Mark Zafereo, Hu Hei, Shaohua Peng, Anastasios Maniakas, Michelle D. Williams, Steve Scherer, Abdallah S.R. Mohamed, Clifford Stephan, David A. Wheeler, Faye M. Johnson, Diana Bell, Gary L. Clayman, Jennifer Wang, Stephen Y. Lai, Maria E. Cabanillas, and Ying C. Henderson
Background Anaplastic thyroid cancer (ATC) is a rare, aggressive, and deadly disease. Robust pre-clinical models are needed to adequately develop and study novel therapeutic agents. Patient-derived xenograft (PDX) models are thought to closely resemble patient tumors by preserving the tumor microenvironment, making them excellent pre-clinical models for drug response evaluation. We used two distinct ATC PDX models and evaluated drug response following a high-throughput screening (HTS). Methods A HTS, using NCI's Approved Oncology Set V (n=112) and a custom collection of agents (n=145), was conducted on patient-derived thyroid cancer cell lines. To identify the most effective drugs, we selected individual agents with maximal growth inhibition at each dose level relative to wells examined on the day of treatment (top 25th percentile) and subsequently used non-parametric statistics to compare effect size with other drugs and controls. This allowed us to identify classes of systemic agents which demonstrated preferential effectiveness against ATC cell lines and certain mutations. Following our prior successful work on orthotopic xenograft models, we used two established ATC PDX models, HOSC68 and HOSC199, harboring distinct genetic profiles and expanded each of them into 50 athymic mice. HOSC68 has a BRAFV600E and a TP53 mutation, while HOSC199 is wild-type for both genes, but has an HRAS mutation. Equal pieces of 4 × 4mm of tumor were transplanted subcutaneously at the level of the right flank. Following tumor growth, the mice were separated into four treatment arms. All mice received their treatment intraperitoneally following standard drug administration schedules. Tumor volume was measured on the first day of treatment and every two to three days thereafter until trial completion (14 days). Drug response was analyzed by evaluating percent tumor growth inhibition (TGI). Mouse weight was recorded over time to evaluate treatment toxicity. Following treatment completion, tumors were surgically retrieved and evaluated morphologically and histologically. Results Microtubule inhibitors, antimetabolites, and HDAC inhibitors were some of the most effective drug classes identified against ATC cell lines. Specifically, in this study, mice were treated with control (CTR), Docetaxel (DOC)-microtubule inhibitor, Pralatrexate (PRA)-antimetabolite, and LBH-589 (LBH)-HDAC inhibitor. Forty-four HOSC68 and 43 HOSC199 mice successfully grew tumor and were included in the trial. Compared to CTR, HOSC68 mice treated with DOC showed a 37% TGI (p=0.04), 88% with PRA (p<0.001), and 83% with LBH (p<0.001), while HOSC199 mice had a 2% TGI with DOC (p=0.56), 76% with PRA (p=0.005), and 83% with LBH (p=0.002). PRA and LBH were significantly more toxic than DOC and CTR (p<0.001) in HOSC68 mice, while all three drugs were significantly more toxic than CTR in the HOSC199 mice (p<0.001). Conclusion We report the first large-scale evaluation of drugs identified through a HTS analysis on ATC PDX models. This trial demonstrates the feasibility of using this platform for in vivo drug testing, while providing an avenue for future drug testing and resistance evaluation, as well as personalized therapeutics development. Citation Format: Anastasios Maniakas, Abdallah S. Mohamed, Ying C. Henderson, Hu Hei, Shaohua Peng, Diana Bell, Michelle D. Williams, Steve Scherer, David A. Wheeler, Gary L. Clayman, Mark Zafereo, Jennifer R. Wang, Maria E. Cabanillas, Clifford Stephan, Faye M. Johnson, Stephen Y. Lai. In vivo drug response evaluation in anaplastic thyroid cancer patient-derived tumor xenografts following high-throughput screening [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1662.