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.

Highlights

  • One goal of biomedical research is to better understand human diseases such as cancer by studying gene patterns associated with diseases and using them to find the best potential treatments

  • Because the Connectivity Map (CMAP) database contains profiles from a large collection of human cancer cell lines containing information on how cells respond to chemical stimulations, it can be used to test the hypothesis that the apoptosis pathway might be a major responsive program to drug perturbations in cancer cells

  • These results indicate that the variability of transcriptional profile for the same type of cell (MCF7 in this study) due to drug heterogeneity is much smaller than that caused by different chemical stimulations

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Summary

Introduction

One goal of biomedical research is to better understand human diseases such as cancer by studying gene patterns associated with diseases and using them to find the best potential treatments. Because the CMAP database contains profiles from a large collection of human cancer cell lines containing information on how cells respond to chemical stimulations, it can be used to test the hypothesis that the apoptosis pathway might be a major responsive program to drug perturbations in cancer cells. One can do this by enrichment analysis of apoptotic genes in drug-responsive genes or in differentially expressed genes in drug-exposed cancer cells [5,6,7,8,9,10]. We used CMAP gene expression profiles to test the hypothesis that

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