A bioinformatics（生物信息学） 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（镇静剂）, antiemetic（止吐剂）, 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（神经内分泌的） 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."