Genome-wide expression profiling identifies deregulated miRNAs in malignant astrocytoma

Malignant astrocytoma includes anaplastic astrocytoma (grade III) and glioblastoma (grade IV). Among them, glioblastoma is the most common primary brain tumor with dismal responses to all therapeutic modalities. We performed a large-scale, genome-wide microRNA (miRNA) (n=756) expression profiling of 26 glioblastoma, 13 anaplastic astrocytoma and 7 normal brain samples with an aim to find deregulated miRNA in malignant astrocytoma. We identified several differentially regulated miRNAs between these groups, which could differentiate glioma grades and normal brain as recognized by PCA. More importantly, we identified a most discriminatory 23-miRNA expression signature, by using PAM, which precisely distinguished glioblastoma from anaplastic astrocytoma with an accuracy of 95%. The differential expression pattern of nine miRNAs was further validated by real-time RT-PCR on an independent set of malignant astrocytomas (n-72) and normal samples (n=7). Inhibition of two glioblastoma-upregulated miRNAs (miR-21 and miR-23a) and exogenous overexpression of two glioblastoma-downregulated miRNAs (miR-218 and miR-219-5p) resulted in reduced soft agar colony formation but showed varying effects on cell proliferation and chemosensitivity. Thus we have identified the miRNA expression signature for malignant astrocytoma, in particular glioblastoma, and showed the miRNA involvement and their importance in astrocytoma development. Modern Pathology (2010) 23, 1404-1417; doi:10.1038/modpathol.2010.135; published online 13 August 2010

A 16-Gene Signature Distinguishes Anaplastic Astrocytoma from Glioblastoma

Anaplastic astrocytoma (AA; Grade III) and glioblastoma (GBM; Grade IV) are diffusely infiltrating tumors and are called malignant astrocytomas. The treatment regimen and prognosis are distinctly different between anaplastic astrocytoma and glioblastoma patients. Although histopathology based current grading system is well accepted and largely reproducible, intratumoral histologic variations often lead to difficulties in classification of malignant astrocytoma samples. In order to obtain a more robust molecular classifier, we analysed RT-qPCR expression data of 175 differentially regulated genes across astrocytoma using Prediction Analysis of Microarrays (PAM) and found the most discriminatory 16-gene expression signature for the classification of anaplastic astrocytoma and glioblastoma. The 16-gene signature obtained in the training set was validated in the test set with diagnostic accuracy of 89%. Additionally, validation of the 16-gene signature in multiple independent cohorts revealed that the signature predicted anaplastic astrocytoma and glioblastoma samples with accuracy rates of 99%, 88%, and 92% in TCGA, GSE1993 and GSE4422 datasets, respectively. The protein-protein interaction network and pathway analysis suggested that the 16-genes of the signature identified epithelial-mesenchymal transition (EMT) pathway as the most differentially regulated pathway in glioblastoma compared to anaplastic astrocytoma. In addition to identifying 16 gene classification signature, we also demonstrated that genes involved in epithelial-mesenchymal transition may play an important role in distinguishing glioblastoma from anaplastic astrocytoma.

Glioblastoma-Specific Protein Interaction Network Identifies PP1A and CSK21 as Connecting Molecules between Cell Cycle-Associated Genes

Glioblastoma (GBM; grade IV astrocytoma) is a very aggressive form of brain cancer with a poor survival and few qualified predictive markers. This study integrates experimentally validated genes that showed specific upregulation in GBM along with their protein-protein interaction information. A system level analysis was used to construct GBM-specific network. Computation of topological parameters of networks showed scale-free pattern and hierarchical organization. From the large network involving 1,447 proteins, we synthesized subnetworks and annotated them with highly enriched biological processes. A careful dissection of the functional modules, important nodes, and their connections identified two novel intermediary molecules CSK21 and protein phosphatase 1 alpha (PP1A) connecting the two subnetworks CDC2-PTEN-TOP2A-CAV1-P53 and CDC2-CAV1-RB-P53-PTEN, respectively. Real-time quantitative reverse transcription-PCR analysis revealed CSK21 to be moderately upregulated and PP1A to be overexpressed by 20-fold in GBM tumor samples. Immunohistochemical staining revealed nuclear expression of PP1A only in GBM samples. Thus, CSK21 and PP1A, whose functions are intimately associated with cell cycle regulation, might play key role in gliomagenesis. Cancer Res; 70(16); 6437-47. (C)2010 AACR.

Proteomic Identification of Haptoglobin alpha 2 as a Glioblastoma Serum Biomarker: Implications in Cancer Cell Migration and Tumor Growth

Glioblastoma (GBM; grade IV astrocytoma) is the most malignant and common primary brain tumor in adults. Using combination of 2-DE and MALDI-TOF MS, we analyzed 14 GBM and 6 normal control sera and identified haptoglobin alpha 2 chain as an up-regulated serum protein in GBM patients. GBM-specific up-regulation was confirmed by ELISA based quantitation of haptoglobin (Hp) in the serum of 99 GBM patients as against lower grades (49 grade III/AA; 26 grade II/DA) and 26 normal individuals (p = 0.0001). Further validation using RT-qPCR on an independent set (n = 78) of tumor and normal brain (n = 4) samples and immunohistochemcial staining on a subset (n = 42) of above samples showed increasing levels of transcript and protein with tumor grade and were highest in GBM (p = < 0.0001 and < 0.0001, respectively). Overexpression of Hp either by stable integration of Hp cDNA or exogenous addition of purified Hp to immortalized astrocytes resulted in increased cell migration. RNAi-mediated silencing of Hp in glioma cells decreased cell migration. Further, we demonstrate that both human glioma and mouse melanoma cells overexpressing Hp showed increased tumor growth. Thus, we have identified haptoglobin as a GBM-specific serum marker with a role on glioma tumor growth and migration.

Insulin Growth Factor-2 Binding Protein 3 (IGF2BP3) Is a Glioblastoma-specific Marker That Activates Phosphatidylinositol 3-Kinase/Mitogen-activated Protein Kinase (PI3K/MAPK) Pathways by Modulating IGF-2

Glioblastoma is the most common and malignant form of primary astrocytoma. Upon investigation of the insulin-like growth factor (IGF) pathway, we found the IGF2BP3/IMP3 transcript and protein to be up-regulated in GBMs but not in lower grade astrocytomas (p<0.0001). IMP3 is an RNA binding protein known to bind to the 5'-untranslated region of IGF-2 mRNA, thereby activating its translation. Overexpression-and knockdown-based studies establish a role for IMP3 in promoting proliferation, anchorage-independent growth, invasion, and chemoresistance. IMP3 overexpressing B16F10 cells also showed increased tumor growth, angiogenesis, and metastasis, resulting in poor survival in a mouse model. Additionally, the infiltrating front, perivascular, and subpial regions in a majority of the GBMs stained positive for IMP3. Furthermore, two different murine glioma models were used to substantiate the above findings. In agreement with the translation activation functions of IMP3, we also found increased IGF-2 protein in the GBM tumor samples without a corresponding increase in its transcript levels. Also, in vitro IMP3 overexpression/knockdown modulated the IGF-2 protein levels without altering its transcript levels. Additionally, IGF-2 neutralization and supplementation studies established that the proproliferative effects of IMP3 were indeed mediated through IGF-2. Concordantly, PI3K and MAPK, the downstream effectors of IGF-2, are activated by IMP3 and are found to be essential for IMP3-induced cell proliferation. Thus, we have identified IMP3 as a GBM-specific proproliferative and proinvasive marker acting through IGF-2 resulting in the activation of oncogenic PI3K and MAPK pathways.

Higher topoisomerase 2 alpha gene transcript levels predict better prognosis in GBM patients receiving temozolomide chemotherapy: identification of temozolomide as a TOP2A inhibitor

The search for molecular markers which predict response to chemotherapy is an important aspect of current neuro-oncology research. MGMT promoter methylation is the only proved marker of glioblastoma. The purpose of this study was to assess the effect of topoisomerase expression on glioblastoma survival and study the mechanisms involved. The transcript levels of all isoforms of the topoisomerase family in all grades of diffuse astrocytoma were assessed. A prospective study of patients with glioblastoma treated by a uniform treatment procedure was performed with the objective of correlating outcome with gene expression. The ability of TOP2A enzyme to relax the super coiled plasmid DNA in the presence of temozolomide was evaluated to assess its effect on TOP2A. The temozolomide cyctotoxicity of TOP2A-silenced U251 cells was assessed. The transcript levels of TOP2A, TOP2B, and TOP3A are upregulated significantly in GBM in comparison with lower grades of astrocytoma and normal brain samples. mRNA levels of TOP2A correlated significantly with survival of the patients. Higher TOP2A transcript levels in GBM patients predicted better prognosis (P = 0.043; HR = 0.889). Interestingly, we noted that temozolomide inhibited TOP2A activity in in-vitro enzyme assays. We also noted that siRNA knock down of TOP2A rendered a glioma cell line resistant to temozolomide chemotherapy. We demonstrated for the first time that temozolomide is also a TOP2A inhibitor and established that TOP2A transcript levels determine the chemosensitivity of glioblastoma to temozolomide therapy. Very high levels of TOP2A are a good prognostic indicator in GBM patients receiving temozolomide chemotherapy.

IDH1 Mutations in Diffusely Infiltrating Astrocytomas Grade Specificity, Association With Protein Expression, and Clinical Relevance

IDH1 mutations are frequent genetic alterations in low-grade diffuse gliomas and secondary glioblastoma (GBM). To validate mutation frequency, IDH1 gene at codon 132 was sequenced in 74 diffusely infiltrating astrocytomas: diffuse astrocytoma (DA; World Health Organization WHO] grade II), anaplastic astrocytoma (AA; WHO grade III), and GBM (WHO grade IV). All cases were immunostained with IDH1-R132H monoclonal antibody. Mutational status was correlated with mutant protein expression, patient age, duration of symptoms, and prognosis of patients with GBM. We detected 31 (41.9%) heterozygous IDH1 mutations resulting in arginine-to-histidine substitution (R132H;CGT-CAT). All 12 DAs (100%), 13 of 14 AAs (92.9%), and 6 of 48 GBMs (12.5%) (5/6 83.3%] secondary, and 1/42 2.4%] primary) harbored IDH1 mutations. The correlation between mutational status and protein expression was significant (P < .001). IDH1 mutation status, though not associated with prognosis of patients with GBM, showed significant association with younger age and longer duration of symptoms in the whole cohort (P < .001). Our study validates IDH1 mutant protein expression across various grades of astrocytoma, and demonstrates a high incidence of IDH1 mutations in DA, AA, and secondary GBM.

Insulin like growth factor binding protein 4 promotes GBM progression and regulates key factors involved in EMT and invasion

Insulin like growth factor binding protein 4 (IGFBP4) regulates growth and development of tissues and organs by negatively regulating IGF signaling. Among most cancers, IGFBP4 has growth inhibitory role and reported as a down-regulated gene, except for renal cell carcinoma, wherein IGFBP4 promotes tumor progression. IGFBP4 expression has been shown to be higher in increasing grades of astrocytoma. However, the functional role of IGFBP4 in gliomas has not been explored. Surgical biopsies of 20 normal brain and 198 astrocytoma samples were analyzed for IGFBP4 expression by qRT-PCR. Highest expression of IGFBP4 mRNA was seen in GBM tumors compared to control brain tissues (median log2 of 2.035, p < 0.0001). Immunohistochemical analysis of 53 tissue samples revealed predominant nuclear staining of IGFBP4, seen maximally in GBMs when compared to DA and AA tumors (median LI = 29.12 +/- A 16.943, p < 0.001). Over expression of IGFBP4 in U343 glioma cells resulted in up-regulation of molecules involved in tumor growth, EMT and invasion such as pAkt, pErk, Vimentin, and N-cadherin and down-regulation of E-cadherin. Functionally, IGFBP4 over expression in these cells resulted in increased proliferation, migration and invasion as assessed by MTT, transwell migration, and Matrigel invasion assays. These findings were confirmed upon IGFBP4 knockdown in U251 glioma cells. Our data suggest a pro-tumorigenic role for IGFBP4 in glioma.

An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals

Glioblastomas (GBM) are largely incurable as they diffusely infiltrate adjacent brain tissues and are difficult to diagnose at early stages. Biomarkers derived from serum, which can be obtained by minimally invasive procedures, may help in early diagnosis, prognosis and treatment monitoring. To develop a serum cytokine signature, we profiled 48 cytokines in sera derived from normal healthy individuals (n = 26) and different grades of glioma patients (n = 194). We divided the normal and grade IV glioma/GBM serum samples randomly into equal sized training and test sets. In the training set, the Prediction Analysis for Microarrays (PAM) identified a panel of 18 cytokines that could discriminate GBM sera fromnormal sera with maximum accuracy (95.40%) and minimum error (4.60%). The 18-cytokine signature obtained in the training set discriminated GBM sera from normal sera in the test set as well (accuracy 96.55%; error 3.45%). Interestingly, the 18-cytokine signature also differentiated grade II/Diffuse Astrocytoma (DA) and grade III/Anaplastic Astrocytoma (AA) sera from normal sera very efficiently (DA vs. normal-accuracy 96.00%, error 4.00%; AA vs. normal-accuracy 95.83%, error 4.17%). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using 18 cytokines resulted in the enrichment of two pathways, cytokine-cytokine receptor interaction and JAK-STAT pathways with high significance. Thus our study identified an 18-cytokine signature for distinguishing glioma sera fromnormal healthy individual sera and also demonstrated the importance of their differential abundance in glioma biology.