Preprints.org · 2019 · 19 citations · 39 references
Life SciencesGeneticsOncologyGene ExpressionGene RegulationTranscriptomicsCancer GenomicsCancer TranscriptomicsGene Expression ProfilingMolecular Tumor ProfilingPersonalized Cancer TherapyTranscriptomic ProfilingCell Phenotype CharacterizationCell Phenotype MaintenanceGene Expression ControlGene Expression CorrelationGene-targeted TherapyMicroarray AnalysisPersonalized Cancer TreatmentTumor Profiling
The dynamic and never exactly repeatable tumor transcriptomic profile of people affected by the same form of cancer requires a personalized and time-sensitive approach of the gene therapy. The Gene Master Regulators (GMRs) were defined as genes whose highly controlled expression by the homeostatic mechanisms commands the cell phenotype by modulating major functional pathways through expression correlation with their genes. The Gene Commanding Height (GCH), a measure that combines the expression control and expression correlation with all other genes, is used to establish the gene hierarchy in each cell phenotype. We developed the experimental protocol, the mathematical algorithm and the computer software to identify the GMRs from transcriptomic data in surgically removed tumors, biopsies or blood from cancer patients. The GMR approach is illustrated with applications to our microarray data on human kidney, thyroid and prostate cancer samples, and on thyroid, prostate and blood cancer cell lines. We proved experimentally that each patient has his/her own GMRs, that cancer nuclei and surrounding normal tissue are governed by different GMRs, and that manipulating the expression has larger consequences for genes with higher GCH. Therefore, we launch the hypothesis that silencing the GMR may selectively kill the cancer cells from a tissue.
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