Medical Cell Biology Commons^™

Mitochondrial Oxidative Stress Drives Tumor Progression And Metastasis: Should We Use Antioxidants As A Key Component Of Cancer Treatment And Prevention?, Federica Sotgia, Ubaldo E Martinez-Outschoorn, Michael P Lisanti

Department of Stem Cell Biology and Regenerative Medicine Faculty Papers & Presentations

The functional role of oxidative stress in cancer pathogenesis has long been a hotly debated topic. A study published this month in BMC Cancer by Goh et al., directly addresses this issue by using a molecular genetic approach, via an established mouse animal model of human breast cancer. More specifically, alleviation of mitochondrial oxidative stress, via transgenic over-expression of catalase (an anti-oxidant enzyme) targeted to mitochondria, was sufficient to lower tumor grade (from high-to-low) and to dramatically reduce metastatic tumor burden by >12-fold. Here, we discuss these new findings and place them in the context of several other recent studies …

Accurate Molecular Classification Of Cancer Using Simple Rules., Xiaosheng Wang, Osamu Gotoh

Journal Articles: Genetics, Cell Biology & Anatomy

BACKGROUND: One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often hampers the interpretability of the models. For a better understanding of the classification results, it is desirable to develop simpler rule-based models with as few marker genes as possible.

METHODS: …

The Significance Of Gata3 Expression In Breast Cancer: A 10-Year Follow-Up Study., Vincenzo Ciocca, Constantine Daskalakis, Robin M. Ciocca, Alejandra Ruiz-Orrico, Juan P. Palazzo

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

GATA3 is a transcription factor closely associated with estrogen receptor alpha in breast carcinoma, with a potential prognostic utility. This study investigated the immunohistochemical expression of GATA3 in estrogen receptor alpha-positive and estrogen receptor alpha-negative breast carcinomas. One hundred sixty-six cases of invasive breast carcinomas with 10-year follow-up information were analyzed. Positive GATA3 and estrogen receptor alpha cases were defined as greater than 20% of cells staining. Time to cancer recurrence and time to death were analyzed with survival methods. Of 166 patients, 40 were estrogen receptor alpha negative and 121 estrogen receptor alpha positive. Thirty-eight (23%) recurrences and 51 …

A Cyclin D1/Microrna 17/20 Regulatory Feedback Loop In Control Of Breast Cancer Cell Proliferation., Zuoren Yu, Chenguang Wang, Min Wang, Zhiping Li, Mathew C Casimiro, Manran Liu, Kongming Wu, James Whittle, Xiaoming Ju, Terry Hyslop, Peter Mccue, Richard G Pestell

Kimmel Cancer Center Faculty Papers

Decreased expression of specific microRNAs (miRNAs) occurs in human tumors, which suggests a function for miRNAs in tumor suppression. Herein, levels of the miR-17-5p/miR-20a miRNA cluster were inversely correlated to cyclin D1 abundance in human breast tumors and cell lines. MiR-17/20 suppressed breast cancer cell proliferation and tumor colony formation by negatively regulating cyclin D1 translation via a conserved 3' untranslated region miRNA-binding site, thereby inhibiting serum-induced S phase entry. The cell cycle effect of miR-17/20 was abrogated by cyclin D1 siRNA and in cyclin D1-deficient breast cancer cells. Mammary epithelial cell-targeted cyclin D1 expression induced miR-17-5p and miR-20a expression …

Department Of Pathology, Thomas Jefferson University, Identification Of Conserved Gene Expression Features Between Murine Mammary Carcinoma Models And Human Breast Tumors., Jason I Herschkowitz, Karl Simin, Victor J Weigman, Igor Mikaelian, Jerry Usary, Zhiyuan Hu, Karen E Rasmussen, Laundette P Jones, Shahin Assefnia, Subhashini Chandrasekharan, Michael G Backlund, Yuzhi Yin, Andrey I Khramtsov, Roy Bastein, John Quackenbush, Robert I Glazer, Powel H Brown, Jeffrey E Green, Levy Kopelovich, Priscilla A Furth, Juan P Palazzo, Olufunmilayo I Olopade, Philip S Bernard, Gary A Churchill, Terry Van Dyke, Charles M Perou

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

BACKGROUND: Although numerous mouse models of breast carcinomas have been developed, we do not know the extent to which any faithfully represent clinically significant human phenotypes. To address this need, we characterized mammary tumor gene expression profiles from 13 different murine models using DNA microarrays and compared the resulting data to those from human breast tumors. RESULTS: Unsupervised hierarchical clustering analysis showed that six models (TgWAP-Myc, TgMMTV-Neu, TgMMTV-PyMT, TgWAP-Int3, TgWAP-Tag, and TgC3(1)-Tag) yielded tumors with distinctive and homogeneous expression patterns within each strain. However, in each of four other models (TgWAP-T121, TgMMTV-Wnt1, Brca1Co/Co;TgMMTV-Cre;p53+/- and DMBA-induced), tumors with a variety of …

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 …