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Non-invasive CT imaging biomarker to predict immunotherapy response in gastric cancer: a multicenter study
被引:5
|作者:
Huang, Weicai
[1
,2
]
Xiong, Wenjun
[3
]
Tang, Lei
[4
]
Chen, Chuanli
[5
]
Yuan, Qingyu
[5
]
Zhang, Cheng
[6
]
Zhou, Kangneng
[7
]
Sun, Zepang
[1
,2
]
Zhang, Taojun
[1
,2
]
Han, Zhen
[1
,2
]
Feng, Hao
[1
,2
]
Liang, Xiaokun
[8
,9
]
Zhong, Yonghong
[10
]
Deng, Haijun
[1
,2
]
Yu, Lequan
[11
]
Xu, Yikai
[5
]
Wang, Wei
[3
]
Shen, Lin
[6
]
Li, Guoxin
[1
,2
]
Jiang, Yuming
[12
]
机构:
[1] Southern Med Univ, Nanfang Hosp, Dept Gen Surg, Guangzhou, Guangdong, Peoples R China
[2] Southern Med Univ, Nanfang Hosp, Guangdong Prov Key Lab Precis Med Gastrointestina, Guangzhou, Guangdong, Peoples R China
[3] Guangzhou Univ Chinese Med, Dept Gastrointestinal Surg, Guangdong Prov Hosp Chinese Med, Affiliated Hosp 2, Guangzhou, Guangdong, Peoples R China
[4] Peking Univ Canc Hosp & Inst, Key Lab Carcinogenesis & Translat Res, Minist Educ, Dept Radiol, Beijing, Peoples R China
[5] Southern Med Univ, Dept Med Imaging Ctr, Nanfang Hosp, Guangzhou, Guangdong, Peoples R China
[6] Peking Univ Canc Hosp & Inst, Key Lab Carcinogenesis & Translat Res, Minist Educ Beijing, Dept Gastrointestinal Oncol, Beijing, Peoples R China
[7] Univ Sci & Technol, Beijing, Peoples R China
[8] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Guangdong, Peoples R China
[9] Univ Chinese Acad Sci, Shenzhen Colleges Adv Technol, Shenzhen, Guangdong, Peoples R China
[10] Guangzhou Univ Chinese Med, Clin Coll 2, Guangzhou, Peoples R China
[11] Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Peoples R China
[12] Wake Forest Univ, Bowman Gray Sch Med, Dept Radiat Oncol, Winston Salem, NC 27101 USA
基金:
中国国家自然科学基金;
中国博士后科学基金;
关键词:
RADIOMICS;
D O I:
10.1136/jitc-2023-007807
中图分类号:
R73 [肿瘤学];
学科分类号:
100214 ;
摘要:
Background 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. Methods 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. Results 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. Conclusion 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.
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页数:15
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