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Influence of RORC on the growth and proliferation of bladder cancer in vivo

Supplementary Figure Legends

Supplementary Tables include Table S1 (The correlation of clinicopathological characteristics and overall survival in bladder cancer patients), Table S2 (The primer sequences of qRT-PCR assay), Table S3 (Acronyms and abbreviations), and Table S4 (The association of clinicopathological characteristics with RORC, PD-L1, ITGB6, STAT3 and p-STAT3 expression in bladder cancer patients).

Retinoic acid–related orphan receptor C (RORC) is a member of the nuclear orphan receptor family and performs critical regulatory functions in cell proliferation, metastasis, and chemoresistance in various types of malignant tumors. Here we showed that expression of RORC is lost in tumor tissues of bladder cancer patients. Enhanced expression of RORC suppressed cell proliferation and glucose metabolism and increased cisplatin-induced apoptosis in vitro and in vivo. RORC bound the promoter region of programmed death ligand-1 (PD-L1) and negatively regulated PD-L1 expression. PD-L1 directly interacted with integrin β6 (ITGB6) and activated the ITGB6/FAK signaling pathway. RORC prevented the nuclear translocation of STAT3 via suppression of the PD-L1/ITGB6 signaling pathway, which further inhibited bladder cell proliferation and glucose metabolism and increased cisplatin-induced apoptosis. These findings reveal that RORC regulates bladder cancer cell proliferation, glucose metabolism, and chemoresistance by participating in the PD-L1/ITGB6/STAT3 signaling axis. Moreover, this new understanding of PD-L1 signaling may guide the selection of therapeutic targets to prevent tumor recurrence.Significance:These findings suggest that RORC-mediated regulation of a PD-L1/ITGB6/FAK/STAT3 signaling axis in bladder cancer provides several potential therapeutic targets to prevent tumor progression.

This paper investigates algebraic objects equipped with an operator, such as operated monoids, operated algebras etc. Various free object functors in these operated contexts are explicitly constructed. For operated algebras whose operator satisfies a set $\Phi$ of relations (usually called operated polynomial identities (aka. OPIs)), Guo defined free objects, called free $\Phi$-algebras, via universal algebra. Free $\Phi$-algebras over algebras are studied in details. A mild sufficient condition is found such that $\Phi$ together with a Gr\"obner-Shirshov basis of an algebra $A$ form a Gr\"obner-Shirshov basis of the free $\Phi$-algebra over algebra $A$ in the sense of Guo et al.. Ample examples for which this condition holds are provided, such as all Rota-Baxter type OPIs, a class of differential type OPIs, averaging OPIs and Reynolds OPI., Comment: Slightly revised version of the published paper in Journal of Algebra

Liver metastases are common in pancreatic neuroendocrine tumors (PanNETs) patients and they are considered a poor prognostic marker. This study aims to analyze the spatiotemporal patterns of genomic variations between primary and metastatic tumors, and to identify the key related biomolecular pathways. We performed next-generation sequencing on paired tissue specimens of primary PanNETs (n = 11) and liver metastases (n = 12). Low genomic heterogeneity between primary PanNETs and liver metastases was observed. Genomic analysis provided evidence that polyclonal seeding is a prevalent event during metastatic progression, and may be associated with the progression-free survival. Besides this, copy number variations of BRCA1/BRCA2 seem to be associated with better prognosis. Pathways analysis showed that pathways in cancer, DNA repair, and cell cycle regulation-related pathways were significantly enriched in primary PanNETs and liver metastases. The study has shown a high concordance of gene mutations between the primary tumor and its metastases and the shared gene mutations may occur during oncogenesis and predates liver metastasis, suggesting an earlier onset of metastasis in patients with PanNETs, providing novel insight into genetic changes in metastatic tumors of PanNETs.

Fructose-1,6-bisphosphatase (FBP1) is a rate-limiting enzyme in gluconeogenesis and an important tumor suppressor in human malignancies. Here, we aimed to investigate the expression profile of FBP1 in ovarian cancer, the molecular mechanisms that regulate FBP1 expression and to examine how the FBP1 regulatory axis contributes to tumorigenesis and progression in ovarian cancer. We showed that FBP1 expression was significantly decreased in ovarian cancer tissues compared with normal ovarian tissues, and low-FBP1 expression predicted poor prognosis in patients with ovarian cancer. The enhanced expression of FBP1 in ovarian cancer cell lines suppressed proliferation and 2-D/3-D invasion, reduced aerobic glycolysis, and sensitized cancer cells to cisplatin-induced apoptosis. Moreover, DNA methylation and C-MYC binding at the promoter inhibited FBP1 expression. Furthermore, through physical interactions with signal transducer and activator of transcription 3 (STAT3), FBP1 suppressed nuclear translocation of STAT3 and exerted its non-metabolic enzymatic activity to induce the dysfunction of STAT3. Thus, our study suggests that FBP1 may be a valuable prognostic predictor for ovarian cancer. C-MYC-dependent downregulation of FBP1 acted as a tumor suppressor via modulating STAT3, and the C-MYC/FBP1/STAT3 axis could be a therapeutic target.

Background Although programmed cell death‐ligand 1 (PD‐L1) plays a well‐known function in immune checkpoint response by interacting with programmed cell death‐1 (PD‐1), the cell‐intrinsic role of PD‐L1 in tumors is still unclear. Here, we explored the molecular regulatory mechanism of PD‐L1 in the progression and metastasis of ovarian cancer. Methods Immunohistochemistry of benign tissues and ovarian cancer samples was performed, followed by migration, invasion, and angiogenesis assays in PD‐L1‐knockdown ovarian cancer cells. Immunoprecipitation, mass spectrometry, and chromatin immunoprecipitation were conducted along with zebrafish and mouse experiments to explore the specific functions and mechanisms of PD‐L1 in ovarian cancer. Results Our results showed that PD‐L1 induced angiogenesis, which further promoted cell migration and invasion in vitro and in vivo of ovarian cancer. Mechanistically, PD‐L1 was identified to directly interact with vascular endothelial growth factor receptor‐2 (VEGFR2) and then activated the FAK/AKT pathway, which further induced angiogenesis and tumor progression, leading to poor prognosis of ovarian cancer patients. Meanwhile, PD‐L1 was found to be regulated by the oncogenic transcription factor c‐JUN at the transcriptional level, which enhanced the expression of PD‐L1 in ovarian cancer. Furthermore, we demonstrated that PD‐L1 inhibitor durvalumab, combined with the antiangiogenic drug, apatinib, could enhance the effect of anti‐angiogenesis and the inhibition of cell migration and invasion. Conclusion Our results demonstrated that PD‐L1 promoted the angiogenesis and metastasis of ovarian cancer by participating in the c‐JUN/VEGFR2 signaling axis, suggesting that the combination of PD‐L1 inhibitor and antiangiogenic drugs may be considered as a potential therapeutic approach for ovarian cancer patients., This manuscript demonstrated that PD‐L1 promoted the angiogenesis and metastasis of ovarian cancer by participating in the c‐JUN/VEGFR2 signaling axis, and suggested that the combination of PD‐L1 inhibitor and antiangiogenic drugs may be considered as a potential therapeutic approach for ovarian cancer patients.

Lipid metabolism is extensively reprogrammed in pancreatic ductal adenocarcinoma (PDAC). Stearoyl-coenzyme A desaturase (SCD) is a critical lipid regulator that was unexplored in PDAC. Here, we characterized the existence of cancer-associated fibroblasts (CAFs) with high SCD expression, and revealed them as an unfavorable prognostic factor. Therefore, primary CAFs and pancreatic cancer cells were harvested and genetically labeled. The mixture of CAFs and cancer cells were co-injected into scd

When the intelligent vehicle is driving on the road, the driving state of the vehicle needs to be monitored and evaluated in real time, such as whether the distance from the vehicle or obstacle in front of it is often less than or close to the safe driving distance, whether it often deviates from the lane at high speed, whether the temperature of the power battery is often higher or lower, etc. The intelligent vehicle has rich environment perception systems and communication systems. A large amount of effective driving state information is obtained through these systems, then the information is fused by intelligent algorithm, which is very useful to evaluate the driving state. By using the developed Intelligent Connected Vehicle (ICV) information collection system platform, including vision, radar, environmental perception, positioning, and V2X communication system for obtaining roadside information, etc. various driving state parameters of the vehicle during the current driving process of the intelligent vehicle are obtained in real time when the vehicle is driving, then transmitted to the monitoring platform, and the intelligent immune algorithm is applied to establish model on monitoring platform. In the model, the state space representation of related problems is designed. The user establishes the autologous library according to the typical vehicle driving state in the monitoring road driving characteristics, which is used as the known antigen. The parameters of the real-time driving state of the vehicle are used as the unknown antigen, and the immune algorithm model is applied to get the evaluation of the current vehicle driving state and feedback the evaluation results to the vehicle and give early warning. In this paper, the model is verified by experiments, and the data are analyzed. In the experiment, the evaluation results of the monitoring platform are consistent with the state of the driving vehicle, which shows the feasibility of this model for the evaluation of the driving state of the ICV.

Recepteur d’origine nantais (RON) has been implicated in cell proliferation, metastasis, and chemoresistance of various human malignancies. The short-form RON (sf-RON) encoded by RON transcripts was overexpressed in gastric cancer tissues, but its regulatory functions remain illustrated. Here, we found that sf-RON promoted gastric cancer cell proliferation by enhancing glucose metabolism. Furthermore, sf-RON was proved to induce the β-catenin expression level through the AKT1/GSK3β signaling pathway. Meanwhile, the binding sites of β-catenin were identified in the promoter region of SIX1 and it was also demonstrated that β-catenin positively regulated SIX1 expression. SIX1 enhanced the promoter activity of key proteins in glucose metabolism, such as GLUT1 and LDHA. Results indicated that sf-RON regulated the cell proliferation and glucose metabolism of gastric cancer by participating in a sf-RON/β-catenin/SIX1 signaling axis and had significant implications for choosing the therapeutic target of gastric cancer. Electronic supplementary material The online version of this article (10.1007/s10565-020-09525-5) contains supplementary material, which is available to authorized users.

Retinoic acid–related orphan receptor C (RORC) is a member of the nuclear orphan receptor family and performs critical regulatory functions in cell proliferation, metastasis, and chemoresistance in various types of malignant tumors. Here we showed that expression of RORC is lost in tumor tissues of bladder cancer patients. Enhanced expression of RORC suppressed cell proliferation and glucose metabolism and increased cisplatin-induced apoptosis in vitro and in vivo. RORC bound the promoter region of programmed death ligand-1 (PD-L1) and negatively regulated PD-L1 expression. PD-L1 directly interacted with integrin β6 (ITGB6) and activated the ITGB6/FAK signaling pathway. RORC prevented the nuclear translocation of STAT3 via suppression of the PD-L1/ITGB6 signaling pathway, which further inhibited bladder cell proliferation and glucose metabolism and increased cisplatin-induced apoptosis. These findings reveal that RORC regulates bladder cancer cell proliferation, glucose metabolism, and chemoresistance by participating in the PD-L1/ITGB6/STAT3 signaling axis. Moreover, this new understanding of PD-L1 signaling may guide the selection of therapeutic targets to prevent tumor recurrence. Significance: These findings suggest that RORC-mediated regulation of a PD-L1/ITGB6/FAK/STAT3 signaling axis in bladder cancer provides several potential therapeutic targets to prevent tumor progression.

Barasertib is a highly selective Aurora kinase B (AURKB) inhibitor and has been widely applied in a variety of cancer cells to investigate the regulatory function of AURKB. However, the effect of barasertib on glucose metabolism in gastric cancer (GC) remains illustrated. Here, barasertib was identified to effectively reduce glucose uptake and lactate production in GC cells in a dose-dependent and time-dependent manner. The expression levels of GLUT1, LDHA and HK2 were decreased by barasertib treatment of GC cells. Furthermore, we found that barasertib induced the expression of ribosomal protein S7 (RPS7), as a tumor suppressor, to regulate glucose metabolism. Silencing of RPS7 rescued the effects of barasertib on glucose metabolism in GC cells. Overexpression of RPS7 suppressed the promoter activity of C-Myc, which has been identified as an important regulator of glucose metabolism in cancer cells. The clinical data showed that the expression level of AURKB in GC patients' sera and tissues were positively correlated with those of C-Myc, GLUT1 and LDHA, but negatively with that of RPS7. Therefore, these findings provide new evidence that barasertib regulates GC cell glucose metabolism by inducing the RPS7/C-Myc signal pathway, and have important implications for the development of therapeutic approaches using AURKB as a target protein to prevent tumor recurrence.

The paradigm of Floquet engineering of topological states of matter can be generalized into the time-quasiperiodic scenario, where a lower dimensional time-dependent system maps into a higher dimensional one by combining the physical dimensions with additional synthetic dimensions generated by multiple incommensurate driving frequencies. Different than most previous works in which gapped topological phases were considered, we propose an experimentally realizable, one dimensional chain driven by two frequencies, which maps into a gapless Weyl semimetal in synthetic dimension. Based on analytical reasoning and numerical simulations, we found the nonadiabatic quantum dynamics of this system exhibit energy pumping behaviors characterized by universal functions. We also numerically found such behaviors are robust against a considerable amount of spatial disorder., Comment: 11 pages, 7 figures

Continuing a work of Ph.~Monnier, we determine the Gerstenhaber algebra structure over the Poisson cohomology groups for a large class of Poisson structures with isolated singularities over the plane. It reveals that there exists a GAGA type phenomenon. We give an explicit description via generators and relations for the case of simple singularities.

BACKGROUND: Cancer-associated fibroblasts (CAFs) are a vital constituent of the tumor microenvironment (TME) and have several activities, but the effect of CAF heterogeneity on the molecular features and clinical outcomes of pancreatic ductal adenocarcinoma (PDAC) remains unknown. METHODS: An algorithm “scFrac” based on single-cell sequencing data from the Gene Expression Omnibus was introduced to emulate the enrichment of CAF subtypes in a TCGA-PDAC cohort and their prognostic influence, and confirmed by an external validation group (66 patients with PDAC) with multiplex immunohistochemistry staining. A comprehensive analysis including metabolic profile and transcription factor regulon activity was carried out among CAF subtypes. RESULTS: Three distinct CAF populations were confirmed: myofibroblast (myCAF), inflammatory CAF (iCAF), and antigen-presenting CAF (apCAF). These subtypes expressed distinct metabolic profiles and transcriptional regulon activity. KEGG pathway annotation demonstrated that complement and coagulation cascades, as well as cytokine-cytokine receptor interaction were dominant in iCAFs, and pathways related to focal adhesion, and ECM-receptor interaction showed dominance in myCAFs, while antigen processing and presentation were the top enriched pathways in apCAFs. iCAFs trended to glycolysis with CREB3L1, EGR2 and SOX4 activation, whereas myCAFs depend on the tricarboxylic acid cycle and its derivatives with NRF2, CEBPD and YBX1 activation. iCAF is a protective factor associated with an inflammatory phenotype, but myCAF is an important factor in the poor prognosis of PDAC. CONCLUSIONS: We identified distinct molecular characteristics of 3 CAF subtypes in PDAC and plotted their metabolism profile. We introduced a novel algorism, scFrac, for exploring how CAF subgroups dysregulate cancer biology, and also shed a new therapeutic light on targeting the CAF subtype in TME.

The current study aims to investigate whether backers’ electronic word-of-mouth (eWOM) is a valuable input when it comes to generating collective intelligence for projects filtering in crowdfunding. Based on theories of collective intelligence and WOM, we developed a research model and conducted an empirical study using a cross-section dataset with 845 crowdfunding projects and a panel dataset of the funding dynamics of those projects. The results indicated that backers’ negative WOM rather than positive WOM can effectively predict project implementation performance. Besides, for entrepreneurs with a high reputation, negative WOM has stronger predictive power for the complaints of product quality. We also found that projects with more accumulated negative WOM tend to attract fewer subsequent backers. Compared with positive WOM, negative WOM has a stronger effect on subsequent investments in a crowdfunding project. Finally, positive WOM can reduce the diffusion of responsibility effect in crowdfunding, that is, a backer is less likely to take responsibility for investing in a project when others have already backed it. Based on these findings, we conclude that backers’ WOM, especially the negative WOM, contributes to projects filtering in crowdfunding.

With more encrypted network traffic gets involved in the Internet, how to effectively classify network traffic has become a more and more important task in the field. Accurate classification of the network traffic is the footstone of basic network services, say QoE, bandwidth allocation, and Intrusion Detection System (IDS). Previous classification methods have many shortcomings since they cannot deal with the encrypted network traffic but require human experts to select tons of features to attain a relatively decent accuracy. Therefore, in this paper, we present a Deep Learning based end-to-end network traffic classification framework, termed TEST, to avoid the aforementioned problems. CNN and LSTM are combined and implemented to help the network intrusion detection systems automatically extract features from both special and time-related features of the raw traffic. The structure of our framework has two layers, which made it possible to attain a remarkable accuracy on encrypted traffic classification tasks. Compared to the LeNet model with the accuracy of 80.27% and the LSTM model with the accuracy of 81.96%, terimental results demonstrate that our model can outperform previous methods with a state-of-the-art accuracy of 99.98%.

Radical surgical resection represents the only hope of cure for pancreatic neuroendocrine tumor (PanNET). Adjuvant therapy is rarely used because there is no evidence to distinguish patients with high recurrence risk. Here we investigated the recurrence feature of resected PanNET and established a novel risk stratification to predict its recurrence. We analyzed 505 PanNET patients who underwent R0 resection at our institute from January 2004 through May 2015. The median follow-up was 71months (range: 12months-143months), 129 patients (25.5%) experienced recurrence with median disease-free survival (mDFS) of 19months. Restricted cubic spline (RCS) functions revealed a positive, linear relationship between Ki-67 index and recurrence. Multivariate analysis showed T stage, N stage, insulinoma and Ki-67 index were independent predictors of recurrence (P

Apatinib is a tyrosine kinase inhibitor that targets vascular endothelial growth factor receptor-2 (VEGFR2), and has shown encouraging therapeutic effects in various malignant tumors. As yet, however, the role of apatinib in ovarian cancer has remained unknown. Here, we sought to elucidate the role of apatinib in the in vitro and in vivo viability and proliferation of ovarian cancer cells, as well as in glucose metabolism in these cells. The effects of apatinib on ovarian cancer cell viability and proliferation were assessed using Cell Counting Kit-8 (CCK-8) and colony formation assays, respectively. The expression of VEGFR2/AKT1/SOX5/GLUT4 pathway proteins was assessed using Western blotting, and glucose uptake and lactate production assays were used to detect glycolysis in ovarian cancer cells. SOX5 was exogenously over-expressed and silenced in ovarian cancer cells using expression vector and shRNA-based methods, respectively. RNA expression analyses were performed using RNA-seq and gene-chip-based methods. GLUT4 promoter activity was assessed using a dual-luciferase reporter assay. The expression of p-VEGFR2 (Tyr1175), p-AKT1 (Ser473), p-GSK3β (Ser9), SOX5 and GLUT4 in xenograft tissues was assessed using immunohistochemistry (IHC). We found that apatinib inhibited the in vitro and in vivo viability and proliferation in Hey and OVCA433 ovarian cancer cells in a dose-dependent and time-dependent manner. We also found that apatinib effectively suppressed glucose uptake and lactate production by blocking the expression of GLUT4 in these cells. In addition, we found that SOX5 predominantly rescued the inhibitory effect of apatinib on GLUT4 expression by activating its promoter. Finally, we found that apatinib regulated the expression of SOX5 by suppressing the VEGFR2/AKT1/GSK3β signaling pathway. From our results, we conclude that apatinib suppresses the in vitro and in vivo viability and proliferation of ovarian cancer cells, as well as glycolysis by inhibiting the VEGFR2/AKT1/GSK3β/SOX5/GLUT4 signaling pathway. Apatinib may serve as a promising drug for the treatment of ovarian cancer.

Many natural language questions are inherently subjective. They can not be answered properly if we do not know the personal preferences of the answerer. For example, "Do you like cats?" There is no "the only correct answer" to this question. To answer it, the model has to be able to capture the persona of the answerers. However, the users usually do not answer different questions with equal chance. Instead, while some are answered with a high frequency, others are hardly answered by anyone. To deal with this imbalanced sparsity in data, we first introduce a Siamese Network to capture the preferences patterns of the users. Then the model is ensembled with an additional dense layer to predict the answers of the users. Applying to an online dating dataset, our approach achieves a high accuracy of 78.7%.