Researchers from the University of Oxford and the MD Anderson Cancer Center reported this week that they have demonstrated that a protein biomarker can predict which patients will respond to a new class of cancer drug, which they said could potentially open the door to the use of protein biomarkers in personalized medicine.
In a study published March 22 in the online edition of the Proceedings of the National Academy of Science, the scientists reported the successful use of the protein HR23B to screen patients with a rare kind of non-Hodgkin lymphoma who respond to a new class of oncotherapeutic called HDAC inhibitors.
In a statement, Nick La Thangue, a co-author of the PNAS study and director of the department of clinical pharmacology at Oxford, said "the presence or absence of the biomarker can now be used as a diagnostic test to identify which patients will benefit from this drug," and added that their approach can be used to screen the efficacy of any drug for any disease.
He and his colleagues focused on a non-Hodgkin lymphoma called cutaneous T-cell lymphoma, or CTCL, and HDAC inhibitors, which work by stopping the action of the protein histone deacetylase. Suberoylanilide hydroxamic acid, or SAHA, was the first drug of this class to receive regulatory approval. Also called Vorinostat, SAHA is marketed under the name Zolinza.
La Thangue and his collaborators used a whole-genome screen to identify genes active in CTCL cells that govern whether the cancer cells respond to SAHA. Each gene was silenced, allowing the researchers to assess how well the drug worked, and eventually to discover that HR23B determined CTCL's sensitivity to SAHA.
According to the researchers, the presence of HR23B in biopsies of patients with CTCL predicted who would respond to SAHA treatment about 72 percent of the time.
Based on their findings, La Thangue said that the whole-genome screen approach can be used as a general tool to find biomarkers for different cancers and different drugs.
"This new work validates our approach for identifying biomarkers," La Thangue said. "It should be possible to find biomarkers for every drug on the market and every drug in development and truly personalize cancer drug medicine."