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Immune signature-based risk stratification and prediction of immune checkpoint inhibitor's efficacy for lung adenocarcinoma

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单位: [1]Department of Oncology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China [2]Department of Medical Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou 450008, China [3]Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medicine, No. 79 Qingchun Road, Hangzhou 310003, China
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关键词: Lung adenocarcinoma Immunotherapy The tumor immune microenvironment Immune checkpoint inhibitor Tumor mutation burden Prognostic model

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Background Lung adenocarcinoma (LUAD) is a common pulmonary malignant disease with a poor prognosis. There were limited studies investigating the influences of the tumor immune microenvironment on LUAD patients' survival and response to immune checkpoint inhibitors (ICIs). Methods Based on TCGA-LUAD dataset, we constructed a prognostic immune signature and validated its predictive capability in the internal as well as total datasets. Then, we explored the differences of tumor-infiltrating lymphocytes, tumor mutation burden, and patients' response to ICI treatment between the high-risk score group and low-risk score group. Results This immune signature consisted of 17 immune-related genes, which was an independent prognostic factor for LUAD patients. In the low-risk score group, patients had better overall survival. Although the differences were non-significant, patients with low-risk scores had more tumor-infiltrating follicular helper T cells and fewer macrophages (M0), which were closely related to clinical outcomes. Additionally, the total TMB was markedly decreased in the low-risk score group. Using immunophenoscore as a surrogate of ICI response, we found that patients with low-risk scores had significantly higher immunophenoscore. Conclusion The 17-immune-related genes signature may have prognostic and predictive relevance with ICI therapy but needs prospective validation.

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基金编号: 81874120 82073370 2017060201010170

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出版当年[2020]版:
大类 | 2 区 医学
小类 | 2 区 免疫学 3 区 肿瘤学
最新[2025]版:
大类 | 3 区 医学
小类 | 3 区 免疫学 3 区 肿瘤学
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出版当年[2019]版:
Q1 IMMUNOLOGY Q1 ONCOLOGY
最新[2023]版:
Q1 ONCOLOGY Q2 IMMUNOLOGY

影响因子: 最新[2023版] 最新五年平均 出版当年[2019版] 出版当年五年平均 出版前一年[2018版] 出版后一年[2020版]

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第一作者单位: [1]Department of Oncology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
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