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Recovering drug-induced apoptosis subnetwork from Connectivity Map data
Jiyang Yu1, Preeti Putcha2, Jose M Silva3
1Department of Precision Medicine, Oncology Research Unit, Pfizer Inc., Pearl River, NY 10965, USA.
Abstract:
The Connectivity Map (CMAP) project profiled human cancer cell lines exposed to a library of anticancer compounds with the goal of connecting cancer with underlying genes and potential treatments. Since the therapeutic goal of most anticancer drugs is to induce tumor-selective apoptosis, it is critical to understand the specific cell death pathways triggered by drugs. This can help to better understand the mechanism of how cancer cells respond to chemical stimulations and improve the treatment of human tumors. In this study, using CMAP microarray data from breast cancer cell line MCF7, we applied a Gaussian Bayesian network modeling approach and identified apoptosis as a major drug-induced cellular-pathway. We then focused on 13 apoptotic genes that showed significant differential expression across all drug-perturbed samples to reconstruct the apoptosis network. In our predicted subnetwork, 9 out of 15 high-confidence interactions were validated in the literature, and our inferred network captured two major cell death pathways by identifying BCL2L11 and PMAIP1 as key interacting players for the intrinsic apoptosis pathway and TAXBP1 and TNFAIP3 for the extrinsic apoptosis pathway. Our inferred apoptosis network also suggested the role of BCL2L11 and TNFAIP3 as "gateway" genes in the drug-induced intrinsic and extrinsic apoptosis pathways.
Insights
This study used Gaussian Bayesian networks to analyze breast cancer cell data, identifying apoptosis as a key drug-induced pathway. The research reconstructed the apoptosis network, revealing critical genes for intrinsic and extrinsic cell death pathways.
Area of Science:
- Computational Biology
- Cancer Research
- Systems Biology
Background:
- The Connectivity Map (CMAP) project aims to link anticancer compounds to genes and treatments.
- Understanding drug-induced apoptosis is crucial for cancer therapy and tumor treatment.
- Apoptosis pathways are central to the efficacy of many anticancer drugs.
Purpose of the Study:
- To identify drug-induced cellular pathways in breast cancer using CMAP data.
- To reconstruct the apoptosis network and identify key genes involved in drug response.
- To elucidate the roles of specific genes in intrinsic and extrinsic apoptosis pathways.
Main Methods:
- Applied Gaussian Bayesian network modeling to CMAP microarray data from MCF7 breast cancer cells.
- Focused on 13 differentially expressed apoptotic genes across drug-perturbed samples.
- Validated inferred network interactions against existing literature.
Main Results:
- Identified apoptosis as a major drug-induced cellular pathway.
- Reconstructed a high-confidence apoptosis subnetwork with 9 validated interactions.
- Identified BCL2L11 and PMAIP1 as key players in the intrinsic pathway, and TAXBP1 and TNFAIP3 in the extrinsic pathway.
- Highlighted BCL2L11 and TNFAIP3 as potential "gateway" genes in drug-induced apoptosis.
Conclusions:
- Gaussian Bayesian networks can effectively model drug-induced cellular pathways.
- The inferred apoptosis network provides insights into cancer cell response to chemical stimuli.
- The study identifies critical genes for intrinsic and extrinsic apoptosis, aiding in understanding cancer treatment mechanisms.
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