A bioinformatics approach to repurposing drugs resulted in identification of a class of antidepressants as a potential new treatment for small-cell lung cancer (SCLC), according to a study published in Cancer Discovery, a journal of the American Association for Cancer Research.
Based on data generated using bioinformatics, two drugs approved by the U.S. Food and Drug Administration (FDA) to treat symptoms of depression were tested on SCLC cells and animal models. Both antidepressants were found to induce SCLC cell death. They were also effective in mice bearing human SCLCs that had become resistant to the chemotherapy drug cisplatin. The antidepressants tested were imipramine, which modulates the activity of certain hormones causing mood disorders; and promethazine, a sedative, antiemetic, and antipsychotic drug.
Bioinformatics is a combination of mathematics and computer science used to sort, classify, and analyze large databases of biological and biochemical information.
"We implemented a bioinformatics-based drug repositioning approach toward accelerated evaluation of FDA-approved drugs for cancer treatment. From the day we started this project, it took less than 20 months to initiate a clinical trial," said Julien Sage, associate professor of pediatrics and genetics at Stanford University School of Medicine in California. "This is a good example of how we can combine 'big data' and the mature field of preclinical animal models to rapidly find new uses for old drugs.
"Unlike most targeted therapies, which are often specific for a single molecule or pathway, the drugs we identified target multiple receptors at the surface of neuroendocrine cancer cells, which may make it difficult for cancer cells to develop resistance," he added. "We are in the process of identifying the optimal treatment regimen for patients with SCLC and modifying these drugs to prevent them from entering the brain, in order to minimize side effects."
SCLC is a deadly subtype of lung cancer of neuroendocrine origin, and patients diagnosed with SCLC have a dismal prognosis. There is currently no approved targeted therapy for this disease and no new drugs have been identified in the last few decades.
Sage and colleagues focused their search on drugs targeting the two top pathways identified using a bioinformatics approach: the neuroactive ligand receptor interaction pathway and the calcium signaling pathway. Of the six antidepressants initially shortlisted, imipramine and promethazine emerged as successful candidates for further study based on the results of experiments using SCLC cell lines and mice bearing human SCLC tumors.
The researchers then generated mutant mice bearing cisplatin-resistant SCLC tumors and found that the growth of chemotherapy-resistant tumors were inhibited by imipramine, suggesting that the identified antidepressants will be effective against SCLCs in patients who developed resistance to standard chemotherapy.
They conducted further experiments and found these two drugs acted on SCLCs primarily by inducing cell death mechanisms within the cancer cells. They also found that SCLC cells express certain receptors called GPCRs, and imipramine and promethazine caused cell death by engaging these receptors and their downstream signaling mechanisms.
Because imipramine was also effective in an animal model of pancreatic neuroendocrine tumors, the researchers are hoping their observations with SCLC can be extended to a number of other neuroendocrine cancers.
Based on their preclinical results, the researchers have initiated a phase 2a clinical trial to test desipramine, a drug similar to imipramine, in SCLC and other high-grade neuroendocrine tumors.
- N. S. Jahchan, J. T. Dudley, P. K. Mazur, N. Flores, D. Yang, A. Palmerton, A.-F. Zmoos, D. Vaka, K. Q. T. Tran, M. Zhou, K. Krasinska, J. W. Riess, J. W. Neal, P. Khatri, K. S. Park, A. J. Butte, J. Sage. A Drug Repositioning Approach Identifies Tricyclic Antidepressants as Inhibitors of Small Cell Lung Cancer and Other Neuroendocrine Tumors. Cancer Discovery, 2013; DOI: 10.1158/2159-8290.CD-13-0183
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