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Dong K, Nihal R, Meyer TJ, Singh SP, Kaur S, Roberts DD. CD47 and IFT57 Are Colinear Genes That Are Highly Coexpressed in Most Cancers and Exhibit Parallel Cancer-Specific Correlations with Survival. Int J Mol Sci 2024; 25:8956. [PMID: 39201643 PMCID: PMC11354933 DOI: 10.3390/ijms25168956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Revised: 08/09/2024] [Accepted: 08/14/2024] [Indexed: 09/02/2024] Open
Abstract
An association between high CD47 expression and poor cancer survival has been attributed to its function on malignant cells to inhibit phagocytic clearance. However, CD47 mRNA expression in some cancers lacks correlation or correlates with improved survival. IFT57 encodes an essential primary cilium component and is colinear with CD47 across amniote genomes, suggesting coregulation of these genes. Analysis of The Cancer Genome Atlas datasets identified IFT57 as a top coexpressed gene with CD47 among 1156 human cancer cell lines and in most tumor types. The primary cilium also regulates cancer pathogenesis, and correlations between IFT57 mRNA and survival paralleled those for CD47 in thyroid and lung carcinomas, melanoma, and glioma. CD47 ranked first for coexpression with IFT57 mRNA in papillary thyroid carcinomas, and higher expression of both genes correlated with significantly improved overall survival. CD47 and IFT57 mRNAs were coordinately regulated in thyroid carcinoma cell lines. Transcriptome analysis following knockdown of CD47 or IFT57 in thyroid carcinoma cells identified the cytoskeletal regulator CRACD as a specific target of IFT57. CRACD mRNA expression inversely correlated with IFT57 mRNA and with survival in low-grade gliomas, lung adenocarcinomas, and papillary thyroid carcinomas, suggesting that IFT57 rather than CD47 regulates survival in these cancers.
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Affiliation(s)
- Kun Dong
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA; (K.D.); (R.N.)
| | - Raghib Nihal
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA; (K.D.); (R.N.)
| | - Thomas J. Meyer
- CCR Collaborative Bioinformatics, Resource, Office of Science and Technology Resources, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA;
| | - Satya P. Singh
- Inflammation Biology Section, Laboratory of Molecular Immunology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA;
| | - Sukhbir Kaur
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA; (K.D.); (R.N.)
| | - David D. Roberts
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA; (K.D.); (R.N.)
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Yao Z, Song P, Jiao W. Pathogenic role of super-enhancers as potential therapeutic targets in lung cancer. Front Pharmacol 2024; 15:1383580. [PMID: 38681203 PMCID: PMC11047458 DOI: 10.3389/fphar.2024.1383580] [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: 02/07/2024] [Accepted: 04/02/2024] [Indexed: 05/01/2024] Open
Abstract
Lung cancer is still one of the deadliest malignancies today, and most patients with advanced lung cancer pass away from disease progression that is uncontrollable by medications. Super-enhancers (SEs) are large clusters of enhancers in the genome's non-coding sequences that actively trigger transcription. Although SEs have just been identified over the past 10 years, their intricate structure and crucial role in determining cell identity and promoting tumorigenesis and progression are increasingly coming to light. Here, we review the structural composition of SEs, the auto-regulatory circuits, the control mechanisms of downstream genes and pathways, and the characterization of subgroups classified according to SEs in lung cancer. Additionally, we discuss the therapeutic targets, several small-molecule inhibitors, and available treatment options for SEs in lung cancer. Combination therapies have demonstrated considerable advantages in preclinical models, and we anticipate that these drugs will soon enter clinical studies and benefit patients.
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Affiliation(s)
- Zhiyuan Yao
- Department of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Peng Song
- Department of Thoracic Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Wenjie Jiao
- Department of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
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Yang X, Tao Y, Xu Y, Cai W, Shao Q. SLC35A2 expression drives breast cancer progression via ERK pathway activation. FEBS J 2024; 291:1483-1505. [PMID: 38143314 DOI: 10.1111/febs.17044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 10/21/2023] [Accepted: 12/22/2023] [Indexed: 12/26/2023]
Abstract
Alterations in glycosylation are associated with breast tumor formation and progression. Nevertheless, the specific functions and mechanisms of the human major UDP-galactose transporter-encoding gene solute carrier family 35 member A2 (SLC35A2) in breast invasive carcinoma (BRCA) have not been fully determined. Here, we report that SLC35A2 promotes BRCA progression by activating extracellular signal regulated kinase (ERK). SLC35A2 expression and prognosis-predictive significance in pan-cancer were evaluated using public databases. The upstream non-coding RNAs (ncRNAs) of SLC35A2 were analyzed, and their expression and regulations were validated in breast tissues and cell lines by a quantitative PCR and dual-luciferase assays. We used bioinformatic tools to assess the link between SLC35A2 expression and immune infiltration and performed immunohistochemistry for validation. Cell Counting Kit-8, 5-ethynyl-2'-deoxyuridine, transwell, flow cytometer and western blotting were used to assess the proliferation, motility, cell cycle and apoptosis of BRCA cells in vitro. The xenograft models were constructed to assess the effect of SLC35A2 on BRCA tumor growth in vivo. The results indicated that SLC35A2 expression was upregulated and linked to an unfavorable prognosis in BRCA. The most likely upstream ncRNA-associated pathway of SLC35A2 in BRCA was the AC074117.1/hsa-let-7b-5p axis. SLC35A2 expression had positive correlations with the presence of Th2 cells, regulatory T cells and immune checkpoints. Knockdown of SLC35A2 could reduce BRCA cell proliferation, motility, and cause G2/M arrest and cell apoptosis via ERK signaling. Moreover, ERK activation can rescue the inhibitory effects of knockdown SLC35A2 in BRCA. In conclusion, AC074117.1/hsa-let-7b-5p axis-mediated high expression of SLC35A2 acts as a tumor promoter in BRCA via ERK signaling, which provides a potential target for BRCA treatment.
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Affiliation(s)
- Xiaochen Yang
- Department of Thyroid and Breast Surgery, Affiliated Kunshan Hospital of Jiangsu University, China
| | - Yukai Tao
- Clinical Research & Lab Center, Affiliated Kunshan Hospital of Jiangsu University, China
| | - Yan Xu
- Department of Thyroid and Breast Surgery, Affiliated Kunshan Hospital of Jiangsu University, China
| | - Weili Cai
- Institute of Medical Genetics and Reproductive Immunity, The Digestive and Reproductive System Cancers Precise Prevention Engineering Research Center of Jiangsu Province, Jiangsu College of Nursing, Huai'an, China
| | - Qixiang Shao
- Clinical Research & Lab Center, Affiliated Kunshan Hospital of Jiangsu University, China
- Institute of Medical Genetics and Reproductive Immunity, The Digestive and Reproductive System Cancers Precise Prevention Engineering Research Center of Jiangsu Province, Jiangsu College of Nursing, Huai'an, China
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Zhan T, Wang W, Guan X, Bao W, Lu N, Zhang J. Construction of an m6A- and neutrophil extracellular traps-related lncRNA model to predict hepatocellular carcinoma prognosis and immune landscape. Front Immunol 2023; 14:1231543. [PMID: 37868992 PMCID: PMC10585104 DOI: 10.3389/fimmu.2023.1231543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/21/2023] [Indexed: 10/24/2023] Open
Abstract
Purpose To investigate the impact of N6-methyladenosine- (m6A) and neutrophil extracellular traps- (NETs) related lncRNAs (MNlncRNAs) on the prognosis of hepatocellular carcinoma (HCC). Methods We collected m6A and NETs-related genes from published studies. We identified the MNlncRNAs by correlation analysis. Cox regression and the least absolute selection operator (LASSO) method were used to select predictive MNlncRNAs. The expressions of predictive MNlncRNAs were detected by cell and tissue experiments. Survival, medication sensitivity, and immunological microenvironment evaluations were used to assess the model's prognostic utility. Finally, we performed cellular experiments to further validate the model's prognostic reliability. Results We obtained a total of 209 MNlncRNAs. 7 MNlncRNAs comprised the prognostic model, which successfully stratifies HCC patients, with the area under the curve (AUC) ranging from 0.7 to 0.8. In vitro tests confirmed that higher risk patients had worse prognosis. Risk score, immunological microenvironment, and immune checkpoint gene expression were all significantly correlated with each other in HCC. In the group at high risk, immunotherapy could be more successful. Cellular assays confirmed that HCC cells with high risk scores have a higher proliferation and invasive capacity. Conclusion The MNlncRNAs-related prognostic model aided in determining HCC prognosis, revealing novel therapeutic options, notably immunotherapy.
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Affiliation(s)
- Tian Zhan
- Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Wei Wang
- Department of Clinical Laboratory, Lianshui County People’s Hospital, Huai’an, China
| | - Xiao Guan
- Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Wei Bao
- Department of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Na Lu
- Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jianping Zhang
- Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
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Sun YF, Chen L, Xia QJ, Wang TH. Identification of necroptosis-related long non-coding RNAs prognostic signature and the crucial lncRNA in bladder cancer. J Cancer Res Clin Oncol 2023; 149:10217-10234. [PMID: 37269345 DOI: 10.1007/s00432-023-04886-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 05/19/2023] [Indexed: 06/05/2023]
Abstract
BACKGROUND Research on the relationships between long non-coding RNAs (lncRNAs) and cancer is attractive and has progressed very rapidly. Necroptosis-related biomarkers can potentially be used for predicting the prognosis of cancer patients. This study aimed to establish a necroptosis-related lncRNA (NPlncRNA) signature to predict the prognosis of patients with bladder cancer (BCa). METHODS First, NPlncRNAs were identified using Pearson correlation analysis and machine learning algorithms, including SVM-RFE, least absolute shrinkage and selection operator (LASSO) regression, and random forest. The prognostic NPlncRNA signature was constructed using univariate and multivariate Cox regression analyses and the diagnostic efficacy and clinically predictive efficiency were evaluated and validated. The biological functions of the signature were analysed using gene set enrichment analysis (GSEA) and functional enrichment analysis. We further integrated the RNA-seq dataset (GSE133624) with our outcomes to reveal the crucial NPlncRNA that was functionally verified by assessing cell viability, proliferation, and apoptosis in BCa cells. RESULTS The prognostic NPlncRNAs signature was composed of PTOV1-AS2, AC083862.2, MAFG-DT, AC074117.1, AL049840.3, and AC078778.1, and a risk score based on this signature was proven to be an independent prognostic factor for the BCa patients, indicated by poor overall survival (OS) of patients in the high-risk group. Additionally, the NPlncRNAs signature had a higher diagnostic validity than that of other clinicopathological variables, with a greater area under the receptor operating characteristic and concordance index curves. A nomogram established by integrating clinical variables and risk score confirmed that the signature can accurately predict the OS of patients and has high clinical practicability. Functional enrichment analysis and GSEA revealed that some cancer-related and necroptosis-related pathways were enriched in high-risk groups. The crucial NPlncRNA MAFG-DT was associated with poor prognosis and was highly expressed in BCa cells. MAFG-DT silencing notably inhibited proliferation and enhanced apoptosis of BCa cells. CONCLUSIONS A novel prognostic NPlncRNAs signature was identified in BCa in this study, which provides potential therapeutic targets among which MAFG-DT plays critical roles in the tumorigenesis of BCa.
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Affiliation(s)
- Yi-Fei Sun
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Li Chen
- Institute of Neurological Disease, National-Local Joint Engineering Research Center of Translational Medicine, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Qing-Jie Xia
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Ting-Hua Wang
- Institute of Neurological Disease, National-Local Joint Engineering Research Center of Translational Medicine, West China Hospital, Sichuan University, Chengdu, 610041, China.
- Laboratory Animal Department, Kunming Medical University, Kunming, 650031, China.
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Wei X, Zhou Z, Long M, Lin Q, Qiu M, Chen P, Huang Q, Qiu J, Jiang Y, Wen Q, Liu Y, Li R, Nong C, Guo Q, Yu H, Zhou X. A novel signature constructed by super-enhancer-related genes for the prediction of prognosis in hepatocellular carcinoma and associated with immune infiltration. Front Oncol 2023; 13:1043203. [PMID: 36845708 PMCID: PMC9948016 DOI: 10.3389/fonc.2023.1043203] [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: 09/13/2022] [Accepted: 01/30/2023] [Indexed: 02/11/2023] Open
Abstract
Background Super-enhancer (SE) refers to a regulatory element with super transcriptional activity, which can enrich transcription factors and drive gene expression. SE-related genes play an important role in the pathogenesis of malignant tumors, including hepatocellular carcinoma (HCC). Methods The SE-related genes were obtained from the human super-enhancer database (SEdb). Data from the transcriptome analysis and related clinical information with HCC were obtained from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. The upregulated SE-related genes from TCGA-LIHC were identified by the DESeq2R package. Multivariate Cox regression analysis was used to construct a four-gene prognostic signature. According to the median risk score, HCC patients were divided into high-risk and low-risk group patients. Results The Kaplan-Meier (KM) curve showed that a significantly worse prognosis was found for the high-risk group (P<0.001). In the TCGA-LIHC dataset, the area under the curve (AUC) values were 0.737, 0.662, and 0.667 for the model predicting overall survival (OS) over 1-, 3-, and 5- years, respectively, indicating the good prediction ability of our prediction model. This model's prognostic value was further validated in the LIRI-JP dataset and HCC samples (n=65). Furthermore, we found that higher infiltration level of M0 macrophages and upregulated of CTLA4 and PD1 in the high-risk group, implying that immunotherapy could be effective for those patients. Conclusion These results provide further evidence that the unique SE-related gene model could accurately predict the prognosis of HCC.
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Affiliation(s)
- Xueyan Wei
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Zihan Zhou
- Department of Cancer Prevention and Control, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Meiying Long
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Qiuling Lin
- Department of Clinical Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Moqin Qiu
- Department of Respiratory Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Peiqin Chen
- Editorial Department of Chinese Journal of Oncology Prevention and Treatment, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Qiongguang Huang
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Jialin Qiu
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Yanji Jiang
- Scientific Research Department, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Qiuping Wen
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Yingchun Liu
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Runwei Li
- Department of Environmental and Occupational Health, School of Public Health, Indiana University, Bloomington, IN, United States
| | - Cunli Nong
- Department of Infectious Diseases, The 4th Affiliated Hospital of Guangxi Medical University/Liuzhou Worker’s Hospital, Liuzhou, Guangxi, China
| | - Qian Guo
- Department of Infectious Diseases, The 4th Affiliated Hospital of Guangxi Medical University/Liuzhou Worker’s Hospital, Liuzhou, Guangxi, China
| | - Hongping Yu
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,Key Laboratory of Early Prevention and Treatment for Regional High-Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, China,Key Cultivated Laboratory of Cancer Molecular Medicine, Health Commission of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China,*Correspondence: Xianguo Zhou, ; Hongping Yu,
| | - Xianguo Zhou
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China,*Correspondence: Xianguo Zhou, ; Hongping Yu,
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Penetrating Exploration of Prognostic Correlations of the FKBP Gene Family with Lung Adenocarcinoma. J Pers Med 2022; 13:jpm13010049. [PMID: 36675710 PMCID: PMC9862762 DOI: 10.3390/jpm13010049] [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: 11/09/2022] [Revised: 12/17/2022] [Accepted: 12/20/2022] [Indexed: 12/28/2022] Open
Abstract
The complexity of lung adenocarcinoma (LUAD), the development of which involves many interacting biological processes, makes it difficult to find therapeutic biomarkers for treatment. FK506-binding proteins (FKBPs) are composed of 12 members classified as conservative intracellular immunophilin family proteins, which are often connected to cyclophilin structures by tetratricopeptide repeat domains and have peptidyl prolyl isomerase activity that catalyzes proline from residues and turns the trans form into the cis form. Since FKBPs belong to chaperone molecules and promote protein folding, previous studies demonstrated that FKBP family members significantly contribute to the degradation of damaged, misfolded, abnormal, and foreign proteins. However, transcript expressions of this gene family in LUAD still need to be more fully investigated. In this research, we adopted high-throughput bioinformatics technology to analyze FKBP family genes in LUAD to provide credible information to clinicians and promote the development of novel cancer target drugs in the future. The current data revealed that the messenger (m)RNA levels of FKBP2, FKBP3, FKBP4, FKBP10, FKBP11, and FKBP14 were overexpressed in LUAD, and FKBP10 had connections to poor prognoses among LUAD patients in an overall survival (OS) analysis. Based on the above results, we selected FKBP10 to further conduct a comprehensive analysis of the downstream pathway and network. Through a DAVID analysis, we found that FKBP10 was involved in mitochondrial electron transport, NADH to ubiquinone transport, mitochondrial respiratory chain complex I assembly, etc. The MetaCore pathway analysis also indicated that FKBP10 was involved in "Ubiquinone metabolism", "Translation_(L)-selenoaminoacid incorporation in proteins during translation", and "Transcription_Negative regulation of HIF1A function". Collectively, this study revealed that FKBP family members are both significant prognostic biomarkers for lung cancer progression and promising clinical therapeutic targets, thus providing new targets for treating LUAD patients.
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Li C, Liu Q, Song Y, Wang W, Zhang X. Construction of a prognostic model of colon cancer patients based on metabolism-related lncRNAs. Front Oncol 2022; 12:944476. [PMID: 36248984 PMCID: PMC9558288 DOI: 10.3389/fonc.2022.944476] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 09/16/2022] [Indexed: 12/24/2022] Open
Abstract
Background Many studies have shown that metabolism-related lncRNAs may play an important role in the pathogenesis of colon cancer. In this study, a prognostic model for colon cancer patients was constructed based on metabolism-related lncRNAs. Methods Both transcriptome data and clinical data of colon cancer patients were downloaded from the TCGA database, and metabolism-related genes were downloaded from the GSEA database. Through differential expression analysis and Pearson correlation analysis, long non-coding RNAs (lncRNAs) related to colon cancer metabolism were obtained. CRC patients were divided into training set and verification set at the ratio of 2:1. Based on the training set, univariate Cox regression analysis was utilized to determine the prognostic differential expression of metabolic-related lncRNAs. The Optimal lncRNAs were obtain by Lasso regression analysis, and a risk model was built to predict the prognosis of CRC patients. Meanwhile, patients were divided into high-risk and low-risk groups and a survival curve was drawn accordingly to determine whether the survival rate differs between the two groups. At the same time, subgroup analysis evaluated the predictive performance of the model. We combined clinical indicators with independent prognostic significance and risk scores to construct a nomogram. C index and the calibration curve, DCA clinical decision curve and ROC curve were obtained as well. The above results were all verified using the validation set. Finally, based on the CIBERSORT analysis method, the correlation between lncRNAs and 22 tumor-infiltrated lymphocytes was explored. Results By difference analysis, 2491 differential lncRNAs were obtained, of which 226 were metabolic-related lncRNAs. Based on Cox regression analysis and Lasso results, a multi-factor prognostic risk prediction model with 13 lncRNAs was constructed. Survival curve results suggested that patients with high scores and have a poorer prognosis than patients with low scores (P<0.05). The area under the ROC curve (AUC) for the 3-year survival and 5-year survival were 0.768 and 0.735, respectively. Cox regression analysis showed that age, distant metastasis and risk scores can be used as independent prognostic factors. Then, a nomogram including age, distant metastasis and risk scores was built. The C index was 0.743, and the ROC curve was drawn to obtain the AUC of the 3-year survival and the 5-year survival, which were 0.802 and 0.832, respectively. The above results indicated that the nomogram has a good predictive effect. Enrichment analysis of KEGG pathway revealed that differential lncRNAs may be related to chemokines, amino acid and sugar metabolism, NOD-like receptor and Toll-like receptor activation as well as other pathways. Finally, the analysis results based on the CIBERSORT algorithm showed that the lncRNAs used to construct the model had a strong polarized correlation with B cells, CD8+T cells and M0 macrophages. Conclusion 13 metabolic-related lncRNAs affecting the prognosis of CRC were screened by bioinformatics methods, and a prognostic risk model was constructed, laying a solid foundation for the research of metabolic-related lncRNAs in CRC.
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Affiliation(s)
- Chenyang Li
- The Department of Gastroenterology and Hepatology, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Qian Liu
- The Department of Gastroenterology and Hepatology, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Yiran Song
- The Department of Gastroenterology and Hepatology, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Wenxin Wang
- The Department of Gastroenterology and Hepatology, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Xiaolan Zhang
- The Department of Gastroenterology and Hepatology, The Second Hospital of Hebei Medical University, Shijiazhuang, China
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Hu J, Lai C, Shen Z, Yu H, Lin J, Xie W, Su H, Kong J, Han J. A Prognostic Model of Bladder Cancer Based on Metabolism-Related Long Non-Coding RNAs. Front Oncol 2022; 12:833763. [PMID: 35280814 PMCID: PMC8913725 DOI: 10.3389/fonc.2022.833763] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 02/03/2022] [Indexed: 11/13/2022] Open
Abstract
Background Some studies have revealed a close relationship between metabolism-related genes and the prognosis of bladder cancer. However, the relationship between metabolism-related long non-coding RNAs (lncRNA) regulating the expression of genetic material and bladder cancer is still blank. From this, we developed and validated a prognostic model based on metabolism-associated lncRNA to analyze the prognosis of bladder cancer. Methods Gene expression, lncRNA sequencing data, and related clinical information were extracted from The Cancer Genome Atlas (TCGA). And we downloaded metabolism-related gene sets from the human metabolism database. Differential expression analysis is used to screen differentially expressed metabolism-related genes and lncRNAs between tumors and paracancer tissues. We then obtained metabolism-related lncRNAs associated with prognosis by correlational analyses, univariate Cox analysis, and logistic least absolute shrinkage and selection operator (LASSO) regression. A risk scoring model is constructed based on the regression coefficient corresponding to lncRNA calculated by multivariate Cox analysis. According to the median risk score, patients were divided into a high-risk group and a low-risk group. Then, we developed and evaluated a nomogram including risk scores and Clinical baseline data to predict the prognosis. Furthermore, we performed gene-set enrichment analysis (GSEA) to explore the role of these metabolism-related lncRNAs in the prognosis of bladder cancer. Results By analyzing the extracted data, our research screened out 12 metabolism-related lncRNAs. There are significant differences in survival between high and low-risk groups divided by the median risk scoring model, and the low-risk group has a more favorable prognosis than the high-risk group. Univariate and multivariate Cox regression analysis showed that the risk score was closely related to the prognosis of bladder cancer. Then we established a nomogram based on multivariate analysis. After evaluation, the modified model has good predictive efficiency and clinical application value. Furthermore, the GSEA showed that these lncRNAs affected bladder cancer prognosis through multiple links. Conclusions A predictive model was established and validated based on 12 metabolism-related lncRNAs and clinical information, and we found these lncRNA affected bladder cancer prognosis through multiple links.
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Affiliation(s)
- Jintao Hu
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Clinical Research Center for Urological Diseases, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Cong Lai
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Clinical Research Center for Urological Diseases, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zefeng Shen
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Clinical Research Center for Urological Diseases, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Hao Yu
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Clinical Research Center for Urological Diseases, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Junyi Lin
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Clinical Research Center for Urological Diseases, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Weibin Xie
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Clinical Research Center for Urological Diseases, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Huabin Su
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Clinical Research Center for Urological Diseases, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jianqiu Kong
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Clinical Research Center for Urological Diseases, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- *Correspondence: Jinli Han, ; Jianqiu Kong,
| | - Jinli Han
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Clinical Research Center for Urological Diseases, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- *Correspondence: Jinli Han, ; Jianqiu Kong,
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