Yin Huihui, Yang Lu, Peng Gongxin, Yang Ke, Mi Yuling, Hu Xingsheng, Hao Xuezhi, Jiao Yuchen, Wang Xiaobing, Wang Yan
State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
Cancer Biol Med. 2021 May 7;18(4):1040-52. doi: 10.20892/j.issn.2095-3941.2020.0450.
Immune checkpoint inhibitors have revolutionized cancer therapy for multiple types of solid tumors, but as expected, a large percentage of patients do not show durable responses. Biomarkers that can predict clinical responses to immunotherapies at diagnosis are therefore urgently needed. Herein, we determined the associations between baseline gut commensal microbes and the clinical treatment efficiencies of patients with thoracic neoplasms during anti-programmed death protein 1 (PD-1) therapy.
Forty-two patients with advanced thoracic carcinoma who received anti-PD-1 treatment were enrolled in the study. Baseline and time-serial stool samples were analyzed using 16S ribosomal RNA gene sequencing. Tumor responses, patient progression-free survival, and overall survival were used to measure clinical outcomes.
The diversities of the baseline gut microbiota were similar between responders ( = 23) and nonresponders ( = 19). The relative abundances of the , , , and bacterial families were significantly higher in the responder group. These 5 bacterial families acted as a commensal consortium and better stratified patients according to clinical responses ( = 0.014). Patients with a higher abundance of commensal microbes had prolonged PFS ( = 0.00016). Using multivariable analysis, the abundance of the commensal consortium was identified as an independent predictor of anti-PD-1 immunotherapy in thoracic neoplasms (hazard ratio: 0.17; 95% confidence interval: 0.05-0.55; = 0.003).
Baseline gut microbiota may have a critical impact on anti-PD-1 treatment in thoracic neoplasms. The abundance of gut commensal microbes at diagnosis might be useful for the early prediction of anti-PD-1 immunotherapy responses.
免疫检查点抑制剂彻底改变了多种实体瘤的癌症治疗方式,但正如预期的那样,很大一部分患者并未表现出持久的反应。因此,迫切需要能够在诊断时预测免疫疗法临床反应的生物标志物。在此,我们确定了基线肠道共生微生物与胸段肿瘤患者在抗程序性死亡蛋白1(PD-1)治疗期间的临床治疗效率之间的关联。
42例接受抗PD-1治疗的晚期胸段癌患者纳入本研究。使用16S核糖体RNA基因测序分析基线和时间序列粪便样本。肿瘤反应、患者无进展生存期和总生存期用于衡量临床结果。
反应者(n = 23)和无反应者(n = 19)之间基线肠道微生物群的多样性相似。反应者组中,、、、和细菌家族的相对丰度显著更高。这5个细菌家族作为一个共生菌群,根据临床反应能更好地对患者进行分层(P = 0.014)。共生微生物丰度较高的患者无进展生存期延长(P = 0.00016)。通过多变量分析,共生菌群的丰度被确定为胸段肿瘤抗PD-1免疫治疗的独立预测因子(风险比:0.17;95%置信区间:0.05 - 0.55;P = 0.003)。
基线肠道微生物群可能对胸段肿瘤的抗PD-1治疗有关键影响。诊断时肠道共生微生物的丰度可能有助于早期预测抗PD-1免疫治疗反应。