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Retraction: Identification of immune-related lncRNAs to improve the prognosis prediction for patients with papillary thyroid cancer. Biosci Rep 2024; 44. [PMID: 38477046 DOI: 10.1042/BSR-2020-4086_RET] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2024] Open
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2
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Ding X, Liang W, Xia H, Liu Y, Liu S, Xia X, Zhu X, Pei Y, Zhang D. Analysis of Immune and Prognostic-Related lncRNA PRKCQ-AS1 for Predicting Prognosis and Regulating Effect in Sepsis. J Inflamm Res 2024; 17:279-299. [PMID: 38229689 PMCID: PMC10790647 DOI: 10.2147/jir.s433057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 12/07/2023] [Indexed: 01/18/2024] Open
Abstract
Background Sepsis was a high mortality and great harm systemic inflammatory response syndrome caused by infection. lncRNAs were potential prognostic marker and therapeutic target. Therefore, we expect to screen and analyze lncRNAs with potential prognostic markers in sepsis. Methods Transcriptome sequencing and limma was used to screen dysregulated RNAs. Key RNAs were screened by correlation analysis, lncRNA-mRNA co-expression and weighted gene co-expression network analysis. Immune infiltration, gene set enrichment analysis and gene set variation analysis were used to analyze the immune correlation. Kaplan-Meier curve, receiver operator characteristic curve, Cox regression analysis and nomogram were used to analyze the correlation between key RNAs and prognosis. Sepsis model was established by lipopolysaccharide-induced HUVECs injury, and then cell viability and migration ability were detected by cell counting kit-8 and wound healing assay. The levels of apoptosis-related proteins and inflammatory cytokines were detected by RT-qPCR and Western blot. Reactive Oxygen Species and superoxide dismutase were detected by commercial kit. Results Fourteen key differentially expressed lncRNAs and 663 key differentially expressed genes were obtained. And these lncRNAs were closely related to immune cells, especially T cell activation, immune response and inflammation. Subsequently, Subsequently, lncRNA PRKCQ-AS1 was identified as the regulator for further investigation in sepsis. RT-qPCR results showed that PRKCQ-AS1 expression was up-regulated in clinical samples and sepsis model cells, which was an independent prognostic factor in sepsis patients. Immune correlation analysis showed that PRKCQ-AS1 was involved in the immune response and inflammatory process of sepsis. Cell function tests confirmed that PRKCQ-AS1 could inhibit sepsis model cells viability and promote cell apoptosis, inflammatory damage and oxidative stress. Conclusion We constructed immune-related lncRNA-mRNA regulatory networks in the progression of sepsis and confirmed that PRKCQ-AS1 is an important prognostic factor affecting the progression of sepsis and is involved in immune response.
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Affiliation(s)
- Xian Ding
- Department of Emergency, Third Affiliated Hospital of Naval Medical University, Shanghai, People’s Republic of China
| | - Wenqi Liang
- Department of Emergency, Shanghai Changhai Hospital, Naval Medical University, Shanghai, People’s Republic of China
| | - Hongjuan Xia
- Department of Emergency, Third Affiliated Hospital of Naval Medical University, Shanghai, People’s Republic of China
| | - Yuee Liu
- Department of Emergency, Shanghai Changhai Hospital, Naval Medical University, Shanghai, People’s Republic of China
| | - Shuxiong Liu
- Department of Emergency, Third Affiliated Hospital of Naval Medical University, Shanghai, People’s Republic of China
| | - Xinyu Xia
- Department of Emergency, Third Affiliated Hospital of Naval Medical University, Shanghai, People’s Republic of China
| | - Xiaoli Zhu
- Department of Emergency, Third Affiliated Hospital of Naval Medical University, Shanghai, People’s Republic of China
| | - Yongyan Pei
- School of Chemistry and Chemical Engineering, Guangdong Pharmaceutical University, Zhongshan, People’s Republic of China
| | - Dewen Zhang
- Longhua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
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Zheng P, Zhang X, Ren D, Bai Q, Jiang P. Novel Immune-Related LncRNA Pairs are Associated with Immunol Infiltration and Survival Status in Glioblastoma. Neurol India 2023; 71:1226-1234. [PMID: 38174463 DOI: 10.4103/0028-3886.391381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Background Immune-related lncRNA is involved in tumor initiation and progression, while its effect in glioblastoma (GBM) is still unknown. Objective We sought to investigate the association between immune-related lncRNA (ir-lncRNA) and GBM. Methods Transcriptomic and clinical data were obtained from the TCGA dataset, and we found 2008 ir-lncRNA differentially expressed between GBM and adjacent brain tissues. Results Appling the univariate Cox and Lasso regression model, we found 30 prognosis-related ir-lncRNA pairs to construct a Cox regression risk model to associate the outcome of GBM patients. Furthermore, with this risk model, we can identify the tumor immune infiltration status, the expression of immunosuppressive biomarkers, and chemical sensitivity in GBM patients. Conclusions We constructed an immunologic risk model with lncRNA to associate the survival outcome of GBM patients, which can provide useful biomarkers.
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Affiliation(s)
- Ping Zheng
- Department of Neurosurgery, Shanghai Pudong New Area People's Hospital; Key Molecular Lab, Shanghai Pudong New Area People's Hospital, Shanghai, China
| | - Xiaoxue Zhang
- Key Molecular Lab, Shanghai Pudong New Area People's Hospital, Shanghai, China
| | - Dabin Ren
- Department of Neurosurgery, Shanghai Pudong New Area People's Hospital, Shanghai, China
| | - Qingke Bai
- Department of Neurology, Shanghai Pudong New Area People's Hospital, Shanghai, China
| | - Ping Jiang
- Department of Nursing, Shanghai Pudong New Area People's Hospital, Shanghai, China
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Zeng Z, Liang Y, Shi J, Xiao L, Tang L, Guo Y, Chen F, Lin G. Identification and Application of a Novel Immune-Related lncRNA Signature on the Prognosis and Immunotherapy for Lung Adenocarcinoma. Diagnostics (Basel) 2022; 12. [PMID: 36428951 DOI: 10.3390/diagnostics12112891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 11/14/2022] [Accepted: 11/16/2022] [Indexed: 11/23/2022] Open
Abstract
Background: Long non-coding RNA (lncRNA) participates in the immune regulation of lung cancer. However, limited studies showed the potential roles of immune-related lncRNAs (IRLs) in predicting survival and immunotherapy response of lung adenocarcinoma (LUAD). Methods: Based on The Cancer Genome Atlas (TCGA) and ImmLnc databases, IRLs were identified through weighted gene coexpression network analysis (WGCNA), Cox regression, and Lasso regression analyses. The predictive ability was validated by Kaplan−Meier (KM) and receiver operating characteristic (ROC) curves in the internal dataset, external dataset, and clinical study. The immunophenoscore (IPS)-PD1/PD-L1 blocker and IPS-CTLA4 blocker data of LUAD were obtained in TCIA to predict the response to immune checkpoint inhibitors (ICIs). The expression levels of immune checkpoint molecules and markers for hyperprogressive disease were analyzed. Results: A six-IRL signature was identified, and patients were stratified into high- and low-risk groups. The low-risk had improved survival outcome (p = 0.006 in the training dataset, p = 0.010 in the testing dataset, p < 0.001 in the entire dataset), a stronger response to ICI (p < 0.001 in response to anti-PD-1/PD-L1, p < 0.001 in response to anti-CTLA4), and higher expression levels of immune checkpoint molecules (p < 0.001 in PD-1, p < 0.001 in PD-L1, p < 0.001 in CTLA4) but expressed more biomarkers of hyperprogression in immunotherapy (p = 0.002 in MDM2, p < 0.001 in MDM4). Conclusion: The six-IRL signature exhibits a promising prediction value of clinical prognosis and ICI efficacy in LUAD. Patients with low risk might gain benefits from ICI, although some have a risk of hyperprogressive disease.
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Gao M, Liu S, Qi Y, Guo X, Shang X. ImReLnc: Identifying Immune-Related LncRNA Characteristics in Human Cancers Based on Heuristic Correlation Optimization. Front Genet 2022; 12:792541. [PMID: 35082835 PMCID: PMC8784420 DOI: 10.3389/fgene.2021.792541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Accepted: 12/16/2021] [Indexed: 12/24/2022] Open
Abstract
Long non-coding RNAs (lncRNAs) play critical roles in cancer through gene expression and immune regulation. Identifying immune-related lncRNA (irlncRNA) characteristics would contribute to dissecting the mechanism of cancer pathogenesis. Some computational methods have been proposed to identify irlncRNA characteristics in human cancers, but most of them are aimed at identifying irlncRNA characteristics in specific cancer. Here, we proposed a new method, ImReLnc, to recognize irlncRNA characteristics for 33 human cancers and predict the pathogenicity levels of these irlncRNAs across cancer types. We first calculated the heuristic correlation coefficient between lncRNAs and mRNAs for immune-related enrichment analysis. Especially, we analyzed the relationship between lncRNAs and 17 immune-related pathways in 33 cancers to recognize the irlncRNA characteristics of each cancer. Then, we calculated the Pscore of the irlncRNA characteristics to evaluate their pathogenicity levels. The results showed that highly pathogenic irlncRNAs appeared in a higher proportion of known disease databases and had a significant prognostic effect on cancer. In addition, it was found that the expression of irlncRNAs in immune cells was higher than that of non-irlncRNAs, and the proportion of irlncRNAs related to the levels of immune infiltration was much higher than that of non-irlncRNAs. Overall, ImReLnc accurately identified the irlncRNA characteristics in multiple cancers based on the heuristic correlation coefficient. More importantly, ImReLnc effectively evaluated the pathogenicity levels of irlncRNAs across cancer types. ImReLnc is freely available at https://github.com/meihonggao/ImReLnc.
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Affiliation(s)
- Meihong Gao
- School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China
| | - Shuhui Liu
- School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China
| | - Yang Qi
- School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China
| | - Xinpeng Guo
- School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China
| | - Xuequn Shang
- School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China
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Sun M, Zhang T, Wang Y, Huang W, Xia L. A Novel Signature Constructed by Immune-Related LncRNA Predicts the Immune Landscape of Colorectal Cancer. Front Genet 2021; 12:695130. [PMID: 34434220 PMCID: PMC8381735 DOI: 10.3389/fgene.2021.695130] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 07/12/2021] [Indexed: 12/13/2022] Open
Abstract
Colorectal cancer (CRC) has the characteristics of high morbidity and mortality. LncRNA not only participates in the progression of CRC through genes and transcription levels, but also regulates the tumor microenvironment and leads to the malignant phenotype of tumors. Therefore, we identified immune-related LncRNAs for the construction of clinical prognostic model. We searched The Cancer Genome Atlas (TCGA) database for original data. Then we identified differentially expressed irlncRNA (DEirlncRNA), which was paired and verified subsequently. Next, univariate analysis, Lasso and Cox regression analysis were performed on the DEirlncRNA pair. The ROC curve of the signature was drawn, and the optimal cut-off value was found. Then the cohort was divided into a high-risk and a low-risk group. Finally, we re-evaluated the signature from different perspectives. A total of 16 pairs of DEirlncRNA were included in the construction of the model. After regrouping according to the cut-off value of 1.275, the high-risk group showed adverse survival outcomes, progressive clinicopathological features, specific immune cell infiltration status, and high sensitivity to some chemotherapy drugs. In conclusion, we constructed a signature composed of immune-related LncRNA pair with no requirement of the specific expression level of genes, which shows promising clinical predictive value in CRC patients.
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Affiliation(s)
- Mengyu Sun
- Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Key Laboratory of Hepato-Pancreato- Biliary Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tongyue Zhang
- Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Key Laboratory of Hepato-Pancreato- Biliary Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yijun Wang
- Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Key Laboratory of Hepato-Pancreato- Biliary Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenjie Huang
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Key Laboratory of Hepato-Pancreato- Biliary Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Limin Xia
- Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Key Laboratory of Hepato-Pancreato- Biliary Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Qi X, Chen G, Chen Z, Li J, Chen W, Lin J, Lin L. Construction of a Novel Lung Adenocarcinoma Immune-Related lncRNA Pair Signature. Int J Gen Med 2021; 14:4279-4289. [PMID: 34421308 PMCID: PMC8371455 DOI: 10.2147/ijgm.s325240] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 07/29/2021] [Indexed: 12/22/2022] Open
Abstract
Background A growing number of studies have demonstrated that immune-related long noncoding ribonucleic acids (irlncRNAs) are potential prognostic factors for lung adenocarcinoma. Two-gene combination patterns could improve the sensitivity of prognostic models, providing us a novel signature construction concept that we applied to lung adenocarcinoma. Methods Gene expression and clinical data were downloaded from the Lung Adenocarcinoma project of The Cancer Genome Atlas (TCGA) database. We applied a co-expression analysis with immune genes obtained from the ImmPort database to recognize irlncRNA. The matrix of irlncRNA pairs was established by a cyclic comparison of each lncRNA pair expression level. Univariate and multivariate Cox regressions and Lasso penalized regression analysis were applied to construct the risk model. Patients with lung adenocarcinoma were divided into high- and low-risk groups, according to the Akaike Information Criterion (AIC) values of the receiver operating characteristic (ROC) curve. Then, we evaluated our signature under various clinical settings: clinical-pathological characteristics, tumor-infiltrating immune cells, checkpoint-related biomarkers, targeted therapy, and chemotherapy. Results Based on the 239 differently expressed irlncRNAs, we constructed an 11-irlncRNA pair signature. The area under the curve (AUC) of the ROC curve for the signature to predict the 4-year survival rate was 0.819, and the cut-off point was recognized as 1.003. Subsequent analysis showed that our signature can effectively distinguish unfavorable survival outcomes, prognostic clinic-pathological characteristics, and specify tumor infiltration status. Highly expressed immune checkpoint-related genes, as well as higher chemosensitivity, were correlated to the low-risk group. Conclusion We constructed a novel lung adenocarcinoma irlncRNA signature with promising prognostic value using the TCGA database, based on paired irlncRNAs and not relying on lncRNAs special expression levels.
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Affiliation(s)
- Xiangjun Qi
- The First Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China
| | - Guoming Chen
- The First Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China
| | - Zhuangzhong Chen
- Department of Oncology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China
| | - Jing Li
- The First Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China.,Department of Oncology, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, People's Republic of China
| | - Wenmin Chen
- The First Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China
| | - Jietao Lin
- Department of Oncology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China
| | - Lizhu Lin
- Department of Oncology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China.,Cancer Project Team of China Center for Evidence Based Traditional Chinese Medicine, Guangzhou, People's Republic of China
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8
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Liu J, Wu H, Gao Z, Lou M, Yuan K. Construction of an immune-related lncRNA pairs model to predict prognosis and immune landscape of lung adenocarcinoma patients. Bioengineered 2021; 12:4123-4135. [PMID: 34288805 PMCID: PMC8806830 DOI: 10.1080/21655979.2021.1953215] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
The model of immune-related lncRNA pairs (IRLPs) seems to be an available predictor in lung adenocarcinoma (LUAD) patients. The aim of our study was to construct a model with IRLPs to predict the survival status and immune landscape of LUAD patients. Based on TCGA-LUAD dataset, a risk assessment model with IRLPs was established. Then, ROC curves were used to assess the predictive accuracy and effectiveness of our model. Next, we identified the difference of survival, immune cell infiltration, immune checkpoint inhibitor-related (ICI-related) biomarkers, and chemotherapeutics between high-risk group and low-risk group. Finally, A nomogram was built for predicting the survival rates of LUAD patients. 464 LUAD samples were randomly and equally divided into a training set and a test set. Six IRLPs were screened out to construct a risk model. K-M analysis and risk-plot suggested the prognosis of high-risk group was worse than low-risk group (p < 0.001). Multivariate analysis shows risk score was independent risk factor of LUAD (p < 0.001). In addition, the expression of immune cell infiltration, ICI-related biomarkers, chemotherapeutics all demonstrate significant difference in two groups. A nomogram was built that could predict the 1-, 3-, and 5-year survival rates of LUAD patients. Our immune-related lncRNA pairs risk model is expected to be a reliable model for predicting the prognosis and immune landscape of LUAD patients.
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Affiliation(s)
- Junhui Liu
- Division of Thoracic Surgery, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, China.,School of Medicine, Dalian Medical University, Dalian, China
| | - Hao Wu
- School of Medicine, Dalian Medical University, Dalian, China
| | - Zhaojia Gao
- Division of Thoracic Surgery, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, China.,Heart and Lung Disease Laboratory, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, China
| | - Ming Lou
- Division of Thoracic Surgery, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, China
| | - Kai Yuan
- Division of Thoracic Surgery, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, China.,Heart and Lung Disease Laboratory, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, China
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Wei J, Fang DL, Huang CK, Hua SL, Lu XS. Screening a novel signature and predicting the immune landscape of metastatic osteosarcoma in children via immune-related lncRNAs. Transl Pediatr 2021; 10:1851-1866. [PMID: 34430433 PMCID: PMC8349967 DOI: 10.21037/tp-21-226] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Accepted: 06/15/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND The immune microenvironment plays an essential role in osteosarcoma (OSs); however, differences in immune-related long non-coding ribonucleic acids (irlncRNAs) in children with localized OSs and metastatic OSs have not yet been investigated. METHODS The clinical data and the transcriptome of OSs were obtained from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, and the immune-related genes were derived from the imported dataset. The correlations between immune-related genes and lncRNAs were examined. Next, the differential expressions of the irlncRNA pairs (IRLPs) in localized OSs and distant metastatic OSs were analyzed, and a prognostic model was constructed based on the significant differentially expressed IRLPs. We also analyzed the association between the IRLPs' signature risk score and the infiltration of the immune cells. Finally, we investigated the correlation between risk score and drug resistance. RESULTS Thirty upregulated and 22 downregulated lncRNAs were identified in the localized and metastatic OSs samples. Univariate and multivariate cox regression analyses were undertaken to select 6 lncRNA pairs to establish the prognostic signature, the model was valuable in predicting OSs prognosis. Further, the expression of the finally selected irlncRNAs indicated that VPS9D1-AS1 (P=0.031), AP003086.2 (P=0.041), AL031847.1 (P=0.008), AL020997.3 (P=0.020), AC011444.1 (P=0.025), and AC006449.2 (P=0.003) were significantly upregulated in metastasis patients, but USP27X-AS1 (P=0.046), AL008721.2 (P=0.005), AC002091.1 (P=0.033), and AL118558.4 (P=0.049) were significantly overexpressed in localized patients. The overexpression of AC002091.1 (P=0.038) and AL118558.4 (P=0.004) resulted in better overall survival, but the upregulation of AC011444.1 (P=0.045), AL031847.1 (P=0.020), VPS9D1-AS1 (P=0.039), and AC006449.2 (0.006) led to a poor outcome. Differences in immune cell infiltration indicated that metastatic patients and localized have significant difference of 4 (CD4) T cells (P=0.006), monocytes (P=0.029), activated mast cells (P=0.018), and neutrophils (P=0.026), and a high abundance of activated dendritic cells (P=0.010) and activated mast cells (P=0.049) resulted in poor prognosis. Patients in the high-risk-score group were resistant to axitinib, but sensitive to dasatinib, bortezomib, and cisplatin. CONCLUSIONS In the present study, IRLPs were used to construct a novel and practical model for predicting the prognosis of localized and metastatic OSs in children.
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Affiliation(s)
- Jie Wei
- Department of Hematology, Baise People's Hospital, Baise, China
| | - Da-Lang Fang
- Department of Breast and Thyroid Surgery, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
| | - Cheng Kua Huang
- Department of Traumatology, Baise People's Hospital, Baise, China
| | - Shu-Liang Hua
- Department of Traumatology, Baise People's Hospital, Baise, China
| | - Xiao-Sheng Lu
- Department of Traumatology, Baise People's Hospital, Baise, China
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Zhang B, Wang R, Li K, Peng Z, Liu D, Zhang Y, Zhou L. An Immune-Related lncRNA Expression Profile to Improve Prognosis Prediction for Lung Adenocarcinoma: From Bioinformatics to Clinical Word. Front Oncol 2021; 11:671341. [PMID: 33968781 PMCID: PMC8100529 DOI: 10.3389/fonc.2021.671341] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 03/29/2021] [Indexed: 12/15/2022] Open
Abstract
Background Lung cancer is still the top-ranked cancer-related deaths all over the world. Now immunotherapy has emerged as a promising option for treating lung cancer. Recent evidence indicated that lncRNAs were also key regulators in immune system. We aimed to develop a novel prognostic signature based on the comprehensive analysis of immune-related lncRNAs to predict survival outcome of LUAD patients. Methods The gene expression profiles of 491 LUAD patients were downloaded from TCGA. 1047 immune-related lncRNAs were obtained through Pearson correlation analysis of immune genes and lncRNAs using statistical software R language. Univariate and multivariate Cox regression analysis were performed to determine the optimal immune-related lncRNAs prognostic signature (ITGCB-DT, ABALON, TMPO-AS1 and VIM-AS1). Finally, we validated the immune-related lncRNAs prognostic signature in The First Affiliated Hospital of Xi'an Jiaotong University cancer center cohort. Results A four immune-related lncRNAs prognostic signature was constructed to predict the survival outcome of LUAD patients. Statistical significance were found that the LUAD patients in high-risk group suffered shorter overall survival than those in low-risk group (P <0.001). ROC curve analysis shown that the four immune-related lncRNAs prognostic signature had the best predictive effect compared with age, gender, AJCC-stage, T stage, N stage, M stage (AUC = 0.756). More importantly, clinical cohort studies proved that the signature could predict the overall survival of LUAD patients with an AUC = 0.714. Conclusions In summary, we demonstrated that the novel immune-related lncRNAs signature had the ability to predict the prognosis of LUAD patients, which might serve as potential prognostic biomarkers and guide the individualized treatment strategies for LUAD patients.
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Affiliation(s)
- Boxiang Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Rui Wang
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Kai Li
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Ziyang Peng
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Dapeng Liu
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yunfeng Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Liuzhi Zhou
- Department of Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Qin F, Xu H, Wei G, Ji Y, Yu J, Hu C, Yuan C, Ma Y, Qian J, Li L, Huo J. A Prognostic Model Based on the Immune-Related lncRNAs in Colorectal Cancer. Front Genet 2021; 12:658736. [PMID: 33959151 PMCID: PMC8093825 DOI: 10.3389/fgene.2021.658736] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 03/22/2021] [Indexed: 12/12/2022] Open
Abstract
Background Colorectal cancer (CRC) is one of the most common malignant tumors with a poor prognosis. At present, the pathogenesis is not completely clear. Therefore, finding reliable prognostic indicators for CRC is of important clinical significance. In this study, bioinformatics methods were used to screen the prognostic immune-related lncRNAs of CRC, and a prognostic risk scoring model based on immune-related lncRNAs signatures were constructed to provide a basis for prognostic evaluation and immunotherapy of CRC patients. Methods The clinical information and RNA-seq data of CRC patients were obtained from The Cancer Genome Atlas (TCGA) database. The information of immune-related lncRNA was downloaded from the immunology database and analysis portal. The differentially expressed immune-related lncRNAs (IRLs) were screened by the edgeR package of R software. The prognostic value of IRLs was studied. Based on Cox regression analysis, a prognostic index (IRLPI) based on IRLs was established, and the relationship between the risk score and the clinicopathological characteristics of CRC was analyzed to determine the effectiveness of the risk score model as an independent prognostic factor. Results A total of 240 differentially expressed IRLs were identified between normal colorectal cancer tissues and normal colorectal cancer tissues, in which 8 were significantly associated with the survival of CRC patients (P < 0.05), including LINC00461, LINC01055, ELFN1-AS1, LMO7-AS1, CYP4A22-AS1, AC079612.1, LINC01351, and MIR31HG. And most of the lncRNAs related to survival were risk factors for the prognosis of CRC. The index established based on the 7 survival-related IRLs found to be highly accurate in monitoring CRC prognosis. Besides, IRLPI was significantly correlated with a variety of pathological factors and immune cell infiltration. Conclusion Eight immune-related lncRNAs closely related to the prognosis of CRC patients were identified from the TCGA database. At the same time, an independent IRLPI was constructed, which may be helpful for clinicians to assess the prognosis of patients with CRC and to formulate individualized treatment plans.
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Affiliation(s)
- Fengxia Qin
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Houxi Xu
- Key Laboratory of Acupuncture and Medicine Research of Ministry of Education, Nanjing University of Chinese Medicine, Nanjing, China
| | - Guoli Wei
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Yi Ji
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Jialin Yu
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Canhong Hu
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Chunyi Yuan
- Department of Oncology, Ganyu District Hospital of Traditional Chinese Medicine, Lianyungang, China
| | - Yuzhu Ma
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Jun Qian
- School of Chinese Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Lingchang Li
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Jiege Huo
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
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Li Z, Lin W, Zheng J, Hong W, Zou J, Zhang T, Chen Y, Lu H. Identification of immune-related lncRNAs to improve the prognosis prediction for patients with papillary thyroid cancer. Biosci Rep 2021; 41:BSR20204086. [PMID: 33554245 PMCID: PMC7902395 DOI: 10.1042/bsr20204086] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 02/05/2021] [Accepted: 02/05/2021] [Indexed: 02/05/2023] Open
Abstract
OBJECTIVE To identify immune-related long non-coding RNAs (lncRNAs) in papillary thyroid cancer (PTC). METHODS The Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were used to obtain the gene expression profile. Immune-related lncRNAs were screened from the Molecular Signatures Database v4.0 (MsigDB). We performed a survival analysis of critical lncRNAs. Further, the function of prognostic lncRNAs was inferred using the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) to clarify the possible mechanisms underlying their predictive ability. The assessment was performed in clinical samples and PTC cells. RESULTS We obtained 4 immune-related lncRNAs, 15 microRNAs (miRNAs), and 375 mRNAs as the key mediators in the pathophysiological processes of PTC from the GEO database. Further, Lasso regression analysis identified seven prognostic markers (LINC02550, SLC26A4-AS1, ACVR2B-AS1, AC005479.2, LINC02454, and AL136366.1), most of which were related to tumor development. The KEGG pathway enrichment analysis showed different, changed genes mainly enriched in the cancer-related pathways, PI3K-Akt signaling pathway, and focal adhesion. Only SLC26A4-AS1 had an intersection in the results of the two databases. CONCLUSION LncRNA SLC26A4-AS1, which is the most associated with prognosis, may play an oncogenic role in the development of PTC.
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Affiliation(s)
- Zhiyang Li
- Department of Thyroid, Breast and Hernia Surgery, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515041, P.R. China
| | - Weixun Lin
- Department of Thyroid, Breast and Hernia Surgery, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515041, P.R. China
| | - Jiehua Zheng
- Department of Thyroid, Breast and Hernia Surgery, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515041, P.R. China
| | - Weida Hong
- Department of Thyroid, Breast and Hernia Surgery, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515041, P.R. China
| | - Juan Zou
- Department of Thyroid, Breast and Hernia Surgery, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515041, P.R. China
| | - Taofeng Zhang
- Department of Thyroid, Breast and Hernia Surgery, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515041, P.R. China
| | - Yexi Chen
- Department of Thyroid, Breast and Hernia Surgery, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515041, P.R. China
| | - Hai Lu
- The Second Affiliated Hospital of GuangZhou University of Chinese Medicine, Guangzhou, Guangdong Province 510282, P.R. China
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province 510282, P.R. China
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13
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Liu J, Mei J, Wang Y, Chen X, Pan J, Tong L, Zhang Y. Development of a novel immune-related lncRNA signature as a prognostic classifier for endometrial carcinoma. Int J Biol Sci 2021; 17:448-459. [PMID: 33613104 PMCID: PMC7893582 DOI: 10.7150/ijbs.51207] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 12/06/2020] [Indexed: 12/13/2022] Open
Abstract
Endometrial carcinoma (EnCa) is one of the deadliest gynecological malignancies. The purpose of the current study was to develop an immune-related lncRNA prognostic signature for EnCa. In the current research, a series of systematic bioinformatics analyses were conducted to develop a novel immune-related lncRNA prognostic signature to predict disease-free survival (DFS) and response to immunotherapy and chemotherapy in EnCa. Based on the newly developed signature, immune status and mutational loading between high‑ and low‑risk groups were also compared. A novel 13-lncRNA signature associated with DFS of EnCa patients was ultimately developed using systematic bioinformatics analyses. The prognostic signature allowed us to distinguish samples with different risks with relatively high accuracy. In addition, univariate and multivariate Cox regression analyses confirmed that the signature was an independent factor for predicting DFS in EnCa. Moreover, a predictive nomogram combined with the risk signature and clinical stage was constructed to accurately predict 1-, 2-, 3-, and 5-year DFS of EnCa patients. Additionally, EnCa patients with different levels of risk had markedly different immune statuses and mutational loadings. Our findings indicate that the immune-related 13-lncRNA signature is a promising classifier for prognosis and response to immunotherapy and chemotherapy for EnCa.
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Affiliation(s)
- Jinhui Liu
- Department of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Jie Mei
- Wuxi School of Clinical Medicine, Nanjing Medical University, Wuxi 214023, Jiangsu, China
| | - Yichun Wang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Xucheng Chen
- College of Pharmacy, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - Jiadong Pan
- Wuxi School of Clinical Medicine, Nanjing Medical University, Wuxi 214023, Jiangsu, China
| | - Laigen Tong
- Department of Hematology, Yixing People's Hospital, The Affiliated Hospital of Jiangsu University, Yixing 214200, Jiangsu, China
| | - Yan Zhang
- Department of Gynecology and Obstetrics, Wuxi Maternal and Child Health Hospital, the Affiliated Hospital of Nanjing Medical University, Wuxi 214000, Jiangsu, China
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Li J, Zhang C, Zhang C, Wang H. Construction of immune-related and prognostic lncRNA clusters and identification of their immune and genomic alterations characteristics in lung adenocarcinoma samples. Aging (Albany NY) 2020; 12:9868-81. [PMID: 32445554 DOI: 10.18632/aging.103251] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Accepted: 04/20/2020] [Indexed: 02/07/2023]
Abstract
Long non-coding RNAs (lncRNAs) play an important role in various biological processes of lung adenocarcinoma (LUAD), such as immune response regulation, tumor microenvironment remodeling and genomic alteration. Nevertheless, immune-related lncRNAs and their immune and genomic alterations characteristics in LUAD samples still remain unreported. Here, using various public databases, statistic and software tools, we constructed two immune-related lncRNA clusters with different immune and genomic alterations characteristics. Notably, cluster 1 had a stronger immunosuppressive tumor microenvironment (TME) and a higher mutation frequency than cluster 2, especially the mutant genes, such as Kelch-like ECH-associated protein 1 (KEAP1) and toll like receptor 4 (TLR4). In cluster 1, both the amplified and deleted portions of copy number variation (CNV) segments were enriched and cyclin dependent kinase inhibitor 2A (CDKN2A) was significantly deleted. GSVA analysis revealed that these immune-related lncRNAs may be involved in stem cell and EMT functions. Furthermore, cluster 1 was related to worse prognosis of LUAD patients. Therefore, we constructed two immune-related and prognostic lncRNA clusters and identified their immune and genomic alterations characteristics in LUAD samples, which could well divide LUAD patients into different immune phenotypes and help to understand immune molecular mechanisms of LUAD.
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