Neoadjuvant therapy with immune checkpoint blockade, antiangiogenesis, and chemotherapy for locally advanced gastric cancer

医学 免疫检查点 肿瘤科 癌症 新辅助治疗 化疗 微卫星不稳定性 免疫疗法 临床终点 病态的 免疫系统 内科学 临床试验 免疫学 乳腺癌 生物 等位基因 基因 微卫星 生物化学
作者
Song Li,Wenbin Yu,Fei Xie,Haitao Luo,Zhimin Liu,Weiwei Lv,Duan‐Bo Shi,Dexin Yu,Peng Gao,Cheng Chen,Wei Meng,Wenhao Zhou,Jiaqian Wang,Zhikun Zhao,Xin Dai,Qian Xu,Xue Zhang,Miao Huang,Kai Huang,Jian Wang,Jisheng Li,Lei Sheng,Lian Liu
出处
期刊:Nature Communications [Nature Portfolio]
卷期号:14 (1) 被引量:117
标识
DOI:10.1038/s41467-022-35431-x
摘要

Abstract Despite neoadjuvant/conversion chemotherapy, the prognosis of cT4a/bN+ gastric cancer is poor. Immune checkpoint inhibitors (ICIs) and antiangiogenic agents have shown activity in late-stage gastric cancer, but their efficacy in the neoadjuvant/conversion setting is unclear. In this single-armed, phase II, exploratory trial (NCT03878472), we evaluate the efficacy of a combination of ICI (camrelizumab), antiangiogenesis (apatinib), and chemotherapy (S-1 ± oxaliplatin) for neoadjuvant/conversion treatment of cT4a/bN+ gastric cancer. The primary endpoints are pathological responses and their potential biomarkers. Secondary endpoints include safety, objective response, progression-free survival, and overall survival. Complete and major pathological response rates are 15.8% and 26.3%. Pathological responses correlate significantly with microsatellite instability status, PD-L1 expression, and tumor mutational burden. In addition, multi-omics examination reveals several putative biomarkers for pathological responses, including RREB1 and SSPO mutation, immune-related signatures, and a peripheral T cell expansion score. Multi-omics also demonstrates dynamic changes in dominant tumor subclones, immune microenvironments, and T cell receptor repertoires during neoadjuvant immunotherapy. The toxicity and post-surgery complications are limited. These data support further validation of ICI- and antiangiogenesis-based neoadjuvant/conversion therapy in large randomized trials and provide candidate biomarkers.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Dr.Zou完成签到,获得积分10
刚刚
wst发布了新的文献求助10
1秒前
1秒前
dsjbk发布了新的文献求助10
2秒前
一只小黑胖关注了科研通微信公众号
2秒前
5秒前
卷卷发布了新的文献求助15
5秒前
5秒前
狂野的初晴完成签到,获得积分20
6秒前
7秒前
Orange应助呆萌的秋天采纳,获得10
8秒前
WUHUANGWANSUI完成签到,获得积分20
8秒前
缓慢的可乐完成签到,获得积分10
8秒前
传奇3应助木木采纳,获得10
9秒前
似宁完成签到,获得积分10
10秒前
英姑应助Trista0036采纳,获得10
12秒前
万能图书馆应助tjfwg采纳,获得10
14秒前
热热带汤发布了新的文献求助10
14秒前
Research完成签到 ,获得积分10
15秒前
fd完成签到,获得积分10
16秒前
17秒前
18秒前
18秒前
19秒前
隐形曼青应助cui采纳,获得10
19秒前
扶光完成签到 ,获得积分10
20秒前
20秒前
dsjbk完成签到,获得积分20
21秒前
所所应助朴素的荠采纳,获得10
23秒前
23秒前
huahua发布了新的文献求助10
24秒前
谢书繁发布了新的文献求助10
25秒前
25秒前
昔我依依发布了新的文献求助10
26秒前
yingying完成签到,获得积分10
26秒前
wpeng326完成签到,获得积分10
28秒前
共享精神应助畲田雨采纳,获得10
29秒前
30秒前
cui发布了新的文献求助10
30秒前
32秒前
高分求助中
Thinking Small and Large 500
Algorithmic Mathematics in Machine Learning 500
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
Deciphering Earth's History: the Practice of Stratigraphy 200
New Syntheses with Carbon Monoxide 200
Quanterion Automated Databook NPRD-2023 200
Interpretability and Explainability in AI Using Python 200
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3835028
求助须知:如何正确求助?哪些是违规求助? 3377526
关于积分的说明 10498888
捐赠科研通 3097008
什么是DOI,文献DOI怎么找? 1705417
邀请新用户注册赠送积分活动 820558
科研通“疑难数据库(出版商)”最低求助积分说明 772123