Construction of Prognostic Prediction Model for Lung Squamous Cell Carcinoma Based on Cuproptosis-related LncRNAs
Objective To develop a new risk scoring model based on cuproptosis-related lncRNAs (CRLs) to predict the prognosis of lung squamous cell carcinoma (LUSC). Methods Data were obtained mainly from TCGA and GTEx databases. Univariate Cox, Lasso, and multivariate Cox regression analyses were conducted to...
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| Format: | Article |
| Language: | zho |
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Magazine House of Cancer Research on Prevention and Treatment
2023-11-01
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| Series: | Zhongliu Fangzhi Yanjiu |
| Subjects: | |
| Online Access: | http://www.zlfzyj.com/EN/10.3971/j.issn.1000-8578.2023.23.0370 |
| _version_ | 1797401544593768448 |
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| author | AN Mengxia WANG Pingyu |
| author_facet | AN Mengxia WANG Pingyu |
| author_sort | AN Mengxia |
| collection | DOAJ |
| description | Objective To develop a new risk scoring model based on cuproptosis-related lncRNAs (CRLs) to predict the prognosis of lung squamous cell carcinoma (LUSC). Methods Data were obtained mainly from TCGA and GTEx databases. Univariate Cox, Lasso, and multivariate Cox regression analyses were conducted to determine CRLs that affect the prognosis of LUSC and establish a risk scoring model. The ability of risk score characteristics to independently predict LUSC survival was compared with that of clinical characteristics by calculating the area under the ROC curve (AUC). Immune-related functions and immune checkpoint differences were compared between high- and low-risk groups. Results Nine CRLs were selected as independent prognostic lncRNAs for LUSC, and a risk scoring model was developed. Risk score was the influence factor for the prognosis of LUSC. The AUC values predicted by the risk score model for 1-, 3-, and 5-year survival rates of patients with LUSC were 0.710, 0.718, and 0.743, respectively. The high- and low-risk groups were partly statistically different in terms of immune-related functional assays and immune checkpoint assays (P < 0.05). Conclusion The risk scoring model developed based on nine CRLs could predict the prognosis and immune therapy response of patients with LUSC in clinical practice. |
| first_indexed | 2024-03-09T02:12:36Z |
| format | Article |
| id | doaj.art-54ee816cea26446cac40e4d862784702 |
| institution | Directory Open Access Journal |
| issn | 1000-8578 |
| language | zho |
| last_indexed | 2024-03-09T02:12:36Z |
| publishDate | 2023-11-01 |
| publisher | Magazine House of Cancer Research on Prevention and Treatment |
| record_format | Article |
| series | Zhongliu Fangzhi Yanjiu |
| spelling | doaj.art-54ee816cea26446cac40e4d8627847022023-12-07T07:46:12ZzhoMagazine House of Cancer Research on Prevention and TreatmentZhongliu Fangzhi Yanjiu1000-85782023-11-0150111084109010.3971/j.issn.1000-8578.2023.23.03708578.2023.23.0370Construction of Prognostic Prediction Model for Lung Squamous Cell Carcinoma Based on Cuproptosis-related LncRNAsAN Mengxia0WANG Pingyu1School of Public Health and Management, Binzhou Medical College, Yantai 264003, ChinaSchool of Public Health and Management, Binzhou Medical College, Yantai 264003, ChinaObjective To develop a new risk scoring model based on cuproptosis-related lncRNAs (CRLs) to predict the prognosis of lung squamous cell carcinoma (LUSC). Methods Data were obtained mainly from TCGA and GTEx databases. Univariate Cox, Lasso, and multivariate Cox regression analyses were conducted to determine CRLs that affect the prognosis of LUSC and establish a risk scoring model. The ability of risk score characteristics to independently predict LUSC survival was compared with that of clinical characteristics by calculating the area under the ROC curve (AUC). Immune-related functions and immune checkpoint differences were compared between high- and low-risk groups. Results Nine CRLs were selected as independent prognostic lncRNAs for LUSC, and a risk scoring model was developed. Risk score was the influence factor for the prognosis of LUSC. The AUC values predicted by the risk score model for 1-, 3-, and 5-year survival rates of patients with LUSC were 0.710, 0.718, and 0.743, respectively. The high- and low-risk groups were partly statistically different in terms of immune-related functional assays and immune checkpoint assays (P < 0.05). Conclusion The risk scoring model developed based on nine CRLs could predict the prognosis and immune therapy response of patients with LUSC in clinical practice.http://www.zlfzyj.com/EN/10.3971/j.issn.1000-8578.2023.23.0370lung squamous cell carcinomacuproptosislncrnaimmune therapy |
| spellingShingle | AN Mengxia WANG Pingyu Construction of Prognostic Prediction Model for Lung Squamous Cell Carcinoma Based on Cuproptosis-related LncRNAs Zhongliu Fangzhi Yanjiu lung squamous cell carcinoma cuproptosis lncrna immune therapy |
| title | Construction of Prognostic Prediction Model for Lung Squamous Cell Carcinoma Based on Cuproptosis-related LncRNAs |
| title_full | Construction of Prognostic Prediction Model for Lung Squamous Cell Carcinoma Based on Cuproptosis-related LncRNAs |
| title_fullStr | Construction of Prognostic Prediction Model for Lung Squamous Cell Carcinoma Based on Cuproptosis-related LncRNAs |
| title_full_unstemmed | Construction of Prognostic Prediction Model for Lung Squamous Cell Carcinoma Based on Cuproptosis-related LncRNAs |
| title_short | Construction of Prognostic Prediction Model for Lung Squamous Cell Carcinoma Based on Cuproptosis-related LncRNAs |
| title_sort | construction of prognostic prediction model for lung squamous cell carcinoma based on cuproptosis related lncrnas |
| topic | lung squamous cell carcinoma cuproptosis lncrna immune therapy |
| url | http://www.zlfzyj.com/EN/10.3971/j.issn.1000-8578.2023.23.0370 |
| work_keys_str_mv | AT anmengxia constructionofprognosticpredictionmodelforlungsquamouscellcarcinomabasedoncuproptosisrelatedlncrnas AT wangpingyu constructionofprognosticpredictionmodelforlungsquamouscellcarcinomabasedoncuproptosisrelatedlncrnas |