scholarly journals Identification of immune-related genes that predict prognosis and risk of bladder cancer: bioinformatics analysis of TCGA database

Aging ◽  
2021 ◽  
Author(s):  
Liqiang Guo ◽  
Qiong Wu ◽  
Zhen Ma ◽  
Mingzhen Yuan ◽  
Shengtian Zhao
2021 ◽  
Vol 12 ◽  
Author(s):  
Bingqi Dong ◽  
Jiaming Liang ◽  
Ding Li ◽  
Wenping Song ◽  
Shiming Zhao ◽  
...  

Background: Bladder cancer (BLCA) ranks 10th in incidence among malignant tumors and 6th in incidence among malignant tumors in males. With the application of immune therapy, the overall survival (OS) rate of BLCA patients has greatly improved, but the 5-year survival rate of BLCA patients is still low. Furthermore, not every BLCA patient benefits from immunotherapy, and there are a limited number of biomarkers for predicting the immunotherapy response. Therefore, novel biomarkers for predicting the immunotherapy response and prognosis of BLCA are urgently needed.Methods: The RNA sequencing (RNA-seq) data, clinical data and gene annotation files for The Cancer Genome Atlas (TCGA) BLCA cohort were extracted from the University of California, Santa Cruz (UCSC) Xena Browser. The BLCA datasets GSE31684 and GSE32894 from the Gene Expression Omnibus (GEO) database were extracted for external validation. Immune-related genes were extracted from InnateDB. Significant differentially expressed genes (DEGs) were identified using the R package “limma,” and Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for the DEGs were performed using R package “clusterProfiler.” Least absolute shrinkage and selection operator (LASSO) regression analysis were used to construct the signature model. The infiltration level of each immune cell type was estimated using the single-sample gene set enrichment analysis (ssGSEA) algorithm. The performance of the model was evaluated with receiver operating characteristic (ROC) curves and calibration curves.Results: In total, 1,040 immune-related DEGs were identified, and eight signature genes were selected to construct a model using LASSO regression analysis. The risk score of BLCA patients based on the signature model was negatively correlated with OS and the immunotherapy response. The ROC curve for OS revealed that the model had good accuracy. The calibration curve showed good agreement between the predictions and actual observations.Conclusions: Herein, we constructed an immune-related eight-gene signature that could be a potential biomarker to predict the immunotherapy response and prognosis of BLCA patients.


2017 ◽  
Vol 16 (6) ◽  
pp. 8709-8720 ◽  
Author(s):  
Liang Chen ◽  
Lushun Yuan ◽  
Gang Wang ◽  
Rui Cao ◽  
Jianping Peng ◽  
...  

2020 ◽  
Vol 8 (21) ◽  
pp. 1380-1380
Author(s):  
Ying-Rui Shi ◽  
Kun Xiong ◽  
Xu Ye ◽  
Pei Yang ◽  
Zheng Wu ◽  
...  

2020 ◽  
Author(s):  
Dali Han ◽  
Bin Xiong ◽  
Xiangxiang Zhang ◽  
Chaohu Chen ◽  
Zhiqiang Yao ◽  
...  

Abstract Background Bladder cancer is the most common malignancy in urinary system, but the therapeutic targets remain elusive. This study aims to reveal the relationship between AMIGO2 and proliferation, migration, drug-resistance and tumorigenicity of bladder cancer, and explore the potential molecular mechanisms. Methods The expression of AMIGO2 in human bladder cancer tissues is measured by qRT-PCR and immunohistochemistry (IHC). Stable AMIGO2 knockdown cell lines T24 and 5637 were established by lentivirus transfection. Cell viability assay (CCK-8 assay) was used to determine cell proliferation, flow cytometry analysis was utilized to detect cell cycle, and wound healing assay was proceeded to test migration ability of bladder cancer cells. Chemosensitivity to cisplatin was measured by CCK-8 assay. Xenograft mouse model was established for investigating the effect of AMIGO2 on tumor formation in vivo. The RNA Sequencing technology was used to explore differentially expressed genes (DEGs) between knockdown group and negative control group of T24. Bioinformatics analysis upon the results of RNA-Seq was proceeded to understand underlying mechanisms. Results AMIGO2 was upregulated in bladder cancer cells and tissues. Inhibited expression of AMIGO2 suppresses cell proliferation and migration, which might be mediated by cell cycle arrest in G1 phase. AMIGO2 could reduce chemoresistance to cisplatin in bladder cancer cells. Low AMIGO2 expression inhibited tumorigenicity of T24 in nude mice. 917 DEGs were identified by RNA-Sequencing technology and bioinformatics analysis. The DEGs were mainly enriched in cell-cell adhesion, ATP-binding cassette transporters (ABC transporters), PPAR signaling pathway and some other pathways. Among ten hub genes, four of them might be associated with the prognosis of bladder cancer patients. Conclusion AMIGO2 is overexpressed in bladder cancer cells and tissues and serves as an oncogene in bladder cancer. It also reduces chemoresistance to cisplatin. The process might be regulated by particular pathways including ABC transporters and PPAR signaling pathway. Four hub genes might be associated with prognosis of bladder cancer patients.


2021 ◽  
Author(s):  
Yiheng Du ◽  
Jin Cao ◽  
Xiang Jiang ◽  
Xiaowei Cai ◽  
Bo Wang ◽  
...  

Abstract Background Bladder cancer (BLCA) is the most common genitourinary tumor but lacks specific diagnostic biomarkers. Recent years have seen significant advances in the use and approval of immune checkpoint blockade (ICB) therapy to manage bladder cancer at advanced stages when platinum-based therapy has failed. The tumor microenvironment (TME) in bladder cancer is an essential player in patient's responsiveness to ICB therapy. Therefore, this manuscript explored the TME and identified CXCL12, a specific marker for inflammatory cancer associated fibroblasts(iCAFs), as potential molecular markers and therapeutic targets for bladder cancer. Methods We examined the gene expression profiles in the TCGA and GEO datasets to reveal the potential association of CXCL12 with the carcinogenesis and prognosis of bladder cancer. Methylation analysis of CXCL12 was performed using the UALCAN and MethSurv databases. The MCP-COUNTER, ESTIMATE, and TIDE algorithms were applied to estimate the TME components and predict immunotherapy responsiveness. An iCAFs signature was constructed using the ssGSEA algorithm. Bioinformatics analysis results were validated through immunohistochemistry of clinical samples. IMvigor210 cohort was used to validate bioinformatic predictions of therapeutic responsiveness to immune checkpoint inhibitors Results Our analysis revealed the potential association between aberrant promoter methylation of CXCL12 and bladder cancer carcinogenesis. CpG sites methylation of the CXCL12 gene body was associated with bladder cancer prognosis. Moreover, the expression level of CXCL12 exhibited a significant correlation with patients' pathological features and prognosis. Through gene enrichment analysis, CXCL12 was demonstrated to be associated with immune modulation and tumor microenvironment remodeling. The MCP-COUNTER and ESTIMATE algorithms verified significant correlations between CXCL12 and TME components, particularly CAFs, macrophages, and T cells. The TIDE algorithm provided evidence that T-cell clearance and dysfunction were more pronounced in bladder cancers characterized by high CXCL12 expression and high iCAFs scores, contributing to inferior responsiveness to ICB therapy. Patients who expressed high CXCL12 levels and had high iCAFs scores were likely to have less frequent FGFR3 mutation and a stromal-rich molecular subtype. Immunohistochemistry revealed that the close association of CXCL12 with iCAFs in bladder cancer potentially influenced the intratumoral infiltration of CD8 + T cells. CXCL12 expression in MIBC was increased significantly in NMIBC, which supports the bioinformatics analysis results. The IMvigor210 cohort confirmed the iCAFs score to be significantly associated with the responsiveness to immune checkpoint blockade therapy. Conclusions This work explores carcinogenesis and cancer-promoting roles of CXCL12 in bladder cancer. As a specific marker gene of iCAFs, CXCL12 potentially promotes bladder cancer progression by regulating the tumor microenvironment. Further exploration of the association between CXCL12 and iCAFs may unravel potential therapeutic targets for bladder precision medicine and improve the responsiveness of immune checkpoint blockade therapy.


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