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Li F, Wang H, Wang C, Li Y, Song JY, Fan KY, Li C, Ma QL, Yu Q, Zhang SP. Comprehensive analysis of the role of a four-gene signature based on EMT in the prognosis, immunity, and treatment of lung squamous cell carcinoma. Aging (Albany NY) 2023; 15:6865-6893. [PMID: 37462692 PMCID: PMC10415548 DOI: 10.18632/aging.204878] [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] [Received: 04/03/2023] [Accepted: 06/15/2023] [Indexed: 08/07/2023]
Abstract
Epithelial-mesenchymal transition (EMT), a biological process through which epithelial cells transform into mesenchymal cells, contributes to tumor progression and metastasis. However, a comprehensive analysis of the role of EMT-related genes in Lung squamous cell carcinoma (LUSC) is still lacking. In this study, data were downloaded from available databases, including The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. The association between differentially expressed EMT-related genes (EMT-RDGs) and LUSC prognosis, drug sensitivity, mutation, and immunity was analyzed using bioinformatics methods. In the results, Lasso and univariate Cox regression analyses identified four EMT-RDGs that were differentially expressed, and used to establish a prognostic model capable of distinguishing between high- and low-risk groups. Then, prognostic factors were identified by multivariate Cox regression analysis and used to construct a nomogram. The high-risk group had a significantly poorer prognosis than the low-risk group. The tumor immune environment was significantly different between the two groups, with the low-risk group exhibiting a better response to immunotherapy. In addition, the half-maximal inhibitory concentration prediction indicating that the constructed model could effectively predict sensitivity to chemotherapy. This study provides new reference for further exploration of new clinical therapeutic strategies for LUSC.
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Affiliation(s)
- Feng Li
- Department of Cell Biology, Shanxi Province Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Hui Wang
- Department of Thoracic Surgery, Yangquan First People's Hospital, Yangquan, China
| | - Can Wang
- Shanxi Medical University, School of Management, Taiyuan, China
| | - Yun Li
- The First Clinical Medical College, Shanxi Medical University, Taiyuan, China
| | - Jing-Yan Song
- The First Clinical Medical College, Shanxi Medical University, Taiyuan, China
| | - Ke-Yi Fan
- The First Clinical Medical College, Shanxi Medical University, Taiyuan, China
| | - Chao Li
- Department of Thoracic Surgery, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, China
| | - Quan-Lin Ma
- Department of Cardiothoracic Surgery, Shanxi Fenyang Hospital, Fenyang, China
| | - Qi Yu
- Shanxi Medical University, School of Management, Taiyuan, China
- Institute of Medical Data Science, Shanxi Medical University, Taiyuan, China
| | - Shuang-Ping Zhang
- Department of Thoracic Surgery, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, China
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Mo X, Wang N, He Z, Kang W, Wang L, Han X, Yang L. The sub-molecular characterization identification for cervical cancer. Heliyon 2023; 9:e16873. [PMID: 37484385 PMCID: PMC10360967 DOI: 10.1016/j.heliyon.2023.e16873] [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: 03/09/2023] [Revised: 05/28/2023] [Accepted: 05/31/2023] [Indexed: 07/25/2023] Open
Abstract
Background The efficacy of therapy in cervical cancer (CESC) is blocked by high molecular heterogeneity. Thus, the sub-molecular characterization remains primarily explored for personalizing the treatment of CESC patients. Methods Datasets with 741 CESC patients were obtained from TCGA and GEO databases. The NMF algorithm, random forest algorithm, and multivariate Cox analysis were utilized to construct a classifier for defining the sub-molecular characterization. Then, the biological characteristics, genomic variations, prognosis, and immune landscape in molecular subtypes were explored. The significance of classifier genes was validated by quantitative Real-Time PCR, cell transfection, cell colony formation assay, wound healing assay, cell proliferation assay, and Western blot. Results The CESC patients were classified into two subtypes, and the high classifier-score patients with significant differences in ECM-receptor interaction, PI3K-Akt signaling pathway, and MAPK signaling pathway showed a poorer prognosis in OS (p < 0.001), DFI (p = 0.016), PFI (p < 0.001) and DSS (p < 0.001), and with high the M0 Macrophage and resting Mast cells infiltration and low HLA family gene expression. Moreover, the constructed classifier owns a high identified accuracy in the tumor/normal groups (AUC: 0.993), the tumor/CIN1-CIN3 groups (AUC: 0.963), and normal/CIN1-CIN3 groups (AUC: 0.962), and the total prediction performance is better than currently published signatures in CESC (C-index: 0,763). The combined prediction performance further indicated that Nomogram (AUC = 0.837) is superior to the classifier (AUC = 0.835) and Stage (AUC = 0.568), and the C-index of calibration curves is 0.784. The potential biological function of classifier genes indicated that silencing GALNT2 inhibited the cancer cell's proliferation, migration, and colony formation; Conversely, the cancer cell's proliferation, migration, and colony formation were increased after the upregulation of GALNT2. The Epithelial-Mesenchymal Transition Experiment showed that GALNT2 knockdown might reduce the levels of Snail and Vimentin proteins and increase E-cadherin; Conversely, the levels of Snail and Vimentin proteins were increased, E-cadherin was reduced by GALNT2 upregulation. Conclusion The classifier we constructed may help improve our understanding of subtype characteristics and provide a new strategy for developing CESC therapeutics. Remarkably, GALNT2 may be an option to directly target drivers in CESC cancer therapy.
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Affiliation(s)
- XinKai Mo
- Department of Clinical Laboratory, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, Shandong, PR China
| | - Na Wang
- Department of Medical Laboratory Science, Xinjiang Bayingoleng Mongolian Autonomous Prefecture People's Hospital, Xinjiang, China
| | - Zanjing He
- Department of Medical Laboratory Science, Xinjiang Bayingoleng Mongolian Autonomous Prefecture People's Hospital, Xinjiang, China
| | - Wenjun Kang
- Department of Medical Laboratory Science, Xinjiang Bayingoleng Mongolian Autonomous Prefecture People's Hospital, Xinjiang, China
| | - Lu Wang
- Department of Medical Laboratory Science, Xinjiang Bayingoleng Mongolian Autonomous Prefecture People's Hospital, Xinjiang, China
| | - Xia Han
- Department of Medical Laboratory Science, Xinjiang Bayingoleng Mongolian Autonomous Prefecture People's Hospital, Xinjiang, China
| | - Liu Yang
- Department of Clinical Laboratory, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, Shandong, PR China
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Zhang J, Huang C, Yang R, Wang X, Fang B, Mi J, Yuan H, Mo Z, Sun Y. Identification of Immune-Related Subtypes and Construction of a Novel Prognostic Model for Bladder Urothelial Cancer. Biomolecules 2022; 12:1670. [PMID: 36421685 PMCID: PMC9687876 DOI: 10.3390/biom12111670] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 11/06/2022] [Accepted: 11/08/2022] [Indexed: 12/20/2023] Open
Abstract
The purpose of this study was to explore the relationship between bladder urothelial cancer (BLCA) and immunity, to screen prognosis-related immune genes (PIGs), and to construct an immune-related prognosis model (IRPM). We processed the relevant data of The Cancer Genome Atlas (TCGA-BLCA) and GSE13507 using R software and Perl. We divided BLCA into high-immunity and low-immunity subtypes. There were significant differences in the two subtypes. In addition, we identified 13 PIGs of BLCA by jointly analyzing the gene expression data and survival information of GSE13507 and TCGA-BLCA, and constructed IRPM through nine of them. The low-risk group had better survival outcome than the high-risk group. We also constructed a nomogram based on clinicopathological information and risk scores of the patients. Moreover, the prognosis of BLCA patients was significantly impacted by the expression of almost every gene used to calculate the risk score. The result of real-time fluorescence quantitative polymerase chain reaction revealed that all the genes used to calculate the risk score were differentially expressed between BLCA and adjacent normal tissues, except PDGFRA. Our research provided potential targets for the treatment of BLCA and a reference for judging the prognosis of BLCA.
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Affiliation(s)
- Jiange Zhang
- Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning 530021, China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Key Laboratory of Colleges and Universities, Nanning 530021, China
- Department of Urology, The Second Affiliated Hospital of Guangxi Medical University, Nanning 530007, China
| | - Caisheng Huang
- Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning 530021, China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Key Laboratory of Colleges and Universities, Nanning 530021, China
- Department of Urology, The Nanning Second People’s Hospital, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, China
| | - Rirong Yang
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning 530021, China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Key Laboratory of Colleges and Universities, Nanning 530021, China
- Department of Immunology, School of Basic Medical Sciences, Guangxi Medical University, Nanning 530021, China
- Collaborative Innovation Center of Regenerative Medicine and Medical BioResource Development and Application Co-Constructed by the Province and Ministry, Guangxi Medical University, Nanning 530021, China
| | - Xiang Wang
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning 530021, China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Key Laboratory of Colleges and Universities, Nanning 530021, China
- Department of Immunology, School of Basic Medical Sciences, Guangxi Medical University, Nanning 530021, China
| | - Bo Fang
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning 530021, China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Key Laboratory of Colleges and Universities, Nanning 530021, China
- Collaborative Innovation Center of Regenerative Medicine and Medical BioResource Development and Application Co-Constructed by the Province and Ministry, Guangxi Medical University, Nanning 530021, China
| | - Junhao Mi
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning 530021, China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Key Laboratory of Colleges and Universities, Nanning 530021, China
- Collaborative Innovation Center of Regenerative Medicine and Medical BioResource Development and Application Co-Constructed by the Province and Ministry, Guangxi Medical University, Nanning 530021, China
| | - Hao Yuan
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning 530021, China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Key Laboratory of Colleges and Universities, Nanning 530021, China
- Department of Immunology, School of Basic Medical Sciences, Guangxi Medical University, Nanning 530021, China
| | - Zengnan Mo
- Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning 530021, China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Key Laboratory of Colleges and Universities, Nanning 530021, China
| | - Yihai Sun
- Department of Urology, The Nanning Second People’s Hospital, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, China
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Li X, Wang R, Wang S, Wang L, Yu J. Construction of a B cell-related gene pairs signature for predicting prognosis and immunotherapeutic response in non-small cell lung cancer. Front Immunol 2022; 13:989968. [PMID: 36389757 PMCID: PMC9647047 DOI: 10.3389/fimmu.2022.989968] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 10/05/2022] [Indexed: 03/30/2024] Open
Abstract
BACKGROUND Accumulating evidence indicates that the B cells play important roles in anti-tumor immunity and shaping tumor development. This study aimed to explore the expression profiles of B cell marker genes and construct a B cell-related gene pairs (BRGPs) signature associated with the prognosis and immunotherapeutic efficiency in non-small cell lung cancer (NSCLC) patients. METHODS B cell-related marker genes in NSCLC were identified using single-cell RNA sequencing data. TCGA and GEO datasets were utilized to identify the prognostic BRGPs based on a novel algorithm of cyclically single pairing along with a 0-or-1 matrix. BRGPs signature was then constructed using Lasso-Cox regression model. Its prognostic value, associated immunogenomic features, putative molecular mechanism and predictive ability to immunotherapy were investigated in NSCLC patients. RESULTS The BRGPs signature was composed of 23 BRGPs including 28 distinct B cell-related genes. This predictive signature demonstrated remarkable power in distinguishing good or poor prognosis and can serve as an independent prognostic factor for NSCLC patients in both training and validation cohorts. Furthermore, BRGPs signature was significantly associated with immune scores, tumor purity, clinicopathological characteristics and various tumor-infiltrating immune cells. Besides, we demonstrated that the tumor mutational burden scores and TIDE scores were positively correlated with the risk score of the model implying immune checkpoint blockade therapy may be more effective in NSCLC patients with high-risk scores. CONCLUSIONS This novel BRGPs signature can be used to assess the prognosis of NSCLC patients and may be useful in guiding immune checkpoint inhibitor treatment in our clinical practice.
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Affiliation(s)
- Xuanzong Li
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Ruozheng Wang
- Department of Radiation Oncology, Affiliated Tumor Hospital of Xinjiang Medical University, Urumqi, China
| | - Shijiang Wang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Linlin Wang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Jinming Yu
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
- Research Unit of Radiation Oncology, Chinese Academy of Medical Sciences, Jinan, China
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Zhang F, Zhang Q, Jiang T, Fan X, Wang W, Liu L, Liu K. Characteristics of circadian rhythm-related genes and establishment of a prognostic scoring system for lung adenocarcinoma with experimental verification: a bioinformatics analysis. J Thorac Dis 2022; 14:3934-3954. [PMID: 36389336 PMCID: PMC9641352 DOI: 10.21037/jtd-22-1112] [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: 07/27/2022] [Accepted: 09/16/2022] [Indexed: 12/01/2022]
Abstract
BACKGROUND Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors worldwide. Lung adenocarcinoma (LUAD), the main subtype of NSCLC, has a poor prognosis. In recent years, circadian rhythm (CR)-related genes (CRRGs) have demonstrated associations with tumor occurrence and development, but the relationship between CRRGs and LUAD is not clear. Because of the correlation between CRRGs and tumors, we have reason to believe that CRRGs will become an important prognostic indicator for LUAD and guide the treatment of LUAD prognosis. METHODS Based on data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we explored the biological function and immune cell infiltration of LUAD in different CR clusters and quantified CR genes using principal component analysis (PCA). Then, we built a CR scoring system (CRscore) to explore the relationship between CRRGs and LUAD prognosis. RESULTS Patients were divided into three clusters (A, B, and C). Biological characteristics, such as survival, immune cell infiltration, and gene enrichment, were significantly different among the three clusters (P<0.001). We then established the usefulness of the CR score, which could probably predict the prognosis of LUAD. Specifically, patients with a high CR score had a better prognosis and were more sensitive to chemotherapy than those with a low CR score. CONCLUSIONS It is possible to use CRRGs to assess the prognosis of patients with LUAD. Quantification of CR using the CRscore tool in patients with LUAD maybe help to guide personalized cancer immunotherapy strategies in the future. Thus, the CRscore may be a prognostic tool for LUAD.
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Affiliation(s)
- Fengbin Zhang
- The Graduate School, Dalian Medical University, Dalian, China;,Department of Cardiothoracic Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China
| | - Qi Zhang
- The Graduate School, Dalian Medical University, Dalian, China
| | - Taie Jiang
- The Graduate School, Dalian Medical University, Dalian, China;,Department of Cardiothoracic Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China
| | - Xiaoyu Fan
- The Graduate School, Dalian Medical University, Dalian, China;,Department of Cardiothoracic Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China
| | - Wenmiao Wang
- The Graduate School, Dalian Medical University, Dalian, China;,Department of Cardiothoracic Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China
| | - Lehan Liu
- Nantong University Medical School, Nantong, China
| | - Kun Liu
- Department of Cardiothoracic Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China
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Xing P, Jiang Z, Liu Y. Construction and validation of a gene signature related to bladder urothelial carcinoma based on immune gene analysis. BMC Cancer 2022; 22:926. [PMID: 36030212 PMCID: PMC9419388 DOI: 10.1186/s12885-022-09794-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 06/15/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND This study developed a gene signature associated with a malignant and common tumor of the urinary system, the Bladder Urothelial Carcinoma (BLCA). METHODS The Cancer Genome Atlas (TCGA) database was searched to obtain 414 BLCA samples and the expression spectra of 19 normal samples. Single-sample Gene Set Enrichment Analysis (ssGSEA) was conducted to determine the enrichment levels in the BLCA samples of the 29 immune genes. Unsupervised hierarchical clustering, gene set enrichment analysis (GSEA), single-factor Cox analysis, least absolute shrinkage and selection operator (LASSO) regression models, and GEO queues were used to determine the BLCA immune gene subtype, analyze the biological pathway differences between immune gene subtypes, determine the characteristic genes of BLCA associated with prognosis, identify the BLCA-related genes, and verify the gene signature, respectively. RESULTS We identified two immune gene subtypes (immunity_L and immunity_H). The latter was significantly related to receptors, JAK STAT signaling pathways, leukocyte interleukin 6 generation, and cell membrane signal receptor complexes. Four characteristic genes (RBP1, OAS1, LRP1, and AGER) were identified and constituted the gene signature. Significant survival advantages, higher mutation frequency, and superior immunotherapy were observed in the low-risk group patients. The gene signature had good predictive ability. The results of the validation group were consistent with TCGA queue results. CONCLUSIONS We constructed a 4-gene signature that helps monitor BLCA occurrence and prognosis, providing an important basis for developing personalized BLCA immunotherapy.
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Affiliation(s)
- Peng Xing
- Department of Urology, The First Hospital of China Medical University, Shenyang, 110013, P.R. China
| | - Zhengming Jiang
- Department of Urology, The First Hospital of China Medical University, Shenyang, 110013, P.R. China
| | - Yang Liu
- Department of Urology, The First Hospital of China Medical University, Shenyang, 110013, P.R. China.
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A novel molecular subtypes and risk model based on inflammatory response-related lncrnas for bladder cancer. Hereditas 2022; 159:32. [PMID: 35964079 PMCID: PMC9375404 DOI: 10.1186/s41065-022-00245-w] [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: 04/22/2022] [Accepted: 07/28/2022] [Indexed: 12/24/2022] Open
Abstract
Background Inflammation and long noncoding RNAs (lncRNAs) are gradually becoming important in the development of bladder cancer (BC). Nevertheless, the potential of inflammatory response-related lncRNAs (IRRlncRNAs) as a prognostic signature remains unexplored in BC. Methods The Cancer Genome Atlas (TCGA) provided RNA expression profiles and clinical information of BC samples, and GSEA Molecular Signatures database provided 1171 inflammation-related genes. IRRlncRNAs were identified using Pearson correlation analysis. After that, consensus clustering was performed to form molecular subtypes. After performing least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses, a risk model constructed based on the prognostic IRRlncRNAs was validated in an independent cohort. Kaplan–Meier (KM) analysis, univariate and multivariate Cox regression, clinical stratification analysis, and time-dependent receiver operating characteristic (ROC) curves were utilized to assess clinical effectiveness and accuracy of the risk model. In clusters and risk model, functional enrichment was investigated using GSEA and GSVA, and immune cell infiltration analysis was demonstrated by ESTIMATE and CIBERSORT analysis. Results A total of 174 prognostic IRRlncRNAs were confirmed, and 406 samples were divided into 2 clusters, with cluster 2 having a significantly inferior prognosis. Moreover, cluster 2 exhibited a higher ESTIMATE score, immune infiltration, and PD-L1 expression, with close relationships with the inflammatory response. Further, 12 IRRlncRNAs were identified and applied to construct the risk model and divide BC samples into low-risk and high-risk groups successfully. KM, ROC, and clinical stratification analysis demonstrated that the risk model performed well in predicting prognosis. The risk score was identified as an independently significant indicator, enriched in immune, cell cycle, and apoptosis-related pathways, and correlated with 9 immune cells. Conclusion We developed an inflammatory response-related subtypes and steady prognostic risk model based on 12 IRRlncRNAs, which was valuable for individual prognostic prediction and stratification and outfitted new insight into inflammatory response in BC. Supplementary Information The online version contains supplementary material available at 10.1186/s41065-022-00245-w.
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Chen Z, Xiong H, Shen H, You Q. Autophagy characteristics and establishment of autophagy prognostic models in lung adenocarcinoma and lung squamous cell carcinoma. PLoS One 2022; 17:e0266070. [PMID: 35333893 PMCID: PMC8956171 DOI: 10.1371/journal.pone.0266070] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 03/11/2022] [Indexed: 12/20/2022] Open
Abstract
Background Non-small cell lung cancer (NSCLC), which makes up the majority of lung cancers, remains one of the deadliest malignancies in the world. It has a poor prognosis due to its late detection and lack of response to chemoradiaiton. Therefore, it is urgent to find a new prognostic marker. Methods We evaluated biological function and immune cell infiltration in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients from TCGA and GEO databases between different clusters based on autophagy related hub genes. Autophagy scores were used to assess the degree of autophagy in each individual by using component analysis. Results Three different clusters were obtained. Gene set variation analysis, single-sample gene set enrichment analysis and survive analysis showed differences among these three clusters. We demonstrated that the autophagy score of each patient could predict tumor stage and prognosis. Patients with a high autophagy score had a better prognosis, higher immune infiltration, and were more sensitive to immunotherapy and conventional chemotherapy. Conclusion It was uncovered that autophagy played an irreplaceable role in NSCLC. Quantified autophagy scores for each NSCLC patient would help guide effective treatment strategies.
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Affiliation(s)
- Zhubei Chen
- Department of Cardiothoracic Surgery, Affiliated Hospital of Nantong University, Nantong, China
- Nantong University Medical School, Nantong, China
| | - Hui Xiong
- Department of Cardiothoracic Surgery, Affiliated Hospital of Nantong University, Nantong, China
- Nantong University Medical School, Nantong, China
| | - Hao Shen
- Department of Cardiothoracic Surgery, Affiliated Hospital of Nantong University, Nantong, China
- Nantong University Medical School, Nantong, China
| | - Qingsheng You
- Department of Cardiothoracic Surgery, Affiliated Hospital of Nantong University, Nantong, China
- * E-mail:
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Identification and Validation of Invasion-Related Molecular Subtypes and Prognostic Features for Cervical Cancer. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:1902289. [PMID: 35345518 PMCID: PMC8957037 DOI: 10.1155/2022/1902289] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 01/20/2022] [Accepted: 01/31/2022] [Indexed: 11/18/2022]
Abstract
Background As one of the main causes leading to female cancer deaths, cervical cancer shows malignant features of local infiltration and invasion into adjacent organs and tissues. This study was designed to categorize novel molecular subtypes according to cervical cancer invasion and screen reliable prognostic markers. Methods Invasion-related gene sets and expression profiles of invasion-related genes were collected from the CancerSEA database and The Cancer Genome Atlas (TCGA), respectively. Samples were clustered by nonnegative matrix factorization (NMF) to obtain different molecular subgroups, immune microenvironment characteristics of which were further systematically compared. Limma was employed to screen differentially expressed gene sets in different subtypes, followed by Lasso analysis for dimension reduction. Multivariate and univariate Cox regression analysis was performed to determine prognostic characteristics. The Kaplan-Meier test showed the prognostic differences of patients with different risks. Additionally, receiver operating characteristic (ROC) curves were applied to validate the prognostic model performance. A nomogram model was developed using clinical and prognostic characteristics of cervical cancer, and its prediction accuracy was reflected by calibration curve. Results This study filtered 19 invasion-related genes with prognosis significance in cervical cancer and 2 molecular subtypes (C1, C2). Specifically, the C1 subtype had an unfavorable prognosis, which was associated with the activation of the TGF-beta signaling pathway, focal adhesion, and PI3K-Akt signaling pathway. 875 differentially expressed genes were screened, and 8 key genes were finally retained by the dimension reduction analysis. An 8-gene signature was established as an independent factor predictive of the prognosis of cervical cancer. The signature performance was even stronger when combined with N stage. Conclusion Based on invasion-related genes, the present study categorized two cervical cancer subtypes with distinct TME characteristics and established an 8-gene marker that can accurately and independently predict the prognosis of cervical cancer.
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Identification and validation of an immune-related gene pairs signature for three urologic cancers. Aging (Albany NY) 2022; 14:1429-1447. [PMID: 35143414 PMCID: PMC8876921 DOI: 10.18632/aging.203886] [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: 10/25/2021] [Accepted: 01/25/2022] [Indexed: 11/25/2022]
Abstract
Reliable biomarkers are needed to recognize urologic cancer patients at high risk for recurrence. In this study, we built a novel immune-related gene pairs signature to simultaneously predict recurrence for three urologic cancers. We gathered 14 publicly available gene expression profiles including bladder, prostate and kidney cancer. A total of 2,700 samples were classified into the training set (n = 1,622) and validation set (n = 1,078). The 25 immune-related gene pairs signature consisting of 41 unique genes was developed by the least absolute shrinkage and selection operator regression analysis and Cox regression model. The signature stratified patients into high- and low-risk groups with significantly different relapse-free survival in the meta-training set and its subpopulations, and was an independent prognostic factor of urologic cancers. This signature showed a robust ability in the meta-validation and multiple independent validation cohorts. Immune and inflammatory response, chemotaxis and cytokine activity were enriched with genes relevant to the signature. A significantly higher infiltration level of M1 macrophages was found in the high-risk group versus the low-risk group. In conclusion, our signature is a promising prognostic biomarker for predicting relapse-free survival in patients with urologic cancer.
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Kang Z, Li W, Yu YH, Che M, Yang ML, Len JJ, Wu YR, Yang JF. Identification of Immune-Related Genes Associated With Bladder Cancer Based on Immunological Characteristics and Their Correlation With the Prognosis. Front Genet 2021; 12:763590. [PMID: 34899848 PMCID: PMC8664377 DOI: 10.3389/fgene.2021.763590] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 11/08/2021] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND To identify the immune-related genes of bladder cancer (BLCA) based on immunological characteristics and explore their correlation with the prognosis. METHODS We downloaded the gene and clinical data of BLCA from the Cancer Genome Atlas (TCGA) as the training group, and obtained immune-related genes from the Immport database. We downloaded GSE31684 and GSE39281 from the Gene Expression Omnibus (GEO) as the external validation group. R (version 4.0.5) and Perl were used to analyze all data. RESULT Univariate Cox regression analysis and Lasso regression analysis revealed that 9 prognosis-related immunity genes (PIMGs) of differentially expressed immune genes (DEIGs) were significantly associated with the survival of BLCA patients (p < 0.01), of which 5 genes, including NPR2, PDGFRA, VIM, RBP1, RBP1 and TNC, increased the risk of the prognosis, while the rest, including CD3D, GNLY, LCK, and ZAP70, decreased the risk of the prognosis. Then, we used these genes to establish a prognostic model. We drew receiver operator characteristic (ROC) curves in the training group, and estimated the area under the curve (AUC) of 1-, 3- and 5-year survival for this model, which were 0.688, 0.719, and 0.706, respectively. The accuracy of the prognostic model was verified by the calibration chart. Combining clinical factors, we established a nomogram. The ROC curve in the external validation group showed that the nomogram had a good predictive ability for the survival rate, with a high accuracy, and the AUC values of 1-, 3-, and 5-year survival were 0.744, 0.770, and 0.782, respectively. The calibration chart indicated that the nomogram performed similarly with the ideal model. CONCLUSION We had identified nine genes, including PDGFRA, VIM, RBP1, RBP1, TNC, CD3D, GNLY, LCK, and ZAP70, which played important roles in the occurrence and development of BLCA. The prognostic model based on these genes had good accuracy in predicting the OS of patients and might be promising candidates of therapeutic targets. This study may provide a new insight for the diagnosis, treatment and prognosis of BLCA from the perspective of immunology. However, further experimental studies are necessary to reveal the underlying mechanisms by which these genes mediate the progression of BLCA.
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Affiliation(s)
- Zhen Kang
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China
- Department of Urology, The First People’s Hospital of Yunnan Province, Kunming, China
| | - Wei Li
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China
- Department of Urology, The First People’s Hospital of Yunnan Province, Kunming, China
| | - Yan-Hong Yu
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China
- Department of Urology, The First People’s Hospital of Yunnan Province, Kunming, China
| | - Meng Che
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China
| | - Mao-Lin Yang
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China
- Department of Urology, The First People’s Hospital of Yunnan Province, Kunming, China
| | - Jin-Jun Len
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China
- Department of Urology, The First People’s Hospital of Yunnan Province, Kunming, China
| | - Yue-Rong Wu
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China
| | - Jun-Feng Yang
- The Affiliated Hospital, Kunming University of Science and Technology, Kunming, China
- Department of Urology, The First People’s Hospital of Yunnan Province, Kunming, China
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