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Non-invasive CT imaging biomarker to predict immunotherapy response in gastric cancer: a multicenter study

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机构: [1]Department of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong, China. [2]Department of Gastrointestinal Surgery, Guangdong Provincial Hospital of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China. [3]Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China. [4]Department of Medical Imaging Center, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong, China. [5]Department of Gastrointestinal Oncology, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, China. [6]University of Science and Technology, Beijing, China. [7]Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China. [8]Shenzhen Colleges of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, Guangdong, China. [9]Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, China. [10]Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong, China. [11]Department of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong, China [12]Department of Radiation Oncology, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
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Despite remarkable benefits have been provided by immune checkpoint inhibitors in gastric cancer (GC), predictions of treatment response and prognosis remain unsatisfactory, making identifying biomarkers desirable. The aim of this study was to develop and validate a CT imaging biomarker to predict the immunotherapy response in patients with GC and investigate the associated immune infiltration patterns.This retrospective study included 294 GC patients who received anti-PD-1/PD-L1 immunotherapy from three independent medical centers between January 2017 and April 2022. A radiomics score (RS) was developed from the intratumoral and peritumoral features on pretreatment CT images to predict immunotherapy-related progression-free survival (irPFS). The performance of the RS was evaluated by the area under the time-dependent receiver operating characteristic curve (AUC). Multivariable Cox regression analysis was performed to construct predictive nomogram of irPFS. The C-index was used to determine the performance of the nomogram. Bulk RNA sequencing of tumors from 42 patients in The Cancer Genome Atlas was used to investigate the RS-associated immune infiltration patterns.Overall, 89 of 294 patients (median age, 57 years (IQR 48-66 years); 171 males) had an objective response to immunotherapy. The RS included 13 CT features that yielded AUCs of 12-month irPFS of 0.787, 0.810 and 0.785 in the training, internal validation, and external validation 1 cohorts, respectively, and an AUC of 24-month irPFS of 0.805 in the external validation 2 cohort. Patients with low RS had longer irPFS in each cohort (p<0.05). Multivariable Cox regression analyses showed RS is an independent prognostic factor of irPFS. The nomogram that integrated the RS and clinical characteristics showed improved performance in predicting irPFS, with C-index of 0.687-0.778 in the training and validation cohorts. The CT imaging biomarker was associated with M1 macrophage infiltration.The findings of this prognostic study suggest that the non-invasive CT imaging biomarker can effectively predict immunotherapy outcomes in patients with GC and is associated with innate immune signaling, which can serve as a potential tool for individual treatment decisions.© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

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大类 | 2 区 医学
小类 | 2 区 肿瘤学 2 区 免疫学
最新[2025]版:
大类 | 1 区 医学
小类 | 1 区 免疫学 2 区 肿瘤学
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出版当年[2021]版:
Q1 IMMUNOLOGY Q1 ONCOLOGY
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Q1 IMMUNOLOGY Q1 ONCOLOGY

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第一作者机构: [1]Department of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong, China.
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