A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma
Background and purpose: Radioresistance remains a major reason of radiotherapeutic failure in esophageal squamous cell carcinoma (ESCC). Our study is to screen the immune-related long non-coding RNA (ir-lncRNAs) of radiation-resistant ESCC (rr-ESCC) via Gene Expression Omnibus (GEO) database and to...
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Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.921902/full |
| _version_ | 1828112433480204288 |
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| author | Jianqing Zheng Jianqing Zheng Jianqing Zheng Xiaohui Chen Xiaohui Chen Xiaohui Chen Bifen Huang Jiancheng Li Jiancheng Li Jiancheng Li |
| author_facet | Jianqing Zheng Jianqing Zheng Jianqing Zheng Xiaohui Chen Xiaohui Chen Xiaohui Chen Bifen Huang Jiancheng Li Jiancheng Li Jiancheng Li |
| author_sort | Jianqing Zheng |
| collection | DOAJ |
| description | Background and purpose: Radioresistance remains a major reason of radiotherapeutic failure in esophageal squamous cell carcinoma (ESCC). Our study is to screen the immune-related long non-coding RNA (ir-lncRNAs) of radiation-resistant ESCC (rr-ESCC) via Gene Expression Omnibus (GEO) database and to construct a prognostic risk model.Methods: Microarray data (GSE45670) related to radioresistance of ESCC was downloaded from GEO. Based on pathologic responses after chemoradiotherapy, patients were divided into a non-responder (17 samples) and responder group (11 samples), and the difference in expression profiles of ir-lncRNAs were compared therein. Ir-lncRNA pairs were constructed for the differentially expressed lncRNAs as prognostic variables, and the microarray dataset (GSE53625) was downloaded from GEO to verify the effect of ir-lncRNA pairs on the long-term survival of ESCC. After modelling, patients are divided into high- and low-risk groups according to prognostic risk scores, and the outcomes were compared within groups based on the COX proportional hazards model. The different expression of ir-lncRNAs were validated using ECA 109 and ECA 109R cell lines via RT-qPCR.Results: 26 ir-lncRNA genes were screened in the GSE45670 dataset with differential expression, and 180 ir-lncRNA pairs were constructed. After matching with ir-lncRNA pairs constructed by GSE53625, six ir-lncRNA pairs had a significant impact on the prognosis of ESCC from univariate analysis model, of which three ir-lncRNA pairs were significantly associated with prognosis in multivariate COX analysis. These three lncRNA pairs were used as prognostic indicators to construct a prognostic risk model, and the predicted risk scores were calculated. With a median value of 2.371, the patients were divided into two groups. The overall survival (OS) in the high-risk group was significantly worse than that in the low-risk group (p < 0.001). The 1-, 2-, and 3-year prediction performance of this risk-model was 0.666, 0.702, and 0.686, respectively. In the validation setting, three ir-lncRNAs were significantly up-regulated, while two ir-lncRNAs were obviouly down-regulated in the responder group.Conclusion: Ir-lncRNAs may be involved in the biological regulation of radioresistance in patients with ESCC; and the prognostic risk-model, established by three ir-lncRNAs pairs has important clinical value in predicting the prognosis of patients with rr-ESCC. |
| first_indexed | 2024-04-11T11:49:05Z |
| format | Article |
| id | doaj.art-ce40a224a51144a0b40427125af4e515 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-11T11:49:05Z |
| publishDate | 2022-09-01 |
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| series | Frontiers in Genetics |
| spelling | doaj.art-ce40a224a51144a0b40427125af4e5152022-12-22T04:25:25ZengFrontiers Media S.A.Frontiers in Genetics1664-80212022-09-011310.3389/fgene.2022.921902921902A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinomaJianqing Zheng0Jianqing Zheng1Jianqing Zheng2Xiaohui Chen3Xiaohui Chen4Xiaohui Chen5Bifen Huang6Jiancheng Li7Jiancheng Li8Jiancheng Li9Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaDepartment of Radiation Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, ChinaThe Graduate School of Fujian Medical University, Fuzhou, Fujian, ChinaClinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaThe Graduate School of Fujian Medical University, Fuzhou, Fujian, ChinaDepartment of Thoracic Surgery, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaDepartment of Obstetrics and Gynecology, Quanzhou Medical College People’s Hospital Affiliated, Fuzhou, Fujian, ChinaClinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaThe Graduate School of Fujian Medical University, Fuzhou, Fujian, ChinaDepartment of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaBackground and purpose: Radioresistance remains a major reason of radiotherapeutic failure in esophageal squamous cell carcinoma (ESCC). Our study is to screen the immune-related long non-coding RNA (ir-lncRNAs) of radiation-resistant ESCC (rr-ESCC) via Gene Expression Omnibus (GEO) database and to construct a prognostic risk model.Methods: Microarray data (GSE45670) related to radioresistance of ESCC was downloaded from GEO. Based on pathologic responses after chemoradiotherapy, patients were divided into a non-responder (17 samples) and responder group (11 samples), and the difference in expression profiles of ir-lncRNAs were compared therein. Ir-lncRNA pairs were constructed for the differentially expressed lncRNAs as prognostic variables, and the microarray dataset (GSE53625) was downloaded from GEO to verify the effect of ir-lncRNA pairs on the long-term survival of ESCC. After modelling, patients are divided into high- and low-risk groups according to prognostic risk scores, and the outcomes were compared within groups based on the COX proportional hazards model. The different expression of ir-lncRNAs were validated using ECA 109 and ECA 109R cell lines via RT-qPCR.Results: 26 ir-lncRNA genes were screened in the GSE45670 dataset with differential expression, and 180 ir-lncRNA pairs were constructed. After matching with ir-lncRNA pairs constructed by GSE53625, six ir-lncRNA pairs had a significant impact on the prognosis of ESCC from univariate analysis model, of which three ir-lncRNA pairs were significantly associated with prognosis in multivariate COX analysis. These three lncRNA pairs were used as prognostic indicators to construct a prognostic risk model, and the predicted risk scores were calculated. With a median value of 2.371, the patients were divided into two groups. The overall survival (OS) in the high-risk group was significantly worse than that in the low-risk group (p < 0.001). The 1-, 2-, and 3-year prediction performance of this risk-model was 0.666, 0.702, and 0.686, respectively. In the validation setting, three ir-lncRNAs were significantly up-regulated, while two ir-lncRNAs were obviouly down-regulated in the responder group.Conclusion: Ir-lncRNAs may be involved in the biological regulation of radioresistance in patients with ESCC; and the prognostic risk-model, established by three ir-lncRNAs pairs has important clinical value in predicting the prognosis of patients with rr-ESCC.https://www.frontiersin.org/articles/10.3389/fgene.2022.921902/fullradioresistanceesophageal squamous cell carcinomalncRNAprognostic modelbioinformatics |
| spellingShingle | Jianqing Zheng Jianqing Zheng Jianqing Zheng Xiaohui Chen Xiaohui Chen Xiaohui Chen Bifen Huang Jiancheng Li Jiancheng Li Jiancheng Li A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma Frontiers in Genetics radioresistance esophageal squamous cell carcinoma lncRNA prognostic model bioinformatics |
| title | A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma |
| title_full | A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma |
| title_fullStr | A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma |
| title_full_unstemmed | A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma |
| title_short | A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma |
| title_sort | novel immune related radioresistant lncrnas signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma |
| topic | radioresistance esophageal squamous cell carcinoma lncRNA prognostic model bioinformatics |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.921902/full |
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