Dissection of the cell communication interactions in lung adenocarcinoma identified a prognostic model with immunotherapy efficacy assessment and a potential therapeutic candidate gene ITGB1
Xing Jin,
Zhengyang Hu,
Jiacheng Yin,
Guangyao Shan,
Mengnan Zhao,
Zhenyu Liao,
Jiaqi Liang,
Guoshu Bi,
Ye Cheng,
Junjie Xi,
Zhencong Chen,
Miao Lin
Affiliations
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; Corresponding author. Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, No. 180, Fenglin Road, Shanghai, 200032, China.
Zhencong Chen
Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Corresponding author. Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, No. 180, Fenglin Road, Shanghai, 200032, China.
Miao Lin
Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Corresponding author. Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, No. 180, Fenglin Road, Shanghai, 200032, China.
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.
