasive, rapid, precise and, in particular, real-time cancer detection, prognosis and treatment monitoring, especially for CNS tumors. This approach can also uncover the heterogeneity of these tumors and will likely replace tissue biopsy in the future. Key components of liquid biopsy mainly include circulating tumor cells (CTC), circulating tumor nucleic acids (ctDNA, miRNA) and exosomes and samples can be obtained from the cerebrospinal fluid, plasma and serum of patients with CNS malignancies. This review covers current progress in application of liquid biopsies for diagnosis and monitoring of CNS malignancies.

Profiling of Cerebrospinal Fluid Lipids and Their Relationship with Plasma Lipids in Healthy Humans

Lipidomics provides an overview of lipid profiles in biological systems. Although blood is commonly used for lipid profiling, cerebrospinal fluid (CSF) is more suitable for exploring lipid homeostasis in brain diseases. However, whether an individual’s background affects the CSF lipid profile remains unclear, and the association between CSF and plasma lipid profiles in heathy individuals has not yet been defined. Herein, lipidomics approaches were employed to analyze CSF and plasma samples obtained from 114 healthy Japanese subjects. Results showed that the global lipid profiles differed significantly between CSF and plasma, with only 13 of 114 lipids found to be significantly correlated between the two matrices. Additionally, the CSF total protein content was the primary factor associated with CSF lipids. In the CSF, the levels of major lipids, namely, phosphatidylcholines, sphingomyelins, and cholesterolesters, correlated with CSF total protein levels. These findings indicate that CSF lipidomics can be applied to explore changes in lipid homeostasis in patients with brain diseases.

Potential biomarkers of childhood brain tumor identified by proteomics of cerebrospinal fluid from extraventricular drainage (EVD)

Brain tumors are the most common solid tumors in childhood. There is the need for biomarkers of residual disease, therapy response and recurrence. Cerebrospinal fluid (CSF) is a source of brain tumor biomarkers. We analyzed the proteome of waste CSF from extraventricular drainage (EVD) from 29 children bearing different brain tumors and 17 controls needing EVD insertion for unrelated causes. 1598 and 1526 proteins were identified by liquid chromatography-coupled tandem mass spectrometry proteomics in CSF control and brain tumor patients, respectively, 263 and 191 proteins being exclusive of either condition. Bioinformatic analysis revealed promising protein biomarkers for the discrimination between control and tumor (TATA-binding protein-associated factor 15 and S100 protein B). Moreover, Thymosin beta-4 (TMSB4X) and CD109, and 14.3.3 and HSP90 alpha could discriminate among other brain tumors and low-grade gliomas plus glyoneuronal tumors/pilocytic astrocytoma, or embryonal tumors/medulloblastoma. Biomarkers were validated by ELISA assay. Our method was able to distinguish among brain tumor vs non-tumor/hemorrhagic conditions (controls) and to differentiate two large classes of brain tumors. Further prospective studies may assess whether the biomarkers proposed by our discovery approach can be identified in other bodily fluids, therefore less invasively, and are useful to guide therapy and predict recurrences.

Effect of aquaporin 4 protein overexpression in nigrostriatal system on development of Parkinson's disease

OBJECTS

Recent studies indicated that aquaporin 4 (AQP4), as the main water channel in the central nervous system (CNS), participated in the onset and progression of Parkinson's disease (PD). But how the AQP4 influenced the exacerbation of PD has not been described in detail. In this study, the effect of the AQP4 protein overexpression in nigrostriatal system that include substantia nigra (SN) and striatum (CPu) on the development of PD was investigated.

METHODS

Forty male Sprague Dawley rats were equally divided into two groups at random: PD group and control group, PD group undergoing surgery and receiving 6-hydroxydopamine (6-OHDA). Using MRI tracer-based method, extracellular space (ECS) diffusion parameters of nigrostriatal system for all rats were measured, including the clearance coefficient (k') and the half-life (t_1/2). Immunohistochemistry of AQP4 was performed for 20 rats.

RESULTS

The area of dark-stained AQP4 immunoreactivity increased markedly in SN of PD rats, there were significant differences between two groups (SN: t = 5.809, p < 0.0001; CPu: t = 5.943, p < 0.0001). And the diffusion parameters were significantly greater in PD group than that of control group, including k' (SN: t = 5.519, p < 0.0001; CPu: t = 2.149, p = 0.045) and t_1/2 (SN: t = 6.131, p < 0.0001; CPu: t = 6.708, p < 0.0001). There was a significant positive correlation between the AQP4 expression level and the k' values (SN: r = 0.827, p = 0.0031; CPu: r = 0.641, p = 0.0046), and a significant negative correlation between AQP4 and the t_1/2 values (SN: r=-0.654, p = 0.0403; CPu: r=-0.664, p = 0.0362).

CONCLUSIONS

The results indicated that AQP4 expression was increased in nigrostriatal system of PD rats, therefore, the overexpression of AQP4 led to acceleration of the diffusion and drainage process of drugs in ECS, reduced the effect of drugs for the treatment of PD, inhibited the development of PD.

A proteomic clock for malignant gliomas: The role of the environment in tumorigenesis at the presymptomatic stage

Malignant gliomas remain incurable with a poor prognosis despite of aggressive treatment. We have been studying the development of brain tumors in a glioma rat model, where rats develop brain tumors after prenatal exposure to ethylnitrosourea (ENU), and there is a sizable interval between when the first pathological changes are noted and tumors become detectable with MRI. Our aim to define a molecular timeline through proteomic profiling of the cerebrospinal fluid (CSF) such that brain tumor commitment can be revealed earlier than at the presymptomatic stage. A comparative proteomic approach was applied to profile CSF collected serially either before, at and after the time MRI becomes positive. Elastic net (EN) based models were developed to infer the timeline of normal or tumor development respectively, mirroring a chronology of precisely timed, “clocked”, adaptations. These CSF changes were later quantified by longitudinal entropy analyses of the EN predictive metric. False discovery rates (FDR) were computed to control the expected proportion of the EN models that are due to multiple hypothesis testing. Our ENU rat brain tumor dating EN model indicated that protein content in CSF is programmed even before tumor MRI detection. The findings of the precisely timed CSF tumor microenvironment changes at presymptomatic stages, deviation from the normal development timeline, may provide the groundwork for the understanding of adaptation of the brain environment in tumorigenesis to devise effective brain tumor management strategies.

Proteomic analysis of cerebrospinal fluid from children with central nervous system tumors identifies candidate proteins relating to tumor metastatic spread

Central nervous system (CNS) tumors are the most common solid tumors in childhood. Since the sensitivity of combined cerebrospinal fluid (CSF) cytology and radiological neuroimaging in detecting meningeal metastases remains relatively low, we sought to characterize the CSF proteome of patients with CSF tumors to identify biomarkers predictive of metastatic spread. CSF samples from 27 children with brain tumors and 13 controls (extra-CNS non-Hodgkin lymphoma) were processed using core-shell hydrogel nanoparticles, and analyzed with reverse-phase liquid chromatography/electrospray tandem mass spectrometry (LC-MS/MS). Candidate proteins were identified with Fisher's exact test and/or a univariate logistic regression model. Reverse phase protein array (RPPA), Western blot (WB), and ELISA were used in the training set and in an independent set of CFS samples (60 cases, 14 controls) to validate our discovery findings. Among the 558 non-redundant proteins identified by LC-MS/MS, 147 were missing from the CSF database at http://www.biosino.org. Fourteen of the 26 final top-candidate proteins were chosen for validation with WB, RPPA and ELISA methods. Six proteins (type 1 collagen, insulin-like growth factor binding protein 4, procollagen C-endopeptidase enhancer 1, glial cell-line derived neurotrophic factor receptor α2, inter-alpha-trypsin inhibitor heavy chain 4, neural proliferation and differentiation control protein-1) revealed the ability to discriminate metastatic cases from controls. Combining a unique dataset of CSFs from pediatric CNS tumors with a novel enabling nanotechnology led us to identify CSF proteins potentially related to metastatic status.

Multi-pronged proteomic analysis to study the glioma pathobiology using cerebrospinal fluid samples

PURPOSE

Gliomas are one of the most aggressive and lethal brain tumors arising from neoplastic transformation of astrocytes and oligodendrocytes. A comprehensive quantitative analysis of proteome level differences in cerebrospinal fluid (CSF) across different grades of gliomas for a better understanding of glioma pathobiology is carried out.

EXPERIMENTAL DESIGN

Glioma patients are diagnosed by radiology and histochemistry-based analyses. Differential proteomic analysis of high (n = 12) and low (n = 5) grade gliomas, and control (n = 3) samples is performed by using two complementary quantitative proteomic approaches; 2D-DIGE and iTRAQ. Further, comparative analysis of three IDH wild-type and five IDH mutants is performed to identify the proteome level differences between these two sub-classes.

RESULTS

Level of several proteins including haptoglobin, transthyretin, osteopontin, vitronectin, complement factor H and different classes of immunoglobulins are found to be considerably increased in CSF of higher grades of gliomas. Subsequent bioinformatics analysis indicated that many of the dysregulated CSF proteins are associated with metabolism of lipids and lipoproteins, complement and coagulation cascades and extracellular matrix remodeling in gliomas. Intriguingly, CSF of glioma patients with IDH mutations exhibite increased levels of multiple proteins involved in response to oxidative stress.

CONCLUSION AND CLINICAL RELEVANCE

To the best of our knowledge, this is the foremost proteome level investigation describing comprehensive proteome profiles of different grades of gliomas using proximal fluid (CSF); and thereby providing insights into disease pathobiology, which aided in identification of grade and sub-type specific alterations. Moreover, if validated in larger clinical cohorts, a panel of differentially abundant CSF proteins may serve as potential disease monitoring and prognostic markers for gliomas.

A Novel Truncated Form of Serum Amyloid A in Kawasaki Disease

Background

Kawasaki disease (KD) is an acute vasculitis in children that can cause coronary artery abnormalities. Its diagnosis is challenging, and many cytokines, chemokines, acute phase reactants, and growth factors have failed evaluation as specific biomarkers to distinguish KD from other febrile illnesses. We performed protein profiling, comparing plasma from children with KD with febrile control (FC) subjects to determine if there were specific proteins or peptides that could distinguish the two clinical states.

Materials and Methods

Plasma from three independent cohorts from the blood of 68 KD and 61 FC subjects was fractionated by anion exchange chromatography, followed by surface-enhanced laser desorption ionization (SELDI) mass spectrometry of the fractions. The mass spectra of KD and FC plasma samples were analyzed for peaks that were statistically significantly different.

Results

A mass spectrometry peak with a mass of 7,860 Da had high intensity in acute KD subjects compared to subacute KD (p = 0.0003) and FC (p = 7.9 x 10⁻¹⁰) subjects. We identified this peak as a novel truncated form of serum amyloid A with N-terminal at Lys-34 of the circulating form and validated its identity using a hybrid mass spectrum immunoassay technique. The truncated form of serum amyloid A was present in plasma of KD subjects when blood was collected in tubes containing protease inhibitors. This peak disappeared when the patients were examined after their symptoms resolved. Intensities of this peptide did not correlate with KD-associated laboratory values or with other mass spectrum peaks from the plasma of these KD subjects.

Conclusions

Using SELDI mass spectrometry, we have discovered a novel truncated form of serum amyloid A that is elevated in the plasma of KD when compared with FC subjects. Future studies will evaluate its relevance as a diagnostic biomarker and its potential role in the pathophysiology of KD.

Novel delivery methods bypassing the blood-brain and blood-tumor barriers

Glioblastoma (GBM) is the most common primary brain tumor and carries a grave prognosis. Despite years of research investigating potentially new therapies for GBM, the median survival rate of individuals with this disease has remained fairly stagnant. Delivery of drugs to the tumor site is hampered by various barriers posed by the GBM pathological process and by the complex physiology of the blood-brain and blood-cerebrospinal fluid barriers. These anatomical and physiological barriers serve as a natural protection for the brain and preserve brain homeostasis, but they also have significantly limited the reach of intraparenchymal treatments in patients with GBM. In this article, the authors review the functional capabilities of the physical and physiological barriers that impede chemotherapy for GBM, with a specific focus on the pathological alterations of the blood-brain barrier (BBB) in this disease. They also provide an overview of current and future methods for circumventing these barriers in therapeutic interventions. Although ongoing research has yielded some potential options for future GBM therapies, delivery of chemotherapy medications across the BBB remains elusive and has limited the efficacy of these medications.

Cerebrospinal fluid protein dynamic driver network: At the crossroads of brain tumorigenesis

To get a better understanding of the ongoing in situ environmental changes preceding the brain tumorigenesis, we assessed cerebrospinal fluid (CSF) proteome profile changes in a glioma rat model in which brain tumor invariably developed after a single in utero exposure to the neurocarcinogen ethylnitrosourea (ENU). Computationally, the CSF proteome profile dynamics during the tumorigenesis can be modeled as non-smooth or even abrupt state changes. Such brain tumor environment transition analysis, correlating the CSF composition changes with the development of early cellular hyperplasia, can reveal the pathogenesis process at network level during a time before the image detection of the tumors. In our controlled rat model study, matched ENU- and saline-exposed rats' CSF proteomics changes were quantified at approximately 30, 60, 90, 120, 150 days of age (P30, P60, P90, P120, P150). We applied our transition-based network entropy (TNE) method to compute the CSF proteome changes in the ENU rat model and test the hypothesis of the critical transition state prior to impending hyperplasia. Our analysis identified a dynamic driver network (DDN) of CSF proteins related with the emerging tumorigenesis progressing from the non-hyperplasia state. The DDN associated leading network CSF proteins can allow the early detection of such dynamics before the catastrophic shift to the clear clinical landmarks in gliomas. Future characterization of the critical transition state (P60) during the brain tumor progression may reveal the underlying pathophysiology to device novel therapeutics preventing tumor formation. More detailed method and information are accessible through our website at http://translationalmedicine.stanford.edu.

Proteomic analysis of cerebrospinal fluid: toward the identification of biomarkers for gliomas

Gliomas are the most common primary brain tumors in adults and, despite advances in the understandings of glioma pathogenesis in the genetic era, they are still ineradicable, justifying the need to develop more reliable diagnostic and prognostic biomarkers for this malignancy. Because changes in cerebrospinal fluid (CSF) are suggested to be capable of sensitively reflecting pathological processes, e.g., neoplastic conditions, in the central nervous system, CSF has been deemed a valuable source for potential biomarkers screening in this era of proteomics. This systematic review focused on the proteomic analysis of glioma CSF that has been published to date and identified a total of 19 differentially expressed proteins. Further functional and protein-protein interaction assessments were performed by using Protein Analysis Through Evolutionary Relationships (PANTHER) website and Ingenuity Pathway Analysis (IPA) software, which revealed several important protein networks (e.g., IL-6/STAT-3) and four novel focus proteins (IL-6, galanin (GAL), HSPA5, and WNT4) that might be involved in glioma pathogenesis. The concentrations of these focus proteins were subsequently determined by enzyme-linked immunosorbent assay (ELISA) in an independent set of CSF and tumor cyst fluid (CF) samples. Specifically, glioblastoma (GBM) CF had significantly lower GAL, HSPA5, and WNT4 levels than CSF from different grades of glioma. In contrast, IL-6 level was significantly higher in GBM CF when compared with CSF and, among different CSF groups, was highest in GBM CSF. Therefore, these candidate protein biomarkers, identified from both the literatures and in silico analysis, may have potentials in clinical diagnosis, prognosis evaluation, treatment response monitoring, and novel therapeutic targets identification for patients with glioma.

Proteomic analyses of CSF aimed at biomarker development for pediatric brain tumors

Primary brain tumors cumulatively represent the most common solid tumors of childhood and are the leading cause of cancer related death in this age group. Traditionally, molecular findings and histological analyses from biopsies of resected tumor tissue have been used for diagnosis and classification of these diseases. However, there is a dearth of useful biomarkers that have been validated and clinically implemented for pediatric brain tumors. Notably, diseases of the central nervous system (CNS) can be assayed through analysis of cerebrospinal fluid (CSF) and as such, CSF represents an appropriate medium to obtain liquid biopsies that can be informative for diagnosis, disease classification and risk stratification. Proteomic profiling of pediatric CNS malignancies has identified putative protein markers of disease, yet few effective biomarkers have been clinically validated or implemented. Advances in protein quantification techniques have made it possible to conduct such investigations rapidly and accurately through proteome-wide analyses. This review summarizes the current literature on proteomics in pediatric neuro-oncology and discusses the implications for clinical applications of proteomics research. We also outline strategies for translating effective CSF proteomic studies into clinical applications to optimize the care of this patient population.

Identifying technical aliases in SELDI mass spectra of complex mixtures of proteins

Background

Biomarker discovery datasets created using mass spectrum protein profiling of complex mixtures of proteins contain many peaks that represent the same protein with different charge states. Correlated variables such as these can confound the statistical analyses of proteomic data. Previously we developed an algorithm that clustered mass spectrum peaks that were biologically or technically correlated. Here we demonstrate an algorithm that clusters correlated technical aliases only.

Results

In this paper, we propose a preprocessing algorithm that can be used for grouping technical aliases in mass spectrometry protein profiling data. The stringency of the variance allowed for clustering is customizable, thereby affecting the number of peaks that are clustered. Subsequent analysis of the clusters, instead of individual peaks, helps reduce difficulties associated with technically-correlated data, and can aid more efficient biomarker identification.

Conclusions

This software can be used to pre-process and thereby decrease the complexity of protein profiling proteomics data, thus simplifying the subsequent analysis of biomarkers by decreasing the number of tests. The software is also a practical tool for identifying which features to investigate further by purification, identification and confirmation.