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Emerging evidence suggests an important role for SIRT1, a nicotinamide adenine dinucleotide (NAD)-dependent deacetylase in cancer development, progression and therapeutic resistance; making it a viable therapeutic target. Here, we examined the impact of resveratrol-mediated pharmacological activation of SIRT1 on the progression of HGPIN lesions (using the Pten(−/−) mouse model) and on prostate tumor development (using an orthotopic model of prostate cancer cells stably silenced for SIRT1). We show that precise SIRT1 modulation could benefit both cancer prevention and treatment. Positive effect of SIRT1 activation can prevent Pten deletion-driven development of HGPIN lesions in mice if resveratrol is administered early (pre-cancer stage) with little to no benefit after the establishment of HGPIN lesions or tumor cell implantation. Mechanistically, our results show that under androgen deprivation conditions, SIRT1 inhibition induces senescence as evidenced by decreased gene signature associated with negative regulators of senescence and increased senescence-associated β-galactosidase activity. Furthermore, pharmacological inhibition of SIRT1 potentiated growth inhibitory effects of clinical androgen receptor blockade agents and radiation. Taken together, our findings provide an explanation for the discrepancy regarding the role of SIRT1 in prostate tumorigenesis. Our results reveal that the bifurcated roles for SIRT1 may occur in stage and context-dependent fashion by functioning in an antitumor role in prevention of early-stage prostate lesion development while promoting tumor development and disease progression post-lesion development. Clinically, these data highlight the importance of precise SIRT1 modulation to provide benefits for cancer prevention and treatment including sensitization to conventional therapeutic approaches.

Osteosarcoma is the most common malignancy of the bone, yet the survival for patients with osteosarcoma is virtually unchanged over the past 30 years. This is principally because development of new therapies is hampered by a lack of recurrent mutations that can be targeted in osteosarcoma. Here, we report that epigenetic changes via mRNA methylation holds great promise to better understand the mechanisms of osteosarcoma growth and to develop targeted therapeutics. In patients with osteosarcoma, the RNA demethylase ALKBH5 was amplified and higher expression correlated with copy-number changes. ALKBH5 was critical for promoting osteosarcoma growth and metastasis, yet it was dispensable for normal cell survival. Methyl RNA immunoprecipitation sequencing analysis and functional studies showed that ALKBH5 mediates its protumorigenic function by regulating m6A levels of histone deubiquitinase USP22 and the ubiquitin ligase RNF40. ALKBH5-mediated m6A deficiency in osteosarcoma led to increased expression of USP22 and RNF40 that resulted in inhibition of histone H2A monoubiquitination and induction of key protumorigenic genes, consequently driving unchecked cell-cycle progression, incessant replication, and DNA repair. RNF40, which is historically known to ubiquitinate H2B, inhibited H2A ubiquitination in cancer by interacting with and affecting the stability of DDB1-CUL4–based ubiquitin E3 ligase complex. Taken together, this study directly links increased activity of ALKBH5 with dysregulation of USP22/RNF40 and histone ubiquitination in cancers. More broadly, these results suggest that m6A RNA methylation works in concert with other epigenetic mechanisms to control cancer growth. Significance: RNA demethylase ALKBH5 upregulates USP22 and RNF40 to inhibit histone H2A ubiquitination and induces expression of key replication and DNA repair–associated genes, driving osteosarcoma progression.

The EWSR1/FLI1 gene fusion is the most common rearrangement leading to cell transformation in Ewing sarcoma (ES). Previous studies have indicated that expression at the cellular level is heterogeneous, and that levels of expression may oscillate, conferring different cellular characteristics. In ES the role of EWSR1/FLI1 in regulating subpopulation dynamics is currently unknown.We used siRNA to transiently suppress EWSR1/FLI1 expression and followed population dynamics using both single cell expression profiling, CyTOF and functional assays to define characteristics of exponentially growing ES cells and of ES cells in which EWSR1/FLI1 had been downregulated. Novel transcriptional states with distinct features were assigned using random forest feature selection in combination with machine learning. Cells isolated from ES xenografts in immune-deficient mice were interrogated to determine whether characteristics of specific subpopulations of cells in vitro could be identified. Stem-like characteristics were assessed by primary and secondary spheroid formation in vitro, and invasion/motility was determined for each identified subpopulation. Autophagy was determined by expression profiling, cell sorting and immunohistochemical staining.We defined a workflow to study EWSR1/FLI1 driven transcriptional states and phenotypes. We tracked EWSR1/FLI1 dependent proliferative activity over time to discover sources of intra-tumoral diversity. Single-cell RNA profiling was used to compare expression profiles in exponentially growing populations (si-Control) or in two dormant populations (D1, D2) in which EWSR1/FLI1 had been suppressed. Three distinct transcriptional states were uncovered contributing to ES intra-heterogeneity. Our predictive model identified ~1% cells in a dormant-like state and ~ 2-4% cells with stem-like and neural stem-like features in an exponentially proliferating ES cell line and in ES xenografts. Following EWSR1/FLI1 knockdown, cells re-entering the proliferative cycle exhibited greater stem-like properties, whereas for those cells remaining quiescent, FAM134B-dependent dormancy may provide a survival mechanism.We show that time-dependent changes induced by suppression of oncogenic EWSR1/FLI1 expression induces dormancy, with different subpopulation dynamics. Cells re-entering the proliferative cycle show enhanced stem-like characteristics, whereas those remaining dormant for prolonged periods appear to survive through autophagy. Cells with these characteristics identified in exponentially growing cell populations and in tumor xenografts may confer drug resistance and could potentially contribute to metastasis.

Dilated cardiomyopathy (DCM) is a cardiomyopathy with left ventricle or double ventricle enlargement and systolic dysfunction. It is an important cause of sudden cardiac death and heart failure and is the leading indication for cardiac transplantation. Major heart diseases like heart muscle damage and valvular problems are diagnosed using cardiac MRI. However, it takes time for cardiologists to measure DCM-related parameters to decide whether patients have this disease. We have presented a method for automatic ventricular segmentation, parameter extraction, and diagnosing DCM. In this paper, left ventricle and right ventricle are segmented by parasternal short-axis cardiac MR image sequence; then, related parameters are extracted in the end-diastole and end-systole of the heart. Machine learning classifiers use extracted parameters as input to predict normal people and patients with DCM, among which Random forest classifier gives the highest accuracy. The results show that the proposed system can be effectively utilized to detect and diagnose DCM automatically. The experimental results suggest the capabilities and advantages of the proposed method to diagnose DCM. A small amount of sample input can generate results comparable to more complex methods.

Most patients with estrogen receptor alpha–positive (ER+) breast cancers initially respond to treatment but eventually develop therapy resistance with disease progression. Overexpression of oncogenic ER coregulators, including proline, glutamic acid, and leucine-rich protein 1 (PELP1), are implicated in breast cancer progression. The lack of small molecules that inhibits PELP1 represents a major knowledge gap. Here, using a yeast-two-hybrid screen, we identified novel peptide inhibitors of PELP1 (PIP). Biochemical assays demonstrated that one of these peptides, PIP1, directly interacted with PELP1 to block PELP1 oncogenic functions. Computational modeling of PIP1 revealed key residues contributing to its activity and facilitated the development of a small-molecule inhibitor of PELP1, SMIP34, and further analyses confirmed that SMIP34 directly bound to PELP1. In breast cancer cells, SMIP34 reduced cell growth in a dose-dependent manner. SMIP34 inhibited proliferation of not only wild-type (WT) but also mutant (MT) ER+ and therapy-resistant breast cancer cells, in part by inducing PELP1 degradation via the proteasome pathway. RNA sequencing analyses showed that SMIP34 treatment altered the expression of genes associated with estrogen response, cell cycle, and apoptosis pathways. In cell line–derived and patient-derived xenografts of both WT and MT ER+ breast cancer models, SMIP34 reduced proliferation and significantly suppressed tumor progression. Collectively, these results demonstrate SMIP34 as a first-in-class inhibitor of oncogenic PELP1 signaling in advanced breast cancer. Significance: Development of a novel inhibitor of oncogenic PELP1 provides potential therapeutic avenues for treating therapy-resistant, advanced ER+ breast cancer.

The worldwide infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) impacts human health and life on multiple levels. People infected with SARS-CoV-2 suffer from physical disorders and psychological distress. At present, no direct evidence indicates that SARS-CoV-2 negatively influences human reproduction, and the possibility that gametes and embryos are affected requires further investigation. To evaluate the potential effects of SARS-CoV-2 infection on human reproduction and fetal health, this review summarizes the basic and clinical research of SARS-CoV-2 on reproduction up to date, hoping to offer guidance and advice to people at reproductive age and provide clues for the prevention and treatment of associated diseases.

Integrin α6 (ITGA6) forms integrin receptors with either integrin β1 (ITGB1) or integrin β4 (ITGB4). How it functions to regulate hepatocellular carcinoma (HCC) progression is not well-elucidated. We found that ITGA6 RNA and protein expression levels are significantly elevated in human HCC tissues in comparison with paired adjacent nontumor tissues by RNA sequencing, RT-qPCR, Western blotting and immunofluorescence staining. Stable knockdown of ITGA6 with different ITGA6 shRNA expression lentivectors significantly inhibited proliferation, migration and anchorage-independent growth of HCC cell lines in vitro, and xenograft tumor growth in vivo. The inhibition of anchorage-dependent and -independent growth of HCC cell lines was also confirmed with anti-ITGA6 antibody. ITGA6 knockdown was shown to induce cell-cycle arrest at G0/G1 phase. Immunoprecipitation assay revealed apparent interaction of ITGA6 with ITGB4, but not ITGB1. Expression studies showed that ITGA6 positively regulates the expression of ITGB4 with no or negative regulation of ITGB1 expression. Finally, while high levels of ITGA6 and ITGB4 together were associated with significantly worse survival of HCC patients in TCGA data set, the association was not significant for high levels of ITGA6 and ITGB1. In conclusion, ITGA6 is upregulated in HCC tumors and has a malignant promoting role in HCC cells through integrin α6β4 complex. Thus, integrin α6β4 may be a therapeutic target for treating patients with HCC.

Background Deep learning (DL) models are highly vulnerable to adversarial attacks for medical image classification. An adversary could modify the input data in imperceptible ways such that a model could be tricked to predict, say, an image that actually exhibits malignant tumor to a prediction that it is benign. However, adversarial robustness of DL models for medical images is not adequately studied. DL in medicine is inundated with models of various complexity—particularly, very large models. In this work, we investigate the role of model complexity in adversarial settings. Results Consider a set of DL models that exhibit similar performances for a given task. These models are trained in the usual manner but are not trained to defend against adversarial attacks. We demonstrate that, among those models, simpler models of reduced complexity show a greater level of robustness against adversarial attacks than larger models that often tend to be used in medical applications. On the other hand, we also show that once those models undergo adversarial training, the adversarial trained medical image DL models exhibit a greater degree of robustness than the standard trained models for all model complexities. Conclusion The above result has a significant practical relevance. When medical practitioners lack the expertise or resources to defend against adversarial attacks, we recommend that they select the smallest of the models that exhibit adequate performance. Such a model would be naturally more robust to adversarial attacks than the larger models.

Hypertrophic scars are a common negative outcome of deep partial-thickness (DPT) burn wounds resulting in increased dermal thickness, wound area contracture, and inflammation of the affected area. The red Duroc and Yorkshire porcine breeds are common large animal models for studying dermal wounds due to their structural similarities to human skin; however, the porcine transcriptomic profiles of dermal burn wounds and healing process are not well known. In response, a longitudinal transcriptomic comparative study was conducted comparing red Duroc and Yorkshire superficial and DPT burn wounds to their respective control uninjured tissue. Using next-generation RNA sequencing, total RNAs were isolated from burn wound tissue harvested on 0, 3, 7, 15, 30, and 60 days postburn, and mRNA-seq and gene expression read counts were generated. Significant differentially expressed genes relative to uninjured tissue were defined, and active biological processes were determined using gene set enrichment analyses. Additionally, collagen deposition, α-smooth muscle actin (SMA) protein concentration, epidermal and dermal thickness measurements, and wound area changes in response to burn injury were characterized. Overall, the red Duroc pigs, in response to both burn wound types, elicited a more robust and prolonged inflammatory immune response, fibroblast migration, and proliferation, as well as heightened levels of extracellular matrix modulation relative to respective burn types in the Yorkshire pigs. Collectively, the red Duroc DPT burn wounds produce a greater degree of hypertrophic scar-like response compared with Yorkshire DPT burn wounds. These findings will facilitate future porcine burn studies down-selecting treatment targets and determining the effects of novel therapeutic strategies.

Being infected by SARS-CoV-2 may cause damage to multiple organs in patients, such as the lung, liver and heart. Angiotensin-converting enzyme 2 (ACE2), reported as a SARS-CoV-2 receptor, is also expressed in human male testes. This suggests a potential risk in human male reproductive system. However, the characteristics of ACE2-positive cells and the expression of other SARS-CoV-2 process-related genes are still worthy of further investigation. Here, we performed singlecell RNA seq (scRNA-seq) analysis on 853 male embryo primordial germ cells (PGCs) and 2,854 normal testis cells to assess the effects of the SARS-CoV-2 virus on the male reproductive system from embryonic stage to adulthood. We also collected and constructed the scRNA-seq library on 228 Sertoli cells from three non-obstructive azoospermia (NOA) patients to assess the effects at disease state. We found that ACE2 expressing cells existed in almost all testis cell types and Sertoli cells had highest expression level and positive cells ratio. Moreover, ACE2 was also expressed in human male PGCs. In adulthood, the level of ACE2 expression decreased with the increase of age. We also found that ACE2 positive cells had high expressions of stress response and immune activation-related genes. Interestingly, some potential SARS-CoV-2 process-related genes such as TMPRSS2, BSG, CTSL and CTSB had different expression patterns in the same cell type. Furthermore, ACE2 expression level in NOA donors’ Sertoli cells was significantly decreased. Our work would help to assess the risk of SARS-CoV-2 infection in the male reproductive system. Electronic Supplementary Material Supplementary material is available for this article at 10.1007/s11427-020-1705-0 and is accessible for authorized users.

Quantifying the activity of gene expression signatures is common in analyses of single-cell RNA sequencing data. Methods originally developed for bulk samples are often used for this purpose without accounting for contextual differences between bulk and single-cell data. More broadly, few attempts have been made to benchmark these methods. Here, we benchmark five such methods, including single sample gene set enrichment analysis (ssGSEA), Gene Set Variation Analysis (GSVA), AUCell, Single Cell Signature Explorer (SCSE), and a new method we developed, Jointly Assessing Signature Mean and Inferring Enrichment (JASMINE). Using cancer as an example, we show cancer cells consistently express more genes than normal cells. This imbalance leads to bias in performance by bulk-sample-based ssGSEA in gold standard tests and down sampling experiments. In contrast, single-cell-based methods are less susceptible. Our results suggest caution should be exercised when using bulk-sample-based methods in single-cell data analyses, and cellular contexts should be taken into consideration when designing benchmarking strategies.

Aberrant activities of various cell cycle and DNA repair proteins promote cancer growth and progression and render them resistant to therapies. Here, we demonstrate that the anti-depressant imipramine blocks growth of triple-negative (TNBC) and estrogen receptor-positive (ER+) breast cancers by inducing cell cycle arrest and by blocking heightened homologous recombination (HR) and non-homologous end joining-mediated (NHEJ) DNA repair activities. Our results reveal that imipramine inhibits the expression of several cell cycle- and DNA repair-associated proteins including E2F1, CDK1, Cyclin D1, and RAD51. In addition, we show that imipramine inhibits the growth of ER + breast cancers by inhibiting the estrogen receptor- α (ER-α) signaling. Our studies in preclinical mouse models and ex vivo explants from breast cancer patients show that imipramine sensitizes TNBC to the PARP inhibitor olaparib and endocrine resistant ER + breast cancer to anti-estrogens. Our studies suggest that repurposing imipramine could enhance routine care for breast cancer patients. Based on these results, we designed an ongoing clinical trial, where we are testing the efficacy of imipramine for treating patients with triple-negative and estrogen receptor-positive breast cancer. Since aberrant DNA repair activity is used by many cancers to survive and become resistant to therapy, imipramine could be used alone and/or with currently used drugs for treating many aggressive cancers.

Background Methyltransferase SETDB1 is highly expressed in breast cancer (BC), however, the mechanisms by which SETDB1 promotes BC progression to endocrine therapy resistance remains elusive. In this study, we examined the mechanisms by which SETDB1 contribute to BC endocrine therapy resistance. Methods We utilized therapy sensitive (MCF7 and ZR75), therapy resistant (MCF7-TamR, MCF7-FR, MCF7-PELP1cyto, MCF7-SETDB1) estrogen receptor alpha positive (ER+)BC models and conducted in vitro cell viability, colony formation, 3-dimensional cell growth assays to investigate the role of SETDB1 in endocrine resistance. RNA-seq of parental and SETDB1 knock down ER+ BC cells was used to identify unique pathways. SETDB1 interaction with PELP1 was identified by yeast-two hybrid screen and confirmed by immunoprecipitation and GST-pull down assays. Mechanistic studies were conducted using Western blotting, reporter gene assays, RT-qPCR, and in vitro methylation assays. Xenograft assays were used to establish the role of PELP1 in SETDB1 mediated BC progression. Results RNA-seq analyses showed that SETDB1 regulates expression of a subset of estrogen receptor (ER) and Akt target genes that contribute to endocrine therapy resistance. Importantly, using yeast-two hybrid screen, we identified ER coregulator PELP1 as a novel interacting protein of SETDB1. Biochemical analyses confirmed SETDB1 and PELP1 interactions in multiple BC cells. Mechanistic studies confirmed that PELP1 is necessary for SETDB1 mediated Akt methylation and phosphorylation. Further, SETDB1 overexpression promotes tamoxifen resistance in BC cells, and PELP1 knockdown abolished these effects. Using xenograft model, we provided genetic evidence that PELP1 is essential for SETDB1 mediated BC progression in vivo. Analyses of TCGA datasets revealed SETDB1 expression is positively correlated with PELP1 expression in ER+ BC patients. Conclusions This study suggests that the PELP1/SETDB1 axis play an important role in aberrant Akt activation and serves as a novel target for treating endocrine therapy resistance in breast cancer.

Since its selection as the method of the year in 2013, single-cell technologies have become mature enough to provide answers to complex research questions. With the growth of single-cell profiling technologies, there has also been a significant increase in data collected from single-cell profilings, resulting in computational challenges to process these massive and complicated datasets. To address these challenges, deep learning (DL) is positioned as a competitive alternative for single-cell analyses besides the traditional machine learning approaches. Here, we survey a total of 25 DL algorithms and their applicability for a specific step in the single cell RNA-seq processing pipeline. Specifically, we establish a unified mathematical representation of variational autoencoder, autoencoder, generative adversarial network and supervised DL models, compare the training strategies and loss functions for these models, and relate the loss functions of these models to specific objectives of the data processing step. Such a presentation will allow readers to choose suitable algorithms for their particular objective at each step in the pipeline. We envision that this survey will serve as an important information portal for learning the application of DL for scRNA-seq analysis and inspire innovative uses of DL to address a broader range of new challenges in emerging multi-omics and spatial single-cell sequencing.

Patients with grade II/III diffuse glioma (lower grade glioma, LGG) with isocitrate dehydrogenase wild-type (IDH-wt) and telomerase reverse-transcriptase promoter mutation (TERTp-mut) experience shorter overall survival (OS) time than IDH mutant patients. The optimal treatment strategy for these patients is unclear. We compared the effects of radiotherapy (RT) alone vs. RT concurrent with temozolomide (TMZ) followed by adjuvant TMZ in these LGG patients.Thirty-seven LGG patients with IDH-wt and TERTp-mut were randomly allocated to either RT alone treatment (RT group, n = 18; 60 Gy in 30 daily fractions) or RT concurrent with TMZ (75 mg/mThe 1-year OS rate was 94.1% [95% confidence interval (CI) 82.9-100] in the CRT group and 74.6% (95% CI, 52.9-96.4) in the RT group. The median OS values in the CRT and RT groups were statistically different [25 vs. 17 months, respectively; hazard ratio (HR) 0.271; 95% CI, 0.092-0.793; P = 0.017], while PFS values were not (16 vs. 7 months, respectively; HR, 0.917; 95% CI, 0.397-2.120; P = 0.840). Multivariate analysis indicated that CRT treatment and female sex were associated with significantly longer OS (P = 0.001, P = 0.016, respectively).CRT treatment for IDH-wt/TERTp-mut grade II/III gliomas resulted in significantly longer OS than RT alone. Female sex was a significant favorable prognostic factor.

Oncogenic RAS signaling is an attractive target for fusion-negative rhabdomyosarcoma (FN-RMS). Our study validates the role of the ERK MAPK effector pathway in mediating RAS dependency in a panel of H/NRASQ61X-mutant RMS cells and correlates in vivo efficacy of the MEK inhibitor trametinib with pharmacodynamics of ERK activity. A screen is used to identify trametinib-sensitizing targets and combinations are evaluated in cells and tumor xenografts. We find that the ERK MAPK pathway is central to H/NRASQ61X-dependency in RMS cells, however there is poor in vivo response to clinically relevant exposures with trametinib, which correlates with inefficient suppression of ERK activity. CRISPR screening points to vertical inhibition of the RAF-MEK-ERK cascade by co-suppression of MEK and either CRAF or ERK. CRAF is central to rebound pathway activation following MEK or ERK inhibition. Concurrent CRAF suppression and MEK or ERK inhibition, or concurrent pan-RAF and MEK/ERK inhibition (pan-RAFi + MEKi/ERKi), or concurrent MEK and ERK inhibition (MEKi + ERKi) all synergistically block ERK activity and induce myogenic differentiation and apoptosis. In vivo assessment of pan-RAFi + ERKi or MEKi + ERKi potently suppress growth of H/NRASQ61X RMS tumor xenografts, with pan-RAFi + ERKi being more effective and better tolerated. We conclude that CRAF reactivation limits the activity of single agent MEK/ERK inhibitors in FN-RMS. Vertical targeting of the RAF-MEK-ERK cascade, and particularly co-targeting of CRAF and MEK or ERK, or the combination of pan-RAF inhibitors with MEK or ERK inhibitors, have synergistic activity and potently suppress H/NRASQ61X-mutant RMS tumor growth.

Transcriptomic and epigenetic alterations during early embryo development have been proven to play essential roles in regulating the cell fate. Nowadays, advances in single-cell transcriptomics and epigenomics profiling techniques provide large volumes of data for understanding the molecular regulatory mechanisms in early embryos and facilitate the investigation of assisted reproductive technology as well as preimplantation genetic testing. However, the lack of integrated data collection and unified analytic procedures greatly limits their usage in scientific research and clinical application. Hence, it is necessary to establish a database integrating the regulatory information of human and mouse early embryos with unified analytic procedures. Here, we introduce DevOmics (http://devomics.cn/), which contains normalized gene expression, DNA methylation, histone modifications (H3K4me3, H3K9me3, H3K27me3, H3K27ac), chromatin accessibility and 3D chromatin architecture profiles of human and mouse early embryos spanning six developmental stages (zygote, 2cell, 4cell, 8cell, morula and blastocyst (ICM, TE)). The current version of DevOmics provides Search and Advanced Search for retrieving genes a researcher is interested in, Analysis Tools including the differentially expressed genes (DEGs) analysis for acquiring DEGs between different types of samples, allelic explorer for displaying allele-specific gene expression as well as epigenetic modifications and correlation analysis for showing the dynamic changes in different layers of data across developmental stages, as well as Genome Browser and Ortholog for visualization. DevOmics offers a user-friendly website for biologists and clinicians to decipher molecular regulatory mechanisms of human and mouse early embryos.

Inflammatory bowel disease (IBD) usually present with systemic and gastrointestinal problems. This may result in both physical and psychological burden. The aim of the study was to investigate the association between psychological burden and Health Related Quality of Life (HRQoL), sleep quality and disease characteristics. A total of 106 patients and 165 general populations were enrolled in this study. The demographic information, disease characteristics of participants were investigated. The SCL-90 was self-administered to evaluate psychometric properties. SF-36 and IBDQ were both used to the assessment of HRQoL, and PSQI to quality of sleep. The SCL-90 score of IBD was significantly higher than that of the control (p = .0007), especially in somatization, anxiety, depression, hostility and psychosis dimensions. Similar to IBDQ (p < .0001), the results of SF-36 (p < .0001) showed that the HRQoL of both Ulcerative colitis (UC) and Crohn’s disease (CD) were somehow inferior to control. However, undifferentiated results were noted in patients between UC and CD. Good linear relationship between disease activity and SCL-90 (RUC = 0.53, pUC = .001; RCD = 0.36, pCD = .002), SF-36 (RUC = −0.42, pUC = .01; RCD = −0.49, pCD < .0001), IBDQ (RUC = −0.57, pUC = .0005; RCD = −0.52, pCD < .0001), PSQI (RUC = 0.50, pUC = .003; RCD = 0.27, pCD = .02) were observed. With the score of SCL-90 of patients increased, the SF-36 (R = −0.78, p < .0001) and IBDQ decreased (R = −0.74, p < .0001), PSQI increased (R = −0.70, p < .0001). Multiple stepwise regression analysis revealed that disease activity, extraintestinal manifestations, weight loss may contribute to identify the psychological anomalies. Altered psychological status can be found in IBD, reflecting the necessity of providing psychological care for them. The disease itself results in lower HRQoL. Better HRQoL and sleep quality are in concordance with better psychological health.

The discovery of embryonic cell-free DNA (cfDNA) in spent embryo culture media (SECM) has brought hope for noninvasive preimplantation genetic testing. However, the cellular origins of SECM cfDNA are not sufficiently understood, and methods for determining maternal DNA contamination are limited. Here, we performed whole-genome DNA methylation sequencing for SECM cfDNA. Our results demonstrated that SECM cfDNA was derived from blastocysts, cumulus cells, and polar bodies. We identified the cumulus-specific differentially methylated regions (DMRs) and oocyte/polar body-specific DMRs, and established an algorithm for deducing the cumulus, polar body, and net maternal DNA contamination ratios in SECM. We showed that DNA methylation sequencing accurately detected chromosome aneuploidy in SECM and distinguished SECM samples with low and high false negative rates and gender discordance rates, after integrating the origin analysis. Our work provides insights into the characterization of embryonic DNA in SECM and provides a perspective for noninvasive preimplantation genetic testing in reproductive medicine.

The major limitations of DNA-targeting chemotherapy drugs include life-threatening toxicity, acquired resistance and occurrence of secondary cancers. Here, we report a small molecule, Carbazole Blue (CB), that binds to DNA and inhibits cancer growth and metastasis by targeting DNA-related processes that tumor cells use but not the normal cells. We show that CB inhibits the expression of pro-tumorigenic genes that promote unchecked replication and aberrant DNA repair that cancer cells get addicted to survive. In contrast to chemotherapy drugs, systemic delivery of CB suppressed breast cancer growth and metastasis with no toxicity in pre-clinical mouse models. Using PDX and ex vivo explants from estrogen receptor (ER) positive, ER mutant and TNBC patients, we further demonstrated that CB effectively blocks therapy-sensitive and therapy-resistant breast cancer growth without affecting normal breast tissue. Our data provide a strong rationale to develop CB as a viable therapeutic for treating breast cancers.

Objective This study sought to evaluate rates of acute kidney injury in patients undergoing contrast-enhanced computerized tomography for acute stroke in the emergency department (ED) before and after the cessation of creatinine screening. Methods This retrospective study compared ED patients receiving contrast-enhanced imaging for suspected acute stroke with and without protocolized creatinine screening. The primary outcome was CIN, defined as an increase in serum creatinine of 0.3 mg/dl within 48 hours or 50% above baseline within 7 days after contrast administration. Secondary outcomes consisted of CIN based on other definitions, renal impairment greater than 30 days from contrast administration, hemodialysis, and mortality. Outcomes were compared using difference of proportions and odds ratios with 95% confidence intervals. Results This study included 382 subjects, with 186 and 196 in the screening and post-screening cohorts, respectively. No significant differences were observed for CIN (7.0% vs 7.1%, difference 0.1% [95% CI -5.6-5.1%], OR 1.02 [95% CI 0.47–2.24]), renal impairment greater than 30 days post-contrast (8.4% vs 7.5%, OR 0.88 [0.38–2.07]), or mortality (index visit: 4.8% vs 2.6%, OR 0.51 [0.17–1.57], 90-day follow-up: 6.7% vs 4.0%, OR 0.58 [0.22–1.53]). No patients from either group required hemodialysis. Conclusions The elimination of creatinine screening prior to obtaining contrast-enhanced computerized tomography in patients with suspected acute stroke did not adversely affect rates of CIN, hemodialysis, or mortality at a comprehensive stroke center.

Sign language translation (SLT) is an important application to bridge the communication gap between deaf and hearing people. In recent years, the research on the SLT based on neural translation frameworks has attracted wide attention. Despite the progress, current SLT research is still in the initial stage. In fact, current systems perform poorly in processing long sign sentences, which often involve long-distance dependencies and require large resource consumption. To tackle this problem, we propose two explainable adaptations to the traditional neural SLT models using optimized tokenization-related modules. First, we introduce a frame stream density compression (FSDC) algorithm for detecting and reducing the redundant similar frames, which effectively shortens the long sign sentences without losing information. Then, we replace the traditional encoder in a neural machine translation (NMT) module with an improved architecture, which incorporates a temporal convolution (T-Conv) unit and a dynamic hierarchical bidirectional GRU (DH-BiGRU) unit sequentially. The improved component takes the temporal tokenization information into consideration to extract deeper information with reasonable resource consumption. Our experiments on the RWTH-PHOENIX-Weather 2014T dataset show that the proposed model outperforms the state-of-the-art baseline up to about 1.5+ BLEU-4 score gains.

Currently, most work on comparing differences between simplified and traditional Chinese only focuses on the character or lexical level, without taking the global differences into consideration. In order to solve this problem, this paper proposes to use complex network analysis of word co-occurrence networks, which have been successfully applied to the language analysis research and can tackle global characters and explore the differences between simplified and traditional Chinese. Specially, we first constructed a word co-occurrence network for simplified and traditional Chinese using selected news corpora. Then, the complex network analysis methods were performed, including network statistics analysis, kernel lexicon comparison, and motif analysis, to gain a global understanding of these networks. After that, the networks were compared based on the properties obtained. Through comparison, we can obtain three interesting results: first, the co-occurrence networks of simplified Chinese and traditional Chinese are both small-world and scale-free networks. However, given the same corpus size, the co-occurrence networks of traditional Chinese tend to have more nodes, which may be due to a large number of one-to-many character/word mappings from simplified Chinese to traditional Chinese; second, since traditional Chinese retains more ancient Chinese words and uses fewer weak verbs, the traditional Chinese kernel lexicons have more entries than the simplified Chinese kernel lexicons; third, motif analysis shows that there is no difference between the simplified Chinese network and the corresponding traditional Chinese network, which means that simplified and traditional Chinese are semantically consistent.

N6-methyladenosine (m6A) is the most abundant form of mRNA modification and controls many aspects of RNA metabolism including gene expression. However, the mechanisms by which m6A regulates cell- and condition-specific gene expression are still poorly understood, partly due to a lack of tools capable of identifying m6A sites that regulate gene expression under different conditions. Here we develop m6A-express, the first algorithm for predicting condition-specific m6A regulation of gene expression (m6A-reg-exp) from limited methylated RNA immunoprecipitation sequencing (MeRIP-seq) data. Comprehensive evaluations of m6A-express using simulated and real data demonstrated its high prediction specificity and sensitivity. When only a few MeRIP-seq samples may be available for the cellular or treatment conditions, m6A-express is particularly more robust than the log-linear model. Using m6A-express, we reported that m6A writers, METTL3 and METTL14, competitively regulate the transcriptional processes by mediating m6A-reg-exp of different genes in Hela cells. In contrast, METTL3 induces different m6A-reg-exp of a distinct group of genes in HepG2 cells to regulate protein functions and stress-related processes. We further uncovered unique m6A-reg-exp patterns in human brain and intestine tissues, which are enriched in organ-specific processes. This study demonstrates the effectiveness of m6A-express in predicting condition-specific m6A-reg-exp and highlights the complex, condition-specific nature of m6A-regulation of gene expression.

Collaboration among writers-readers-erasers of m6A regulates the stability of tumor-specific genes., The importance of RNA methylation in biological processes is an emerging focus of investigation. We report that altering m6A levels by silencing either N6-adenosine methyltransferase METTL14 (methyltransferase-like 14) or demethylase ALKBH5 (ALKB homolog 5) inhibits cancer growth and invasion. METTL14/ALKBH5 mediate their protumorigenic function by regulating m6A levels of key epithelial-mesenchymal transition and angiogenesis-associated transcripts, including transforming growth factor–β signaling pathway genes. Using MeRIP-seq (methylated RNA immunoprecipitation sequencing) analysis and functional studies, we find that these target genes are particularly sensitive to changes in m6A modifications, as altered m6A status leads to aberrant expression of these genes, resulting in inappropriate cell cycle progression and evasion of apoptosis. Our results reveal that METTL14 and ALKBH5 determine the m6A status of target genes by controlling each other’s expression and by inhibiting m6A reader YTHDF3 (YTH N6-methyladenosine RNA binding protein 3), which blocks RNA demethylase activity. Furthermore, we show that ALKBH5/METTL14 constitute a positive feedback loop with RNA stability factor HuR to regulate the stability of target transcripts. We discover that hypoxia alters the level/activity of writers, erasers, and readers, leading to decreased m6A and consequently increased expression of target transcripts in cancer cells. This study unveils a previously undefined role for m6A in cancer and shows that the collaboration among writers-erasers-readers sets up the m6A threshold to ensure the stability of progrowth/proliferation-specific genes, and protumorigenic stimulus, such as hypoxia, perturbs that m6A threshold, leading to uncontrolled expression/activity of those genes, resulting in tumor growth, angiogenesis, and progression.

The developmental pathway of the neural retina (NR) and retinal pigment epithelium (RPE) has been revealed by extensive research in mice. However, the molecular mechanisms underlying the development of the human NR and RPE, as well as the interactions between these two tissues, have not been well defined. Here, we analyzed 2,421 individual cells from human fetal NR and RPE using single-cell RNA sequencing (RNA-seq) technique and revealed the tightly regulated spatiotemporal gene expression network of human retinal cells. We identified major cell classes of human fetal retina and potential crucial transcription factors for each cell class. We dissected the dynamic expression patterns of visual cycle– and ligand-receptor interaction–related genes in the RPE and NR. Moreover, we provided a map of disease-related genes for human fetal retinal cells and highlighted the importance of retinal progenitor cells as potential targets of inherited retinal diseases. Our findings captured the key in vivo features of the development of the human NR and RPE and offered insightful clues for further functional studies., Single-cell RNA sequencing allows dissection of the transcriptomic landscape of the human fetal neural retina (NR) and retinal pigment epithelium (RPE), revealing a tightly regulated spatiotemporal gene expression network of human retinal cells, as well as dynamic and functional interactions between the NR and RPE.

Summary: Healthy renal function depends on normal nephrogenesis during embryonic development. However, a comprehensive gene expression profile of human fetal kidney development remains largely unexplored. Here, using a single-cell RNA-sequencing technique, we analyzed >3,000 human fetal renal cells spanning 4 months of development in utero. Unsupervised analysis identified two progenitor subtypes during cap mesenchyme development, suggesting a mechanism for sustaining their progenitor states. Furthermore, we identified critical transcriptional regulators and signaling pathways involved in the segmentation of nephron tubules. We explored the development of the highly heterogeneous collecting duct epithelia and dissected the metabolic gene repertoire and the extracellular matrix composition of the glomerular mesangium. The results provide insights on the molecular basis and regulatory events in human renal development. Moreover, the cell-type-specific expression features of causal genes in congenital renal diseases may be helpful in the treatment of these diseases. : To investigate the gene expression profiles of human fetal kidney development, Wang et al. performed single-cell RNA-seq for >3,000 renal cells. They highlight the heterogeneity of cap mesenchyme and regulatory factors in nephron formation. The results reveal cell-type-specific risk genes in congenital renal diseases. Keywords: human fetal kidney development, single-cell RNA-seq, nephron progenitors, nephron tubule segmentation, congenital renal diseases, single cell transcriptome analysis, STRT

Altered DNA methylation in CpG islands of gene promoters has been implicated in prostate cancer (PCa) progression and can be used to predict disease outcome. In this study, we determine whether methylation changes of androgen biosynthesis pathway (ABP)-related genes in patients' plasma cell-free DNA (cfDNA) can serve as prognostic markers for biochemical recurrence (BCR).Methyl-binding domain capture sequencing (MBDCap-seq) was used to identify differentially methylated regions (DMRs) in primary tumors of patients who subsequently developed BCR or not, respectively. Methylation pyrosequencing of candidate loci was validated in cfDNA samples of 86 PCa patients taken at and/or post-radical prostatectomy (RP) using univariate and multivariate prediction analyses.Putative DMRs in 13 of 30 ABP-related genes were found between tumors of BCR (n = 12) versus no evidence of disease (NED) (n = 15). In silico analysis of The Cancer Genome Atlas data confirmed increased DNA methylation of two loci-SRD5A2 and CYP11A1, which also correlated with their decreased expression, in tumors with subsequent BCR development. Their aberrant cfDNA methylation was also associated with detectable levels of PSA taken after patients' post-RP. Multivariate analysis of the change in cfDNA methylation at all of CpG sites measured along with patient's treatment history predicted if a patient will develop BCR with 77.5% overall accuracy.Overall, increased DNA methylation of SRD5A2 and CYP11A1 related to androgen biosynthesis functions may play a role in BCR after patients' RP. The correlation between aberrant cfDNA methylation and detectable PSA in post-RP further suggests their utility as predictive markers for PCa recurrence. .

To assess the efficacy and prognostic factors of preoperative radiation therapy in patients of elbow arthrolysis.From October 2008 to September 2010, 43 patients with heterotopic ossification (HO) history at elbow were studied retrospectively. Radiation therapy was given in single fraction of 8 Gy within 1-4 h pre-operation. The elbow HO classifications at preoperation and the last follow-up were analyzed and their efficacy and related prognostic factors evaluated.The median follow-up period was 34 (23.24-46.26) months. The elbow function of 19 (44.2%) cases returned to normal. One case was ineffective. Only one case had vulnus swelling. Graham and Hastings HO classification scores were significantly different between pre-operation and the last follow-up (Z = -5.899, P = 0.000). Logistic analysis showed that age and time between diagnoses and treatment had a significant influence of elbow HO.Preoperative radiation therapy of 8 Gy within 1-4 h of elbow arthrolysis is both safe and effective. And greater age, milder wound and longer time between diagnoses and treatment have better outcomes.

Exon recognition is a fundamental task in bioinformatics to identify the exons of DNA sequence. Currently, exon recognition algorithms based on digital signal processing techniques have been widely used. Unfortunately, these methods require many calculations, resulting in low recognition efficiency. In order to overcome this limitation, a two-stage exon recognition model is proposed and implemented in this paper. There are three main works. Firstly, we use synergetic neural network to rapidly determine initial exon intervals. Secondly, adaptive sliding window is used to accurately discriminate the final exon intervals. Finally, parameter optimization based on artificial fish swarm algorithm is used to determine different species thresholds and corresponding adjustment parameters of adaptive windows. Experimental results show that the proposed model has better performance for exon recognition and provides a practical solution and a promising future for other recognition tasks.

We used hierarchical clustering to examine gene expression profiles generated by serial analysis of gene expression (SAGE) in a total of nine normal lung epithelial cells and non-small cell lung cancers. Separation of normal and tumor, as well as histopathological subtypes, was evident by using the 3,921 most abundant transcript tags. This distinction remained when only 115 highly differentially expressed tags were used. Furthermore, these 115 transcript tags clustered into groups suggestive of the unique biological and pathological features of the different tissues examined. Adenocarcinomas were characterized by high-level expression of small airway-associated or immunologically related proteins, whereas squamous cell carcinomas overexpressed genes involved in cellular detoxification or antioxidation. The messages of two p53-regulated genes, p21 WAF1/CIP1 and 14-3-3σ , were consistently underexpressed in the adenocarcinomas, suggesting that the p53 pathway itself might be compromised in this cancer type. Gene expression patterns observed by SAGE were consistent with results obtained by quantitative real-time PCR or cDNA array analyses by using a total of 43 lung tumor and normal samples. Thus, although derived from only a few tissue libraries, gene expression profiles obtained by using SAGE most likely represent an unbiased yet distinctive molecular signature for the most common forms of human lung cancer.

New technologies allow for genome-scale measurement of DNA methylation. In an effort to increase the clinical utility of DNA methylation as a biomarker, we have adapted a commercial bisulfite epigenotyping assay for genome-wide methylation profiling in archival formalin-fixed paraffin-embedded pathology specimens. This chapter takes the reader step by step through a biomarker discovery experiment to identify phenotype-correlated DNA methylation signatures in routine pathology specimens.

The effects of hormone and growth factor signaling on gene expression contribute significantly to breast tumorigenesis and disease progression; however, the targets of signaling networks associated with deregulated growth are not well understood. We defined the dynamic transcriptional effects elicited in MCF7, T-47D, and MDA-MB-436 breast cancer cell lines by nine regulators of growth and differentiation (17beta-estradiol, antiestrogens fulvestrant and tamoxifen, progestin R5020, antiprogestin RU486, all-trans-retinoic acid, epidermal growth factor, mitogen-activated protein/extracellular signal-regulated kinase 1/2 inhibitor U0126 and phorbol ester 12-O-tetradecanoylphorbol-13-acetate) and compared the patterns of gene regulation to published tumor expression profiles. The complex pattern of response to these agents revealed unexpected relationships between their effects, including a profound overlap in genes regulated by both steroids and epidermal growth factor, and striking overlaps between fulvestrant and all-trans-retinoic acid. Estrogen-responsive genes could be divided into two major clusters, only one of which is associated with cell proliferation. Gene ontology analysis was used to highlight functionally distinct biological responses to different mitogens. Significant correlations were identified between several clusters of drug-responsive genes and genes that discriminate estrogen receptor status or disease outcome in patient samples. The majority of estrogen receptor status discriminators were not responsive in our dataset and are therefore likely to reflect underlying differences in histogenesis and disease progression rather than growth factor signaling. This article highlights the overall impact at the gene expression level of diverse regulators of breast cancer growth and links the behavior of breast cancer cells in culture to important clinical properties of human breast tumors.

Synovial sarcoma is an aggressive spindle cell sarcoma with two major histological subtypes, biphasic and monophasic, defined respectively by the presence or absence of areas of glandular epithelial differentiation. It is characterized by a specific chromosomal translocation, t(X;18)(p11.2;q11.2), which juxtaposes the SYT gene on chromosome 18 to either the SSX1 or the SSX2 gene on chromosome X. The chimeric SYT-SSX products are thought to function as transcriptional proteins that deregulate gene expression, thereby providing a putative oncogenic stimulus. We investigated the pattern of gene expression in synovial sarcoma using cDNA microarrays containing 6548 sequence-verified human cDNAs. A tissue microarray containing 37 synovial sarcoma samples verified to bear the SYT-SSX fusion was constructed for complementary analyses. Gene expression analyses were performed on individual tumor samples; 14 synovial sarcomas, 4 malignant fibrous histiocytomas, and 1 fibrosarcoma. Statistical analysis showed a distinct expression profile for the group of synovial sarcomas as compared to the other soft tissue sarcomas, which included variably high expression of ERBB2, IGFBP2, and IGF2 in the synovial sarcomas. Immunohistochemical analysis of protein expression in tissue microarrays of 37 synovial sarcomas demonstrated strong expression of ERBB2 and IGFBP2 in the glandular epithelial component of biphasic tumors and in solid epithelioid areas of some monophasic tumors. Fluorescence in situ hybridization analysis indicated that the ERBB2 overexpression was not because of gene amplification. Differentially expressed genes were also found in a comparison of the expression profiles of the biphasic and monophasic histological subgroups of synovial sarcoma, notably several keratin genes, and ELF3, an epithelial-specific transcription factor gene. Finally, we also noted differential overexpression of several neural- or neuroectodermal-associated genes in synovial sarcomas relative to the comparison sarcoma group, including OLFM1, TLE2, CNTNAP1, and DRPLA. Our high-throughput studies of gene expression patterns, complemented by tissue microarray studies, confirm the distinctive expression profile of synovial sarcoma, provide leads for the study of glandular morphogenesis in this tumor, and identify a new potential therapeutic target, ERBB2, in a subset of cases.

Global gene expression patterns in breast cancer cells after treatment with oxidants (hydrogen peroxide, menadione, and t-butyl hydroperoxide) were investigated in three replicate experiments. RNA collected after treatment (at 1, 3, 7, and 24 h) rather than after a single time point, enabled an analysis of gene expression patterns. Using a 17,000 microarray, template-based clustering and multidimensional scaling analysis of the gene expression over the entire time course identified 421 genes as being either up- or down-regulated by the three oxidants. In contrast, only 127 genes were identified for any single time point and a 2-fold change criteria. Surprisingly, the patterns of gene induction were highly similar among the three oxidants; however, differences were observed, particularly with respect to p53, IL-6, and heat-shock related genes. Replicate experiments increased the statistical confidence of the study, whereas changes in gene expression patterns over a time course demonstrated significant additional information versus a single time point. Analyzing the three oxidants simultaneously by template cluster analysis identified genes that heretofore have not been associated with oxidative stress.

To investigate the phenotype associated with estrogen receptor alpha (ER) expression in breast carcinoma, gene expression profiles of 58 node-negative breast carcinomas discordant for ER status were determined using DNA microarray technology. Using artificial neural networks as well as standard hierarchical clustering techniques, the tumors could be classified according to ER status, and a list of genes which discriminate tumors according to ER status was generated. The artificial neural networks could accurately predict ER status even when excluding top discriminator genes, including ER itself. By reference to the serial analysis of gene expression database, we found that only a small proportion of the 100 most important ER discriminator genes were also regulated by estradiol in MCF-7 cells. The results provide evidence that ER+ and ER- tumors display remarkably different gene-expression phenotypes not solely explained by differences in estrogen responsiveness.

In previous studies using cDNA microarray analysis, we have identified an expressed sequence tag which is consistently down-regulated in six human breast tumor cell lines. In the current study, we have determined this tag to be part of the mRNA sequence of human desmocollin 3, a member of the cadherin superfamily of proteins and an integral component of desmosomes. Desmosomes are sites of adhesion between adjacent cells in layers of epithelia, as well as in some non-epithelial tissues, and play an important role in the maintenance of tissue structure. Northern analysis, quantitative real-time polymerase chain reaction assay and Western blot analysis showed that desmocollin 3 is present in normal and immortalized human mammary epithelial cells, but consistently exhibits a significant, and often complete, down-regulation in breast cancer cell lines and primary breast tumors, both at the mRNA and protein levels.

A cDNA microarray is a complex biochemical-optical sys- tem whose purpose is the simultaneous measurement of gene expres- sion for thousands of genes. In this paper we propose a general statis- tical approach to finding associations between the expression patterns of genes via the coefficient of determination. This coefficient mea- sures the degree to which the transcriptional levels of an observed gene set can be used to improve the prediction of the transcriptional state of a target gene relative to the best possible prediction in the absence of observations. The method allows incorporation of knowl- edge of other conditions relevant to the prediction, such as the appli- cation of particular stimuli or the presence of inactivating gene muta- tions, as predictive elements affecting the expression level of a given gene. Various aspects of the method are discussed: prediction quan- tification, unconstrained prediction, constrained prediction using ter- nary perceptrons, and design of predictors given small numbers of replicated microarrays. The method is applied to a set of genes under- going genotoxic stress for validation according to the manner in which it points toward previously known and unknown relationships. The entire procedure is supported by software that can be applied to large gene sets, has a number of facilities to simplify data analysis, and provides graphics for visualizing experimental data, multiple gene in- teraction, and prediction logic. © 2000 Society of Photo-Optical Instrumentation Engineers. (S1083-3668(00)00204-5)