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Recovering drug-induced apoptosis subnetwork from Connectivity Map data.

Yu J, Putcha P, Silva JM - Biomed Res Int (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department 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.

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Heat map of top differentially expressed genes (FDR < 0.05) in drug-perturbed and control samples. The genes are ranked from most upregulated (labeled in dark red on right panel) to most downregulated (labeled in dark green) in drug-perturbed samples, and the 13 selected apoptotic genes are labeled on the right with their ranks in the list.
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fig3: Heat map of top differentially expressed genes (FDR < 0.05) in drug-perturbed and control samples. The genes are ranked from most upregulated (labeled in dark red on right panel) to most downregulated (labeled in dark green) in drug-perturbed samples, and the 13 selected apoptotic genes are labeled on the right with their ranks in the list.

Mentions: Our framework may be improved in a few ways. First, we only considered the general effects of drugs based on the assumption that cancer cells have a similar response mechanism to different drugs. However this assumption may be overgeneralized, since there are some drugs to which the cells have no response. This can be clearly seen in Figure 3, which contains a heat map of signature genes across all drugs. One way to deal with this limitation may be to cluster drugs by their expression profiles or by their physical or chemical properties. A similar comparison analysis may be performed but would take into account the effects of different drug groups. Second, to reduce computational complexity, we limited our analysis to apoptotic genes that were differentially expressed with a Bonferroni-corrected P value threshold of 0.05. This threshold might have been overly stringent and may have caused us to filter informative genes from the analysis. One way to deal with this problem might be to include more candidate genes, but this would increase complexity and computation.


Recovering drug-induced apoptosis subnetwork from Connectivity Map data.

Yu J, Putcha P, Silva JM - Biomed Res Int (2015)

Heat map of top differentially expressed genes (FDR < 0.05) in drug-perturbed and control samples. The genes are ranked from most upregulated (labeled in dark red on right panel) to most downregulated (labeled in dark green) in drug-perturbed samples, and the 13 selected apoptotic genes are labeled on the right with their ranks in the list.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4389823&req=5

fig3: Heat map of top differentially expressed genes (FDR < 0.05) in drug-perturbed and control samples. The genes are ranked from most upregulated (labeled in dark red on right panel) to most downregulated (labeled in dark green) in drug-perturbed samples, and the 13 selected apoptotic genes are labeled on the right with their ranks in the list.
Mentions: Our framework may be improved in a few ways. First, we only considered the general effects of drugs based on the assumption that cancer cells have a similar response mechanism to different drugs. However this assumption may be overgeneralized, since there are some drugs to which the cells have no response. This can be clearly seen in Figure 3, which contains a heat map of signature genes across all drugs. One way to deal with this limitation may be to cluster drugs by their expression profiles or by their physical or chemical properties. A similar comparison analysis may be performed but would take into account the effects of different drug groups. Second, to reduce computational complexity, we limited our analysis to apoptotic genes that were differentially expressed with a Bonferroni-corrected P value threshold of 0.05. This threshold might have been overly stringent and may have caused us to filter informative genes from the analysis. One way to deal with this problem might be to include more candidate genes, but this would increase complexity and computation.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department 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.

Show MeSH
Related in: MedlinePlus