Independent Validation of EarlyR Gene Signature in BIG 1-98: A Randomized, Double-Blind, Phase III Trial Comparing Letrozole and Tamoxifen as Adjuvant Endocrine Therapy for Postmenopausal Women With Hormone Receptor-Positive, Early Breast Cancer.

Background: EarlyR gene signature in estrogen receptor-positive (ER+) breast cancer is computed from the expression values of , , , , and . EarlyR has been validated in multiple cohorts profiled using microarrays. This study sought to verify the prognostic features of EarlyR in a case-cohort sample from BIG 1-98, a randomized clinical trial of ER+ postmenopausal breast cancer patients treated with adjuvant endocrine therapy (letrozole or tamoxifen).

Sharing Programming Resources Between Bio* Projects.

Open-source software encourages computer programmers to reuse software components written by others. In evolutionary bioinformatics, open-source software comes in a broad range of programming languages, including C/C++, Perl, Python, Ruby, Java, and R. To avoid writing the same functionality multiple times for different languages, it is possible to share components by bridging computer languages and Bio* projects, such as BioPerl, Biopython, BioRuby, BioJava, and R/Bioconductor.

Exploratory Analysis of Single-Gene Predictive Biomarkers in HERA DASL Cohort Reveals That C8A mRNA Expression Is Prognostic of Outcome and Predictive of Benefit of Trastuzumab.

Purpose: The Herceptin Adjuvant study is an international multicenter randomized trial that compared 1 or 2 years of trastuzumab given every 3 weeks with observation in women with human epidermal growth factor 2-positive (HER2+) breast cancer after chemotherapy. Identification of biomarkers predictive of a benefit from trastuzumab will minimize overtreatment and lower health care costs.

Methods: To identify possible single-gene biomarkers, an exploratory analysis of 3,669 gene probes not expected to be expressed in normal breast tissue was conducted.

High Expression of FGD3, a Putative Regulator of Cell Morphology and Motility, Is Prognostic of Favorable Outcome in Multiple Cancers.

Purpose: Identification of single-gene biomarkers that are prognostic of outcome can shed new insights on the molecular mechanisms that drive breast cancer and other cancers.

Methods: Exploratory analysis of 20,464 single-gene messenger RNAs (mRNAs) in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) discovery cohort indicates that low expression of mRNA is prognostic for poor outcome. Prognostic significance of faciogenital dysplasia 3 (FGD3), SUSD3, and other single-gene proliferation markers was evaluated in breast cancer and The Cancer Genome Atlas (TCGA) cohorts.

RAC1 GTP-ase signals Wnt-beta-catenin pathway mediated integrin-directed metastasis-associated tumor cell phenotypes in triple negative breast cancers.

The acquisition of integrin-directed metastasis-associated (ID-MA) phenotypes by Triple-Negative Breast Cancer (TNBC) cells is caused by an upregulation of the Wnt-beta-catenin pathway (WP). We reported that WP is one of the salient genetic features of TNBC. RAC-GTPases, small G-proteins which transduce signals from cell surface proteins including integrins, have been implicated in tumorigenesis and metastasis by their role in essential cellular functions like motility.

Effects of Estrogen Receptor and Human Epidermal Growth Factor Receptor-2 Levels on the Efficacy of Trastuzumab: A Secondary Analysis of the HERA Trial.

Importance: A number of studies suggest that response to antihuman epidermal growth factor receptor-2 (currently known as ERBB2, butreferred to asHER2 in this study) agents differs by estrogen receptor (ER) level status. The clinical relevance of this is unknown.

Objective: To determine the magnitude of trastuzumab benefit according to quantitative levels of ER and HER2 in the HERceptin Adjuvant (HERA) trial.

Single Gene Prognostic Biomarkers in Ovarian Cancer: A Meta-Analysis.

Purpose: To discover novel prognostic biomarkers in ovarian serous carcinomas.

Methods: A meta-analysis of all single genes probes in the TCGA and HAS ovarian cohorts was performed to identify possible biomarkers using Cox regression as a continuous variable for overall survival. Genes were ranked by p-value using Stouffer's method and selected for statistical significance with a false discovery rate (FDR) <.

Enriched transcription factor signatures in triple negative breast cancer indicates possible targeted therapies with existing drugs.

Purpose: Triple negative (TN) breast cancers which lack expression of the estrogen (ER), progesterone (PR), and human epidermal growth factor 2 (HER2) receptors convey a poor prognosis due in part to a lack of targeted therapies.

Methods: To identify viable targets for the treatment of TN disease, we have conducted a gene set enrichment analysis (GSEA) on seven different breast cancer whole genome gene expression cohorts comparing TN vs. ER + HER2 - to identify consistently enriched genes that share a common promoter motif.

Elevated APOBEC3B correlates with poor outcomes for estrogen-receptor-positive breast cancers.

Recent observations connected DNA cytosine deaminase APOBEC3B to the genetic evolution of breast cancer. We addressed whether APOBEC3B is associated with breast cancer clinical outcomes. APOBEC3B messenger RNA (mRNA) levels were related in 1,491 primary breast cancers to disease-free (DFS), metastasis-free (MFS), and overall survival (OS).

BioJava: an open-source framework for bioinformatics in 2012.

Unlabelled: BioJava is an open-source project for processing of biological data in the Java programming language. We have recently released a new version (3.0.

HDX workbench: software for the analysis of H/D exchange MS data.

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) is an established method for the interrogation of protein conformation and dynamics. While the data analysis challenge of HDX-MS has been addressed by a number of software packages, new computational tools are needed to keep pace with the improved methods and throughput of this technique. To address these needs, we report an integrated desktop program titled HDX Workbench, which facilitates automation, management, visualization, and statistical cross-comparison of large HDX data sets.

Sharing programming resources between Bio* projects through remote procedure call and native call stack strategies.

Open-source software (OSS) encourages computer programmers to reuse software components written by others. In evolutionary bioinformatics, OSS comes in a broad range of programming languages, including C/C++, Perl, Python, Ruby, Java, and R. To avoid writing the same functionality multiple times for different languages, it is possible to share components by bridging computer languages and Bio* projects, such as BioPerl, Biopython, BioRuby, BioJava, and R/Bioconductor.

Methods for the Analysis of High Precision Differential Hydrogen Deuterium Exchange Data.

Hydrogen/deuterium exchange (HDX) mass spectrometry has been widely applied to the characterization of protein dynamics. More recently, differential HDX has been shown to be effective for the characterization of ligand binding. Previously we have described a fully automated HDX system for use as a ligand screening platform.

Mutual information identifies sequence positions conserved within the nuclear receptor superfamily: approach reveals functionally important regions for DNA binding specificity.

Members of the nuclear receptor superfamily differentiate in terms of specificity for DNA recognition and binding, oligomeric state, and ligand binding. The wide range of specificities are impressive given the high degree of sequence conservation in the DNA binding domain (DBD) and moderate sequence conservation with high structural similarity within the ligand binding domains (LBDs). Determining sequence positions that are conserved within nuclear receptor subfamilies can provide important indicators into the structural dynamics that translate to oligomeric state of the active receptor, DNA binding specificity and ligand affinity and selectivity.