Multifarious proteomic signatures and regional heterogeneity in glioblastomas

Exploring glioblastoma stem cell heterogeneity: Immune microenvironment modulation and therapeutic opportunities

Despite its growing use in cancer treatment, immunotherapy has been virtually ineffective in clinical trials for gliomas. The inherently cold tumor immune microenvironment (TIME) in gliomas, characterized by a high ratio of pro-tumor to anti-tumor immune cell infiltrates, acts as a seemingly insurmountable barrier to immunotherapy. Glioma stem cells (GSCs) within these tumors are key contributors to this cold TIME, often functioning indirectly through activation and recruitment of pro-tumor immune cell types. Furthermore, drivers of GSC plasticity and heterogeneity (e.g., reprogramming transcription factors, epigenetic modifications) are associated with induction of immunosuppressive cell states. Recent studies have identified GSC-intrinsic mechanisms, including functional mimicry of immune suppressive cell types, as key determinants of anti-tumor immune escape. In this review, we cover recent advancements in our understanding of GSC-intrinsic mechanisms that modulate GSC-TIME interactions and discuss cutting-edge techniques and bioinformatics platforms available to study immune modulation at high cellular resolution with exploration of both malignant (i.e., GSC) and non-malignant (i.e., immune) cell fractions. Finally, we provide insight into the therapeutic opportunities for targeting immunomodulatory GSC-intrinsic mechanisms to potentiate immunotherapy response in gliomas.

Tumor Heterogeneity in Glioblastomas: From Light Microscopy to Molecular Pathology

One of the main reasons for the aggressive behavior of glioblastoma (GBM) is its intrinsic intra-tumor heterogeneity, characterized by the presence of clonal and subclonal differentiated tumor cell populations, glioma stem cells, and components of the tumor microenvironment, which affect multiple hallmark cellular functions in cancer. "Tumor Heterogeneity" usually encompasses both inter-tumor heterogeneity (population-level differences); and intra-tumor heterogeneity (differences within individual tumors). Tumor heterogeneity may be assessed in a single time point (spatial heterogeneity) or along the clinical evolution of GBM (longitudinal heterogeneity). Molecular methods may detect clonal and subclonal alterations to describe tumor evolution, even when samples from multiple areas are collected in the same time point (spatial-temporal heterogeneity). In GBM, although the inter-tumor mutational landscape is relatively homogeneous, intra-tumor heterogeneity is a striking feature of this tumor. In this review, we will address briefly the inter-tumor heterogeneity of the CNS tumors that yielded the current glioma classification. Next, we will take a deeper dive in the intra-tumor heterogeneity of GBMs, which directly affects prognosis and response to treatment. Our approach aims to follow technological developments, allowing for characterization of intra-tumor heterogeneity, beginning with differences on histomorphology of GBM and ending with molecular alterations observed at single-cell level.

Proteins inform survival-based differences in patients with glioblastoma

BACKGROUND

Improving the care of patients with glioblastoma (GB) requires accurate and reliable predictors of patient prognosis. Unfortunately, while protein markers are an effective readout of cellular function, proteomics has been underutilized in GB prognostic marker discovery.

METHODS

For this study, GB patients were prospectively recruited and proteomics discovery using liquid chromatography-mass spectrometry analysis (LC-MS/MS) was performed for 27 patients including 13 short-term survivors (STS) (≤10 months) and 14 long-term survivors (LTS) (≥18 months).

RESULTS

Proteomics discovery identified 11 941 peptides in 2495 unique proteins, with 469 proteins exhibiting significant dysregulation when comparing STS to LTS. We verified the differential abundance of 67 out of these 469 proteins in a small previously published independent dataset. Proteins involved in axon guidance were upregulated in STS compared to LTS, while those involved in p53 signaling were upregulated in LTS. We also assessed the correlation between LS MS/MS data with RNAseq data from the same discovery patients and found a low correlation between protein abundance and mRNA expression. Finally, using LC-MS/MS on a set of 18 samples from 6 patients, we quantified the intratumoral heterogeneity of more than 2256 proteins in the multisample dataset.

CONCLUSIONS

These proteomic datasets and noted protein variations present a beneficial resource for better predicting patient outcome and investigating potential therapeutic targets.

Identification of Plasma Membrane Glycoproteins Specific to Human Glioblastoma Multiforme Cells Using Lectin Arrays and LC-MS/MS

Glioblastoma, also known as glioblastoma multiforme (GBM), is the most malignant type of brain cancer and has poor prognosis with a median survival of less than one year. While the structural changes of tumor cell surface carbohydrates are known to be associated with invasive behavior of tumor cells, the cell surface glycoproteins to differentiate the low- and high-grade glioma cells can be potential diagnostic markers and therapeutic targets for GBMs. In the present study, lectin arrays consisting of eight lectins were employed to explore cell surface carbohydrate expression patterns on low-grade oligodendroglioma cells (Hs683) and GBM cells (T98G). Griffonia simplicifolia I (GS I) was found to selectively bind to T98G cells and not to Hs683 cells. For identification of the glioblastoma-specific cell surface markers, the glycoproteins from each cell type were captured by a GS I lectin column and analyzed by LC-MS/MS. The identified proteins from the two cell types were quantified using label-free quantitative analysis based on spectral counting. Of cell surface glycoproteins showing significant increases in T98G cells, five proteins were selected for verification of both protein and glycosylation level changes using Western blot and GS I lectin-based immunosorbent assay.

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.

Proteomics analysis of human brain glial cell proteome by 2D gel

INTRODUCTION

Proteomics is increasingly employed in both neurological and oncological research, and applied widely in every area of neuroscience research including brain cancer. Astrocytomas are the most common glioma and can occur in most parts of the brain and occasionally in the spinal cord. Patients with high-grade astrocytomas have a life expectancy of <1 year even after surgery, chemotherapy, and radiotherapy.

MATERIALS AND METHODS

We extracted proteins from tumors and normal brain tissues and then evaluated the protein purity by Bradford test and spectrophotometry method. In this study, we separated proteins by the two-dimensional (2DG) gel electrophoresis method, and the spots were analyzed and compared using statistical data.

RESULTS

On each analytical 2D gel, an average of 800 spots was observed. In this study, 164 spots exhibited up-regulation of expression level, whereas the remaining 179 spots decreased in astrocytoma tumor relative to normal tissue. RESULTS demonstrate that functional clustering and principal component analysis (PCA) has considerable merits in aiding the interpretation of proteomic data. Proteomics is a powerful tool in identifying multiple proteins that are altered following a neuropharmacological intervention in a disease of the central nervous system (CNS).

CONCLUSION

2-D gel and cluster analysis have important roles in the diagnostic management of astrocytoma patients, providing insight into tumor biology. The application of proteomics to CNS research has invariably been very successful in yielding large amounts of data.

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.

Alterations in cerebrospinal fluid proteins in a presymptomatic primary glioma model

Background

Understanding the early relationship between brain tumor cells and their environment could lead to more sensitive biomarkers and new therapeutic strategies. We have been using a rodent model of neurocarcinogenesis in which all animals develop brain tumors by six months of age to establish two early landmarks in glioma development: the appearance of a nestin⁺ cell at thirty days of age and the appearance of cellular hyperplasia between 60 and 120 days of age. We now report an assessment of the CSF proteome to determine the changes in protein composition that occur during this period.

Materials and Methods

Nestin⁺ cell clusters and microtumors were assessed in 63 ethylnitrosourea-exposed rats on 30, 60, and 90 days of age. CSF was obtained from the cisterna magna from 101 exposed and control rats at 30, 60, and 90 days and then analyzed using mass spectrometry. Differentially expressed peaks were isolated and identified.

Results

Nestin⁺ cells were noted in all ethylnitrosourea-exposed rats assessed pathologically. Small microtumors were noted in 0%, 18%, and 67% of 30-, 60-, and 90-day old rats, respectively (p<0.05, Chi square). False Discovery Rate analysis of peak intensities showed that the number of true discoveries with p<0.05 increased markedly with increasing age. Isolation and identification of highly differentially detected proteins at 90 days of age revealed increases in albumin and a fragment of α1 macroglobulin and alterations in glutathionylated transthyretin.

Conclusions

The presence of increased albumin, fragments of cerebrospinal fluid proteins, and glutathione breakdown in temporal association with the development of cellular hyperplasia, suggests that, similar to many other systemic cancers, inflammation and oxidative stress is playing an important early role in the host’s response to brain tumor development and may be involved in affecting the early growth of brain tumor.

Quantitative proteomic Isotope-Coded Protein Label (ICPL) analysis reveals alteration of several functional processes in the glioblastoma

Glioblastoma (GB), the most frequent primary tumor of the central nervous system, remains one of the most lethal human cancers despite intensive researches. Current paradigm in the study of GB has been focused on inter-patient variability and on trying to isolate new classification elements or prognostic factors. Here, using ICPL, a technique for protein relative quantification by mass spectrometry, we investigated protein expression between the four regions of GB on clinically relevant biopsies from 5 patients. We identified 584 non-redundant proteins and 31 proteins were found to be up-regulated in the tumor region compared to the peri-tumoral brain tissue, among which, 24 proteins belong to an interaction network linked to 4 biological processes. The core of this network is mainly constituted of interactions between beta-actin (ACTB) with heat shock proteins (HSP90AA1, HSPA8) and 14-3-3 proteins (YWHAZ, YWHAG, YWHAB). A cluster of three isoforms of the sodium pump α-subunit (ATP1A1, ATP1A2, ATP1A3) was also identified outside this network. The differential expression observed for ACTB and 14-3-3γ was further validated by western blot and/or immunohistochemistry. Our study confirms the identity of previously proposed molecular targets, highlights several functional processes altered in GB such as energy metabolism and synaptic transmission and could thus provide added value to new therapeutic trails.

Recent advances in the molecular understanding of glioblastoma

Glioblastoma is the most common and most aggressive primary brain tumor. Despite maximum treatment, patients only have a median survival time of 15 months, because of the tumor’s resistance to current therapeutic approaches. Thus far, methylation of the O⁶-methylguanine-DNA methyltransferase (MGMT) promoter has been the only confirmed molecular predictive factor in glioblastoma. Novel “genome-wide” techniques have identified additional important molecular alterations as mutations in isocitrate dehydrogenase 1 (IDH1) and its prognostic importance. This review summarizes findings and techniques of genetic, epigenetic, transcriptional, and proteomic studies of glioblastoma. It provides the clinician with an up-to-date overview of current identified molecular alterations that should ultimately lead to new therapeutic targets and more individualized treatment approaches in glioblastoma.

Proteomics of gliomas: initial biomarker discovery and evolution of technology

Gliomas are a group of aggressive brain tumors that diffusely infiltrate adjacent brain tissues, rendering them largely incurable, even with multiple treatment modalities and agents. Mostly asymptomatic at early stages, they present in several subtypes with astrocytic or oligodendrocytic features and invariably progress to malignant forms. Gliomas are difficult to classify precisely because of interobserver variability during histopathologic grading. Identifying biological signatures of each glioma subtype through protein biomarker profiling of tumor or tumor-proximal fluids is therefore of high priority. Such profiling not only may provide clues regarding tumor classification but may identify clinical biomarkers and pathologic targets for the development of personalized treatments. In the past decade, differential proteomic profiling techniques have utilized tumor, cerebrospinal fluid, and plasma from glioma patients to identify the first candidate diagnostic, prognostic, predictive, and therapeutic response markers, highlighting the potential for glioma biomarker discovery. The number of markers identified, however, has been limited, their reproducibility between studies is unclear, and none have been validated for clinical use. Recent technological advancements in methodologies for high-throughput profiling, which provide easy access, rapid screening, low sample consumption, and accurate protein identification, are anticipated to accelerate brain tumor biomarker discovery. Reliable tools for biomarker verification forecast translation of the biomarkers into clinical diagnostics in the foreseeable future. Herein we update the reader on the recent trends and directions in glioma proteomics, including key findings and established and emerging technologies for analysis, together with challenges we are still facing in identifying and verifying potential glioma biomarkers.

Bevacizumab has differential and dose-dependent effects on glioma blood vessels and tumor cells

PURPOSE

Bevacizumab targets VEGF-A and has proved beneficial in glioma patients, improving clinical symptoms by the reduction of tumor edema. However, it remains controversial whether or not bevacizumab exerts antitumor effects in addition to (and potentially independent of) its effects on tumor vessels, and it is unknown what doses are needed to achieve this.

EXPERIMENTAL DESIGN

We established a novel orthotopic glioma mouse model that allowed us to simultaneously study the kinetics of the morphologic and functional vascular changes, tumor growth, and the viability of individual tumor cells during the course of anti-VEGF therapy in the same microscopic tumor region in real-time. Three doses of bevacizumab were compared, a subclinical dose and two clinical doses (medium and high).

RESULTS

Low (subclinical) doses of bevacizumab led to a significant reduction of the total vascular volume without affecting tumor cell viability or the overall tumor growth rates. Medium and high doses triggered a similar degree of vascular regression but significantly decreased tumor growth and prolonged survival. Remaining vessels revealed morphologic features of vascular normalization, reduced permeability, and an increase in blood flow velocity; the latter was dose dependent. We observed an uncoupling of the antitumoral and the antivascular effects of bevacizumab with the high dose only, which showed the potential to cause microregional glioma cell regression. In some tumor regions, pronounced glioma cell regression occurred even without vascular regression. In vitro, there was no effect of bevacizumab on glioma cell proliferation.

CONCLUSIONS

Regression of glioma cells can occur independently from vascular regression, suggesting that high doses of bevacizumab have indirect anticancer cell properties in vivo.

Differential analysis of glioblastoma multiforme proteome by a 2D-DIGE approach

Background

Genomics, transcriptomics and proteomics of glioblastoma multiforme (GBM) have recently emerged as possible tools to discover therapeutic targets and biomarkers for new therapies including immunotherapy. It is well known that macroscopically complete surgical excision, radiotherapy and chemotherapy have therapeutic limitations to improve survival in these patients. In this study, we used a differential proteomic-based technique (2D-Difference Gel Electrophoresis) coupled with matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry to identify proteins that may serve as brain tumor antigens in new therapeutic assays. Five samples of patients presenting a GBM and five samples of microscopically normal brain tissues derived from brain epileptic surgery specimen were labeled and run in 2D-PAGE (Two-Dimensional Polyacrylamide Gel Electrophoresis) with an internal pool sample on each gel. Five gels were matched and compared with DIA (Difference In-gel Analysis) software. Differential spots were picked, in-gel digested and peptide mass fingerprints were obtained.

Results

From 51 protein-spots significantly up-regulated in GBM samples, mass spectrometry (MS) identified twenty-two proteins. The differential expression of a selected protein set was first validated by western-blotting, then tested on large cohorts of GBM specimens and non-tumor tissues, using immunohistochemistry and real-time RT-PCR.

Conclusions

Our results confirmed the importance of previously described proteins in glioma pathology and their potential usefulness as biological markers but also revealed some new interesting targets for future therapies.

Rapid T cell-based identification of human tumor tissue antigens by automated two-dimensional protein fractionation

Identifying the antigens that have the potential to trigger endogenous antitumor responses in an individual cancer patient is likely to enhance the efficacy of cancer immunotherapy, but current methodologies do not efficiently identify such antigens. This study describes what we believe to be a new method of comprehensively identifying candidate tissue antigens that spontaneously cause T cell responses in disease situations. We used the newly developed automated, two-dimensional chromatography system PF2D to fractionate the proteome of human tumor tissues and tested protein fractions for recognition by preexisting tumor-specific CD4+ Th cells and CTLs. Applying this method using mice transgenic for a TCR that recognizes an OVA peptide presented by MHC class I, we demonstrated efficient separation, processing, and cross-presentation to CD8+ T cells by DCs of OVA expressed by the OVA-transfected mouse lymphoma RMA-OVA. Applying this method to human tumor tissues, we identified MUC1 and EGFR as tumor-associated antigens selectively recognized by T cells in patients with head and neck cancer. Finally, in an exemplary patient with a malignant brain tumor, we detected CD4+ and CD8+ T cell responses against two novel antigens, transthyretin and calgranulin B/S100A9, which were expressed in tumor and endothelial cells. The immunogenicity of these antigens was confirmed in 4 of 10 other brain tumor patients. This fast and inexpensive method therefore appears suitable for identifying candidate T cell antigens in various disease situations, such as autoimmune and malignant diseases, without being restricted to expression by a certain cell type or HLA allele.

Glioma proteomics: status and perspectives

High grade gliomas are the most common brain tumors in adults and their malignant nature makes them the fourth biggest cause of cancer death. Major efforts in neuro-oncology research are needed to reach similar progress in treatment efficacy as that achieved for other cancers in recent years. In addition to the urgent need to identify novel effective drug targets against malignant gliomas, the search for glioma biomarkers and grade specific protein signatures will provide a much needed contribution to diagnosis, prognosis, treatment decision and assessment of treatment response. Over the past years glioma proteomics has been attempted at different levels, including proteome analysis of patient biopsies and bodily fluids, of glioma cell lines and animal models. Here we provide an extensive review of the outcome of these studies in terms of protein identifications (protein numbers and regulated proteins), with an emphasis on the methods used and the limitations of the studies with regard to biomarker discovery. This is followed by a perspective on novel technologies and on the potential future contribution of proteomics in a broad sense to understanding glioma biology.