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Published on: December 26, 2016
Computational Modeling to Identify Drugs Targeting Metastatic Castration-Resistant Prostate Cancer Characterized by
Mei-Chi Su1, Adam M Lee1, Weijie Zhang2
1Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN 55455, USA.
Abstract:
Metastatic castration-resistant prostate cancer (mCRPC) remains a deadly disease due to a lack of efficacious treatments. The reprogramming of cancer metabolism toward elevated glycolysis is a hallmark of mCRPC. Our goal is to identify therapeutics specifically associated with high glycolysis. Here, we established a computational framework to identify new pharmacological agents for mCRPC with heightened glycolysis activity under a tumor microenvironment, followed by in vitro validation. First, using our established computational tool, OncoPredict, we imputed the likelihood of drug responses to approximately 1900 agents in each mCRPC tumor from two large clinical patient cohorts. We selected drugs with predicted sensitivity highly correlated with glycolysis scores. In total, 77 drugs predicted to be more sensitive in high glycolysis mCRPC tumors were identified. These drugs represent diverse mechanisms of action. Three of the candidates, ivermectin, CNF2024, and P276-00, were selected for subsequent vitro validation based on the highest measured drug responses associated with glycolysis/OXPHOS in pan-cancer cell lines. By decreasing the input glucose level in culture media to mimic the mCRPC tumor microenvironments, we induced a high-glycolysis condition in PC3 cells and validated the projected higher sensitivity of all three drugs under this condition (p < 0.0001 for all drugs). For biomarker discovery, ivermectin and P276-00 were predicted to be more sensitive to mCRPC tumors with low androgen receptor activities and high glycolysis activities (AR(low)Gly(high)). In addition, we integrated a protein-protein interaction network and topological methods to identify biomarkers for these drug candidates. EEF1B2 and CCNA2 were identified as key biomarkers for ivermectin and CNF2024, respectively, through multiple independent biomarker nomination pipelines. In conclusion, this study offers new efficacious therapeutics beyond traditional androgen-deprivation therapies by precisely targeting mCRPC with high glycolysis.
Insights
Researchers identified new drugs targeting high glycolysis in metastatic castration-resistant prostate cancer (mCRPC). This approach offers novel treatments beyond standard therapies for mCRPC patients with specific metabolic profiles.
Area of Science:
- Oncology
- Cancer Metabolism
- Pharmacology
Background:
- Metastatic castration-resistant prostate cancer (mCRPC) poses a significant therapeutic challenge due to limited effective treatments.
- Elevated glycolysis, a metabolic shift, is a recognized hallmark of mCRPC, suggesting it as a potential therapeutic target.
- Existing treatments for mCRPC often lack efficacy, necessitating the exploration of novel therapeutic strategies.
Purpose of the Study:
- To identify novel pharmacological agents that specifically target mCRPC characterized by high glycolysis.
- To establish a computational framework for predicting drug sensitivity in mCRPC based on metabolic profiles.
- To validate potential drug candidates through in vitro experiments simulating the tumor microenvironment.
Main Methods:
- Utilized the OncoPredict computational tool to impute drug responses for approximately 1900 agents across two mCRPC patient cohorts.
- Selected drugs with predicted sensitivity strongly correlated with high glycolysis scores in mCRPC tumors.
- Performed in vitro validation of selected drug candidates (ivermectin, CNF2024, P276-00) in PC3 cells under simulated low-glucose conditions.
Main Results:
- Identified 77 drugs predicted to be more sensitive in high glycolysis mCRPC tumors, representing diverse mechanisms of action.
- In vitro validation confirmed higher sensitivity to ivermectin, CNF2024, and P276-00 under simulated mCRPC tumor microenvironment conditions (p < 0.0001).
- Identified potential biomarkers (EEF1B2 for ivermectin, CCNA2 for CNF2024) associated with drug sensitivity in specific mCRPC subtypes.
Conclusions:
- This study provides a novel therapeutic strategy by targeting high glycolysis in mCRPC.
- Identified ivermectin, CNF2024, and P276-00 as promising candidates for treating mCRPC with high glycolytic activity.
- The findings offer potential new treatments beyond androgen-deprivation therapies for specific mCRPC patient populations.
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