The objective of this paper is to identify the underlying pathways that regulate the cytotoxicity induced by free fatty acids (FFA) and tumor necrosis factor (TNF)-a in human hepatoblastoma cells (HepG2/C3A). Gene expression profiles of HepG2/C3A cells were measured after 24, 48, and 72 hours of exposure to FFA and TNF-a. Saturated fatty acid (palmitate) was found to be cytotoxic and TNF-a exacerbated this effect. To identify the underlying pathways, module map analysis [1] was used to identify the important genes and dynamic Bayesian network analysis was applied to reconstruct the pathways from those genes. 522 biologically meaningful gene sets were first defined based upon their functional category or pathway, as defined by the MsigDB database [2]. The functional gene modules were extracted from the 522 gene sets based upon the expression profile with Genomica. This was accomplished by separating the gene sets into clusters and identifying the genes with similar profiles in the cluster and placing them in a functional module [1]. The functional modules reflect the specific biological process captured by the genes in the module. The cytotoxic and nontoxic phenotypes were characterized by the modules that were found activated or deactivated for each phenotype. This methodology was used to formulate a module map to characterize the relation between the modules and treatments. The module maps at different time points were compared to identify the dynamics of the modules that are important to the cytotoxic phenotype. The profiles of the genes in the modules identified to be involved in activating/inducing cytotoxicity along with the profile of the phenotype were used for network reconstruction to identify potential targets that can be perturbed to modulate the cytotoxicity. Some of the targets identified to be important to palmitate induced cytotoxcity were experimentally validated.

Reference: 1. Segal E. et al. (2004) A module map showing conditional activity of expression modules in caner, Nature Genetics, 36 (10):1090-1098. 2. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP. “Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles” Proc Natl Acad Sci U S A. 2005, 102(43):15545-50.

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