Integration of Cancer Gene Co-expression Network and Metabolic Network To Uncover Potential Cancer Drug Targets

Abstract

Cell metabolism is critical for cancer cell transformation and progression. In this study, we have developed a novel method, named Met-express, that integrates a cancer gene co-expression network with the metabolic network to predict key enzyme-coding genes and metabolites in cancer cell metabolism. Met-express successfully identified a group of key enzyme-coding genes and metabolites in lung, leukemia, and breast cancers. Literature reviews suggest that approximately 33-53% of the predicted genes are either known or suggested anti-cancer drug targets, while 22% of the predicted metabolites are known or high-potential drug compounds in therapeutic use. Furthermore, experimental validations prove that 90% of the selected genes and 70% of metabolites demonstrate the significant anti-cancer phenotypes in cancer cells, implying that they may play important roles in cancer metabolism. Therefore, Met-express is a powerful tool for uncovering novel therapeutic biomarkers.

Prediction of Metabolic Gene Biomarkers for Neurodegenerative Disease by an Integrated Network-Based Approach

“…Met-express is a published method originally applied to cancer expression data. It has been successfully used to predict key enzyme-coding genes as potential candidates for therapeutic uses [ 14 ]. As in Figure 1 , it integrated disease specific gene coexpression network and the metabolic network, to identify those enzyme-coding genes that have a potential to influence downstream genes and thus may play an important role in the disease-related pathways.…”

“…As two files of PD were from the same samples and tested on similar microarrays, we combined the two files to one file to extend the data size (Supplementary Table 1in Supplementary Material available online at http://dx.doi.org/10.1155/2015/432012 ). For each GDS file, we selected only genes with a median ratio of null values less than 80% and used R ( http://www.r-project.org/ ) to normalize gene expression values as previously described [ 14 ].…”

“…We followed the procedures as Chen et al described [ 14 ] to detect the key enzyme-coding genes of PD and HD. Here, we briefly describe the workflow of Met-express.…”

“…Detection of enzyme-coding genes that are significantly differentially expressed and that may drive the metabolic changes in ND patients may therefore help understand the mechanisms of ND development. In a previous study, we have developed a computational method named Met-express that integrated cancer gene coexpression network and metabolic network to predict key enzyme-coding genes in cancer development [ 14 ]. In Met-express, a coexpression network of cancer gene was first constructed, from which cancer-specific gene coexpression modules were determined.…”

Integrating <b><i>Omics</i></b> Technologies to Study Pulmonary Physiology and Pathology at the Systems Level

“…Potential cancer drug targets have also been identified by integrating cancer gene co-expression network and metabolic networks [205]. Thus, users can integrate “omic” profiles to better understand pulmonary disorders by combining genomic, proteomic and metabolic signatures.…”