Suppr超能文献

独特的功能宏基因组标记物可预测中国非小细胞肺癌患者对抗PD-1治疗的反应性。

Distinct Functional Metagenomic Markers Predict the Responsiveness to Anti-PD-1 Therapy in Chinese Non-Small Cell Lung Cancer Patients.

作者信息

Fang Chao, Fang Wenfeng, Xu Liqin, Gao Fangfang, Hou Yong, Zou Hua, Ma Yuxiang, Moll Janne Marie, Yang Yunpeng, Wang Dan, Huang Yan, Ren Huahui, Zhao Hongyun, Qin Shishang, Zhong Huanzi, Li Junhua, Liu Sheng, Yang Huanming, Wang Jian, Brix Susanne, Kristiansen Karsten, Zhang Li

机构信息

Laboratory of Genomics and Molecular Biomedicine, Department of Biology, University of Copenhagen, Copenhagen, Denmark.

BGI-Shenzhen, Shenzhen, China.

出版信息

Front Oncol. 2022 Apr 21;12:837525. doi: 10.3389/fonc.2022.837525. eCollection 2022.

Abstract

BACKGROUND

Programmed death 1 (PD-1) and the ligand of PD-1 (PD-L1) are central targets for immune-checkpoint therapy (ICT) blocking immune evasion-related pathways elicited by tumor cells. A number of PD-1 inhibitors have been developed, but the efficacy of these inhibitors varies considerably and is typically below 50%. The efficacy of ICT has been shown to be dependent on the gut microbiota, and experiments using mouse models have even demonstrated that modulation of the gut microbiota may improve efficacy of ICT.

METHODS

We followed a Han Chinese cohort of 85 advanced non-small cell lung cancer (NSCLC) patients, who received anti-PD-1 antibodies. Tumor biopsies were collected before treatment initiation for whole exon sequencing and variant detection. Fecal samples collected biweekly during the period of anti-PD-1 antibody administration were used for metagenomic sequencing. We established gut microbiome abundance profiles for identification of significant associations between specific microbial taxa, potential functionality, and treatment responses. A prediction model based on random forest was trained using selected markers discriminating between the different response groups.

RESULTS

NSCLC patients treated with antibiotics exhibited the shortest survival time. Low level of tumor-mutation burden and high expression level of HLA-E significantly reduced progression-free survival. We identified metagenomic species and functional pathways that differed in abundance in relation to responses to ICT. Data on differential enrichment of taxa and predicted microbial functions in NSCLC patients responding or non-responding to ICT allowed the establishment of random forest algorithm-adopted models robustly predicting the probability of whether or not a given patient would benefit from ICT.

CONCLUSIONS

Overall, our results identified links between gut microbial composition and immunotherapy efficacy in Chinese NSCLC patients indicating the potential for such analyses to predict outcome prior to ICT.

摘要

背景

程序性死亡蛋白1(PD-1)及其配体(PD-L1)是免疫检查点疗法(ICT)的核心靶点,该疗法可阻断肿瘤细胞引发的免疫逃逸相关通路。已研发出多种PD-1抑制剂,但这些抑制剂的疗效差异很大,通常低于50%。研究表明,ICT的疗效取决于肠道微生物群,使用小鼠模型的实验甚至证明,调节肠道微生物群可能会提高ICT的疗效。

方法

我们对85例接受抗PD-1抗体治疗的晚期非小细胞肺癌(NSCLC)汉族患者进行了随访。在开始治疗前采集肿瘤活检样本,用于全外显子测序和变异检测。在抗PD-1抗体给药期间,每两周采集一次粪便样本,用于宏基因组测序。我们建立了肠道微生物组丰度图谱,以确定特定微生物分类群、潜在功能和治疗反应之间的显著关联。使用区分不同反应组的选定标志物训练基于随机森林的预测模型。

结果

接受抗生素治疗的NSCLC患者生存时间最短。低肿瘤突变负担和高HLA-E表达水平显著缩短了无进展生存期。我们确定了与ICT反应相关的宏基因组物种和功能通路,其丰度存在差异。NSCLC患者对ICT有反应或无反应时,分类群差异富集数据和预测的微生物功能数据有助于建立随机森林算法模型,该模型能够可靠地预测给定患者是否会从ICT中获益。

结论

总体而言,我们的研究结果确定了中国NSCLC患者肠道微生物组成与免疫治疗疗效之间的联系,表明此类分析在ICT前预测结果的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2121/9069064/52f0b407c3b7/fonc-12-837525-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验