scholarly journals Combining Bioinformatics and Experiments to Identify and Verify Gene Prognostic Markers in Hepatocellular Carcinoma

2021 ◽  
pp. 1-12
Author(s):  
Li Luo ◽  
Rong Wang ◽  
Liaoyun Zhang ◽  
Piao Zhang ◽  
Dongmei Tian ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Proportional Hazards ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Disease Free Survival ◽  
Enrichment Analysis ◽  
Cox Proportional Hazards ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes

Background: Hepatocellular Carcinoma (HCC) is one of the highly malignant tumors threatening human health. The current research aimed to identify potential prognostic gene biomarkers for HCC. Materials and Methods: Microarray data of gene expression profiles of HCC from GEO were downloaded. After screening overlapping differentially expressed genes (DEGs) by R software. The STRING database and Cytoscape were used to identify hub genes. Cox proportional hazards regression was performed to screen the potential prognostic genes. Moreover, quantitative real-time PCR analyses were performed to detect the expression of ANLN in liver cancer cells and tissues. Finally, its possible pathways and functions were predicted using gene set enrichment analysis (GSEA). Result: A total of 566 DEGs were obtained from the overlapping analysis of three mRNA microarray dataset. Six key hub genes including RACGAP1, KIF20, DLGAP5, CDK1, BUB1B and ANLN, were associated with poor prognosis of patients with HCC. Higher expression of ANLN was associated with reduced overall survival and disease-free survival in patients with HCC. Multivariate analysis revealed that ANLN expression was an independent risk factor affecting overall survival. RT-PCR and Western blot analysis further demonstrated that ANLN expression was increased in HCC compared with patient-matched adjacent normal tissues. Notably, Gene enrichment analysis revealed that DEGs in ANLN-high patients were enriched in cell cycle, DNA duplication and p53 signaling pathway. Conclusion: The high expression of RACGAP1, KIF20, DLGAP5, CDK1, BUB1B and ANLN might be poor prognostic biomarkers in HCC patients, and may help to individualize the management of HCC.

scholarly journals Cyclin B1 acts as a tumor microenvironment-related cancer promoter and prognostic biomarker in hepatocellular carcinoma

2021 ◽  
Vol 49 (5) ◽  
pp. 030006052110162
Author(s):  
Yangming Hou ◽  
Xin Wang ◽  
Junwei Wang ◽  
Xuemei Sun ◽  
Xinbo Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Proportional Hazards ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Cyclin B1 ◽  
Cox Proportional Hazards ◽  
Gene Set Enrichment Analysis ◽  
Tumor Promoter ◽  
Protein Protein Interaction

Objectives The present study aimed to develop a gene signature based on the ESTIMATE algorithm in hepatocellular carcinoma (HCC) and explore possible cancer promoters. Methods The ESTIMATE and CIBERSORT algorithms were applied to calculate the immune/stromal scores and the proportion of tumor-infiltrating immune cells (TICs) in a cohort of HCC patients. The differentially expressed genes (DEGs) were screened by Cox proportional hazards regression analysis and protein–protein interaction (PPI) network construction. Cyclin B1 (CCNB1) function was verified using experiments. Results The stromal and immune scores were associated with clinicopathological factors and recurrence-free survival (RFS) in HCC patients. In total, 546 DEGs were up-regulated in low score groups, 127 of which were associated with RFS. CCNB1 was regarded as the most predictive factor closely related to prognosis of HCC and could be a cancer promoter. Gene Set Enrichment Analysis (GSEA) and CIBERSORT analyses indicated that CCNB1 levels influenced HCC tumor microenvironment (TME) immune activity. Conclusions The ESTIMATE signature can be used as a prognosis tool in HCC. CCNB1 is a tumor promoter and contributes to TME status conversion.

scholarly journals Identification of a five-gene signature in association with overall survival for hepatocellular carcinoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11273
Author(s):  
Lei Yang ◽  
Weilong Yin ◽  
Xuechen Liu ◽  
Fangcun Li ◽  
Li Ma ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Overall Survival ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Enrichment Score ◽  
Hub Genes ◽  
Cox Regression Analysis

Background Hepatocellular carcinoma (HCC) is considered to be a malignant tumor with a high incidence and a high mortality. Accurate prognostic models are urgently needed. The present study was aimed at screening the critical genes for prognosis of HCC. Methods The GSE25097, GSE14520, GSE36376 and GSE76427 datasets were obtained from Gene Expression Omnibus (GEO). We used GEO2R to screen differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed by Cytoscape in order to find hub genes by module analysis. The Metascape was performed to discover biological functions and pathway enrichment of DEGs. MCODE components were calculated to construct a module complex of DEGs. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. ONCOMINE was employed to assess the mRNA expression levels of key genes in HCC, and the survival analysis was conducted using the array from The Cancer Genome Atlas (TCGA) of HCC. Then, the LASSO Cox regression model was performed to establish and identify the prognostic gene signature. We validated the prognostic value of the gene signature in the TCGA cohort. Results We screened out 10 hub genes which were all up-regulated in HCC tissue. They mainly enrich in mitotic cell cycle process. The GSEA results showed that these data sets had good enrichment score and significance in the cell cycle pathway. Each candidate gene may be an indicator of prognostic factors in the development of HCC. However, hub genes expression was weekly associated with overall survival in HCC patients. LASSO Cox regression analysis validated a five-gene signature (including CDC20, CCNB2, NCAPG, ASPM and NUSAP1). These results suggest that five-gene signature model may provide clues for clinical prognostic biomarker of HCC.

scholarly journals Prognostic Value of BIRC5 in Lung Adenocarcinoma Lacking EGFR, KRAS, and ALK Mutations by Integrated Bioinformatics Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Yajuan Cao ◽  
Weikang Zhu ◽  
Wanqing Chen ◽  
Jianchun Wu ◽  
Guozhen Hou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Lung Adenocarcinoma ◽  
Prognostic Value ◽  
Expression Profiles ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Hub Genes

Objective. This study was aimed at investigating the prognostic significance of Baculoviral IAP repeat containing 5 (BIRC5) in lung adenocarcinoma (LAD) lacking EGFR, KRAS, and ALK mutations (triple-negative (TN) adenocarcinomas). Methods. The gene expression profiles were obtained from Gene Expression Omnibus (GEO). The identification of the differentially expressed genes (DEGs) was performed by GeneSpring GX. Gene set enrichment analysis (GSEA) was used to execute gene ontology function and pathway enrichment analysis. The protein interaction network was constructed by Cytoscape. The hub genes were extracted by MCODE and cytoHubba plugin from the network. Then, using BIRC5 as a candidate, the prognostic value in LAD and TN adenocarcinomas was verified by the Kaplan-Meier plotter and The Cancer Genome Atlas (TCGA) database, respectively. Finally, the mechanism of BIRC5 was predicted by a coexpressed network and enrichment analysis. Results. A total of 38 upregulated genes and 121 downregulated genes were identified. 9 hub genes were extracted. Among them, the mRNA expression of 5 genes, namely, BIRC5, MCM4, CDC20, KIAA0101, and TRIP13, were significantly upregulated among TN adenocarcinomas (all P<0.05). Notably, only the overexpression of BIRC5 was associated with unfavorable overall survival (OS) in TN adenocarcinomas (log rank P=0.0037). TN adenocarcinoma patients in the BIRC5 high-expression group suffered from a significantly high risk of distant metastasis (P=0.046), advanced N stage (P=0.033), and tumor-bearing (P=0.031) and deceased status (P=0.003). The mechanism of BIRC5 and coexpressed genes may be linked closely with the cell cycle. Conclusion. Overexpressed in tumors, BIRC5 is associated with unfavorable overall survival in TN adenocarcinomas. BIRC5 is a potential predictor and therapeutic target in TN adenocarcinomas.

scholarly journals Identification of Arp2/3 Complex Subunits as Prognostic Biomarkers for Hepatocellular Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Shenglan Huang ◽  
Dan Li ◽  
LingLing Zhuang ◽  
Liying Sun ◽  
Jianbing Wu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Mrna Expression ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Biomarkers ◽  
Migration And Invasion ◽  
Regression Analyses ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression

The actin-related protein 2/3 complex (Arp2/3) is a major actin nucleator that has been widely reported and plays an important role in promoting the migration and invasion of various cancers. However, the expression patterns and prognostic values of Arp2/3 subunits in hepatocellular carcinoma (HCC) remain unclear. In this study, The Cancer Genome Atlas (TCGA) and UCSC Xena databases were used to obtain mRNA expression and the corresponding clinical information, respectively. The differential expression and Arp2/3 subunits in HCC were analyzed using the “limma” package of R 4.0.4 software. The prognostic value of each subunit was evaluated using Kaplan–Meier survival analysis and Cox proportional hazards regression analyses. The results revealed that mRNA expression of Arp2/3 members (ACTR2, ACTR3, ARPC1A, APRC1B, ARPC2, ARPC3, ARPC4, ARPC5, and ARPC5L) was upregulated in HCC. Higher expression of Arp2/3 members was significantly correlated with worse overall survival (OS) and shorter progression-free survival (PFS) in HCC patients. Cox proportional hazards regression analyses demonstrated that ACTR3, ARPC2, and ARPC5 were independent prognostic biomarkers of survival in patients with HCC. The relation between tumor immunocyte infiltration and the prognostic subunits was determined using the TIMER 2.0 platform and the GEPIA database. Gene set enrichment analysis (GSEA) was performed to explore the potential mechanisms of prognostic subunits in the carcinogenesis of HCC. The results revealed that ACTR3, ARPC2, and ARPC5 were significantly positively correlated with the infiltration of immune cells in HCC. The GSEA results indicated that ACTR3, ARPC2, and ARPC5 are involved in multiple cancer-related pathways that promote the development of HCC. In brief, various analyses indicated that Arp2/3 complex subunits were significantly upregulated and predicted worse survival in HCC, and they found that ACTR3, ARPC2, and ARPC5 could be used as independent predictors of survival and might be applied as promising molecular targets for diagnosis and therapy of HCC in the future.

scholarly journals Expression Profile and Prognostic Values of SMC Family Members in HCC

2021 ◽  
Author(s):  
Wei Yan ◽  
Dan-dan Wang ◽  
He-da Zhang ◽  
Jinny Huang ◽  
Jun-Chen Hou ◽  
...  
Keyword(s):  
Gene Family ◽  
Expression Profile ◽  
Proportional Hazards ◽  
Wide Spectrum ◽  
Clinical Stage ◽  
Family Members ◽  
Enrichment Analysis ◽  
Cox Proportional Hazards ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas

Abstract Background: The structural maintenance of chromosome (SMC) gene family, comprising 6 members, is involved in a wide spectrum of biological functions in many types of human cancers. However, there is little research on the expression profile and prognostic values of SMC genes in hepatocellular carcinoma (HCC). Based on updated public resources and integrative bioinformatics analysis, we tried to determine the value of SMC gene expression in predicting the risk of developing HCC. Methods and materials: The expression data of SMC family members were obtained from The Cancer Genome Atlas (TCGA). The prognostic values of SMC members and clinical features were identified. A gene set enrichment analysis (GSEA) was conducted to explore the mechanism underlying the involvement of SMC members in liver cancer. The associations between tumor immune infiltrating cells (TIICs) and the SMC family members were evaluated using the Tumor Immune Estimation Resource (TIMER) database. Results: Our analysis demonstrated that mRNA downregulation of SMC genes was common alteration in HCC patients. SMC1A, SMC2, SMC3, SMC4, SMC6 were upregulated in HCC. Upregulation of SMC2, SMC3 and SMC4, along with clinical stage, were associated with a poor HCC prognosis based on the results of univariate and multivariate Cox proportional hazards regression analyses. SMC2, SMC3 and SMC4 are also related to tumor purity and immune infiltration levels of HCC. The GSEA results indicated that SMC members participate in multiple biological processes underlying tumorigenesis. Conclusion: This study comprehensively analyzed the expression of SMC gene family members in patients with HCC. This can provide insights for further investigation of the SMC family members as potential targets in HCC and suggest that the use of SMC inhibitor targeting SMC2, SMC3 and SMC4 may be an effective strategy for HCC therapy.

scholarly journals Identification of Key Genes and Prognostic Value Analysis in Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-21 ◽  
Author(s):  
Meng Wang ◽  
Licheng Wang ◽  
Shusheng Wu ◽  
Dongsheng Zhou ◽  
Xianming Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Expression Profiles ◽  
Cyclin B1 ◽  
Ppi Network ◽  
Hub Genes ◽  
Altered Expression ◽  
Value Analysis ◽  
Kaplan Meier ◽  
Key Genes

Emerging evidence indicates that various functional genes with altered expression are involved in the tumor progression of human cancers. This study is aimed at identifying novel key genes that may be used for hepatocellular carcinoma (HCC) diagnosis, prognosis, and targeted therapy. This study included 3 expression profiles (GSE45267, GSE74656, and GSE84402), which were obtained from the Gene Expression Omnibus (GEO). GEO2R was used to analyze the differentially expressed genes (DEGs) between HCC and normal samples. The functional and pathway enrichment analysis was performed by the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of the identified DEGs was constructed using the Search Tool for the Retrieval of Interacting Gene, and hub genes were identified. ONCOMINE and CCLE databases were used to verify the expression of the hub genes in HCC tissues and cells. Kaplan-Meier plotter was used to assess the effects of the hub genes on the overall survival of HCC patients. A total of 99 DEGs were identified from the 3 expression profiles. These DEGs were enriched with functional processes and pathways related to HCC pathogenesis. From the PPI network, 5 hub genes were identified. The expression of the 5 hub genes was all upregulated in HCC tissues and cells compared with the control tissues and cells. Kaplan-Meier survival curves indicated that high expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), cyclin B2 (CCNB2), MAD2 mitotic arrest deficient-like 1 (MAD2L1), and topoisomerase IIα (TOP2A) predicted poor overall survival in HCC patients (all log-rank P<0.01). These results revealed that the DEGs may serve as candidate key genes during HCC pathogenesis. The 5 hub genes, including CDK1, CCNB1, CCNB2, MAD2L1, and TOP2A, may serve as promising prognostic biomarkers in HCC.

scholarly journals Identification of an IRGP Signature to Predict Prognosis and Immunotherapeutic Efficiency in Bladder Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Liang-Hao Zhang ◽  
Long-Qing Li ◽  
Yong-Hao Zhan ◽  
Zhao-Wei Zhu ◽  
Xue-Pei Zhang
Keyword(s):  
Bladder Cancer ◽  
Stromal Cells ◽  
Molecular Mechanisms ◽  
Proportional Hazards ◽  
Enrichment Analysis ◽  
Cox Proportional Hazards ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Validation Set

BackgroundIdentify immune-related gene pairs (IRGPs) signature related to the prognosis and immunotherapeutic efficiency for bladder cancer (BLCA) patients.Materials and MethodsOne RNA-seq dataset (The Cancer Genome Atlas Program) and two microarray datasets (GSE13507 and GSE31684) were included in this study. We defined these cohorts as training set to construct IRGPs and one immunotherapy microarray dataset as validation set. Identifying BLCA subclasses based on IRGPs by consensus clustering. The Lasso penalized Cox proportional hazards regression model was used to construct prognostic signature and potential molecular mechanisms were analyzed.ResultsThis signature can accurately predict the overall survival of BLCA patients and was verified in the immunotherapy validation set. IRGP-signatures can be used as independent prognostic risk factor in various clinical subgroups. Use the CIBERSORT algorithm to assess the abundance of infiltrating immune cells in each sample, and combine the results of the gene set enrichment analysis of a single sample to explore the differences in the immune microenvironment between IRPG signature groups. According to the results of GSVA, GSEA, and CIBERSORT algorithm, we found that IRGP is strikingly positive correlated with tumor microenvironment (TME) stromal cells infiltration, indicating that the poor prognosis and immunotherapy might be caused partly by enrichment of stromal cells. Finally, the results from the TIDE analysis revealed that IRGP could efficiently predict the response of immunotherapy in BLCA.ConclusionThe novel IRGP signature has a significant prognostic value for BLCA patients might facilitate personalized for immunotherapy.

scholarly journals Identification of Key Immune-Related Genes, Molecular Pathways and Immune Infiltration as Diagnostic and Therapeutic Candidate Targets for RA: an integrated bioinformatics-based analysis

2021 ◽  
Author(s):  
Sheng Fang ◽  
Xiao Fang ◽  
Xin Xu ◽  
Lin Zhong ◽  
An-quan Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Mast Cells ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Systemic Autoimmune Disease ◽  
Molecular Pathways ◽  
Hub Genes ◽  
Immune Infiltration

Abstract Relevance Rheumatoid arthritis (RA) is a systemic autoimmune disease with an aggressive, chronic synovial inflammation as the main pathological change. However, the specific etiology, pathogenesis, and related biomarkers in diagnosis and treatment are still not fully elucidated. This study attempts to provide new perspectives and insights into RA at the genetic, molecular, and cellular levels through the tenet of personalized medicine. Methods Gene expression profiles of four individual knee synovial tissues were downloaded from a comprehensive gene expression database, R language was used to screen for significantly differentially expressed genes (DEGs), Gene Ontology Enrichment Analysis, Kyoto Gene Encyclopedia, and Gene Set Enrichment Analysis were performed to analyze the biological functions and signaling pathways of these DEGs, STRING online database was used to establish protein-protein interaction networks, Cytoscape software to obtain ten hub genes, Goplot to get six inflammatory immune-related hub genes, and CIBERSORT algorithm to impute immune infiltration. Results Molecular pathways that play important roles in RA were obtained: Toll-like receptors, AMPK, MAPK, TNF, FoxO, TGF-beta, PI3K and NF-κB pathways, Ten hub genes: Ccr1, Ccr2, Ccr5, Ccr7, Cxcl5, Cxcl6, Cxcl13, Ccl13, Adcy2, and Pnoc. among which Adcy2 and Pnoc have not been reported in RA studies, suggesting that they may be worthy targets for further study. It was also found that among the synoviocytes in RA, the proportions of plasma cells, CD8 T cells, follicular helper T cells, monocytes, γ delta T cells, and M0 macrophages were higher, while the proportions of CD4 memory resting T cells, regulatory T cells (Tregs), activated NK cells, resting dendritic cells, M1 macrophages, eosinophils, activated mast cells, resting mast cells were lower in proportion, and each cell played an important role in RA. Conclusions This study may help understand the key genes, molecular pathways, the role of inflammatory immune infiltrating cells in RA’s pathogenesis and provide new targets and ideas for the diagnosis and personalized treatment of RA.

scholarly journals A Nomogram Based on Glycolysis-related Gene Expression Profilings Serve as a Novel Prognosis Risk Classifiers for Human Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Lingyu Zhang ◽  
Yu Li ◽  
Yibei Dai ◽  
Danhua Wang ◽  
Xuchu Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Expression Profiles ◽  
Area Under The Curve ◽  
Prognostic Index ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Related Gene ◽  
Metabolic Pattern

Abstract Metabolic pattern reconstruction is an important element in tumor progression. The metabolism of tumor cells is characterized by the abnormal increase of anaerobic glycolysis, regardless of the higher oxygen concentration, resulting in a large accumulation of energy from glucose sources, and contributes to rapid cell proliferation and tumor growth which is further referenced as the Warburg effect. We tried to reconstruct the metabolic pattern in the progression of cancer to screen which genetic changes are specific in cancer cells. A total of 12 common types of solid tumors were enrolled in the prospective study. Gene set enrichment analysis (GSEA) was implemented to analyze 9 glycolysis-related gene sets, which are closely related to the glycolysis process. Univariate and multivariate analyses were used to identify independent prognostic variables for the construction of a nomogram based on clinicopathological characteristics and a glycolysis-related gene prognostic index (GRGPI). The prognostic model based on glycolysis genes has the highest area under the curve (AUC) in LIHC (Liver hepatocellular carcinoma). 8-gene signatures (AURKA, CDK1, CENPA, DEPDC1, HMMR, KIF20A, PFKFB4, STMN1) were related to overall survival (OS) and recurrence-free survival (RFS). Further analysis demonstrates that the prediction model can accurately distinguish between high- and low-risk cancer patients among patients in different clusters in LIHC. A nomogram with a well-fitted calibration curve based on gene expression profiles and clinical characteristics improves discrimination in internal and external cohorts. Furthermore, the altering expression of metabolic genes related to glycolysis may contribute to the reconstruction of the tumor-related microenvironment.

scholarly journals ARID1A Is a Prognostic Biomarker and Associated with Immune Infiltrates in Hepatocellular Carcinoma

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Yuanyuan Feng ◽  
Xinfang Tang ◽  
Changcheng Li ◽  
Ying Su ◽  
Xiaoyu Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Migration And Invasion ◽  
Risk Indicator ◽  
Immune Cell Infiltration

Objective. ARID1A has been discovered as a potential cancer biomarker. But its role in hepatocellular carcinoma (HCC) is subject to considerable dispute. Methods. The relationship between ARID1A and clinical factors was investigated. Clinicopathological variables related to overall survival in HCC subjects were identified using Cox and Kaplan–Meier studies. The connection between immune infiltrating cells and ARID1A expression was investigated using the tumor Genome Atlas (TCGA) dataset for gene set enrichment analysis (GSEA). Finally, a cell experiment was used to confirm it. Results. The gender and cancer topography (T) categorization of HCC were linked to increased ARID1A expression. Participants with advanced levels of ARID1A expression had a worse prognosis than someone with lower levels. ARID1A was shown to be a risk indicator of overall survival on its own. ARID1A expression is inversely proportional to immune cell infiltration. In vitro, decreasing ARID1A expression substantially slowed the cell cycle and decreased HCC cell proliferation, migration, and invasion. Conclusion. The expression of ARID1A could be used to predict the outcome of HCC. It is closely related to tumor immune cell infiltration.

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