Identification of Key Molecular Pathways and Associated Genes as Targets to Overcome Radiotherapy Resistance Using a Combination of Radiotherapy and Immunotherapy in Glioma Patients.

Recent mechanistic studies have indicated that combinations of radiotherapy (RT) plus immunotherapy (via CSF-1R inhibition) can serve as a strategy to overcome RT resistance and improve the survival of glioma mice. Given the high mortality rate for glioma, including low-grade glioma (LGG) patients, it is of critical importance to investigate the mechanism of the combination of RT and immunotherapy and further translate the mechanism from mouse studies to improve survival of RT-treated human glioma patients. Using the RNA-seq data from a glioma mouse study, 874 differentially expressed genes (DEGs) between the group of RT-treated mice at glioma recurrence and the group of mice with combination treatment (RT plus CSF-1R inhibition) were translated to the human genome to identify significant molecular pathways using the KEGG enrichment analysis. The enrichment analysis yields statistically significant signaling pathways, including the phosphoinositide 3-kinase (PI3K)/AKT pathway, Hippo pathway, and Notch pathway. Within each pathway, a candidate gene set was selected by Cox regression models as genetic biomarkers for resistance to RT and response to the combination of RT plus immunotherapies. Each Cox model is trained using a cohort of 295 RT-treated LGG patients from The Cancer Genome Atlas (TCGA) database and validated using a cohort of 127 RT-treated LGG patients from the Chinese Glioma Genome Atlas (CGGA) database. A four-DEG signature (ITGB8, COL9A3, TGFB2, JAG1) was identified from the significant genes within the three pathways and yielded the area under time-dependent ROC curve AUC = 0.86 for 5-year survival in the validation set, which indicates that the selected DEGs have strong prognostic value and are potential intervention targets for combination therapies. These findings may facilitate future trial designs for developing combination therapies for glioma patients.

Identification of memory B-cell-associated miRNA signature to establish a prognostic model in gastric adenocarcinoma.

BACKGROUND: Memory B cells and microRNAs (miRNAs) play important roles in the progression of gastric adenocarcinoma (GAC), also known as stomach adenocarcinoma (STAD). However, few studies have investigated the use of memory B-cell-associated miRNAs in predicting the prognosis of STAD. METHODS: We identified the marker genes of memory B cells by single-cell RNA sequencing (scRNA-seq) and identified the miRNAs associated with memory B cells by constructing an mRNA‒miRNA coexpression network. Then, univariate Cox, random survival forest (RSF), and stepwise multiple Cox regression (StepCox) algorithms were used to identify memory B-cell-associated miRNAs that were significantly related to overall survival (OS). A prognostic risk model was constructed and validated using these miRNAs, and patients were divided into a low-risk group and a high-risk group. In addition, the differences in clinicopathological features, tumour microenvironment, immune blocking therapy, and sensitivity to anticancer drugs in the two groups were analysed. RESULTS: Four memory B-cell-associated miRNAs (hsa-mir-145, hsa-mir-125b-2, hsa-mir-100, hsa-mir-221) with significant correlations to OS were identified and used to construct a prognostic model. Time-dependent receiver operating characteristic (ROC) curve analysis confirmed the feasibility of the model. Kaplan‒Meier (K‒M) survival curve analysis showed that the prognosis was poor in the high-risk group. Comprehensive analysis showed that patients in the high-risk group had higher immune scores, matrix scores, and immune cell infiltration and a poor immune response. In terms of drug screening, we predicted eight drugs with higher sensitivity in the high-risk group, of which CGP-60474 was associated with the greatest sensitivity. CONCLUSIONS: In summary, we identified memory B-cell-associated miRNA prognostic features and constructed a novel risk model for STAD based on scRNA-seq data and bulk RNA-seq data. Among patients in the high-risk group, STAD showed the highest sensitivity to CGP-60474. This study provides prognostic insights into individualized and precise treatment for STAD patients.

Virus Control in Vaccinated Rhesus Macaques Is Associated with Neutralizing and Capturing Antibodies against the SHIV Challenge Virus but Not with V1V2 Vaccine-Induced Anti-V2 Antibodies Alone.

The role of vaccine-induced anti-V2 Abs was tested in three protection experiments in rhesus macaques. In an experiment using immunogens similar to those in the RV144 vaccine trial (Anti-envelope [Env]), nine rhesus macaques were coimmunized with gp16092TH023 DNA and SIV gag and gp120A244 and gp120MN proteins. In two V2-focused experiments (Anti-V2 and Anti-V2 Mucosal), nine macaques in each group were immunized with V1V292TH023 DNA, V1V2A244 and V1V2CasaeA2 proteins, and cyclic V2CaseA2 peptide. DNA and protein immunogens, formulated in Adjuplex, were given at 0, 4, 12, and 20 weeks, followed by intrarectal SHIVBaL.P4 challenges. Peak plasma viral loads (PVL) of 106-107 copies/ml developed in all nine sham controls. Overall, PVL was undetectable in one third of immunized macaques, and two animals tightly controlled the virus with the Anti-V2 Mucosal vaccine strategy. In the Anti-Env study, Abs that captured or neutralized SHIVBaL.P4 inversely correlated with PVL. Conversely, no correlation with PVL was found in the Anti-V2 experiments with nonneutralizing plasma Abs that only captured virus weakly. Titers of Abs against eight V1V2 scaffolds and cyclic V2 peptides were comparable between controllers and noncontrollers as were Ab-dependent cellular cytotoxicity and Ab-dependent cell-mediated virus inhibition activities against SHIV-infected target cells and phagocytosis of gp120-coated beads. The Anti-Env experiment supports the role of vaccine-elicited neutralizing and nonneutralizing Abs in control of PVL. However, the two V2-focused experiments did not support a role for nonneutralizing V2 Abs alone in controlling PVL, as neither Ab-dependent cellular cytotoxicity, Ab-dependent cell-mediated virus inhibition, nor phagocytosis correlated inversely with heterologous SHIVBaL.P4 infection.

Impact of white matter hyperintensities on subjective cognitive decline phenotype in a diverse cohort of cognitively normal older adults.

OBJECTIVES: Subjective cognitive decline (SCD) is a preclinical stage of AD. White matter hyperintensities (WMH), an MRI marker of cerebral small vessel disease, associate with AD biomarkers and progression. The impact of WMH on SCD phenotype is unclear. METHODS/DESIGN: A retrospective, cross-sectional analysis was conducted on a diverse cohort with SCD evaluated at the NYU Alzheimer's Disease Research Center between January 2017 and November 2021 (n = 234). The cohort was dichotomized into none-to-mild (n = 202) and moderate-to-severe (n = 32) WMH. Differences in SCD and neurocognitive assessments were evaluated via Wilcoxon or Fisher exact tests, with p-values adjusted for demographics using multivariable logistic regression. RESULTS: Moderate-to-severe WMH participants reported more difficulty with decision making on the Cognitive Change Index (1.5 SD 0.7 vs. 1.2 SD 0.5, p = 0.0187) and worse short-term memory (2.2 SD 0.4 vs. 1.9 SD 0.3, p = 0.0049) and higher SCD burden (9.5 SD 1.6 vs. 8.7 SD 1.7, p = 0.0411) on the Brief Cognitive Rating Scale. Moderate-to-severe WMH participants scored lower on the Mini-Mental State Examination (28.0 SD 1.6 vs. 28.5 SD 1.9, p = 0.0491), and on delayed paragraph (7.2 SD 2.0 vs. 8.8 SD 2.9, p = 0.0222) and designs recall (4.5 SD 2.3 vs. 6.1 SD 2.5, p = 0.0373) of the Guild Memory Test. CONCLUSIONS: In SCD, WMH impact overall symptom severity, specifically in executive and memory domains, as well as objective performance on global and domain-specific tests in verbal memory and visual working/associative memory.

Integrated partially linear model for multi-center studies with heterogeneity and batch effect in covariates.

The design of multi-center study is increasingly used for borrowing strength from multiple research groups to obtain broadly applicable and reproducible study findings. Regression analysis is widely used for analyzing multi-group studies, however, some of the large number of regression predictors are nonlinear and/or often measured with batch effects in many large scale collaborative studies. Also, the group compositions of the nonlinear predictors are potentially heterogeneous across different centers. The conventional pooled data analysis ignores the interplay between nonlinearity and batch effect, group composition heterogeneity, measurement error and other data incoherence in multi-center setting that can cause biased regression estimates and misleading outcomes. In this paper, we propose an integrated partially linear regression model (IPLM) based analysis to account for the predictor's nonlinearity, general batch effect, group composition heterogeneity, high-dimensional covariates, potential measurement-error in covariates, and combinations of these complexities simultaneously. A local linear regression based approach is employed to estimate the nonlinear component and a regularization procedure is introduced to identify the predictors' effects that can be either homogeneous or heterogeneous across groups. In particular, when the effects of all predictors are homogeneous across the study centers, the proposed IPLM can automatically reduce to one single parsimonious partially linear model for all centers. The proposed method has asymptotic estimation and variable selection consistency including high-dimensional covariates. Moreover, it has a fast computing algorithm and its effectiveness is supported by numerical simulation studies. A multi-center Alzheimer's disease research project is provided to illustrate the proposed IPLM based analysis.

Innate immunity stimulation via CpG oligodeoxynucleotides ameliorates Alzheimer's disease pathology in aged squirrel monkeys.

Alzheimer's disease is the most common cause of dementia and the only illness among the top 10 causes of death for which there is no disease-modifying therapy. The failure rate of clinical trials is very high, in part due to the premature translation of successful results in transgenic mouse models to patients. Extensive evidence suggests that dysregulation of innate immunity and microglia/macrophages plays a key role in Alzheimer's disease pathogenesis. Activated resident microglia and peripheral macrophages can display protective or detrimental phenotypes depending on the stimulus and environment. Toll-like receptors (TLRs) are a family of innate immune regulators known to play an important role in governing the phenotypic status of microglia. We have shown in multiple transgenic Alzheimer's disease mouse models that harnessing innate immunity via TLR9 agonist CpG oligodeoxynucleotides (ODNs) modulates age-related defects associated with immune cells and safely reduces amyloid plaques, oligomeric amyloid-ß, tau pathology, and cerebral amyloid angiopathy (CAA) while promoting cognitive benefits. In the current study we have used a non-human primate model of sporadic Alzheimer's disease pathology that develops extensive CAA-elderly squirrel monkeys. The major complications in current immunotherapeutic trials for Alzheimer's disease are amyloid-related imaging abnormalities, which are linked to the presence and extent of CAA; hence, the prominence of CAA in elderly squirrel monkeys makes them a valuable model for studying the safety of the CpG ODN-based concept of immunomodulation. We demonstrate that long-term use of Class B CpG ODN 2006 induces a favourable degree of innate immunity stimulation without producing excessive or sustained inflammation, resulting in efficient amelioration of both CAA and tau Alzheimer's disease-related pathologies in association with behavioural improvements and in the absence of microhaemorrhages in aged elderly squirrel monkeys. CpG ODN 2006 has been well established in numerous human trials for a variety of diseases. The present evidence together with our earlier, extensive preclinical research, validates the beneficial therapeutic outcomes and safety of this innovative immunomodulatory approach, increasing the likelihood of CpG ODN therapeutic efficacy in future clinical trials.

The ROC of Cox proportional hazards cure models with application in cancer studies.

With recent advancement in cancer screening and treatment, many patients with cancers are identified at early stage and clinically cured. Importantly, uncured patients should be treated timely before the cancer progresses to advanced stages for which therapeutic options are rather limited. It is also crucial to identify uncured subjects among patients with early-stage cancers for clinical trials to develop effective adjuvant therapies. Thus, it is of interest to develop statistical predictive models with as high accuracy as possible in predicting the latent cure status. The receiver operating characteristic curve (ROC) and the area under the ROC curve (AUC) are among the most widely used statistical metrics for assessing predictive accuracy or discriminatory power for a dichotomous outcome (cured/uncured). Yet the conventional AUC cannot be directly used due to incompletely observed cure status. In this article, we proposed new estimates of the ROC curve and its AUC for predicting latent cure status in Cox proportional hazards (PH) cure models and transformation cure models. We developed explicit formulas to estimate sensitivity, specificity, the ROC and its AUC without requiring to know the patient cure status. We also developed EM type estimates to approximate sensitivity, specificity, ROC and AUC conditional on observed data. Numerical studies were used to assess their finite-sample performance of the proposed methods. Both methods are consistent and have similar efficiency as shown in our numerical studies. A melanoma dataset was used to demonstrate the utility of the proposed estimates of the ROC curve for the latent cure status. We also have developed an [Formula: see text] package called [Formula: see text] to efficiently compute the proposed estimates.

Mediterranean Diet and the Association Between Air Pollution and Cardiovascular Disease Mortality Risk.

BACKGROUND: Recent experimental evidence suggests that nutritional supplementation can blunt adverse cardiopulmonary effects induced by acute air pollution exposure. However, whether usual individual dietary patterns can modify the association between long-term air pollution exposure and health outcomes has not been previously investigated. We assessed, in a large cohort with detailed diet information at the individual level, whether a Mediterranean diet modifies the association between long-term exposure to ambient air pollution and cardiovascular disease mortality risk. METHODS: The National Institutes of Health-American Association for Retired Persons Diet and Health Study, a prospective cohort (N=548 845) across 6 states and 2 cities in the United States and with a follow-up period of 17 years (1995-2011), was linked to estimates of annual average exposures to fine particulate matter and nitrogen dioxide at the residential census-tract level. The alternative Mediterranean Diet Index, which uses a 9-point scale to assess conformity with a Mediterranean-style diet, was constructed for each participant from information in cohort baseline dietary questionnaires. We evaluated mortality risks for cardiovascular disease, ischemic heart disease, cerebrovascular disease, or cardiac arrest associated with long-term air pollution exposure. Effect modification of the associations between exposure and the mortality outcomes by alternative Mediterranean Diet Index was examined via interaction terms. RESULTS: For fine particulate matter, we observed elevated and significant associations with cardiovascular disease (hazard ratio [HR] per 10 µg/m3, 1.13; 95% CI, 1.08-1.18), ischemic heart disease (HR, 1.16; 95% CI, 1.10-1.23), and cerebrovascular disease (HR, 1.15; 95% CI, 1.03-1.28). For nitrogen dioxide, we found significant associations with cardiovascular disease (HR per 10 ppb, 1.06; 95% CI, 1.04-1.08) and ischemic heart disease (HR, 1.08; 95% CI, 1.05-1.11). Analyses indicated that Mediterranean diet modified these relationships, as those with a higher alternative Mediterranean Diet Index score had significantly lower rates of cardiovascular disease mortality associated with long-term air pollution exposure ( P-interaction<0.05). CONCLUSIONS: A Mediterranean diet reduced cardiovascular disease mortality risk related to long-term exposure to air pollutants in a large prospective US cohort. Increased consumption of foods rich in antioxidant compounds may aid in reducing the considerable disease burden associated with ambient air pollution.

A numerical strategy to evaluate performance of predictive scores via a copula-based approach.

Assessing and comparing the performance of correlated predictive scores are of current interest in precision medicine. Given the limitations of available theoretical approaches for assessing and comparing the predictive accuracy, numerical methods are highly desired which, however, have not been systematically developed due to technical challenges. The main challenges include the lack of a general strategy on effectively simulating many kinds of correlated predictive scores each with some given level of predictive accuracy in either concordance index or the area under a receiver operating characteristic curve area under the curves (AUC). To fill in this important knowledge gap, this paper is to provide a general copula-based numeric framework for assessing and comparing predictive performance of correlated predictive or risk scores. The new algorithms are designed to effectively simulate correlated predictive scores with given levels of predictive accuracy as measured in terms of concordance indices or time-dependent AUC for predicting survival outcomes. The copula-based numerical strategy is convenient for numerically evaluating and comparing multiple measures of predictive accuracy of correlated risk scores and for investigating finite-sample properties of test statistics and confidence intervals as well as assessing for optimism of given performance measures using cross-validation or bootstrap.

Psychometric Cognitive Decline Precedes the Advent of Subjective Cognitive Decline in the Evolution of Alzheimer's Disease.

BACKGROUND: We have described the clinical stages of the brain aging and Alzheimer's disease (AD) continuum. In terms of the pre-dementia stages of AD, we introduced the terminology "mild cognitive impairment" (MCI) for the first pre-dementia stage and "subjective cognitive decline" (SCD) for the pre-MCI stage. We now report the characteristics of a pre-SCD condition eventuating in likely AD. OBJECTIVE: The aim of this study was to characterize a pre-SCD condition eventuating in AD. METHOD: Sixty healthy persons with "no cognitive decline" (NCD) were recruited and 47 were followed (mean baseline age, 64.1 ± 8.9 years; mean follow-up time, 6.7 ± 3.1 years). Outcome was determined at the final assessment prior to 2002 as "decliner," if SCD or worse, or "nondecliner" if NCD. RESULTS: After controlling for age, gender, years of education, and follow-up time, there was a between-group difference in the decline rate (p < 0.001). Also, after controlling for demographic variables and follow-up time, the combinatorial psychometric score was lower at baseline in the future decliners (p = 0.035). Of the 9 psychometric variables, after controlling for demographic variables and follow-up time, 3 were significantly lower at baseline in future decliners. Since AD is known to be age related and all subjects in this study were otherwise healthy, we also did an analysis without controlling for age. The combinatorial psychometric score was highly significantly better at baseline in the future nondecliners than in the future decliners (p = 0.008). CONCLUSION: This is ostensibly the first study to link psychometric cognitive decline to the subsequent SCD stage of eventual AD.

Long-Term Exposure to Ozone and Cause-Specific Mortality Risk in the United States.

Rationale: Many studies have linked short-term exposure to ozone (O3) with morbidity and mortality, but epidemiologic evidence of associations between long-term O3 exposure and mortality is more limited.Objectives: To investigate associations of long-term (annual or warm season average of daily 8-h maximum concentrations) O3 exposure with all-cause and cause-specific mortality in the NIH-AARP Diet and Health Study, a large prospective cohort of U.S. adults with 17 years of follow-up from 1995 to 2011.Methods: The cohort (n = 548,780) was linked to census tract-level estimates for O3. Associations between long-term O3 exposure (averaged values from 2002 to 2010) and multiple causes of death were evaluated using multivariate Cox proportional hazards models, adjusted for individual- and census tract-level covariates, and potentially confounding copollutants and temperature.Measurements and Main Results: Long-term annual average exposure to O3 was significantly associated with deaths caused by cardiovascular disease (per 10 ppb; hazard ratio [HR], 1.03; 95% confidence interval [CI], 1.01-1.06), ischemic heart disease (HR, 1.06; 95% CI, 1.02-1.09), respiratory disease (HR, 1.04; 95% CI, 1.00-1.09), and chronic obstructive pulmonary disease (HR, 1.09; 95% CI, 1.03-1.15) in single-pollutant models. The results were robust to alternative models and adjustment for copollutants (fine particulate matter and nitrogen dioxide), although some evidence of confounding by temperature was observed. Significantly elevated respiratory disease mortality risk associated with long-term O3 exposure was found among those living in locations with high temperature (Pinteraction < 0.05).Conclusions: This study found that long-term exposure to O3 is associated with increased risk for multiple causes of mortality, suggesting that establishment of annual and/or seasonal federal O3 standards is needed to more adequately protect public health from ambient O3 exposures.

Concordance measure and discriminatory accuracy in transformation cure models.

Many populations of early-stage cancer patients have non-negligible latent cure fractions that can be modeled using transformation cure models. However, there is a lack of statistical metrics to evaluate prognostic utility of biomarkers in this context due to the challenges associated with unknown cure status and heavy censorship. In this article, we develop general concordance measures as evaluation metrics for the discriminatory accuracy of transformation cure models including the so-called promotion time cure models and mixture cure models. We introduce explicit formulas for the consistent estimates of the concordance measures, and show that their asymptotically normal distributions do not depend on the unknown censoring distribution. The estimates work for both parametric and semiparametric transformation models as well as transformation cure models. Numerical feasibility of the estimates and their robustness to the censoring distributions are illustrated via simulation studies and demonstrated using a melanoma data set.

Multicellular gene network analysis identifies a macrophage-related gene signature predictive of therapeutic response and prognosis of gliomas.

BACKGROUND: The tumor-associated microenvironment plays important roles in tumor progression and drug resistance. However, systematic investigations of macrophage-tumor cell interactions to identify novel macrophage-related gene signatures in gliomas for predicting patient prognoses and responses to targeted therapies are lacking. METHODS: We developed a multicellular gene network approach to investigating the prognostic role of macrophage-tumor cell interactions in tumor progression and drug resistance in gliomas. Multicellular gene networks connecting macrophages and tumor cells were constructed from re-grouped drug-sensitive and drug-resistant samples of RNA-seq data in mice gliomas treated with BLZ945 (a CSF1R inhibitor). Subsequently, a differential network-based COX regression model was built to identify the risk signature using a cohort of 310 glioma samples from the Chinese Glioma Genome Atlas database. A large independent validation set of 690 glioma samples from The Cancer Genome Atlas database was used to test the prognostic significance and accuracy of the gene signature in predicting prognosis and targeted therapeutic response of glioma patients. RESULTS: A macrophage-related gene signature was developed consisting of twelve genes (ANPEP, DPP4, PRRG1, GPNMB, TMEM26, PXDN, CDH6, SCN3A, SEMA6B, CCDC37, FANCA, NETO2), which was tested in the independent validation set to examine its prognostic significance and accuracy. The generation of 1000 random gene signatures by a bootstrapping scheme justified the non-random nature of the macrophage-related gene signature. Moreover, the discovered gene signature was verified to be predictive of the sensitivity or resistance of glioma patients to molecularly targeted therapeutics and outperformed other existing gene signatures. Additionally, the macrophage-related gene signature was an independent and the strongest prognostic factor when adjusted for clinicopathologic risk factors and other existing gene signatures. CONCLUSION: The multicellular gene network approach developed herein indicates profound roles of the macrophage-mediated tumor microenvironment in the progression and drug resistance of gliomas. The identified macrophage-related gene signature has good prognostic value for predicting resistance to targeted therapeutics and survival of glioma patients, implying that combining current targeted therapies with new macrophage-targeted therapy may be beneficial for the long-term treatment outcomes of glioma patients.

Serum perfluoroalkyl substances and lung function in adolescents exposed to the World Trade Center disaster.

The effects of childhood exposure to perfluoroalkyl substances (PFASs) on lung function remain mostly unknown. Previous research indicates that children living or going to school near the World Trade Center (WTC) disaster were exposed to high levels of PFASs, among other toxic chemicals. To explore the effects of PFAS exposure on lung function, we measured serum PFASs in a cohort of children from the WTC Health Registry and a matched control group. Perfluorooctanesulfonate had the highest median concentrations in both groups (WTCHR = 3.72 ng/mL, Comparison = 2.75 ng/mL), while the lowest median concentrations were seen for perfluoroundecanoic acid (WTCHR = 0.12 ng/mL, Comparison = 0.01 ng/mL). Lung function outcomes were measured by spirometry, plethysmography, and oscillometry. Asthma diagnosis and serum eosinophil count were also recorded. We examined the relationships of each PFAS with lung function parameters and eosinophil count using linear regressions. Odds ratios for asthma were obtained for each PFAS using logistic regression. The effect of total PFASs on these outcomes was also assessed. All regression models were adjusted for sex, race/ethnicity, age, body mass index (BMI) and tobacco smoke exposure. We found that serum PFASs were not statistically associated with the measured lung function parameters, asthma diagnosis, or eosinophil count in this cohort (p < 0.05). These findings highlight the need for more longitudinal studies to explore the long-term effects of childhood PFAS exposure on lung function past adolescence and early adulthood.

Respiratory Health and Lung Function in Children Exposed to the World Trade Center Disaster.

OBJECTIVES: To compare lung function in a representative sample of World Trade Center (WTC)-exposed children with matched comparisons, and examine relationships with reported exposures. STUDY DESIGN: Study population consisted of 402 participants. Oscillometry, spirometry, and plethysmography were performed on WTC Health Registry (WTCHR) respondents who were ≤8 years of age on September 11, 2001 (n = 180) and a sociodemographically matched group of New York City residents (n = 222). We compared lung function by study arm (WTCHR and comparison group) as well as dust cloud (acute); home dust (subchronic); and other traumatic, nondust exposures. RESULTS: In multivariable models, post-9/11 risk of incident asthma was higher in the WTCHR participants than in the comparison group (OR 1.109, 95% CI 1.021, 1.206; P = .015). Comparing by exposure rather than by group, dust cloud (OR 1.223, 95% CI 1.095, 1.365; P < .001) and home dust (OR 1.123, 95% CI 1.029, 1.226; P = .009) exposures were also associated with a greater risk of incidence of post-9/11 asthma. No differences were identified for lung function measures. CONCLUSIONS: Although we cannot exclude an alternative explanation to the null findings, these results may provide some measure of reassurance to exposed children and their families regarding long-term consequences. Further study with bronchodilation and/or methacholine challenge may be needed to identify and further evaluate effects of WTC exposure. Biomarker studies may also be more informative in delineating exposure-outcome relationships. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02068183.

Association between Ki-67 expression and clinical outcomes among patients with clinically node-negative, thick primary melanoma who underwent nodal staging.

BACKGROUND: Patients with thick primary melanomas (≥4 mm) have highly variable survival outcomes. Cell proliferation marker Ki-67 has been identified as promising biomarker in thick melanoma but has not been evaluated since the wide spread adoption of sentinel lymph node biopsy. We revisit its prognostic relevance in the sentinel node era. METHODS: We studied patients with thick (≥4 mm) primary melanoma prospectively enrolled in a clinicopathological biospecimen database from 2002 to 2015, and evaluated the prognostic value of Ki-67 expression while controlling for features included in the existing staging criteria. RESULTS: We analyzed 68 patients who underwent lymph node sampling and who had an available tumor for Ki-67 immunohistochemical (IHC) staining. The median tumor thickness was 6.0 mm; the median follow-up was 2.6 years. In multivariable analysis including nodal status and primary tumor ulceration, Ki-67 expression was an independent predictor of worse recurrence-free survival (HR 2.19, P = 0.024) and overall survival (HR 2.49, P = 0.028). Natural log-transformed tumor thickness (ln [thickness]) was also significantly associated with worse OS (HR 2.39, P = 0.010). CONCLUSION: We identify Ki-67 and ln (thickness) as potential biomarkers for patients with thick melanoma who have undergone nodal staging. If validated in additional studies, these biomarkers could be integrated into the staging criteria to improve risk-stratification.

Cardiometabolic profiles of adolescents and young adults exposed to the World Trade Center Disaster.

BACKGROUND AND OBJECTIVE: Few studies have examined the possible cardiometabolic consequences of World Trade Center-related exposures on children who lived and/or attended school near the disaster site. Our objective was to compare cardiometabolic profiles of participants in the World Trade Center Health Registry (WTCHR) with a matched comparison group. METHODS: We evaluated WTCHR enrollees who resided in New York City and were born between September 11, 1993 and September 10, 2001, and a matched comparison group. We assessed exposure to dust cloud, home dust, as well as traumatic exposure, and associations with blood pressure, arterial wall stiffness, body mass index (BMI), total cholesterol, triglycerides, HDL, and LDL. RESULTS: A total of 402 participants completed the study, 222 in the comparison group and 180 in the WTCHR group. In multivariable regression analysis, after adjusting for relevant confounders we detected a weak association between participation in the WTCHR group and lower BMI (-1.12kg/m2, 95% CI -2.11, -0.12; p = 0.03), which became non-significant after adjusting for multiple comparisons. With respect to traumatic and psychosocial exposures, the only association that persisted in our multivariable model, below our predefined level of significance, was between post-traumatic stress disorder and higher BMI (2.06kg/m2, 95% CI 0.37, 3.74; p = 0.02). CONCLUSIONS: Our findings do not support an association between self-reported exposures to the WTC disaster and adverse cardiometabolic profile. However, further longitudinal studies may better inform the full extent of WTC-related conditions associated with exposure to the disaster.

Association between long-term exposure to ambient air pollution and diabetes mortality in the US.

OBJECTIVE: Recent mechanistic and epidemiological evidence implicates air pollution as a potential risk factor for diabetes; however, mortality risks have not been evaluated in a large US cohort assessing exposures to multiple pollutants with detailed consideration of personal risk factors for diabetes. RESEARCH DESIGN AND METHODS: We assessed the effects of long-term ambient air pollution exposures on diabetes mortality in the NIH-AARP Diet and Health Study, a cohort of approximately a half million subjects across the contiguous U.S. The cohort, with a follow-up period between 1995 and 2011, was linked to residential census tract estimates for annual mean concentration levels of PM2.5, NO2, and O3. Associations between the air pollutants and the risk of diabetes mortality (N = 3598) were evaluated using multivariate Cox proportional hazards models adjusted for both individual-level and census-level contextual covariates. RESULTS: Diabetes mortality was significantly associated with increasing levels of both PM2.5 (HR = 1.19; 95% CI: 1.03-1.39 per 10 µg/m3) and NO2 (HR = 1.09; 95% CI: 1.01-1.18 per 10 ppb). The strength of the relationship was robust to alternate exposure assessments and model specifications. We also observed significant effect modification, with elevated mortality risks observed among those with higher BMI and lower levels of fruit consumption. CONCLUSIONS: We found that long-term exposure to PM2.5 and NO2, but not O3, is related to increased risk of diabetes mortality in the U.S, with attenuation of adverse effects by lower BMI and higher fruit consumption, suggesting that air pollution is involved in the etiology and/or control of diabetes.

Functional variant analyses (FVAs) predict pathogenicity in the BRCA1 DNA double-strand break repair pathway.

Heritable mutations in the BRCA1 and BRCA2 and other genes in the DNA double-strand break (DSB) repair pathway disrupt binding of the encoded proteins, transport into the nucleus and initiation of homologous recombination, thereby increasing cancer risk [Scully, R., Chen, J., Plug, A., Xiao, Y., Weaver, D., Feunteun, J., Ashley, T. and Livingston, D.M. (1997) Association of BRCA1 with Rad51 in mitotic and meiotic cells. Cell, 88, 265-275, Chen, J., Silver, D.P., Walpita, D., Cantor, S.B., Gazdar, A.F., Tomlinson, G., Couch, F.J., Weber, B.L., Ashley, T., Livingston, D.M. et al. (1998) Stable interaction between the products of the BRCA1 and BRCA2 tumor suppressor genes in mitotic and meiotic cells. Mol. Cell, 2, 317-328]. To meet the challenge of correct classification, flow cytometry-based functional variant analyses (FVAs) were developed to determine whether variants in DSB repair genes disrupted the binding of BRCA1 to BARD1, PALB2, BRCA2 and FANCD2, phosphorylation of p53 or BRCA1 nuclear localization in response to DNA damage caused by diepoxybutane, mitomycin C and bleomycin. Lymphoblastoid cells from individuals with BRCA1 pathogenic mutations, benign variants, and variants of uncertain significance or with known BRCA2, FANCC or NBN mutations were tested. Mutations in BRCA1 decreased nuclear localization of BRCA1 in response to individual or combination drug treatment. Mutations in BRCA1 reduced binding to co-factors, PALB2 and FANCD2 and decreased phosphorylation of p53. Mutations in BRCA2, FANCC and NBN decreased nuclear localization of BRCA1 in response to drug treatment, cofactors binding and p53 phosphorylation. Unsupervised cluster analysis of all and as few as two assays demonstrated two apparent clusters, high-risk BRCA1 mutations and phenocopies and low-risk, fully sequenced controls and variants of uncertain significance (VUS). Thus, two FVA assays distinguish BRCA1 mutations and phenocopies from benign variants and categorize most VUS as benign. Mutations in other DSB repair pathway genes produce molecular phenocopies. FVA assays may represent an adjunct to sequencing for categorizing VUS or may represent a stand-alone measure for assessing breast cancer risk.

Prediction of breast cancer risk based on flow-variant analysis of circulating peripheral blood B cells.

PURPOSE: Identifying women at high risk for breast cancer can trigger a personal program of annual mammograms and magnetic resonance imaging scans for early detection, prophylactic surgery, or chemoprevention to reduce the risk of cancer. Yet, current strategies to identify high-risk mutations based on sequencing panels of genes have significant false-positive and false-negative results, suggesting the need for alternative approaches. METHODS: Flow-variant assays (FVAs) that assess the effects of mutations in the double-strand break (DSB) repair genetic pathway in lymphoblastoid cells in response to treatment with radiomimetic agents were assessed for sensitivity, specificity, and accuracy both alone and as part of a logistic regression classification score. In turn, these assays were validated in circulating B cells and applied to individuals with personal and/or family history of breast and/or ovarian cancer. RESULTS: A three-FVA classification score based on logistic regression had 95% accuracy. Individuals from a breast cancer-positive cohort with affected family members had high-risk FVA classification scores. CONCLUSION: Application of a classification score based on multiple FVAs could represent an alternative to panel sequencing for identifying women at high risk for cancer.Genet Med advance online publication 16 March 2017.