Combining autophagy and immune characterizations to predict prognosis and therapeutic response in lung adenocarcinoma
BackgroundAutophagy, a key regulator of programmed cell death, is critical for maintaining the stability of the intracellular environment. Increasing evidence has revealed the clinical importance of interactions between autophagy and immune status in lung adenocarcinoma. The present study evaluated...
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Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.944378/full |
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| author | Qiaxuan Li Qiaxuan Li Daipeng Xie Daipeng Xie Lintong Yao Lintong Yao Hongrui Qiu Hongrui Qiu Peimeng You Jialong Deng Congsen Li Congsen Li Weijie Zhan Weijie Zhan Maotao Weng Maotao Weng Shaowei Wu Shaowei Wu Fasheng Li Yubo Zhou Fanjun Zeng Yong Zheng Haiyu Zhou Haiyu Zhou Haiyu Zhou |
| author_facet | Qiaxuan Li Qiaxuan Li Daipeng Xie Daipeng Xie Lintong Yao Lintong Yao Hongrui Qiu Hongrui Qiu Peimeng You Jialong Deng Congsen Li Congsen Li Weijie Zhan Weijie Zhan Maotao Weng Maotao Weng Shaowei Wu Shaowei Wu Fasheng Li Yubo Zhou Fanjun Zeng Yong Zheng Haiyu Zhou Haiyu Zhou Haiyu Zhou |
| author_sort | Qiaxuan Li |
| collection | DOAJ |
| description | BackgroundAutophagy, a key regulator of programmed cell death, is critical for maintaining the stability of the intracellular environment. Increasing evidence has revealed the clinical importance of interactions between autophagy and immune status in lung adenocarcinoma. The present study evaluated the potential of autophagy-immune-derived biomarkers to predict prognosis and therapeutic response in patients with lung adenocarcinoma.MethodsPatients from the GSE72094 dataset were randomized 7:3 to a training set and an internal validation set. Three independent cohorts, TCGA, GSE31210, and GSE37745, were used for external verification. Unsupervised hierarchical clustering based on autophagy- and immune-associated genes was used to identify autophagy- and immune-associated molecular patterns, respectively. Significantly prognostic autophagy-immune genes were identified by LASSO analysis and by univariate and multivariate Cox regression analyses. Differences in tumor immune microenvironments, functional pathways, and potential therapeutic responses were investigated to differentiate high-risk and low-risk groups.ResultsHigh autophagy status and high immune status were associated with improved overall survival. Autophagy and immune subtypes were merged into a two-dimensional index to characterize the combined prognostic classifier, with 535 genes defined as autophagy-immune-related differentially expressed genes (DEGs). Four genes (C4BPA, CD300LG, CD96, and S100P) were identified to construct an autophagy-immune-related prognostic risk model. Survival and receiver operating characteristic (ROC) curve analyses showed that this model was significantly prognostic of survival. Patterns of autophagy and immune genes differed in low- and high-risk patients. Enrichment of most immune infiltrating cells was greater, and the expression of crucial immune checkpoint molecules was higher, in the low-risk group. TIDE and immunotherapy clinical cohort analysis predicted that the low-risk group had more potential responders to immunotherapy. GO, KEGG, and GSEA function analysis identified immune- and autophagy-related pathways. Autophagy inducers were observed in patients in the low-risk group, whereas the high-risk group was sensitive to autophagy inhibitors. The expression of the four genes was assessed in clinical specimens and cell lines.ConclusionsThe autophagy-immune-based gene signature represents a promising tool for risk stratification in patients with lung adenocarcinoma, guiding individualized targeted therapy or immunotherapy. |
| first_indexed | 2024-12-10T14:47:53Z |
| format | Article |
| id | doaj.art-419dd885ce44425aa9283d5c8a262e46 |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-12-10T14:47:53Z |
| publishDate | 2022-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-419dd885ce44425aa9283d5c8a262e462022-12-22T01:44:31ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-09-011310.3389/fimmu.2022.944378944378Combining autophagy and immune characterizations to predict prognosis and therapeutic response in lung adenocarcinomaQiaxuan Li0Qiaxuan Li1Daipeng Xie2Daipeng Xie3Lintong Yao4Lintong Yao5Hongrui Qiu6Hongrui Qiu7Peimeng You8Jialong Deng9Congsen Li10Congsen Li11Weijie Zhan12Weijie Zhan13Maotao Weng14Maotao Weng15Shaowei Wu16Shaowei Wu17Fasheng Li18Yubo Zhou19Fanjun Zeng20Yong Zheng21Haiyu Zhou22Haiyu Zhou23Haiyu Zhou24Department of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, ChinaShantou University Medical College, Shantou, ChinaDepartment of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, ChinaGuangdong Cardiovascular Institute, Guangzhou, ChinaDepartment of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, ChinaShantou University Medical College, Shantou, ChinaDepartment of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, ChinaGuangzhou University of Chinese Medicine, Guangzhou, ChinaDepartment of Thoracic radiology, Cancer Hospital of Nanchang University, Jiangxi Key Laboratory of Translational Cancer Research (Jiangxi Cancer Hospital of Nanchang University), Nanchang, ChinaDepartment of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, ChinaDepartment of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, ChinaShantou University Medical College, Shantou, ChinaDepartment of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, ChinaThe Second School of Clinical Medicine, Southern Medical University, Guangzhou, ChinaDepartment of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, ChinaShantou University Medical College, Shantou, ChinaDepartment of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, ChinaShantou University Medical College, Shantou, ChinaDepartment of Cardiothoracic Surgery, Affiliated Hospital of Guangdong Medical University, Guangzhou, ChinaDepartment of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, ChinaDepartment of General Practice, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, ChinaDepartment of Anesthesiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, ChinaDepartment of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, ChinaShantou University Medical College, Shantou, China0Jiangxi Lung Cancer Institute, Nanchang, ChinaBackgroundAutophagy, a key regulator of programmed cell death, is critical for maintaining the stability of the intracellular environment. Increasing evidence has revealed the clinical importance of interactions between autophagy and immune status in lung adenocarcinoma. The present study evaluated the potential of autophagy-immune-derived biomarkers to predict prognosis and therapeutic response in patients with lung adenocarcinoma.MethodsPatients from the GSE72094 dataset were randomized 7:3 to a training set and an internal validation set. Three independent cohorts, TCGA, GSE31210, and GSE37745, were used for external verification. Unsupervised hierarchical clustering based on autophagy- and immune-associated genes was used to identify autophagy- and immune-associated molecular patterns, respectively. Significantly prognostic autophagy-immune genes were identified by LASSO analysis and by univariate and multivariate Cox regression analyses. Differences in tumor immune microenvironments, functional pathways, and potential therapeutic responses were investigated to differentiate high-risk and low-risk groups.ResultsHigh autophagy status and high immune status were associated with improved overall survival. Autophagy and immune subtypes were merged into a two-dimensional index to characterize the combined prognostic classifier, with 535 genes defined as autophagy-immune-related differentially expressed genes (DEGs). Four genes (C4BPA, CD300LG, CD96, and S100P) were identified to construct an autophagy-immune-related prognostic risk model. Survival and receiver operating characteristic (ROC) curve analyses showed that this model was significantly prognostic of survival. Patterns of autophagy and immune genes differed in low- and high-risk patients. Enrichment of most immune infiltrating cells was greater, and the expression of crucial immune checkpoint molecules was higher, in the low-risk group. TIDE and immunotherapy clinical cohort analysis predicted that the low-risk group had more potential responders to immunotherapy. GO, KEGG, and GSEA function analysis identified immune- and autophagy-related pathways. Autophagy inducers were observed in patients in the low-risk group, whereas the high-risk group was sensitive to autophagy inhibitors. The expression of the four genes was assessed in clinical specimens and cell lines.ConclusionsThe autophagy-immune-based gene signature represents a promising tool for risk stratification in patients with lung adenocarcinoma, guiding individualized targeted therapy or immunotherapy.https://www.frontiersin.org/articles/10.3389/fimmu.2022.944378/fullmicroenvironmentautophagypreclinical modelschemotherapyimmunotherapy |
| spellingShingle | Qiaxuan Li Qiaxuan Li Daipeng Xie Daipeng Xie Lintong Yao Lintong Yao Hongrui Qiu Hongrui Qiu Peimeng You Jialong Deng Congsen Li Congsen Li Weijie Zhan Weijie Zhan Maotao Weng Maotao Weng Shaowei Wu Shaowei Wu Fasheng Li Yubo Zhou Fanjun Zeng Yong Zheng Haiyu Zhou Haiyu Zhou Haiyu Zhou Combining autophagy and immune characterizations to predict prognosis and therapeutic response in lung adenocarcinoma Frontiers in Immunology microenvironment autophagy preclinical models chemotherapy immunotherapy |
| title | Combining autophagy and immune characterizations to predict prognosis and therapeutic response in lung adenocarcinoma |
| title_full | Combining autophagy and immune characterizations to predict prognosis and therapeutic response in lung adenocarcinoma |
| title_fullStr | Combining autophagy and immune characterizations to predict prognosis and therapeutic response in lung adenocarcinoma |
| title_full_unstemmed | Combining autophagy and immune characterizations to predict prognosis and therapeutic response in lung adenocarcinoma |
| title_short | Combining autophagy and immune characterizations to predict prognosis and therapeutic response in lung adenocarcinoma |
| title_sort | combining autophagy and immune characterizations to predict prognosis and therapeutic response in lung adenocarcinoma |
| topic | microenvironment autophagy preclinical models chemotherapy immunotherapy |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.944378/full |
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