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Background: High-grade serous ovarian carcinoma (HGSOC) is the most prevalent and aggressive histological subtype of epithelial ovarian cancer. Around 80% of individuals will experience a recurrence within five years because of resistance to chemotherapy, despite initially responding well to platinum-based treatment. Biomarkers associated with chemoresistance are desperately needed in clinical practice. Methods: We jointly analyzed the transcriptomic profiles of single-cell and bulk datasets of HGSOC to identify cell types associated with chemoresistance. Copy number variation (CNV) inference was performed to identify malignant cells. We subsequently analyzed the expression of candidate biomarkers and their relationship with patients' prognosis. The enrichment analysis and potential biological function of candidate biomarkers were explored. Then, we validated the candidate biomarker using in vitro experiments. Results: We identified 8871 malignant epithelial cells in a single-cell RNA sequencing dataset, of which 861 cells were associated with chemoresistance. Among these malignant epithelial cells, FBXO2 (F-box protein 2) is highly expressed in cells related to chemoresistance. Moreover, FBXO2 expression was found to be higher in epithelial cells from chemoresistance samples compared to those from chemosensitivity samples in a separate single-cell RNA sequencing dataset. Patients exhibiting elevated levels of FBXO2 experienced poorer outcomes in terms of both overall survival (OS) and progression-free survival (PFS). FBXO2 could impact chemoresistance by influencing the PI3K-Akt signaling pathway, focal adhesion, and ECM-receptor interactions and regulating tumorigenesis. The 50% maximum inhibitory concentration (IC50) of cisplatin decreased in A2780 and SKOV3 ovarian carcinoma cell lines with silenced FBXO2 during an in vitro experiment. Conclusions: We determined that FBXO2 is a potential biomarker linked to chemoresistance in HGSOC by combining single-cell RNA-seq and bulk RNA-seq dataset. Our results suggest that FBXO2 could serve as a valuable prognostic marker and potential target for drug development in HGSOC.

Background: Chemotherapy resistance is the main cause of ovarian cancer progression and even death. However, there are no clear indicators for predicting the risk of drug resistance in patients. Intra-tumor heterogeneity (ITH) is one of the characteristics of malignant tumors, which is associated with the treatment and prognosis of tumors. Accordingly, our study aims to investigate the correlation between the image features of intra-tumor heterogeneity and drug resistance of ovarian cancer based on artificial intelligence. Methods: We obtained hematoxylin and eosin staining frozen histopathological images of ovarian cancer and paracarcinoma tissues from the Cancer Genome Atlas. We extracted quantitative image features of whole-slide images based on the automatic image nuclear segmentation processing technology. After that, we used bioinformatics analysis to find the relationship between image features of intra-tumor heterogeneity and drug resistance. Results: Our results show that our automatic image processing process based on computer artificial intelligence can extract image features effectively, and the key image features extracted are closely related to ITH. Among them, the Perimeter.sd image feature with the most prominent ITH feature can accurately predict the risk of platinum-based chemotherapy drug resistance in ovarian cancer patients. Conclusion: Automatic image processing and feature extraction based on artificial intelligence have excellent results. Perimeter.sd can be used as a useful image feature indicator for evaluating ITH. ITH is associated with drug resistance of ovarian cancer, so ITH characteristics can be used as an effective indicator to evaluate drug resistance in patients with ovarian cancer.

Abstract Background Hepatocellular carcinoma (HCC) is a cancer with a poor prognosis. Many recent studies have suggested that pyroptosis is important in tumour progression. However, the role of pyroptosis-related genes (PRGs) in HCC remains unclear. Materials and methods We identified differentially expressed PRGs in tumours versus normal tissues. Through univariate, LASSO, and multivariate Cox regression analyses, a prognostic PRG signature was established. The signature effectiveness was evaluated by time-dependent receiver operating characteristic (t-ROC) curve and Kaplan–Meier (KM) survival analysis. The signature was validated in the ICGC (LIRI-JP) cohort. In addition, single-sample gene enrichment analysis (ssGSEA) showed the infiltration of major immune cell types and the activity of common immune pathways in different subgroups. Results Twenty-nine pyroptosis-related DEGs from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset were detected, and four genes (CTSV, CXCL8, MKI67 and PRF1) among them were selected to construct a prognostic signature. Then, the patients were divided into high- and low-risk groups. The pyroptosis-related signature was significantly associated with overall survival (OS). In addition, the patients in the high-risk group had lower levels of immune infiltration. Conclusion The prognostic signature for HCC based on 4 pyroptosis-related genes has reliable prognostic and predictive value for HCC patients.

Over various terrain types, natural forests exhibit tree size and biomass variation. We started long- term research that consists of forest vegetation surveys in the Dinghushan National Nature Reserve to comprehensively investigate productivity based on the structure and species composition of China’s forest communities. We grouped the trees into three categories, i.e., as large or mature (DBH > 30 cm), medium-sized or growing (DBH 10–30 cm), and small-sized or regenerating seedlings (DBH

Purpose: The study aimed to assess the value of the resting-state electroencephalogram (EEG)-based convolutional neural network (CNN) method for the diagnosis of depression and its severity in order to better serve depressed patients and at-risk populations.Methods: In this study, we used the resting state EEG-based CNN to identify depression and evaluated its severity. The EEG data were collected from depressed patients and healthy people using the Nihon Kohden EEG-1200 system. Analytical processing of resting-state EEG data was performed using Python and MATLAB software applications. The questionnaire included the Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), Symptom Check-List-90 (SCL-90), and the Eysenck Personality Questionnaire (EPQ).Results: A total of 82 subjects were included in this study, with 41 in the depression group and 41 in the healthy control group. The area under the curve (AUC) of the resting-state EEG-based CNN in depression diagnosis was 0.74 (95%CI: 0.70–0.77) with an accuracy of 66.40%. In the depression group, the SDS, SAS, SCL-90 subscales, and N scores were significantly higher in the major depression group than those in the non-major depression group (p < 0.05). The AUC of the model in depression severity was 0.70 (95%CI: 0.65–0.75) with an accuracy of 66.93%. Correlation analysis revealed that major depression AI scores were significantly correlated with SAS scores (r = 0.508, p = 0.003) and SDS scores (r = 0.765, p < 0.001).Conclusion: Our model can accurately identify the depression-specific EEG signal in terms of depression diagnosis and severity identification. It would eventually provide new strategies for early diagnosis of depression and its severity.

Abstract Background Glioblastoma (GBM) is the most common primary malignant brain tumor in adults. For patients with GBM, the median overall survival (OS) is 14.6 months and the 5‐year survival rate is 7.2%. It is imperative to develop a reliable model to predict the survival probability in new GBM patients. To date, most prognostic models for predicting survival in GBM were constructed based on bulk RNA‐seq dataset, which failed to accurately reflect the difference between tumor cores and peripheral regions, and thus show low predictive capability. An effective prognostic model is desperately needed in clinical practice. Methods We studied single‐cell RNA‐seq dataset and The Cancer Genome Atlas‐glioblastoma multiforme (TCGA‐GBM) dataset to identify differentially expressed genes (DEGs) that impact the OS of GBM patients. We then applied the least absolute shrinkage and selection operator (LASSO) Cox penalized regression analysis to determine the optimal genes to be included in our risk score prognostic model. Then, we used another dataset to test the accuracy of our risk score prognostic model. Results We identified 2128 DEGs from the single‐cell RNA‐seq dataset and 6461 DEGs from the bulk RNA‐seq dataset. In addition, 896 DEGs associated with the OS of GBM patients were obtained. Five of these genes (LITAF, MTHFD2, NRXN3, OSMR, and RUFY2) were selected to generate a risk score prognostic model. Using training and validation datasets, we found that patients in the low‐risk group showed better OS than those in the high‐risk group. We validated our risk score model with the training and validating datasets and demonstrated that it can effectively predict the OS of GBM patients. Conclusion We constructed a novel prognostic model to predict survival in GBM patients by integrating a scRNA‐seq dataset and a bulk RNA‐seq dataset. Our findings may advance the development of new therapeutic targets and improve clinical outcomes for GBM patients.

Abstract Hedgehog (Hh) signaling plays a critical role in embryogenesis and tissue homeostasis, and its deregulation has been associated with tumor growth. The tumor suppressor SuFu inhibits Hh signaling by preventing the nuclear translocation of Gli and suppressing cell proliferation. Regulation of SuFu activity and stability is key to controlling Hh signaling. Here, we unveil SuFu Negating Protein 1 (SNEP1) as a novel Hh target, that enhances the ubiquitination and proteasomal degradation of SuFu and thus promotes Hh signaling. We further show that the E3 ubiquitin ligase LNX1 plays a critical role in the SNEP1-mediated degradation of SuFu. Accordingly, SNEP1 promotes colorectal cancer (CRC) cell proliferation and tumor growth. High levels of SNEP1 are detected in CRC tissues and are well correlated with poor prognosis in CRC patients. Moreover, SNEP1 overexpression reduces sensitivity to anti-Hh inhibitor in CRC cells. Altogether, our findings demonstrate that SNEP1 acts as a novel feedback regulator of Hh signaling by destabilizing SuFu and promoting tumor growth and anti-Hh resistance.

Our understanding on how CAFs can be activated to support tumour progression is still limited. Here, the authors demonstrate that adenosine produced in the tumour microenvironment can enhance the expression of CD73 in CAFs ultimately driving CD8 T-Cell suppression and tumour growth.

ObjectiveIschemic stroke (IS) with subsequent cerebrocardiac syndrome (CCS) has a poor prognosis. We aimed to investigate electrocardiogram (ECG) changes after IS with artificial intelligence (AI).MethodsWe collected ECGs from a healthy population and patients with IS, and then analyzed participant demographics and ECG parameters to identify abnormal features in post-IS ECGs. Next, we trained the convolutional neural network (CNN), random forest (RF) and support vector machine (SVM) models to automatically detect the changes in the ECGs; Additionally, We compared the CNN scores of good prognosis (mRS ≤ 2) and poor prognosis (mRS > 2) to assess the prognostic value of CNN model. Finally, we used gradient class activation map (Grad-CAM) to localize the key abnormalities.ResultsAmong the 3506 ECGs of the IS patients, 2764 ECGs (78.84%) led to an abnormal diagnosis. Then we divided ECGs in the primary cohort into three groups, normal ECGs (N-Ns), abnormal ECGs after the first ischemic stroke (A-ISs), and normal ECGs after the first ischemic stroke (N-ISs). Basic demographic and ECG parameter analyses showed that heart rate, QT interval, and P-R interval were significantly different between 673 N-ISs and 3546 N-Ns (p < 0.05). The CNN has the best performance among the three models in distinguishing A-ISs and N-Ns (AUC: 0.88, 95%CI = 0.86-0.90). The prediction scores of the A-ISs and N-ISs obtained from the all three models are statistically different from the N-Ns (p < 0.001). Futhermore, the CNN scores of the two groups (mRS > 2 and mRS ≤ 2) were significantly different (p < 0.05). Finally, Grad-CAM revealed that the V4 lead may harbor the highest probability of abnormality.ConclusionOur study showed that a high proportion of post-IS ECGs harbored abnormal changes. Our CNN model can systematically assess anomalies in and prognosticate post-IS ECGs.

Spherical bearings are widely applied in high-speed railway bridges (HSRBs) in China. The experimental and computational analyses were carried out to help understand the damage mechanism of these bearings under earthquake loading. A shaking table test of scaled HSRB specimen (installed with spherical bearings) was performed under the simulated earthquake action, and the intensities were, respectively, 0.15 g, 0.20 g, 0.32 g, and 0.38 g (common intensities in China) of actual earthquakes in accordance with similarity relationships. After investigating and analyzing results of the shaking table test, it is shown that no damage occurred to movable bearings in all experimental earthquake scenarios, while slight damage could be found in fixed bearings at 0.32 g earthquake. Moreover, a finite element (FE) model of the prototype HSRB was established and validated. The damage degree of spherical bearings in stronger earthquakes (i.e., 0.40 g to 1.00 g) was studied through this validated FE model. The numerical results showed that the fixed bearing was completely damaged at 0.80 g earthquake, while only moderate damage occurred to the movable bearing at that intensity.

Rounded rectangular cross section piers were widely used for high-speed railway (HSR) bridges in China. However, the performance of such piers under seismic scenarios has not been well studied. To study the earthquake behavior and damage of rounded rectangular cross section piers under different intensities of earthquake excitation, nine scaled pier specimens were constructed and tested on the shaking table. Experimental results show that the specimen remains elastic (no or slight damaged) for all experimental earthquake scenarios (from 0.45 g to 0.96 g). Finite element (FE) models were developed and validated by the experimental results. Using this FE model, the damage levels of these specimens under severe earthquake excitations (from 1.05 g to 1.95 g) were quantified. Numerical results show that the specimen in transverse direction shows no or slight damage, while repairable damage can be seen in longitudinal direction as the earthquake intensity increases from 1.05 g to 1.65 g. Repairable and unrepairable damage can be seen in transverse and longitudinal direction, respectively, as the earthquake intensity increases to 1.95 g. Researchers can make good use of these findings for better earthquake design or protection of this type of HSR piers in the future.

To investigate refractory hypercholesterolemia, a female patient and relatives were subjected to whole-genome sequencing. The proband was found to have compound heterozygous substitutions p. Arg446Gln and c.1118+3G>T in ABCG5, one of two genes causing sitosterolemia. When tracing these variants in the full pedigree, all maternally related heterozygotes for the intronic ABCG5 variant exhibited large platelets (over 30 fl), which segregated in an autosomal dominant manner, consistent with macrothrombocytopenia, or large platelet syndrome which may be associated with a bleeding tendency. In vitro cell-line and in vivo rat model experiments supported a pathogenic role for the variant and the macrothrombocytopenia was recapitulated in heterozygous rats and human cell lines exhibiting that single variant. Ezetimibe treatment successfully ameliorated all the symptoms of the proband with sitosterolemia and resolved the macrothrombocytopenia of the treated heterozygote relatives. Subsequently, in follow up these observations, platelet size, and size distribution were measured in 1,180 individuals; 30 were found to be clinically abnormal, three of which carried a single known pathogenic ABCG5 variant (p.Arg446Ter) and two individuals carried novel ABCG5 variants of uncertain significance. In this study, we discovered that identification of large platelets and therefore a possible macrothrombocytopenia diagnosis could easily be inadvertently missed in clinical practice due to variable instrument settings. These findings suggest that ABCG5 heterozygosity may cause macrothrombocytopenia, that Ezetimibe treatment may resolve macrothrombocytopenia in such individuals, and that increased attention to platelet size on complete blood counts can aid in the identification of candidates for ABCG5 genetic testing who might benefit from Ezetimibe treatment.

BackgroundQuiescin Q6 sulfhydryl oxidase 2 (QSOX2), an enzyme that can be directly secreted into the extracellular space, is known to be associated with oxidative protein folding. However, whether QSOX2 is abnormally expressed in non-small cell lung cancer (NSCLC) and its role in tumor growth remains unclear.MethodsReal-time quantitative PCR (qPCR), immunohistochemistry (IHC), bioinformatics analyses were applied to analyze the expression pattern and prognostic significance of QSOX2 in NSCLC. Xenografts model, enzyme-linked immunosorbent assays (ELISA), western blot analysis (WB), and IHC were preformed to examine in vivo tumor suppression and intracellular and extracellular expression of QSOX2. Flow cytometry, WB and qPCR analyses were used to elucidate the role of QSOX2 in cell cycle regulation. Chromatin immunoprecipitation assay (ChIP) assay and Dual-Luciferase reporter assay were employed to investigate transcriptional regulation of QSOX2 by E2F Transcription Factor 1 (E2F1).ResultsQuiescin sulfhydryl oxidase 2 was significantly overexpressed in NSCLC and associated with poor survival in advanced-stage patients. The intracellular and extracellular expression of QSOX2 by tumor cells markedly decreased after anti-cancer therapy in vitro, in vivo and in the clinic. Moreover, QSOX2 silencing in NSCLC cell lines resulted in inhibition of cancer cell proliferation, induction of apoptosis, and decreased expression of cell division-related genes (CENPF and NUSAP1) and Wnt pathway activators (PRRX2 and Nuc-β-catenin). Mechanistically, QSOX2 was expressed periodically during cell cycle and directly regulated by E2F1.ConclusionsOur findings demonstrate that QSOX2 is directly regulated by E2F1 in the cell cycle, which is essential for the proliferation of NSCLC cells. Furthermore, QSOX2 is a prognostic indicator for NSCLC and may be developed into a biomarker for monitoring tumor burden and therapeutic progress.

Abstract Background Forkhead box M1 (FOXM1) is a proliferation-associated transcription factor of the forkhead box proteins superfamily, which includes four isoforms FOXM1a, b, c, and d. FOXM1 has been implicated in hepatocellular carcinoma (HCC) progression, but the underlying molecular mechanism remains elusive. In this study, we aim to clarify the molecular basis for FOXM1-mediated HCC progression. Methods Bioinformatic analysis was used to explore the differentially expressed genes predicting HCC proliferation. The expression of FOXM1 and kinesin family member (KIF)4A was confirmed by western blotting and immunohistochemistry in HCC tissues. Kaplan-Meier survival analysis was conducted to analyze the clinical impact of FOXM1 and KIF4A on HCC. The effect of FOXM1 on the regulation of KIF4A expression was studied in cell biology experiments. The interaction between KIF4A and FOXM1 was analyzed by chromatin immunoprecipitation and luciferase experiments. A series of experiments was performed to explore the functions of FOXM1/KIF4A in HCC progression, such as cell proliferation, cell growth, cell viability, and cell cycle. A xenograft mouse model was used to explore the regulatory effect of FOXM1-KIF4A axis on HCC tumor growth. Results FOXM1 and KIF4A were overexpressed in human primary HCC tissues compared to that in matched adjacent normal liver tissue and are significant risk factors for HCC recurrence and shorter survival. We found that KIF4A was dominantly regulated by FOXM1c among the four isoforms, and further identified KIF4A as a direct downstream target of FOXM1c. Inhibiting FOXM1 decreased KIF4A expression in HCC cells, whereas its overexpression had the opposite effect. FOXM1-induced HCC cell proliferation was dependent on elevated KIF4A expression as KIF4A knockdown abolished FOXM1-induced proliferation of HCC cells both in vitro and in vivo. Conclusion The FOXM1–KIF4A axis mediates human HCC progression and is a potential therapeutic target for HCC treatment.

Long noncoding RNA (lncRNA) plays crucial roles in various biological processes of different cancers, especially acting as a competing endogenous RNA (ceRNA). However, the role of lncRNA-mediated ceRNA in Wilms tumor (WT), which is the most common malignant kidney cancer in children, remains unknown. In present study, RNA sequence profiles and clinical data of 125 patients with WT consisting of 119 tumor and 6 normal tissues from Therapeutically Applicable Research To Generate Effective Treatments database were analyzed. A total of 1833 lncRNAs, 156 microRNAs (miRNAs), and 3443 messenger RNAs (mRNAs) were identified as differentially expressed (DE) using “DESeq2” package. The lncRNA-miRNA-mRNA ceRNA regulatory network involving 748 DElncRNAs, 33 DEmiRNAs, and 189 DEmRNAs was constructed based on miRcode, Targetscan, miRTarBase, and miRDB database. Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that DEmRNAs were mainly enriched in cell proliferation-related processes and tumor-related pathways, respectively, and 13 hub genes were identified by a protein–protein interaction network. Survival analysis detected 48 lncRNAs, 7 miRNAs, and 16 mRNAs to have significant impact on the overall survival of patients with WT. Additionally, we found that 6 DElncRNAs with potential prognostic value were correlated with tumor stage ( DENND5B-AS1 ) and histologic classification ( TMPO-AS1 , RP3-523K23.2 , RP11-598F7.3 , LAMP5-AS1 , and AC013275.2 ) of patients with WT. Our research provides a great insight into understanding the molecular mechanism underlying occurrence and progression of WT, as well as the potential to develop targeted therapies and prognostic biomarkers.

Macrophage migration inhibitory factor (MIF) has multiple intrinsic enzymatic activities of the dopachrome/phenylpyruvate tautomerase and thiol protein oxidoreductase, and plays an important role in the development of obesity as a pro-inflammatory cytokine. However, which enzymatic activity of MIF is responsible for regulating in obesity are still unknown. In the present study, we investigated the roles of the tautomerase of MIF in high fat diet (HFD)-induced obesity using MIF tautomerase activity-lacking (MIFP1G/P1G) mice. Our results showed that the serum MIF and the expression of MIF in adipose tissue were increased in HFD-treated mice compared with normal diet fed mice. The bodyweights were significantly reduced in MIFP1G/P1G mice compared with WT mice fed with HFD. The sizes of adipocytes were smaller in MIFP1G/P1G mice compared with WT mice fed with HFD using haematoxylin and eosin (H&E) staining. In addition, the MIFP1G/P1G mice reduced the macrophage infiltration, seen as the decreases of the expression of inflammatory factors such as F4/80, IL-1β, TNFα, MCP1, and IL-6. The glucose tolerance tests (GTT) and insulin tolerance tests (ITT) assays showed that the glucose tolerance and insulin resistance were markedly improved, and the expressions of IRS and PPARγ were upregulated in adipose tissue from MIFP1G/P1G mice fed with HFD. Furthermore, we observed that the expressions of Bax, a pro-apoptotic protein, and the cleaved caspase 3-positive cells in white tissues were decreased and the ratio of Bcl2/Bax was increased in MIFP1G/P1G mice compared with WT mice. Taken together, our results demonstrated that the tautomerase activity-lacking of MIF significantly alleviated the HFD-induced obesity and adipose tissue inflammation, and improved insulin resistance in MIFP1G/P1G mice.

As cancer mortality is high in most regions of the world, early screening of cancer has become increasingly important. Minimally invasive screening programs that use peripheral blood mononuclear cells (PBMCs) are a new and reliable strategy that can achieve early detection of tumors by identifying marker genes. From 797 datasets, four (GSE12771, GSE24536, GSE27562, and GSE42834) including 428 samples, 236 solid tumor cases, and 192 healthy controls were chosen according to the inclusion criteria. A total of 285 genes from among 440 reported genes were selected by meta-analysis. Among them, 4 of the top significantly differentially expressed genes (ANXA1, IFI44, IFI44L, and OAS1) were identified as marker genes of PBMCs. Pathway enrichment analysis identified, two significant pathways, the 'primary immunodeficiency' pathway and the 'cytokine-cytokine receptor interaction' pathway. Protein- protein interaction (PPI) network analysis revealed the top 27 hubs with a degree centrality greater than 23 to be hub genes. We also identified 3 modules in Molecular Complex Detection (MCODE) analysis: Cluster 1 (related to ANXA1), Cluster 2 (related to IFI44 and IFI44L) and Cluster 3 (related to OAS1). Among the 4 marker genes, IFI44, IFI44L, and OAS1 are potential diagnostic biomarkers, even though their results were not as remarkable as those for ANXA1 in our study. ANXA1 is involved in the immunosuppressive mechanism in tumor-bearing hosts and may be used in a new strategy involving the use of the host's own immunity to achieve tumor suppression.

BACKGROUND:Hepatocellular carcinoma (HCC) is one of the most lethal and malignant tumours worldwide. New therapeutic targets for HCC are urgently needed. CYCLOPS (copy number alterations yielding cancer liabilities owing to partial loss) genes have been noted to be associated with cancer-targeted therapies. Therefore, we intended to explore the effects of the CYCLOPS gene RBM17 on HCC oncogenesis to determine if it could be further used for targeted therapy. METHODS:We collected data on 12 types of cancer from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) queries for comparison with adjacent non-tumour tissues. RBM17 expression levels, clinicopathological factors and survival times were analysed. RNAseq data were downloaded from the Encyclopaedia of DNA Elements database for molecular mechanism exploration. Two representative HCC cell models were built to observe the proliferation capacity of HCC cells when RBM17 expression was inhibited by shRBM17. Cell cycle progression and apoptosis were also examined to investigate the pathogenesis of RBM17. RESULTS:Based on 6,136 clinical samples, RBM17 was markedly overexpressed in most cancers, especially HCC. Moreover, data from 442 patients revealed that high RBM17 expression levels were related to a worse prognosis. Overexpression of RBM17 was related to the iCluster1 molecular subgroup, TNM stage, and histologic grade. Pathway analysis of RNAseq data suggested that RBM17 was involved in mitosis. Further investigation revealed that the proliferation rates of HepG2 (P = 0.003) and SMMC-7721 (P = 0.030) cells were significantly reduced when RBM17 was knocked down. In addition, RBM17 knockdown also arrested the progression of the cell cycle, causing cells to halt at the G2/M phase. Increased apoptosis rates were also found in vitro. CONCLUSION:These results suggest that RBM17 is a potential therapeutic target for HCC treatment.

Immune thrombocytopenia (ITP) is an acquired bleeding disease due to immune-mediated destruction of antilogous platelets and ineffective thrombopoiesis. Although the etiology of ITP remains unknown, genetic variants are thought to predispose individuals to the disease. Several candidate gene analyses have identified several loci that increased ITP susceptibility, but no systematic genetic analysis on a genome-wide scope. To extend the genetic evidence and to identify novel candidates of ITP, we performed a pooling genome-wide association study (GWAS) by IlluminaHumanOmniZhongHua-8 combining pathway analysis in 200 ITP cases and 200 controls from Chinese Han population (CHP). The results revealed that 4 novel loci (rs117503120, rs5998634, rs4483616, and rs16866133) were strongly associated with ITP (P

Hepatitis A virus (HAV), a classic nonenveloped virus, has recently been found to be released mainly in the form of quasi-enveloped HAV (eHAV) by hijacking host endosomal sorting complexes required for transport (ESCRT) complexes. Unlike the nonenveloped virion, eHAV contains the viral protein pX on the surface of the HAV capsid as an extension of VP1. How HAV capsids acquire the host envelope and whether the pX protein is involved in this process were previously unknown. Here, we analyse the role of pX in foreign protein secretion in exosome-like extracellular vesicles (EVs) and the formation of eHAV. Fusion of pX to eGFP guided eGFP into exosome-like EVs through directing eGFP into multivesicular bodies (MVBs), and apoptosis-linked gene 2-interacting protein X (ALIX) release was significantly enhanced. Coimmunoprecipitation (co-IP) demonstrated the interaction between pX and the ALIX V domain. Removal of the C-terminal half of pX abolished eHAV release and reduced the interaction between the HAV virion and ALIX. Finally, the C-terminal half of pX alone was sufficient for loading eGFP into EVs by interacting with ALIX. In conclusion, the C-terminal part of pX is important for eHAV production and may have potential for large protein complex loading into exosome-like EVs for therapeutic purposes.

Abstract Background Autism spectrum disorders (ASD) are hereditary, heterogeneous and biologically complex neurodevelopmental disorders. Individual studies on gene expression in ASD cannot provide clear consensus conclusions. Therefore, a systematic review to synthesize the current findings from brain tissues and a search tool to share the meta-analysis results are urgently needed. Methods Here, we conducted a meta-analysis of brain gene expression profiles in the current reported human ASD expression datasets (with 84 frozen male cortex samples, 17 female cortex samples, 32 cerebellum samples and 4 formalin fixed samples) and knock-out mouse ASD model expression datasets (with 80 collective brain samples). Then, we applied R language software and developed an interactive shared and updated database (dbMDEGA) displaying the results of meta-analysis of data from ASD studies regarding differentially expressed genes (DEGs) in the brain. Results This database, dbMDEGA ( https://dbmdega.shinyapps.io/dbMDEGA/ ), is a publicly available web-portal for manual annotation and visualization of DEGs in the brain from data from ASD studies. This database uniquely presents meta-analysis values and homologous forest plots of DEGs in brain tissues. Gene entries are annotated with meta-values, statistical values and forest plots of DEGs in brain samples. This database aims to provide searchable meta-analysis results based on the current reported brain gene expression datasets of ASD to help detect candidate genes underlying this disorder. Conclusion This new analytical tool may provide valuable assistance in the discovery of DEGs and the elucidation of the molecular pathogenicity of ASD. This database model may be replicated to study other disorders.

SWItch/Sucrose NonFermentable (SWI/SNF) is a set of multi-subunits chromatin remodeling complexes, playing important roles in a variety of biological processes. Loss-of-function mutations in the genes encoding SWI/SNF subunits have been reported in more than 20% of human cancers. Thus, it was widely considered as a tumor suppressor in the past decade. However, recent studies reported that some genes encoding subunits of SWI/SNF complexes were amplified and play oncogenic roles in human cancers. In present study, we summarized the genetic alteration spectrum of SWI/SNF complexes, and firstly systematically estimated both the copy number variations and point mutations of all 30 genes encoding the subunits in this complex. Additionally, the bioinformatics analyses were performed for two significantly amplified genes, ACTL6A and BRD9, to investigate their oncogenic roles in human cancers. Our findings may lay a foundation for the discovery of potential treatment targets in SWI/SNF complexes of cancers.

Hepatitis C virus (HCV) spread involves two distinct entry pathways: cell-free transmission and cell-to-cell transmission. Cell-to-cell transmission is not only an efficient way for viruses to spread but also an effective method for escaping neutralizing antibodies. We adapted the viral infection-activated split-intein-mediated reporter system (VISI) and developed a straightforward model for Live-cell monitoring of HCV cell-to-cell transmission ex-vivo: co-culture of HCV infected donor cells (red signal) with uninfected recipient cells (green signal) and elimination of the cell-free transmission by adding potent neutralizing antibody AR3A in the supernatant. With this model, the efficiency of cell-to-cell transmission can be evaluated by counting the number of foci designated by the green signal of recipient cells.

Recent evidence suggests that aberrant activation of Hedgehog (Hh) signaling by Gli transcription factors is characteristic of a variety of aggressive human carcinomas including ovarian cancer. Therefore, chemotherapeutic agents that inhibit activation of Gli transcription factors have emerged as promising novel therapeutic drugs for ovarian cancer.In this study, we show that activation of Hh signaling promoted cellular migration and invasion, whereas blockade of Hh signaling with GANT61 suppressed cellular migration and invasion in ovarian cancer cells. After treatment with GANT61, cDNA microarray analyses revealed changes in many genes such as Integrin β4 subunit (ITGB4), focal adhesion kinase (FAK), etc. Furthermore, ITGB4 expression was up-regulated by Sonic Hedgehog (Shh) ligand and down-regulated by Hh signaling inhibitor. The Shh-mediated ovarian cell migration and invasion was blocked by neutralizing antibodies to ITGB4. In addition, phosphorylations of FAK were increased by Shh and decreased by Hh signaling inhibitor. Inhibition of Gli1 expression using siRNA mimicked the effects of GANT61 treatment, supporting the specificity of GANT61. Further investigations showed that activation of FAK was required for Shh-mediated cell migration and invasion. Finally, we found that down-regulation of Gli reduced the expression of ITGB4 and the phosphorylated FAK, resulting in the inhibition of tumor growth in vivo.The Hh signaling pathway induces cell migration and invasion through ITGB4-mediated activation of FAK in ovarian cancer. Our findings suggest that the diminishment of crosstalk between phosphorylated FAK and ITGB4 due to the down-regulation of Gli family transcription factors might play a pivotal role for inhibiting ovarian cancer progression.