title: Regulators associated with clinical outcomes revealed by DNA methylation data in breast cancer.
abstract: The regulatory architecture of breast cancer is extraordinarily complex and gene misregulation can occur at many levels, with transcriptional malfunction being a major cause. This dysfunctional process typically involves additional regulatory modulators including DNA methylation. Thus, the interplay between transcription factor (TF) binding and DNA methylation are two components of a cancer regulatory interactome presumed to display correlated signals. As proof of concept, we performed a systematic motif-based in silico analysis to infer all potential TFs that are involved in breast cancer prognosis through an association with DNA methylation changes. Using breast cancer DNA methylation and clinical data derived from The Cancer Genome Atlas (TCGA), we carried out a systematic inference of TFs whose misregulation underlie different clinical subtypes of breast cancer. Our analysis identified TFs known to be associated with clinical outcomes of p53 and ER (estrogen receptor) subtypes of breast cancer, while also predicting new TFs that may also be involved. Furthermore, our results suggest that misregulation in breast cancer can be caused by the binding of alternative factors to the binding sites of TFs whose activity has been ablated. Overall, this study provides a comprehensive analysis that links DNA methylation to TF binding to patient prognosis.
authors.affiliation: Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America.
authors.forename: Matthew H
authors.initials: MH
authors.lastname: Ung
authors.affiliation: Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America.
authors.forename: Frederick S
authors.initials: FS
authors.lastname: Varn
authors.affiliation: Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America.
authors.forename: Shaoke
authors.initials: S
authors.lastname: Lou
authors.affiliation: Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America; Institute for Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, United States of America; Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, United States of America.
authors.forename: Chao
authors.initials: C
authors.lastname: Cheng
mesh_terms: D020816:Amino Acid Motifs; D001665:Binding Sites; D001943:Breast Neoplasms / Q000235:genetics* / Q000473:pathology; D016000:Cluster Analysis; D018899:CpG Islands; D019175:DNA Methylation; D004273:DNA, Neoplasm / Q000378:metabolism; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D011379:Prognosis; D011960:Receptors, Estrogen / Q000235:genetics / Q000378:metabolism; D014157:Transcription Factors / Q000378:metabolism; D016896:Treatment Outcome; D016159:Tumor Suppressor Protein p53 / Q000378:metabolism
chemical_list: D004273:DNA, Neoplasm; D011960:Receptors, Estrogen; C495901:TP53 protein, human; D014157:Transcription Factors; D016159:Tumor Suppressor Protein p53