New molecular tests for brain tumor

K. S. Jayaraman

doi:10.1038/nindia.2011.59 Published online 26 April 2011

Scientists at the Indian Institute of Science (IISc) in Bangalore have discovered potentially new molecular diagnostic tests for better management of glioblastoma or GBM — the commonest form of malignant brain cancer in adults.

They have found unique molecular signatures that would allow rapid and accurate detection of glioblastoma and also predict the response of patients to the treatment.

Kumaravel Somasundaram

"Predicting the benefit of various cancer therapies to patients is very important and forms the foundation of personalized cancer therapy," Kumaravel Somasundaram, professor of microbiology and cell biology and one of the authors of the report, told Nature India.

Glioma, the most common primary brain tumor, have four distinct grades from least aggressive (Grade I) to the fastest growing (Grade IV), which kills nearly every patient within two years. "Precise identification of GBM is essential for choosing the correct treatment option and clinical management," Somasundaram said.

Moreover, since more than one grade of cells exist within the same tumor, sometimes pathologists may not be able to accurately grade the tumor. "This necessitates a more robust molecular classifier for improvement of glioblastoma patient management," he said.

The IISc researchers decided to focus on microRNAs or miRNAs. MicroRNAs are short ribonucleic acid (RNA) molecules — on average only 22 nucleotides long — which, by affecting gene expression, are involved in most biological processes. Since miRNAs can act as oncogenes (potential cancer causing genes) or tumor suppressor genes, they have been linked to a variety of cancers.

Last year, following genome-wide expression profiling, Somasundaram's group reported identification of a 'miRNA expression signature' which can accurately discriminate glioblastoma from tumors of other grades. Now they have identified a unique miRNA expression signature that can predict GBM patient survival.

In this study, supported by India government's Department of Biotechnology, the IISc researchers made use of the GBM patients' data available with The Cancer Genome Atlas (TCGA) maintained by the U.S. National Institutes of Health. They subjected the miRNA expression data from a total of 222 GBM patients derived from TCGA data set to a standard statistical analysis called "Cox proportional hazards regression analysis" leading to identification of 10 miRNAs that were significantly correlated with patient survival.

"Of these 10 miRNAs, three were protective and seven risky with respect to the association between their expression and patient survival," the scientists reported. Tumors from patients belonging to high risk group tend to express higher levels of risky miRNAs, whereas tumors from patients with low risk group tend to express higher levels of protective miRNAs. "The protective and risky nature of these miRNAs is suggestive of their functions being either inhibitory or promoting, respectively, of various properties of cancer cells like proliferation, migration and invasion," they said.

These 10 risky and protective miRNAs were used to create a signature by calculating a risk score for each patient's survival prediction. Patients with high risk scores had shorter survival compared to those with low scores.

The scientists said that their method for predicting the survival time of GBM patients was fully validated by analyzing the TCGA patients' data. For instance 35% of patients who survived at the end of two years were in low risk group in contrast to only 11% who survived in high risk group. While the survival rate was 21.5% at 3 years, 18.5% at 4 years and 11.8% at 5 years in the low risk group, only 5.5% in the high risk group survived at the end of three years. All those in the TCGA dataset who did not survive after three years belonged to the high risk group.

The 10 miRNA signature, identified in this study, classifies patients into low and high risk groups. This may help clinicians identify high risk patients for more effective adjuvant therapy in addition to the standard treatment protocol, the IISc scientists reported.

Similar studies predicting patient survival have been done in other cancers like lung, breast and pancreas cancer as well as lymphocytic leukemia. However, it had not been done for GBM patients thus far, Somasundaram said. "To our knowledge, this is the first report of a miRNA expression signature predicting GBM patient survival," he said.

"Our finding is also likely to generate potential molecular targets for the development of anticancer therapy," the report said. "Since miRNAs can target multiple genes, more thorough studies are needed to understand the mechanism of action of these miRNAs which is likely to result in better understanding of glioma."


  1. Srinivasan, S. et al. A Ten-microRNA Expression Signature Predicts Survival in Glioblastoma. PLoS ONE 6, e17438 doi: 10.1371/journal.pone.0017438 (2011)  | Article | PubMed |
  2. Rao, S. A. et al. Genome-wide expression profiling identifies deregulated miRNAs in malignant astrocytoma. Modern Pathol. 23, 1404-1417 (2010)  | Article | ISI |