Molecular Fingerprint for Classifying Gliomas

Scientists have demonstrated that the molecular fingerprint, or protein pattern, of gliomas can be used to classify tumors and predict their aggressiveness. Their work was reported at the annual International Molecular Targets and Cancer Therapeutics meeting in Boston (MA, USA).

Using a new process and mass spectrometry, researchers developed profiles of proteins active in 60 human brain samples. These included 19 samples of normal tissue and 15 grade II, 11 grade III, and 15 grade IV gliomas. The researchers identified more than 200 potential molecular markers that distinguished normal from malignant tissue and differentiated grade of tumor. With these profiles, they were able to group tumors according to survival rate with about 90% accuracy. The new process was developed by co-author Richard Caprioli, Ph.D., professor of biochemistry at Vanderbilt University (Nashville, TN, USA).

"We want to be able to provide patients with a complete picture of how their tumor is expected to behave and how it is expected to respond to treatment,” said Dr. Carprioli. "Clinicians would be able to aggressively treat those cancers that are truly aggressive and in those that are not, avoid such powerful treatment and exposing patients to more risk than necessary.”




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