Medical Anatomy Commons^™

Estimated Impact Of Low Isolate Numbers On The Reliability Of Cumulative Antibiogram Data, Christian Tran, John Hargy, Bryan Hess, Matthew Pettengill

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

Antibiograms are cumulative reports of antimicrobial susceptibility results that are used to guide the selection of empirical antibiotic therapy. Although Clinical and Laboratory Standards Institute (CLSI) guidelines recommend including only organisms that have at least 30 isolates in an antibiogram, previous studies demonstrated that adherence to this recommendation is highly variable. This paper aims to model the impact of small sample sizes on expected levels of error in cumulative antibiograms by comparing percent susceptibility results for random samples to those of the larger, entire data set. The results demonstrate relatively high error rates when utilizing low numbers of isolates in …

Unreliable Automated Complete Blood Count Results: Causes, Recognition, And Resolution, Gene Gulati, Guldeep Uppal, Jerald Z. Gong

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

Automated hematology analyzers generate accurate complete blood counts (CBC) results on nearly all specimens. However, every laboratory encounters, at times, some specimens that yield no or inaccurate result(s) for one or more CBC parameters even when the analyzer is functioning properly and the manufacturer's instructions are followed to the letter. Inaccurate results, which may adversely affect patient care, are clinically unreliable and require the attention of laboratory professionals. Laboratory professionals must recognize unreliable results, determine the possible cause(s), and be acquainted with the ways to obtain reliable results on such specimens. We present a concise overview of the known causes …

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 …

Decorin Protein Core Affects The Global Gene Expression Profile Of The Tumor Microenvironment In A Triple-Negative Orthotopic Breast Carcinoma Xenograft Model., Simone Buraschi, Thomas Neill, Rick T Owens, Leonardo A Iniguez, George Purkins, Rajanikanth Vadigepalli, Barry Evans, Liliana Schaefer, Stephen C Peiper, Zi-Xuan Wang, Renato V Iozzo

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

Decorin, a member of the small leucine-rich proteoglycan gene family, exists and functions wholly within the tumor microenvironment to suppress tumorigenesis by directly targeting and antagonizing multiple receptor tyrosine kinases, such as the EGFR and Met. This leads to potent and sustained signal attenuation, growth arrest, and angiostasis. We thus sought to evaluate the tumoricidal benefits of systemic decorin on a triple-negative orthotopic breast carcinoma xenograft model. To this end, we employed a novel high-density mixed expression array capable of differentiating and simultaneously measuring gene signatures of both Mus musculus (stromal) and Homo sapiens (epithelial) tissue origins. We found that …

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 …