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Jin X, Hu Z, Yin J, Shan G, Zhao M, Liao Z, Liang J, Bi G, Cheng Y, Xi J, Chen Z, Lin M. Dissection of the cell communication interactions in lung adenocarcinoma identified a prognostic model with immunotherapy efficacy assessment and a potential therapeutic candidate gene ITGB1. Heliyon 2024; 10:e36599. [PMID: 39263115 PMCID: PMC11388764 DOI: 10.1016/j.heliyon.2024.e36599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Revised: 08/17/2024] [Accepted: 08/19/2024] [Indexed: 09/13/2024] Open
Abstract
Background The tumor microenvironment (TME) in lung adenocarcinoma (LUAD) influences tumor progression and immunosuppressive phenotypes through cell communication. We aimed to decipher cellular communication and molecular patterns in LUAD. Methods We analyzed scRNA-seq data from LUAD patients in multiple cohorts, revealing complex cell communication networks within the TME. Using cell chat analysis and COSmap technology, we inferred LUAD's spatial organization. Employing the NMF algorithm and survival screening, we identified a cell communication interactions (CCIs) model and validated it across various datasets. Results We uncovered intricate cell communication interactions within the TME, identifying three LUAD patient subtypes with distinct prognosis, clinical characteristics, mutation status, expression patterns, and immune infiltration. Our CCI model exhibited robust performance in prognosis and immunotherapy response prediction. Several potential therapeutic targets and agents for high CCI score patients with immunosuppressive profiles were identified. Machine learning algorithms pinpointed the novel candidate gene ITGB1 and validated its role in LUAD tumor phenotype in vitro. Conclusion Our study elucidates molecular patterns and cell communication interactions in LUAD as effective biomarkers and predictors of immunotherapy response. Targeting cell communication interactions offers novel avenues for LUAD immunotherapy and prognostic evaluations, with ITGB1 emerging as a promising therapeutic target.
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Affiliation(s)
- Xing Jin
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhengyang Hu
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jiacheng Yin
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Guangyao Shan
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Mengnan Zhao
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhenyu Liao
- Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Jiaqi Liang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Guoshu Bi
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ye Cheng
- Institutes of Biomedical Sciences and Children's Hospital, Fudan University, Shanghai, China
| | - Junjie Xi
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhencong Chen
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Miao Lin
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
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Yang S, Wang M, Li Z, Luan X, Yu Y, Jiang J, Li Y, Xie Y, Wang L. Tripterygium wilfordii Hook.f induced kidney injury through mediating inflammation via PI3K-Akt/HIF-1/TNF signaling pathway: A study of network toxicology and molecular docking. Medicine (Baltimore) 2024; 103:e36968. [PMID: 38335377 PMCID: PMC10860970 DOI: 10.1097/md.0000000000036968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 12/20/2023] [Accepted: 12/21/2023] [Indexed: 02/12/2024] Open
Abstract
We intend to explore potential mechanisms of Tripterygium wilfordii Hook.f (TwHF) induced kidney injury (KI) using the methods of network toxicology and molecular docking. We determined TwHF potential compounds with its targets and KI targets, obtained the TwHF induced KI targets after intersecting targets of TwHF and KI. Then we conducted protein-protein interaction (PPI) network, gene expression analysis, gene ontology (GO) function and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis to explore the mechanism of TwHF-induced KI. Finally we conducted molecular docking to verify the core toxic compounds and the targets. We obtained 12 TwHF toxic compounds and 62 TwHF-induced KI targets. PPI network, gene expression analysis and GO function enrichment analysis unveiled the key biological process and suggested the mechanism of TwHF-induced KI might be associated with inflammation, immune response, hypoxia as well as oxidative stress. KEGG pathway enrichment analysis indicated PI3K-Akt signaling pathway, HIF-1 signaling pathway and TNF signaling pathway were key signaling pathways of TwHF induced KI. Molecular docking showed that the binding energy of core targets and toxic compounds was all less than -6.5 kcal/mol that verified the screening ability of network pharmacology and provided evidence for modifying TwHF toxic compounds structure. Through the study, we unveiled the mechanism of TwHF induce KI that TwHF might activate PI3K-Akt signaling pathway as well as TNF signaling pathway to progress renal inflammation, mediate hypoxia via HIF-1 signaling pathway to accelerate inflammatory processes, and also provided a theoretical basis for modifying TwHF toxic compounds structure as well as supported the follow-up research.
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Affiliation(s)
- Shuo Yang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Mengmeng Wang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zhongming Li
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China
| | - Xiangjia Luan
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yanan Yu
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Junjie Jiang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yuanyuan Li
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yanming Xie
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Lianxin Wang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
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