Out with the New, In with the Old

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Science Translational Medicine  30 Oct 2013:
Vol. 5, Issue 209, pp. 209ec179
DOI: 10.1126/scitranslmed.3007775

Many people wax nostalgic about the 1950s. Cancer researchers may now wish to join their ranks. Jahchan and colleagues use 21st-century computational biology techniques to reveal that tricyclic antidepressants—first discovered in the 1950s—have predicted efficacy against small-cell lung carcinoma (SCLC).

In the treatment of metastatic cancer, small-molecule–based approaches to targeting oncogenic signaling cascades in cancer have had some modest successes. Still, the lengthy and expensive path to regulatory approval of such a drug is fraught with failure, which can occur at any stage of translation. Thus, the repurposing of already approved drugs with their well-characterized side effects and voluminous toxicology data has attracted current drug-development efforts. Repurposed drugs can have a much-accelerated path to approval for a new indication, aided in part by a lower barrier—relative to new drugs—for inclusion in clinical trials for advanced cancer. In addition, successful trial results provide the molecular and conceptual framework for further rational drug design around the parent structure so as to maximize on-target efficacy while minimizing potential dose-limiting toxicities.

Using a high-throughput assay and computational biology techniques, Jahchan and colleagues assessed gene-expression profiles in a variety of cell types across multiple diseases before and after individual treatment with a library of U.S. Food and Drug Administration–approved drugs. The process generated a computed list of candidate drugs with predicted efficacy against SCLC. Some of the top “hits” from the screen were tricyclic antidepressants. Efficacy against SCLC was subsequently validated in both cell culture and in vivo models of SCLC. Specifically, these drugs induced caspase-dependent apoptosis in lung cancer cell lines and significant tumor growth inhibition (TGI) in vivo (both in transgenic and xenograft models of the disease) through modulation of G protein–coupled receptor (GPCR) signaling. On the basis of the postulated mechanisms of action, the authors tested the drugs on neuroendocrine tumors that express high levels of GPCRs and demonstrated significant tumor growth inhibition and improved survival in a mouse model of pancreatic neuroendocrine cancer. The new work illustrates the power of modern bioinformatics-based drug discovery approaches to unearth new uses for old drugs as therapies for currently untreatable diseases.

N. S. Jahchan et al., A drug repositioning approach identifies tricyclic antidepressants as inhibitors of small cell lung cancer and other neuroendocrine tumors. Cancer Discov., published online September 2013 (10.1158/2159-8290.CD-13-0183). [Abstract]

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