The Times of India(14.06.05)

IISc scientists find key brain cancer gene


Johnson T.A.

Bangalore: In a finding that could have a significant impact on brain cancer diagnosis and treatment around the world, scientists from Indian Institute of Science (IISc) here have identified nearly 20 genes differentially expressed in brain cancer.
 
The scientists have found that one of the genes (labelled X for now) can indicate the progression path a glioma (brain cancer tumour) will take to develop into different tumour grades.
 
This finding can lead to a new diagnostic method to accurately evaluate the aggression of a tumour, say the scientists.
 
The findings on the X gene by scientists M.R.S. Rao, P. Kondaiah and Kumar Somasundaram; clinicians A.S. Hegde from the Sathya Sai Hospital, Sridevi Hegde from Manipal Hospital and Vani Santhosh from NIMHANS are to be published in Nature’s cancer journal Oncogene.
 
Using their discovery, the researchers are hoping to develop a DNA chip to predict the progression of brain cancer in a patient — by analysing theexpression of a group of genes. They have currently sought an international patent on the X gene.
 
The scientists are also set to publish papers on their findings regarding the other genes linked to brain cancer. Several of the genes are being linked with cancer for the first time and their roles are not yet known.
 
“We have found at least 100 genes linked to brain cancer during our DNA microarray studies. We have validated the expression pattern of 20 of them to date,’’ says Professor M.R.S. Rao from the department of biochemistry, IISc, who headed the work.
 
 “What is most exciting is that we can identify the grade of a cancer on the basis of genes expressed which act as markers,’’ says Prof. Rao. One of the most common tumours in the world with an incidence of 12 per one lakh, gliomas are among the biggest challenges in modern medicine.
 
These tumours are classified into four distinct grades (I to IV) on the basis of their aggressiveness. The grading of the tumours is done by analysing tumour tissue in the lab.
 
Grade IV gliomas are the most aggressive type and patients can die within a year of development even after treatment using currently available therapies.

   However, identifying the grade of the glioma is not an easy task and often the aggressive ones are mistaken for a less malignant one or vice-versa — affecting optimal treatment in either case.

   The researchers at Bangalore found that among the genes expressed in brain tumours, some are expressed differentially between grades and hence are accurate markers of the grade of the tumour.

   “This will enable a doctor to distinguish the slower type of tumour from the aggressive type, and optimise treatment for an individual patient, enhancing the prospects of survival,’’ says P. Kondaiah, professor in IISc’s department of molecular reproduction, development and genetics.

   “The genes discovered could also provide a new molecular markers-based system of classification of tumours,’’ says Kumaravel Somasundaram from the department of microbiology and cell biology, IISc.

   The scientists are now looking at taking their research from the “bench to the bedside’’ by co-relating the gene expression patterns they have found with patients responding to brain cancer treatment.

   The brain cancer genomics study has been carried out under the New Millennium Research Initiative of the Council for Scientific and Industrial Research — aimed at using cutting-edge technologies to solve important problems and to develop new applications.

Brain gain

Scientists from IISc, Bangalore have identified 20 genes that express in brain cancer.

This method can lead to a new diagnostic method to accurately evaluate the aggression of brain tumour.

The next stage is to develop DNA chip to predict progression of brain cancer in a patient.

The team has sought a global patent for the discovery. The findings will appear in Oncogene, Nature’s specialised journal.

Grading of brain cancer tumours becomes easy with the new method, allowing optimal treatment.