title: The role of master regulators in the metabolic/transcriptional coupling in breast carcinomas.
abstract: Metabolic transformations have been reported as involved in neoplasms survival. This suggests a role of metabolic pathways as potential cancer pharmacological targets. Modulating tumor's energy production pathways may become a substantial research area for cancer treatment. The significant role of metabolic deregulation as inducing transcriptional instabilities and consequently whole-system failure, is thus of foremost importance. By using a data integration approach that combines experimental evidence for high-throughput genome wide gene expression, a non-equilibrium thermodynamics analysis, nonlinear correlation networks as well as database mining, we were able to outline the role that transcription factors MEF2C and MNDA may have as main master regulators in primary breast cancer phenomenology, as well as the possible interrelationship between malignancy and metabolic dysfunction. The present findings are supported by the analysis of 1191 whole genome gene expression experiments, as well as probabilistic inference of gene regulatory networks, and non-equilibrium thermodynamics of such data. Other evidence sources include pathway enrichment and gene set enrichment analyses, as well as motif comparison with a comprehensive gene regulatory network (of homologue genes) in Arabidopsis thaliana. Our key finding is that the non-equilibrium free energies provide a realistic description of transcription factor activation that when supplemented with gene regulatory networks made us able to find deregulated pathways. These analyses also suggest a novel potential role of transcription factor energetics at the onset of primary tumor development. Results are important in the molecular systems biology of cancer field, since deregulation and coupling mechanisms between metabolic activity and transcriptional regulation can be better understood by taking into account the way that master regulators respond to physicochemical constraints imposed by different phenotypic conditions.
authors.affiliation: Computational Genomics Department, National Institute of Genomic Medicine, México City, México.
authors.forename: Karol
authors.initials: K
authors.lastname: Baca-López
authors.forename: Miguel
authors.initials: M
authors.lastname: Mayorga
authors.forename: Alfredo
authors.initials: A
authors.lastname: Hidalgo-Miranda
authors.forename: Nora
authors.initials: N
authors.lastname: Gutiérrez-Nájera
authors.forename: Enrique
authors.initials: E
authors.lastname: Hernández-Lemus
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000378:metabolism*; D002277:Carcinoma / Q000378:metabolism*; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D015894:Genome, Human; D023281:Genomics; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis; D010641:Phenotype; D013816:Thermodynamics; D014158:Transcription, Genetic