Change in patterns of HIV status disclosure in the HAART era and association of HIV status disclosure with depression level among women

Whether widespread use of HAART changed patterns of HIV status disclosure among women living with HIV is largely unknown. In addition, the association between time to first HIV disclosure and depression has not been fully explored among women. A retrospective cross-sectional survey was conducted among HIV-infected women from the Washington, DC site of the Women's Interagency HIV Study to collect detailed information about their HIV status disclosure behavior. A sample of 202 HIV-positive women, 102 diagnosed prior to and 100 post-HAART era participated in this study. Relationships between treatment era when diagnosed (pre-HAART or HAART era) and patterns of HIV status disclosure, and associations between HIV status disclosure and depression level were examined using generalized linear regression models with generalized estimating equation to adjust for repeated measurements from the same individuals. Our analyses showed that treatment era was not associated with either comfort level of HIV status disclosure or time to first HIV disclosure to either family members or friends. However, women were less likely to disclose HIV status to their family members in the HAART era (P = 0.006) after adjusting for social network type, comfort level of disclosure, time to first disclosure and length of follow-up time. In addition, longer time to first HIV disclosure, but not comfort level or extent of HIV status disclosure, was independently associated with depression levels as measured by CES-D score at study enrollment ("a few months after" vs "within a few days": P = 0.008). More definitive studies utilizing longitudinal designs should be conducted to further examine impact of HAART era on HIV status disclosure and effect of HIV status disclosure on mental health

Summarizing performance for genome scale measurement of miRNA: reference samples and metrics

Background: The potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls. Results: Three pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes. Conclusions: The set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Healthcare Empowerment and HIV Viral Control: Mediating Roles of Adherence and Retention in Care

Introduction: This study assessed longitudinal relationships between patient healthcare empowerment, engagement in care, and viral control in the Women's Interagency HIV Study, a prospective cohort study of U.S. women living with HIV. Methods: From April 2014 to March 2016, four consecutive 6-month visits were analyzed among 973 women to assess the impact of Time 1 healthcare empowerment variables (Tolerance for Uncertainty and the state of Informed Collaboration Committed Engagement) on Time 2 reports of ≥95% HIV medication adherence and not missing an HIV primary care appointment since last visit; and on HIV RNA viral control across Times 3 and 4, controlling for illicit drug use, heavy drinking, depression symptoms, age, and income. Data were analyzed in 2017. Results: Adherence of ≥95% was reported by 83% of women, 90% reported not missing an appointment since the last study visit, and 80% were categorized as having viral control. Logistic regression analyses revealed a significant association between the Informed Collaboration Committed Engagement subscale and viral control, controlling for model covariates (AOR=1.08, p=0.04), but not for the Tolerance for Uncertainty subscale and viral control (AOR=0.99, p=0.68). In separate mediation analyses, the indirect effect of Informed Collaboration Committed Engagement on viral control through adherence (β=0.04, SE=0.02, 95% CI=0.02, 0.08), and the indirect effect of Informed Collaboration Committed Engagement on viral control through retention (β=0.01, SE=0.008, 95% CI=0.001, 0.030) were significant. Mediation analyses with Tolerance for Uncertainty as the predictor did not yield significant indirect effects. Conclusions: The Informed Collaboration Committed Engagement healthcare empowerment component is a promising pathway through which to promote engagement in care among women living with HIV

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts