Search

The thesis of this dissertation proposes a novel filter algorithm to improve tracking and catalog maintenance of uncooperative satellites and other Resident Space Objects (RSOs) in Geosynchronous Equatorial Orbit (GEO). Tracking can be supported by space-based tracking from observer satellites (OBSs). Practical limitations can lead to long time gaps between measurement updates when tracking RSOs from an OBS, which may induce a loss of fidelity or divergence of the estimation algorithm. The Extended Kalman filter (EKF) is commonly used for tracking RSOs but it diverges as a consequence of nonlinearity in the dynamics and nonlinearity in the optical measurements from OBSs. Both nonlinear- ities cause the underlying probability density (PDF) of the state vector to deviate from a Gaussian distribution, leading to divergence after measurement update. The Unscented Kalman filter (UKF) and the Gaussian Mixture Model filter (GMM) were proposed to solve the divergence problem in the EKF. A hybrid algorithm, the Hybrid Kalman-particle filter (HKF), was developed and likewise assessed to improve on the EKF methodology by com- bining with particle filtering techniques. Lastly, this work presents a novel filter algorithm, the Extended Step-Back Kalman filter (ESBKF), in which the measurement update is ap- plied at a time in the past when the distribution of the RSO in state-space is approximately Gaussian. The filter statistics are then propagated forward to the present, and the nonlinear effects of the dynamics are dramatically reduced, thereby avoiding divergence longer.

Colorectal cancer (CRC) is the third most common cancer in the world. The accessibility of the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus data allows the prognostic evaluation of CRC. Fibroblasts play a key role in the development and progression of tumors while fibroblast-related risk signature in CRC patients has rarely been mentioned. In this study, TCGA data was classified into high-fibroblast and low-fibroblast groups according to the median of fibroblast content. Among 3845 differentially expressed genes between two groups, 14 prognostic genes commonly expressed in GSE39582 and TCGA were identified by LASSO-COX analysis. Then we established a fibroblast-related risk signature in TCGA training group and validated in the GSE39582 testing group. The risk score was significantly associated with the overall survival (OS), and the poor prognosis of patients in high-risk group might relate to the immune cell infiltration in the tumor microenvironment, epithelial-mesenchymal transition, and extracellular matrix related processes. Overall, we proved that the fibroblast-related signature could predict the prognosis of patients which might shed light on the treatment of CRC.

Background: Multiple myeloma (MM) is one of the most common cancers of the blood system. N6-methyladenosine (m6A) plays an important role in cancer progression. We aimed to investigate the prognostic relevance of the m6A score in multiple myeloma through a series of bioinformatics analyses. Methods: The microarray dataset GSE4581 and GSE57317 used in this study were downloaded from the Gene Expression Omnibus (GEO) database. The m6A score was calculated using the GSVA package. The Random forests, univariate Cox regression analysis and Lasso analyses were performed for the differentially expressed genes (DEGs). Kaplan–Meier analysis and an ROC curve were used to diagnose the effectiveness of the model. Results: The GSVA R software package was used to predict the function. A total of 21 m6A genes were obtained, and 286 DEGs were identified between high and low m6A score groups. The risk model was constructed and composed of PRX, LBR, RB1, FBXL19-AS1, ARSK, MFAP3L, SLC44A3, UNC119 and SHCBP1. Functional analysis of risk score showed that with the increase in the risk score, Activated CD4 T cells, Memory B cells and Type 2 T helper cells were highly infiltrated. Conclusions: Immune checkpoints such as HMGB1, TGFB1, CXCL9 and HAVCR2 were significantly positively correlated with the risk score. We believe that the m6A score has a certain prognostic value in multiple myeloma.

Background: Osteosarcoma (OS) is a common disease in the world, and its pathogenesis is still unclear. This study aims to identify the key genes that promote the proliferation, invasion, and metastasis of osteosarcoma cells. Method: GSE124768 and GSE126209 were downloaded from the Gene Expression Omnibus (GEO) database. The gene ontology and enrichment pathway were analyzed by FunRich software. qPCR and Western blot were used to detect the gene expression. After gene knockdown, Transwell and wound healing assays were conducted on osteosarcoma cells to detect whether the genes were defined before enhancing the invasion of osteosarcoma. Results: Totally, 341 mRNAs were found to be regulated differentially in osteosarcoma cells compared to osteoblasts. In addition, the expression level of Serglycin (SRGN) in osteosarcoma cells was higher than that in human osteoblasts. The invasion and proliferation ability of osteosarcoma cells with upregulated Serglycin was significantly increased, and on the contrary, decreased after Serglycin knockdown. Moreover, we preliminarily found that Serglycin may associate with the JAK/STAT signaling pathway. Conclusions: By using microarray and bioinformatics analyses, differently expressed mRNAs were identified and a complete gene network was constructed. To our knowledge, we describe for the first time Serglycin as a potential biomarker.

The aim of our study was to perform a comprehensive analysis of the gene expression, copy number variation (CNV) and mutation of key mitophagy genes in the progression and prognosis of lung adenocarcinoma (LUAD). We obtained the data from The Cancer Genome Atlas (TCGA). Clustering analysis was performed to stratify the mitophagy related groups. The least absolute shrinkage and selection operator (LASSO) based cox model was used to select hub survival genes. An independent validation cohort was retrieved from Gene Expression Omnibus database. We found 24 out of 27 mitophagy genes were aberrantly expressed between tumor and normal samples. CNV gains were associated with higher expression of mitophagy genes in 23 of 27 mitophagy genes. The clustering analysis identified high and low risk mitophagy groups with distinct survival differences. The high risk mitophagy groups had higher tumor mutation burden, stemness phenotype, total CNVs and lower CD4+ T cells infiltration. Drugs targeted to high risk mitophagy groups were identified including the PI3K/AKT/mTOR inhibitor, HDAC inhibitor and chemotherapy agents such as cisplatin and gemcitabine. In addition, the differentially expressed genes (DEGs) were identified between mitophagy groups. Further univariate Cox analysis of each DEG and subsequent LASSO-based Cox model revealed a mitophagy-related prognostic signature. The risk score model of this signature showed a strong ability to predict the overall survival of LUAD patients in training and validation datasets. In conclusion, the mitophagy genes played an important role in the progression and prognosis of LUAD, which might provide useful information for the treatment of LUAD.

Background: Diffuse large B-cell lymphoma (DLBCL) is the most prevalent type of lymphoma that is potentially curable by chemotherapy. Immunogenic cell death (ICD) is regarded as an essential process for the clearance of residual tumor cells. However, the impact of ICD on DLBCL remains unknown. Here, we tried to explore the prognostic role of ICD in DLBCL. Methods: A gene expression microarray of DLBCL was downloaded from the Gene Expression Omnibus (GEO). The genes involved in ICD were obtained via literature reviews. Then, based on univariate, multivariate, and LASSO Cox regression analysis, the ICD-related gene signature was identified. The effect of the ICD-related gene signature on DLBCL was explored. The chi-square test was used to compare complete response rate (CRR) and recurrence rate between high- and low-risk groups. Results: The signature based on 12 ICD-related genes could independently predict the overall survival of DLBCL. Furthermore, high risk was linked to lower CRR and higher recurrence rate. Then, a nomogram based on the ICD-related gene signature was established. The area under the curve of the prediction model reached 0.820 in the training set and 0.780 in the validation set. Conclusions: This study suggested that the ICD-related gene signature could be a novel prognostic indicator for DLCBL.

The fifth generation (5G) Wireless Communication systems development has brought out a paradigm shift using advanced technologies e.g., softwarization, virtualization, Massive MIMO, ultra-densification and introduction of new frequency bands. However, as the societal needs grow, and to satisfy UN's Sustainable Development Goals (SDGs), 6G and beyond systems are envisioned. Non- Terrestrial Networks including satellite systems, Unmanned Aerial Vehicles (UAVs) and High-Altitude Platforms (HAPs) provide the best solutions to connect the unconnected, unserved and underserved in remote and rural areas in particular. Over the past few decades, Geo Synchronous Orbits (GSO) satellite systems have been deployed to support broadband services, backhauling, Disaster Recovery and Continuity of Operations (DR-COOP) and emergency services. Recently, there is a considerable renewed interest in planning and developing non-GSO satellite systems. Within the next few years several thousands of Low Earth Orbit (LEO) satellites and mega LEO constellations will be ready to provide global Internet services. This report is the 2022 Edition of the INGR Satellite Working Group Report, subsequent to the previous two editions [1] [2]. The topics considered in this INGR Satellite WG 2022 Edition of the roadmap are the following taking 6G systems into account: applications and services, reference architectures (both backhaul and direct access), satellite loT, mm Wave use for satellite networks, machine learning and artificial intelligence, edge computing, QoS/QoE, security, network management and standardization. The work on the roadmap will continue towards the next edition of the roadmap addressing new challenges and potential solutions for future networks. © 2022 IEEE.

Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers worldwide. We aimed to identify potential genetic markers that could predict the prognosis of HNSCC. A total of 44 samples of GSE83519 from Gene Expression Omnibus (GEO) datasets and 546 samples of HNSCC from The Cancer Genome Atlas (TCGA) were adopted. The differently expressed genes (DEGs) of the samples were screened by GEO2R. We integrated the expression information of DEGs with clinical data from GES42743 using the weighted gene co-expression network analysis (WGCNA). A total of 17 hub genes were selected by the module membership (|MM| > 0.8), and the gene significance (|GS| > 0.3) was selected from the turquoise module. GOLM1 and FAM49B genes were chosen based on single-gene analysis results. Survival analysis showed that the higher expression of GOLM1 and FAM49B genes was correlated with a worse prognosis of HNSCC patients. Immunohistochemistry and multiplex immunofluorescence techniques verified that GOLM1 and FAM49B genes were highly expressed in HNSCC cells, and high expressions of GOLM1 were associated with the pathological grades of HNSCC. In conclusion, our study illustrated a new insight that GOLM1 and FAM49B genes might be used as potential biomarkers to determine the development of HNSCC, while GOLM1 and FAM49B have the possibility to be prognostic indicators for HNSCC.

An Attitude control system for a satellite in low earth orbit is designed in this project. As a reference, CARTOSAT-2 is selected to design the AOCS. CARTOSAT-2 is located in LEO so it suits the needs of the projects. It is mainly used for mapping of urban, rural areas and wetlands in India. To design a basic AOCS, a DC motor based model is considered. Transfer functions of DC motor and satellite dynamics model are calculated using Laplace transformation. Stability of the system is checked by plotting poles and zeroes of the systems. PID controller is used to improve the overall stability of the system by decreasing the errors in the output of the system. The systems are subjected to sine and step inputs and responses are plotted in the form of graphs. The plots are studied using SciLab as the tool to design the block diagram and the control system for the AOCS. Scilab along with FlightGear is used to visualize the response of the system.

Background Tacrolimus is a powerful immunosuppressant and has been widely used in organ transplantation. In order to further explore the role of tacrolimus in liver transplantation, we conducted network pharmacology analysis. Methods GSE100155 was obtained from the GEO database, and the DEGs of liver transplantation were analyzed. The 2D structure of tacrolimus was obtained from the National Library of Medicine, and the pharmacophore model of tacrolimus was predicted using the online tool pharmmapper. Then a network of tacrolimus and target genes was constructed through network pharmacology, and visualization and GO enrichment analysis was performed through Cytoscape. In addition, we also analyzed the correlation between key genes and immune infiltrating cells. The data of GSE84908 was used to verify the changes of key gene expression levels after tacrolimus treatment. Results The results of network pharmacological analysis showed that tacrolimus had 43 target genes, and the GO enrichment results showed many potential functions. Further analysis found that there were 5 key target genes in DEGs, and these 5 genes were significantly down-regulated in liver transplant patients. Another important finding was that 5 genes were significantly related to some immune infiltrating cells. The results of the GSE84908 data analysis showed that after tacrolimus treatment, the expression of DAAM1 was significantly increased (p = 0.015). Conclusion Tacrolimus may inhibit the human immune response by affecting the expression of DAAM1 in liver transplant patients.

Background Colorectal cancer (CRC) is the third most common cancer worldwide. The opening of the TCGA and GEO databases has promoted the progress of CRC prognostic assessment, while the aging-related risk signature has never been mentioned. Methods R software packages, GSEA software, Venn diagram, Metascape, STRING, Cytoscape, cBioPortal, TIMER and GeneMANIA website were used in this study. Results Aging-related gene sets, GO_AGING, GO_CELL_AGING and GO_CELLULAR_SENESCENCE, were activated significantly in CRC tissues. We constructed an aging-related risk signature using LASSO COX regression in training group TCGA and validated in testing group GSE39582. The risk score was significantly associated with the overall survival of CRC patients, whose stability was clarified by stratified survival analysis and accuracy was demonstrated using the ROC curve. The risk score was significantly increased in the advanced stage, T3-4, N1-3 and M1 and positively correlated with the richness of immune cell infiltration in the tumor microenvironment. We further investigated the molecular characteristics of 15 hub genes at the DNA and protein levels and performed GSEA between high- and low-risk groups. Conclusions The aging-related signature is a reliable prognostic analysis model and can predict the severity and immune cell infiltration of CRC patients.

Bladder cancer is one of the most common malignant tumors worldwide. Accordingly, its incidence and mortality are high. One of the characteristics of cancer is genomic instability. New studies suggest that long non-coding RNAs (lncRNAs) play an important role in maintaining genomic instability. This study aimed to identify a genomic instability-associated lncRNA signature to predict the outcome of patients with bladder cancer. We downloaded data for bladder cancer patients from The Cancer Genome Atlas database to obtain lncRNA expression profiles as well as somatic mutation profiles. Using the lncRNA computational framework, a genomic instability-related lncRNA signature (GIlncSig) was established and the prognostic value of this signature was assessed and validated. A five-lncRNA signature based on genomic instability (CFAP58-DT, MIR100HG, LINC02446, AC078880.3, and LINC01833) was obtained from 58 differentially expressed lncRNAs. Patients were divided into high-risk and low-risk groups, with the high-risk group having a substantially worse prognosis than the low-risk group. Univariate and multivariate Cox analyses indicated that GIlncSig may be an independent prognostic factor; this finding was subsequently validated. In addition, enrichment analysis indicated that GIlncSig is associated with genomic instability in bladder cancer. GIlncSig has a predictive value for the prognosis of bladder cancer patients and provides guidance for the clinical treatment of these patients.

Background: Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignancy in the respiratory tract and could reduce the quality of life seriously like dyspnea, dysphonia and dysphagia. Moreover, 5-year survival rate has decreased over the past 40 years. This study was designed to identify mRNAs that related to prognosis in LSCC to enable early detection and outcome improvement. Methods: Gene expression profiles from Gene Expression Omnibus (GEO) (GSE59102, GSE84957) and The Cancer Genome Atlas (TCGA) were analyzed to identify differentially expressed genes (DEGs) with the help of bioinformatics tools. Functional enrichment analyses including Gene Ontology (GO) and pathway analysis were carried out to investigate the role of those genes and underlying molecular mechanisms in LSCC. Cox's regression analyses (univariate, LASSO and multivariate in order) were utilized to identify DEGs related with patients' overall survival and a 4-mRNA-based prognostic risk score model was established. Univariate and multivariate Cox's regression analyses were then performed on LSCC data (90 patients left) to identify independent predictors of OS, including the signature and clinicopathologic variables. The prognostic value of the gene signature was further validated and the genes were analyzed by GEPIA to get pan-cancer expression profiles. Results: 444 differentially expressed mRNAs (250 up-regulated, 194 down-regulated) were identified based on the threshold of fold change > 2 and adjusted p value < 0.05. Univariate Cox's regression analysis showed that high risk score (HR: 3.056, 95% confidence interval [CI]: 0.135-0.649, p

Oral squamous cell carcinoma (OSCC) is a common human malignancy. However, its pathogenesis and prognostic information are poorly elucidated. In the present study, we aimed to probe the most significant differentially expressed genes (DEGs) and their prognostic performance in OSCC. Multiple microarray datasets from the Gene Expression Omnibus (GEO) database were aggregated to identify DEGs between OSCC tissue and control tissue. Least absolute shrinkage and selection operator (LASSO) Cox model was constructed to determine the prognostic performance of the aggregated DEGs based on The Cancer Genome Atlas (TCGA) OSCC cohort. Ten datasets with 341 OSCC samples and 283 control samples were included. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment revealed that the integrated DEGs were enriched in the IL-17 signaling pathway, viral protein interactions with cytokines and cytokine receptors, and amoebiasis, among others. Our LASSO Cox model was able to discriminate two groups with different overall survival in the training cohort and test cohort (p, Graphical abstract

Summary Objective Low back pain (LBP) is the predominant cause of disc degeneration in patients, which brings serious social problems and economic burdens. Increasing evidence has indicated that intervertebral disc degeneration (IDD) is one of the most common causes triggering LBP. Accumulating evidence has shown that circRNAs are involved in the pathological process of IDD. Nevertheless, the circRNA-mediated IDD pathogenesis still remains unknown. This study explored the potential mechanism and functions of circ-FAM169A in NPCs. Methods Bioinformatics analysis was conducted to identify key circRNA, miRNA and mRNA and predict their potential role in IDD. Dual-luciferase reporter assay, western blot, qRT-PCR, and fluorescence in situ hybridisation (FISH) were used to demonstrate the interaction among circ-FAM169A, miR-583 and Sox9 in NPCs. Results Herein, we identified circ-FAM169A, which was dramatically up-regulated in degenerative nucleus pulposus (NP) tissues and negatively correlated with expression levels of miR-583. We constructed a circ-FAM169A-miR-583-mRNAs co-expression network and predicted circ-FAM169A-miR-583 pathway predominantly involved in extracellular matrix metabolism and cell apoptosis etc. FISH experiments confirmed circ-FAM169A and miR-583 co-existence in the cytoplasm of NPCs. Luciferase reporter assay illustrated that circ-FAM169A was directly bound to miR-583 and Sox9 was the directly target gene of miR-583. Additionally, miR-583 negatively regulated Sox9 mRNA and protein levels in NPCs. Conclusion Findings of this study indicated that circ-FAM169A-miR-583 pathway may play a significant role in the regulation of IDD, which will provide novel diagnostic biomarkers and develop effective treatment strategy of IDD diseases. The translational potential of this article This study suggested that circ-FAM169A-miR-583 pathway may regulate NPCs apoptosis and extracellular matrix synthesis and catabolism by targeting Sox9. It provides a novel therapeutic target and strategy for IVDD diseases.

Space laser communication optical antennas have very high requirements for the stability and uniformity of the temperature field. The GEO satellite-borne laser communication is affected by the violent alternating solar heat flow, which causes the thermal disturbance of the in-orbit temperature field of the extra-satellite optical antenna to become unstable. Reduce optical communication time. For this reason, the paper proposes a ?sun window? as a solar spectral filter device to shield solar radiation, combined with the thermal design of the optical antenna system, based on thermal simulation analysis to study the effectiveness of the solar window to suppress the thermal disturbance of the optical antenna temperature field. The research results show that the thermal control optimization design of the optical antenna system based on the "sun window" has a significant effect in suppressing the thermal disturbance of the optical antenna temperature field: the stability of the temperature field of the primary mirror is increased by 2.2 times, the stability of the temperature field of the secondary mirror is increased by 10.6 times. The uniformity of the temperature field of the secondary mirror is increased by about ten times, and the time that meets the requirements of the stability and uniformity of the optical communication antenna temperature field can be up to 24 hours per day, which is more than three times that of the solution without the "sun window".

Aberrant expression of DNA repair genes (DRGs) can be related to tumor progression and clinical outcomes in colon cancer. Here, we aimed to establish a DRGs signature to identify the vital prognostic DRGs in colon cancer. Firstly, gene set enrichment analysis (GSEA) was performed to demonstrate the association between abnormal expression level of DRGs and tumorigenesis. Then, a total of 476 DRGs were obtained for detecting candidate biomarkers in randomly selected 295 cases from The Cancer Genome Atlas (TCGA) colon cancer cohort. Eleven genes were screened by LASSO Cox regression analyses to develop the prognostic model. Then, the prognostic model and the expression levels of the eleven genes were validated using the internal validation dataset (the rest 125 cases in TCGA cohort) and an external validation dataset (obtained from Gene Expression Omnibus dataset). Further analysis revealed the independent prognostic capacity of the prognostic model in relation to other clinical characteristics. The receiver operating characteristic (ROC) curve analysis confirmed the good performance of the prognostic model. Furthermore, we provided a nomogram for interpreting the clinical application of the 11-DRG signature. In conclusion, we propose a newly developed 11-DRG signature as a practical prognostic predictor for patients with colon cancer, which can facilitate the individualized counselling and treatment.

Endometrial carcinoma(EC) is the most common cancer of female reproductive system, thus requiring for new effective biomarkers which could predict the onset of EC and poor prognosis. Our study integrated two GEO datasets(i.e.GSE63678, GSE17025) and TCGA(The Cancer Genome Atlas ) UCEC data to screen out 344 common differentially expressed genes(DEGs), which were further analyzed by GO(gene ontology) functions and KEGG(Kyoto Encyclopedia of Gene and Genome) pathways. KEGG analysis results showed these DEGs were mainly enriched in cell cycle, oocyte meiosis, cellular senescence, carbon metabolism and p53 signaling pathway. Top 20 hub genes with higher degree were selected from PPI(protein-protein interaction) network and 15 of them were associated with the prognosis of EC, that is, CCNB2, CDC20, BUB1B, UBE2C, AURKB, FOXM1, NCAPG, RRM2, TPX2, DLGAP5, CDCA8, CDC45, MKI67, BUB1, KIF2C. UBE2C(Ubiquitin Conjugating Enzyme E2 C) was chosen for further validation in TCGA cohort on mRNA level and in our patient samples on protein level by immunohistochemistry. UBE2C was significantly highly expressed in endometrial carcinoma, and its expression level was associated with advanced FIGO staging and poor prognosis. Cox risk model demonstrated high UBE2C expression was an independent risk factor. Somatic mutations, elevated copy number, DNA hypomethylation all contributed to its overexpression. Therefore, by combination of bioinformatics and experiment, our study provided a unique insight into the pathogenesis and molecular mechanisms underlying EC and discovered new biomarkers for early diagnosis and prognostic prediction. UBE2C could serve as a potential marker to predict poor prognosis and as a therapeutic target.

Gastric cancer is a heterogeneous tumor that underlying molecular mechanisms are largely unclear. This study aimed to elucidate the expression level of HGF-c-MET in gastric cancer patients and to investigate the prognostic and diagnostic value of HGF-c-MET. In silico analysis of the TCGA and GEO database found that HGF and c-MET mRNA expression are significantly higher in gastric cancer tissues than those in peritumor tissues. Both higher mRNA expression of HGF and c-MET were associated with a poorer prognosis. c-MET expression was modulated by methylation in the promoter regions. HGF was positively correlated with CD8+ T cell, CD4+ T cell, macrophage, neutrophil and dendritic cell. Furthermore, functional enrichment analysis and protein-protein interaction networks further shown that HGF-c-MET and related proteins mainly participated in growth factor receptor binding, protein tyrosine kinase activity and signaling receptor binding. Finally, outcome of GSEA analysis showed 13 shared KEGG pathways enriched in high expressed group of HGF and c-MET.

Background: Focal segmental glomerulosclerosis (FSGS) is a type of nephrotic syndrome leading to end-stage renal disease, and this study aimed to explore the hub genes and pathways associated with FSGS to identify potential diagnostic and therapeutic targets.Methods: We downloaded the microarray datasets GSE121233 and GSE129973 from the Gene Expression Omnibus (GEO) database. The datasets comprise 25 FSGS samples and 25 normal samples. The differential expression genes (DEGs) were identified using the R package “limma”. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the database for Annotation, Visualization and Integrated Discovery (DAVID) to identify the pathways and functional annotation of the DEGs. The protein–protein interaction (PPI) was constructed based on the Search Tool for the Retrieval of Interacting Genes (STRING) database and visualized using Cytoscape software. The hub genes of the DEGs were then evaluated using the cytoHubba plugin of Cytoscape. The expression of the hub genes was validated by quantitative real-time polymerase chain reaction (qRT-PCR) using the FSGS rat model, and receiver operating characteristic (ROC) curve analysis was performed to validate the accuracy of these hub genes.Results: A total of 45 DEGs including 18 upregulated and 27 downregulated DEGs, were identified in the two GSE datasets (GSE121233 and GSE129973). Among them, five hub genes with a high degree of connectivity were selected. From the PPI network, of the top five hub genes, FN1 was upregulated, while ALB, EGF, TTR, and KNG1 were downregulated. The qRT-PCR analysis of FSGS rats confirmed that the expression of FN1 was upregulated and that of EGF and TTR was downregulated. The ROC analysis indicated that FN1, EGF, and TTR showed considerable diagnostic efficiency for FSGS.Conclusion: Three novel FSGS-specific genes were identified through bioinformatic analysis combined with experimental validation, which may promote our understanding of the molecular underpinning of FSGS and provide potential therapeutic targets for the clinical management.

La finalidad de los sistemas de comunicaciones por satélites es proporcionar una cobertura inalámbrica que permita completar y ampliar las redes de comunicaciones terrestres para alcanzar cobertura global. Uno de los objetivos a alcanzar en los próximos años es la integración de los satélites con redes 5G para proporcionar acceso inalámbrico con velocidades de datos mejoradas. Una de las técnicas de capa física utilizadas por 5G es el Multiple-Input Multiple-Output (MIMO) masivo. Aunque esta tecnología es utilizada ampliamente en los sistemas de comunicaciones terrestres, su carácter masivo hace aún compleja su integración en sistemas de comunicaciones por satélite. En este trabajo se propone estudiar las oportunidades de análisis del segmento espacio y del segmento terrestre. En el segmento espacio se utilizará una herramienta de diseño como General Mission Analysis Tool (GMAT) para simular las órbitas de las constelaciones de satélites LEO. En el segmento terrestre se plantea analizar las oportunidades de integración de MIMO masivo en satélites y proponer una solución viable desde el punto de vista de sistemas. Las técnicas de MIMO masivo que se van analizar consisten en los algoritmos adaptativos y las comunicaciones no coherentes. Los algoritmos adaptativos en beamforming realizan apuntamientos a las direcciones deseada eliminando las interferencias y mejorando la comunicación, ayudando al desarrollo de las tecnologías de quinta generación, la cuales utilizarán el MIMO masivo. Por otro lado, la comunicación no coherente se propone como una alternativa a los inconvenientes que tiene el MIMO masivo en los sistemas coherente. Para el estudio de ambas técnicas se utilizará la herramienta MATLAB. La finalitat dels sistemes de comunicacions per satèl·lits és proporcionar una cobertura sense fil que permeti completar i ampliar les xarxes de comunicacions terrestres per a aconseguir cobertura global. Un dels objectius a aconseguir en els pròxims anys és la integració dels satèl·lits amb xarxes 5G per a proporcionar accés sense fil amb velocitats de dades millorades. Una de les tècniques de capa física utilitzades per 5G és el Multiple-Input Multiple-Output (MANYAGA) massiu. Encara que aquesta tecnologia és utilitzada àmpliament en els sistemes de comunicacions terrestres, el seu caràcter massiu fa encara complexa la seva integració en sistemes de comunicacions per satèl·lit. En aquest treball es proposa estudiar les oportunitats d'anàlisis del segment espai i del segment terrestre. En el segment espai s'utilitzarà una eina de disseny com a General Mission Analysis Tool (GMAT) per a simular les òrbites de les constel·lacions de satèl·lits LEO. En el segment terrestre es planteja analitzar les oportunitats d'integració de MANYAGA massiva en satèl·lits i proposar una solució viable des del punt de vista de sistemes. Les tècniques de MANYAGA massiva que es van analitzar consisteixen en els algorismes adaptatius i les comunicacions no coherents. Els algorismes adaptatius en beamforming realitzen apuntamientos a les direccions desitjada eliminant les interferències i millorant la comunicació, ajudant al desenvolupament de les tecnologies de cinquena generació, la quals utilitzaran la MANYAGA massiva. D'altra banda, la comunicació no coherent es proposa com una alternativa als inconvenients que té la MANYAGA massiva en els sistemes coherent. Per a l'estudi de totes dues tècniques s'utilitzarà l'eina MATLAB. The purpose of satellite communications systems is to provide wireless coverage to complement and extend terrestrial communications networks to achieve global coverage. One of the goals to be achieved in the coming years is the integration of satellites with 5G networks to provide wireless access with improved data rates. One of the physical layer techniques used by 5G is Massive Multiple-Input Multiple-Output (MIMO). Although this technology is widely used in terrestrial communications systems, its massive nature still makes its integration in satellite communications systems complex. In this work we propose to study the opportunities for analysis of the space segment and the terrestrial segment. In the space segment, a design tool such as the General Mission Analysis Tool (GMAT) will be used to simulate the orbits of LEO satellite constellations. In the terrestrial segment, we plan to analyze the opportunities for integration of massive MIMO in satellites and propose a viable solution from a systems point of view. The massive MIMO techniques to be analyzed are adaptive algorithms and non-coherent communications. Adaptive algorithms in beamforming perform pointing to the desired directions eliminating interference and improving communication, helping the development of fifth generation technologies, which will use massive MIMO. On the other hand, non-coherent communication is proposed as an alternative to the drawbacks of massive MIMO in coherent systems. MATLAB will be used to study both techniques.

Background Peripheral blood mononuclear cells (PBMCs) play an important role in the pathogenesis of pulmonary arterial hypertension (PAH). However, the specific roles of PBMCs in the development and progression of idiopathic PAH (IPAH) have not been fully understood. Methods Here, differentially expressed genes (DEGs) of PBMCs or lung tissues between IPAH patients and healthy controls were identified via bioinformatics analysis of Gene Expression Omnibus (GEO) datasets GSE33463 and GSE48149, respectively. Subsequently, extensive target prediction and network analysis were performed to assess protein–protein interaction (PPI) networks, Gene Ontology (GO) terms, and pathway enrichment for DEGs. Co‐expressed DEGs between PBMCs and lung tissues coupled with corresponding predicted miRNAs involved in PAH were also assessed. We identified 251 DEGs in PBMCs and 151 DEGs in lung tissue samples from IPAH. PDK4, RBPMS2, and PDE5A expression were altered in both PBMCs and lung tissues from IPAH patients compared to healthy control. Results CXCL8, JUN, TLR8, IL1B, and TLR7 could be implicated as the hub genes in PBMCs, whereas ENO1, STAT1, CXCL10, GPI, and IRF1 in lung tissues. Finally, co‐expressed DEGs of PDK4, RBPMS2, and PDE5A coupled with corresponding predicted miRNAs, especially miR‐103a‐3p, miR‐185‐5p, and miR‐515‐5p, are significantly associated with IPAH. Conclusion Our findings collectively suggest that the expression levels of PDK4, RBPMS2, and PDE5A in PBMCs are associated with the expression of these genes in lung tissues. Thus, these molecules may serve as potential circulating biomarkers and/or possible therapeutic targets for IPAH., It is reported that PBMCs play a vital role in the pathogenesis of pulmonary arterial hypertension. An analysis of gene expression in lung homogenates may provide insight into genes involved in vascular remodeling in IPAH patients. We thus wrote this letter to discuss the necessity to identify the potential biomarkers and possible therapeutic targets for IPAH by a bioinformatics analysis of the transcriptome in PBMCs and lung tissues of IPAH.

Background and Objectives: A subject with diabetes and obesity is a class of the metabolic disorder. The current investigation aimed to elucidate the potential biomarker and prognostic targets in subjects with diabetes and obesity. Materials and Methods: The next-generation sequencing (NGS) data of GSE132831 was downloaded from Gene Expression Omnibus (GEO) database. Functional enrichment analysis of DEGs was conducted with ToppGene. The protein–protein interactions network, module analysis, target gene–miRNA regulatory network and target gene–TF regulatory network were constructed and analyzed. Furthermore, hub genes were validated by receiver operating characteristic (ROC) analysis. A total of 872 DEGs, including 439 up-regulated genes and 433 down-regulated genes were observed. Results: Second, functional enrichment analysis showed that these DEGs are mainly involved in the axon guidance, neutrophil degranulation, plasma membrane bounded cell projection organization and cell activation. The top ten hub genes (MYH9, FLNA, DCTN1, CLTC, ERBB2, TCF4, VIM, LRRK2, IFI16 and CAV1) could be utilized as potential diagnostic indicators for subjects with diabetes and obesity. The hub genes were validated in subjects with diabetes and obesity. Conclusion: This investigation found effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting new and key therapeutic targets for subjects with diabetes and obesity.

Objectives The high frequency of chemotherapy resistance is ultimately responsible for clinical relapse in acute lymphoblastic leukemia (ALL). Nevertheless, the molecular mechanism relevant to glucocorticoid (GC) resistance remains ambiguous. Methods Quantitative real-time polymerase chain reaction and Western blot were performed to detect the expressions of paraoxonase 2 (PON2), Bcl-2 and Bax. shRNA was used to knockdown PON2 expression in SUP-B15 and REH cell. CCK-8 and flow cytometry assay were conducted to monitor the changes of proliferation and apoptosis in ALL cells. The growth of ALL REH cells in vivo was determined using transplanted tumor model. Results This study was designed to identify GC resistance-associated genes by means of the transcriptome chip from the public Gene Expression Omnibus database, and preliminarily investigation of dexamethasone (DEX)-resistance mechanism in ALL. We disclosed that PON2 expression was elevated in ALL patients and especially higher in DEX-resistance ALL patients. Then, cell apoptosis assay suggested that silencing of PON2 dramatically promoted in DEX-resistant ALL cells apoptosis and the activity of Caspase 3 induced by DEX administration. In xenograft tumor model, PON2 knockdown significantly reduced DEX-resistant ALL cells growth in immunodeficient mice. Conclusions Collectively, inhibition of PON2 may represent a novel method to restore the sensitivity of treatment-resistant ALL to GC-induced cell death.

Bladder cancer (BC) is the most common malignant tumor of the urinary system and is associated with high morbidity and mortality; however, the molecular mechanism underlying its occurrence is not clear. In this study, the gene expression profile and related clinical information of GSE13507 were downloaded from the Gene Expression Omnibus (GEO) database. RNA sequencing (RNA-seq) expression data and related clinical information were retrieved from The Cancer Genome Atlas (TCGA) database. Overlapping genes were identified by differential gene expression analysis and weighted gene co-expression network analysis (WGCNA). Then, we carried out functional enrichment analysis to understand the potential biological functions of these co-expressed genes. Finally, we performed a protein–protein interaction (PPI) analysis combined with survival analysis. Using the CytoHubba plug-in of Cytoscape, TROAP, CENPF, PRC1, AURKB, CCNB2, CDC20, TTK, CEP55, ASPM, and CDCA8 were identified as candidate central genes. According to the survival analysis, the high expression of TTK was related to the poor overall survival (OS) of patients with BC. TTK may also affect the bladder tumor microenvironment (TME) by affecting the number of immune cells. The expression level of TTK was verified by immunohistochemistry (IHC) and real-time quantitative polymerase chain reaction (RT-qPCR), and the tumor-promoting effect of TTK in BC cells was confirmed in vitro. Our results also identified the MSC-AS1/hsa-miR-664b-3p/TTK regulatory axis, which may also play an important role in the progression of BC, but further research is needed to verify this result. In summary, our results provide a new idea for accurate early diagnosis, clinical treatment, and prognosis of BC

IntroductionAlzheimer’s disease (AD) is the most prevalent cause of dementia, and emerging evidence suggests that ferroptosis is involved in the pathological process of AD.Materials and MethodsThree microarray datasets (GSE122063, GSE37263, and GSE140829) about AD were collected from the GEO database. AD-related module genes were identified through a weighted gene co-expression network analysis (WGCNA). The ferroptosis-related genes were extracted from FerrDb. The apoptosis-related genes were downloaded from UniProt as a control to show the specificity of ferroptosis. The overlap was performed to obtain the module genes associated with ferroptosis and apoptosis. Then the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and the protein-protein interaction (PPI) were conducted. Cytoscape with CytoHubba was used to identify the hub genes, and the Logistic regression was performed to distinguish the AD patients from controls.Results53 ferroptosis-related module genes were obtained. The GO analysis revealed that response to oxidative stress and starvation, and multicellular organismal homeostasis were the most highly enriched terms. The KEGG analysis showed that these overlapped genes were enriched not only in renal cell carcinoma pathways and central carbon metabolism in cancer, but also in autophagy-related pathways and ferroptosis. Ferroptosis-related hub genes in AD (JUN, SLC2A1, TFRC, ALB, and NFE2L2) were finally identified, which could distinguish AD patients from controls (P < 0.05). The area under the ROC curve (AUC) was 0.643. Apoptosis-related hub genes in AD (STAT1, MCL1, and BCL2L11) were also identified and also could distinguish AD patients from controls (P < 0.05). The AUC was 0.608, which was less than the former AUC value, suggesting that ferroptosis was more special than apoptosis in AD.ConclusionWe identified five hub genes (JUN, SLC2A1, TFRC, ALB, and NFE2L2) that are closely associated with ferroptosis in AD and can differentiate AD patients from controls. Three hub genes of apoptosis-related genes in AD (STAT1, MCL1, and BCL2L11) were also identified as a control to show the specificity of ferroptosis. JUN, SLC2A1, TFRC, ALB, and NFE2L2 are thus potential ferroptosis-related biomarkers for disease diagnosis and therapeutic monitoring.

Background Bladder cancer (BC) is one of the most common malignancies and has a relatively poor outcome worldwide. In this study, we attempted to construct a novel metabolism-related gene (MRG) signature for predicting the survival probability of BC patients. Methods First, differentially expressed MRGs between BC and normal samples were identified and used to construct a protein-protein interaction (PPI) network and perform mutation analysis. Next, univariate Cox regression analysis was utilized to select prognostic genes, and multivariate Cox regression analysis was applied to establish an MRG signature for predicting the survival probability of BC patients. Moreover, Kaplan-Meier (KM) survival analysis and receiver operating characteristic (ROC) analysis were performed to evaluate the predictive capability of the MRG signature. Finally, a nomogram based on the MRG signature was established to better predict the survival of BC. Results In the present study, 27 differentially expressed MRGs were identified, most of which presented mutations in BC patients, and LRP1 showed the highest mutation rate. Next, an MRG signature, including MAOB, FASN and LRP1, was established by using univariate and multivariate Cox regression analysis. Furthermore, survival analysis indicated that BC patients in the high-risk group had a dramatically lower survival probability than those in the low-risk group. Finally, Cox regression analysis showed that the risk score was an independent prognostic factor, and a nomogram integrating age, pathological tumor stage and risk score was established and presented good predictive ability. Conclusion We successfully constructed a novel MRG signature to predict the prognosis of BC patients, which might contribute to the clinical treatment of BC.

This study aims to determine hub genes related to the incidence and prognosis of EGFR-mutant (MT) lung adenocarcinoma (LUAD) with weighted gene coexpression network analysis (WGCNA). From The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we used 253 EGFR-MT LUAD samples and 38 normal lung tissue samples. At the same time, GSE19188 was additionally included to verify the accuracy of the predicted gene. To discover differentially expressed genes (DEGs), the R package “limma” was used. The R packages “WGCNA” and “survival” were used to perform WGCNA and survival analyses, respectively. The functional analysis was carried out with the R package “clusterProfiler.” In total, 1450 EGFR-MT–specific DEGs were found, and 7 tumor-related modules were marked with WGCNA. We found 6 hub genes in DEGs that overlapped with the tumor-related modules, and the overexpression level of B3GNT3 was significantly associated with the worse OS (overall survival) of the EGFR-MT LUAD patients (p < 0.05). Functional analysis of the hub genes showed the metabolism and protein synthesis–related terms added value. In conclusion, we used WGCNA to identify hub genes in the development of EGFR-MT LUAD. The established prognostic factors could be used as clinical biomarkers. To confirm the mechanism of those genes in EGFR-MT LUAD, further molecular research is required.

To identify key biomarkers in gemcitabine (GEM)-resistant bladder cancer (BCa) and investigate their associations with tumor-infiltrating immune cells in a tumor immune microenvironment, we performed the present study on the basis of large-scale sequencing data. Expression profiles from the Gene Expression Omnibus GSE77883 dataset and The Cancer Genome Atlas BLCA dataset were analyzed. Both BCa development and GEM-resistance were identified to be immune-related through evaluating tumor-infiltrating immune cells. Eighty-two DEGs were obtained to be related to GEM-resistance. Functional enrichment analysis demonstrated they were related to regulation of immune cells proliferation. Protein–protein interaction network selected six key genes (CAV1, COL6A2, FABP4, FBLN1, PCOLCE, and CSPG4). Immunohistochemistry confirmed the down-regulation of the six key genes in BCa. Survival analyses revealed the six key genes were significantly associated with BCa overall survival. Correlation analyses revealed the six key genes had high infiltration of most immune cells. Gene set enrichment analysis further detected the key genes might regulate GEM-resistance through immune response and drug metabolism of cytochrome P450. Next, microRNA-gene regulatory network identified three key microRNAs (hsa-miR-124-3p, hsa-miR-26b-5p, and hsa-miR-192-5p) involved in GEM-resistant BCa. Connectivity Map analysis identified histone deacetylase inhibitors might circumvent GEM-resistance. In conclusion, CAV1, COL6A2, FABP4, FBLN1, PCOLCE, and CSPG4 were identified to be critical biomarkers through regulating the immune cell infiltration in an immune microenvironment of GEM-resistance and could act as promising treatment targets for GEM-resistant muscle-invasive BCa.

Background Circular RNAs (circRNAs) are a class of non-coding RNA that play critical roles in the development and pathogenesis of various cancers. The circRNA circGSK3B (hsa_circ_0003763) has been shown to enhance cell proliferation, migration, and invasion in hepatocellular carcinoma. However, the specific functions and underlying mechanistic involvement of circGSK3B in gastric cancer (GC) have not yet been explored. Our study aimed to investigate the effect of circGSK3B on the progression of GC and to identify any potential mechanisms underlying this process. Methods CircRNA datasets associated with GC were obtained from the PubMed, GEO, and ArrayExpress databases, and circRNAs were validated via RT-qPCR and Sanger sequencing. Biotin-labeled RNA pull-down, mass spectrometry, RNA immunoprecipitation, and in vitro binding assays were employed to determine proteins demonstrating interactions with circGSK3B. Gene expression regulation was assessed through RT-qPCR, chromatin immunoprecipitation, and western blot assays. Gain- and loss-of-function assays were used to analyze any effects of circGSK3B and its partner regulatory molecule (EZH2) on the proliferation, invasion, and migration abilities of GC cells both in vitro and in vivo. Results CircGSK3B was mainly identified in the nucleus. This circRNA was present at a reduced concentration in GC tissues and cell lines. Overexpression of circGSK3B was shown to inhibit the growth, invasion, and metastasis of GC cells both in vitro and in vivo. Mechanistically, circGSK3B directly interacted with EZH2, acting to suppress the binding of EZH2 and H3K27me3 to the RORA promoter, and leading to an elevation in RORA expression and ultimately the suppression of GC progression. Conclusions CircGSK3B acts as a tumor suppressor, reducing EZH2 trans-inhibition and GC progression. This demonstrates the potential use of this RNA as a therapeutic target for GC.

Sustainability in space is often discussed, but as a community we are only gradually learning what it actually means. To inform this understanding, a set of three parallel projects ran at Cranfield University (Oct 2020 to Mar 2021) to develop a scenario of sustainable use of the geostationary orbit region. The three projects were to develop mission designs for (a) a Scavenger spacecraft equipped with tools, actuators and sensors to perform rendezvous with selected satellites at their end of life, to harvest selected parts and components (i.e. solar panels, radiators, antenna reflectors), store and deliver them to the Recycler for refurbishment or recycling, (b) a Recycler space station located in GEO, capable of receiving parts and materials obtained by the Scavenger spacecraft and performing a range of inspection, recycling and repurposing operations on them, and (c) a candidate customer mission: a huge communications satellite based on the Airbus VASANT (VASt ANTenna) concept, with two antenna arrays, each 35 m square, sized to be able to communicate directly from GEO to mobile phone users at Earth's surface. Some of the features highlighted by these studies are (a) the technical challenges of reusing parts from old satellites: modularity and design-for-reuse seem to be key enablers, (b) the advanced robotics and autonomy implied by the on-orbit operations, (c) the challenge of long-term orbit control without excessive propellant consumption, and (d) although the technology is challenging, there are major non-technical challenges for the business case and for aspects such as the legal use of debris, liability for accidents, and compliance with any regulations. Sustainability is challenging, but nature leaves us no alternative.

Background Pyroptosis can not only inhibit the occurrence and development of tumors but also develop a microenvironment conducive to cancer growth. However, pyroptosis research in prostate cancer (PCa) has rarely been reported. Methods The expression profile and corresponding clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Patients were divided into different clusters using consensus clustering analysis, and differential genes were obtained. We developed and validated a prognostic biomarker for biochemical recurrence (BCR) of PCa using univariate Cox analysis, Lasso-Cox analysis, Kaplan–Meier (K–M) survival analysis, and time-dependent receiver operating characteristics (ROC) curves. Results The expression levels of most pyroptosis-related genes (PRGs) are different not only between normal and tumor tissues but also between different clusters. Cluster 2 patients have a better prognosis than cluster 1 patients, and there are significant differences in immune cell content and biological pathway between them. Based on the classification of different clusters, we constructed an eight genes signature that can independently predict the progression-free survival (PFS) rate of a patient, and this signature was validated using a GEO data set (GSE70769). Finally, we established a nomogram model with good accuracy. Conclusions In this study, PRGs were used as the starting point and based on the expression profile and clinical data, a prognostic signature with a high predictive value for biochemical recurrence (BCR) following radical prostatectomy (RP) was finally constructed, and the relationship between pyroptosis, immune microenvironment, and PCa was explored, providing important clues for future research on pyroptosis and immunity.

Researches have suggested that aerobic glycolysis can reflect the development and progression of most carcinomas. We aimed to investigate whether glycolysis-related genes (GRGs) are associated with overall survival in laryngeal squamous cell carcinoma (LSCC). Here, we identified differentially expressed GRGs in TCGA dataset and microarray sample of GSE27020 from GEO database. A set of two glycolytic gene signatures, including DDIT4 and PLOD2 was screened through Cox and Lasso regression. The risk score was calculated using the gene expression of the two GRGs. The high-risk group presented a poor prognosis through Kaplan–Meier method. The ROC curve indicated good prediction performance in survival based on the validation of four cohorts. Univariate and multivariate Cox regression analyses suggested that two-gene signature could be an independent risk factor in LSCC. A total of 17 LSCC patients were enrolled to clarify the genetic expression through using reverse transcription-polymerase chain reaction (RT-PCR). A visualized nomogram was then constructed to predict 1-, 3-, and 5-year overall survival. Taken together, two novel glycolytic gene signatures were discovered and validated, providing a potential therapeutic and overall survival (OS)-prediction biomarker for LSCC., GRAPHICAL ABSTRACT

Background: The aim of this paper was to identify an immunotherapy-sensitive subtype for estrogen receptor-positive breast cancer (ER+ BC) patients by exploring the relationship between cancer genetic programs and antitumor immunity via multidimensional genome-scale analyses.Methods: Multidimensional ER+ BC high-throughput data (raw count data) including gene expression profiles, copy number variation (CNV) data, single-nucleotide polymorphism mutation data, and relevant clinical information were downloaded from The Cancer Genome Atlas to explore an immune subtype sensitive to immunotherapy using the Consensus Cluster Plus algorithm based on multidimensional genome-scale analyses. One ArrayExpress dataset and eight Gene Expression Omnibus (GEO) datasets (GEO-meta dataset) as well as the Molecular Taxonomy of Breast Cancer International Consortium dataset were used as validation sets to confirm the findings regarding the immune profiles, mutational features, and survival outcomes of the three identified immune subtypes. Moreover, the development trajectory of ER+ BC patients from the single-cell resolution level was also explored.Results: Through comprehensive bioinformatics analysis, three immune subtypes of ER+ BC (C1, C2, and C3, designated the immune suppressive, activation, and neutral subtypes, respectively) were identified. C2 was associated with up-regulated immune cell signatures and immune checkpoint genes. Additionally, five tumor-related pathways (transforming growth factor, epithelial–mesenchymal transition, extracellular matrix, interferon-γ, and WNT signaling) tended to be more activated in C2 than in C1 and C3. Moreover, C2 was associated with a lower tumor mutation burden, a decreased neoantigen load, and fewer CNVs. Drug sensitivity analysis further showed that C2 may be more sensitive to immunosuppressive agents.Conclusion: C2 (the immune activation subtype) may be sensitive to immunotherapy, which provides new insights into effective treatment approaches for ER+ BC.

Background: Breast cancer (BRCA) is the most frequent malignancy. Identification of potential biomarkers could help to better understand and combat the disease at early stages.Methods: We selected the overlapping genes of differential expressed genes and genes in BRCA-highly correlated modules by Weighted Gene Co-Expression Network Analysis (WGCNA) in TCGA and GEO data and performed KEGG and GO enrichment. PPARG was achieved from Protein-Protein Interaction (PPI) network analysis and prognostic analysis. TIMER, UALCAN, GEO, TCGA, and western blot analysis were used to validate the expression of PPARG in BRCA. PPARG was further analyzed by DNA methylation, immune parameters, and tumor mutation burden.Results: Among 381 overlapping genes, the lipid metabolic process was identified as highly enriched pathways in BRCA by TCGA and GEO data. When the prognostic analysis of 10 core genes by PPI network was performed, results revealed that high expression of PPARG was significantly correlated to a better prognosis. PPARG was lesser expression in BRCA according to TIMER, UALCAN, GEO, TCGA, and western blot in both mRNA level and protein level. PPARG had several high DNA methylation level sites and the methylation level is negatively correlated to expression. PPARG is also correlated to TNM stages, tumor microenvironment, and tumor burden.Conclusions: Findings of our study identified the PPARG as a potential biomarker by confirming its low expression in BRCA and its correlation to prognosis. Moreover, its correlation to DNA methylation and tumor microenvironment may guide new therapeutic strategies for BRCA patients.

The purpose of this study is to explore the correlation between ferroptosis-related genes and schizophrenia in order to explore the new direction of diagnosis and treatment of schizophrenia. We screened the datasets related to schizophrenia from the Gene Expression Comprehensive Database (GEO) and obtained ferroptosis-related genes from the FerrDB database. Bioinformatics methods were used to analyze differentially expressed genes (DEGs) and genes associated with ferroptosis-related between schizophrenia patients and healthy controls. On this basis, the hub genes were finally screened by enrichment analysis and PPI interaction analysis. Hub genes associated with ferroptosis were validated using other schizophrenia datasets in the GEO database. Finally, the hub gene-microRNA (miRNA), gene-transcription factor interaction network was constructed, and three ferroptosis-related hub genes (TP53, VEGFA and PTGS2) were screened. The validation results of these three genes in other datasets also support this conclusion. A miRNA: hsa-mir-16-5p was found to be related to the three hub genes, and pPHF8, SAP30 and lKDM5B were identified as common regulators of the three hub genes. Our results indicate that TP53, VEGFA and PTGS2 are significantly associated with schizophrenia, and may be ferroptosis-related markers of the disease.

Osteoarthritis (OA) is a type of arthritis that causes joint pain and limited mobility. In recent years, some studies have shown that the pathological process of OA chondrocytes is related to ferroptosis. Our study aims to identify and validate differentially expressed ferroptosis-related genes (DEFRGs) in OA chondrocytes and to investigate the potential molecular mechanisms. RNA-sequencing and microarray datasets were downloaded from Gene Expression Omnibus (GEO) data repository. Differentially expressed genes (DEGs) were screened by four methods: limma-voom, edgeR, DESeq2, and Wilcoxon rank-sum test. Weighted correlation network analysis (WGCNA), protein-protein interactions (PPI), and cytoHubba of Cytoscape were applied to identify hub genes. Clinical OA cartilage specimens were collected for quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis, western blotting (WB), histological staining, transmission electron microscopy (TEM), and transfection. Sankey diagram was used to visualize the relationships between the expression level of SLC3A2 in the damaged area and clinical factors. Based on bioinformatics analysis, clinical factors, and experiment validation, SLC3A2 was identified as a hub gene. It was down-regulated in OA cartilage compared to normal cartilage (p < 0.05). Functional enrichment analysis revealed that SLC3A2 was associated with ferroptosis-related functions. Spearman correlation analysis showed that the expression level of SLC3A2 in the OA cartilage-damaged area was closely related to BMI, obesity grade, and Kellgren-Lawrence grade. Furthermore, in vitro experiments validated that SLC3A2 inhibited ferroptosis and suppressed cartilage degeneration in OA. In summary, we demonstrated that SLC3A2 inhibited ferroptosis and suppressed cartilage degeneration in OA. These findings provide a new idea for the study of the pathogenesis of OA, thus providing new means for the clinical diagnosis and targeted therapy of OA.

Background and objectives: In clinical practice, we observed that the prognoses of patients with heart failure and atrial fibrillation were worse than those of patients with only heart failure or atrial fibrillation. The study aims to get a better understanding of the common pathogenesis of the two diseases and find new therapeutic targets. Materials and Methods: We downloaded heart failure datasets and atrial fibrillation datasets from the gene expression omnibus database. The common DEGs (differentially expressed genes) in heart failure and atrial fibrillation were identified by a series of bioinformatics methods. To better understand the functions and possible pathways of DEGs, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Results: We identified 22 up-regulated genes and 14 down-regulated genes in two datasets of heart failure and 475 up-regulated and 110 down-regulated genes in atrial fibrillation datasets. In addition, two co-upregulated (FRZB, SFRP4) and three co-downregulated genes (ENTPPL, AQP4, C1orf105) were identified. GO enrichment results showed that these common differentially expressed genes were mainly concentrated in the signal regulation of the Wnt pathway. Conclusions: We found five crucial genes in heart failure and atrial fibrillation, which may be potential therapeutic targets for patients with heart failure and atrial fibrillation.

Background The tumor microenvironment (TME) has significantly correlation with tumor occurrence and prognosis. Our study aimed to identify the prognostic immune-related genes (IRGs)in the tumor microenvironment of colorectal cancer (CRC). Methods Transcriptome and clinical data of CRC cases were downloaded from TCGA and GEO databases. Stromal score, immune score, and tumor purity were calculated by the ESTIMATE algorithm. Based on the scores, we divided CRC patients from the TCGA database into low and high groups, and the differentially expressed genes (DEGs) were identified. Immune-related genes (IRGs) were selected by venn plots. To explore underlying pathways, protein-protein interaction (PPI) networks and functional enrichment analysis were used. After utilizing LASSO Cox regression analysis, we finally established a multi-IRGs signature for predicting the prognosis of CRC patients. A nomogram consists of the thirteen-IRGs signature and clinical parameters was developed to predict the overall survival (OS). We investigated the association between prognostic validated IRGs and immune infiltrates by TIMER database. Results Gene expression profiles and clinical information of 1635 CRC patients were collected from the TCGA and GEO databases. Higher stromal score, immune score and lower tumor purity were observed positive correlation with tumor stage and poor OS. Based on stromal score, immune score and tumor purity, 1517 DEGs, 1296 DEGs, and 1892 DEGs were identified respectively. The 948 IRGs were screened by venn plots. A thirteen-IRGs signature was constructed for predicting survival of CRC patients. Nomogram with a C-index of 0.769 (95%CI, 0.717–0.821) was developed to predict survival of CRC patients by integrating clinical parameters and thirteen-IRGs signature. The AUC for 1-, 3-, and 5-year OS were 0.789, 0.783 and 0.790, respectively. Results from TIMER database revealed that CD1B, GPX3 and IDO1 were significantly related with immune infiltrates. Conclusions In this study, we established a novel thirteen immune-related genes signature that may serve as a validated prognostic predictor for CRC patients, thus will be conducive to individualized treatment decisions.

Background Bladder cancer (BC) is a common malignancy neoplasm diagnosed in advanced stages in most cases. It is crucial to screen ideal biomarkers and construct a more accurate prognostic model than conventional clinical parameters. The aim of this research was to develop and validate an mRNA-based signature for predicting the prognosis of patients with bladder cancer. Methods The RNA-seq data was downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were screened in three datasets, and prognostic genes were identified from the training set of TCGA dataset. The common genes between DEGs and prognostic genes were narrowed down to six genes via Least Absolute Shrinkage and Selection Operator (LASSO) regression, and stepwise multivariate Cox regression. Then the gene-based risk score was calculated via Cox coefficient. Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier (KM) survival analysis were used to assess the prognostic power of risk score. Multivariate Cox regression analysis was applied to construct a nomogram. Decision curve analysis (DCA), calibration curves, and time-dependent ROC were performed to assess the nomogram. Finally, functional enrichment of candidate genes was conducted to explore the potential biological pathways of candidate genes. Results SORBS2, GPC2, SETBP1, FGF11, APOL1, and H1–2 were screened to be correlated with the prognosis of BC patients. A nomogram was constructed based on the risk score, pathological stage, and age. Then, the calibration plots for the 1-, 3-, 5-year OS were predicted well in entire TCGA-BLCA patients. Decision curve analysis (DCA) indicated that the clinical value of the nomogram was higher than the stage model and TNM model in predicting overall survival analysis. The time-dependent ROC curves indicated that the nomogram had higher predictive accuracy than the stage model and risk score model. The AUC of nomogram time-dependent ROC was 0.763, 0.805, and 0.806 for 1-year, 3-year, and 5-year, respectively. Functional enrichment analysis of candidate genes suggested several pathways and mechanisms related to cancer. Conclusions In this research, we developed an mRNA-based signature that incorporated clinical prognostic parameters to predict BC patient prognosis well, which may provide a novel prognosis assessment tool for clinical practice and explore several potential novel biomarkers related to the prognosis of patients with BC.

Although more and more studies have shown that EZH2 was closely related to human cancer, no pan-cancer analysis is available. Therefore, we summarized and analyzed the potential carcinogenic effect of EZH2 for the first time based on TCGA (cancer genome map) datasets. EZH2 is expressed highly in most tumors and there is a significant correlation between the EZH2 expression and the prognosis of patients. We observed the increased phosphorylation levels of T487 in breast cancer, colon cancer, UCEC, and LUAD. The expression of EZH2 was associated with the CD8+, tregs, macrophage, and cancer-associated fibroblast infiltration in some tumors. In addition, the cell cycle and cellular biology were involved in the functional mechanisms of EZH2. Our study summarized and analyzed the carcinogenic effect of EZH2 in different tumors comprehensively and provided a theoretical basis for targeting EZH2 therapy.

Hepatocellular carcinoma (HCC) is one of the most common carcinomas worldwide. Our study aims to analyze how NUSAP1 affects progression of HCC from clinical, molecular mechanism and immune perspectives. Firstly, we downloaded GSE62232, GSE102079, GSE112790, and GSE121248 gene expression profile datasets from GEO database. R studio was used to screen DEGs of each dataset, and 86 overlapping DEGs of the four datasets were screened at last. Then, CytoHubba plug-in in Cytoscape software was used to screen out NUSAP1 from the 86 DEGs. Subsequently, survival analysis, clinical correlation analysis, independent prognostic analysis, and GSEA enrichment analysis of NUSAP1 were analyzed using HCC patients from GSE76427 dataset, ICGC database, and TCGA database. The results revealed that HCC patients with higher expression level of NUSAP1 had a worse prognosis. NUSAP1 was an independent prognostic factor of HCC, and it may promote HCC progress by regulating cell cycle. To further elucidate its underlying molecular mechanism, we used cBioProtal online data analysis tool to screen all co-expression genes of NUSAP1 and used top 300 co-expression genes to accomplish KEGG and GO enrichment analysis; the results confirmed that NUSAP1 accelerated progression of HCC by regulating cell cycle. We continued to draw KEGG pathway map of cell cycle using co-expression genes enriched in cell cycle pathway by KEGG online tool. The map depicted that most of co-expression genes of NUSAP1 were located in S phase and G2/M phase of the cell cycle, and they could regulate the genes in G1 phase. To further understand the mechanism of cell cycle, we also did qRT-PCR, Western blot, and flow cytometry; the results showed that NUSAP1 was closely associated with CDK4, CDK6, and cyclinD1, which could regulate G1 to S phase transition. Besides, we also analyzed correlation between NUSAP1 and immune cells using HCC patients from GSE76427 dataset, ICGC database, and TCGA database. NUSAP1 was associated with some immune cells, and we speculated that NUSAP1 could also promote HCC progression by influencing T cell CD4 memory resting and macrophage M0 through some underlying mechanism.

Background Bone is the most common site of metastatic breast cancer, and it is a leading cause of breast cancer-related death. This study aimed to explore bone metastasis-related long non-coding RNAs (lncRNAs) in breast cancer. Methods Four mRNA datasets and two lncRNA datasets of bone metastasis, lung metastasis and liver metastasis of breast cancer were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) in group of bone metastasis vs lung metastasis and bone metastasis vs liver metastasis, as well as the overlap of the two groups, were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and protein–protein interaction (PPI) network construction of DEmRNAs were conducted. The cis nearby-targeted DEmRNAs of DElncRNAs were obtained. Quantitative real-time polymerase chain reactions (qRT-PCR) was used to detect the expression levels of selected DEmRNAs and DElncRNAs. LOC641518-lymphoid enhancer-binding factor 1 (LEF1) pair was selected to verify its role in migration and invasion capability of breast cancer cells by wounding healing assay and transwell invasion assay. Results A total of 237 DEmRNAs were obtained in bone metastasis compared with both lung metastasis and liver metastasis. A total of three DElncRNAs in bone metastasis compared with both lung metastasis and liver metastasis were obtained. A total of seven DElncRNA-nearby-targeted DEmRNA pairs and 15 DElncRNA-nearby-targeted DEmRNA pairs in group of bone metastasis vs lung metastasis and bone metastasis vs liver metastasis, were detected, respectively. Four cis LncRNA-mRNA interaction pairs were identified, which are LOC641518-LEF1, FLJ35024-Very Low Density Lipoprotein Receptor (VLDLR), LOC285972-Retinoic Acid Receptor Responder 2 (RARRES2) and LOC254896-TNF receptor superfamily member 10c (TNFRSF10C). qRT-PCR using clinical samples from our hospital confirms the bioinformatics prediction. siRNA knocking down LOC641518 down-regulates LEF1 mRNA expression, and reduces the migration and invasion capability of breast cancer cells. Conclusions We concluded that four LncRNA-mRNA pairs, including LOC641518-LEF1, may play a central role in breast cancer bone metastasis.

The growing evidence suggests that circular RNAs (circRNAs) have significant associations with tumor occurrence and progression, yet the regulatory mechanism of circRNAs in lung adenocarcinoma (LUAD) remains unclear. This study clarified the potentially regulatory network and functional mechanism of circRNAs in LUAD. The expression data of circRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) were obtained from the Gene Expression Omnibus (GEO) database. Relying on GSE101586, GSE101684, and GSE112214, we identified differentially expressed circRNAs (DEcircRNAs). Depending on GSE135918 and GSE32863, we screened out differentially expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs), respectively. Then, a novel competing endogenous RNA (ceRNA) regulatory network related to LUAD was constructed. We also revealed biological processes and signal pathways regulated by these DEcircRNAs. Based on gene expression data and survival information of LUAD patients in The Cancer Genome Atlas (TCGA) and GEO, we implemented survival analysis to select DEmRNAs related to prognosis and build a novel circRNA–miRNA–mRNA hub regulatory network. Meanwhile, quantitative real-time PCR (qRT-PCR) was utilized to validate DEcircRNAs in the ceRNA hub regulatory network. As a result, a total of 8 DEcircRNAs, 19 DEmiRNAs, and 85 DEmRNAs were identified. The novel ceRNA regulatory network included 5 circRNAs, 8 miRNAs, and 22 mRNAs. The final ceRNA hub regulatory network contained two circRNAs, two miRNAs, and two mRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that the five DEcircRNAs may affect LUAD onset and progression through Wnt signaling pathway and Hippo signaling pathway. All in all, this study revealed the regulatory network and functional mechanism of circRNA-related ceRNAs in LUAD.

Hepatocellular carcinoma (HCC) is the most common malignant tumor of the liver, with high morbidity and mortality, yet its molecular mechanisms of tumorigenesis are still unclear. In this study, gene expression profile of GSE62232 was downloaded from the Gene Expression Omnibus (GEO). The RNA-seq expression data and relative clinical information were retrieved from the Cancer Genome Atlas (TCGA) database. The datasets were analyzed by differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) to obtain the overlapping genes. Then, we performed a functional enrichment analysis to understand the potential biological functions of these co-expression genes. Finally, we constructed the protein-protein interaction (PPI) analysis combined with survival analysis. MARCO, CLEC4M, FCGR2B, LYVE1, TIMD4, STAB2, CFP, CLEC4G, CLEC1B, FCN2, FCN3 and FOXO1 were identified as the candidate hub genes using the CytoHubba plugin of Cytoscape. Based on survival analysis, the lower expression of FCN3 and FOXO1 were associated with worse overall survival (OS) in HCC patients. Furthermore, the expression levels of FCN3 and FOXO1 were validated by the Human Protein Atlas (HPA) database and the qRT-PCR. In summary, our findings contribute new ideas for the precise early diagnosis, clinical treatment and prognosis of HCC in the future.

AimPterygium is a common ocular surface disease, which is affected by a variety of factors. Invasion of the cornea can cause severe vision loss. N6-methyladenosine (m6A) is a common post-transcriptional modification of eukaryotic mRNA, which can regulate mRNA splicing, stability, nuclear transport, and translation. To our best knowledge, there is no current research on the mechanism of m6A in pterygium.MethodsWe obtained 24 pterygium tissues and 24 conjunctival tissues from each of 24 pterygium patients recruited from Shanghai Yangpu Hospital, and the level of m6A modification was detected using an m6A RNA Methylation Quantification Kit. Expression and location of METTL3, a key m6A methyltransferase, were identified by immunostaining. Then we used m6A-modified RNA immunoprecipitation sequencing (MeRIP-seq), RNA sequencing (RNA-seq), and bioinformatics analyses to compare the differential expression of m6A methylation in pterygium and normal conjunctival tissue.ResultsWe identified 2,949 dysregulated m6A peaks in pterygium tissue, of which 2,145 were significantly upregulated and 804 were significantly downregulated. The altered m6A peak of genes were found to play a key role in the Hippo signaling pathway and endocytosis. Joint analyses of MeRIP-seq and RNA-seq data identified 72 hypermethylated m6A peaks and 15 hypomethylated m6A peaks in mRNA. After analyzing the differentially methylated m6A peaks and synchronously differentially expressed genes, we searched the Gene Expression Omnibus database and identified five genes related to the development of pterygium (DSP, MXRA5, ARHGAP35, TMEM43, and OLFML2A).ConclusionOur research shows that m6A modification plays an important role in the development of pterygium and can be used as a potential new target for the treatment of pterygium in the future.

The dysregulation of transcriptional factors (TFs) leads to malignant growth and the development of colorectal cancer (CRC). Herein, we sought to identify the transcription factors relevant to the prognosis of colorectal cancer patients. We found 526 differentially expressed TFs using the TCGA database of colorectal cancer patients (n = 544) for the differential analysis of TFs (n = 1,665) with 210 upregulated genes as well as 316 downregulated genes. Subsequently, GO analysis and KEGG pathway analysis were performed for these differential genes for investigating their pathways and function. At the same time, we established a genetic risk scoring model for predicting the overall survival (OS) by using the mRNA expression levels of these differentially regulated TFs, and defined the CRC into low and high-risk categories which showed significant survival differences. The genetic risk scoring model included four high-risk genes (HSF4, HEYL, SIX2, and ZNF26) and two low-risk genes (ETS2 and SALL1), and validated the OS in two GEO databases (p = 0.0023 for the GSE17536, p = 0.0193 for the GSE29623). To analyze the genetic and epigenetic changes of these six risk-related TFs, a unified bioinformatics analysis was conducted. Among them, ZNF26 is progressive in CRC and its high expression is linked with a poor diagnosis as well. Knockdown of ZNF26 inhibits the proliferative capacity of CRC cells. Moreover, the positive association between ZNF26 and cyclins (CDK2, CCNE2, CDK6, CHEK1) was also identified. Therefore, as a novel biomarker, ZNF26 may be a promising candidate in the diagnosis and prognostic evaluation of colorectal cancer.

Background Gastric cancer (GC) is the most prevalent malignancy among the digestive system tumors. Increasing evidence has revealed that lower mRNA expression of ANXA9 is associated with a poor prognosis in colorectal cancer. However, the role of ANXA9 in GC remains largely unknown. Material and Methods The Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas databases were used to investigate the expression of ANXA9 in GC, which was then validated in the four Gene Expression Omnibus (GEO) datasets. The diagnostic value of ANXA9 for GC patients was demonstrated using a receiver operating characteristic (ROC) curve. The correlation between ANXA9 expression and clinicopathological parameters was analyzed in The Cancer Genome Atlas (TCGA) and UALCAN databases. The Kaplan-Meier (K-M) survival curve was used to elucidate the relationship between ANXA9 expression and the survival time of GC patients. We then performed a gene set enrichment analysis (GSEA) to explore the biological functions of ANXA9. The relationship of ANXA9 expression and cancer immune infiltrates was analyzed using the Tumor Immune Estimation Resource (TIMER). In addition, the potential mechanism of ANXA9 in GC was investigated by analyzing its related genes. Results ANXA9 was significantly up-regulated in GC tissues and showed obvious diagnostic value. The expression of ANXA9 was related to the age, gender, grade, TP53 mutation, and histological subtype of GC patients. We also found that ANXA9 expression was associated with immune-related biological function. ANXA9 expression was also correlated with the infiltration level of CD8+ T cells, neutrophils, and dendritic cells in GC. Additionally, copy number variation (VNV) of ANXA9 occurred in GC patients. Function enrichment analyses revealed that ANXA9 plays a role in the GC progression by interacting with its related genes. Conclusions Our results provide strong evidence of ANXA9 expression as a prognostic indicator related to immune responses in GC.

Cervical squamous cell carcinoma (CSCC) accounts for a significant proportion of cervical cancer; thus, there is a need for novel and noninvasive diagnostic biomarkers for this malignancy. In this study, we performed integrated analysis of a dataset from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) between CSCC, cervical intraepithelial neoplasia (CIN) and healthy control subjects. We further established protein‐protein interaction and DEmiRNA‐target gene interaction networks, and performed functional annotation of the target genes of DEmiRNAs. In total, we identified 1375 DEGs and 19 DEmiRNAs in CIN versus normal control, and 2235 DEGs and 33 DEmiRNAs in CSCC versus CIN by integrated analysis. Our protein‐protein interaction network indicates that the common DEGs, Cyclin B/cyclin‐dependent kinase 1 (CDK1), CCND1, ESR1 and Aurora kinase A (AURKA), are the top four hub genes. P53 and prostate cancer were identified as significantly enriched signaling pathways of common DEGs and DEmiRNA targets, respectively. We validated that expression levels of three DEGs (TYMS, SASH1 and CDK1) and one DEmiRNA of hsa‐miR‐99a were altered in blood samples of patients with CSCC. In conclusion, a total of four DEGs (TYMS, SASH1, CDK1 and AURKA) and two DEmiRNAs (hsa‐miR‐21 and hsa‐miR‐99a) may be involved in the pathogenesis of CIN and the progression of CIN into CSCC. Of these, TYMS is predicted to be regulated by hsa‐miR‐99a and SASH1 to be regulated by hsa‐miR‐21., Here, we performed integrated analysis of a Gene Expression Omnibus database dataset to identify differentially expressed mRNAs and differentially expressed miRNAs in cervical intraepithelial neoplasia (CIN) and cervical squamous cell carcinoma. We identified a total of four differentially expressed genes (TYMS, SASH1, Cyclin B/cyclin‐dependent kinase 1 and Aurora kinase A) and two differentially expressed miRNAs (hsa‐miR‐21 and hsa‐miR‐99a) that may be involved in the pathogenesis of CIN and the progression of CIN into cervical squamous cell carcinoma.

The transition from non–muscle‐invasive bladder cancer (NMIBC) to muscle‐invasive bladder cancer (MIBC) is detrimental to bladder cancer (BLCA) patients. Here, we aimed to study the underlying mechanism of the subtype transition. Gene set variation analysis (GSVA) revealed the epithelial‐mesenchymal transition (EMT) signalling pathway with the most positive correlation in this transition. Then, we built a LASSO Cox regression model of an EMT‐related gene signature in BLCA. The patients with high risk scores had significantly worse overall survival (OS) and disease‐free survival (DFS) than those with low risk scores. The EMT‐related gene signature also performed favourably in the accuracy of prognosis and in the subtype survival analysis. Univariate and multivariate Cox regression analyses demonstrated that the EMT‐related gene signature, pathological N stage and age were independent prognostic factors for predicting survival in BLCA patients. Furthermore, the predictive nomogram model was able to effectively predict the outcome of BLCA patients by appropriately stratifying the risk score. In conclusion, we developed a novel EMT‐related gene signature that has tumour‐promoting effects, acts as a negative independent prognostic factor and might facilitate personalized counselling and treatment in BLCA.