An artificial intelligence network-guided signature for predicting outcome and immunotherapy response in lung adenocarcinoma patients based on 26 machine learning algorithms

作者全名："Zhang, Nan; Zhang, Hao; Liu, Zaoqu; Dai, Ziyu; Wu, Wantao; Zhou, Ran; Li, Shuyu; Wang, Zeyu; Liang, Xisong; Wen, Jie; Zhang, Xun; Zhang, Bo; Ouyang, Sirui; Zhang, Jian; Luo, Peng; Li, Xizhe; Cheng, Quan"

作者地址："[Zhang, Nan; Dai, Ziyu; Wu, Wantao; Wang, Zeyu; Liang, Xisong; Wen, Jie; Zhang, Xun; Zhang, Bo; Ouyang, Sirui; Cheng, Quan] Cent South Univ, Xiangya Hosp, Dept Neurosurg, Changsha, Peoples R China; [Zhang, Nan] Huazhong Univ Sci & Technol, Coll Life Sci & Technol, Wuhan, Peoples R China; [Liu, Zaoqu; Dai, Ziyu; Wang, Zeyu; Liang, Xisong; Wen, Jie; Zhang, Xun; Zhang, Bo; Ouyang, Sirui; Li, Xizhe; Cheng, Quan] Cent South Univ, Xiangya Hosp, Natl Clin Res Ctr Geriatr Disorders, Changsha, Peoples R China; [Zhang, Hao] Chongqing Med Univ, Affiliated Hosp 2, Dept Neurosurg, Chongqing, Peoples R China; [Liu, Zaoqu] Zhengzhou Univ, Dept Intervent Radiol, Affiliated Hosp 1, Zhengzhou, Peoples R China; [Wu, Wantao] Cent South Univ, Xiangya Hosp, Dept Oncol, Changsha, Peoples R China; [Zhou, Ran] Univ Manchester, Fac Biol Med & Hlth, Div Neurosci & Expt Psychol, Manchester, England; [Li, Shuyu] Huazhong Univ Sci & Technol, Tongji Hosp, Tongji Med Coll, Dept Thyroid & Breast Surg, Wuhan, Peoples R China; [Zhang, Jian; Luo, Peng] Southern Med Univ, Zhujiang Hosp, Dept Oncol, Guangzhou, Peoples R China; [Li, Xizhe] Cent South Univ, Xiangya Hosp, Dept Thorac Surg, Changsha 410008, Hunan, Peoples R China; [Li, Xizhe] Hunan Engn Res Ctr Pulm Nodules Precise Diag & Tr, Xiangya Hosp, Dept Thorac Surg, Changsha 410008, Hunan, Peoples R China"

通信作者："Cheng, Q (通讯作者)，Cent South Univ, Xiangya Hosp, Dept Neurosurg, Changsha, Peoples R China.; Li, XZ (通讯作者)，Cent South Univ, Xiangya Hosp, Dept Thorac Surg, Changsha 410008, Hunan, Peoples R China."

来源：CELL PROLIFERATION

ESI学科分类：MOLECULAR BIOLOGY & GENETICS

WOS号：WOS:000937386900001

JCR分区：Q2

影响因子：5.9

年份：2023

卷号：56

期号：4

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结束页：　

文献类型：Article

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摘要："The immune cells play an increasingly vital role in influencing the proliferation, progression, and metastasis of lung adenocarcinoma (LUAD) cells. However, the potential of immune cells' specific genes-based model remains largely unknown. In the current study, by analysing single-cell RNA sequencing (scRNA-seq) data and bulk RNA sequencing data, the tumour-infiltrating immune cell (TIIC) associated signature was developed based on a total of 26 machine learning (ML) algorithms. As a result, the TIIC signature score could predict survival outcomes of LUAD patients across five independent datasets. The TIIC signature score showed superior performance to 168 previously established signatures in LUAD. Moreover, the TIIC signature score developed by the immunofluorescence staining of the tissue array of LUAD patients showed a prognostic value. Our research revealed a solid connection between TIIC signature score and tumour immunity as well as metabolism. Additionally, it has been discovered that the TIIC signature score can forecast genomic change, chemotherapeutic drug susceptibility, and-most significantly-immunotherapeutic response. As a newly demonstrated biomarker, the TIIC signature score facilitated the selection of the LUAD population who would benefit from future clinical stratification."

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