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Yeast As a Chassis for Developing Functional Assays to Study Human P53
Published on: August 4, 2019
Comparison of gene expression patterns across 12 tumor types identifies a cancer supercluster characterized by TP53
E Martínez1, K Yoshihara2, H Kim3
11] Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA [2] Catedra de Bioinformatica, Tecnologico de Monterrey, Monterrey, Nuevo Leon, Mexico.
Abstract:
Transcriptional profile-based subtypes of cancer are often viewed as identifying different diseases from the same tissue origin. Understanding the mechanisms driving the subtypes may be key in development of novel therapeutics but is challenged by lineage-specific expression signals. Using a t-test statistics approach, we compared gene expression subtypes across 12 tumor types, which identified eight transcriptional superclusters characterized by commonly activated disease pathways and similarities in gene expression. One of the largest superclusters was determined by the upregulation of a proliferation signature, significant enrichment in TP53 mutations, genomic loss of CDKN2A (p16(ARF)), evidence of increased numbers of DNA double strand breaks and high expression of cyclin B1 protein. These correlations suggested that abrogation of the P53-mediated apoptosis response to DNA damage results in activation of cell cycle pathways and represents a common theme in cancer. A second consistent pattern, observed in 9 of 11 solid tumor types, was a subtype related to an activated tumor-associated stroma. The similarity in transcriptional footprints across cancers suggested that tumor subtypes are commonly unified by a limited number of molecular themes.
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