Emerging Biomarkers and Clinical Implications in Endometrial Carcinoma

Endometrial cancer (EmCa) is the most common type of gynecological cancer. EmCa is the fourth most common cancer in the United States, which has been linked to increased incidence of obesity. EmCa can be classified into two main types: Type I and Type II, which include the major histological subtypes. Type I EmCa is hormonally driven, less aggressive, and has a more favorable prognosis. In contrast, Type II EmCa grows independently of hormonal signals, is more aggressive, and generally has an unfavorable prognosis. Various tumor biomarkers [i.e., tumor suppressor p53, hypoxia-inducible factor 1-alpha (HIF1-α), human epidermal growth factor receptor 2 (HER2/neu), and vascular endothelial growth factor (VEGF)] have been identified in EmCa. Biomarkers of treatment effectiveness involve immunosuppressive factors targeted by microRNA (miRNA)-based therapy. However, there are no reliable biomarker tests for early detection of EmCa and treatment effectiveness. A potential new biomarker is Notch, Interleukin-1, leptin crosstalk outcome (NILCO) that could affect the progression of Type II EmCa. NILCO expression in EmCa might be dependent on patient’s obesity status. This chapter presents updated information on these, and other potential emerging biomarkers for EmCa, and discusses current challenges and clinical implications on this area of research

Elevated Circulating Angiogenic Progenitors and White Blood Cells Are Associated with Hypoxia-Inducible Angiogenic Growth Factors in Children with Sickle Cell Disease

We studied the number and function of angiogenic progenitor cells and growth factors in children aged 5–18 years without acute illness, 43 with Hemoglobin SS and 68 with normal hemoglobin. Hemoglobin SS subjects had at least twice as many mononuclear cell colonies and more circulating progenitor cell than Control subjects. Plasma concentrations of erythropoietin, angiopoietin-2, and stromal-derived growth factor (SDF)-1α were significantly higher in children with Hemoglobin SS compared to Control subjects. In a multivariate analysis model, SDF-1α concentration was found to be associated with both CPC number and total white blood cell count in the Hemoglobin SS group, suggesting that SDF-1α produced by ischemic tissues plays a role in mobilizing these cells in children with Hemoglobin SS. Despite having a higher number of angiogenic progenitor cells, children with Hemoglobin SS had slower migration of cultured mononuclear cells

Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS): Architecture

We describe the architecture of the Patient Centered Outcomes Research Institute (PCORI) funded Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS, http://www.SCILHS.org) clinical data research network, which leverages the $48 billion dollar federal investment in health information technology (IT) to enable a queryable semantic data model across 10 health systems covering more than 8 million patients, plugging universally into the point of care, generating evidence and discovery, and thereby enabling clinician and patient participation in research during the patient encounter. Central to the success of SCILHS is development of innovative ‘apps’ to improve PCOR research methods and capacitate point of care functions such as consent, enrollment, randomization, and outreach for patient-reported outcomes. SCILHS adapts and extends an existing national research network formed on an advanced IT infrastructure built with open source, free, modular components

COMPARATIVE FREQUENCY OF ANGIOGRAPHIC CORONARY ARTERY DISEASE IN AFRICAN AMERICANS AND HISPANICS

https://www.ethndis.org/priorarchives/ethn-16-01-58.pd

A Multiinstitutional, Multidisciplinary Model for Developing and Teaching Translational Research in Health Disparities

Abstract available at publisher's web site

Detection of HIV-1 and Human Proteins in Urinary Extracellular Vesicles from HIV+ Patients

Background. Extracellular vesicles (EVs) are membrane bound, secreted by cells, and detected in bodily fluids, including urine, and contain proteins, RNA, and DNA. Our goal was to identify HIV and human proteins (HPs) in urinary EVs from HIV+ patients and compare them to HIV− samples. Methods. Urine samples were collected from HIV+ (n=35) and HIV− (n=12) individuals. EVs were isolated by ultrafiltration and characterized using transmission electron microscopy, tandem mass spectrometry (LC/MS/MS), and nanoparticle tracking analysis (NTA). Western blots confirmed the presence of HIV proteins. Gene ontology (GO) analysis was performed using FunRich and HIV Human Interaction database (HHID). Results. EVs from urine were 30–400 nm in size. More EVs were in HIV+ patients, P<0.05, by NTA. HIV+ samples had 14,475 HPs using LC/MS/MS, while only 111 were in HIV−. HPs in the EVs were of exosomal origin. LC/MS/MS showed all HIV+ samples contained at least one HIV protein. GO analysis showed differences in proteins between HIV+ and HIV− samples and more than 50% of the published HPs in the HHID interacted with EV HIV proteins. Conclusion. Differences in the proteomic profile of EVs from HIV+ versus HIV− samples were found. HIV and HPs in EVs could be used to detect infection and/or diagnose HIV disease syndromes