Protein patterns and proteins that identify subtypes of glioblastoma multiforme

Advanced image analysis-based evaluation of protein antibody microarray chemiluminescence signal improves glioma type identification by blood serum proteins concentrations

BACKGROUND AND OBJECTIVE

Gliomas are the most common brain tumors usually classified as benign low-grade or aggressive high-grade glioma. One of the promising possibilities of glioma diagnostics and tumor type identification could be based on concentration measurements of glioma secreted proteins in blood. However, several published approaches of quantitative proteomic analysis emphasize limits of one single protein to be used as biomarker of these types of tumors. Simultaneous multi-protein concentrations analysis giving antibody array-based methods suffer from poor measurement accuracy due to technical limitations of imaging systems.

METHODS

We applied Principal Component Analysis (PCA) for series of repeated antibody array chemiluminescence images to extract the component representing relative values of protein concentrations, free from zero-mean noise and uneven background illumination - main factors corrupting evaluation result.

RESULTS

The proposed method increased accuracy of protein concentration estimates at least 2-fold. Decision tree classifier applied to the relative concentration values of three proteins TIMP-1, PAI-1 and NCAM-1 estimated by proposed image analysis method effectively distinguished between low-grade glioma, high-grade glioma and healthy control subjects showing validation accuracy of 74.9% with the highest positive predictive value of 81.2% for high grade glioma and 57.1% for low grade glioma cases.

CONCLUSIONS

PCA-based image processing could be applied in protein antibody microarray and other multitarget detection/evaluation investigations to increase estimation accuracy.

Enhanced proteasomal activity is essential for long term survival and recurrence of innately radiation resistant residual glioblastoma cells

Therapy resistance and recurrence in Glioblastoma is due to the presence of residual radiation resistant cells. However, because of their inaccessibility from patient biopsies, the molecular mechanisms driving their survival remain unexplored. Residual Radiation Resistant (RR) and Relapse (R) cells were captured using cellular radiation resistant model generated from patient derived primary cultures and cell lines. iTRAQ based quantitative proteomics was performed to identify pathways unique to RR cells followed by in vitro and in vivo experiments showing their role in radio-resistance. 2720 proteins were identified across Parent (P), RR and R population with 824 and 874 differential proteins in RR and R cells. Unsupervised clustering showed proteasome pathway as the most significantly deregulated pathway in RR cells. Concordantly, the RR cells displayed enhanced expression and activity of proteasome subunits, which triggered NFkB signalling. Pharmacological inhibition of proteasome activity led to impeded NFkB transcriptional activity, radio-sensitization of RR cells in vitro, and significantly reduced capacity to form orthotopic tumours in vivo. We demonstrate that combination of proteasome inhibitor with radio-therapy abolish the inaccessible residual resistant cells thereby preventing GBM recurrence. Furthermore, we identified first proteomic signature of RR cells that can be exploited for GBM therapeutics.

Epidermal Growth Factor Receptor Serum Levels and Prognostic Value in Malignant Gliomas

Aims and background

The epidermal growth factor receptor (EGFR) is a member of a family of cell membrane receptors that use tyrosine kinase activity as the signal transduction mechanism. It is commonly expressed or overexpressed by many solid tumors and correlates with disease progression and a poor clinical prognosis. Increased EGFR expression might therefore be a strong prognostic feature in multiple tumor types, and inhibition of its cellular actions may have substantial therapeutic benefit. The aim of this study was to estimate the EGFR serum concentration for potential use as a biological marker of brain cancer to predict prognosis and follow-up after treatment.

Methods and study design

Serum samples obtained from 50 healthy individuals and 65 brain cancer patients (35 glioblastoma multiforme and 30 anaplastic astrocytomas) were collected before and after treatment and assayed for EGFR extracellular domain serum concentrations by a sandwich ELISA.

Results

EGFR was elevated in 47 of 65 brain cancer patients, with mean serum values of 84 ± 18 ng/ml, compared with that of healthy controls (43.6 ± 11 ng/ml, P = 0.001). There was a significant difference in the mean serum levels of EGFR between glioblastoma multiforme patients (96.2 ± 12 ng/ml) and anaplastic astrocytoma patients (71.6 ± 18 ng/ml, P = 0.04). Sixty brain cancer patients underwent surgery; EGFR serum levels did not show significant differences from those observed before surgery. For all patients, median overall survival was 13 months (anaplastic astrocytoma, 18 months; glioblastoma multiforme, 12.5 months). In 47 patients with high EGFR serum levels, overall survival was reduced (P = 0. 01), with a median survival time corresponding to 11.5 months (anaplastic astrocytoma, 14.5 months; glioblastoma multiforme, 10.5 months).

Conclusions

Although a prospective study with large sample size is warranted, serum EGFR extracellular domain may be potentially useful as a biological marker of gliomas for prediction of prognosis and follow-up after treatment.

The Expression Profile of Complement Components in Podocytes

Podocytes are critical for maintaining the glomerular filtration barrier and are injured in many renal diseases, especially proteinuric kidney diseases. Recently, reports suggested that podocytes are among the renal cells that synthesize complement components that mediate glomerular diseases. Nevertheless, the profile and extent of complement component expression in podocytes remain unclear. This study examined the expression profile of complement in podocytes under physiological conditions and in abnormal podocytes induced by multiple stimuli. In total, 23/32 complement component components were detected in podocyte by conventional RT-PCR. Both primary cultured podocytes and immortalized podocytes expressed the complement factors C1q, C1r, C2, C3, C7, MASP, CFI, DAF, CD59, C4bp, CD46, Protein S, CR2, C1qR, C3aR, C5aR, and Crry (17/32), whereas C4, CFB, CFD, C5, C6, C8, C9, MBL1, and MBL2 (9/32) complement factors were not expressed. C3, Crry, and C1q-binding protein were detected by tandem mass spectrometry. Podocyte complement gene expression was affected by several factors (puromycin aminonucleoside (PAN), angiotensin II (Ang II), interleukin-6 (IL-6), and transforming growth factor-β (TGF-β)). Representative complement components were detected using fluorescence confocal microscopy. In conclusion, primary podocytes express various complement components at the mRNA and protein levels. The complement gene expressions were affected by several podocyte injury factors.

Molecular and Genomic Alterations in Glioblastoma Multiforme

In recent years, important advances have been achieved in the understanding of the molecular biology of glioblastoma multiforme (GBM); thus, complex genetic alterations and genomic profiles, which recurrently involve multiple signaling pathways, have been defined, leading to the first molecular/genetic classification of the disease. In this regard, different genetic alterations and genetic pathways appear to distinguish primary (eg, EGFR amplification) versus secondary (eg, IDH1/2 or TP53 mutation) GBM. Such genetic alterations target distinct combinations of the growth factor receptor-ras signaling pathways, as well as the phosphatidylinositol 3-kinase/phosphatase and tensin homolog/AKT, retinoblastoma/cyclin-dependent kinase (CDK) N2A-p16(INK4A), and TP53/mouse double minute (MDM) 2/MDM4/CDKN2A-p14(ARF) pathways, in cells that present features associated with key stages of normal neurogenesis and (normal) central nervous system cell types. This translates into well-defined genomic profiles that have been recently classified by The Cancer Genome Atlas Consortium into four subtypes: classic, mesenchymal, proneural, and neural GBM. Herein, we review the most relevant genetic alterations of primary versus secondary GBM, the specific signaling pathways involved, and the overall genomic profile of this genetically heterogeneous group of malignant tumors.

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.

Tissue proteomics using capillary isoelectric focusing-based multidimensional separations

The capabilities of capillary isoelectric focusing-based multidimensional separations for performing proteome analysis from minute samples create new opportunities in the pursuit of biomarker discovery using enriched and selected cell populations procured from tissue specimens. In this article, recent advances in online integration of capillary isoelectric focusing with nano-reversed phase liquid chromatography for achieving high-resolution peptide and protein separations prior to mass spectrometry analysis are reviewed, along with its potential application to tissue proteomics. These proteome technological advances combined with recently developed tissue microdissection techniques, provide powerful tools for those seeking to gain a greater understanding at the global level of the cellular machinery associated with human diseases such as cancer.

Mitochondrial dysfunction in gliomas

Mitochondrial (mt) dysfunction in gliomas has been linked to abnormalities of mt energy metabolism, marked by a metabolic shift from oxidative phosphorylation to glycolysis ("Warburg effect"), disturbances in mt membrane potential regulation and apoptotic signaling, as well as to somatic mutations involving the Krebs cycle enzyme isocitrate dehydrogenase. Evolving biological concepts with potential therapeutic implications include interaction between microtubule proteins and mitochondria (mt) in the control of closure of voltage-dependent anion channels and in the regulation of mt dynamics and the mt-endoplasmic reticulum network. The cytoskeletal protein βIII-tubulin, which is overexpressed in malignant gliomas, has emerged as a prosurvival factor associated in part with mt and also as a marker of chemoresistance. Mt-targeted therapeutic strategies that are discussed include the following: (1) metabolic modulation with emphasis on dichloroacetate, a pyruvate dehydrogenase kinase inhibitor; (2) tumor cell death via apoptosis induced by tricyclic antidepressants, microtubule-modulating drugs, and small molecules or compounds capable of inflicting reactive oxygen species-dependent tumor cell death; and (3) pretreatment mt priming and mt-targeted prodrug cancer therapy.

Proteomic analysis of glioblastomas: what is the best brain control sample?

Glioblastoma (GB) is the most frequent and aggressive tumor of the central nervous system. There is currently growing interest in proteomic studies of GB, particularly with the aim of identifying new prognostic or therapeutic response markers. However, comparisons between different proteomic analyses of GB have revealed few common differentiated proteins. The types of control samples used to identify such proteins may in part explain the different results obtained. We therefore tried to determine which control samples would be most suitable for GB proteomic studies. We used an isotope-coded protein labeling (ICPL) method followed by mass spectrometry to reveal and compare the protein patterns of two commonly used types of control sample: GB peritumoral brain zone samples (PBZ) from six patients and epilepsy surgery brain samples (EB) pooled from three patients. The data obtained were processed using AMEN software for network analysis. We identified 197 non-redundant proteins and 35 of them were differentially expressed. Among these 35 differentially expressed proteins, six were over-expressed in PBZ and 29 in EB, showing different proteomic patterns between the two samples. Surprisingly, EB appeared to display a tumoral-like expression pattern in comparison to PBZ. In our opinion, PBZ may be more appropriate control sample for GB proteomic analysis.

BIOLOGICAL SIGNIFICANCE

This manuscript describes an original study in which we used an isotope-coded protein labeling method followed by mass spectrometry to identify and compare the protein patterns in two types of sample commonly used as control for glioblastoma (GB) proteomic analysis: peritumoral brain zone and brain samples obtained during surgery for epilepsy. The choice of control samples is critical for identifying new prognostic and/or diagnostic markers in GB.

Identifying dysfunctional miRNA-mRNA regulatory modules by inverse activation, cofunction, and high interconnection of target genes: a case study of glioblastoma

BACKGROUND

Accumulating evidence demonstrates that complex diseases may arise from cooperative effects of multiple dysfunctional miRNAs. Thus, identifying abnormal functions cooperatively regulated by multiple miRNAs is useful for understanding the pathogenesis of complex diseases.

METHODS

In this study, we proposed a multistep method to identify dysfunctional miRNA-mRNA regulatory modules (dMiMRMs) in a specific disease, in which a group of miRNAs cooperatively regulate a group of target genes involved in a specific function. We identified dysfunctional miRNAs, which were differentially expressed and inversely regulated most of their target genes, by integrating paired miRNA and mRNA expression profiles and miRNA target information. Then, we identified cooperative functional units, in each of which a pair of miRNAs cooperatively repressed function-enriched and highly interconnected target genes. Finally, the cooperative functional units were assembled into dMiMRMs.

RESULTS

We applied our method to glioblastoma (GBM) and identified GBM-associated dMiMRMs at the population, subtype, and individual levels. We identified 5 common dMiMRMs using all GBM samples, 3 of which were associated with the prognosis in patients with GBM and were better predictors of prognosis than were miRNAs or mRNAs alone. By applying our approach to GBM subtypes, we found consistent dMiMRMs across GBM subtypes, and some subtype-specific dMiMRMs were observed. Furthermore, personalized dMiMRMs were identified, suggesting significant individual differences in different patients with GBM.

CONCLUSIONS

Our method provides the capability to identify miRNA-mediated dysfunctional mechanisms underlying complex diseases.

Secretome analysis of Glioblastoma cell line--HNGC-2

Glioblastoma multiforme (GBM) is the most common and aggressive type of primary malignant tumor of the central nervous system. We have carried out a deep analysis of the secretome of a rapidly proliferating and tumorigenic cell line HNGC-2, representing GBM, in an effort to identify proteins, which may be targeted in the plasma of GBM patients as markers for diagnosis and disease surveillance. Prefractionation of the proteins from the conditioned medium of HNGC-2 cells in SDS gels followed by LC-MS/MS analysis using an ESI-IT mass spectrometer (LTQ) led to a total of 996 protein identifications with ≥2 peptides each. Of them, 664 proteins were observed in the transcriptome of HNGC-2 cells. The dataset of 996 proteins was mapped to important functional groups, such as cellular assembly and organisation, DNA recombination and repair, and other classes. Actin cytoskeleton signalling, phosphatidyl inositol 3 kinase (PI3K/AKT) and integrin linked kinase (ILK) signalling pathways were seen as enriched pathways. Comparisons with the published secretome of cell lines from 12 different cancers, including GBM, revealed that 348 proteins shared a commonality with a secretome of at least one other cell line, 321 of which were found to contain signal sequences or transmembrane domains and 335 could be linked to a plasma membrane or extracellular localization. Through intergration of this data we arrived at a non-redundant list of 597 protein identifications with the potential for secretion either by classical secretory pathways or by non-secretory processes; 233 of them have been detected in cerebrospinal fluid or plasma as per the published literature, and 172 have been implicated in GBM or other cancers. The HNGC-2 secretome dataset could serve as a useful resource for designing a targeted investigation of GBM biomarkers in plasma.

Proteomic analysis of glioma chemoresistance

Malignant glioma is the most common and destructive form of primary brain tumor. Along with surgery and radiation, chemotherapy remains as the major treatment modality. The emergence of drug resistance, however, often leads to a therapeutic failure in the treatment of glioma, precluding long-term survival of the patients. A proteomic approach has recently been adapted for the mechanistic analysis of glioma drug resistance. The proteomic analysis of drug-resistant glioma led to the discovery of novel biomarkers that can be used for the prognosis of glioma as well as for monitoring the drug response or resistance of glioma. These proteomics-based biomarkers can also be a druggable target that one can exploit for successful glioma chemotherapy. In this review, recent reports on proteomic analysis of glioma from the perspective of chemoresistance are discussed with a focus on the proteome profiles of glioma cells that are resistant to the alkylating agent, 1, 3-bis (2-chloroethyl)-1-nitrosourea (BCNU), as a prime example. Among numerous proteins that were up- or down-regulated in drug-resistant glioma cells, lipocalin 2 (LCN2) and integrin β3 (ITGB3) were identified as key proteins that determine the survival and death of glioma cells. LCN2, ITGB3, and other proteins identified by proteomic analysis could be utilized to overcome glioma chemoresistance.

Missense mutations in the human SDHB gene increase protein degradation without altering intrinsic enzymatic function

Mutations of succinate dehydrogenase subunit B (SDHB) play a crucial role in the pathogenesis of the most aggressive and metastatic pheochromocytomas (PHEOs) and paragangliomas (PGLs). Although a variety of missense mutations in the coding sequence of the SDHB gene have been found in PHEOs and PGLs, it has been unclear whether these mutations impair mRNA expression, protein stability, subcellular localization, or intrinsic protein function. RT-PCR and Western blot analysis of SDHB mRNA and protein expression from SDHB-related PHEOs and PGLs demonstrated intact mRNA expression but significantly reduced protein expression compared to non-SDHB PHEOs and PGLs. A pulse-chase assay of common SDHB missense mutations in transfected HeLa cell lines demonstrated that the loss of SDHB function was due to a reduction in mutant protein half-life, whereas colocalization of SDHB with mitochondria and immunoprecipitation with SDHA demonstrated intact subcellular localization and complex formation. The half-life of the SDHB protein increased after treatment with histone deacetylase inhibitors (HDACis), implicating the protein quality control machinery in the degradation of mutant SDHB protein. These findings provide the first direct mechanism of functional loss resulting from SDHB mutations and suggest that reducing protein degradation with HDACis may serve as a novel therapeutic paradigm for preventing the development of SDHB-related tumors.

Targeted tissue proteomic analysis of human astrocytomas

Complicating proteomic analysis of whole tissues is the obvious problem of cell heterogeneity in tissues, which often results in misleading or confusing molecular findings. Thus, the coupling of tissue microdissection for tumor cell enrichment with capillary isotachophoresis-based selective analyte concentration not only serves as a synergistic strategy to characterize low abundance proteins, but it can also be employed to conduct comparative proteomic studies of human astrocytomas. A set of fresh frozen brain biopsies were selectively microdissected to provide an enriched, high quality, and reproducible sample of tumor cells. Despite sharing many common proteins, there are significant differences in the protein expression level among different grades of astrocytomas. A large number of proteins, such as plasma membrane proteins EGFR and Erbb2, are up-regulated in glioblastoma. Besides facilitating the prioritization of follow-on biomarker selection and validation, comparative proteomics involving measurements in changes of pathways are expected to reveal the molecular relationships among different pathological grades of gliomas and potential molecular mechanisms that drive gliomagenesis.

β-Catenin signaling initiates the activation of astrocytes and its dysregulation contributes to the pathogenesis of astrocytomas

Astrocytes are the most abundant cell of the CNS and demonstrate contact inhibition in which a nonproliferative, nonmotile cellular state is achieved once stable intercellular contacts are formed between mature cells. Cellular injury disrupts these intercellular contacts, causing a loss of contact inhibition and the rapid initiation of healing. Dysregulation of the molecular pathways involved in this process is thought to lead to an aggressive cellular state associated with neoplasia. We investigated whether a comparable correlation exists between the response of astrocytes to injury and the malignant phenotype of astrocytomas. We discovered that the loss of contact inhibition plays a critical role in the initiation and regulation of reactive astrocytes in the healing of wounds. In particular, injury of the astrocytes interrupts and destabilizes the cadherin-catenin complexes at the cell membrane leading to nuclear translocation of β-catenin and characteristic changes associated with the activation of astrocytes. Similar signaling pathways are found to be active--but dysregulated--in astrocytomas. Inhibition of β-catenin signaling diminished both the response of astrocytes to injury and induction of the malignant phenotype of astrocytomas. The findings shed light on a unique mechanism associated with the pathogenesis of astrocytomas and provide a model for the loss of contact inhibition that may broadly apply to understanding the mechanisms of tissue repair and tumorigenesis in the brain.

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.

Proteomic identification of glutamine synthetase as a differential marker for oligodendrogliomas and astrocytomas

OBJECT

Astrocytomas and oligodendrogliomas are primary CNS tumors that remain a challenge to differentiate histologically because of their morphological variability and because there is a lack of reliable differential diagnostic markers. To identify proteins that are differentially expressed between astrocytomas and oligodendrogliomas, the authors analyzed the proteomic expression patterns and identified uniquely expressed proteins in these neoplasms.

METHODS

Proteomes of astrocytomas and oligodendrogliomas were analyzed using 2D gel electrophoresis and subsequent computerized gel analysis to detect differentially expressed proteins. The proteins were identified using high-performance liquid chromatography accompanied by tandem mass spectrometry. To determine the role of the differentially expressed proteins in astrocytes, undifferentiated glial cell cultures were treated with dibutyryl-cyclic adenosine monophosphate (cAMP).

RESULTS

Two-dimensional gel electrophoresis revealed that glutamine synthetase was differentially expressed in astrocytomas and oligodendrogliomas. Western blot and immunohistochemical analyses confirmed the increased expression of glutamine synthetase in astrocytomas compared with oligodendrogliomas. Whereas glutamine synthetase expression was demonstrated across all grades of astrocytomas (Grade II-IV [15 tumors]) and oligoastrocytomas (4 tumors), it was expressed in only 1 oligodendroglioma (6% [16 tumors]). Treatment of undifferentiated glial cell cultures with dibutyryl-cAMP resulted in astrocyte differentiation that was associated with increased levels of glial fibrillary acidic protein and glutamine synthetase.

CONCLUSIONS

These data indicate that glutamine synthetase expression can be used to distinguish astrocytic from oligodendroglial tumors and may play a role in the pathogenesis of astrocytomas.

Missense mutations in the NF2 gene result in the quantitative loss of merlin protein and minimally affect protein intrinsic function

Neurofibromatosis type 2 (NF2) is a multiple neoplasia syndrome and is caused by a mutation of the NF2 tumor suppressor gene that encodes for the tumor suppressor protein merlin. Biallelic NF2 gene inactivation results in the development of central nervous system tumors, including schwannomas, meningiomas, ependymomas, and astrocytomas. Although a wide variety of missense germline mutations in the coding sequences of the NF2 gene can cause loss of merlin function, the mechanism of this functional loss is unknown. To gain insight into the mechanisms underlying loss of merlin function in NF2, we investigated mutated merlin homeostasis and function in NF2-associated tumors and cell lines. Quantitative protein and RT-PCR analysis revealed that whereas merlin protein expression was significantly reduced in NF2-associated tumors, mRNA expression levels were unchanged. Transfection of genetic constructs of common NF2 missense mutations into NF2 gene-deficient meningioma cell lines revealed that merlin loss of function is due to a reduction in mutant protein half-life and increased protein degradation. Transfection analysis also demonstrated that recovery of tumor suppressor protein function is possible, indicating that these mutants maintain intrinsic functional capacity. Further, increased expression of mutant protein is possible after treatment with specific proteostasis regulators, implicating protein quality control systems in the degradative fate of mutant tumor suppressor proteins. These findings provide direct insight into protein function and tumorigenesis in NF2 and indicate a unique treatment paradigm for this disorder.

Identification of diagnostic serum protein profiles of glioblastoma patients

Diagnosis of a glioblastoma (GBM) is triggered by the onset of symptoms and is based on cerebral imaging and histological examination. Serum-based biomarkers may support detection of GBM. Here, we explored serum protein concentrations of GBM patients and used data mining to explore profiles of biomarkers and determine whether these are associated with the clinical status of the patients. Gene and protein expression data for astrocytoma and GBM were used to identify secreted proteins differently expressed in tumors and in normal brain tissues. Tumor expression and serum concentrations of 14 candidate proteins were analyzed for 23 GBM patients and nine healthy subjects. Data-mining methods involving all 14 proteins were used as an initial evaluation step to find clinically informative profiles. Data mining identified a serum protein profile formed by BMP2, HSP70, and CXCL10 that enabled correct assignment to the GBM group with specificity and sensitivity of 89 and 96%, respectively (p < 0.0001, Fischer’s exact test). Survival for more than 15 months after tumor resection was associated with a profile formed by TSP1, HSP70, and IGFBP3, enabling correct assignment in all cases (p < 0.0001, Fischer’s exact test). No correlation was found with tumor size or age of the patient. This study shows that robust serum profiles for GBM may be identified by data mining on the basis of a relatively small study cohort. Profiles of more than one biomarker enable more specific assignment to the GBM and survival group than those based on single proteins, confirming earlier attempts to correlate single markers with cancer. These conceptual findings will be a basis for validation in a larger sample size.

An extensive invasive intracranial human glioblastoma xenograft model: role of high level matrix metalloproteinase 9

The lack of an intracranial human glioma model that recapitulates the extensive invasive and hypervascular features of glioblastoma (GBM) is a major hurdle for testing novel therapeutic approaches against GBM and studying the mechanism of GBM invasive growth. We characterized a high matrix metalloproteinase-9 (MMP-9) expressing U1242 MG intracranial xenograft mouse model that exhibited extensive individual cells and cell clusters in a perivascular and subpial cellular infiltrative pattern, geographic necrosis and infiltrating tumor-induced vascular proliferation closely resembling the human GBM phenotype. MMP-9 silencing cells with short hairpin RNA dramatically blocked the cellular infiltrative pattern, hypervascularity, and cell proliferation in vivo, and decreased cell invasion, colony formation, and cell motility in vitro, indicating that a high level of MMP-9 plays an essential role in extensive infiltration and hypervascularity in the xenograft model. Moreover, epidermal growth factor (EGF) failed to stimulate MMP-9 expression, cell invasion, and colony formation in MMP-9-silenced clones. An EGF receptor (EGFR) kinase inhibitor, a RasN17 dominant-negative construct, MEK and PI3K inhibitors significantly blocked EGF/EGFR-stimulated MMP-9, cell invasion, and colony formation in U1242 MG cells, suggesting that MMP-9 is involved in EGFR/Ras/MEK and PI3K/AKT signaling pathway-mediated cell invasion and anchorage-independent growth in U1242 MG cells. Our data indicate that the U1242 MG xenograft model is valuable for studying GBM extensive invasion and angiogenesis as well as testing anti-invasive and anti-angiogenic therapeutic approaches.

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.

Comparison of multidimensional shotgun technologies targeting tissue proteomics

A compelling need exists for the development of technologies that facilitate and accelerate the discovery of novel protein biomarkers with therapeutic and diagnostic potential. Comparisons among shotgun proteome technologies, including capillary isotachophoresis (CITP)-based multidimensional separations and multidimensional LC system, are therefore performed in this study regarding their abilities to address the challenges of protein complexity and relative abundance inherent in glioblastoma multiforme-derived cancer stem cells. Comparisons are conducted using a single processed protein digest with equal sample loading, identical second-dimension separation (RPLC) and MS conditions, and consistent search parameters and cutoff established by the target-decoy determined false-discovery rate. Besides achieving superior overall proteome performance in total peptide, distinct peptide, and distinct protein identifications; analytical reproducibility of the CITP proteome platform coupled with the spectral counting approach are determined by a Pearson R(2) value of 0.98 and a CV of 15% across all proteins quantified. In contrast, extensive fraction overlapping in strong cation exchange greatly limits the ability of multidimensional LC separations for mining deeper into the tissue proteome as evidenced by the poor coverage in various protein functional categories and key protein pathways. The CITP proteomic technology, equipped with selective analyte enrichment and ultrahigh resolving power, is expected to serve as a critical component in the overall toolset required for biomarker discovery via shotgun proteomic analysis of tissue specimens.

Glioma pathophysiology: insights emerging from proteomics

Proteomics is increasingly employed in both neurological and oncological research to provide insight into the molecular basis of disease but rarely has a coherent, novel pathophysiological insight emerged. Gliomas account for >50% of adult primary intracranial tumors, with malignant gliomas (anaplastic astrocytomas and glioblastoma multiforme) being the most common. In glioma, the application of proteomic technology has identified altered protein expression but without consistency of these alterations or their biological significance being established. A systematic review of multiple independent proteomic analyses of glioma has demonstrated alterations of 99 different proteins. Importantly 10 of the 99 proteins found differentially expressed in glioma [PHB, Hsp20, serum albumin, epidermal growth factor receptor (EGFR), EA-15, RhoGDI, APOA1, GFAP, HSP70, PDIA3] were identified in multiple publications. An assessment of protein-protein interactions between these proteins compiled using novel web-based technology, revealed a robust and cohesive network for glioblastoma. The protein network discovered (containing TP53 and RB1 at its core) compliments recent findings in genomic studies of malignant glioma. The novel perspective provided by network analysis indicates that the potential of this technology to explore crucial aspects of glioma pathophysiology can now be realized but only if the conceptual and technical limitations highlighted in this review are addressed.

Genetic alterations and signaling pathways in the evolution of gliomas

Gliomas are the most common primary brain tumors. They account for more than 70% of all neoplasms of the central nervous system and vary considerably in morphology, location, genetic alterations, and response to therapy. Most frequent and malignant are glioblastomas. The vast majority (>90%) develops rapidly after a short clinical history and without evidence of a less malignant precursor lesion (primary or de novo glioblastoma). Secondary glioblastomas develop more slowly through progression from low-grade or anaplastic astrocytoma. These glioblastoma subtypes constitute distinct disease entities that affect patients of different age, develop through distinct genetic pathways, show different RNA and protein expression profiles, and may differ in their response to radio- and chemotherapy. Recently, isocitrate dehydrogenase 1 (IDH1) mutations have been identified as a very early and frequent genetic alteration in the pathway to secondary glioblastomas as well as that in oligodendroglial tumors, providing the first evidence that low-grade astrocytomas and oligodendrogliomas may share common cells of origin. In contrast, primary glioblastomas very rarely contain IDH1 mutations, suggesting that primary and secondary glioblastomas may originate from different progenitor cells, despite the fact that they are histologically largely indistinguishable. In this review, we summarize the current status of genetic alterations and signaling pathways operative in the evolution of astrocytic and oligodendroglial tumors.

Different molecular patterns in glioblastoma multiforme subtypes upon recurrence

One of the hallmarks of glioblastoma is its inherent tendency to recur. At this point patients with relapsed GBM show a survival time of only few months. The molecular basis of the recurrence process in GBM is still poorly understood. The aim of the present study was to investigate the genetic profile of relapsed GBM compared to their respective primary tumors. We have included 20 paired GBMs. In all tumor samples, we have analyzed p53 and PTEN status by sequencing analysis, EGFR amplification by semiquantitative PCR and a wide-genome fingerprinting was performed by microsatellite analysis. Among primary GBM, we observed twelve type 2 GBM, four type 1 GBM and four further GBM showing neither p53 mutations nor EGFR amplification (non-type 1-non-type 2 GBM). Upon recurrence, we have detected two molecular patterns of tumor progression: GBM initially showing either type 1 or type 2 profiles conserved them at the time of relapse. In contrast, non-type 1-non-type 2 GBM acquired the typical pattern of type 2 GBM and harbor EGFR amplification without p53 mutation. New PTEN mutations upon relapse were only detected in type 2 GBM. Additional LOH were more frequently identified in relapses of type 2 GBM than in those showing the type 1 signature. Taken together, our results strongly suggest that recurrences of GBM may display two distinct pattern of accumulation of molecular alterations depending on the profile of the original tumor.

The utility of functional interaction and cluster analysis in CNS proteomics

Proteomic studies offer enormous potential for gaining insight into cellular dynamics and disease processes. An immediate challenge for enhancing the utility of proteomics in translational research lies in methods of handling and interpreting the large datasets generated. Publications rarely extend beyond lists of proteins, putatively altered derived from basic statistics. Here we describe two additional distinct approaches (with particular strengths and limitations) that will enhance the analysis of proteomic datasets. Arithmetic and functional cluster analyses have been performed on proteins found differentially regulated in human glioma. These two approaches highlight (i) subgroups of proteins that may be co-regulated and play a role in glioma pathophysiology, and (ii) functional protein interactions that may improve comprehension of the biological mechanisms involved. A coherent proteomic strategy which involves both arithmetic and functional clustering, (together with careful consideration of conceptual limitations), is imperative for quantitative proteomics to deliver and advance the biological understanding of disease of the CNS. A strategy which combines arithmetic analysis and bioinformatics of protein-protein interactions is both generally applicable and will facilitate the interpretation of proteomic data.

Application and implementation of selective tissue microdissection and proteomic profiling in neurological disease

OBJECTIVE

Proteins are the primary components of cells and are vital constituents of any living organism. The proteins that make up an organism (proteome) are constantly changing and are intricately linked to neurological disease processes. The study of proteins, or proteomics, is a relatively new but rapidly expanding field with increasing relevance to neurosurgery.

METHODS

We present a review of the state-of-the-art proteomic technology and its applications in central nervous system diseases.

RESULTS

The technique of "selective microdissection" allows an investigator to selectively isolate and study a pathological tissue of interest. By evaluating protein expression in a variety of central nervous system disorders, it is clear that proteins are differentially expressed across disease states, and protein expression changes markedly during disease progression.

CONCLUSION

Understanding the patterns of protein expression in the nervous system has critical implications for the diagnosis and treatment of neurological disease. As gatekeepers in the diagnosis, evaluation, and treatment of central nervous system diseases, it is important for neurosurgeons to develop an appreciation for proteomic techniques and their utility.

Multifarious proteomic signatures and regional heterogeneity in glioblastomas

To investigate the underlying intratumoral diversity of molecular profiles in glioblastomas, a proteomic approach was introduced to compare samples from regions of different histological grade. Using two-dimensional gel electrophoresis (2DE) with matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), we compared prospectively collected tissue samples of different histological grade areas of three glioblastoma patients. Consistent results showing relatively high expression of ubiquitin carboxyl-terminal esterase L1 in low-histological-grade areas (Grade 2 > Grades 3 and 4) and high expression of transthyretin in high-histological-grade areas (Grade 2 < Grades 3 and 4) were demonstrated. These results were confirmed by western blot (WB) analysis and immunohistochemical staining. This study provided the evidence of multifarious proteomic signatures according to regional and histological heterogeneity in glioblastomas.

9-Aminoacridine-based anticancer drugs target the PI3K/AKT/mTOR, NF-kappaB and p53 pathways

Acquisition of a transformed phenotype involves deregulation of several signal transduction pathways contributing to unconstrained cell growth. Understanding the interplay of different cancer-related signaling pathways is important for development of efficacious multitargeted anticancer drugs. The small molecule 9-aminoacridine (9AA) and its derivative, the antimalaria drug quinacrine, have selective toxicity for tumor cells and can simultaneously suppress nuclear factor-kappaB (NF-kappaB) and activate p53 signaling. To investigate the mechanism underlying these drug activities, we used a combination of two-dimensional protein separation by gel electrophoresis and mass spectrometry to identify proteins whose expression is altered in tumor cells by 9AA treatment. We found that 9AA treatment results in selective downregulation of a specific catalytic subunit of the phosphoinositide 3-kinase (PI3K) family, p110 gamma. Further exploration of this observation demonstrated that the mechanism of action of 9AA involves inhibition of the prosurvival AKT/mammalian target of rapamycin (mTOR) pathway that lies downstream of PI3K. p110 gamma translation appears to be regulated by mTOR and feeds back to further modulate mTOR and AKT, thereby impacting the p53 and NF-kappaB pathways as well. These results reveal functional interplay among the PI3K/AKT/mTOR, p53 and NF-kappaB pathways that are frequently deregulated in cancer and suggest that their simultaneous targeting by a single small molecule such as 9AA could result in efficacious and selective killing of transformed cells.

Applications of emerging molecular technologies in glioblastoma multiforme

Glioblastoma multiforme (GBM) is the most common primary brain tumor in adults. Median survival from the time of diagnosis is less than a year, with less than 5% of patients surviving 5 years. These tumors are thought to arise through two different pathways. Primary GBMs represent de novo tumors, while secondary GBMs represent the malignant progression of lower-grade astrocytomas. Moreover, despite improvements in deciphering the complex biology of these tumors, the overall prognosis has not changed in the past three decades. The hope for improving the outlook for these glial-based malignancies is centered on the successful clinical application of current high-throughput technologies. For example, the complete sequencing of the human genome has brought both genomics and proteomics to the forefront of cancer research as a powerful approach to systematically identify large volumes of data that can be utilized to study the molecular and cellular basis of oncology. The organization of these data into a comprehensive view of tumor growth and progression translates into a unique opportunity to diagnose and treat cancer patients. In this review, we summarize current genomic and proteomic alterations associated with GBM and how these modalities may ultimately impact treatment and survival.

Proteomic characterization of primary diffuse large B-cell lymphomas in the central nervous system

OBJECT

The lack of primary lymphoid tissue within the central nervous system (CNS) confounds our understanding of the pathogenesis of primary CNS lymphomas (PCNSLs). Comparing the protein expression of PCNSLs and sporadic systemic lymphomas (SSLs) provides a useful strategy for identifying a molecular signature that characterizes disease-associated features and provides information regarding tumor initiation and progression.

METHODS

Seven diffuse large B-cell PCNSLs were selected to undergo 2D gel electrophoresis, and profiled proteomes from these PCNSLs were compared with those from 7 diffuse large B-cell SSLs. Distinguishing proteins were sequenced using mass spectrometry.

RESULTS

Two-dimensional gel electrophoresis identified an average of 706 proteins from each specimen. Computerized gel analysis and manual reconfirmation revealed a 96% similarity in the proteomes of PCNSLs and SSLs. Comparative analysis identified 9 proteins significantly overexpressed (p < 0.05) and 16 proteins downregulated in PCNSLs. The proteomic findings were further validated using Western blot and immunohistochemical staining.

CONCLUSIONS

The similarities in proteomic patterns between PCNSLs and SSLs suggest that these tumor types share structural similarities, acquired during differentiation. The ultimate fate of lymphomatous cells (CNS vs systemic) may be related to differentially expressed proteins, which function in homing and host processing. Elucidating the roles of these differentially expressed proteins will prove valuable in understanding the pathogenesis of PCNSL.

Genomic expression patterns distinguish long-term from short-term glioblastoma survivors: a preliminary feasibility study

We used microarray analysis to investigate associations between genotypic expression profiles and survival phenotypes in patients with primary glioblastoma (GBM). Tumor samples from 7 long-term glioblastoma survivors (>24 months) and 13 short-term survivors (<9 months) were analyzed to detect differential patterns of gene expression between these groups and to identify genotypic subclasses of glioblastomas that correlate with survival phenotypes. Five unsupervised and three supervised clustering algorithms consistently and accurately grouped the tumors into genotypic subgroups corresponding to the two clinical survival phenotypes. Three unique prospective mathematical classification algorithms were subsequently trained to use expression data to stratify unknown glioblastomas between survival groups and performed this task with 100% accuracy in validation studies. A set of 1478 genes with significant differential expression (p<0.01) between long-term and short-term survivors was identified, and additional mathematical filtering was used to isolate a 43-gene "fingerprint" that distinguished survival phenotypes. Differential regulation of a subset of these genes was confirmed using RT-PCR. Gene ontology analysis of the fingerprint demonstrated pathophysiologic functions for the gene products that are consistent with current models of tumor biology, suggesting that differential expression of these genes may contribute etiologically to the observed differences in survival. These results demonstrate that unique expression profiles characterize genotypic subsets of primary GBMs associated with differential survival phenotypes, and these profiles can be used in a prospective fashion to assign unknown tumors to survival groups. Future efforts will focus on building more robust classifiers and identifying additional subclasses of gliomas with phenotypic significance.

Identification of a novel proliferation-related protein, WHSC1 4a, in human gliomas

Dynamic changes in the expression of multiple genes appear to be common features that distinguish transformed cells from their normal counterparts. We compared the proteomic profiles of four glioblastoma multiforme (GBM) tissue samples and four normal brain cortex samples to examine the molecular basis of gliomagenesis. Trypsin-digested protein samples were separated by capillary isoelectric focusing with nano-reversed-phase liquid chromatography and were profiled by mass spectrometric sequencing. Wolf-Hirschhorn syndrome candidate 1 (WHSC1), along with 103 other proteins, was found only in the GBM proteomes. Western blot and immunohistochemistry verified our proteomic findings and demonstrated that 30-kDa WHSC1 expression increases with ascending tumor proliferation activity. RNA interference could suppress glioma cell growth by blocking WHSC1 expression. Our novel findings encourage the application of proteomic techniques in cancer research.

Prognostic markers of astrocytoma: how to predict the unpredictable?

Astrocytomas are the most frequent tumors originating in the human nervous system. They carry a dismal prognosis as high-grade astroctyoma patients (World Health Organization [WHO] grade III and IV) rarely live beyond 5 years. At present, these tumors are mainly diagnosed through the difficult task of histologic examination of tissue obtained through stereotactic biopsy or tumor resection. In addition to determining the malignancy grade through histologic studies, the only other prognostic factors used in clinical setting are patient age and performance status. To overcome current limitations, research is underway to develop molecular approaches for glioma classification. These include identification, characterization and expansion of clinical (patient characteristics and imaging variables), histologic (WHO classification criteria) and molecular (genetic and proteomic) factors with prognostic potential. In this review the established classification characteristics, along with recent advances that may lead to the addition of new parameters and thus improve patient management and survival, are discussed.

Investigation of molecular factors associated with malignant transformation of oligodendroglioma by proteomic study of a single case of rapid tumor progression

PURPOSE

Frozen tumor tissues from a patient who showed rapid progression to anaplastic oligodendroglioma after near total resection of oligodendroglioma were used to examine differential expression of proteins to gain better understanding of the pathogenesis of malignant transformation.

METHODS

We have determined their protein profiles using a 2D gel electrophoresis and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry approach.

RESULTS

Among 23 differentially expressed spots, overexpression of peroxiredoxin 6 and underexpression of rho GDP dissociation inhibitor alpha were confirmed to be valid after western blot and immunocytochemical analysis of oligodendroglioma tissue.

CONCLUSIONS

Abnormal expression of peroxiredoxin 6 and rho GDP dissociation inhibitor alpha may be associated with malignant transformation in oligodendroglioma and these proteins might be candidates of molecular predictive factors.

Genetic pathways to primary and secondary glioblastoma

Glioblastoma is the most frequent and most malignant human brain tumor. The prognosis remains very poor, with most patients dying within 1 year after diagnosis. Primary and secondary glioblastoma constitute distinct disease subtypes, affecting patients of different age and developing through different genetic pathways. The majority of cases (>90%) are primary glioblastomas that develop rapidly de novo, without clinical or histological evidence of a less malignant precursor lesion. They affect mainly the elderly and are genetically characterized by loss of heterozygosity 10q (70% of cases), EGFR amplification (36%), p16(INK4a) deletion (31%), and PTEN mutations (25%). Secondary glioblastomas develop through progression from low-grade diffuse astrocytoma or anaplastic astrocytoma and manifest in younger patients. In the pathway to secondary glioblastoma, TP53 mutations are the most frequent and earliest detectable genetic alteration, already present in 60% of precursor low-grade astrocytomas. The mutation pattern is characterized by frequent G:C-->A:T mutations at CpG sites. During progression to glioblastoma, additional mutations accumulate, including loss of heterozygosity 10q25-qter ( approximately 70%), which is the most frequent genetic alteration in both primary and secondary glioblastomas. Primary and secondary glioblastomas also differ significantly in their pattern of promoter methylation and in expression profiles at RNA and protein levels. This has significant implications, particularly for the development of novel, targeted therapies, as discussed in this review.

Methylation ofO6-Methylguanine DNA Methyltransferase and Loss of Heterozygosity on 19q and/or 17p Are Overlapping Features of Secondary Glioblastomas with Prolonged Survival

PURPOSE

Recent data suggest that methylation of the DNA repair gene O(6)-methylguanine DNA methyltransferase (MGMT), by increasing the chemosensitivity of glioblastoma multiforme, is significantly associated with improved prognosis. Results in contradiction with these findings, however, are present in the literature and the clinical and genetic context framing MGMT methylation is poorly characterized.

EXPERIMENTAL DESIGN

To address these issues, we have investigated the MGMT methylation status, clinical and magnetic resonance imaging characteristics, and relevant genetic features (loss of heterozygosity on 17p and 19q, EGFR amplification, and p53 mutations) in a retrospective study on 86 patients affected by glioblastoma multiforme: 72 patients had a clinical history indicating de novo insurgence of the tumor and the remaining 14 were secondary glioblastoma multiforme.

RESULTS

MGMT methylation was detected by methylation-specific PCR in 41 of 86 cases (47.7%; Meth+). Progression-free survival and overall survival were significantly longer in Meth+ than in Meth- patients [10 versus 7 months (P=0.003, log-rank test) and 18 versus 14 months (P=0.0003, log-rank test), respectively]. Mixed-nodular enhancement at magnetic resonance imaging was significantly more frequent in Meth+ and secondary glioblastoma multiforme and ring enhancement in Meth- and primary glioblastoma multiforme (P<0.005). MGMT methylation was more present in secondary glioblastoma multiforme (P=0.006) and associated with loss of heterozygosity on 17p and/or 19q (P=0.005).

CONCLUSIONS

These observations suggest that MGMT methylation is part of a genetic signature of glioblastomas that developed from lower-grade gliomas.

Proteome analysis of microdissected formalin-fixed and paraffin-embedded tissue specimens

Targeted proteomics research, based on the enrichment of disease-relevant proteins from isolated cell populations selected from high-quality tissue specimens, offers great potential for the identification of diagnostic, prognostic, and predictive biological markers for use in the clinical setting and during preclinical testing and clinical trials, as well as for the discovery and validation of new protein drug targets. Formalin-fixed and paraffin-embedded (FFPE) tissue collections, with attached clinical and outcome information, are invaluable resources for conducting retrospective protein biomarker investigations and performing translational studies of cancer and other diseases. Combined capillary isoelectric focusing/nano-reversed-phase liquid chromatography separations equipped with nano-electrospray ionization-tandem mass spectrometry are employed for the studies of proteins extracted from microdissected FFPE glioblastoma tissues using a heat-induced antigen retrieval (AR) technique. A total of 14,478 distinct peptides are identified, leading to the identification of 2733 non-redundant SwissProt protein entries. Eighty-three percent of identified FFPE tissue proteins overlap with those obtained from the pellet fraction of fresh-frozen tissue of the same patient. This large degree of protein overlapping is attributed to the application of detergent-based protein extraction in both the cell pellet preparation protocol and the AR technique.

Biomarker discovery: a proteomic approach for brain cancer profiling

Gliomas in the form of astrocytomas, anaplastic astrocytomas and glioblastomas are the most common brain tumors in humans. Early detection of these cancers is crucial for successful treatment. Proteomics promises the discovery of biomarkers and tumor markers for early detection and diagnosis. In the current study, a differential gel electrophoresis technology coupled with matrix-assisted laser desorption/ionization-time of flight and liquid chromatography-tandem mass spectroscopy was used to investigate tumor-specific changes in the proteome of human brain cancer. Fifty human brain tissues comprising varying diagnostic groups (non-tumor, grade I, grade II, grade III and grade IV) were run in duplicate together with an internal pool sample on each gel. The proteins of interest were automatically picked, in-gel digested and mass spectrometry fingerprinted. Two hundred and eleven protein spots were identified successfully and were collapsed into 91 unique proteins. Approximately 20 of those 91 unique proteins had, to our knowledge, not been reported previously as differentially expressed in human brain cancer. Alb protein, peroxiredoxin 4 and SH3 domain-binding glutamic acid-rich-like protein 3 were upregulated in glioblastoma multiform versus non-tumor tissues. However, aldolase C fructose-biphosphate, creatine kinase, B chain dihydrolipoyl dehydrogenase, enolase 2, fumarate hydratase, HSP60, lactoylglutathione lyase, lucine aminopeptidase, Mu-crystallin homolog, NADH-UO 24, neurofilament triplet L protein, septin 2, stathmin and vacuolar ATP synthase subunit E were downregulated in glioblastoma multiform compared with non-tumor tissues. These differentially expressed proteins provided novel information on the differences existing between normal brain and gliomas, and thus might prove to be useful molecular indicators of diagnostic or prognostic value.

Comparative proteomic profiles of meningioma subtypes

Meningiomas are classified into three groups (benign, atypical, and anaplastic) based on morphologic characteristics. Atypical meningiomas, which are WHO grade 2 tumors, and anaplastic meningiomas, which are WHO grade 3 tumors, exhibit an increased risk of recurrence and premature death compared with benign WHO grade 1 tumors. Although atypical and anaplastic meningiomas account for <10% of all of meningiomas, it can be difficult to distinguish them from benign meningiomas by morphologic criteria alone. We used selective tissue microdissection to examine 24 human meningiomas and did two-dimensional gel electrophoresis to determine protein expression patterns. Proteins expressed differentially by meningiomas of each WHO grade were identified and sequenced. Proteomic analysis revealed protein expression patterns unique to WHO grade 1, 2, and 3 meningiomas and identified 24 proteins that distinguish each subtype. Fifteen proteins showed significant changes in expression level between benign and atypical meningiomas, whereas nine distinguished atypical from anaplastic meningiomas. Differential protein expression was confirmed by Western blotting and immunohistochemistry. We established differential proteomic profiles that characterize and distinguish meningiomas of increasing grades. The proteins and proteomic profiles enhance understanding of the pathogenesis of meningiomas and have implications for diagnosis, prognosis, and treatment.

Proteomic analysis of inclusion body myositis

Sporadic inclusion body myositis (IBM) is the most frequently acquired inflammatory myopathy of late adult life, yet its diagnostic criteria and pathogenesis remain poorly defined. Because effective treatment is lacking, research efforts have intensified to identify specific markers for this debilitating disorder. In this study, proteomic analysis of 4 cases of sporadic IBM was compared with 5 cases of inflammatory myopathy without clinicopathologic features of IBM to distinguish the IBM-specific proteome. Proteins were separated by 2-dimensional polyacrylamide gel electrophoresis and profiled by mass spectrometric sequencing. Expression of most proteins remained unchanged; however, 16 proteins were upregulated and 6 proteins were downregulated in IBM compared with cases of non-IBM inflammatory myopathy. These IBM-specific proteins included apolipoprotein A-I, amyloid beta precursor protein, and transthyretin, which have been associated with amyloidosis; superoxide dismutase, enolase, and various molecular chaperones indicate perturbations in detoxification, energy metabolism, and protein folding, respectively. The IBM-downregulated proteins mainly serve as carriers for muscle contraction and other normal muscle functions. We further applied Western blot and immunohistochemistry to verify the proteomic findings. This study validates proteomics as a powerful tool in the study of muscle disease and indicates a unique pattern of protein expression in IBM.

Capillary separations enabling tissue proteomics-based biomarker discovery

Development of the capability to enable large-scale proteome studies, analogous to comprehensive gene expression analysis, will clearly have far-reaching impacts on protein biomarker investigations of human diseases such as cancer through interrogation of the archived fresh frozen and formalin-fixed and paraffin-embedded tissue collections. This review therefore focuses on the most recent advances in microdissection techniques and proteome platforms for procuring homogeneous subpopulations of tumor cells or structures and performing comprehensive analysis of protein profiles within tissue specimens, respectively. Developments in capillary separations capable of providing extremely high resolving power and selective analyte enrichment are particularly highlighted for their roles within the broader context of a state-of-the-art integrated tissue proteome effort. The capabilities of CIEF-based multidimensional separations for performing proteome analysis from minute samples create new opportunities in the pursuit of biomarker discovery using enriched and selected cell populations procured from tissue specimens. These proteome technological advances combined with recently developed tissue microdissection techniques provide powerful tools for those seeking to gain a greater understanding at the global level of the cellular machinery associated with human diseases such as cancer.

Proteomic analysis in cancer research: potential application in clinical use

The ultimate goal of cancer proteomics is to adapt proteomic technologies for routine use in clinical laboratories for the purpose of diagnostic and prognostic classification of disease states, as well as in evaluating drug toxicity and efficacy. The novel technologies allows researchers to facilitate the comprehensive analyses of genomes, transcriptomes, and proteomes in health and disease. The information that is expected from such technologies may soon exert a dramatic change in cancer research and impact dramatically on the care of cancer patients. Analysis of tumor-specific proteomic profiles may also allow better understanding of tumor development and the identification of novel targets for cancer therapy. The localization of gene products, which is often difficult to deduce from the sequence, can be determined experimentally. Mechanisms, such as regulation of protein function by proteolysis, recycling, and isolation in cell compartments, affect gene products, not genes. Finally, protein-protein interactions and the molecular composition of cellular structures can be determined only at the protein level. The biological variability among patient samples as well as the great dynamic range of biomarker concentrations are currently the main challenges facing efforts to deduce diagnostic patterns that are unique to specific disease states. While several strategies exist to address this problem, we have tried to offer a wide perspective about the current possibilities.

Protein expression in experimental malignant glioma varies over time and is altered by radiotherapy treatment

Radiotherapy is one of the mainstays of glioblastoma (GBM) treatment. This study aims to investigate and characterise differences in protein expression patterns in brain tumour tissue following radiotherapy, in order to gain a more detailed understanding of the biological effects. Rat BT4C glioma cells were implanted into the brain of two groups of 12 BDIX-rats. One group received radiotherapy (12 Gy single fraction). Protein expression in normal and tumour brain tissue, collected at four different time points after irradiation, were analysed using surface enhanced laser desorption/ionisation – time of flight – mass spectrometry (SELDI-TOF-MS). Mass spectrometric data were analysed by principal component analysis (PCA) and partial least squares (PLS). Using these multivariate projection methods we detected differences between tumours and normal tissue, radiation treatment-induced changes and temporal effects. 77 peaks whose intensity significantly changed after radiotherapy were discovered. The prompt changes in the protein expression following irradiation might help elucidate biological events induced by radiation. The combination of SELDI-TOF-MS with PCA and PLS seems to be well suited for studying these changes. In a further perspective these findings may prove to be useful in the development of new GBM treatment approaches.

Distinct transcription profiles of primary and secondary glioblastoma subgroups

Glioblastomas are invasive and aggressive tumors of the brain, generally considered to arise from glial cells. A subset of these cancers develops from lower-grade gliomas and can thus be clinically classified as "secondary," whereas some glioblastomas occur with no prior evidence of a lower-grade tumor and can be clinically classified as "primary." Substantial genetic differences between these groups of glioblastomas have been identified previously. We used large-scale expression analyses to identify glioblastoma-associated genes (GAG) that are associated with a more malignant phenotype via comparison with lower-grade astrocytomas. We have further defined gene expression differences that distinguish primary and secondary glioblastomas. GAGs distinct to primary or secondary tumors provided information on the heterogeneous properties and apparently distinct oncogenic mechanisms of these tumors. Secondary GAGs primarily include mitotic cell cycle components, suggesting the loss of function in prominent cell cycle regulators, whereas primary GAGs highlight genes typical of a stromal response, suggesting the importance of extracellular signaling. Immunohistochemical staining of glioblastoma tissue arrays confirmed expression differences. These data highlight that the development of gene pathway-targeted therapies may need to be specifically tailored to each subtype of glioblastoma.