Advances in Clinical Medicine
Vol. 13  No. 08 ( 2023 ), Article ID: 70391 , 8 pages
10.12677/ACM.2023.1381754

肠道菌群与肺癌免疫治疗的研究进展

谢欣悦,赵红*

延安大学附属医院肿瘤科,陕西 延安

收稿日期:2023年7月13日;录用日期:2023年8月3日;发布日期:2023年8月10日

摘要

肠道菌群与人体共同进化,通过代谢、炎症、免疫等方面参与维持人体健康。人类与微生物之间存在一定的动态平衡,但不当饮食、各种医疗措施打破这种平衡状态,导致菌群失调,继而引起各种疾病。肠道菌群在肿瘤诊断和治疗方面是目前的研究热点。在肺癌的治疗中,免疫疗法应用广泛且发挥了很好的作用,但不同人群对免疫治疗的疗效以及不良反应存在很大差异。大量研究表明肠道菌群与肺癌的发生发展以及免疫治疗均有关联。本文将对肺癌患者肠道菌群与免疫治疗的研究进展进行综述,探讨肠道菌群对于肺癌的发生、免疫治疗疗效、免疫相关不良事件的影响,以及目前能够通过干预肠道菌群增加免疫治疗疗效的方法。

关键词

肠道菌群,肺癌,免疫治疗

Research Progress on Gut Microbiota and Immunotherapy of Lung Cancer

Xinyue Xie, Hong Zhao*

Department of Oncology, Affiliated Hospital of Yan’an University, Yan’an Shaanxi

Received: Jul. 13th, 2023; accepted: Aug. 3rd, 2023; published: Aug. 10th, 2023

ABSTRACT

The gut microbiota has co-evolved with the human body and participates in maintaining human health through metabolism, inflammation, immunity, and other aspects. There is a certain dynamic balance between humans and microorganisms, but improper diet and various medical measures disrupt this equilibrium and lead to gut microbiota dysbiosis, which subsequently causes various diseases. Gut microbiota is a current research hotspot in tumor diagnosis and treatment. In the treatment of lung cancer, immunotherapy is widely used and has played a good role, but the efficacy and adverse effects of immunotherapy vary greatly among different populations. Numerous studies have shown that gut microbiota is associated with the development of lung cancer and immunotherapy. In this paper, we review the current research on gut microbiota and immunotherapy in lung cancer patients, and discuss the effects of gut microbiota on lung cancer development, immunotherapy efficacy and immune-related adverse events, as well as the current methods to increase the efficacy of immunotherapy through gut microbiota intervention.

Keywords:Gut Microbiota, Lung Cancer, Immunotherapy

Copyright © 2023 by author(s) and Hans Publishers Inc.

This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).

http://creativecommons.org/licenses/by/4.0/

1. 肠道菌群

肠道是一个大型微生物生态系统,含多达100万亿(1014)个微生物,是体细胞和生殖细胞总数的10倍,其中绝大多数在结肠。健康成人肠道菌群以拟杆菌门和厚壁菌门为主,及较小比例的放线菌门、变形菌门、疣菌门、产甲烷古生菌、真菌和多种噬菌体。肠道菌群通过肠道上皮细胞以及合成代谢产物维持与宿主的共生关系,但当平衡被打破时,可能与多种疾病的发生有关 [1] [2] 。

肠道菌群与性别、年龄、饮食、新生儿的分娩方式、宿主遗传特征、免疫反应、抗生素、免疫抑制药物、感染、昼夜节律、环境微生物暴露相关,每个人的肠道菌群是独一无二的 [2] 。Tom等提出了两个可能解释微生物群和宿主之间关系的模型,一是单向模型,即一个主要原因导致单向过程,如具有特定遗传背景的个体在触发环境因素后会诱导疾病的发生,从而导致肠道菌群的改变,继而引起全身免疫反应。二是多向模型,模型的四个主要组成部分,基因、微生物群、环境和免疫反应之间缺乏平衡导致疾病的发生 [1] 。

2. 肠道菌群与肺癌

2.1. 肺癌患者肠道菌群的变化

尽管个体间存在差异,在肺癌患者与健康人群中有以下菌群表现出显著差异。Zhuang等 [3] 发现,健康对照组中放线菌在门水平与纲水平上增加,双歧杆菌在目水平与科水平丰度更高,而肺癌组中肠球菌科的数量增加。Zheng等 [4] 发现早期肺癌组中变形菌门、瘤胃球菌属高度富集,而健康组中链球菌属、双歧杆菌属和韦荣氏球菌属显著富集。肿瘤组中较为丰富的菌群主要来自拟杆菌属和变形菌门,种类明显减少的主要来自厚壁菌门和放线菌门。Vernocchi等 [5] 发现Akkermansia muciniphilaRikenellaceae、拟杆菌属、PeptostreptococcaceaeMogibacteriaceae和梭菌科等共生菌在健康组中更丰富。在一项关于非小细胞肺癌(Non-small cell lung cancer, NSCLC)的研究中,厚壁菌门丰度减少,而变形菌门、梭杆菌属、粪杆菌属丰度升高 [6] 。

在两项根据不同病理类型分析的研究中,一项研究发现毛螺菌属、瘤胃球菌属、粪杆菌属、罗氏菌属和纺锤链杆属在肺腺癌患者中显著富集,在肺鳞癌和肺良性病变中无明显差异。嗜血杆菌属、普雷沃氏菌属、链球菌属和柠檬酸杆菌属在肺良性病变患者肠道中显著富集 [6] 。另一项研究发现巨球型菌属和Erysipelatoclostridium在肺腺癌组患者肠道中富集,而肠球菌属、韦荣氏球菌属、Selenomonas_4Eubacterium_eligens_group在肺鳞癌组患者肠道中富集。随着肺癌病理分期的增加,韦荣球菌的含量有增加的趋势 [7] 。还有研究根据生物标志物将新诊断肺癌患者分为CYFRA21-1阳性患者、NSE阳性患者和CEA阳性患者,肺癌患者中酸杆菌门、厚壁菌门、毛螺菌科的丰度明显低于健康对照组,变形菌门和疣微菌门的丰度明显高于健康对照组;NSE组的肠杆菌科、梭杆菌科和疣微菌科含量高于其他组,拟杆菌门丰度相对较低,而CEA组的梭杆菌门、拟杆菌科和链球菌科相对较多,CYF组中普雷沃菌科和韦荣氏球菌科较其他类群丰富 [8] 。综上所述,我们发现肺癌患者与健康组的肠道菌群存在差异,并且不同病理类型的肺癌患者肠道菌群特征也不同,因此,寻找特殊的具有代表性的菌群有望成为肺癌患者的预测标志物,但由于肠道菌群种类繁多,且受多种因素影响,需要大量的研究去证明。近来,关于肺部微生物与口腔微生物的研究也越来越多 [9] [10] [11] [12] 。

2.2. 肺癌患者肠道菌群的代谢变化

通过KEGG和COG途径发现,肺癌患者的微生物组在淀粉和蔗糖代谢、果糖和甘露糖代谢、半乳糖代谢、戊糖和葡萄糖醛酸的相互转化、戊糖磷酸途径以及ABC型转运途径中的丰度较低 [8] 。参与辅酶转运和代谢、氨基酸转运和代谢、细胞周期控制、细胞分裂的功能蛋白的表达均下降了10%以上,参与RNA加工和修饰的功能蛋白的表达下降了80%以上 [3] 。与细菌运动蛋白、细菌趋化性、黄酮和黄酮醇生物合成、凋亡和G蛋白偶联受体相关的途径减少。与细胞抗原、类固醇生物合成、泛素系统、转录相关蛋白、胆汁分泌和线粒体脂肪酸延伸相关的途径增多 [4] 。肠道菌群的变化影响了肺癌患者的代谢途径。

3. 肠道菌群在宿主中的作用机制

3.1. 肠–肺轴

“肠–肺轴”理论即抗原被肠道相关淋巴组织(gut-associated lymphoid tissue, GALT)捕获并传递给抗原提呈细胞,原始T和B细胞被激活后,迁移到肠系膜淋巴结继而进入胸导管和血流,最后分布到GALT、呼吸道和乳腺等各个效应点产生特异性IgA。肠道中的刺激转移到肺,肺又向肠道反馈,肠道再次发送信号,形成一个循环 [13] 。在肠道菌群耗尽的小鼠中,炎症、器官损伤和死亡率增加,而接受粪便微生物群移植后,肺细菌数、肿瘤坏死因子-α、白细胞介素-10水平恢复正常 [14] ,进一步证明了肠道菌群对宿主的保护作用以及肠–肺轴理论。研究发现节段丝状细菌通过诱导肠–肺轴Th17细胞表达双TCRs增强肺自身免疫 [15] [16] 。肠道菌群、免疫细胞、炎性介质从肠道迁移至肺从而发挥保护或伤害作用。

3.2. 短链脂肪酸(Short Chain Fatty Acids, SCFAs)

肠道菌群与肠道屏障共同维持肠道微环境的稳态。结肠杯状细胞产生粘液将腔内微生物与宿主上皮细胞物理分离,肠道粘液层是双层结构,内层由于粘蛋白-2、分泌型IgA及抗菌肽的水平高通常不存在微生物,SCFAs可以调节这些分子来维持粘膜免疫 [17] 。NSCLC患者的大部分肠道丁酸盐产生菌显著减少 [18] 。SCFAs能够直接或间接地影响上皮细胞、先天和适应性免疫细胞,并且能够在骨髓中启动髓系细胞,随后迁移到肺并形成抗炎环境 [19] 。目前,抑制组蛋白去乙酰酶和激活G蛋白偶联受体已经被确定为两种主要的信号机制 [20] 。研究发现,正丁酸盐通过抑制组蛋白去乙酰酶,下调NO,IL-6和IL-12等促炎介质以维持对共生菌的耐受性 [21] 。丁酸盐比丙酸盐更能有效地促进FOXP3的表达和IL-9的抑制以减轻肺部炎症 [22] 。丁酸盐通过解耦CD8+ T细胞糖酵解后的三羧酸循环,持续的利用谷氨酰胺和脂肪酸分解代谢促进氧化磷酸化,增强CD8+ T细胞的记忆潜能 [23] 。KiM等 [24] 研究发现丙酸钠通过降低G2/M期相关基因的转录,诱导细胞周期素依赖性激酶抑制剂p21的表达,从而诱导肺癌中H1299和H1703细胞系的凋亡。SCFAs的代谢产物如吲哚、吲哚3-甲基、丁醛3-甲基、戊醇和庚烷可能是调节健康肠道生态系统的重要信号分子 [5] 。SCFAs通过免疫、代谢、基因、炎症多方面保护宿主。

4. 肠道菌群与肺癌的免疫治疗

ICI (Immune checkpoint inhibitors, ICI)通过抑制免疫负调控起作用。虽然肺癌的免疫治疗显著延长了患者的生存期,但在临床应用中仍然有很多不足,如耐药、获益人群有限、不良反应等问题。肠道微生物与免疫治疗的疗效、不良反应都有着一定的关联。

4.1. 肠道菌群与免疫治疗疗效的关系

研究发现,抗生素的使用与接受免疫治疗的癌症患者较差的生存期相关 [25] 。在291名接受ICI治疗的晚期癌症患者中,接受了一个疗程的抗生素的中位总生存期显著降低,接受多个疗程患者的生存期更低 [26] 。ICI治疗后30天内使用抗生素的NSCLC患者的无进展生存期(progression-free survival, PFS)和总生存期(overall survival, OS)显著短于未使用抗生素的患者,但在开始治疗后60天内使用抗生素的患者与较短的OS显著相关,PFS却没有差异 [27] 。抗生素导致的低生存期可能与PD-L1表达有关,在PD-L1表达≥50%的NSCLC患者中,使用抗生素与OS和PFS显著缩短相关,在PD-L1表达<50%的NSCLC患者中没有负面影响 [28] 。

抗生素可能通过改变肠道菌群影响免疫治疗疗效。在一项接受抗PD-1(L1)单药治疗的晚期NSCLC患者的前瞻性研究中,抗生素的使用显著降低了α多样性,未使用抗生素患者的粪便中富含梭状芽胞杆菌,特别是瘤胃球菌科UCG 13、梭菌目和Agathobacter,而接受抗生素治疗患者的粪便富含Hungatella。在未使用抗生素的患者中,瘤胃球菌科UCG 13和Agathobacter在PFS > 6个月的患者中比例高,瘤胃球菌科UCG 13与梭菌目在OS > 12个月的患者中含量增加。此研究还纳入了组织学类型、分期、治疗方案、PD-L1表达、ECOG、PS进行多因素分析,结果显示瘤胃球菌科UCG 13与OS的改善有关 [29] 。接受纳武利尤单抗治疗前2个月到后1个月使用过抗生素的晚期NSCLC患者OS显著降低,而未使用抗生素患者的血液微生物高瓜氨酸率与更长的PFS和OS相关 [30] 。在一项NSCLC患者的回顾性研究中,使用抗生素的患者更有可能出现不良结果,但差异未达到统计学意义,为了进一步明确肠道菌群与ICI疗效的相关性,该研究团队正在开展一项前瞻性研究 [31] 。Mitchell等发现在ICI开始前接受抗生素的患者核仁素、MDA5、c反应蛋白和肝脏细胞质抗原1型抗体的水平较低,硫酸肝素和基质抗体水平较高,在ICI开始后使用抗生素的患者MDA5、CENP.B和核仁素抗体水平显著降低 [32] 。在Zhang等的研究中,抗生素的使用与肠道微生物多样性的减少显著相关,但与ICI疗效低无关 [33] 。也有研究认为抗生素的使用造成较差的生存结果更可能是混杂因素导致 [34] 。抗生素的使用种类、时间、用药方式、剂量等因素,以及样本量不足都可能造成不同的研究结果。在临床中,应严格按照规范使用抗生素,避免不良后果。

以下是不同免疫疗效中肠道菌群及相关代谢途径的研究。肠道菌群α多样性高与更好的抗PD-1反应和更长的PFS相关。双歧杆菌属、脱硫弧菌属、AlistipesAnaerostipesFaecalibacterium对抗PD-1治疗有利,而梭杆菌属对抗PD-1治疗有害 [35] 。Vernocchi等 [8] 发现Granulicatella与抗PD-1治疗反应显著相关。Song等前瞻性分析了63名接受抗PD-1(L1)治疗的中国晚期NSCLC患者,PFS ≥ 6个月患者中最显著的菌群是ParabacteroidesMethanobacteriaceae,主要功能是甲烷代谢、苯甲酸酯降解、细菌分泌系统、二甲苯降解和核糖体合成;PFS < 6个月的患者中,菌群丰富于韦荣氏球菌属、SelenomonadalesNegativicutes,主要功能类别为细菌鞭毛组装、细菌趋化、半乳糖代谢、细菌双组分调节系统和钙信号通路 [36] 。Cox比例风险模型显示NSCLC患者的活检标本中γ-变形菌门与低PD-L1表达和较差的生存期显著相关 [37] 。Heshiki等 [38] 发现应答者(responser, R)比无应答者(non-responser, NR)的肠道菌群具有更高的α多样性,NR的厚壁菌门/拟杆菌门比例显著高于R。ABC转运体、磷酸转移酶系统、碳水化合物代谢通路和异生物降解途径在NR富集,黄酮类化合物、玉米素和次级胆汁酸等代谢产物的生物合成途径在R中显著富集。接受纳武利尤单抗治疗的NSCLC患者的肠道代谢组学分析显示,2-戊酮和十三烷与早期进展显著相关,SCFAs、赖氨酸和烟酸与长期有益作用显著相关 [39] 。不同的免疫疗效中肠道菌群及相关代谢途径不同,肠道菌群有望成为预测肺癌免疫治疗疗效的标志物。

4.2. 肠道菌群与免疫相关不良事件的关系

临床约40%的肿瘤患者使用ICI后会出现不同程度的皮疹、间质性肺炎、肠炎、肝炎等各种免疫相关不良事件(Immune-Related Adverse Events, irAEs)。低微生物群多样性与ICI相关的皮肤毒性有关 [33] ,取自26例晚期肺癌患者首次注射抗PD-L1前的粪便样本中,拟杆菌门在无腹泻患者中较高,而厚壁菌门较低。拟杆菌门的拟杆菌和Parabacteroides,厚壁菌门的Phascolarctobacterium在无腹泻患者中更丰富,而变形菌门的韦永氏球菌属含量较低 [40] 。一项前瞻性、单中心队列试点研究中,双歧杆菌(放线菌门)和Desulfovibrio (变形菌门)的富集与irAEs的降低显著相关 [41] 。乳酸杆菌科和Raoultella在irAEs症状较轻的患者中富集,而Agathobacter则与严重的irAEs症状相关 [29] 。这些与免疫相关不良事件相关的菌群可以作为预后的生物标志物,指导治疗方式的选择。

5. 肠道菌群在恶性肿瘤中的治疗作用

由于微生物和宿主在共同进化,因此利用微生物来治疗或预防可能不会产生严重的副作用 [2] 。目前,主要通过补充益生菌、益生元,粪便菌群移植等方面进行。

一项包括美国、欧洲和亚洲的144万多人的前瞻性研究中,在调整了吸烟和其他肺癌危险因素后,膳食纤维(益生元的主要来源)和酸奶(一种益生菌食品)摄入量与肺癌风险呈负相关,表明了益生元和益生菌对肺癌的潜在保护作用 [42] 。一项118例NSCLC患者的回顾性研究中,开始ICI前6个月内或同时接受益生菌丁酸梭菌属直到停止治疗的患者与未接受丁酸梭菌属的患者相比,生存结果得到显著改善。而且,接受抗生素治疗的患者在接受益生菌丁酸梭菌属治疗后获得了无进展生存期和总生存期的改善 [43] 。口服补充富含多酚的浆果卡姆果会改变小鼠肠道微生物的组成,增强抗肿瘤活性和抗PD-1反应。卡姆果中的鞣花鞣质益生元栗木鞣花素可以增多与高效免疫治疗反应相关的细菌(瘤胃球菌科和Alistipes),并提高肿瘤微环境中的CD8+/FOXP3+CD4+的比例,并且诱导牛磺酸结合胆汁酸的增加 [44] 。Lee等 [45] 发现两歧双歧杆菌在R中显著富集,而Akkermansia muciniphilaBlautia beum在NR中富集。与单独使用抗PD-1的小鼠相比,两歧双歧杆菌联合抗PD-1治疗小鼠的抗肿瘤淋巴细胞数量以及效应CD8+ T/Treg细胞比例增加,IFN-γ、IL-2的表达增加,血清l-色氨酸增加。研究还发现,两歧双歧杆菌单独治疗可以抑制肿瘤生长。Huang等 [46] 采用人参多糖(ginseng polysaccharides, GPs)和αPD-1单克隆抗体(αPD-1 monoclonal antibody, mAb)对同源小鼠模型进行联合治疗,发现GPs通过增加微生物代谢产物戊酸、降低L-kynurenine和kynurenine/tryptophan的比值,增加了αPD-1 mAb的抗肿瘤反应。联合治疗增加了活化的CD8+ T细胞数量,减少了周围Foxp3+调节性T细胞数量。Routy等 [47] 发现将对ICI有反应癌症患者的粪便菌群移植到无菌或经抗生素治疗的小鼠中可以改善抗肿瘤效果。患者粪便样本的宏基因组学显示了ICI的临床反应与Akkermansia muciniphila的相对丰度之间存在相关性。于是给予粪便菌群移植无应答者的小鼠口服Akkermansia muciniphila发现,通过增加小鼠瘤床中CCR9+CXCR3+CD4+ T淋巴细胞的招募,以IL-12依赖性的方式恢复了PD-1阻断的疗效。从健康人体粪便中分离出的11种细菌菌株混合物能够在肠道中诱导IFNγ+ CD8 T cells,对细胞内病原体李斯特菌具有抗性,与ICIs联合使用可有效抑制肿瘤生长 [48] 。综上,针对肠道菌群的治疗可以改善免疫治疗的疗效,只有完全了解其机制,才能针对性的治疗以达到更好效果。

6. 小结

肠道菌群在正常情况下处于动态平衡,维持着人体健康,而菌群失调会导致各种疾病的发生。随着对肠道菌群更多的研究,利用肠道菌群预测肺癌的发生发展、免疫治疗疗效以及免疫相关不良事件,利用肠道菌群来增强肺癌免疫治疗疗效都成为可能。由于个体之间的差异以及肠道菌群的复杂性,研究结果并不完全一致。在未来,需要更多的去研究肠道菌群与宿主相互作用的机制,研究肠道菌群、抗生素、ICI疗效及不良反应之间的关系,以指导临床治疗。

文章引用

谢欣悦,赵 红. 肠道菌群与肺癌免疫治疗的研究进展
Research Progress on Gut Microbiota and Immunotherapy of Lung Cancer[J]. 临床医学进展, 2023, 13(08): 12514-12521. https://doi.org/10.12677/ACM.2023.1381754

参考文献

  1. 1. Van de Wiele, T., Van Praet, J.T., Marzorati, M., Drennan, M.B. and Elewaut, D. (2016) How the Microbiota Shapes Rheumatic Diseases. Nature Reviews Rheumatology, 12, 398-411. https://doi.org/10.1038/nrrheum.2016.85

  2. 2. Lynch, S.V. and Pedersen, O. (2016) The Human Intestinal Micro-biome in Health and Disease. The New England Journal of Medicine, 375, 2369-2379. https://doi.org/10.1056/NEJMra1600266

  3. 3. Zhuang, H., Cheng, L., Wang, Y., et al. (2019) Dysbiosis of the Gut Microbiome in Lung Cancer. Frontiers in Cellular and Infection Microbiology, 9, Article 112. https://doi.org/10.3389/fcimb.2019.00112

  4. 4. Zheng, Y., Fang, Z., Xue, Y., et al. (2020) Specific Gut Microbi-ome Signature Predicts the Early-Stage Lung Cancer. Gut Microbes, 11, 1030-1042. https://doi.org/10.1080/19490976.2020.1737487

  5. 5. Vernocchi, P., Gili, T., Conte, F., et al. (2020) Network Analysis of Gut Microbiome and Metabolome to Discover Microbiota-Linked Biomarkers in Patients Affected by Non-Small Cell Lung Cancer. International Journal of Molecular Sciences, 21, Article 8730. https://doi.org/10.3390/ijms21228730

  6. 6. 袁文杰, 郭亚琼, 韩毅, 等. 非小细胞肺癌患者肠道微生物特征分析[J]. 微生物学报, 2021, 61(9): 2776-2790.

  7. 7. 安瑞. 肺癌患者肠道微生物群落结构特征的初步研究[D]: [硕士或博士学位论文]. 杭州: 南京医科大学, 2021.

  8. 8. Liu, F., Li, J., Guan, Y., et al. (2019) Dysbiosis of the Gut Mi-crobiome Is Associated with Tumor Biomarkers in Lung Cancer. International Journal of Biological Sciences, 15, 2381-2392. https://doi.org/10.7150/ijbs.35980

  9. 9. Weinberg, F., Dickson, R.P., Nagrath, D. and Ramnath, N. (2020) The Lung Microbiome: A Central Mediator of Host Inflammation and Metabolism in Lung Cancer Patients? Cancers, 13, Article 13. https://doi.org/10.3390/cancers13010013

  10. 10. Lu, H., Gao, N.L., Tong, F., et al. (2021) Alterations of the Human Lung and Gut Microbiomes in Non-Small Cell Lung Carcinomas and Distant Metastasis. Microbiology Spectrum, 9, e00802-21. https://doi.org/10.1128/Spectrum.00802-21

  11. 11. Ma, Y., Qiu, M.T., Wang, S.S., et al. (2021) Distinct Tumor Bac-terial Microbiome in Lung Adenocarcinomas Manifested as Radiological Subsolid Nodules. Translational Oncology, 14, Article ID: 101050. https://doi.org/10.1016/j.tranon.2021.101050

  12. 12. Lim, M.Y., Hong, S., Hwang, K.H., et al. (2021) Diagnostic and Prognostic Potential of the Oral and Gut Microbiome for Lung Adenocarcinoma. Clinical and Translational Medicine, 11, e508. https://doi.org/10.1002/ctm2.508

  13. 13. He, Y., Wen, Q., Yao, F., et al. (2017) Gut-Lung Axis: The Microbial Contributions and Clinical Implications. Critical Reviews in Microbiology, 43, 81-95. https://doi.org/10.1080/1040841X.2016.1176988

  14. 14. Schuijt, T.J., Lankelma, J.M., Scicluna, B.P., et al. (2016) The Gut Microbiota Plays a Protective Role in the Host Defence against Pneumococcal Pneumonia. Gut, 65, 575-583. https://doi.org/10.1136/gutjnl-2015-309728

  15. 15. Atarashi, K., Tanoue, T., Ando, M., et al. (2015) Th17 Cell In-duction by Adhesion of Microbes to Intestinal Epithelial Cells. Cell, 163, 367-380. https://doi.org/10.1016/j.cell.2015.08.058

  16. 16. Bradley, C.P., Teng, F., Felix, K.M., et al. (2017) Segmented Fila-mentous Bacteria Provoke Lung Autoimmunity by Inducing Gut-Lung Axis Th17 Cells Expressing Dual TCRs. Cell Host Microbe, 2, 697-704.E4. https://doi.org/10.1016/j.chom.2017.10.007

  17. 17. Birchenough, G.M., Nystrom, E.E., Johansson, M.E., et al. (2016) A Sentinel Goblet Cell Guards the Colonic Crypt by Triggering Nlrp6-Dependent Muc2 Secretion. Science, 352, 1535-1542. https://doi.org/10.1126/science.aaf7419

  18. 18. Gui, Q., Li, H., Wang, A., et al. (2020) The Association between Gut Butyrate-Producing Bacteria and Non-Small-Cell Lung Cancer. Journal of Clinical Laboratory Analysis, 34, e23318. https://doi.org/10.1002/jcla.23318

  19. 19. Dang, A.T. and Marsland, B.J. (2019) Microbes, Metabolites, and the Gut-Lung Axis. Mucosal Immunology, 12, 843-850. https://doi.org/10.1038/s41385-019-0160-6

  20. 20. Tan, J., McKenzie, C., Potamitis, M., et al. (2014) The Role of Short-Chain Fatty Acids in Health and Disease. Advances in Im-munology, 121, 91-119. https://doi.org/10.1016/B978-0-12-800100-4.00003-9

  21. 21. Chang, P.V., Hao, L., Offer-manns, S. and Medzhitov, R. (2014) The Microbial Metabolite Butyrate Regulates Intestinal Macrophage Function via Histone Deacetylase Inhibition. Proceedings of the National Academy of Sciences of the United States of America, 111, 2247-2252. https://doi.org/10.1073/pnas.1322269111

  22. 22. Vieira, R.S., Castoldi, A., Basso, P.J., et al. (2019) Bu-tyrate Attenuates Lung Inflammation by Negatively Modulating Th9 Cells. Frontiers in Immunology, 10, Article 67. https://doi.org/10.3389/fimmu.2019.00067

  23. 23. Bachem, A., Makhlouf, C., Binger, K.J., et al. (2019) Microbio-ta-Derived Short-Chain Fatty Acids Promote the Memory Potential of Antigen-Activated CD8+ T Cells. Immunity, 51, 285-297.E5. https://doi.org/10.1016/j.immuni.2019.06.002

  24. 24. Kim, K., Kwon, O., Ryu, T.Y., et al. (2019) Propionate of a Microbiota Metabolite Induces Cell Apoptosis and Cell Cycle Arrest in Lung Cancer. Molecular Medicine Reports, 20, 1569-1574. https://doi.org/10.3892/mmr.2019.10431

  25. 25. Gaucher, L., Adda, L., Séjourné, A., et al. (2021) Asso-ciations between Dysbiosis-Inducing Drugs, Overall Survival and Tumor Response in Patients Treated with Immune Checkpoint Inhibitors. Therapeutic Advances in Medical Oncology, 13. https://doi.org/10.1177/17588359211000591

  26. 26. Tinsley, N., Zhou, C., Tan, G., et al. (2020) Cumulative Antibi-otic Use Significantly Decreases Efficacy of Checkpoint Inhibitors in Patients with Advanced Cancer. Oncologist, 25, 55-63. https://doi.org/10.1634/theoncologist.2019-0160

  27. 27. Derosa, L., Hellmann, M.D., Spaziano, M., et al. (2018) Negative Association of Antibiotics on Clinical Activity of Immune Checkpoint Inhibitors in Patients with Ad-vanced Renal Cell and Non-Small-Cell Lung Cancer. Annals of Oncology, 29, 1437-1444. https://doi.org/10.1093/annonc/mdy103

  28. 28. Ochi, N., Ichihara, E., Takigawa, N., et al. (2021) The Effects of An-tibiotics on the Efficacy of Immune Checkpoint Inhibitors in Patients with Non-Small-Cell Lung Cancer Differ Based on PD-L1 Expression. European Journal of Cancer, 149, 73-81. https://doi.org/10.1016/j.ejca.2021.02.040

  29. 29. Hakozaki, T., Richard, C., Elkrief, A., et al. (2020) The Gut Micro-biome Associates with Immune Checkpoint Inhibition Outcomes in Patients with Advanced Non-Small Cell Lung Cancer. Cancer Immunology Research, 8, 1243-1250. https://doi.org/10.1158/2326-6066.CIR-20-0196

  30. 30. Ouaknine Krief, J., de Tauriers P.H., Dumenil, C., et al. (2019) Role of Antibiotic Use, Plasma Citrulline and Blood Microbiome in Advanced Non-Small Cell Lung Cancer Pa-tients Treated with Nivolumab. Journal for ImmunoTherapy of Cancer, 7, Article 176. https://doi.org/10.1186/s40425-019-0658-1

  31. 31. Nyein, A.F., Bari, S., Hogue, S., et al. (2022) Effect of Prior An-tibiotic or Chemotherapy Treatment on Immunotherapy Response in Non-Small Cell Lung Cancer. BMC Cancer, 22, Ar-ticle No. 101. https://doi.org/10.1186/s12885-022-09210-2

  32. 32. Itzstein, M.S.V., Gonugunta, A.S., Sheffield, T., et al. (2022) Association between Antibiotic Exposure and Systemic Immune Parameters in Cancer Patients Receiving Checkpoint In-hibitor Therapy. Cancers, 14, Article 1327. https://doi.org/10.3390/cancers14051327

  33. 33. Zhang, F., Ferrero, M., Dong, N., et al. (2021) Analysis of the Gut Microbiota: An Emerging Source of Biomarkers for Immune Checkpoint Blockade Therapy in Non-Small Cell Lung Cancer. Cancers, 13, Article 2514. https://doi.org/10.3390/cancers13112514

  34. 34. Verschueren, M.V., van der Welle, C.M.C., Tonn, M., et al. (2021) The Association between Gut Microbiome Affecting Concomitant Medication and the Effectiveness of Immunotherapy in Patients with Stage IV NSCLC. Scientific Reports, 11, Article No. 23331. https://doi.org/10.1038/s41598-021-02598-0

  35. 35. Zhang, C., Wang, J., Sun, Z., et al. (2021) Commensal Microbi-ota Contributes to Predicting the Response to Immune Checkpoint Inhibitors in Non-Small-Cell Lung Cancer Patients. Cancer Science, 112, 3005-3017. https://doi.org/10.1111/cas.14979

  36. 36. Song, P., Yang, D., Wang, H., et al. (2020) Relationship between Intestinal Flora Structure and Metabolite Analysis and Immunotherapy Efficacy in Chinese NSCLC Patients. Thoracic Cancer, 11, 1621-1632. https://doi.org/10.1111/1759-7714.13442

  37. 37. Boesch, M., Baty, F., Albrich, W.C., et al. (2021) Local Tumor Mi-crobial Signatures and Response to Checkpoint Blockade in Non-Small Cell Lung Cancer. Oncoimmunology, 10, Article 1988403. https://doi.org/10.1080/2162402X.2021.1988403

  38. 38. Heshiki, Y., Vazquez-Uribe, R., Li, J., et al. (2020) Pre-dictable Modulation of Cancer Treatment Outcomes by the Gut Microbiota. Microbiome, 8, Article No. 28. https://doi.org/10.1186/s40168-020-00811-2

  39. 39. Botticelli, A., Vernocchi, P., Marini, F., et al. (2020) Gut Metab-olomics Profiling of Non-Small Cell Lung Cancer (NSCLC) Patients under Immunotherapy Treatment. Journal of Translational Medicine, 18, Article No. 49. https://doi.org/10.1186/s12967-020-02231-0

  40. 40. Liu, T., Xiong, Q., Li, L.L. And Hu, Y. (2019) Intestinal Micro-biota Predicts Lung Cancer Patients at Risk of Immune-Related Diarrhea. Immunotherapy, 11, 385-396. https://doi.org/10.2217/imt-2018-0144

  41. 41. Chau, J., Yadav, M., Liu, B., et al. (2021) Prospective Correlation be-tween the Patient Microbiome with Response to and Development of Immune-Mediated Adverse Effects to Immuno-therapy in Lung Cancer. BMC Cancer, 21, Article No. 808. https://doi.org/10.1186/s12885-021-08530-z

  42. 42. Yang, J.J., Yu, D.X. and Shu, X.O. (2020) Association of Dietary Fiber and Yogurt Consumption with Lung Cancer Risk: A Pooled Analysis. JAMA Oncology, 6, 788-789. https://doi.org/10.1001/jamaoncol.2020.0270

  43. 43. Tomita, Y., Ikeda, T., Sakata, S., et al. (2020) Association of Probiotic Clostridium butyricum Therapy with Survival and Response to Immune Checkpoint Blockade in Patients with Lung Cancer. Cancer Immunology Research, 8, 1236-1242. https://doi.org/10.1158/2326-6066.CIR-20-0051

  44. 44. Messaoudene, M., Pidgeon, R., Richard, C., et al. (2022) A Natural Polyphenol Exerts Antitumor Activity and Circumvents Anti-PD-1 Resistance through Effects on the Gut Micro-biota. Cancer Discovery, 12, 1070-1087. https://doi.org/10.1158/2159-8290.CD-21-0808

  45. 45. Lee, S.H., Cho, S.Y., Yoon, Y., et al. (2021) Bifidobacterium bifidum Strains Synergize with Immune Checkpoint Inhibitors to Reduce Tumour Burden in Mice. Nature Microbiology, 6, 277-288. https://doi.org/10.1038/s41564-020-00831-6

  46. 46. Huang, J.M., Liu, D., Wang, Y.W., et al. (2022) Ginseng Poly-saccharides Alter the Gut Microbiota and Kynurenine/Tryptophan Ratio, Potentiating the Antitumour Effect of Antipro-grammed Cell Death 1/Programmed Cell Death Ligand 1 (Anti-PD-1/PD-L1) Immunotherapy. Gut, 71, 734-745. https://doi.org/10.1136/gutjnl-2020-321031

  47. 47. Routy, B., Le Chatelier, E., Derosa, L., et al. (2018) Gut Micro-biome Influences Efficacy of PD-1-Based Immunotherapy against Epithelial Tumors. Science, 359, 91-97.

  48. 48. Tanoue, T., Morita, S., Plichta, D.R., et al. (2019) A Defined Commensal Consortium Elicits CD8 T Cells and Anti-Cancer Im-munity. Nature, 565, 600-605. https://doi.org/10.1038/s41586-019-0878-z

  49. NOTES

    *通讯作者。

期刊菜单