Moffitt scientists discover new applications for Novartis’s Zykadia
pharmafile | October 11, 2017 | News story | Research and Development | Cancer, Moffitt, NSCLC, ceritinib, lung cancer, zykadia
Through the use of molecular screening, functional proteomics and computer-based modelling, researchers from the Moffitt Cancer Center have been working to determine new biological targets for treatments already approved in other indications or that otherwise have well-known uses. The team have now announced that they have identified the already FDA-approved ceritinib to provide anti-cancer benefits in previously unidentified targets.
Researchers at Moffitt screened 240 FDA-approved treatments as well as those currently in development to identify potential alternative uses. Among this number, they singled out ceritinib for its unique mode of action. Ceritinib, as known as Novartis’s Zykadia, is approved for the treatment of ALK-rearranged metastatic non-small cell lung cancer (NSCLC), and works in this way by targeting protein ALK and inhibiting the growth of lung cancer cells that do not have genetic alterations in the ALK gene.
In cells without ALK arrangements, the team discovered that drug inhibits a number of previously unidentified targets, which in turn lead to resistance to chemotherapy treatment paclitaxel. As such, when combined, the researchers found that they produced greater effectiveness in reducing cell viability than either agent alone, meaning the combination could be useful in treating other cancers without ALK rearrangements.
“The results also demonstrate the benefits of using a combined screening, proteomics and computer-based modelling approach to identify drugs that act on multiple targets and to determine how they function,” explained study lead author Uwe Rix, assistant member of the Drug Discovery Program at Moffitt. “In the future, this strategy may facilitate further drug repurposing efforts and lead to an increase in new therapy options for patients with difficult-to-treat diseases.”
Matt Fellows
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