Mechanisms of unphosphorylated STAT3 transcription factor binding to DNA.

Phosphorylation of signal transducer and activator of transcription 3 (STAT3) on a single tyrosine residue in response to growth factors, cytokines, interferons, and oncogenes activates its dimerization, translocation to the nucleus, binding to the interferon γ (gamma)-activated sequence (GAS) DNA-binding site and activation of transcription of target genes. STAT3 is constitutively phosphorylated in various cancers and drives gene expression from GAS-containing promoters to promote tumorigenesis. Recently, roles for unphosphorylated STAT3 (U-STAT3) have been described in response to cytokine stimulation, in cancers, and in maintenance of heterochromatin stability. However, the mechanisms underlying U-STAT3 binding to DNA has not been fully investigated. Here, we explore STAT3-DNA interactions by atomic force microscopy (AFM) imaging. We observed that U-STAT3 molecules bind to the GAS DNA-binding site as dimers and monomers. In addition, we observed that U-STAT3 binds to AT-rich DNA sequence sites and recognizes specific DNA structures, such as 4-way junctions and DNA nodes, within negatively supercoiled plasmid DNA. These structures are important for chromatin organization and our data suggest a role for U-STAT3 as a chromatin/genome organizer. Unexpectedly, we found that a C-terminal truncated 67.5-kDa STAT3 isoform recognizes single-stranded spacers within cruciform structures that also have a role in chromatin organization and gene expression. This isoform appears to be abundant in the nuclei of cancer cells and, therefore, may have a role in regulation of gene expression. Taken together, our data highlight novel mechanisms by which U-STAT3 binds to DNA and supports U-STAT3 function as a transcriptional activator and a chromatin/genomic organizer.

The association of intimate partner violence, recreational drug use with HIV seroprevalence among MSM.

Intimate partner violence (IPV) has been significantly associated with HIV among heterosexual individuals. Yet a similar relationship has not been so clearly described among men who have sex with men (MSM). The aim of this study was to investigate the association of IPV with HIV seroprevalence among MSM. Participants consisted of 7,844 MSM clients who visited the Whitman Walker Clinic in Washington DC from 2000 through 2007, the majority of whom were Caucasian with a median age of 30. The univariate analysis showed that self-reported IPV was significantly associated with HIV (OR: 1.67, CI: 1.14-2.45) among the sampled MSM clients. However, when adjusting for sexually transmitted infection (STI) status and self-reported risk behaviors including recreational drug use, condom use, number of male sex partners, and having sex with a positive HIV partner, the association of IPV with HIV was not statistically significant. Results indicated that the strong independent association of recreational drug use with HIV seroprevalence decreased the association of IPV with HIV significantly (with recreational drug use, OR: 1.36, CI: 0.93-2.00 vs. without recreational drug use, OR: 1.51, CI: 1.03-2.22).

Region-based Statistical Analysis of 2D PAGE Images.

A new comprehensive procedure for statistical analysis of two-dimensional polyacrylamide gel electrophoresis (2D PAGE) images is proposed, including protein region quantification, normalization and statistical analysis. Protein regions are defined by the master watershed map that is obtained from the mean gel. By working with these protein regions, the approach bypasses the current bottleneck in the analysis of 2D PAGE images: it does not require spot matching. Background correction is implemented in each protein region by local segmentation. Two-dimensional locally weighted smoothing (LOESS) is proposed to remove any systematic bias after quantification of protein regions. Proteins are separated into mutually independent sets based on detected correlations, and a multivariate analysis is used on each set to detect the group effect. A strategy for multiple hypothesis testing based on this multivariate approach combined with the usual Benjamini-Hochberg FDR procedure is formulated and applied to the differential analysis of 2D PAGE images. Each step in the analytical protocol is shown by using an actual dataset. The effectiveness of the proposed methodology is shown using simulated gels in comparison with the commercial software packages PDQuest and Dymension. We also introduce a new procedure for simulating gel images.

Social Media, Digital Scholarship, and Academic Promotion in US Medical Schools.

BACKGROUND AND OBJECTIVES: Academic promotion is critical in academic medicine. Traditionally, peer-reviewed journal articles have been at the core of advancement deliberations. With the increasing prominence digital content and social media, an increasing number of academics have begun linking their scholarly value with their online activities. It is unclear whether and how US academic medical institutions have updated their promotion criteria to reflect the changing environment and digital practices of faculty members. METHODS: We reviewed publicly available advancement and promotion policies and faculty handbooks of 148 allopathic medical schools in the United States (April 2018 through September 2018), to see if social media was explicitly included in their scholarship criteria. RESULTS: Of the 148 allopathic institutions only 12 (8.1%) stated that digital and social media products would be factored into the scholarship and/or other domains of the promotion application. There were no associations between acceptability of social media in the tenure process and schools' characteristics. CONCLUSIONS: Digital media use has the potential to distribute scholarship widely. Including digital scholarship in promotion would help destigmatize the use of digital platforms and promote science dissemination to the public. Medical institutions should embrace new models of digital scholarship and lead the way in defining and ensuring quality.

Efficient two-stage sequential arrays of proof of concept studies for pharmaceutical portfolios.

Previous work has shown that individual randomized "proof-of-concept" (PoC) studies may be designed to maximize cost-effectiveness, subject to an overall PoC budget constraint. Maximizing cost-effectiveness has also been considered for arrays of simultaneously executed PoC studies. Defining Type III error as the opportunity cost of not performing a PoC study, we evaluate the common pharmaceutical practice of allocating PoC study funds in two stages. Stage 1, or the first wave of PoC studies, screens drugs to identify those to be permitted additional PoC studies in Stage 2. We investigate if this strategy significantly improves efficiency, despite slowing development. We quantify the benefit, cost, benefit-cost ratio, and Type III error given the number of Stage 1 PoC studies. Relative to a single stage PoC strategy, significant cost-effective gains are seen when at least one of the drugs has a low probability of success (10%) and especially when there are either few drugs (2) with a large number of indications allowed per drug (10) or a large portfolio of drugs (4). In these cases, the recommended number of Stage 1 PoC studies ranges from 2 to 4, tracking approximately with an inflection point in the minimization curve of Type III error.

Comorbid Insomnia With Obstructive Sleep Apnea: Clinical Characteristics and Risk Factors.

STUDY OBJECTIVES: Obstructive sleep apnea (OSA) and chronic insomnia are two common sleep disorders and both are considered independent risk factors for heart disease. The aim of this study was to investigate the prevalence of comorbid insomnia with OSA and to compare its clinical characteristics with those of OSA without insomnia. METHODS: Patients who visited two tertiary university hospital sleep centers were screened. Those with a diagnosis of OSA using polysomnography were divided into two groups based on their scores on the Korean version of the Insomnia Severity Index (ISI-K): OSA with insomnia (OSA+I) (ISI-K score ≥ 15) and OSA without insomnia (OSA-I) (ISI-K score < 15). Subjective symptoms were evaluated using sleep questionnaires including ISI-K. Demographic and clinical characteristics of OSA+I and OSA-I were compared. RESULTS: Out of 476 patients with OSA, 139 (29.2%) had significant insomnia. Patients in the OSA+I group had a higher percentage of females (35.3% versus 19.6%, P < .001) and have higher rates of heart disease (19.4% versus 8.6%, P < .001). OSA+I group showed lower quality of life, lower quality of sleep, higher sleep propensity, and higher depression as measured by the Korean versions of the Short-Form 36-Item Health Survey, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and Beck Depression Inventory, respectively. There were no significant differences in adherence to continuous positive airway pressure between the groups. CONCLUSIONS: There is a high prevalence of comorbid insomnia with OSA (29.2%), consistent with previous findings in Western studies. Comorbid insomnia with OSA may constitute a cumulative risk factor for cardiovascular disease. These findings warrant further investigation into the mechanisms involved in its pathogenesis and devising more efficient treatments.

Pharmacological relevance of endoxifen in a laboratory simulation of breast cancer in postmenopausal patients.

BACKGROUND: Tamoxifen is metabolically activated via a CYP2D6 enzyme system to the more potent hydroxylated derivatives 4-hydroxytamoxifen and endoxifen. This study addresses the pharmacological importance of endoxifen by simulating clinical scenarios in vitro. METHODS: Clinical levels of tamoxifen metabolites in postmenopausal breast cancer patients previously genotyped for CYP2D6 were used in vitro along with clinical estrogen levels (estrone and estradiol) in postmenopausal patients determined in previous studies. The biological effects on cell growth were evaluated in a panel of estrogen receptor-positive breast cancer cell lines via cell proliferation assays and real-time polymerase chain reaction (PCR). Data were analyzed with one- and two-way analysis of variance and Student's t test. All statistical tests were two-sided. RESULTS: Postmenopausal levels of estrogen-induced proliferation of all test breast cancer cell lines (mean fold induction ± SD vs vehicle control: MCF-7 = 11 ± 1.74, P < .001; T47D = 7.52 ± 0.72, P < .001; BT474 = 1.75 ± 0.23, P < .001; ZR-75-1 = 5.5 ± 1.95, P = .001. Tamoxifen and primary metabolites completely inhibited cell growth regardless of the CYP2D6 genotype in all cell lines (mean fold induction ± SD vs vehicle control: MCF-7 = 1.57 ± 0.38, P = .54; T47D = 1.17 ± 0.23, P = .79; BT474 = 0.96 ± 0.2, P = .98; ZR-75-1 = 0.86 ± 0.67, P = .99). Interestingly, tamoxifen and its primary metabolites were not able to fully inhibit the estrogen-stimulated expression of estrogen-responsive genes in MCF-7 cells (P < .05 for all genes), but the addition of endoxifen was able to produce additional antiestrogenic effect on these genes. CONCLUSIONS: The results indicate that tamoxifen and other metabolites, excluding endoxifen, completely inhibit estrogen-stimulated growth in all cell lines, but additional antiestrogenic action from endoxifen is necessary for complete blockade of estrogen-stimulated genes. Endoxifen is of supportive importance for the therapeutic effect of tamoxifen in a postmenopausal setting.

Simulation with cells in vitro of tamoxifen treatment in premenopausal breast cancer patients with different CYP2D6 genotypes.

BACKGROUND AND PURPOSE: Tamoxifen is a prodrug that is metabolically activated by 4-hydroxylation to the potent primary metabolite 4-hydroxytamoxifen (4OHT) or via another primary metabolite N-desmethyltamoxifen (NDMTAM) to a biologically active secondary metabolite endoxifen through a cytochrome P450 2D6 variant system (CYP2D6). To elucidate the mechanism of action of tamoxifen and the importance of endoxifen for its effect, we determined the anti-oestrogenic efficacy of tamoxifen and its metabolites, including endoxifen, at concentrations corresponding to serum levels measured in breast cancer patients with various CYP2D6 genotypes (simulating tamoxifen treatment). EXPERIMENTAL APPROACH: The biological effects of tamoxifen and its metabolites on cell growth and oestrogen-responsive gene modulation were evaluated in a panel of oestrogen receptor-positive breast cancer cell lines. Actual clinical levels of tamoxifen metabolites in breast cancer patients were used in vitro along with actual levels of oestrogens observed in premenopausal patients taking tamoxifen. KEY RESULTS: Tamoxifen and its primary metabolites (4OHT and NDMTAM) only partially inhibited the stimulant effects of oestrogen on cells. The addition of endoxifen at concentrations corresponding to different CYP2D6 genotypes was found to enhance the anti-oestrogenic effect of tamoxifen and its metabolites with an efficacy that correlated with the concentration of endoxifen; at concentrations corresponding to the extensive metabolizer genotype it further inhibited the actions of oestrogen. In contrast, lower concentrations of endoxifen (intermediate and poor metabolizers) had little or no anti-oestrogenic effects. CONCLUSIONS AND IMPLICATIONS: Endoxifen may be a clinically relevant metabolite in premenopausal patients as it provides additional anti-oestrogenic actions during tamoxifen treatment.

Independent component analysis of 2-D electrophoresis gels.

We present a novel application of independent component analysis (ICA), an exploratory data analysis technique, to two-dimensional electrophoresis (2-DE) gels, which have been used to analyze differentially expressed proteins across groups. Unlike currently used pixel-wise statistical tests, ICA is a data-driven approach that utilizes the information contained in the entire gel data. We also apply ICA on wavelet-transformed 2-DE gels to address the high dimensionality and noise problems typically found in 2-DE gels. Also, we use an analysis-of-variance (ANOVA) approach as a benchmark for comparison. Using simulated data, we show that ICA detects the group differences accurately in both the spatial and wavelet domains. We also apply these techniques to real 2-DE gels. ICA proves to be much faster than ANOVA, and unlike ANOVA it does not depend on the selection of a threshold. Application of principal component analysis reduces the dimensionality and tends to improve the performance by reducing the noise.