Contribution of the GSTP1 c.313A>G variant to hearing loss risk in patients exposed to platin chemotherapy during childhood.

BACKGROUND AND AIM: Ototoxicity is a potential adverse effect of chemotherapy with platin drugs, such as cisplatin and carboplatin, in children. Hearing loss (HL) affecting frequencies below 4 kHz can compromise speech perception. The aim of this study was to investigate whether genetic variants previously implicated in ototoxicity are associated with HL overall and HL below 4 kHz in pediatric oncology patients treated with cisplatin or carboplatin. MATERIALS AND METHODS: Patients given cisplatin or carboplatin for a pediatric cancer at least 5 years prior to the start of the study were enrolled. The patients underwent comprehensive audiological evaluations and genotyping to detect the presence of the GJB2 c.35delG, GSTP1 c.313A>G, and MT-RNR1 m.1555A>G polymorphisms. RESULTS: HL was identified in 31/61 patients (50.8%), including 28/42 treated with cisplatin (66.6%) and 3/19 treated with carboplatin (15.8%). HL was associated with higher mean doses of cisplatin (p = .002) and carboplatin (p = .010). The c.313A>G variant of GSTP1 (heterozygous or homozygous) was detected in 31/61 patients (50.8%). An association between this variant allele and HL involving frequencies ≤ 4 kHz was identified (p = .020; 10-fold vs. non-carriers). No associations with HL were observed for GJB2 or MT-RNR1 gene variants. CONCLUSION: The GSTP1 c.313A>G variant may increase the risk of low-frequency HL in pediatric oncology patients treated with cisplatin or carboplatin chemotherapy.

Immunomodulatory activity of ouabain in Leishmania leishmania amazonensis-infected Swiss mice.

Ouabain is a cardiotonic steroid identified as an endogenous substance of human plasma, being produced by the adrenal, pituitary, and hypothalamus. Despite the studies demonstrating the ability of ouabain to modulate inflammation and other aspects of the immune response, the effects of this substance in Leishmaniasis is unknown. The purpose of this work was to understand the immunomodulatory activity of ouabain in experimental Leishmaniasis in Swiss mice. It was demonstrated that ouabain reduced total cell numbers in the peritoneal cavity as a reflex of the inhibition of neutrophil migration induced by Leishmania (L.) Amazonensis. Furthermore, ouabain reduced TNF-α and IFN-γ levels, without cytotoxicity against peritoneal macrophages. These data showed the anti-inflammatory role of ouabain in the early events of the immune response triggered by Leishmania (L.) Amazonensis infection in murine model.

An adaptive alpha spending algorithm improves the power of statistical inference in microarray data analysis.

The adaptive alpha-spending algorithm incorporates additional contextual evidence (including correlations among genes) about differential expression to adjust the initial p-values to yield the alpha-spending adjusted p-values. The alpha-spending algorithm is named so because of its similarity with the alpha-spending algorithm in interim analysis of clinical trials in which stage-specific significance levels are assigned to each stage of the clinical trial. We show that the Bonferroni correction applied to the alpha-spending adjusted p-values approximately controls the Family Wise Error Rate under the complete null hypothesis. Using simulations we also show that the use of the alpha spending algorithm yields increased power over the unadjusted p-values while controlling FDR. We found the greater benefits of the alpha spending algorithm with increasing sample sizes and correlation among genes. The use of the alpha spending algorithm will result in microarray experiments that make more efficient use of their data and may help conserve resources.

HDBStat!: a platform-independent software suite for statistical analysis of high dimensional biology data.

BACKGROUND: Many efforts in microarray data analysis are focused on providing tools and methods for the qualitative analysis of microarray data. HDBStat! (High-Dimensional Biology-Statistics) is a software package designed for analysis of high dimensional biology data such as microarray data. It was initially developed for the analysis of microarray gene expression data, but it can also be used for some applications in proteomics and other aspects of genomics. HDBStat! provides statisticians and biologists a flexible and easy-to-use interface to analyze complex microarray data using a variety of methods for data preprocessing, quality control analysis and hypothesis testing. RESULTS: Results generated from data preprocessing methods, quality control analysis and hypothesis testing methods are output in the form of Excel CSV tables, graphs and an Html report summarizing data analysis. CONCLUSION: HDBStat! is a platform-independent software that is freely available to academic institutions and non-profit organizations. It can be downloaded from our website http://www.soph.uab.edu/ssg_content.asp?id=1164.

Applications of Bayesian statistical methods in microarray data analysis.

Microarray technology allows one to measure gene expression levels simultaneously on the whole-genome scale. The rapid progress generates both a great wealth of information and challenges in making inferences from such massive data sets. Bayesian statistical modeling offers an alternative approach to frequentist methodologies, and has several features that make these methods advantageous for the analysis of microarray data. These include the incorporation of prior information, flexible exploration of arbitrarily complex hypotheses, easy inclusion of nuisance parameters, and relatively well developed methods to handle missing data. Recent developments in Bayesian methodology generated a variety of techniques for the identification of differentially expressed genes, finding genes with similar expression profiles, and uncovering underlying gene regulatory networks. Bayesian methods will undoubtedly become more common in the future because of their great utility in microarray analysis.

Novel tumor necrosis factor alpha-regulated genes in rheumatoid arthritis.

OBJECTIVE: To determine novel genes regulated by tumor necrosis factor alpha (TNFalpha) signaling in primary rheumatoid arthritis synovial fibroblasts (RASFs). METHODS: Oligonucleotide microarrays were used to measure gene expression levels in 6 independent replicate samples of RASFs. RASFs were transfected for 18 hours with AdIkappaB-dominant negative (AdIkappaB-DN) (n = 3) or with control AdTet expressing the reverse tetracycline trans-activator (n = 3). The cells were stimulated for 3 hours with TNFalpha, and total RNA was prepared. Several novel parametric and nonparametric methods were used to rank genes in terms of the magnitude and significance of intergroup differences. Microarray expression differences were confirmed by real-time quantitative reverse transcription-polymerase chain reaction. Small interfering RNA (siRNA) was used to specifically down-modulate microarray-identified genes to demonstrate their role in the promotion of apoptosis, proliferation, or matrix metalloproteinase (MMP) expression. RESULTS: Blocking of NF-kappaB by AdIkappaB-DN was associated with a down-modulation of antiapoptosis genes, including BIRC-3, and several novel genes, including GG2-1, a TNFalpha-inducible FLIP-like gene. Other families of genes that were significantly down-regulated by AdIkappaB-DN included cytokines/chemokines (interleukin-1beta [IL-1beta], IL-8, IL-15, and RANTES), adhesion molecule (vascular cell adhesion molecule 1, intercellular adhesion molecule 1), and unique genes that have not previously been reported to be regulated by TNFalpha in RA. Inhibition of the GG2-1 gene using the siRNA technique resulted in significantly enhanced apoptosis, decreased proliferation, and decreased production of MMP-1 in TNFalpha-stimulated RASFs. CONCLUSION: These studies provide a comprehensive analysis of genes that are differentially regulated by TNFalpha signaling and NF-kappaB nuclear translocation in RASFs and demonstrate methods for confirming the expression and functional significance of such genes.