Assessing the use of GEE methods for analyzing binary outcomes in family studies: the Strong Heart Family Study.

The generalized estimating equations method (GEE) is commonly applied to analyze data obtained from family studies. GEE is well known for its robustness on misspecification of correlation structure. However, the unbalanced distribution of family sizes and complicated genetic relatedness structure within each family may challenge GEE performance. We focused our research on binary outcomes. To evaluate the performance of GEE, we conducted a series of simulations, on data generated adopting the kinship matrix (correlation structure within each family) from the Strong Heart Family Study (SHFS). We performed a fivefold cross-validation to further evaluate the GEE predictive power on data from the SHFS. A Bayesian modeling approach, with direct integration of the kinship matrix, was also included to contrast with GEE. Our simulation studies revealed that GEE performs well on a binary outcome from families having a relatively simple kinship structure. However, data with a binary outcome generated from families with complex kinship structures, especially with a large genetic variance, can challenge the performance of GEE.

Isolating Neurologic Deficits in Cervical Spondylotic Myelopathy: A Case-Controlled Study, Using the NIH Toolbox Motor Battery.

Background and Objectives: Patients with cervical spondylotic myelopathy (CSM) have motor impairments, including weakness, imbalance, and loss of dexterity. The reliable assessment of these symptoms is critical for treatment decisions. This study aimed to determine, for the first time, the use of the NIH Toolbox motor battery (NIHTBm) in the objective assessment of motor deficits in patients with CSM. Methods: Patients with symptoms and MRI evidence of CSM and age-matched healthy controls (HC), with no evidence of spinal disorder or surgery were included in this case-control study based on our inclusion and exclusion criteria. We performed motor tests, dexterity, gait speed, grip strength, and balance tests, using the NIHTBm in patients with CSM and HCs. Motor impairment rates were determined in patients with CSM based on the NIHTBm scores. We determined the association between NIHTBm scores and patient-reported outcome scores; patient-reported outcome measures (the modified Japanese Orthopedic Association [mJOA] and Nurick grade) to determine the association. One-way analysis of variance was used to analyze group differences and the Spearman rank correlation to determine the relationship between assessment scores. Results: We enrolled 24 patients with CSM with a mean age (SD) of 57.96 (10.61) years and 24 age-matched HCs with a mean age (SD) of 53.17 (6.04) years in this study. Overall, we observed a significant decrease in the motor function T-scores mean (SD): dexterity 31.54 (14.82) vs 51.54 (9.72), grip strength 32.00 (17.47) vs 56.79 (8.46), balance 27.58 (16.65) vs 40.21 (6.35), and gait speed 0.64 (0.18) vs 0.99 (0.17) m/s, in patients with CSM compared with that in HCs. The lower extremity dysfunction scores on the NIHTBm, balance (ρ = -0.67) and gait speed (ρ = -0.62), were associated with higher Nurick grades. We observed a similar but weaker association with the Nurick grades and NIHTBm tests: dexterity (ρ = -0.49) and grip strength (ρ = -0.31) scores. The total motor mJOA showed a positive but weak association with NIHTBm scores, gait speed (ρ = 0.38), balance (ρ = 0.49), grip strength (ρ = 0.41), and dexterity (ρ = 0.45). Discussion: Patients with CSM had significantly lower NIHTBm scores compared with HCs. The results from the NIHTBm are consistent with the clinical presentation of CSM showing patients have motor impairments in both upper and lower extremities. As a neurologic-specific scale, NIHTBm should be used in the evaluation and clinical management of patients with CSM.

Meta-analysis Analyzing the Effect of Therapies on 6-Minute Walk Distance in Heart Failure With Reduced Ejection Fraction.

The 6-minute walk distance (6MWD) carries prognostic value in patients with heart failure with reduced ejection fraction (HFrEF). We performed this systematic review and meta-analysis to evaluate the effect of heart failure therapies on improvement in 6MWD. A systematic search of MEDLINE and Embase was conducted for randomized controlled trials measuring 6MWD at baseline and at follow-up in at least 50 patients with HFrEF across both arms. The primary outcome was improvement in 6MWD at follow-up. Meta-analysis was stratified in groups on the basis of medical therapy, device-based therapy, autonomic modulation, and exercise. Mean differences (MDs) with 95% confidence interval (CI) were reported across multiple studies that were included in the meta-analysis. A total of 44 studies met the inclusion criteria for systematic review; 17 of which were included for meta-analysis. Statistical analysis showed a statistically significant improvement in 6MWD in meters (m) at follow-up for device-based therapy (MD 20.01 m, 95% CI 18.71 to 21.31), autonomic modulation (MD 76.64 m, 95% CI 54.10 to 99.19), and exercise group (MD 39.52 m, 95% CI 19.68 to 59.35). Pooled analysis of medical therapy did not show statistically significant improvement in 6MWD at follow-up (MD 31.69 m, 95% CI -6.52 to 69.91). Device-based therapy (cardiac resynchronization therapy and cardiac contractility modulation), autonomic modulation, and exercise training programs are associated with improvement in 6MWD in patients with HFrEF. 6MWD is a useful test to gauge improvement in functional capacity among patients with HFrEF, especially those with severe symptomatic heart failure.

Oncology and Primary Care Provider Views on Cancer Survivorship Care: Mind the Gap.

CONTEXT: Coordination between oncology and primary care practices in cancer survivorship is lacking. OBJECTIVE: To identify cancer care coordination perceptions, knowledge, and practices in a sample of Oklahoma oncology care providers (ONCs) and primary care providers (PCPs) regarding post-treatment care of adult cancer survivors. DESIGN: Cross-sectional, statewide survey by mail/web link in 2014/5. SETTING: PCPs identified through a primary care research network, primary care organization membership lists; ONCs identified through www.Healthgrades.com. PARTICIPANTS: Contacts who were clinically active and seeing cancer patients were eligible. The final sample size included 101 ONCs and 58 PCPs who reported actively seeing cancer patients. MEASURES: Responses to predominately Likert scale or ranked-order questions derived from the Survey of Physician Attitudes Regarding the Care of Cancer Survivors. ANALYSES: Chi square and t tests were performed to test bivariate associations between provider type and survey measures. RESULTS: Statistically significant differences (P < .05) between ONC and PCP perceptions were observed for several questions on communication between the 2 provider types, ONC perceptions of PCP ability to address survivorship care, and responsibilities for post-treatment care. CONCLUSIONS: Highly discrepant perspectives between ONCs and PCPs regarding communications and responsibilities for survivorship care may lead to adverse health outcomes. Interventions aimed at improving care coordination for cancer survivors should define each provider group's responsibilities in survivorship care, and create structures and processes that foster clear channels of communication between ONC and PCP practices.

A two-stage adaptive clinical trial design with data-driven subgroup identification at interim analysis.

In this paper, we consider randomized controlled clinical trials comparing two treatments in efficacy assessment using a time to event outcome. We assume a relatively small number of candidate biomarkers available in the beginning of the trial, which may help define an efficacy subgroup which shows differential treatment effect. The efficacy subgroup is to be defined by one or two biomarkers and cut-offs that are unknown to the investigator and must be learned from the data. We propose a two-stage adaptive design with a pre-planned interim analysis and a final analysis. At the interim, several subgroup-finding algorithms are evaluated to search for a subgroup with enhanced survival for treated versus placebo. Conditional powers computed based on the subgroup and the overall population are used to make decision at the interim to terminate the study for futility, continue the study as planned, or conduct sample size recalculation for the subgroup or the overall population. At the final analysis, combination tests together with closed testing procedures are used to determine efficacy in the subgroup or the overall population. We conducted simulation studies to compare our proposed procedures with several subgroup-identification methods in terms of a novel utility function and several other measures. This research demonstrated the benefit of incorporating data-driven subgroup selection into adaptive clinical trial designs.

A Novel Mobile Device-Based Approach to Quantitative Mobility Measurements for Power Wheelchair Users.

This study is motivated by the fact that there are currently no widely used applications available to quantitatively measure a power wheelchair user's mobility, which is an important indicator of quality of life. To address this issue, we propose an approach that allows power wheelchair users to use their own mobile devices, e.g., a smartphone or smartwatch, to non-intrusively collect mobility data in their daily life. However, the convenience of data collection brings substantial challenges in data analysis because the data patterns associated with wheelchair maneuvers are not as strong as other activities, e.g., walking, running, etc. In addition, the built-in sensors in different mobile devices create significant heterogeneity in terms of sensitivity, noise patterns, sampling settings, etc. To address the aforementioned challenges, we developed a novel approach composed of algorithms that work collaboratively to reduce noise, identify patterns intrinsic to wheelchair maneuvers, and finalize mobility analysis by removing spikes and dips caused by abrupt maneuver changes. We conducted a series of experiments to evaluate the proposed approach. Experimental results showed that our approach could accurately determine wheelchair maneuvers regardless of the models and placements of the mobile devices.

Effects of enzyme-based removal of collagen and elastin constituents on the biaxial mechanical responses of porcine atrioventricular heart valve anterior leaflets.

The leaflets of the atrioventricular heart valves (AHVs) regulate the one-directional flow of blood through a coordination of the extracellular matrix components, including the collagen fibers, elastin, and glycosaminoglycans. Dysfunction of the AHVs, such as those caused by unfavorable microstructural remodeling, lead to valvular heart diseases and improper blood flow, which can ultimately cause heart failure. In order to better understand the mechanics and remodeling of the AHV leaflets and how therapeutics can inadvertently cause adverse microstructural changes, a systematic characterization of the role of each constituent in the biomechanical properties is appropriate. Previous studies have quantified the contributions of the individual microstructural components to tissue-level behavior for the semilunar valve cusps, but not for the AHV leaflets. In this study, for the first time, we quantify the relationships between microstructure and mechanics of the AHV leaflet using a three-step experimental procedure: (i) biaxial tension and stress relaxation testing of control (untreated) porcine AHV anterior leaflet specimens; (ii) enzyme treatment to remove a portion of either the collagen or elastin constituent; and (iii) biaxial tensile and stress relaxation testing of the constituent-removed (treated) specimens. We have observed that the removal of ∼100% elastin resulted in a ∼10% decrease in the tissue extensibility with biaxial tension and a ∼10% increase in the overall stress reduction with stress relaxation. In contrast, removal of 46% of the collagen content insignificantly affected tissue extensibility with biaxial tension and significantly increased stress decay (10%) with stress relaxation. These findings provide an insight into the microstructure-mechanics relationship of the AHVs and will be beneficial for future developments and refinements of microstructurally informed constitutive models for the simulation of diseased and surgically intervened AHV function. STATEMENT OF SIGNIFICANCE: This study presents, for the first time, a thorough mechanical characterization of the atrioventricular heart valve leaflets before and after enzymatic removal of elastin and collagen. We found that the biaxial tensile properties of elastin-deficient tissues and collagen-deficient are stiffer. The fact of elastin supporting low-stress valve function and collagen as the main load-bearing component was evident in a decrease in the low-tension modulus for elastin-deficient tissues and in the high-tension modulus for collagen-deficient tissues. Our quantification and experimental technique could be useful in predicting the disease-related changes in heart valve mechanics. The information obtained from this work is valuable for refining the constitutive models that describe the essential microstructure-mechanics relationship.

Misclassification Error-Adjusted Prevalence of Injection Drug Use Among Infective Endocarditis Hospitalizations in the United States: A Serial Cross-Sectional Analysis of the 2007-2016 National Inpatient Sample.

Administrative health databases have been used to monitor trends in infective endocarditis hospitalization related to nonprescription injection drug use (IDU) using International Classification of Diseases (ICD) code algorithms. Because no ICD code for IDU exists, drug dependence and hepatitis C virus (HCV) have been used as surrogate measures for IDU, making misclassification error (ME) a threat to the accuracy of existing estimates. In a serial cross-sectional analysis, we compared the unadjusted and ME-adjusted prevalences of IDU among 70,899 unweighted endocarditis hospitalizations in the 2007-2016 National Inpatient Sample. The unadjusted prevalence of IDU was estimated with a drug algorithm, an HCV algorithm, and a combination algorithm (drug and HCV). Bayesian latent class models were used to estimate the median IDU prevalence and 95% Bayesian credible intervals and ICD algorithm sensitivity and specificity. Sex- and age group-stratified IDU prevalences were also estimated. Compared with the misclassification-adjusted prevalence, unadjusted estimates were lower using the drug algorithm and higher using the combination algorithm. The median ME-adjusted IDU prevalence increased from 9.7% (95% Bayesian credible interval (BCI): 6.3, 14.8) in 2008 to 32.5% (95% BCI: 26.5, 38.2) in 2016. Among persons aged 18-34 years, IDU prevalence was higher in females than in males. ME adjustment in ICD-based studies of injection-related endocarditis is recommended.

Validity of Medical Record Abstraction and Electronic Health Record-Generated Reports to Assess Performance on Cardiovascular Quality Measures in Primary Care.

Importance: Cardiovascular disease is the leading cause of death in the United States. To improve cardiovascular outcomes, primary care must have valid methods of assessing performance on cardiovascular clinical quality measures, including aspirin use (aspirin measure), blood pressure control (BP measure), and smoking cessation counseling and intervention (smoking measure). Objective: To compare observed performance scores measured using 2 imperfect reference standard data sources (medical record abstraction [MRA] and electronic health record [EHR]-generated reports) with misclassification-adjusted performance scores obtained using bayesian latent class analysis. Design, Setting, and Participants: This cross-sectional study used a subset of the 2016 aspirin, BP, and smoking performance data from the Healthy Hearts for Oklahoma Project. Each clinical quality measure was calculated for a subset of a practice's patient population who can benefit from recommended care (ie, the eligible population). A random sample of 380 eligible patients were included for the aspirin measure; 126, for the BP measure; and 115, for the smoking measure. Data were collected from 21 primary care practices belonging to a single large health care system from January 1 to December 31, 2018, and analyzed from February 21 to April 17, 2019. Main Outcomes and Measures: The main outcomes include performance scores for the aspirin, BP, and smoking measures using imperfect MRA and EHRs and estimated through bayesian latent class models. Results: A total of 621 eligible patients were included in the analysis. Based on MRA and EHR data, observed aspirin performance scores were 76.0% (95% bayesian credible interval [BCI], 71.5%-80.1%) and 74.9% (95% BCI, 70.4%-79.1%), respectively; observed BP performance scores, 80.6% (95% BCI, 73.2%-86.9%) and 75.1% (95% BCI, 67.2%-82.1%), respectively; and observed smoking performance scores, 85.7% (95% BCI, 78.6%-91.2%) and 75.4% (95% BCI, 67.0%-82.6%), respectively. Misclassification-adjusted estimates were 74.9% (95% BCI, 70.5%-79.1%) for the aspirin performance score, 75.0% (95% BCI, 66.6%-82.5%) for the BP performance score, and 83.0% (95% BCI, 74.4%-89.8%) for the smoking performance score. Conclusions and Relevance: Ensuring valid performance measurement is critical for value-based payment models and quality improvement activities in primary care. This study found that extracting information for the same individuals using different data sources generated different performance score estimates. Further research is required to identify the sources of these differences.

Complementary Targeting of Rb Phosphorylation and Growth in Cervical Cancer Cell Cultures and a Xenograft Mouse Model by SHetA2 and Palbociclib.

Cervical cancer is caused by high-risk human papillomavirus (HPV) types and treated with conventional chemotherapy with surgery and/or radiation. HPV E6 and E7 proteins increase phosphorylation of retinoblastoma (Rb) by cyclin D1/cyclin dependent kinase (CDK)4/6 complexes. We hypothesized that cyclin D1 degradation by the SHetA2 drug in combination with palbociclib inhibition of CDK4/6 activity synergistically reduces phosphorylated Rb (phospho-Rb) and inhibits cervical cancer growth. The effects of these drugs, alone, and in combination, were evaluated in SiHa and CaSki HPV-positive and C33A HPV-negative cervical cancer cell lines using cell culture, western blots and ELISA, and in a SiHa xenograft model. Endpoints were compared by isobolograms, ANOVA, and Chi-Square. In all cell lines, combination indexes documented synergistic interaction of SHetA2 and palbociclib in association SHetA2 reduction of cyclin D1 and phospho-Rb, palbociclib reduction of phospho-Rb, and enhanced phospho-Rb reduction upon drug combination. Both drugs significantly reduced phospho-Rb and growth of SiHa xenograft tumors as single agents and acted additively when combined, with no evidence of toxicity. Dilated CD31-negative blood vessels adjacent to, or within, areas of necrosis and apoptosis were observed in all drug-treated tumors. These results justify development of the SHetA2 and palbociclib combination for targeting phospho-Rb in cervical cancer treatment.

Validity of ICD-based algorithms to estimate the prevalence of injection drug use among infective endocarditis hospitalizations in the absence of a reference standard.

BACKGROUND: International Classification of Diseases (ICD) code algorithms are routinely used to estimate the frequency of illicit injection drug use (IDU)-associated hospitalizations in administrative health datasets despite a lack of evidence regarding their validity. We aimed to measure the sensitivity and specificity of ICD code algorithms used to estimate the prevalence of current/recent IDU among infective endocarditis (IE) hospitalizations without a reference standard. METHODS: We reviewed medical records of 321 patients aged 18-64 years old from an urban academic hospital with an IE diagnosis between 2007 and 2017. Diagnostic tests for IDU included self-reported IDU in medical records; a drug use, abuse and dependence (UAD) ICD algorithm; a Hepatitis C Virus (HCV) ICD algorithm; and a combination drug UAD/HCV ICD algorithm. Sensitivity, specificity and the misclassification error (ME)-adjusted IDU prevalence were estimated using Bayesian latent class models. RESULTS: The combination algorithm had the highest sensitivity and lowest specificity. Sensitivity increased for the drug UAD algorithm in the ICD-10 period compared to the ICD-9 period. The ME-adjusted current/recent IDU prevalence estimated using the drug UAD and HCV algorithms was 23 % (95 % Bayesian credible interval: 16 %, 31 %). The unadjusted prevalence estimate from the drug UAD algorithm underestimated the ME-adjusted prevalence, while the combination algorithm overestimated it. CONCLUSION: The validity of ICD code algorithms for IDU among IE hospitalizations is imperfect and differs between ICD-9 and ICD-10. Commonly used ICD-based algorithms could lead to substantially biased prevalence estimates in IDU-associated hospitalizations when using administrative health data.

Validity of International Classification of Diseases codes in identifying illicit drug use target conditions using medical record data as a reference standard: A systematic review.

BACKGROUND: The twenty-first century opioid crisis has spurred interest in using International Classification of Diseases (ICD) code algorithms to identify patients using illicit drugs from administrative healthcare data. We conducted a systematic review of studies that validated ICD code algorithms for illicit drug use against a reference standard of medical record data. METHODS: Systematic searches of MEDLINE, EMBASE, PsycINFO, and Web of Science were conducted for studies published between 1980 and 2018 in English, French, Italian, or Spanish. We included validation studies of ICD-9 or ICD-10 code algorithms for an illicit drug use target condition (e.g., illicit drug use, abuse, or dependence (UAD), illicit drug use-related complications) given the sensitivity or specificity was reported or could be calculated. Bias was assessed with the Quality Assessment of Diagnostic Accuracy Studies Version 2 (QUADAS-2) tool. RESULTS: Six of the 1210 articles identified met the inclusion criteria. For validation studies of broad UAD (n = 4), the specificity was nearly perfect, but the sensitivity ranged from 47% to 83%, with higher sensitivities tending to occur in higher prevalence populations. For validation studies of injection drug use (IDU)-associated infective endocarditis (n = 2), sensitivity and specificity were poor due to the lack of an ICD code for IDU. For all six studies, the risk of bias for the QUADAS-2 "reference standard" and "flow/timing domains" was scored as "unclear" due to insufficient reporting. CONCLUSIONS: Few studies have validated ICD code algorithms for illicit drug use target conditions, and available evidence is challenging to interpret due to inadequate reporting. PROSPERO Registration: CRD42019118401.

Quantile Regression Analysis of Survey Data Under Informative Sampling.

For complex survey data, the parameters in a quantile regression can be estimated by minimizing an objective function with units weighted by the original design weights. However, when the complex survey sampling design is informative (i.e., when the design weights are correlated with the study variable even after conditioning on other covariates), the efficiency of this design-weighted estimator may be improved. In this article, we propose several weight-smoothing estimators for quantile regression analysis of complex survey data collected with an informative sampling design. Our new estimators incorporate nonparametric methods for modeling the weight functions and pseudo-population bootstrap methods for variance estimation. A simulation study compares, our proposed methods with the original design-based method in terms of bias, standard error, mean squared error, and confidence coverage. Our proposed estimators have smaller bias and mean squared error than does the design-based estimator. We further illustrate and compare estimators for the 1988 US National Maternal and Infant Health Survey.

A Non-invasive Liquid Biopsy Screening of Urine-Derived Exosomes for miRNAs as Biomarkers in Endometrial Cancer Patients.

Exosomes have great potential to serve as a source of diagnostic and prognostic biomarkers for endometrial cancer (EC). Urine-derived exosomes from patients with EC and patients with symptoms of EC, but without established EC, were used to evaluate a unique miRNA expression profile. Of the 84 miRNA studied, 57 were amplified in qPCR, suggesting the differential packaging of miRNA in exosomes. Further, hsa-miR-200c-3p was identified to be enriched the most. Various bioinformatics and in silico tools were used to evaluate the biological significance of hsa-miR-200c-3p in EC. We conclude that differential miRNA in exosomes can be utilized for discovery of biomarker signatures and EC diagnosis; hsa-miR-200c-3p is one such candidate. Urine-derived exosomes pave the way for the development of non-invasive biomarkers.

Exosomes as Theranostics for Lung Cancer.

Extensive research in genetics and genomics has revealed that lung cancer is a physiologically complex and genetically heterogeneous disease. Although molecular targets that can yield favorable response have been identified, those targets cannot be exploited due to the lack of suitable drug carriers. Furthermore, lung cancer often is diagnosed at an advanced stage when the disease has metastasized. Conventional treatments are not effective for treating metastatic lung cancer. Targeted therapeutics while beneficial has challenges that include poor tumor-targeting, off-target effects, and development of resistance to therapy. Therefore, improved drug delivery systems that can deliver drugs specifically to tumor will produce improved treatment outcomes. Exosomes have a natural ability to carry functional biomolecules, such as small RNAs, DNAs, and proteins, in their lumen. This property makes exosomes attractive for use in drug delivery and molecular diagnosis. Moreover, exosomes can be attached to nanoparticles and used for high precision imaging. Exosomes are now considered an important component in liquid biopsy assessments, which are useful for detecting cancers, including lung cancer. Several studies are currently underway to develop methods of exploiting exosomes for use as efficient drug delivery vehicles and to develop novel diagnostic modalities. This chapter summarizes the current status of exosome studies with regard to their use as theranostics in lung cancer. Examples from other cancers have also been cited to illustrate the extensive applicability of exosomes to therapy and diagnosis.

Clinicopathologic Features and Radiation Therapy Utilization in Patients with Male Breast Cancer: A National Cancer Database Study.

Male breast cancer (MBC) accounts for approximately 1% of all breast cancers, limiting the data characterizing clinicopathologic features and treatment outcomes in patients with MBC. This paucity of data has led to most of our treatment guidance being extrapolated from patients with female breast cancer (FBC). From 1998 to 2012, data were captured using the National Cancer Database to identify patients with nonmetastatic MBC (n = 23 305) and FBC (n = 2 678 061). Tumor and clinicopathologic features were obtained and compared. Patients with MBC were more likely to have invasive disease, T2-4 tumors, centrally located tumors, positive lymph nodes, estrogen receptor-positive or progesterone receptor-positive tumors, lymphovascular space invasion, and were less likely to have Her2/neu-positive or triple-negative tumors. All of these differences were statistically significant (P < .001). Treatment comparisons showed that patients with MBC were more likely to undergo mastectomy and less likely to undergo breast-conserving surgery with postoperative radiation utilization found to be less in patients with MBC, both as part of breast-conserving therapy (BCT) and for postmastectomy radiation treatment (PMRT) (P < .001). Stage-by-stage comparisons showed that median survival, 5-year, and 10-year overall survival (OS) rates are lower in patients with MBC vs patients with FBC (P < .001). The utilization of adjuvant radiation, both BCT and PMRT, was shown to improve 5- and 10-year OS (P < .001). Male breast cancer clinicopathologic features appear to be unfavorable in relation to FBC and adjuvant radiation is shown beneficial in survival outcomes. Further investigation is needed to help guide future utilization and treatment with radiation, systemic, and endocrine manipulation in this small population of patients with MBC.

HuR-targeted small molecule inhibitor exhibits cytotoxicity towards human lung cancer cells.

Human antigen (Hu) R is an RNA-binding protein whose overexpression in human cancer correlates with aggressive disease, drug resistance, and poor prognosis. HuR inhibition has profound anticancer activity. Pharmacologic inhibitors can overcome the limitations of genetic inhibition. In this study, we examined the antitumor activity of CMLD-2, a small-molecule inhibitor directed against HuR, using non-small cell lung cancer (NSCLC) as a model. CMLD-2 efficacy was tested in vitro using H1299, A549, HCC827, and H1975 NSCLC cells and MRC-9 and CCD-16 normal human fibroblasts. Treatment of NSCLC cells with CMLD-2 produced dose-dependent cytotoxicity, caused a G1 phase cell-cycle arrest and induced apoptosis. CMLD-2 decreased HuR mRNA and the mRNAs of HuR-regulated proteins (Bcl2 and p27) in tumor cells. Additionally, reduction in the expression of HuR, Bcl2, cyclin E, and Bcl-XL with increased expression of Bax and p27 in CMLD-2-treated NSCLC cells were observed. CMLD-2-treated normal cells, HuR-regulated mRNAs and proteins albeit showed some reduction were less compared to tumor cells. Finally, CMLD-2 treatment resulted in greater mitochondrial perturbation, activation of caspase-9 and -3 and cleavage of PARP in tumor cells compared to normal cells. Our proof-of concept study results demonstrate CMLD-2 represents a promising HuR-targeted therapeutic class that with further development could lead to advanced preclinical studied and ultimately for lung cancer treatment.

Strawberries Improve Pain and Inflammation in Obese Adults with Radiographic Evidence of Knee Osteoarthritis.

Osteoarthritis (OA), the most common form of arthritis, is a significant public health burden in U.S. adults. Among its many risk factors, obesity is a key player, causing inflammation, pain, impaired joint function, and reduced quality of life. Dietary polyphenols and other bioactive compounds in berries, curcumin, and tea have shown effects in ameliorating pain and inflammation in OA, but few clinical studies have been reported. The purpose of the present study was to examine the effects of dietary strawberries on pain, markers of inflammation, and quality of life indicators in obese adults with OA of the knee. In a randomized, double-blind cross-over trial, adults with radiographic evidence of knee OA (n = 17; body mass index (BMI): (mean ± SD) 39.1 ± 1.5; age (years): 57 ± 7) were randomized to a reconstituted freeze-dried strawberry beverage (50 g/day) or control beverage daily, each for 12 weeks, separated by a 2-week washout phase (total duration, 26 weeks). Blood draws and assessments of pain and quality of life indicators were conducted using the Visual Analog Scale for Pain (VAS Pain), Measures of Intermittent and Constant Osteoarthritis Pain (ICOAP), and Health Assessment Questionnaire-Disability Index (HAQ-DI) questionnaires, which were completed at baseline and at weeks 12, 14, and 26 of the study. Among the serum biomarkers of inflammation and cartilage degradation, interleukin (IL)-6, IL-1ß, and matrix metalloproteinase (MMP)-3 were significantly decreased after strawberry vs. control treatment (all p < 0.05). Strawberry supplementation also significantly reduced constant, intermittent, and total pain as evaluated by the ICOAP questionnaire as well as the HAQ-DI scores (all p < 0.05). No effects of treatment were noted on serum C-reactive protein (CRP), nitrite, glucose, and lipid profiles. Dietary strawberries may have significant analgesic and anti-inflammatory effects in obese adults with established knee OA.

Tumor-targeted Nanoparticle Delivery of HuR siRNA Inhibits Lung Tumor Growth In Vitro and In Vivo By Disrupting the Oncogenic Activity of the RNA-binding Protein HuR.

Selective downregulation of the human antigen R (HuR) protein by siRNA may provide a powerful approach for treating lung cancer. To this end, we investigated the efficacy of transferrin receptor-targeted liposomal nanoparticle-based HuR siRNA (HuR-TfNP) therapy and compared with control siRNA (C)-TfNP therapy both, in vitro and in vivo using lung cancer models. In vitro studies showed HuR-TfNP, but not C-TfNP, efficiently downregulated HuR and HuR-regulated proteins in A549, and HCC827 lung cancer cells, resulting in reduced cell viability, inhibition of cell migration and invasion, and induction of G1 cell-cycle arrest culminating in apoptosis. However, HuR-TfNP activity in normal MRC-9 lung fibroblasts was negligible. In vivo biodistribution study demonstrated that fluorescently labeled HuR-siRNA or ICG dye-loaded TfNP localized in tumor tissues. Efficacy studies showed intratumoral or intravenous administration of HuR-TfNP significantly inhibited A549 (>55% inhibition) and HCC827 (>45% inhibition) subcutaneous tumor growth compared with C-TfNP. Furthermore, HuR-TfNP treatment reduced HuR, Ki67, and CD31 expression and increased caspase-9 and PARP cleavage and TUNEL-positive staining indicative of apoptotic cell death in tumor tissues compared with C-TfNP treatment. The antitumor activity of HuR-TfNP was also observed in an A549-luc lung metastatic model, as significantly fewer tumor nodules (9.5 ± 3.1; P < 0.001; 88% inhibition) were observed in HuR-TfNP-treated group compared with the C-TfNP-treated group (77.7 ± 20.1). Significant reduction in HuR, Ki67, and CD31 expression was also observed in the tumor tissues of HuR-TfNP-treatment compared with C-TfNP treatment. Our findings highlight HuR-TfNP as a promising nanotherapeutic system for lung cancer treatment. Mol Cancer Ther; 16(8); 1470-86. ©2017 AACR.

Nanosomes carrying doxorubicin exhibit potent anticancer activity against human lung cancer cells.

Successful chemotherapeutic intervention for management of lung cancer requires an efficient drug delivery system. Gold nanoparticles (GNPs) can incorporate various therapeutics; however, GNPs have limitations as drug carriers. Nano-sized cellular vesicles like exosomes (Exo) can ferry GNP-therapeutic complexes without causing any particle aggregation or immune response. In the present study, we describe the development and testing of a novel Exo-GNP-based therapeutic delivery system -'nanosomes'- for lung cancer therapy. This system consists of GNPs conjugated to anticancer drug doxorubicin (Dox) by a pH-cleavable bond that is physically loaded onto the exosomes (Exo-GNP-Dox). The therapeutic efficacy of Dox in nanosomes was assessed in H1299 and A549 non-small cell lung cancer cells, normal MRC9 lung fibroblasts, and Dox-sensitive human coronary artery smooth muscle cells (HCASM). The enhanced rate of drug release under acidic conditions, successful uptake of the nanosomes by the recipient cells and the cell viability assays demonstrated that nanosomes exhibit preferential cytotoxicity towards cancer cells and have minimal activity on non-cancerous cells. Finally, the underlying mechanism of cytotoxicity involved ROS-mediated DNA damage. Results from this study mark the establishment of an amenable drug delivery vehicle and highlight the advantages of a natural drug carrier that demonstrates reduced cellular toxicity and efficient delivery of therapeutics to cancer cells.