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A Drug Repositioning Approach Identifies Tricyclic Antidepressants As Inhibitors of Small Cell Lung Cancer and Other Neuroendocrine Tumors

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A Drug Repositioning Approach Identifies Tricyclic Antidepressants As Inhibitors of Small Cell Lung Cancer and Other Neuroendocrine Tumors Published OnlineFirst September 26, 2013; DOI: 10.1158/2159-8290.CD-13-0183 RESEARCH ARTICLE A Drug Repositioning Approach Identifi es Tricyclic Antidepressants as Inhibitors of Small Cell Lung Cancer and Other Neuroendocrine Tumors Nadine S. Jahchan 1 , 2 , Joel T. Dudley 1 , Pawel K. Mazur 1 , 2 , Natasha Flores 1 , 2 , Dian Yang 1 , 2 , Alec Palmerton 1 , 2 , Anne-Flore Zmoos 1 , 2 , Dedeepya Vaka 1 , 2 , Kim Q.T. Tran 1 , 2 , Margaret Zhou 1 , 2 , Karolina Krasinska 3 , Jonathan W. Riess 4 , Joel W. Neal 5 , Purvesh Khatri 1 , 2 , Kwon S. Park 1 , 2 , Atul J. Butte 1 , 2 , and Julien Sage 1 , 2 Downloaded from cancerdiscovery.aacrjournals.org on September 29, 2021. © 2013 American Association for Cancer Research. Published OnlineFirst September 26, 2013; DOI: 10.1158/2159-8290.CD-13-0183 ABSTRACT Small cell lung cancer (SCLC) is an aggressive neuroendocrine subtype of lung cancer with high mortality. We used a systematic drug repositioning bioinformat- ics approach querying a large compendium of gene expression profi les to identify candidate U.S. Food and Drug Administration (FDA)–approved drugs to treat SCLC. We found that tricyclic antidepressants and related molecules potently induce apoptosis in both chemonaïve and chemoresistant SCLC cells in culture, in mouse and human SCLC tumors transplanted into immunocompromised mice, and in endog- enous tumors from a mouse model for human SCLC. The candidate drugs activate stress pathways and induce cell death in SCLC cells, at least in part by disrupting autocrine survival signals involving neurotransmitters and their G protein–coupled receptors. The candidate drugs inhibit the growth of other neuroendocrine tumors, including pancreatic neuroendocrine tumors and Merkel cell carcinoma. These experiments identify novel targeted strategies that can be rapidly evaluated in patients with neuroendocrine tumors through the repurposing of approved drugs. SIGNIFICANCE: Our work shows the power of bioinformatics-based drug approaches to rapidly repur- pose FDA-approved drugs and identifi es a novel class of molecules to treat patients with SCLC, a cancer for which no effective novel systemic treatments have been identifi ed in several decades. In addition, our experiments highlight the importance of novel autocrine mechanisms in promoting the growth of neuroendocrine tumor cells. Cancer Discov; 3(12); 1–14. ©2013 AACR. INTRODUCTION are still in their infancy, emerging evidence suggests that they enable the discovery of novel treatment options for a wide range The identifi cation of therapeutic approaches for the treat- of human diseases ( 2–6 ). ment of cancer is an arduous, costly, and often ineffi cient Lung cancer is the number-one cause of cancer-related process. Drug repositioning, which is the discovery of new indi- deaths in the world, with more than 1.3 million deaths annu- cations for existing drugs that are outside their original indica- ally. Lung cancer is divided into two major histopathologic tions, is an increasingly attractive mode of therapeutic discovery. groups: non–small cell lung cancer (NSCLC; ∼80%–85% of In addition to saving time and money, an advantage of drug cases) and small cell lung cancer (SCLC; ∼15%–20% of cases; repurposing strategies is the fact that existing drugs have already refs. 7, 8 ). SCLC is a very deadly subtype of lung cancer char- been vetted in terms of safety, dosage, and toxicity. Therefore, acterized by the rapid expansion and metastasis of small cells repurposed candidate drugs can often enter clinical trials much with neuroendocrine features. Patients are most commonly more rapidly than newly developed drugs ( 1 ). Recent advance- diagnosed with metastatic (extensive stage) disease. Without ments in computing, concomitant with the dramatic expansion treatment, they may survive only a few weeks to months after of available high-throughput datasets, have enabled the devel- the initial diagnosis, but systemic chemotherapy improves the opment of in silico approaches to drug discovery, including the median survival to approach a year. Still, cure is not possible incorporation of genomics-, network-, systems-, and signature- with currently used therapies, and there is no approved tar- based approaches. Although these computational approaches geted therapy for SCLC despite numerous attempts and clini- cal trials ( 9 ). In recent years, a substantial effort from many Authors’ Affi liations: Departments of 1 Pediatrics, 2 Genetics, and 5 Medicine- groups has been made to identify novel treatment options 3 Oncology, Vincent Coates Mass Spectrometry Laboratory, Stanford for SCLC. For instance, a proteomic profi ling approach has University, Stanford; and 4 Division of Hematology/Oncology, Department of Internal Medicine, University of California Davis Cancer Center, Univer- recently identifi ed PARP1 as a novel therapeutic target in sity of California Davis School of Medicine, Sacramento, California SCLC ( 10 ). However, it is essential to identify additional thera- Note: Supplementary data for this article are available at Cancer Discov- peutic strategies to block the growth of SCLC tumors. ery Online (http://cancerdiscovery.aacrjournals.org/). In this study, we sought to use a systematic drug- J.T. Dudley and P.K. Mazur contributed equally to this work. repositioning bioinformatics approach to identify novel U.S. Current address for J.T. Dudley: Department of Genetics and Genomic Sci- Food and Drug Administration (FDA)–approved candidate ences, Mount Sinai School of Medicine, New York, NY; current address for drugs to treat SCLC. Using this strategy, we identifi ed tri- P. Khatri, Department of Medicine-Biomedical Informatics Research, Stan- cyclic antidepressants (TCA) and related inhibitors of G ford University, Stanford, CA; current address for K.S. Park, Department of Microbiology, University of Virginia, Charlottesville, VA. protein–coupled receptors (GPCR) as potent inducers of cell Corresponding Authors: Julien Sage, Stanford University, 265 Campus death in SCLC cells and other neuroendocrine tumors. Drive, SIM1 G2078, Stanford, CA 94305-5457. Phone: 650-724-9246; Fax: 650-736-0195; E-mail: [email protected] ; and Atul J. Butte, Stanford RESULTS University, 251 Campus Drive West, MSOB X1C63, Stanford, CA 94305- 5479. Phone: 650-725-1337; Fax: 650-723-7070; [email protected] To identify novel therapeutic strategies for patients with SCLC, doi: 10.1158/2159-8290.CD-13-0183 we used a bioinformatics approach that evaluates the thera- © 2013 American Association for Cancer Research. peutic potential of FDA-approved drugs for a given disease by DECEMBER 2013CANCER DISCOVERY | OF2 Downloaded from cancerdiscovery.aacrjournals.org on September 29, 2021. © 2013 American Association for Cancer Research. Published OnlineFirst September 26, 2013; DOI: 10.1158/2159-8290.CD-13-0183 RESEARCH ARTICLE Jahchan et al. A D1 D2 D3 ...Dn N N + S Compute disease signature from Compute drug signature from SCLC-affected lung vs. healthy lung drug-treated vs. -untreated cell lines Compute drug activity score between drugs and disease (SCLC) +1 Pathways enriched in targets of top-scoring drugs e.g., imipramine, 1) “Neuroactive ligand promethazine receptor interactions” Drugs opposing SCLC e.g., bepridil 2) “Calcium signaling” Drug activity score Drugs synergizing with SCLC −1 5% FDR Targets of top-scoring drugs B Clomipramine Imipramine Promethazine ns ns ns 100 100 100 75 75 75 ns * * 50 50 50 ** *** *** *** *** *** 25 25 25 *** *** *** *** *** % Survival (MTT) *** % Survival (MTT) % Survival (MTT) *** *** 0 *** 0 0 2 H82 H69 Kp1 Kp2 Kp3 H82 H69 Kp1 Kp2 Kp3 H82 H69 Kp1 Kp Kp3 A549 H187 A549 H187 A549 H187 Tranylcypromine Pargyline Bepridil 200 ns ns 100 ns 100 ns *** ** * ns 150 ns 75 ns ns 75 ns * * ** 100 50 50 *** 50 *** 25 25 *** *** *** *** % Survival (MTT) % Survival (MTT) 0 0 % Survival (MTT) 0 p2 H82 H69 Kp1 Kp2 Kp3 H82 H69 Kp1 Kp2 Kp3 H82 H69 Kp1 K Kp3 A549 H187 A549 H187 A549 H187 C Imipramine Promethazine Bepridil ns ns ns ns 100 100 100 * 75 75 *** 75 ** *** ** ** 50 50 50 ** *** ** *** 25 *** 25 25 *** *** *** *** *** *** % Survival (MTT) *** *** % Survival (MTT) *** 0 % Survival (MTT) 0 0 2 9 2 8 87 p 87 H82 H69 Kp1 Kp2 Kp3 H H6 Kp1 K Kp3 H82 H69 Kp1 Kp2 Kp3 A549 H187 A549 H1 A549 H1 LKR13 LKR13 LKR13 Figure 1. A bioinformatics-based drug-repositioning approach identifi es candidate drugs to inhibit SCLC. A, schematic representation of the bioin- formatics workfl ow for the repositioning approach used to identify potential candidate drugs for the treatment of SCLC. B, representative MTT survival assays of cells cultured in 0.5% serum (n ≥ 3 independent experiments). A549 are NSCLC cells, H82, H69, and H187 are human SCLC cell lines, and Kp1, Kp2, and Kp3 are mouse SCLC cell lines. Cells were treated for 48 hours with 20 μmol/L clomipramine, 50 μmol/L imipramine, 30 μmol/L promethazine, 100 μmol/L tranylcypromine, 100 μmol/L pargyline, and 10 μmol/L bepridil. C, MTT survival assays of NSCLC (A549 and LKR13) and SCLC cells (H82, H69, H187, Kp1, Kp2, and Kp3) cultured in 2% serum ( n > 3 independent experiments) for 48 hours with 50 μmol/L imipramine, 30 μmol/L promethazine, and 10 μmol/L bepridil. Similar results were obtained in cells growing in dialyzed serum (data not shown). The black bars represent the vehicle-treated cells normalized to 100%. *, P < 0.05; **, P < 0.01; ***, P < 0.001. OF3 | CANCER DISCOVERYDECEMBER 2013 www.aacrjournals.org Downloaded from cancerdiscovery.aacrjournals.org on September 29, 2021. © 2013 American Association for Cancer
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