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Systems approach to identify environmental exposures contributing to organ-specific carcinogenesis.


ABSTRACT: The most effective way to reduce cancer burden is Q2 prevention which is dependent on identifying individuals at risk for a particular cancer and counseling them to avoid exposure to causative agents. Other than a few well characterized environmental agents linked to specific cancers, linkage between any particular environmental exposure and a specific type of cancer is mostly unknown. Thus, we propose a systems approach to analyze publicly available large datasets to identify candidate agents that play a role in organ-specific carcinogenesis.Publicly available datasets for mRNA and miRNA expression in ovarian cancer were queried to define the differentially expressed genes that are also targets of differentially expressed miRNAs. These target genes were then used to query the Comparative Toxicogenomics Database to identify interacting chemicals and also were analyzed by Ingenuity Pathway Analysis to identify pathways.The interacting chemicals interact with genes in known pathways in ovarian carcinogenesis and support the hypothesis that these chemicals are likely etiologic agents in ovarian carcinogenesis.A systems approach may prove useful to identify specific etiologic agents to better develop personalized preventive medicine strategies for those most at risk.

SUBMITTER: States JC 

PROVIDER: S-EPMC4035223 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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Systems approach to identify environmental exposures contributing to organ-specific carcinogenesis.

States J Christopher JC   Ouyang Ming M   Helm C William CW  

Cancer epidemiology 20140412 3


<h4>Background</h4>The most effective way to reduce cancer burden is Q2 prevention which is dependent on identifying individuals at risk for a particular cancer and counseling them to avoid exposure to causative agents. Other than a few well characterized environmental agents linked to specific cancers, linkage between any particular environmental exposure and a specific type of cancer is mostly unknown. Thus, we propose a systems approach to analyze publicly available large datasets to identify  ...[more]

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