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Analysis of breast cancer genomic data to identify master gene regulators in a network context using Transcription Factor Enriched Regulons (TFERs) and Topologically Associating Domains (TADs)

AutorCampos-Laborie, Francisco J.; De Las Rivas, Javier
Fecha de publicación2017
CitaciónFEBS3+ (2017)
XL SEBBM Congress (2017)
ResumenTumorigenesis and tumor progression is a complex pathological process that occurs in cells that undergo a progressive alteration in which multiple genes and gene products are modified to change the normal state of a native cell in an transformed state. This progressive alteration is not always the same in every cell, and we currently know that there are –at least in humans– several hundred “onco-genes” that can drive such transformation and are different in different types of cancer. Despite this complexity, all cancer cells acquire or gain some common features such as: (i) reversion towards less differentiated cellular states; (ii) stimulation of cell cycle with enhanced proliferation; (iii) increased basal metabolic rate; etc. These common functional features allow to postulate that cancer formation and growth relies on the existence of some master and critical genes that regulate and drive tumorigenesis. This idea is in line with the “tumor bottleneck hypothesis” postulated by Dr. Andrea Califano (http://califano.c2b2.columbia.edu/cancer-systems-biology), which holds that if different genetic events contribute to a relatively uniform disease phenotype, their effect must eventually converge to a single gene or a small number of genes within the context of the tumor-driving cellular network. Based on this approach we performed a network-based analysis of the genome-wide expression profiles of a large dataset of breast cancer (BCC) samples (including major subtypes). Within this data set, we applied an algorithm to look for “master regulators” based on two complementary strategies: (i) search and mapping of Transcription Factor Enriched Regulons (TFERs) to identify co-regulated genes under the control of specific TFs; (ii) search and mapping of Topologically Associating Domains (TADs) to identify modular units of coordinated gene expression. We developed an algorithm to implement these analyses and we discovered genes postulated as “master regulators” that are different in different BCC subtypes (luminal, basal, etc.).
DescripciónResumen del póster presentado al 1st Joint Meeting of the French-Portuguese-Spanish Biochemical and Molecular Biology Societies y al XL Spanish Society of Biochemistry and Molecular Biology (SEBBM) Congress, celebrado en Barcelona (España) del 23 al 26 de octubre de 2017.
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