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Our purpose was to evaluate the effect of sequence and type of adjuvant therapy for patients with stage IIIC endometrial carcinoma (EC) on outcomes.In a multi-institutional retrospective cohort study, patients with stage IIIC EC who had surgical staging and received both adjuvant chemotherapy and radiation therapy (RT) were included. Adjuvant treatment regimens were classified as adjuvant chemotherapy followed by sequential RT (upfront chemo), which was predominant sequence; RT with concurrent chemotherapy followed by chemotherapy (concurrent); systemic chemotherapy before and after RT (sandwich); adjuvant RT followed by chemotherapy (upfront RT); or chemotherapy concurrent with vaginal cuff brachytherapy alone (chemo-brachy). Overall survival (OS) and recurrence-free survival (RFS) rates were estimated by the Kaplan-Meier method.A total of 686 eligible patients were included with a median follow-up of 45.3 months. The estimated 5-year OS and RFS rates were 74% and 66%, respectively. The sequence and type of adjuvant therapy were not correlated with OS or RFS (adjusted P = .68 and .84, respectively). On multivariate analysis, black race, nonendometrioid histology, grade 3 tumor, stage IIIC2, and presence of adnexal and cervical involvement were associated with worse OS and RFS (all P.05). Regardless of the sequence of treatment, the most common site of first recurrence was distant metastasis (20.1%). Vaginal only, pelvic only, and paraortic lymph node (PALN) recurrences occurred in 11 (1.6%),15 (2.2 %), and 43 (6.3 %) patients, respectively. Brachytherapy alone was associated with a higher rate of PALN recurrence (15%) compared with external beam radiation therapy (5%) P.0001.The sequence and type of combined adjuvant therapy did not affect OS or RFS rates. Brachytherapy alone was associated with a higher rate of PALN recurrence, emphasizing the role of nodal radiation for stage IIIC EC. The vast proportion of recurrences were distant despite systemic chemotherapy, highlighting the need for novel regimens.

Background Recreational use of the betel nut, which is common among the South Asian population, is a known risk factor for developing Head and Neck cancer. As South Asians comprise a significant proportion of the United States population, we seek to determine if those living within the country experience a higher rate of head and neck cancers compared to other races. Methods Data of patients diagnosed with head & neck cancers from 2010-2016 was collected from the National Cancer Database® and compared to race-matched US census data for each corresponding year to calculate incidence. Pairwise comparisons were performed between the incidence for South Asians versus Whites and South Asians versus Blacks using one sided Chi-square tests. Results South Asians experienced a significantly higher incidence of buccal mucosa/vestibule cancers when compared to Whites or Blacks for every year between 2010-2016, but a comparatively lower incidence of larynx or oropharynx cancers. Conclusions South Asians residing within the United States have a higher incidence of buccal mucosa/vestibule cancers, but a lower incidence of more common cancers, such as larynx or oropharynx cancer. This may suggest that the etiology behind the high buccal mucosa/vestibule cancer incidence is due to a social habit, as opposed to an inherent racial susceptibility.

Although a majority of somatic mutations in cancer are passengers, their mutational signatures provide mechanistic insights into mutagenesis and DNA repair processes. Mutational signature SBS8 is common in most cancers, but its etiology is debated. Incorporating genomic, epigenomic, and cellular process features for multiple cell-types we develop genome-wide composite epigenomic context-maps relevant for mutagenesis and DNA repair. Analyzing somatic mutation data from multiple cancer types in their epigenomic contexts, we show that SBS8 preferentially occurs in gene-poor, lamina-proximal, late replicating heterochromatin domains. While SBS8 is uncommon among mutations in non-malignant tissues, in tumor genomes its proportions increase with replication timing and speed, and checkpoint defects further promote this signature - suggesting that SBS8 probably arises due to uncorrected late replication errors during cancer progression. Our observations offer a potential reconciliation among different perspectives in the debate about the etiology of SBS8 and its relationship with other mutational signatures., Vinod Kumar Singh, Arnav Rastogi, et al. study etiology of mutational signature 8 (SBS8) in human cancers. They develop genome-wide composite epigenomic context maps related to mutagenesis and DNA repair. They report that SBS8 preferentially occurs in heterochromatin and likely arises from late replication errors during cancer progression.

Purpose To compare health-related quality of life (HRQOL) of high-dose-rate brachytherapy (HDRB) versus low dose-rate brachytherapy (LDRB) for localized prostate cancer in a multi-institutional phase 2 randomized trial. Methods and Materials Men with favorable-risk prostate cancer were randomized between monotherapy brachytherapy with either Iodine-125 LDRB to 144 Gy or single-fraction Iridium-192 HDRB to 19 Gy. HRQOL and urinary toxicity were recorded at baseline and at 1, 3, 6, and 12 months using the Expanded Prostate Cancer Index Composite (EPIC)-26 scoring and the International Prostate Symptom Score (IPSS). Independent samples t test and mixed effects modeling were performed for continuous variables. Time to IPSS resolution, defined as return to its baseline score ±5 points, was calculated using Kaplan-Meier estimator curves with the log-rank test. A multiple-comparison adjusted P value of ≤.05 was considered significant. Results LDRB and HDRB were performed in 15 and 16 patients, respectively, for a total of 31 patients. At 3 months, patients treated with LDRB had a higher IPSS score (mean, 15.5 vs 6.0, respectively; P = .003) and lower EPIC urinary irritative score (mean, 69.2 vs 85.3, respectively; P = .037) compared with those who received HDRB. On repeated measures at 1, 3, 6, and 12 months, the IPSS (P = .003) and EPIC urinary irritative scores (P = .019) were significantly better in the HDR arm, translating into a lower urinary toxicity profile. There were no significant differences in the EPIC urinary incontinence, sexual, or bowel habit scores between the 2 groups at any measured time point. Time to IPSS resolution was significantly shorter in the HDRB group (mean, 2.0 months) compared with the LDRB group (mean, 6.0 months; P = .028). Conclusions HDRB monotherapy is a promising modality associated with a lower urinary toxicity profile and higher HRQOL in the first 12 months compared with LDRB.

Chlamydia trachomatis is an obligate intracellular bacterium whose unique developmental cycle consists of an infectious elementary body and a replicative reticulate body. Progression of this developmental cycle requires temporal control of the transcriptome. In addition to the three chlamydial sigma factors (σ66, σ28, and σ54) that recognize promoter sequences of genes, chlamydial transcription factors are expected to play crucial roles in transcriptional regulation. Here, we investigate the function of GrgA, a Chlamydia-specific transcription factor, in C. trachomatis transcriptomic expression. We show that 10 to 30 min of GrgA overexpression induces 13 genes, which likely comprise the direct regulon of GrgA. Significantly, σ66-dependent genes that code for two important transcription repressors are components of the direct regulon. One of these repressors is Euo, which prevents the expression of late genes during early phases. The other is HrcA, which regulates molecular chaperone expression and controls stress response. The direct regulon also includes a σ28-dependent gene that codes for the putative virulence factor PmpI. Furthermore, overexpression of GrgA leads to decreased expression of almost all tRNAs. Transcriptomic studies suggest that GrgA, Euo, and HrcA have distinct but overlapping indirect regulons. These findings, together with temporal expression patterns of grgA, euo, and hrcA, indicate that a transcriptional regulatory network of these three transcription factors plays critical roles in C. trachomatis growth and development. IMPORTANCEChlamydia trachomatis is the most prevalent sexually transmitted bacterial pathogen worldwide and is a leading cause of preventable blindness in underdeveloped areas as well as some developed countries. Chlamydia carries genes that encode a limited number of known transcription factors. While Euo is thought to be critical for early chlamydial development, the functions of GrgA and HrcA in the developmental cycle are unclear. Activation of euo and hrcA immediately following GrgA overexpression indicates that GrgA functions as a master transcriptional regulator. In addition, by broadly inhibiting tRNA expression, GrgA serves as a key regulator of chlamydial protein synthesis. Furthermore, by upregulating pmpI, GrgA may act as an upstream virulence determinant. Finally, genes coregulated by GrgA, Euo, and HrcA likely play critical roles in chlamydial growth and developmental control.

As overfertilization leads to environmental concerns and the cost of N fertilizer increases, the issue of how to select crop cultivars that can produce high yields on N-deficient soils has become crucially important. However, little information is known about the genetic mechanisms by which crops respond to environmental changes induced by N signaling. Here, we dissected the genetic architecture of N-induced phenotypic plasticity in bread wheat (Triticum aestivum L.) by integrating functional mapping and semiautomatic high-throughput phenotyping data of yield-related canopy architecture. We identified a set of quantitative trait loci (QTLs) that determined the pattern and magnitude of how wheat cultivars responded to low N stress from normal N supply throughout the wheat life cycle. This analysis highlighted the phenological landscape of genetic effects exerted by individual QTLs, as well as their interactions with N-induced signals and with canopy measurement angles. This information may shed light on our mechanistic understanding of plant adaptation and provide valuable information for the breeding of N-deficiency tolerant wheat varieties.

Motivation Large scale genome-wide association studies (GWAS) have resulted in the identification of a wide range of genetic variants related to a host of complex traits and disorders. Despite their success, the individual single-nucleotide polymorphism (SNP) analysis approach adopted in most current GWAS can be limited in that it is usually biologically simple to elucidate a comprehensive genetic architecture of phenotypes and statistically underpowered due to heavy multiple-testing correction burden. On the other hand, multiple-SNP analyses (e.g. gene-based or region-based SNP-set analysis) are usually more powerful to examine the joint effects of a set of SNPs on the phenotype of interest. However, current multiple-SNP approaches can only draw an overall conclusion at the SNP-set level and does not directly inform which SNPs in the SNP-set are driving the overall genotype–phenotype association. Results In this article, we propose a new permutation-assisted tuning procedure in lasso (plasso) to identify phenotype-associated SNPs in a joint multiple-SNP regression model in GWAS. The tuning parameter of lasso determines the amount of shrinkage and is essential to the performance of variable selection. In the proposed plasso procedure, we first generate permutations as pseudo-SNPs that are not associated with the phenotype. Then, the lasso tuning parameter is delicately chosen to separate true signal SNPs and non-informative pseudo-SNPs. We illustrate plasso using simulations to demonstrate its superior performance over existing methods, and application of plasso to a real GWAS dataset gains new additional insights into the genetic control of complex traits. Availability and implementation R codes to implement the proposed methodology is available at https://github.com/xyz5074/plasso. Supplementary information Supplementary data are available at Bioinformatics online.

Background Tai Chi, a kind of physical exercise, may act as a non-pharmacologic approach to reducing the symptoms of Parkinson's disease. This study was conducted to investigate the effect of simplified Tai Chi training plus routine exercise on motor and non-motor symptoms in patients with mild to moderate Parkinson's disease in comparison with routine exercise regimen alone. Methods Forty-one outpatients and inpatients with Parkinson's disease (PD) were randomized into Tai Chi group (N.=19) and routine exercise group as control group (N.=22) for 12 weeks. The Tai Chi group included both Tai Chi traning and routine exercise. Motor and non-motor functions were assessed. Motor function was evaluated by Unified Parkinson's Disease Rating Scale part III (UPDRS-III) and Berg Balance Scale (BBS). The non-motor symptoms like quality of life, sleep quality, depression and anxiety state, cognitive function were assessed by Parkinson's Disease Questionnaire-39 (PDQ-39), Parkinson's Disease Sleep Scale (PDSS), Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale (HAMA), Montreal Cognitive Assessment (MOCA) respectively. Results After 12 weeks of intervention, participants in both Tai Chi and routine exercise groups gained effects in UPDRS-III, BBS, PDQ-39, PDSS and HAMD compared to the baseline. However, significant improvements between Tai Chi group and routine exercise group were only found in PDSS (P=0.029) and MoCA (P=0.024). Conclusions Tai Chi training plus routine exercise might therefore be an ideal alternative non-pharmacological approach for the motor and non-motor symptoms of PD patients, and especially be more useful for the improvement of sleep quality and cognitive function in Parkinson's disease compared with routine exercise regimen alone.

Bone morphogenetic protein 9 (BMP9) has recently been described as a crucial regulator in modulating fibroblast-type cell activation. Activin receptor-like kinase 1 (ALK1) is a high affinity receptor for BMP9 that exerts its role via Smad1/5. However, the functional roles of BMP9 in activating lung fibroblasts and the underlying signaling pathway are not completely understood. The present study aimed to explore the effect of exogenous BMP9 on human lung fibroblast HFL-1 cell proliferation and differentiation, as well as the potential role of the ALK1/Smad1/5 signaling pathway. In the present study, fibroblast proliferation was assessed using Cell Counting Kit-8 and colony formation assays, and the mRNA and protein expression of target genes was examined using reverse transcription-quantitative PCR and western blot assays, respectively. Compared with the control group, BMP9 treatment increased HFL-1 cell proliferation, mRNA and protein expression of differentiated markers, including α-smooth muscle actin, type I collagen and type III collagen, and the expression of ALK1 and phosphorylated Smad1/5 expression. Furthermore, the effects of BMP9 were partially rescued by dorsomorphin-1, an inhibitor of ALK1. The results indicated that BMP9 may serve as a key inducer of lung fibroblast activation and ALK1/Smad1/5 signaling might be associated with BMP9-mediated effects in HFL-1 cells. Therefore, the present study highlighted that the potential role of the BMP9/ALK1/Smad1/5 signaling pathway in the development of pulmonary fibrosis requires further investigation.

Background Exposure to ultraviolet radiation from the sun or indoor tanning is the cause of most skin cancers. Although indoor tanning has decreased in recent years, it remains most common among adolescents and young adults, whose skin is particularly vulnerable to long-term damage. US states have adopted several types of legislation to attempt to minimize indoor tanning among minors: a ban on indoor tanning among all minors, a partial minor ban by age (eg, Objective This study investigated whether internet searches (as an indicator of interest) related to indoor tanning varied across US states by the type of indoor tanning legislation, using data from Google Trends from 2006 to 2019. Methods We conducted a time-series analysis of Google Trends data on indoor tanning from 2006 to 2019 by US state. Time-series linear regression models were generated to assess the Google Trends data over time by the type of indoor tanning legislation. Results We found that indoor tanning search rates decreased significantly for all 50 states and the District of Columbia over time (P Conclusions Our findings are consistent with those of other studies on the association between indoor tanning regulations and attitudinal and behavioral trends related to indoor tanning. The main limitation of the study is that raw search data were not available for more precise analysis. With changes in interest and norms, indoor tanning and skin cancer risk among young people may change. Future studies should continue to determine the impact of such public health policies in order to inform policy efforts and minimize risks to public health.

Summary Genome-wide association studies (GWAS), particularly designed with thousands and thousands of single-nucleotide polymorphisms (SNPs) (big p) genotyped on tens of thousands of subjects (small n), are encountered by a major challenge of p ≪ n. Although the integration of longitudinal information can significantly enhance a GWAS’s power to comprehend the genetic architecture of complex traits and diseases, an additional challenge is generated by an autocorrelative process. We have developed several statistical models for addressing these two challenges by implementing dimension reduction methods and longitudinal data analysis. To make these models computationally accessible to applied geneticists, we wrote an R package of computer software, HiGwas, designed to analyze longitudinal GWAS datasets. Functions in the package encompass single SNP analyses, significance-level adjustment, preconditioning and model selection for a high-dimensional set of SNPs. HiGwas provides the estimates of genetic parameters and the confidence intervals of these estimates. We demonstrate the features of HiGwas through real data analysis and vignette document in the package. Availability and implementation https://github.com/wzhy2000/higwas. Contact rwu@phs.psu.edu Supplementary information Supplementary data are available at Bioinformatics online.

Background The aim of the present study was to assess the frequency and severity of female sexual dysfunction (FSD) in those with T2D (T2D) compared with non-diabetic controls. In addition, risk factors for FSD were analyzed. Methods Sexual dysfunction, measured using the Female Sexual Function Index (FSFI), was evaluated using a questionnaire in 184 women with T2D and 146 non-diabetic controls at three study sites in China. In the T2D group, FSD was examined by education level, correlations between FSD and other variables were analyzed, and risk factors were studied. Results The frequency of FSD in the T2D group was 75.0%, much higher than in the control group (56.2%; P = 0.001). The severity of FSD in the T2D group was 17.84 ± 8.47 (mean ± SD), significantly lower than in the control group (21.14 ± 8.08; P = 0.001). In patients with T2D, being older (P = 0.001), taking oral antidiabetic medications (P = 0.013), and having diabetic neuropathy (P = 0.036) were risk factors for FSD. Conclusions The rate of FSD is high in China and, as seen in the literature, more severe in diabetics than non-diabetics. Being older, taking oral antidiabetic medications, and diabetic neuropathy are risk factors for FSD.

Background: Despite being the definitive treatment for lower extremity peripheral arterial disease, vein bypass grafts fail in half of all cases. Early repair mechanisms after implantation, governed largely by the immune environment, contribute significantly to long-term outcomes. The current study investigates the early response patterns of circulating monocytes as a determinant of graft outcome. Methods: In 48 patients undergoing infrainguinal vein bypass grafting, the transcriptomes of circulating monocytes were analyzed preoperatively and at 1, 7, and 28 days post-operation. Results: Dynamic clustering algorithms identified 50 independent gene response patterns. Three clusters (64 genes) were differentially expressed, with a hyperacute response pattern defining those patients with failed versus patent grafts 12 months post-operation. A second independent data set, comprised of 96 patients subjected to major trauma, confirmed the value of these 64 genes in predicting an uncomplicated versus complicated recovery. Causal network analysis identified 8 upstream elements that regulate these mediator genes, and Bayesian analysis with a priori knowledge of the biological interactions was integrated to create a functional network describing the relationships among the regulatory elements and downstream mediator genes. Linear models predicted the removal of either STAT3 (signal transducer and activator of transcription 3) or MYD88 (myeloid differentiation primary response 88) to shift mediator gene expression levels toward those seen in successful grafts. Conclusions: A novel combination of dynamic gene clustering, linear models, and Bayesian network analysis has identified a core set of regulatory genes whose manipulations could migrate vein grafts toward a more favorable remodeling phenotype.

Background Osteoarthritis (OA) is a common degenerative joint disease, which seriously impacts the health of elderly. However, there is no effective treatment for curing this disease until now. Numerous studies reported that long noncoding RNAs (lncRNAs) are closely related to the pathogenesis of OA. Therefore, the study aims to investigate the effect of maternally expressed gene 3 (MEG3) on lipopolysaccharide (LPS)-induced inflammatory injury of ATDC5 cells. Methods Different concentrations (0, 1, 5, and 10 μg/ml) of LPS were used to induce ATDC5 cells injury. The specific expressing vectors were then transfected into ATDC5 cells to alter MEG3, Sirt1 and miR-203 expressions. Flow cytometry, luciferase reporter, qRT-PCR and western blot assays were used to detect cell viability, apoptosis, and the expressions of apoptosis-related proteins and pro-inflammatory factors (IL-1β, IL-6, IL-8 and TNF-α). Meanwhile, ELISA was used for analyzing the concentrations of inflammatory cytokines in culture supernatant. Besides, the key pathways of PI3K/AKT and NF-κB were examined by western blot. Results LPS decreased cell viability, increased cell apoptosis, promoted the release of pro-inflammatory factors, and down-regulated MEG3 expression, Moreover, MEG3 knockdown alleviated LPS-induced inflammatory injury. MEG3 acted as a competing endogenous RNAs (ceRNA) for miR-203, and MEG3 knockdown reduced inflammatory injury by regulating miR-203. Furthermore, miR-203 positively regulated Sirt1 expression, and Sirt1 alleviated LPS-induced inflammatory injury via mediating PI3K/AKT and NF-κB pathways. Conclusion This study showed that MEG3 knockdown alleviated LPS-induced inflammatory injury in ATDC5 cells by regulating miR-203 expression. Hence, the findings may offer a potential treatment perspective of OA.

Phenotypic traits, such as seed development, are a consequence of complex biochemical interactions among genes, proteins and metabolites, but the underlying mechanisms that operate in a coordinated and sequential manner remain elusive. Here, we address this issue by developing a computational algorithm to monitor proteome changes during the course of trait development. The algorithm is built within the mixture-model framework in which each mixture component is modeled by a specific group of proteins that display a similar temporal pattern of expression in trait development. A nonparametric approach based on Legendre orthogonal polynomials was used to fit dynamic changes of protein expression, increasing the power and flexibility of protein clustering. By analyzing a dataset of proteomic dynamics during early embryogenesis of the Chinese fir, the algorithm has successfully identified several distinct types of proteins that coordinate with each other to determine seed development in this forest tree commercially and environmentally important to China. The algorithm will find its immediate applications for the characterization of mechanistic underpinnings for any other biological processes in which protein abundance plays a key role.

The capacity of an organism to respond to its environment is facilitated by the environmentally induced alteration of gene and protein expression, i.e. expression plasticity. The reconstruction of gene regulatory networks based on expression plasticity can gain not only new insights into the causality of transcriptional and cellular processes but also the complex regulatory mechanisms that underlie biological function and adaptation. We describe an approach for network inference by integrating expression plasticity into Shannon’s mutual information. Beyond Pearson correlation, mutual information can capture non-linear dependencies and topology sparseness. The approach measures the network of dependencies of genes expressed in different environments, allowing the environment-induced plasticity of gene dependencies to be tested in unprecedented details. The approach is also able to characterize the extent to which the same genes trigger different amounts of expression in response to environmental changes. We demonstrated the usefulness of this approach through analysing gene expression data from a rabbit vein graft study that includes two distinct blood flow environments. The proposed approach provides a powerful tool for the modelling and analysis of dynamic regulatory networks using gene expression data from distinct environments.

Mathematical models of viral dynamics in vivo provide incredible insights into the mechanisms for the nonlinear interaction between virus and host cell populations, the dynamics of viral drug resistance, and the way to eliminate virus infection from individual patients by drug treatment. The integration of these mathematical models with high-throughput genetic and genomic data within a statistical framework will raise a hope for effective treatment of infections with HIV virus through developing potent antiviral drugs based on individual patients’ genetic makeup. In this opinion article, we will show a conceptual model for mapping and dictating a comprehensive picture of genetic control mechanisms for viral dynamics through incorporating a group of differential equations that quantify the emergent properties of a system.

The multilocus analysis of polymorphisms has emerged as a vital ingredient of population genetics and evolutionary biology. A fundamental assumption used for existing multilocus analysis approaches is Hardy-Weinberg equilibrium (HWE) at which maternally- and paternally-derived gametes combine randomly during fertilization. Given the fact that natural populations are rarely panmictic, these approaches will have a significant limitation for practical use. We present a robust model for multilocus linkage disequilibrium analysis which does not rely on the assumption of random mating. This new disequilibrium model capitalizes on Weir’s definition of zygotic disequilibria and is based on an open-pollinated design in which multiple maternal individuals and their half-sib families are sampled from a natural population. This design captures two levels of associations: one is at the upper level that describes the pattern of co-segregation between different loci in the parental population and the other is at the lower level that specifies the extent of co-transmission of non-alleles at different loci from parents to their offspring. An MCMC method was implemented to estimate genetic parameters that define these associations. Simulation studies were used to validate the statistical behavior of the new model.