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Culture of Bladder Cancer Organoids as Precision Medicine Tools
Published on: December 28, 2021
Systems Drug Design for Muscle Invasive Bladder Cancer and Advanced Bladder Cancer by Genome-Wide Microarray Data and
1Laboratory of Automatic Control, Signal Processing and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan.
Abstract:
Bladder cancer is the 10th most common cancer worldwide. Due to the lack of understanding of the oncogenic mechanisms between muscle-invasive bladder cancer (MIBC) and advanced bladder cancer (ABC) and the limitations of current treatments, novel therapeutic approaches are urgently needed. In this study, we utilized the systems biology method via genome-wide microarray data to explore the oncogenic mechanisms of MIBC and ABC to identify their respective drug targets for systems drug discovery. First, we constructed the candidate genome-wide genetic and epigenetic networks (GWGEN) through big data mining. Second, we applied the system identification and system order detection method to delete false positives in candidate GWGENs to obtain the real GWGENs of MIBC and ABC from their genome-wide microarray data. Third, we extracted the core GWGENs from the real GWGENs by selecting the significant proteins, genes and epigenetics via the principal network projection (PNP) method. Finally, we obtained the core signaling pathways from the corresponding core GWGEN through the annotations of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway to investigate the carcinogenic mechanisms of MIBC and ABC. Based on the carcinogenic mechanisms, we selected the significant drug targets NFKB1, LEF1 and MYC for MIBC, and LEF1, MYC, NOTCH1 and FOXO1 for ABC. To design molecular drug combinations for MIBC and ABC, we employed a deep neural network (DNN)-based drug-target interaction (DTI) model with drug specifications. The DNN-based DTI model was trained by drug-target interaction databases to predict the candidate drugs for MIBC and ABC, respectively. Subsequently, the drug design specifications based on regulation ability, sensitivity and toxicity were employed as filter criteria for screening the potential drug combinations of Embelin and Obatoclax for MIBC, and Obatoclax, Entinostat and Imiquimod for ABC from their candidate drugs. In conclusion, we not only investigated the oncogenic mechanisms of MIBC and ABC, but also provided promising therapeutic options for MIBC and ABC, respectively.
Insights
This study reveals bladder cancer
Area of Science:
- Oncology
- Systems Biology
- Bioinformatics
Background:
- Bladder cancer is a significant global health concern, ranking as the 10th most common cancer.
- Current treatment limitations and a poor understanding of oncogenic mechanisms in muscle-invasive bladder cancer (MIBC) and advanced bladder cancer (ABC) necessitate novel therapeutic strategies.
Purpose of the Study:
- To elucidate the oncogenic mechanisms driving MIBC and ABC using systems biology approaches.
- To identify novel drug targets and design effective molecular drug combinations for MIBC and ABC.
Main Methods:
- Genome-wide microarray data analysis to construct and refine genome-wide genetic and epigenetic networks (GWGENs).
- Principal Network Projection (PNP) method to extract core GWGENs and identify significant proteins, genes, and epigenetic factors.
- Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to investigate carcinogenic mechanisms.
- Deep Neural Network (DNN)-based drug-target interaction (DTI) model for predicting candidate drugs and designing drug combinations based on regulation ability, sensitivity, and toxicity.
Main Results:
- Identified key oncogenic mechanisms and significant drug targets for MIBC (NFKB1, LEF1, MYC) and ABC (LEF1, MYC, NOTCH1, FOXO1).
- Predicted potential drug combinations for MIBC (Embelin and Obatoclax) and ABC (Obatoclax, Entinostat, and Imiquimod) using a DNN-based DTI model and specific drug design criteria.
Conclusions:
- The study provides a comprehensive investigation into the molecular underpinnings of MIBC and ABC.
- Novel therapeutic strategies and drug combinations are proposed, offering promising avenues for treating advanced bladder cancer.

