Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung Adenocarcinoma
BackgroundLung adenocarcinoma (LUAD) is the major non-small-cell lung cancer pathological subtype with poor prognosis worldwide. Herein, we aimed to build an energy metabolism-associated prognostic gene signature to predict patient survival.MethodsThe gene expression profiles of patients with LUAD w...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-04-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.867470/full |
| _version_ | 1818146984209416192 |
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| author | Teng Mu Haoran Li Xiangnan Li |
| author_facet | Teng Mu Haoran Li Xiangnan Li |
| author_sort | Teng Mu |
| collection | DOAJ |
| description | BackgroundLung adenocarcinoma (LUAD) is the major non-small-cell lung cancer pathological subtype with poor prognosis worldwide. Herein, we aimed to build an energy metabolism-associated prognostic gene signature to predict patient survival.MethodsThe gene expression profiles of patients with LUAD were downloaded from the TCGA and GEO databases, and energy metabolism (EM)-related genes were downloaded from the GeneCards database. Univariate Cox and LASSO analyses were performed to identify the prognostic EM-associated gene signatures. Kaplan–Meier and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signatures. A CIBERSORT analysis was used to evaluate the correlation between the risk model and immune cells. A nomogram was used to predict the survival probability of LUAD based on a risk model.ResultsWe constructed a prognostic signature comprising 13 EM-related genes (AGER, AHSG, ALDH2, CIDEC, CYP17A1, FBP1, GNB3, GZMB, IGFBP1, SORD, SOX2, TRH and TYMS). The Kaplan–Meier curves validated the good predictive ability of the prognostic signature in TCGA AND two GEO datasets (p<0.0001, p=0.00021, and p=0.0034, respectively). The area under the curve (AUC) of the ROC curves also validated the predictive accuracy of the risk model. We built a nomogram to predict the survival probability of LUAD, and the calibration curves showed good predictive ability. Finally, a functional analysis also unveiled the different immune statuses between the two different risk groups.ConclusionOur study constructed and verified a novel EM-related prognostic gene signature that could improve the individualized prediction of survival probability in LUAD. |
| first_indexed | 2024-12-11T12:28:02Z |
| format | Article |
| id | doaj.art-1c349f4562c44844ad3acff0d691c63e |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-11T12:28:02Z |
| publishDate | 2022-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-1c349f4562c44844ad3acff0d691c63e2022-12-22T01:07:19ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-04-011210.3389/fonc.2022.867470867470Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung AdenocarcinomaTeng Mu0Haoran Li1Xiangnan Li2Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Thoracic Surgery, Peking University People’s Hospital, Beijing, ChinaDepartment of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaBackgroundLung adenocarcinoma (LUAD) is the major non-small-cell lung cancer pathological subtype with poor prognosis worldwide. Herein, we aimed to build an energy metabolism-associated prognostic gene signature to predict patient survival.MethodsThe gene expression profiles of patients with LUAD were downloaded from the TCGA and GEO databases, and energy metabolism (EM)-related genes were downloaded from the GeneCards database. Univariate Cox and LASSO analyses were performed to identify the prognostic EM-associated gene signatures. Kaplan–Meier and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signatures. A CIBERSORT analysis was used to evaluate the correlation between the risk model and immune cells. A nomogram was used to predict the survival probability of LUAD based on a risk model.ResultsWe constructed a prognostic signature comprising 13 EM-related genes (AGER, AHSG, ALDH2, CIDEC, CYP17A1, FBP1, GNB3, GZMB, IGFBP1, SORD, SOX2, TRH and TYMS). The Kaplan–Meier curves validated the good predictive ability of the prognostic signature in TCGA AND two GEO datasets (p<0.0001, p=0.00021, and p=0.0034, respectively). The area under the curve (AUC) of the ROC curves also validated the predictive accuracy of the risk model. We built a nomogram to predict the survival probability of LUAD, and the calibration curves showed good predictive ability. Finally, a functional analysis also unveiled the different immune statuses between the two different risk groups.ConclusionOur study constructed and verified a novel EM-related prognostic gene signature that could improve the individualized prediction of survival probability in LUAD.https://www.frontiersin.org/articles/10.3389/fonc.2022.867470/fulllung adenocarcinomaenergy metabolismrisk modelprognosisnomogram |
| spellingShingle | Teng Mu Haoran Li Xiangnan Li Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung Adenocarcinoma Frontiers in Oncology lung adenocarcinoma energy metabolism risk model prognosis nomogram |
| title | Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung Adenocarcinoma |
| title_full | Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung Adenocarcinoma |
| title_fullStr | Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung Adenocarcinoma |
| title_full_unstemmed | Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung Adenocarcinoma |
| title_short | Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung Adenocarcinoma |
| title_sort | prognostic implication of energy metabolism related gene signatures in lung adenocarcinoma |
| topic | lung adenocarcinoma energy metabolism risk model prognosis nomogram |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2022.867470/full |
| work_keys_str_mv | AT tengmu prognosticimplicationofenergymetabolismrelatedgenesignaturesinlungadenocarcinoma AT haoranli prognosticimplicationofenergymetabolismrelatedgenesignaturesinlungadenocarcinoma AT xiangnanli prognosticimplicationofenergymetabolismrelatedgenesignaturesinlungadenocarcinoma |