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

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单位： [1]Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China. [2]College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China. [3]National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China. [4]Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China. [5]Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China. [6]Department of Oncology, Xiangya Hospital, Central South University, Changsha, China. [7]Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK. [8]Department of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China. [9]Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China. [10]Department of Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, China. [11]Hunan Engineering Research Center for Pulmonary Nodules Precise Diagnosis &amp [12]Treatment, Changsha, China.

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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.© 2023 The Authors. Cell Proliferation published by Beijing Institute for Stem Cell and Regenerative Medicine and John Wiley & Sons Ltd.

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出版当年[2022]版：

大类 | 1 区

生物学

小类 | 2 区细胞生物学

最新[2025]版：

大类 | 1 区

生物学

小类 | 1 区细胞生物学

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出版当年[2021]版：

Q1 CELL BIOLOGY

最新[2023]版：

Q2 CELL BIOLOGY

影响因子： 5.9 最新[2023版] 7.3 最新五年平均 8.755 出版当年[2021版] 7.834 出版当年五年平均 6.831 出版前一年[2020版] 8.5 出版后一年[2022版]

第一作者：

第一作者单位： [1]Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China. [2]College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China. [3]National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.

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通讯作者：

通讯机构： [1]Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China. [3]National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China. [10]Department of Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, China. [11]Hunan Engineering Research Center for Pulmonary Nodules Precise Diagnosis &amp [*1]Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha 410008, Hunan, China [*2]Department of Thoracic Surgery, Xiangya Hospital, Central South University, Changsha 410008, Hunan, China

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