Medicine and Health Sciences Commons^™

Cytoplasmic Localization Of Alteration/Deficiency In Activation 3 (Ada3) Predicts Poor Clinical Outcome In Breast Cancer Patients., Sameer Mirza, Emad A. Rakha, Alaa Alshareeda, Shakur Mohibi, Xiangshan Zhao, Bryan J. Katafiasz, Jun Wang, Channabasavaiah B. Gurumurthy, Aditya Bele, Ian O. Ellis, Andrew R. Green, Hamid Band, Vimla Band

Journal Articles: Genetics, Cell Biology & Anatomy

Transcriptional activation by estrogen receptor (ER) is a key step to breast oncogenesis. Given previous findings that ADA3 is a critical component of HAT complexes that regulate ER function and evidence that overexpression of other ER coactivators such as SRC-3 is associated with clinical outcomes in breast cancer, the current study was designed to assess the potential significance of ADA3 expression/localization in human breast cancer patients. In this study, we analyzed ADA3 expression in breast cancer tissue specimens and assessed the correlation of ADA3 staining with cancer progression and patient outcome. Tissue microarrays prepared from large series of breast cancer …

Microarray-Based Cancer Prediction Using Single Genes., Xiaosheng Wang, Richard Simon

Journal Articles: Genetics, Cell Biology & Anatomy

BACKGROUND: Although numerous methods of using microarray data analysis for cancer classification have been proposed, most utilize many genes to achieve accurate classification. This can hamper interpretability of the models and ease of translation to other assay platforms. We explored the use of single genes to construct classification models. We first identified the genes with the most powerful univariate class discrimination ability and then constructed simple classification rules for class prediction using the single genes.

RESULTS: We applied our model development algorithm to eleven cancer gene expression datasets and compared classification accuracy to that for standard methods including Diagonal Linear …

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: …

Intercenter Reliability And Validity Of The Rhesus Macaque Genechip, Fenghai Duan, Eliot R. Spindel, Yu-Hua Li, Robert B. Norgren

Journal Articles: Genetics, Cell Biology & Anatomy

BACKGROUND: The non-human primate (NHP) research community has been intensely interested in obtaining whole-genome expression arrays for their work. Recently, novel approaches were used to generate the DNA sequence information for a rhesus GeneChip. To test the reliability of the rhesus GeneChip across different centers, RNA was isolated from five sources: cerebral cortex, pancreas, thymus, testis, and an immortalized fibroblast cell line. Aliquots of this RNA were sent to each of three centers: Yerkes National Primate Research Center, Oregon National Primate Research Center and the University of Nebraska Medical Center. Each center labeled the samples and hybridized them with two …