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Full-Text Articles in Medicine and Health Sciences
Distinct P53 Acetylation Cassettes Differentially Influence Gene-Expression Patterns And Cell Fate., Chad D Knights, Jason Catania, Simone Di Giovanni, Selen Muratoglu, Ricardo Perez, Amber Swartzbeck, Andrew A Quong, Xiaojing Zhang, Terry Beerman, Richard Pestell, Maria Laura Avantaggiati
Distinct P53 Acetylation Cassettes Differentially Influence Gene-Expression Patterns And Cell Fate., Chad D Knights, Jason Catania, Simone Di Giovanni, Selen Muratoglu, Ricardo Perez, Amber Swartzbeck, Andrew A Quong, Xiaojing Zhang, Terry Beerman, Richard Pestell, Maria Laura Avantaggiati
Kimmel Cancer Center Faculty Papers
The activity of the p53 gene product is regulated by a plethora of posttranslational modifications. An open question is whether such posttranslational changes act redundantly or dependently upon one another. We show that a functional interference between specific acetylated and phosphorylated residues of p53 influences cell fate. Acetylation of lysine 320 (K320) prevents phosphorylation of crucial serines in the NH(2)-terminal region of p53; only allows activation of genes containing high-affinity p53 binding sites, such as p21/WAF; and promotes cell survival after DNA damage. In contrast, acetylation of K373 leads to hyperphosphorylation of p53 NH(2)-terminal residues and enhances the interaction with …
Classification And Risk Stratification Of Invasive Breast Carcinomas Using A Real-Time Quantitative Rt-Pcr Assay., Laurent Perreard, Cheng Fan, John F Quackenbush, Michael Mullins, Nicholas P Gauthier, Edward Nelson, Mary Mone, Heidi Hansen, Saundra S Buys, Karen Rasmussen, Alejandra Ruiz Orrico, Donna Dreher, Rhonda Walters, Joel Parker, Zhiyuan Hu, Xiaping He, Juan P Palazzo, Olufunmilayo I Olopade, Aniko Szabo, Charles M Perou, Philip S Bernard
Classification And Risk Stratification Of Invasive Breast Carcinomas Using A Real-Time Quantitative Rt-Pcr Assay., Laurent Perreard, Cheng Fan, John F Quackenbush, Michael Mullins, Nicholas P Gauthier, Edward Nelson, Mary Mone, Heidi Hansen, Saundra S Buys, Karen Rasmussen, Alejandra Ruiz Orrico, Donna Dreher, Rhonda Walters, Joel Parker, Zhiyuan Hu, Xiaping He, Juan P Palazzo, Olufunmilayo I Olopade, Aniko Szabo, Charles M Perou, Philip S Bernard
Department of Pathology, Anatomy, and Cell Biology Faculty Papers
INTRODUCTION: Predicting the clinical course of breast cancer is often difficult because it is a diverse disease comprised of many biological subtypes. Gene expression profiling by microarray analysis has identified breast cancer signatures that are important for prognosis and treatment. In the current article, we use microarray analysis and a real-time quantitative reverse-transcription (qRT)-PCR assay to risk-stratify breast cancers based on biological 'intrinsic' subtypes and proliferation. METHODS: Gene sets were selected from microarray data to assess proliferation and to classify breast cancers into four different molecular subtypes, designated Luminal, Normal-like, HER2+/ER-, and Basal-like. One-hundred and twenty-three breast samples (117 invasive …