Gut microbiome model predicts response to neoadjuvant immunotherapy plus chemoradiotherapy in rectal cancer.

IF 12.8 Q1 MEDICINE, RESEARCH & EXPERIMENTAL Med Pub Date : 2024-10-11 Epub Date: 2024-07-23 DOI:10.1016/j.medj.2024.07.002

Zhengyang Yang, Jingxin Ma, Jiagang Han, Ang Li, Gang Liu, Yi Sun, Jianyong Zheng, Jie Zhang, Guangyong Chen, Rui Xu, Liting Sun, Cong Meng, Jiale Gao, Zhigang Bai, Wei Deng, Chenlin Zhang, Jianrong Su, Hongwei Yao, Zhongtao Zhang

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Abstract

Background: Accurate evaluation of the response to preoperative treatment enables the provision of a more appropriate personalized therapeutic schedule for locally advanced rectal cancer (LARC), which remains an enormous challenge, especially neoadjuvant immunotherapy plus chemoradiotherapy (nICRT).

Methods: This prospective, multicenter cohort study enrolled patients with LARC from 6 centers who received nICRT. The dynamic variation in the gut microbiome during nICRT was evaluated. A species-level gut microbiome prediction (SPEED) model was developed and validated to predict the pathological complete response (pCR) to nICRT.

Findings: A total of 50 patients were enrolled, 75 fecal samples were collected from 33 patients at different time points, and the pCR rate reached 42.4% (14/33). Lactobacillus and Eubacterium were observed to increase after nICRT. Additionally, significant differences in the gut microbiome were observed between responders and non-responders at baseline. Significantly higher abundances of Lachnospiraceae bacterium and Blautia wexlerae were found in responders, while Bacteroides, Prevotella, and Porphyromonas were found in non-responders. The SPEED model showcased a superior predictive performance with areas under the curve of 98.80% (95% confidence interval [CI]: 95.67%-100%) in the training cohort and 77.78% (95% CI: 65.42%-88.29%) in the validation cohort.

Conclusions: Programmed death 1 (PD-1) blockade plus concurrent long-course CRT showed a favorable pCR rate and is well tolerated in microsatellite-stable (MSS)/mismatch repair-proficient (pMMR) patients with LARC. The SPEED model can be used to predict the pCR to nICRT based on the baseline gut microbiome with high robustness and accuracy, thereby assisting clinical physicians in providing individualized management for patients with LARC.

Funding: This research was funded by the China National Natural Science Foundation (82202884).

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肠道微生物组模型可预测直肠癌患者对新辅助免疫疗法加化疗放疗的反应。

背景：准确评估术前治疗的反应有助于为局部晚期直肠癌（LARC）提供更合适的个性化治疗方案，而这仍是一项巨大的挑战，尤其是新辅助免疫治疗加化学放疗（nICRT）：这项前瞻性多中心队列研究从 6 个中心招募了接受 nICRT 的局部晚期直肠癌患者。评估了 nICRT 期间肠道微生物组的动态变化。开发并验证了物种级肠道微生物组预测（SPEED）模型，用于预测 nICRT 的病理完全反应（pCR）：共有 50 名患者入组，从 33 名患者的不同时间点采集了 75 份粪便样本，pCR 率达到 42.4%（14/33）。据观察，乳酸杆菌和大肠杆菌在 nICRT 后有所增加。此外，还观察到有反应者和无反应者的肠道微生物组在基线上存在明显差异。在应答者中发现 Lachnospiraceaebacterium 和 Blautiawexlerae 的丰度明显更高，而在非应答者中发现 Bacteroides、Prevotella 和 Porphyromonas。SPEED 模型显示出卓越的预测性能，训练队列中的曲线下面积为 98.80%（95% 置信区间 [CI]：95.67%-100%），验证队列中的曲线下面积为 77.78%（95% 置信区间 [CI]：65.42%-88.29%）：程序性死亡1（PD-1）阻断联合长程CRT对微卫星稳定（MSS）/错配修复功能良好（pMMR）的LARC患者显示出良好的pCR率和耐受性。SPEED模型可用于根据基线肠道微生物组预测nICRT的pCR，具有很高的稳健性和准确性，从而帮助临床医生为LARC患者提供个体化治疗：本研究由国家自然科学基金资助（82202884）。

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来源期刊

Med MEDICINE, RESEARCH & EXPERIMENTAL-

CiteScore

17.70

自引率

0.60%

发文量

102

期刊介绍： Med is a flagship medical journal published monthly by Cell Press, the global publisher of trusted and authoritative science journals including Cell, Cancer Cell, and Cell Reports Medicine. Our mission is to advance clinical research and practice by providing a communication forum for the publication of clinical trial results, innovative observations from longitudinal cohorts, and pioneering discoveries about disease mechanisms. The journal also encourages thought-leadership discussions among biomedical researchers, physicians, and other health scientists and stakeholders. Our goal is to improve health worldwide sustainably and ethically. Med publishes rigorously vetted original research and cutting-edge review and perspective articles on critical health issues globally and regionally. Our research section covers clinical case reports, first-in-human studies, large-scale clinical trials, population-based studies, as well as translational research work with the potential to change the course of medical research and improve clinical practice.