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Sun P, Wang Y, Liu X, Li Z, Cui D, Li Q, Wang Q, Wang J. Methylation-driven mechanisms of allergic rhinitis during pollen and non-pollen seasons using integrated bioinformatics analysis. Front Genet 2024; 15:1242974. [PMID: 38699230 PMCID: PMC11063319 DOI: 10.3389/fgene.2024.1242974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 03/25/2024] [Indexed: 05/05/2024] Open
Abstract
Background Allergic rhinitis (AR) is a widespread allergic airway disease that results from a complex interplay between genetic and environmental factors and affects approximately 10%-40% of the global population. Pollen is a common allergen, and exposure to pollen can cause epigenetic changes. However, the mechanism underlying pollen-induced DNA methylation changes and their potential effects on the allergic march are still unclear. The purpose of this study was to explore the methylation-driven mechanisms of AR during the pollen and non-pollen seasons using bioinformatics analysis and to investigate their relationship with asthma. Methods We downloaded DNA methylation and gene expression data from the GEO database (GSE50387: GSE50222, GSE50101) and identified differentially methylated positions (DMPs) and differentially expressed genes (DEGs) during the pollen and non-pollen seasons using the CHAMP and limma packages. Through correlation analysis, we identified methylation-driven genes and performed pathway enrichment analysis to annotate their functions. We incorporated external data on AR combined with asthma (GSE101720) for analysis to identify key CpGs that promote the transformation of AR to asthma. We also utilized external data on olive pollen allergy (GSE54522) for analysis to validate the methylation-driven genes. Weighted correlation network analysis (WGCNA) was employed to identify gene modules significantly correlated with pollen allergy. We extracted genes related to the key methylation-driven gene ZNF667-AS1 from the significant module and performed pathway intelligent clustering using KOBAS-i. We also utilized gene set enrichment analysis to explore the potential function of ZNF667-AS1. Results We identified 20 and 24 CpG-Gene pairings during the pollen and non-pollen seasons. After incorporating external data from GSE101720, we found that ZNF667-AS1 is a key gene that may facilitate the transformation of AR into asthma during the pollen season. This finding was further validated in another external dataset, GSE54522, which is associated with pollen allergy. WGCNA identified 17 modules, among which the blue module showed significant correlation with allergies. ZNF667-AS1 was located in the blue module. We performed pathway analysis on the genes correlated with ZNF667-AS1 extracted from the blue module and identified a prominent cluster of pathways in the KOBAS-i results, including Toll-like receptor (TLR) family, MyD88, MAPK, and oxidative stress. Gene set enrichment analysis around cg05508084 (paired with ZNF667-AS1) also indicated its potential involvement in initiating and modulating allergic inflammation from the perspective of TLR and MAPK signaling. Conclusion We identified methylation-driven genes and their related pathways during the pollen and non-pollen seasons in patients with AR and identified key CpGs that promote the transformation of AR into asthma due to pollen exposure. This study provides new insights into the underlying molecular mechanisms of the transformation of AR to asthma.
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Affiliation(s)
- Pengcheng Sun
- College of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Yi Wang
- College of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Xing Liu
- College of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Zhuqing Li
- College of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Diankun Cui
- College of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Qianru Li
- Qinghai Golmud Jianqiao Hospital, Golmud, Qinghai, China
| | - Qi Wang
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Ji Wang
- National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
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Ahmadi M, Morshedzadeh F, Ghaderian SMH, Mousavi P, Habibipour L, Peymani M, Abbaszadegan MR, Ghafouri-Fard S. Carcinogenic roles of MAFG-AS1 in human cancers. Clin Transl Oncol 2024; 26:52-68. [PMID: 37351806 DOI: 10.1007/s12094-023-03246-x] [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: 01/21/2023] [Accepted: 06/02/2023] [Indexed: 06/24/2023]
Abstract
The MAF bZIP transcription factor G-antisense RNA 1 (MAFG-AS1) is located on chromosome 17. MAFG-AS1 was upregulated in 15 human cancers. MAFG-AS1 not only suppresses 16 miRNAs but also directly impacts 22 protein-coding genes' expression. Notably, abnormal MAFG-AS1 expression is connected to clinicopathological characteristics and a worse prognosis in a variety of cancers. Moreover, MAFG-AS1 takes its part in the tumorigenesis and progression of various human malignancies by suppressing apoptosis and promoting proliferation, migration, invasion, aerobic glycolysis, ferroptosis, angiogenesis, EMT, and metastasis. Besides, it can predict treatment effectiveness in ER + breast cancer, urothelial bladder carcinoma, and liver cancer by functioning as a trigger of resistance to tamoxifen, sorafenib, and cisplatin. This study systematically presents the functions of MAFG-AS1 in various cancers, as well as the findings of bioinformatics analyses of the MAFG-AS1, which should give clear advice for future research.
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Affiliation(s)
- Mohsen Ahmadi
- Department of Medical Genetics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Firouzeh Morshedzadeh
- Department of Genetics, Faculty of Basic Sciences, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
- Department of Medical Genetics and Molecular Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | | | - Pegah Mousavi
- Molecular Medicine Research Center, Hormozgan Health Institute, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.
| | - Leila Habibipour
- Department of Biotechnology, Institute of Science and High Technology and Environmental Science, Graduate University of Advanced Technology, Kerman, Iran
| | - Maryam Peymani
- Department of Genetics, Faculty of Basic Sciences, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
| | - Mohammad Reza Abbaszadegan
- Department of Medical Genetics and Molecular Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Soudeh Ghafouri-Fard
- Department of Medical Genetics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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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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Wu Y, Wang Y, Yao H, Li H, Meng F, Li Q, Lin X, Liu L. MNX1-AS1, a c-Myc induced lncRNA, promotes the Warburg effect by regulating PKM2 nuclear translocation. JOURNAL OF EXPERIMENTAL & CLINICAL CANCER RESEARCH : CR 2022; 41:337. [PMID: 36476366 PMCID: PMC9727912 DOI: 10.1186/s13046-022-02547-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 11/23/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Altered glycolysis is the most fundamental metabolic change associated with the Warburg effect. Some glycolytic enzymes such as PKM2, the dominant pyruvate kinase in cancer cells, have been shown to engage in non-glycolytic functions that contribute to tumor metabolism. However, the precise mechanisms are not completely understood. METHODS The role of MNX1-AS1 in hepatocellular carcinoma progression was assessed both in vitro and in vivo. Northern blotting, RNA pulldown, mass spectrometry, RNA-binding protein immunoprecipitation, ChIP, luciferase reporter assays, RNA FISH and immunofluorescence staining were used to explore the detail molecular mechanism of MNX1-AS1 in hepatocellular carcinoma (HCC). RESULTS Here we dissect how MNX1-AS1, a long non-coding RNA (lncRNA), reinforces the Warburg effect through facilitating the non-glycolytic actions of PKM2 in the cell nucleus. We found that MNX1-AS1 expression was frequently overexpressed in HCC-derived cell lines and tissues compared to their normal hepatic cell counterparts, a finding consistent with its status as pan-cancer expressed lncRNA. In the context of HCC, we show MNX1-AS1 acts as a scaffold to promote interactions between PKM2 and importin α5. In response to EGFR activation, the resulting ternary complex drives the translocation of PKM2 into the nucleus. In consequence, glycolytic pathway components including key mediators of the Warburg effect (LDHA, GLUT1 and PDK1) are upregulated though the coactivator function of PKM2. Manipulating MNX1-AS1 elicited robust effects on glycolysis associated with marked changes in HCC growth in vitro and in xenograft models, indicative of the significant contribution of MNX1-AS1 to tumorigenic phenotypes. Moreover, while MNX1-AS1 expression is driven by c-Myc, its actions associated with PKM2 were shown to be downstream and independent of c-Myc. CONCLUSIONS Given the status of MNX1-AS1 as a pan-cancer upregulated lncRNA, this implicitly highlights the potential of targeting MNX1-AS1 to selectively counter the Warburg effect in a range of tumor types.
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Affiliation(s)
- Yang Wu
- grid.27255.370000 0004 1761 1174Cheeloo College of Medicine, Shandong University, Jinan, 250002 China ,grid.59053.3a0000000121679639Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, 230001 China
| | - Yichun Wang
- grid.59053.3a0000000121679639Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, 230001 China
| | - Hanhui Yao
- grid.59053.3a0000000121679639Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, 230001 China
| | - Heng Li
- grid.27255.370000 0004 1761 1174Cheeloo College of Medicine, Shandong University, Jinan, 250002 China ,grid.59053.3a0000000121679639Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, 230001 China
| | - Fanzheng Meng
- grid.59053.3a0000000121679639Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, 230001 China
| | - Qidong Li
- grid.59053.3a0000000121679639Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, 230001 China
| | - Xiansheng Lin
- grid.59053.3a0000000121679639Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, 230001 China
| | - Lianxin Liu
- grid.27255.370000 0004 1761 1174Cheeloo College of Medicine, Shandong University, Jinan, 250002 China ,grid.59053.3a0000000121679639Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, 230001 China
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Yu Z, Lu B, Gao H, Liang R. A New Prognostic Signature Constructed with Necroptosis-Related lncRNA in Bladder Cancer. JOURNAL OF ONCOLOGY 2022; 2022:5643496. [PMID: 36425941 PMCID: PMC9681547 DOI: 10.1155/2022/5643496] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 11/03/2022] [Accepted: 11/04/2022] [Indexed: 08/01/2023]
Abstract
BACKGROUND Bladder cancer (BC) accounts for the most common urologic malignancy, leading to a heavy social burden over the world. We aim to search for a novel prognostic biomarker with necroptosis-related lncRNAs of bladder cancer in this study. METHODS We download the RNA-sequencing data and corresponding clinical information of BC patients from TCGA. We performed Pearson correlation analysis to identify necroptosis-related lncRNAs (NRlncRNAs). Then, we used univariate Cox regression, Lasso Cox analysis, and multivariate Cox regression to construct the optimal prognostic model. Next, we used Kaplan-Meier curves, Cox regression, receiver operating characteristic (ROC) curves, nomogram, and stratified survival analysis to evaluate the capacity of the prognostic signature. Furthermore, gene set enrichments in the signature and the correlation between prognostic signature and necroptosis genes, tumor microenvironment, immune infiltration, and immune checkpoints of BC were also explored. RESULTS A 7-NRlncRNAs signature comprising FKBP14-AS1, AL731567.1, LINC02178, AC011503.2, LINC02195, AC068196.1, and AL136084.2 was constructed to predict the prognosis of BC in this research. Cox regression analysis showed that the signature could be an independent prognostic factor for BC patients (P < 0.001). Compared to other clinicopathological characteristics, this signature displayed a better capacity of prediction with the area under the curve (AUC) of 0.745. Stratified analysis using various clinical variables demonstrated that the prognostic signature has good clinical fitness. GSEA showed that focal adhesion and the WNT signaling pathway were enriched in the high-risk group. Immune infiltration analysis indicated that the signature was significantly inversely correlated with infiltration of CD8+ T cells and CD4+ T cells while positively correlated with macrophages and cancer associated fibroblasts. Immune checkpoint analysis revealed that the expressions of protective factors were significantly lower in the high-risk group, while expressions of cancer promotors were significantly higher in this group. The gene expression analysis displayed that necroptosis genes such as FADD, FAS, MYC, STAT3, PLK1, LEF1, EGFR, RIPK3, CASP8, BRAF, ID1, GATA3, MYCN, CD40, and TNFRSF21 were significantly different between the two groups. CONCLUSIONS The 7-NRlncRNAs signature can predict the overall survival of BC and may provide help for the individualized treatment of BC patients.
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Affiliation(s)
- Zuhu Yu
- Department of Urology, University of Chinese Academy of Sciences Shenzhen Hospital, Guangming, Shenzhen, China
| | - Bin Lu
- Department of Urology, University of Chinese Academy of Sciences Shenzhen Hospital, Guangming, Shenzhen, China
| | - Hong Gao
- Department of Urology, University of Chinese Academy of Sciences Shenzhen Hospital, Guangming, Shenzhen, China
| | - Rongfang Liang
- Department of Urology, University of Chinese Academy of Sciences Shenzhen Hospital, Guangming, Shenzhen, China
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Xu Y, Wang C, Li S, Zhou H, Feng Y. Prognosis and immune response of a cuproptosis-related lncRNA signature in low grade glioma. Front Genet 2022; 13:975419. [PMID: 36338998 PMCID: PMC9633682 DOI: 10.3389/fgene.2022.975419] [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: 06/28/2022] [Accepted: 10/10/2022] [Indexed: 11/25/2022] Open
Abstract
Cuproptosis is a newly discovered new mechanism of programmed cell death, and its unique pathway to regulate cell death is thought to have a unique role in understanding cancer progression and guiding cancer therapy. However, this regulation has not been studied in low grade glioma (LGG) at present. In this study, data on low grade glioma patients were downloaded from the TCGA database. We screened the genes related to cuproptosis from the published papers and confirmed the lncRNAs related to them. We applied univariate/multivariate, and LASSO regression algorithms, finally identified 11 lncRNAs for constructing prognosis prediction models, and constructed a risk scoring model. The reliability and validity test of the model indicated that the model could well distinguish the prognosis and survival of LGG patients. Furthermore, the analyses of immunotherapy, immune microenvironment, as well as functional enrichment were also performed. Finally, we verified the expression of these six prognostic key lncRNAs using real-time polymerase chain reaction (RT-PCR). In conclusion, this study is the first analysis based on cuproptosis-related lncRNAs in LGG and aims to open up new directions for LGG therapy.
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Affiliation(s)
- Yifan Xu
- *Correspondence: Yifan Xu, ; Yugong Feng,
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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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Tan W, Yuan Y, Huang H, Ma J, Li Y, Gou Y, Wu H, Hu Z. Comprehensive analysis of autophagy related long non-coding RNAs in prognosis, immunity, and treatment of muscular invasive bladder cancer. Sci Rep 2022; 12:11242. [PMID: 35787635 PMCID: PMC9253343 DOI: 10.1038/s41598-022-13952-1] [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: 02/05/2022] [Accepted: 05/31/2022] [Indexed: 02/08/2023] Open
Abstract
To predict disease outcome in muscle-invasive bladder cancer (MIBC), we constructed a prognostic autophagy-related (PAR) lncRNA signature. Comprehensive bioinformatics analyses were performed using data from TCGA and GTEx databases. Univariate Cox, and least absolute shrinkage and selection operator regression analyses were also performed, based on differentially expressed genes, to identify PAR-related lncRNAs to establish the signature. Furthermore, the Kaplan–Meier OS curve and receiver operating characteristic curve analyses were performed and a nomogram was constructed, all of which together confirmed the strong predictive ability of the constructed signature. Patients with MIBC were then divided into high- and low-risk groups. Gene enrichment and immune infiltration analyses revealed the potential mechanisms in MIBC. We also further evaluated the signature of molecules related to immune checkpoints and the sensitivity toward chemotherapeutic agents and antitumor-targeted drugs to find better treatment prescriptions. We identified a number of PAR-related lncRNA signatures, including HCP5, AC024060.1, NEAT1, AC105942.1, XIST, MAFG-DT, and NR2F1-AS1, which could be valuable prognostic tools to develop more efficient, individualized drug therapies for MIBC patients.
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Affiliation(s)
- Wei Tan
- Department of Urology Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Ye Yuan
- Department of Urology Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Hao Huang
- Department of Urology Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Junhao Ma
- Department of Urology Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yadong Li
- Department of Urology Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yuanqing Gou
- Department of Urology Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Hao Wu
- Department of Urology Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
| | - Zili Hu
- Department of Urology Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
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Hou J, Lu Z, Dong R, Wu G, Nie H, Yang G, Tang C, Qu G, Xu Y. A Necroptosis-Related lncRNA to Develop a Signature to Predict the Outcome, Immune Landscape, and Chemotherapeutic Responses in Bladder Urothelial Carcinoma. Front Oncol 2022; 12:928204. [PMID: 35814472 PMCID: PMC9270023 DOI: 10.3389/fonc.2022.928204] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 05/18/2022] [Indexed: 12/24/2022] Open
Abstract
Objective Many studies have drawn their attention to the immunotherapy of bladder urothelial carcinoma in terms of immunologic mechanisms of human body. These include immunogenicity of the tumor cells and involvement of long non-coding RNA (lncRNA). We constructed a necroptosis-related long noncoding RNA (nrlncRNA) risk factor model to predict BLCA outcomes and calculate correlations with chemosensitivity and immune infiltration. Methods Transcriptomic data from BLCA specimens were accessed from The Cancer Genome Atlas, and nrlncRNAs were identified by performing co-expression analysis. Univariate analysis was performed to identify differentially expressed nrlncRNA pairs. We constructed least absolute contraction and selector operation regression models and drew receiver operating characteristic curves for 1-, 3-, and 5-year survival rates. Akaike information criterion (AIC) values for survival over 1 year were determined as cutoff values in high- and low-risk subgroups. We reassessed the differences between subgroups in terms of survival, clinicopathological characteristics, chemotherapy efficacy, tumor-infiltrating immune cells, and markers of immunosuppression. Results We identified a total of 260 necroptosis-related lncRNA pairs, of which we incorporated 13 into the prognostic model. Areas under the curve of 1-, 3-, and 5- year survival time were 0.763, 0.836, and 0.842, respectively. We confirmed the excellent predictive performance of the risk model. Based on AIC values, we confirmed that the high-risk group was susceptible to unfavorable outcomes. The risk scores correlated with survival were age, clinical stage, grade, and tumor node metastases. The risk model was an independent predictor and demonstrated higher predictive power. The risk model can also be utilized to determine immune cell infiltration status, expression levels of immune checkpoint genes, and the sensitivity to cisplatin, doxorubicin, and methotrexate. Conclusion We constructed a novel necroptosis-related signature that predicts BLCA outcomes and performs satisfactorily in the immune landscape and chemotherapeutic responses.
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Affiliation(s)
- Jian Hou
- Department of Urology, Zhuzhou Central Hospital, Zhuzhou, China
- Division of Urology, Department of Surgery, The University of Hongkong-ShenZhen Hospital, ShenZhen, China
| | - Zhenquan Lu
- Division of Urology, Department of Surgery, The University of Hongkong-ShenZhen Hospital, ShenZhen, China
| | - Runan Dong
- Division of Urology, Department of Surgery, The University of Hongkong-ShenZhen Hospital, ShenZhen, China
| | - Guoqing Wu
- Division of Urology, Department of Surgery, The University of Hongkong-ShenZhen Hospital, ShenZhen, China
| | - Haibo Nie
- Department of Urology, Zhuzhou Central Hospital, Zhuzhou, China
| | - Guang Yang
- Department of Urology, Zhuzhou Central Hospital, Zhuzhou, China
| | - Cheng Tang
- Department of Urology, Zhuzhou Central Hospital, Zhuzhou, China
| | - Genyi Qu
- Department of Urology, Zhuzhou Central Hospital, Zhuzhou, China
- *Correspondence: Genyi Qu, ; Yong Xu,
| | - Yong Xu
- Department of Urology, Zhuzhou Central Hospital, Zhuzhou, China
- *Correspondence: Genyi Qu, ; Yong Xu,
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Li J, Zhang J, Tao S, Hong J, Zhang Y, Chen W. Prognostication of Pancreatic Cancer Using The Cancer Genome Atlas Based Ferroptosis-Related Long Non-Coding RNAs. Front Genet 2022; 13:838021. [PMID: 35237306 PMCID: PMC8883032 DOI: 10.3389/fgene.2022.838021] [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: 12/17/2021] [Accepted: 01/18/2022] [Indexed: 12/20/2022] Open
Abstract
Background: Long non-coding RNAs (lncRNAs) are key regulators of pancreatic cancer development and are involved in ferroptosis regulation. LncRNA transcript levels serve as a prognostic factor for pancreatic cancer. Therefore, identifying ferroptosis-related lncRNAs (FRLs) with prognostic value in pancreatic cancer is critical. Methods: In this study, FRLs were identified by combining The Cancer Genome Atlas (TCGA) and FerrDb databases. For training cohort, univariate Cox, Lasso, and multivariate Cox regression analyses were applied to identify prognosis FRLs and then construct a prognostic FRLs signature. Testing cohort and entire cohort were applied to validate the prognostic signature. Moreover, the nomogram was performed to predict prognosis at different clinicopathological stages and risk scores. A co-expression network with 76 lncRNA-mRNA targets was constructed. Results: Univariate Cox analysis was performed to analyze the prognostic value of 193 lncRNAs. Furthermore, the least absolute shrinkage and selection operator and the multivariate Cox analysis were used to assess the prognostic value of these ferroptosis-related lncRNAs. A prognostic risk model, of six lncRNAs, including LINC01705, AC068620.2, TRAF3IP2-AS1, AC092171.2, AC099850.3, and MIR193BHG was constructed. The Kaplan Meier (KM) and time-related receiver operating characteristic (ROC) curve analysis were performed to calculate overall survival and compare high- and low-risk groups. There was also a significant difference in survival time between the high-risk and low-risk groups for the testing cohort and the entire cohort, with AUCs of .723, .753, respectively. Combined with clinicopathological characteristics, the risk model was validated as a new independent prognostic factor for pancreatic adenocarcinoma through univariate and multivariate Cox regression. Moreover, a nomogram showed good prediction. Conclusion: The signature of six FRLs had significant prognostic value for pancreatic adenocarcinoma. They may be a promising therapeutic target in clinical practice.
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Affiliation(s)
- Jiayu Li
- The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Jinghui Zhang
- School of Life Sciences, Zhejiang Chinese Medical University, Hangzhou, China
| | - Shuiliang Tao
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, China
| | - Jiaze Hong
- The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yuyan Zhang
- School of Life Sciences, Zhejiang Chinese Medical University, Hangzhou, China
- *Correspondence: Yuyan Zhang, ; Weiyan Chen,
| | - Weiyan Chen
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, China
- *Correspondence: Yuyan Zhang, ; Weiyan Chen,
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