Genes associated with prostate cancer are differentially expressed in African American and European American men.

BACKGROUND: Despite more aggressive screening across all demographics and gradual declines in mortality related to prostate cancer (PCa) in the United States, disparities among populations persist. A substantial proportion of African American men (AAM) have a higher overall incidence, earlier age of onset, increased proportion of clinically advanced disease, and increased bone metastases and mortality from PCa compared to European American men (EAM). Limited early evidence indicates that underlying causes for disparities may be observed in tumor-specific gene expression programs. METHODS: This study used microarray-based methods to measure expression levels for 517 genes that were previously associated with PCa in archived formalin-fixed paraffin embedded (FFPE) specimens; testing the hypothesis that gene expression features of functional consequence to cancer distinguish PCa from AAM and EAM. A t test was conducted comparing AAM to EAM expression levels for each probe on the array. RESULTS: Analysis of 639 tumor samples (270 AAM, 369 EAM) showed that 95 genes were overexpressed specifically in PCa from AAM relative to EAM and 132 were overexpressed in PCa from EAM relative to AAM. Furthermore, systems-level analyses highlight the relevant signaling pathways and functions associated with the EAM- or AAM-specific overexpressed gene sets, for example, inflammation and lipid metabolism. CONCLUSIONS: Results here bring further understanding to the potential for molecular differences for PCa in AAM versus EAM. IMPACT: The results support the notion that therapeutic benefits will be realized when targeted treatments are designed to acknowledge and address a greater spectrum of PCa subtypes and molecular distinctions.

Transforming properties of 8p11-12 amplified genes in human breast cancer.

Amplification of the 8p11-12 region has been found in about 15% of human breast cancers and is associated with poor prognosis. Earlier, we used genomic analysis of copy number and gene expression to perform a detailed analysis of the 8p11-12 amplicon to identify candidate oncogenes in breast cancer. We identified 21 candidate genes and provided evidence that three genes, namely, LSM-1, TC-1, and BAG4, have transforming properties when overexpressed. In the present study, we systematically investigated the transforming properties of 13 newly identified 8p11-12 candidate oncogenes in vitro. WHSC1L1, DDHD2, and ERLIN2 were most potently transforming oncogenes based on the number of altered phenotypes expressed by the cells. WHSC1L1 contains a PWWP-domain that is a methyl-lysine recognition motif involved in histone code modification and epigenetic regulation of gene expression. Knockdown of WHSC1L1 in 8p11-12-amplified breast cancer cells resulted in profound loss of growth and survival of these cells. Further, we identified several WHSC1L1 target genes, one of which is iroquois homeobox 3 gene (IRX3), a member of the Iroquois homeobox transcription factor family.

HER-2 signaling, acquisition of growth factor independence, and regulation of biological networks associated with cell transformation.

Activated oncogenes are the dominant drivers of malignant progression in human cancer, yet little is known about how the transformation from proto-oncogene to activated oncogene drives the expression of transformed phenotypes. An isogenic model of HER-2-mediated transformation of human mammary epithelial cells was used along with HER-2-amplified human breast cancers to investigate how HER-2 activation alters its properties as a signaling molecule and changes the networks of HER-2-regulated genes. Our results show that full oncogenic activation of HER-2 is the result of a transition in which activated HER-2 acquires dominant signaling properties that qualitatively alter the network of genes regulated by the activated oncogene compared with the proto-oncogene. Consequently, gene expression programs related to invasion, cell stress, and stemness become regulated by HER-2 in a manner not observed in nontransformed cells, even when HER-2 is overexpressed. Our results offer novel insights into biological processes that come under the control of HER-2 after it acquires full oncogenic potential.

Cytokine and cytokine receptor single-nucleotide polymorphisms predict risk for non-small cell lung cancer among women.

Studies on the relationships between inflammatory pathway genes and lung cancer risk have not included African-Americans and have only included a handful of genes. In a population-based case-control study on 198 African-American and 744 Caucasian women, we examined the association between 70 cytokine and cytokine receptor single-nucleotide polymorphisms (SNPs) and risk of non-small cell lung cancer (NSCLC). Unconditional logistic regression was used to estimate odds ratios and 95% confidence intervals in a dominant model adjusting for major risk factors for lung cancer. Separate analyses were conducted by race and by smoking history and history of chronic obstructive pulmonary disease among Caucasians. Random forest analysis was conducted by race. On logistic regression analysis, IL6 (interleukin 6), IL7R, IL15, TNF (tumor necrosis factor), and IL10 SNP were associated with risk of non-small cell lung cancer among African-Americans; IL7R and IL10 SNPs were also associated with risk of lung cancer among Caucasians. Although random forest analysis showed IL7R and IL10 SNPs as being associated with risk for lung cancer among African-Americans, it also identified TNFRSF10A SNP as an important predictor. On random forest analysis, an IL1A SNP was identified as an important predictor of lung cancer among Caucasian women. Inflammatory SNPs differentially predicted risk for NSCLC according to race, as well as based on smoking history and history of chronic obstructive pulmonary disease among Caucasian women. Pathway analysis results are presented. Inflammatory pathway genotypes may serve to define a high risk group; further exploration of these genes in minority populations is warranted.

Emerging applications of network and pathway analysis in drug discovery and development.

Molecular pathway and network analysis tools that have been developed over the past decade provide an emerging systems-wide perspective for the analysis of gene expression, proteomic and metabolomic data. These tools link relevant extracted literature information available from structured knowledge bases with user-friendly features that enable analysis and interpretation of the global impact of a disease stage or drug treatment. Pathway and network analysis tools have been found to have broad applicability within the biomedical community, most specifically in cancer research to elucidate mechanisms of tumor progression and for biomarker discovery, and more recently in the area of drug discovery and development. This review discusses recent applications of pathway and network analysis for predictive in silico modeling in the area of drug discovery and development, including theoretical and practical advances and the implications for their application.

High-throughput phenotypic profiling of gene-environment interactions by quantitative growth curve analysis in Saccharomyces cerevisiae.

Cell-based assays are widely used in high-throughput screening to determine the effects of toxicants and drugs on their biological targets. To enable a functional genomics modeling of gene-environment interactions, quantitative assays are required both for gene expression and for the phenotypic responses to environmental challenge. To address this need, we describe an automated high-throughput methodology that provides phenotypic profiling of the cellular responses to environmental stress in Saccharomyces cerevisiae. Standardized assay conditions enable the use of a single metric value to quantify yeast microculture growth curves. This assay format allows precise control of both genetic and environmental determinants of the cellular responses to oxidative stress, a common mechanism of environmental insult. These yeast-cell-based assays are validated with hydrogen peroxide, a simple direct-acting oxidant. Phenotypic profiling of the oxidative stress response of a yap1 mutant strain demonstrates the mechanistic analysis of genetic susceptibility to oxidative stress. As a proof of concept for analysis of more complex gene-environment interactions, we describe a combinatorial assay design for phenotypic profiling of the cellular responses to tert-butyl hydroperoxide, a complex oxidant that is actively metabolized by its target cells. Thus, the yeast microculture assay format supports comprehensive applications in toxicogenomics.