The glioblastoma, the grade IV glioma, is one of the highly malignant human cancers with very poor patient survival. We use tumor tissue materials, tumor derived cell lines and animal models to study the biology of glioma development. Investigating the role of epigenetic regulation including DNA methylation, miRNA regulation and chromatin remodeling during glioma development is an important area of research currently. We also use multiple proteomic approaches to identify serum biomarkers of glioma. Some of the recently carried out work are described below.
Insulin-like growth factor signaling in glioma
Upon investigation of the IGF pathway, we found IGF2BP3/IMP3 transcript and protein to be up-regulated in GBMs but not in lower grade astrocytomas (common form of glioma). IMP3 is a RNA binding protein known to bind to the 5’-untranslated region of IGF-2 mRNA thereby activating its translation. Over-expression and knockdown based studies establish a role for IMP3 in promoting proliferation, anchorage-independent growth, invasion and chemoresistance. IMP3 over-expressing 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. Further, 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. Further, 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 pro-proliferative effects of IMP3 were indeed mediated through IGF-2. Concordantly, PI3-kinase and MAP-kinase, 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 pro-proliferative and pro-invasive marker acting through IGF2 resulting in the activation of oncogenic PI3-kinase and MAP-kinase pathways
Increased IGF2BP3 enhances the translation of IGF2, which contributes to glioma malignancy
MicroRNA regulation during glioma development
MicroRNAs (miRNAs) are endogenous noncoding small RNAs which negatively regulate gene expression either by degrading specific mRNA or inhibiting translation. miRNAs have been linked to variety of cancers, in which miRNAs were shown to act like either oncogenes or tumor suppressors
We carried out a large-scale genome-wide miRNA expression profiling of several GBM (grade IV), grade III and normal brain samples with an aim to find deregulated microRNAs in malignant astrocytoma. We identified several differentially regulated miRNAs between these groups which could differentiate glioma grades and normal brain as recognized by Principal Component Analysis (PCA). More importantly, we identified a most discriminatory 23 miRNA expression signature, by using Prediction Analysis of Microarrays (PAM) that precisely distinguished GBM from grade III 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 and normal samples. Inhibition of two GBM up regulated miRNAs (miR-21 and miR-23a) and exogenous over expression of two GBM down regulated 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 miRNA expression signature for malignant astrocytoma, in particular GBM and demonstrated the miRNA involvement and their importance in astrocytoma development.
Heat map showing expression profiles of 23 microRNAs that can be used to classify anaplastic astrocytoma (grade 3) and glioblastoma (grade 4) samples (red indicates that the miRNA is over expressed, and green that it is under expressed). Source: Modern Pathology (2010) 23, 1404–1417; doi:10.1038/modpathol.2010.135
To identify a miRNA expression signature that can predict GBM patient survival, we analyzed the miRNA expression data of GBM patients derived from The Cancer Genome Atlas (TCGA) dataset. We divided the patients randomly into training and testing sets with equal number in each group. We identified 10 significant miRNAs using Cox regression analysis on the training set and formulated a risk score based on the expression signature of these miRNAs that segregated the patients into high and low risk groups with significantly different survival times (P < 0.0001). Of these 10 miRNAs, 7 were found to be risky miRNAs and 3 were found to be protective. This signature was independently validated in the testing set. GBM patients with high risk scores had overall poor survival compared to the patients with low risk scores. Overall survival among the entire patient set was 35.0% at 2 years, 21.5% at 3 years, 18.5% at 4 years and 11.8% at 5 years in the low risk group, versus 11.0%, 5.5%, 0.0 and 0.0% respectively in the high risk group (P < 0.0001). Cox multivariate analysis with patient age as a covariate on the entire patient set identified risk score based on the 10 miRNA expression signature to be an independent predictor of patient survival (P = 0.003). Thus we have identified a miRNA expression signature that can predict GBM patient survival. These findings may have implications in the understanding of gliomagenesis, development of targeted therapy and selection of high risk cancer patients for adjuvant therapy.
Ten miRNA Risk-Score Analysis of 111 GBM patients (training set). A) Heat map of ten miRNA expression profiles of GBM patients; rows represent risky and protective miRNAs, and columns represent patients. The blue line represents the miRNA signature cutoff dividing patients into low-risk and high-risk groups. B) Patient survival status along with risk score. C) miRNA risk-score distribution of the GBM patients.