NFκB pathway analysis: An approach to analyze gene co-expression networks employing feedback cycles. (February 2018)

• Record Type: Journal Article
• Authors: Dillenburg, Fabiane Cristine; Zanotto-Filho, Alfeu; Fonseca Moreira, José Cláudio; Ribeiro, Leila; Carro, Luigi
• Is Part Of: Computational biology and chemistry. Volume 72(2018)
• Page Start: 62
• Page End: 76
• Publication Date: 2018-02
• Subjects: NFκB -- Microarray data analysis -- Gene co-expression networks -- Cycles -- Feedback mechanisms -- Gliobastoma multiforme; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2017.08.012
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: An analysis based on cycles among genes of gene co-expression networks is proposed. Cycles are associated with feedback mechanisms, very common in biological networks. NF κ B pathway analysis in tumor specimens of GBM compared to normal brain tissues. GBM patients carry aberrant NF κ B activation. Stoichiometric relationship of NF κ B pathway genes is unbalanced in GBM samples. Abstract: The genes of the NF κ B pathway are involved in the control of a plethora of biological processes ranking from inhibition of apoptosis to metastasis in cancer. It has been described that Gliobastoma multiforme (GBM) patients carry aberrant NF κ B activation, but the molecular mechanisms are not completely understood. Here, we present a NF κ B pathway analysis in tumor specimens of GBM compared to non-neoplasic brain tissues, based on the different kind of cycles found among genes of a gene co-expression network constructed using quantized data obtained from the microarrays. A cycle is a closed walk with all vertices distinct (except the first and last). Thanks to this way of finding relations among genes, a more robust interpretation of gene correlations is possible, because the cycles are associated with feedback mechanisms that are very common in biological networks. In GBM samples, we could conclude that the stoichiometric relationship between genes involved in NF κ B pathway regulation is unbalanced. This can be measured and explained by the identification of a cycle. This conclusion helps to understand more about the biology of this type of tumor.