Hepatocellular Carcinoma (HCC) is the third leading cause of cancer-related death globally, with roughly 700,000 cases diagnosed worldwide in 2012 alone. Treatment with the standard care agent sorafenib only modestly improves overall survival by an average of 3-months. Therefore, there is a huge unmet clinical need to identify new effective therapies for HCC patients. Drug repurposing is one shortcut to give HCC patients more options. One drug repurposing method makes prediction based on the reversal relation of gene expression between diseases and drugs. It has led to a number of drug candidates successfully validated in preclinical models. The recent NIH-funded projects The Cancer Genome Atlas (TCGA), and Library of Integrated Network-Based Cellular Signatures (LINCS) have dramatically increased the number of expression profiles of diseases and drugs, providing new exciting drug repurposing opportunities. By use the data from TCGA and LINCS, we identified four candidates (niclosamide, pyrvinium pamoate, mebendazole, and miglitol) that could significantly reverse HCC gene expression and are novel to HCC. Interestingly, these candidates are reported to target glucose metabolism. Therefore, the objective of this proposal is to leverage our capabilities to evaluate the four candidates based on the criteria proposed by this RFA. Our central hypothesis is that a drug that reverses the HCC gene expression signature and targets glucose metabolism could be a novel therapeutic in HCC. To validate our hypothesis, we propose two aims:(1) Select Drug X from four drug candidates based on their efficacy, specificity, potency to reverse disease gene expression, and the effect on glucose metabolism in vitro (2) Evaluate in vivo anti-tumor efficacy of Drug X in PDX models and primary mouse models. Our methodology can be extended to the evaluation of other top predicted candidates, and be applied to the study of other types of cancers
Hepatocellular Carcinoma is the third leading cause of cancer-related death globally, and its effective treatment is still limited. We plan to leverage the recent public molecular datasets to predict drugs for Hepatocellular Carcinoma and evaluate them using rigorous preclinical models.
| Zhang, Shanshan; Wang, Jingxiao; Wang, Haichuan et al. (2018) Hippo Cascade Controls Lineage Commitment of Liver Tumors in Mice and Humans. Am J Pathol 188:995-1006 |
