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Liu C, Fang J, Kang W, Yang Y, Yu C, Chen H, Zhang Y, Ouyang H. Identification of novel potential homologous repair deficiency-associated genes in pancreatic adenocarcinoma via WGCNA coexpression network analysis and machine learning. Cell Cycle 2023; 22:2392-2408. [PMID: 38124367 PMCID: PMC10802216 DOI: 10.1080/15384101.2023.2293594] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 12/05/2023] [Indexed: 12/23/2023] Open
Abstract
Homologous repair deficiency (HRD) impedes double-strand break repair, which is a common driver of carcinogenesis. Positive HRD status can be used as theranostic markers of response to platinum- and PARP inhibitor-based chemotherapies. Here, we aimed to fully investigate the therapeutic and prognostic potential of HRD in pancreatic adenocarcinoma (PAAD) and identify effective biomarkers related to HRD using comprehensive bioinformatics analysis. The HRD score was defined as the unweighted sum of the LOH, TAI, and LST scores, and it was obtained based on the previous literature. To characterize PAAD immune infiltration subtypes, the "ConsensusClusterPlus" package in R was used to conduct unsupervised clustering. A WGCNA was conducted to elucidate the gene coexpression modules and hub genes in the HRD-related gene module of PAAD. The functional enrichment study was performed using Metascape. LASSO analysis was performed using the "glmnet" package in R, while the random forest algorithm was realized using the "randomForest" package in R. The prognostic variables were evaluated using univariate Cox analysis. The prognostic risk model was built using the LASSO approach. ROC curve and KM survival analyses were performed to assess the prognostic potential of the risk model. The half-maximal inhibitory concentration (IC50) of the PARP inhibitors was estimated using the "pRRophetic" package in R and the Genomics of Drug Sensitivity in Cancer database. The "rms" package in R was used to create the nomogram. A high HRD score indicated a poor prognosis and an advanced clinical process in PAAD patients. PAAD tumors with high HRD levels revealed significant T helper lymphocyte depletion, upregulated levels of cancer stem cells, and increased sensitivity to rucaparib, Olaparib, and veliparib. Using WGCNA, 11 coexpression modules were obtained. The red module and 122 hub genes were identified as the most correlated with HRD in PAAD. Functional enrichment analysis revealed that the 122 hub genes were mainly concentrated in cell cycle pathways. One novel HRD-related gene signature consisting of CKS1B, HJURP, and TPX2 were screened via LASSO analysis and a random forest algorithm, and they were validated using independent validation sets. No direct association between HRD and CKS1B, HJURP, or TPX2 has not been reported in the literature so far. Thus, these findings indicated that CKS1B, HJURP, and TPX2 have potential as diagnostic and prognostic biomarkers for PAAD. We constructed a novel HRD-related prognostic model that provides new insights into PAAD prognosis and immunotherapy. Based on bioinformatics analysis, we comprehensively explored the therapeutic and prognostic potential of HRD in PAAD. One novel HRD-related gene signature consisting of CKS1B, HJURP, and TPX2 were identified through the combination of WGCNA, LASSO analysis and a random forest algorithm. A novel HRD-related risk model that can predict clinical prognosis and immunotherapeutic response in PAAD patients was constructed.
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Affiliation(s)
- Chun Liu
- Department of General surgery, The People’s Hospital of Chizhou, Chizhou, Anhui Province, China
| | - Jingyun Fang
- Department of Nursing, The People’s Hospital of Chizhou, Chizhou, Anhui Province, China
| | - Weibiao Kang
- Department of General surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Yang Yang
- Department of General surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Changjun Yu
- Department of General surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Hao Chen
- Department of Emergency Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Yongwei Zhang
- Department of general surgery, Anqing First People’s Hospital, Anqing, Anhui Province, China
| | - Huan Ouyang
- Department of General surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
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2
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Wang Z, Wang T, Wu G, Zhu L, Zhang J. Clinical Significance and Tumor Microenvironment Characterization of a Novel Immune-Related Gene Signature in Bladder Cancer. J Clin Med 2023; 12:jcm12051892. [PMID: 36902678 PMCID: PMC10003605 DOI: 10.3390/jcm12051892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Revised: 02/20/2023] [Accepted: 02/23/2023] [Indexed: 03/04/2023] Open
Abstract
Cancer immunotherapy plays a crucial role in bladder cancer (BC) progression. Increasing evidence has elucidated the clinicopathologic significance of the tumor microenvironment (TME) in predicting outcomes and therapeutic efficacy. This study sought to establish a comprehensive analysis of the immune-gene signature combined with TME to assist in BC prognosis. We selected sixteen immune-related genes (IRGs) after a weighted gene co-expression network and survival analysis. Enrichment analysis revealed that these IRGs were actively involved in Mitophagy and Renin secretion pathways. After multivariable COX analysis, the IRGPI comprising NCAM1, CNTN1, PTGIS, ADRB3, and ANLN was established to predict the overall survival of BC, which was validated in both TCGA and GSE13507 cohorts. In addition, a TME gene signature was developed for molecular and prognosis subtyping with unsupervised clustering, followed by a panoramic landscape characterization of BC. In summary, the IRGPI model developed in our study provided a valuable tool with an improved prognosis for BC.
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Affiliation(s)
- Zhaohui Wang
- Department of Gynecology and Obstetrics, Xiangya Hospital, Central South University, Changsha 410008, China
- Advanced Biological Screening Facility, BioQuant, Heidelberg University, 69120 Heidelberg, Germany
- Department of Surgery, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany
| | - Tao Wang
- Department of Urology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200080, China
| | - Gangfeng Wu
- Department of Urology, Shaoxing People’s Hospital, Shaoxing 312000, China
| | - Lei Zhu
- Department of Surgery, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany
- Junior Clinical Cooperation Unit Translational Surgical Oncology (A430), German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Correspondence: (L.Z.); (J.Z.)
| | - Jian Zhang
- Department of Urology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200080, China
- Correspondence: (L.Z.); (J.Z.)
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3
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Huang C, Li Y, Ling Q, Wei C, Fang B, Mao X, Yang R, Zhang L, Huang S, Cheng J, Liao N, Wang F, Mo L, Mo Z, Li L. Establishment of a risk score model for bladder urothelial carcinoma based on energy metabolism-related genes and their relationships with immune infiltration. FEBS Open Bio 2023; 13:736-750. [PMID: 36814419 PMCID: PMC10068335 DOI: 10.1002/2211-5463.13580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 01/28/2023] [Accepted: 02/21/2023] [Indexed: 02/24/2023] Open
Abstract
Bladder urothelial carcinoma (BLCA) is a common malignant tumor of the human urinary system, and a large proportion of BLCA patients have a poor prognosis. Therefore, there is an urgent need to find more efficient and sensitive biomarkers for the prognosis of BLCA patients in clinical practice. RNA sequencing (RNA-seq) data and clinical information were obtained from The Cancer Genome Atlas, and 584 energy metabolism-related genes (EMRGs) were obtained from the Reactome pathway database. Cox regression analysis and least absolute shrinkage and selection operator analysis were applied to assess prognostic genes and build a risk score model. The estimate and cibersort algorithms were used to explore the immune microenvironment, immune infiltration, and checkpoints in BLCA patients. Furthermore, we used the Human Protein Atlas database and our single-cell RNA-seq datasets of BLCA patients to verify the expression of 13 EMRGs at the protein and single-cell levels. We constructed a risk score model; the area under the curve of the model at 5 years was 0.792. The risk score was significantly correlated with the immune markers M0 macrophages, M2 macrophages, CD8 T cells, follicular helper T cells, regulatory T cells, and dendritic activating cells. Furthermore, eight immune checkpoint genes were significantly upregulated in the high-risk group. The risk score model can accurately predict the prognosis of BLCA patients and has clinical application value. In addition, according to the differences in immune infiltration and checkpoints, BLCA patients with the most significant benefit can be selected for immune checkpoint inhibitor therapy.
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Affiliation(s)
- Caihong Huang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yexin Li
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Qiang Ling
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,School of Public Health, Guangxi Medical University, Nanning, China
| | - Chunmeng Wei
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Bo Fang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China
| | - Xingning Mao
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China
| | - Rirong Yang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China
| | - LuLu Zhang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China
| | - Shengzhu Huang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jiwen Cheng
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,School of Public Health, Guangxi Medical University, Nanning, China
| | - Naikai Liao
- School of Public Health, Guangxi Medical University, Nanning, China
| | - Fubo Wang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,School of Public Health, Guangxi Medical University, Nanning, China
| | - Linjian Mo
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Zengnan Mo
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China.,School of Public Health, Guangxi Medical University, Nanning, China
| | - Longman Li
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China.,School of Public Health, Guangxi Medical University, Nanning, China
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4
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Liu Y, Han YS, Wang JF, Pang ZQ, Wang JS, Zhang L, He JX, Shen LK, Ji B, Ding BC, Ren MH. A new immune-related gene signature predicts the prognosis and immune escape of bladder cancer. Cancer Biomark 2023; 38:567-581. [PMID: 38073378 DOI: 10.3233/cbm-230190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2023]
Abstract
BACKGROUND The biological roles of immune-related genes (IRGs) in bladder cancer (BC) need to be further elucidated. OBJECTIVE To elucidate the predictive value of IRGs for prognosis and immune escape in BC. METHODS We comprehensively analyzed the transcriptomic and clinical information of 430 cases, including 19 normal and 411 BC patients from the TCGA database, and verified 165 BC cases in the GSE13507 dataset. The risk model was constructed based on IRGs by applying LASSO Cox regression and exploring the relationship between the risk score and prognosis, gene mutations, and immune escape in BC patients. RESULTS We identified 4 survival-related genes (PSMC1, RAC3, ROBO2 and ITGB3) among 6,196 IRGs in both the TCGA and GES13507 datasets,, which were used to establish a gene risk model by applying LASSO Cox regression. The results showed that the high-risk (HR) group was closely associated with poor survival or advanced pathological stage of BC. Furthermore, the risk score was found to be an independent risk factor for prognosis of BC patients. In addition, high-risk individuals showed a greater prevalence of TP53 mutations lower CD8+ T-cell and NK cell infiltration, higher Treg cell infiltration, higher expression of PD-L1, and higher immune exclusion scores than those in the low-risk (LR) group. Finally, the experimental verification shows that the model construction gene, especially PMSC1, plays an important role in the growth and metastasis of bladder cancer. CONCLUSIONS These evidences revealed the vital role of IRGs in predicting prognosis, TP53 mutation and immune escape in BC patients.
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5
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Guo Y, Dong J, Ji T, Li X, Rong S, Guan H. A risk score for the prognosis prediction of the muscle-invasive bladder cancer patients who received gemcitabine plus cisplatin chemotherapy. Aging (Albany NY) 2022; 14:9715-9729. [PMID: 36470668 PMCID: PMC9792215 DOI: 10.18632/aging.204424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 11/21/2022] [Indexed: 12/12/2022]
Abstract
To develop an individualized gene-based risk score to predict the prognosis of muscle-invasive bladder cancer (MIBC) patients who received GC regimens. We downloaded transcriptome profiling data and clinical information from the Cancer Genome Atlas (TCGA) database. We identified 1854 survival-associated genes and then constructed the risk score based on six special genes selected from the survival-associated genes. We divided patients into high-risk and low-risk groups according to the median risk score. High-risk patients have significantly poorer overall survival than low-risk patients (log-rank test chi-square = 38.08, p = 7e-10, C-index = 0.785, se = 0.032). The risk score was evaluated by Kaplan-Meier survival curve, time-dependent ROC curves, and C-index. Multivariate Cox regression and nomogram suggested that the risk score was an independent prognostic indicator. Gene set enrichment analysis indicated that the survival-associated genes were significantly enriched in immune-related terms. Among six special genes, CHPF2, TRAV26-2, and BTF3P12 were found to be immune-related genes. In conclusion, our risk score provided an indicator to predict the prognosis of MIBC patients who received GC regimens and potential immunotherapeutic targets for MIBC.
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Affiliation(s)
- Yupeng Guo
- Department of Epidemiology and Statistics, School of Public Health of Mudanjiang Medical University, Mudanjiang, Heilongjiang Province 157011, China
| | - Jing Dong
- Department of Epidemiology and Statistics, School of Public Health of Mudanjiang Medical University, Mudanjiang, Heilongjiang Province 157011, China
| | - Tao Ji
- Department of Epidemiology and Statistics, School of Public Health of Mudanjiang Medical University, Mudanjiang, Heilongjiang Province 157011, China
| | - Xiaoxia Li
- Department of Epidemiology and Statistics, School of Public Health of Mudanjiang Medical University, Mudanjiang, Heilongjiang Province 157011, China
| | - Shengzhong Rong
- Department of Epidemiology and Statistics, School of Public Health of Mudanjiang Medical University, Mudanjiang, Heilongjiang Province 157011, China
| | - Hongjun Guan
- Department of Epidemiology and Statistics, School of Public Health of Mudanjiang Medical University, Mudanjiang, Heilongjiang Province 157011, China
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6
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Shen C, Li Z, Zhang Y, Zhang Z, Wu Z, Da L, Yang S, Wang Z, Zhang Y, Qie Y, Zhao G, Lin Y, Huang S, Zhou M, Hu H. Identification of a dysregulated CircRNA-associated gene signature for predicting prognosis, immune landscape, and drug candidates in bladder cancer. Front Oncol 2022; 12:1018285. [PMID: 36300085 PMCID: PMC9589509 DOI: 10.3389/fonc.2022.1018285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
Increasing evidences have demonstrated that circular RNA (circRNAs) plays a an essential regulatory role in initiation, progression and immunotherapy resistance of various cancers. However, circRNAs have rarely been studied in bladder cancer (BCa). The purpose of this research is to explore new circRNAs and their potential mechanisms in BCa. A novel ceRNA-regulated network, including 87 differentially expressed circRNAs (DE-circRNAs), 126 DE-miRNAs, and 217 DE-mRNAs was constructed to better understanding the biological processes using Cytoscape 3.7.1 based on our previously high-throughput circRNA sequencing and five GEO datasets. Subsequently, five randomly selected circRNAs (upregulated circ_0001681; downregulated circ_0000643, circ_0001798, circ_0006117 and circ_0067900) in 20 pairs of BCa and paracancerous tissues were confirmed using qRT-PCR. Functional analysis results determined that 772 GO functions and 32 KEGG pathways were enriched in the ceRNA network. Ten genes (PFKFB4, EDNRA, GSN, GAS1, PAPPA, DTL, TGFBI, PRSS8, RGS1 and TCF4) were selected for signature construction among the ceRNA network. The Human Protein Atlas (HPA) expression of these genes were consistent with the above sequencing data. Notably, the model was validated in multiple external datasets (GSE13507, GSE31684, GSE48075, IMvigor210 and GSE32894). The immune-infiltration was evaluated by 7 published algorithms (i.e., TIMER, CIBERSORT, CIBERSORT-ABS, QUANTISEQ, MCPCOUNTER, XCELL and EPIC). Next, Correlations between riskscore or risk groups and clinicopathological data, overall survival, recognized immunoregulatory cells or common chemotherapeutic agents of BCa patients were performed using wilcox rank test, chi-square test, cox regression and spearman’s correlation analysis; and, these results are significant. According to R package “GSVA” and “clusterProfiler”, the most significantly enriched HALLMARK and KEGG pathway was separately the ‘Epithelial Mesenchymal Transition’ and ‘Ecm Receptor Interaction’ in the high- vs. low-risk group. Additionally, the functional experiments in vitro also revealed that the overexpression of has_circ_0067900 significantly impaired the proliferation, migration, and invasion capacities of BCa cells. Collectively, the results of the current study provide a novel landscape of circRNA-associated ceRNA-regulated network in BCa. The ceRNA-associated gene model which was constructed presented a high predictive performance for the prognosis, immunotherapeutic responsiveness, and chemotherapeutic sensitivity of BCa. And, has_circ_0067900 was originally proposed as tumor suppressor for patients with BCa.
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Affiliation(s)
- Chong Shen
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Zhi Li
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Yinglang Zhang
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Zhe Zhang
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Zhouliang Wu
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - La Da
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Shaobo Yang
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Zejin Wang
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Yu Zhang
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Yunkai Qie
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Gangjian Zhao
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Yuda Lin
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Shiwang Huang
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Mingli Zhou
- Department of Neuromuscular Diseases, Third Hospital of Hebei Medical University, Shijiazhuang, China
| | - Hailong Hu
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
- *Correspondence: Hailong Hu,
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7
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Jin K, He M, Chen B, Zhou X, Zhang C, Zhang Z, Hu D, Jiang Z, Wei Q, Qiu S, Yang L. A single-sample mRNA molecular classification of bladder cancer predicting prognosis and response to immunotherapy. Transl Androl Urol 2022; 11:943-958. [PMID: 35958899 PMCID: PMC9360513 DOI: 10.21037/tau-21-887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 05/18/2022] [Indexed: 11/12/2022] Open
Abstract
Background As an immunogenic cancer, crosstalk between cancer cells and immune cells has been gradually recognized in bladder cancer (BC). Several studies have emphasized the clinical significance of the molecular stratification of BC without highlighting the role of the immune microenvironment. Although immunotherapy acted as a prospective treatment, more precise molecular stratification should be established to select those sensitive to immunotherapy. Methods To select specific immune genes forming subtypes indicating disparate prognoses, we performed bioinformatic analysis using BC transcriptomic profiles from six published datasets, with 408 BC samples in The Cancer Genome Atlas (TCGA) database and 295 individuals in International Cancer Genome Consortium (ICGC) database. Survival analyses were conducted using Kaplan-Meier curves, while Kruskal-Wallis tests were applied to test the differences among groups. Except for unsupervised clustering based on the differential expression of genes, we additionally performed binomial logistic regression, focusing on the mRNA level of a single sample. Results Unsupervised clustering showed that 4 clusters captured the best segmentation. After validation with survival data and simplification using binomial logistic regression, we found that cluster B and cluster D showed worse survival outcomes (P=0.012). Considering the similar survival outcomes of these two clusters, we recombined and performed another survival analysis, which also showed significant survival differences (P=0.0041). Bonding with clinical data, a greater proportion of risk factors were assigned to the worse prognosis subtype, especially showing higher grades in the subtype (P<0.001). In addition, immune cell infiltration, single nucleotide polymorphism (SNP) and copy number variation (CNV) all showed differences between clusters, indicating changes in the immune microenvironment and mutation burden. Through phenotypical analysis, we found metabolism and proliferation phenotypes associated with the immune clusters and mutually exclusive in BC, of which proliferation contributed to worse outcomes. Using the tumor immune dysfunction and exclusion (TIDE) score, a worse immunotherapy benefit was predicted in clusters B&D, defined as the worse prognosis subtype. Conclusions With this novel clustering criterion based on immune-related genes, we provide a better understanding of the immune microenvironment, further guiding the use of immunotherapy.
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Affiliation(s)
- Kun Jin
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Mingjing He
- Department of Urology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Bo Chen
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Xianghong Zhou
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Chichen Zhang
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Zilong Zhang
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Dan Hu
- Department of Clinical Research Management, West China Hospital, Sichuan University, Chengdu, China
| | - Zhongyuan Jiang
- Department of Clinical Research Management, West China Hospital, Sichuan University, Chengdu, China
| | - Qiang Wei
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Shi Qiu
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China.,Center of Biomedical Big Data, West China Hospital, Sichuan University, Chengdu, China
| | - Lu Yang
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
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8
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Jiang L, Chen S, Pan Q, Zheng J, He J, Sun J, Han Y, Yang J, Zhang N, Fu G, Gao F. The feasibility of proteomics sequencing based immune-related prognostic signature for predicting clinical outcomes of bladder cancer patients. BMC Cancer 2022; 22:676. [PMID: 35725413 PMCID: PMC9210750 DOI: 10.1186/s12885-022-09783-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 06/15/2022] [Indexed: 12/02/2022] Open
Abstract
Background Bladder cancer (BCa) shows its potential immunogenity in current immune-checkpoint inhibitor related immunotherapies. However, its therapeutic effects are improvable and could be affected by tumor immune microenvironment. Hence it is interesting to find some more prognostic indicators for BCa patients concerning immunotherapies. Methods In the present study, we retrospect 129 muscle-invasive BCa (MIBC) patients with radical cystectomy in Shanghai General Hospital during 2007 to 2018. Based on the results of proteomics sequencing from 9 pairs of MIBC tissue from Shanghai General Hospital, we focused on 13 immune-related differential expression proteins and their related genes. An immune-related prognostic signature (IRPS) was constructed according to Cancer Genome Atlas (TCGA) dataset. The IRPS was verified in ArrayExpress (E-MTAB-4321) cohort and Shanghai General Hospital (General) cohort, separately. A total of 1010 BCa patients were involved in the study, including 405 BCa patients in TCGA cohort, 476 BCa patients in E-MTAB-4321 cohort and 129 MIBC patients in General cohort. Result It can be indicated that high IRPS score was related to poor 5-year overall survival and disease-free survival. The IRPS score was also evaluated its immune infiltration. We found that the IRPS score was adversely associated with GZMB, IFN-γ, PD-1, PD-L1. Additionally, higher IRPS score was significantly associated with more M2 macrophage and resting mast cell infiltration. Conclusion The study revealed a novel BCa prognostic signature based on IRPS score, which may be useful for BCa immunotherapies. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-022-09783-y.
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Affiliation(s)
- Liren Jiang
- Pathology Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100, Hai Ning Road, Shanghai, 200080, China
| | - Siteng Chen
- Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qi Pan
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Zheng
- Pathology Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100, Hai Ning Road, Shanghai, 200080, China
| | - Jin He
- Pathology Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100, Hai Ning Road, Shanghai, 200080, China
| | - Juanjuan Sun
- Pathology Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100, Hai Ning Road, Shanghai, 200080, China
| | - Yaqin Han
- Pathology Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100, Hai Ning Road, Shanghai, 200080, China
| | - Jiji Yang
- Pathology Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100, Hai Ning Road, Shanghai, 200080, China
| | - Ning Zhang
- Department of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin 2nd Road, Shanghai, 200020, China.
| | - Guohui Fu
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Institutes of Medical Sciences, Shanghai Jiao Tong University School of Medicine, Shanghai, China. .,Shanghai Key Laboratory of Gastric Neoplasms, Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 280, South Chong-Qing Road, Shanghai, 200025, China.
| | - Feng Gao
- Pathology Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100, Hai Ning Road, Shanghai, 200080, China.
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9
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Three Prognostic Biomarkers Correlate with Immune Checkpoint Blockade Response in Bladder Urothelial Carcinoma. Int J Genomics 2022; 2022:3342666. [PMID: 35664691 PMCID: PMC9162857 DOI: 10.1155/2022/3342666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/09/2022] [Indexed: 11/17/2022] Open
Abstract
Aim We aim to develop a signature that could accurately predict prognosis and evaluate the response to immune checkpoint blockade (ICB) in bladder urothelial carcinoma (BLCA). Methods Based on comprehensive analysis of public database, we identified prognosis-related hub genes and investigated their predictive values for the ICB response in BLCA. Results Among 69 common DEGs, three genes (AURKA, BIRC5, and CKS1B) were associated with poor prognosis, and which were related to histological subtypes, TP53 mutation status, and the C2 (IFN-gamma dominant) subtype. Three genes and their related risk model can effectively predict the response of immunotherapy. Their related drugs were identified through analysis of drug bank database. Conclusions Three genes could predict prognosis and evaluate the response to ICB in BLCA.
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10
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Jiang Y, Zeng Z, Xiong S, Jiang M, Huang G, Zhang C, Xi X. New Prognostic Gene Signature and Immune Escape Mechanisms of Bladder Cancer. Front Cell Dev Biol 2022; 10:775417. [PMID: 35646934 PMCID: PMC9133907 DOI: 10.3389/fcell.2022.775417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 04/14/2022] [Indexed: 11/13/2022] Open
Abstract
Background: The immune microenvironment profoundly affects tumor prognosis and therapy. The present study aimed to reveal potential immune escape mechanisms and construct a novel prognostic signature via systematic bioinformatic analysis of the bladder cancer (BLCA) immune microenvironment. Patients and Methods: The transcriptomic data and clinicopathological information for patients with BLCA were obtained from The Cancer Genome Atlas (TCGA). Consensus clustering analysis based on the CIBERSORT and ESTIMATE algorithms was performed with patients with BLCA, which divided them into two clusters. Subsequently, the differentially expressed genes (DEGs) in the two were subjected to univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses to identify prognostic genes, which were used to construct a prognostic model. The predictive performance of the model was verified by receiver operating characteristic (ROC) and Kaplan–Meier (K-M) analyses. In addition, we analyzed the differentially altered immune cells, mutation burden, neoantigen load, and subclonal genome fraction between the two clusters to reveal the immune escape mechanism. Results: Based on the ESTIMATE and clustering analyses, patients with BLCA were classified into two heterogeneous clusters: ImmuneScoreH and ImmuneScoreL. Univariate Cox and LASSO regression analyses identified CD96 (HR = 0.83) and IBSP (HR = 1.09), which were used to construct a prognostic gene signature with significant predictive accuracy. Regarding potential immune escape mechanisms, ImmuneScoreH and ImmuneScoreL were characterized by inactivation of innate immune cell chemotaxis. In ImmuneScoreL, a low tumor antigen load might contribute to immune escape. ImmuneScoreH featured high expression of immune checkpoint molecules. Conclusion: CD96 and IBSP were considered prognostic factors for BLCA. Innate immune inactivation and a low tumor antigen load may be associated with immune escape mechanisms in both clusters. Our research complements the exploration of the immune microenvironment in BLCA.
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Affiliation(s)
- Yi Jiang
- Department of Urology, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Zhenhao Zeng
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Situ Xiong
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Ming Jiang
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Gaomin Huang
- Department of Urology, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Chiyu Zhang
- Department of Urology, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xiaoqing Xi
- Department of Urology, The Second Affiliated Hospital of Nanchang University, Nanchang, China
- *Correspondence: Xiaoqing Xi,
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11
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Cai HY, Yang HS, Shan SC, Lei YY, Zou JY, Zhu Y, Luo HH. A novel signature based on immune-related gene pairs and clinical features to predict prognosis and treatment effect in "driver gene negative" lung adenocarcinoma. Cancer Med 2022; 11:2259-2270. [PMID: 35246970 PMCID: PMC9160806 DOI: 10.1002/cam4.4577] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 01/06/2022] [Accepted: 01/07/2022] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVE Examining the role of immune-related genes (IRGs) in "driver gene negative" lung adenocarcinoma (LUAD) may provide new ideas for the treatment and study for this LUAD subgroup. We aimed to find the hub immune-related gene pairs can stratify the risk of "driver-gene-negative" LUAD. MATERIALS AND METHODS IRGs were identified according to ImmPort database based on RNA sequencing results of tumors and normal tissues from 46 patients with "driver gene negative" LUAD at The First Affiliated Hospital of Sun Yat-sen University and cyclically singly paired as immune-related gene pairs (IRGPs). Multivariate Cox analysis was used to construct an immune risk model and a prognostic nomogram combining was also been developed. Immune microenvironment landscape described by CIBERSORT and drug sensitivity calculated by pRRophetic algorithm were used to explore possible treatment improvements. RESULTS A novel immune risk model with 5-IRGPs (CD1A|CXCL135, CD1A|S100A7L2, IFNA7|CMTM2, IFNA7|CSF3, CAMP|TFR2) can accurately distinguish patients in the high- and low-risk groups. Risk score act as an independent prognostic factor and is related to clinical stage. There are significant differences in tumor immune microenvironment and PD-1/PD-L1/CTLA-4 expression between groups. The low-risk patient may benefit more from the commonly used chemotherapy regimens such as gemcitabine and paclitaxel. CONCLUSION This study constructed 5-IRGPs as a reliable prognostic tool and may represent genes pairs that are potential rationale for choice of treatment for "driver gene negative" LUAD.
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Affiliation(s)
- He-Yuan Cai
- Department of Thoracic Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Hao-Shuai Yang
- Department of Thoracic Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Shi-Chao Shan
- Department of Thoracic Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yi-Yan Lei
- Department of Thoracic Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jian-Yong Zou
- Department of Thoracic Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ying Zhu
- Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Hong-He Luo
- Department of Thoracic Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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12
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Dyugay IA, Lukyanov DK, Turchaninova MA, Serebrovskaya EO, Bryushkova EA, Zaretsky AR, Khalmurzaev O, Matveev VB, Shugay M, Shelyakin PV, Chudakov DM. Accounting for B-cell Behavior and Sampling Bias Predicts Anti-PD-L1 Response in Bladder Cancer. Cancer Immunol Res 2022; 10:343-353. [PMID: 35013004 PMCID: PMC9381118 DOI: 10.1158/2326-6066.cir-21-0489] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 08/18/2021] [Accepted: 01/06/2022] [Indexed: 01/07/2023]
Abstract
Cancer immunotherapy is predominantly based on T cell-centric approaches. At the same time, the adaptive immune response in the tumor environment also includes clonally produced immunoglobulins and clonal effector/memory B cells that participate in antigen-specific decisions through their interactions with T cells. Here, we investigated the role of infiltrating B cells in bladder cancer via patient dataset analysis of intratumoral immunoglobulin repertoires. We showed that the IgG1/IgA ratio is a prognostic indicator for several subtypes of bladder cancer and for the whole IMVigor210 anti-PD-L1 immunotherapy study cohort. A high IgG1/IgA ratio associated with the prominence of a cytotoxic gene signature, T-cell receptor signaling, and IL21-mediated signaling. Immunoglobulin repertoire analysis indicated that effector B-cell function, rather than clonally produced antibodies, was involved in antitumor responses. From the T-cell side, we normalized a cytotoxic signature against the extent of immune cell infiltration to neutralize the artificial sampling-based variability in immune gene expression. Resulting metrics reflected proportion of cytotoxic cells among tumor-infiltrating immune cells and improved prediction of anti-PD-L1 responses. At the same time, the IgG1/IgA ratio remained an independent prognostic factor. Integration of the B-cell, natural killer cell, and T-cell signatures allowed for the most accurate prediction of anti-PD-L1 therapy responses. On the basis of these findings, we developed a predictor called PRedIctive MolecUlar Signature (PRIMUS), which outperformed PD-L1 expression scores and known gene signatures. Overall, PRIMUS allows for reliable identification of responders among patients with muscle-invasive urothelial carcinoma, including the subcohort with the low-infiltrated "desert" tumor phenotype.
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Affiliation(s)
- Ilya A. Dyugay
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Daniil K. Lukyanov
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Maria A. Turchaninova
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Ekaterina O. Serebrovskaya
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Ekaterina A. Bryushkova
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia.,Molecular Biology Department, Lomonosov Moscow State University, Moscow, Russia
| | - Andrew R. Zaretsky
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Oybek Khalmurzaev
- Department of Urology, Federal State Budgetary Institution “N.N. Blokhin National Medical Research Center of Oncology” of the Ministry of Health of the Russian Federation, Moscow, Russia
| | - Vsevolod B. Matveev
- Department of Urology, Federal State Budgetary Institution “N.N. Blokhin National Medical Research Center of Oncology” of the Ministry of Health of the Russian Federation, Moscow, Russia
| | - Mikhail Shugay
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Pavel V. Shelyakin
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Dmitriy M. Chudakov
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia.,Corresponding Author: Dmitriy M. Chudakov, Genomics of Adaptive Immunity, IBCH RAS, Miklukho-Maklaya, 16/10, Moscow 117997, Russia. Phone: 7 (495) 335-01-00; E-mail:
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13
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Yuan K, Zeng R, Deng P, Zhang A, Liu H, Wang N, Tang Y, Yin Z, Liu H. Identification and Verification of Immune-Related Genes Prognostic Signature Based on ssGSEA for Adrenocortical Carcinoma (ACC). Int J Gen Med 2022; 15:1471-1483. [PMID: 35210821 PMCID: PMC8857983 DOI: 10.2147/ijgm.s345123] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 01/26/2022] [Indexed: 01/07/2023] Open
Abstract
Purpose Adrenocortical carcinoma (ACC) is an endocrine malignant tumor with poor prognosis. The study aimed to construct ACC immune-related gene prognostic signature and verify the efficacy of prognostic signature. Methods ACC RNA-seq data and clinical information are downloaded from TCGA databases and GEO databases. We used single sample gene set enrichment analysis (ssGSEA) to assess immune cell infiltration in ACC patients and ACC patients were divided into high- and low-immune cell infiltration clusters. The validity of ssGSEA grouping was verified using the ESTIMATE algorithm. A total of 275 differentially expressed immune-related genes (IRGs) were obtained from the intersection of IRGs and differentially expressed genes (DEGs) in high and low immune cell infiltration clusters. LASSO analysis was used to identify 13 IRGs that regulate the prognosis of ACC patients through immune infiltration. Kaplan–Meier analysis, ROC curve, univariate and multivariate Cox regression further confirmed that these 13 immune-related gene signatures were innovative and significant prognostic factors, which were independent of clinical features. Finally, ACC prognostic nomogram was constructed, ROC curve and calibration curve were drawn to evaluate the accuracy of the prognostic nomogram. Results LASSO regression analysis was used to screen out ACC survival-related genes. Univariate and multivariate Cox proportional risk regression models were used to analyze and construct the ACC prognosis nomogram. The AUC for predicting 1-, 3- and 5-year overall survival rate of ACC patients was 0.799, 0.966 and 0.969, suggesting good prediction accuracy. The calibration curve shows that the predicted results of the prognostic nomogram are in good agreement with the actual situation. Conclusion ssGSEA technique plays an important role in the construction of ACC prognostic model. Based on IRGs associated with survival independently predicted ACC prognosis, we identified thirteen immune-related genes as prognostic signature for ACC.
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Affiliation(s)
- Kaisheng Yuan
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China
| | - Ruiqi Zeng
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China
| | - Pengteng Deng
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China
| | - Aiping Zhang
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China
| | - Huiqian Liu
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China
| | - Ning Wang
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China
| | - Yongxi Tang
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China
| | - Zhikang Yin
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China
| | - Hang Liu
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China
- Correspondence: Hang Liu, Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China, Tel +86-185-8030-9681, Email
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14
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Inal Gültekin G, Timirci Kahraman Ö, Işbilen M, Durmuş S, Çakir T, Yaylim İ, Isbir T. Six potential biomarkers for bladder cancer: key proteins in cell-cycle division and apoptosis pathways. J Egypt Natl Canc Inst 2022; 34:54. [PMID: 36529823 PMCID: PMC9760318 DOI: 10.1186/s43046-022-00153-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 09/23/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The bladder cancer (BC) pathology is caused by both exogenous environmental and endogenous molecular factors. Several genes have been implicated, but the molecular pathogenesis of BC and its subtypes remains debatable. The bioinformatic analysis evaluates high numbers of proteins in a single study, increasing the opportunity to identify possible biomarkers for disorders. METHODS The aim of this study is to identify biomarkers for the identification of BC using several bioinformatic analytical tools and methods. BC and normal samples were compared for each probeset with T test in GSE13507 and GSE37817 datasets, and statistical probesets were verified with GSE52519 and E-MTAB-1940 datasets. Differential gene expression, hierarchical clustering, gene ontology enrichment analysis, and heuristic online phenotype prediction algorithm methods were utilized. Statistically significant proteins were assessed in the Human Protein Atlas database. GSE13507 (6271 probesets) and GSE37817 (3267 probesets) data were significant after the extraction of probesets without gene annotation information. Common probesets in both datasets (2888) were further narrowed by analyzing the first 100 upregulated and downregulated probesets in BC samples. RESULTS Among the total 400 probesets, 68 were significant for both datasets with similar fold-change values (Pearson r: 0.995). Protein-protein interaction networks demonstrated strong interactions between CCNB1, BUB1B, and AURKB. The HPA database revealed similar protein expression levels for CKAP2L, AURKB, APIP, and LGALS3 both for BC and control samples. CONCLUSION This study disclosed six candidate biomarkers for the early diagnosis of BC. It is suggested that these candidate proteins be investigated in a wet lab to identify their functions in BC pathology and possible treatment approaches.
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Affiliation(s)
- Güldal Inal Gültekin
- grid.444283.d0000 0004 0371 5255Department of Physiology, Faculty of Medicine, Istanbul Okan University, Tepeören Campus, Tuzla, Istanbul, Turkey ,grid.9601.e0000 0001 2166 6619Department of Molecular Medicine, Istanbul University, Aziz Sancar Experimental Research Institute, Çapa, Istanbul, Turkey
| | - Özlem Timirci Kahraman
- grid.9601.e0000 0001 2166 6619Department of Molecular Medicine, Istanbul University, Aziz Sancar Experimental Research Institute, Çapa, Istanbul, Turkey
| | - Murat Işbilen
- grid.411117.30000 0004 0369 7552Department of Biostatistics and Bioinformatics, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Saliha Durmuş
- grid.448834.70000 0004 0595 7127Department of Bioengineering, Faculty of Engineering, Gebze Technical University, Kocaeli, Turkey
| | - Tunahan Çakir
- grid.448834.70000 0004 0595 7127Department of Bioengineering, Faculty of Engineering, Gebze Technical University, Kocaeli, Turkey
| | - İlhan Yaylim
- grid.9601.e0000 0001 2166 6619Department of Molecular Medicine, Istanbul University, Aziz Sancar Experimental Research Institute, Çapa, Istanbul, Turkey
| | - Turgay Isbir
- grid.32140.340000 0001 0744 4075Department of Molecular Medicine, Faculty of Medicine, Yeditepe University, Kayışdağı, Istanbul, Turkey
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15
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Lv W, Zhao C, Tan Y, Hu W, Yu H, Zeng N, Zhang Q, Wu Y. Identification of an Aging-Related Gene Signature in Predicting Prognosis and Indicating Tumor Immune Microenvironment in Breast Cancer. Front Oncol 2021; 11:796555. [PMID: 34976839 PMCID: PMC8716799 DOI: 10.3389/fonc.2021.796555] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 11/25/2021] [Indexed: 12/17/2022] Open
Abstract
Breast cancer (BC) is the most commonly diagnosed malignancy accompanied by high invasion and metastasis features. Importantly, emerging studies have supported that aging is a key clue that participates in the immune state and development of BC. Nevertheless, there are no studies concerning the aging-related genes (AGs) in constructing the prognosis signature of BC. Here, to address this issue, we initially performed a systematic investigation of the associations between AGs and BC prognosis and accordingly constructed a prognosis risk model with 10 AGs including PLAU, JUND, IL2RG, PCMT1, PTK2, HSPA8, NFKBIA, GCLC, PIK3CA, and DGAT1 by using the least absolute shrinkage and selection operator (LASSO) regression and Cox regression analysis. Meanwhile, our analysis further confirmed that the nomogram possessed a robust performance signature for predicting prognosis compared to clinical characteristics of BC patients, including age, clinical stage, and TNM staging. Moreover, the risk score was confirmed as an independent prognostic index of BC patients and was potentially correlated with immune scores, estimate score, immune cell infiltration level, tumor microenvironment, immunotherapy effect, and drug sensitivity. Furthermore, in the external clinical sample validation, AGs were expressed differentially in patients from different risk groups, and tumor-associated macrophage markers were elevated in high-risk BC tissues with more co-localization of AGs. In addition, the proliferation, transwell, and wound healing assays also confirmed the promoting effect of DGAT1 in BC cell proliferation and migration. Therefore, this well-established risk model could be used for predicting prognosis and immunotherapy in BC, thus providing a powerful instrument for combating BC.
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Affiliation(s)
| | | | | | | | | | - Ning Zeng
- *Correspondence: Ning Zeng, ; Qi Zhang, ; Yiping Wu,
| | - Qi Zhang
- *Correspondence: Ning Zeng, ; Qi Zhang, ; Yiping Wu,
| | - Yiping Wu
- *Correspondence: Ning Zeng, ; Qi Zhang, ; Yiping Wu,
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16
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Pyatnitskiy MA, Arzumanian VA, Radko SP, Ptitsyn KG, Vakhrushev IV, Poverennaya EV, Ponomarenko EA. Oxford Nanopore MinION Direct RNA-Seq for Systems Biology. BIOLOGY 2021; 10:1131. [PMID: 34827124 PMCID: PMC8615092 DOI: 10.3390/biology10111131] [Citation(s) in RCA: 146] [Impact Index Per Article: 48.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 10/28/2021] [Accepted: 11/02/2021] [Indexed: 12/14/2022]
Abstract
Long-read direct RNA sequencing developed by Oxford Nanopore Technologies (ONT) is quickly gaining popularity for transcriptome studies, while fast turnaround time and low cost make it an attractive instrument for clinical applications. There is a growing interest to utilize transcriptome data to unravel activated biological processes responsible for disease progression and response to therapies. This trend is of particular interest for precision medicine which aims at single-patient analysis. Here we evaluated whether gene abundances measured by MinION direct RNA sequencing are suited to produce robust estimates of pathway activation for single sample scoring methods. We performed multiple RNA-seq analyses for a single sample that originated from the HepG2 cell line, namely five ONT replicates, and three replicates using Illumina NovaSeq. Two pathway scoring methods were employed-ssGSEA and singscore. We estimated the ONT performance in terms of detected protein-coding genes and average pairwise correlation between pathway activation scores using an exhaustive computational scheme for all combinations of replicates. In brief, we found that at least two ONT replicates are required to obtain reproducible pathway scores for both algorithms. We hope that our findings may be of interest to researchers planning their ONT direct RNA-seq experiments.
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Affiliation(s)
- Mikhail A. Pyatnitskiy
- Institute of Biomedical Chemistry, 119121 Moscow, Russia; (V.A.A.); (S.P.R.); (K.G.P.); (I.V.V.); (E.V.P.); (E.A.P.)
- Federal Research and Clinical Center of Physical-Chemical Medicine, 119435 Moscow, Russia
| | - Viktoriia A. Arzumanian
- Institute of Biomedical Chemistry, 119121 Moscow, Russia; (V.A.A.); (S.P.R.); (K.G.P.); (I.V.V.); (E.V.P.); (E.A.P.)
| | - Sergey P. Radko
- Institute of Biomedical Chemistry, 119121 Moscow, Russia; (V.A.A.); (S.P.R.); (K.G.P.); (I.V.V.); (E.V.P.); (E.A.P.)
| | - Konstantin G. Ptitsyn
- Institute of Biomedical Chemistry, 119121 Moscow, Russia; (V.A.A.); (S.P.R.); (K.G.P.); (I.V.V.); (E.V.P.); (E.A.P.)
| | - Igor V. Vakhrushev
- Institute of Biomedical Chemistry, 119121 Moscow, Russia; (V.A.A.); (S.P.R.); (K.G.P.); (I.V.V.); (E.V.P.); (E.A.P.)
| | - Ekaterina V. Poverennaya
- Institute of Biomedical Chemistry, 119121 Moscow, Russia; (V.A.A.); (S.P.R.); (K.G.P.); (I.V.V.); (E.V.P.); (E.A.P.)
| | - Elena A. Ponomarenko
- Institute of Biomedical Chemistry, 119121 Moscow, Russia; (V.A.A.); (S.P.R.); (K.G.P.); (I.V.V.); (E.V.P.); (E.A.P.)
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Li L, Liu W, Tang H, Wang X, Liu X, Yu Z, Gao Y, Wang X, Wei M. Hypoxia-related prognostic model in bladder urothelial reflects immune cell infiltration. Am J Cancer Res 2021; 11:5076-5093. [PMID: 34765313 PMCID: PMC8569353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/09/2021] [Indexed: 06/13/2023] Open
Abstract
Hypoxia is a common feature of tumor microenvironment (TME). This study aims to establish the genetic features related to hypoxia in Bladder urothelial carcinoma (BLCA) and investigate the potential correlation with hypoxia in the TME and immune cells. We established a BLCA outcome model using the hypoxia-related genes from The Cancer Genome Atlas using regression analysis and verified the model using the Gene Expression Omnibus GSE32894 cohort. We measured the effect of each gene in the hypoxia-related risk model using the Human Protein Atlas website. The predictive abilities were compared using the area under the receiver operating characteristic curves. Gene Set Enrichment Analysis was utilized for indicating enrichment pathways. We analyzed immune cell infiltration between risk groups using the CIBERSORT method. The indicators related to immune status between the two groups were also analyzed. The findings indicated that the high-risk group had better outcomes than the low-risk group in the training and validation sets. Each gene in the model affected the survival of BLCA patients. Our hypoxia-related risk model had better performance compared to other hypoxia-related markers (HIF-1α and GLUT-1). The high-risk group was enriched in immune-related pathways. The expression of chemokines and immune cell markers differed significantly between risk groups. Immune checkpoints were more highly expressed in the high-risk group. These findings suggest that the hypoxia-related risk model predicts patients' outcomes and immune status in BLCA risk groups. Our findings may contribute to the treatment of BLCA.
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Affiliation(s)
- Luanfeng Li
- Department of Pharmacology, School of Pharmacy, China Medical UniversityShenyang 110122, Liaoning, China
- Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and EvaluationShenyang 110122, Liaoning, China
- Liaoning Cancer Immune Peptide Drug Engineering Technology Research CenterShenyang 110122, Liaoning, China
- Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors (China Medical University), Ministry of EducationShenyang 110122, Liaoning, China
- Shenyang Kangwei Medical Laboratory Analysis Co. LTDShenyang, Liaoning, China
| | - Wensi Liu
- Department of Pharmacology, School of Pharmacy, China Medical UniversityShenyang 110122, Liaoning, China
- Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and EvaluationShenyang 110122, Liaoning, China
- Liaoning Cancer Immune Peptide Drug Engineering Technology Research CenterShenyang 110122, Liaoning, China
- Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors (China Medical University), Ministry of EducationShenyang 110122, Liaoning, China
| | - Haichao Tang
- Department of Pharmacology, School of Pharmacy, China Medical UniversityShenyang 110122, Liaoning, China
- Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and EvaluationShenyang 110122, Liaoning, China
- Liaoning Cancer Immune Peptide Drug Engineering Technology Research CenterShenyang 110122, Liaoning, China
- Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors (China Medical University), Ministry of EducationShenyang 110122, Liaoning, China
| | - Xiangyi Wang
- Department of Pharmacology, School of Pharmacy, China Medical UniversityShenyang 110122, Liaoning, China
- Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and EvaluationShenyang 110122, Liaoning, China
- Liaoning Cancer Immune Peptide Drug Engineering Technology Research CenterShenyang 110122, Liaoning, China
- Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors (China Medical University), Ministry of EducationShenyang 110122, Liaoning, China
| | - Xinli Liu
- Medical Oncology Department of Gastrointestinal Cancer, Liaoning Cancer Hospital & Institute, Cancer Hospital of China Medical UniversityShenyang 110042, Liaoning, China
| | - Zhaojin Yu
- Department of Pharmacology, School of Pharmacy, China Medical UniversityShenyang 110122, Liaoning, China
- Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and EvaluationShenyang 110122, Liaoning, China
- Liaoning Cancer Immune Peptide Drug Engineering Technology Research CenterShenyang 110122, Liaoning, China
- Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors (China Medical University), Ministry of EducationShenyang 110122, Liaoning, China
| | - Yanan Gao
- Department of Pharmacology, School of Pharmacy, China Medical UniversityShenyang 110122, Liaoning, China
- Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and EvaluationShenyang 110122, Liaoning, China
- Liaoning Cancer Immune Peptide Drug Engineering Technology Research CenterShenyang 110122, Liaoning, China
- Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors (China Medical University), Ministry of EducationShenyang 110122, Liaoning, China
| | - Xiaobin Wang
- Center of Reproductive Medicine, Shengjing Hospital of China Medical UniversityShenyang 117004, Liaoning, China
| | - Minjie Wei
- Department of Pharmacology, School of Pharmacy, China Medical UniversityShenyang 110122, Liaoning, China
- Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and EvaluationShenyang 110122, Liaoning, China
- Liaoning Cancer Immune Peptide Drug Engineering Technology Research CenterShenyang 110122, Liaoning, China
- Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors (China Medical University), Ministry of EducationShenyang 110122, Liaoning, China
- Shenyang Kangwei Medical Laboratory Analysis Co. LTDShenyang, Liaoning, China
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18
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An immune cell infiltration-related gene signature predicts prognosis for bladder cancer. Sci Rep 2021; 11:16679. [PMID: 34404901 PMCID: PMC8370985 DOI: 10.1038/s41598-021-96373-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 08/09/2021] [Indexed: 02/07/2023] Open
Abstract
To explore novel therapeutic targets, develop a gene signature and construct a prognostic nomogram of bladder cancer (BCa). Transcriptome data and clinical traits of BCa were downloaded from UCSC Xena database and Gene Expression Omnibus (GEO) database. We then used the method of Single sample Gene Set Enrichment analysis (ssGSEA) to calculate the infiltration abundances of 24 immune cells in eligible BCa samples. By weighted correlation network analysis (WGCNA), we identified turquoise module with strong and significant association with the infiltration abundance of immune cells which were associated with overall survival of BCa patients. Subsequently, we developed an immune cell infiltration-related gene signature based on the module genes (MGs) and immune-related genes (IRGs) from the Immunology Database and Analysis Portal (ImmPort). Then, we tested the prognostic power and performance of the signature in both discovery and external validation datasets. A nomogram integrated with signature and clinical features were ultimately constructed and tested. Five prognostic immune cell infiltration-related module genes (PIRMGs), namely FPR1, CIITA, KLRC1, TNFRSF6B, and WFIKKN1, were identified and used for gene signature development. And the signature showed independent and stable prognosis predictive power. Ultimately, a nomogram consisting of signature, age and tumor stage was constructed, and it showed good and stable predictive ability on prognosis. Our prognostic signature and nomogram provided prognostic indicators and potential immunotherapeutic targets for BCa. Further researches are needed to verify the clinical effectiveness of this nomogram and these biomarkers.
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19
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Fu Y, Sun S, Bi J, Kong C, Yin L. Construction and analysis of a ceRNA network and patterns of immune infiltration in bladder cancer. Transl Androl Urol 2021; 10:1939-1955. [PMID: 34159075 PMCID: PMC8185653 DOI: 10.21037/tau-20-1250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Background Bladder cancer (BC) is the ninth most common malignant tumor, accounting for an estimate of 549,000 new BC cases and 200,000 BC-related deaths worldwide in 2018. The prognosis of BC has not substantially improved despite significant advances in the diagnosis and treatment of the disease. Methods The RNA sequencing (RNA-seq) data and clinical information of BC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm was used to assess immune infiltration. The survival analyses were performed using the selected components of a ceRNA network and selected immune cell types by least absolute shrinkage and selection operator (LASSO) Cox regression to calculate the risk score. The accuracy of prognosis prediction was determined by receiver operating characteristic (ROC) curves, survival curves, and nomograms. Finally, the correlation analysis was performed to investigate the relationships between the signature components of the ceRNA network and the immune cell signature. Results Two completed survival analyses included selected components of the ceRNA network (ELN, SREBF1, DSC2, TTLL7, DIP2C, SATB1, hsa-miR-20a-5p, and hsa-miR-29c-3p) and selected immune cell types (M0 macrophages, M2 macrophages, resting mast cells, and neutrophils). ROC curves, survival curves (all P values <0.05), nomograms, and calibration curves indicated that the accuracy of the two survival analyses was acceptable. Moreover, the correlations between TTLL7 and resting mast cells (R=0.24, P<0.001), DSC2 and resting mast cells (R=−0.23, P<0.001), ELN and resting mast cells (R=0.44, P<0.001), and hsa-miR-29c-3p and M0 macrophages (R=−0.29, P<0.001) were significant, indicating that interactions of these factors may play significant roles in the prognosis of BC. Conclusions TTLL7, DSC2, ELN, hsa-miR-29c-3p, resting mast cells, and M0 macrophages may play an important role in the development of BC. However, additional studies are needed to confirm this hypothesis.
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Affiliation(s)
- Yang Fu
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Shanshan Sun
- Department of Pharmacy, The First Hospital of China Medical University, Shenyang, China
| | - Jianbin Bi
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Chuize Kong
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Lei Yin
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
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20
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Weng H, Yuan S, Huang Q, Zeng XT, Wang XH. STAT1 is a key gene in a gene regulatory network related to immune phenotypes in bladder cancer: An integrative analysis of multi-omics data. J Cell Mol Med 2021; 25:3258-3271. [PMID: 33608980 PMCID: PMC8034450 DOI: 10.1111/jcmm.16395] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 01/31/2021] [Accepted: 02/04/2021] [Indexed: 12/13/2022] Open
Abstract
The immunophenotype of bladder cancer plays a pivotal role in the prognosis of cancer, but the effect of different epigenetic factors on different immunophenotypes in bladder tumours remains unclear. This study used multi-omics data analysis to provide molecular basis support for different immune phenotypes. Unsupervised cluster analysis revealed distinct subclusters with higher (subcluster B2) or lower cytotoxic immune phenotypes (subcluster A1) related to PD-L1 and IFNG expression. Mutational landscape analyses showed that the mutation level of TP53 in subcluster B1 was highest than other subclusters, and subcluster B1 had a lower frequency of concurrent mutation than subcluster A2. A total of 2364 differentially expressed genes were identified between subclusters A2 and B1, and the main functions of the up-regulated genes in subcluster B1 were enriched in the activation of T cells and other related pathways. We found that STAT1 was a key gene in a gene regulatory network related to immune phenotypes in bladder cancer. Finally, we constructed a prognostic prediction model by LASSO Cox regression which could distinguish high-risk and low-risk cases significantly. In conclusion, the present study addressed a field synopsis between genetic and epigenetic events in immune phenotypes of bladder cancer.
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Affiliation(s)
- Hong Weng
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Wuhan University, Wuhan, China.,Institute of Urology, Wuhan University, Wuhan, China
| | - Shuai Yuan
- Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Wuhan University, Wuhan, China
| | - Qiao Huang
- Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Wuhan University, Wuhan, China
| | - Xian-Tao Zeng
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Wuhan University, Wuhan, China.,Institute of Urology, Wuhan University, Wuhan, China
| | - Xing-Huan Wang
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Wuhan University, Wuhan, China.,Institute of Urology, Wuhan University, Wuhan, China
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21
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Lv Y, Jin P, Chen Z, Zhang P. Characterization of hazard infiltrating immune cells and relative risk genes in bladder urothelial carcinoma. Am J Transl Res 2020; 12:7510-7527. [PMID: 33312386 PMCID: PMC7724318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 10/08/2020] [Indexed: 06/12/2023]
Abstract
OBJECTIVES Bladder urothelial carcinoma (BLCA) is one of the most common malignancies in urinary system. With the development of next-generation sequencing technology, we intended to investigate prognostic immune cells and related signature to predict the prognosis of BLCA and potential therapeutic targets. METHODS We obtained the transcriptome profiles of 573 BLCA patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The fractions of immune cells in each sample was calculated by "CIBERSORT" algorithm. Tumor Infiltrating Immune Cells Scores (TIICS) was accordingly derived and Receiver Operating Characteristic (ROC) curve was conducted to evaluate the predictive efficiency. Moreover, differential analysis was performed between two TIICS groups and hub TIICS-related immune signature was identified. The correlation of key immune genes and immune-infiltrating immune cells was evaluated based on the TIMER database. An Immune Signature Prognostic Index (ISPI) based on these signatures was constructed with superior predictive accuracy. Last, the TIICS model or related immune signature were all validated in an independent cohort from the GSE13507. RESULTS The least absolute shrinkage and selection operator (LASSO) algorithm was utilized to screen the 6 hub tumor-infiltrating immune cells in TCGA cohort, where higher infiltrating levels of M0 Macrophages, M2 Macrophages and Neutrophils were hazard factors, while CD8+ T cells and memory activated CD4+ T cells were protective factors. CONCLUSION Taken together, our study identified several prognostic immune cells and related immune signature in BLCA, shedding insight on the individualized immunotherapy or potential drug targets.
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Affiliation(s)
- Yinxiang Lv
- Department of Oncology, People’s Hospital of Xinchang CountyXinchang, Zhejiang Province, China
| | - Peng Jin
- Organ Transplant Center, Xiangya Hospital, Central South UniversityChangsha, Hunan Province, China
| | - Zheng Chen
- Organ Transplant Center, The Second Affiliated Hospital of Guangzhou Medical UniversityGuangzhou, Guangdong Province, China
| | - Peng Zhang
- Organ Transplant Center, The Second Affiliated Hospital of Guangzhou Medical UniversityGuangzhou, Guangdong Province, China
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