Pub Date : 2018-09-01DOI: 10.1158/2326-6074.TUMIMM17-A02
Chi Ma, Miaojun Han, B. Heinrich, Qiong Fu, Qian-fei Zhang, X. Wang, G. Trinchieri, T. Greten
Aim: The gut microbiome can modify tumor immunity and has been suggested to be involved in the development and growth of liver cancer as well as metastasis in the liver. However, it remains unknown how the gut microbiome controls hepatic immune responses. This study was designed to exam the effect of the gut microbiome on liver antitumor immunity, and to study potential mechanism. Experimental Procedure: An antibiotic cocktail containing 0.5g/L vancomycin, 0.5 g/L neomycin and 0.6 g/L primaxin in drinking water was given to reduce mouse gut microbiota. Control mice were kept on regular water. EL4 thymoma cells were injected s.c. to induces spontaneous liver metastasis. B16 melanoma and CT26 colon cancer cells were injected intrasplenically to form liver metastasis. Lung metastasis was induced by tail injection of tumor cells. Spontaneous hepatocellular carcinomas were studied in TRE-MYC mice. Gut bacteria and metabolic studies were performed. Results: Antibiotic cocktail efficiently depleted gut bacteria. Removing gut commensal bacteria did not affect the growth of primary s.c. EL4 tumors, but impaired formation of liver metastasis in different models. The inhibitory effect on liver metastasis by removing gut microbiome was found after intrasplenic injection of tumor cells to form liver metastasis using both B16 melanoma and CT26 colon cancer tumor cells as well as in TRE-MYC mice. Interestingly, formation of lung metastasis caused by tail vein injection of B16 cells was not impaired by antibiotics treatment, suggesting a liver specific effect. The inhibition of liver metastasis by antibiotic treatment was absent in Rag1 knockout mice, suggesting that the observed mechanism is mediated by the adaptive immune system. A detailed mechanism how the gut microbiome causes metabolic liver changes and thereby growth of liver tumors will be presented. Conclusion: Our results suggest that the gut microbiome affects the liver immune microenvironment and modulates antitumor immunity Citation Format: Chi Ma, Miaojun Han, Bernd Heinrich, Qiong Fu, Qianfei Zhang, Xin W. Wang, Giorgio Trinchieri, Tim Greten. Gut microbiome controls growth of liver tumors [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2017 Oct 1-4; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2018;6(9 Suppl):Abstract nr A02.
目的:肠道微生物群可以改变肿瘤免疫，并被认为参与了肝癌的发生、生长和肝脏转移。然而，肠道微生物群如何控制肝脏免疫反应仍不清楚。本研究旨在探讨肠道菌群对肝脏抗肿瘤免疫的影响，并探讨其可能的机制。实验步骤:在饮用水中加入含有0.5g/L万古霉素、0.5g/L新霉素、0.6 g/L原霉素的抗生素鸡尾酒，减少小鼠肠道菌群。对照组小鼠定期饮水。将EL4胸腺瘤细胞注射sc诱导自发性肝转移。B16黑色素瘤和CT26结肠癌细胞经脾内注射形成肝转移。肿瘤细胞尾注射诱导肺转移。研究了TRE-MYC小鼠的自发性肝细胞癌。进行肠道细菌和代谢研究。结果:鸡尾酒抗生素能有效地减少肠道细菌。在不同的模型中，去除肠道共生菌不影响原发s.c. EL4肿瘤的生长，但会损害肝转移的形成。B16黑色素瘤和CT26结肠癌肿瘤细胞脾脏内注射肿瘤细胞形成肝转移后，以及在TRE-MYC小鼠中，发现去除肠道微生物组对肝转移有抑制作用。有趣的是，抗生素治疗并未影响尾静脉注射B16细胞引起的肺转移的形成，提示其具有肝脏特异性作用。在Rag1基因敲除小鼠中，抗生素治疗对肝转移的抑制作用不存在，提示观察到的机制是由适应性免疫系统介导的。肠道微生物组如何引起肝脏代谢变化从而导致肝脏肿瘤生长的详细机制将被提出。结论:我们的研究结果表明，肠道微生物组影响肝脏免疫微环境并调节抗肿瘤免疫。引用本文:马驰，韩淼军，Bernd Heinrich，傅琼，张前飞，王新伟，Giorgio Trinchieri, Tim Greten。肠道微生物组控制肝脏肿瘤的生长[摘要]。摘自:AACR肿瘤免疫学和免疫治疗特别会议论文集;2017年10月1-4日;波士顿,MA。费城(PA): AACR;癌症免疫学杂志，2018;6(9增刊):摘要nr A02。
{"title":"Abstract A02: Gut microbiome controls growth of liver tumors","authors":"Chi Ma, Miaojun Han, B. Heinrich, Qiong Fu, Qian-fei Zhang, X. Wang, G. Trinchieri, T. Greten","doi":"10.1158/2326-6074.TUMIMM17-A02","DOIUrl":"https://doi.org/10.1158/2326-6074.TUMIMM17-A02","url":null,"abstract":"Aim: The gut microbiome can modify tumor immunity and has been suggested to be involved in the development and growth of liver cancer as well as metastasis in the liver. However, it remains unknown how the gut microbiome controls hepatic immune responses. This study was designed to exam the effect of the gut microbiome on liver antitumor immunity, and to study potential mechanism. Experimental Procedure: An antibiotic cocktail containing 0.5g/L vancomycin, 0.5 g/L neomycin and 0.6 g/L primaxin in drinking water was given to reduce mouse gut microbiota. Control mice were kept on regular water. EL4 thymoma cells were injected s.c. to induces spontaneous liver metastasis. B16 melanoma and CT26 colon cancer cells were injected intrasplenically to form liver metastasis. Lung metastasis was induced by tail injection of tumor cells. Spontaneous hepatocellular carcinomas were studied in TRE-MYC mice. Gut bacteria and metabolic studies were performed. Results: Antibiotic cocktail efficiently depleted gut bacteria. Removing gut commensal bacteria did not affect the growth of primary s.c. EL4 tumors, but impaired formation of liver metastasis in different models. The inhibitory effect on liver metastasis by removing gut microbiome was found after intrasplenic injection of tumor cells to form liver metastasis using both B16 melanoma and CT26 colon cancer tumor cells as well as in TRE-MYC mice. Interestingly, formation of lung metastasis caused by tail vein injection of B16 cells was not impaired by antibiotics treatment, suggesting a liver specific effect. The inhibition of liver metastasis by antibiotic treatment was absent in Rag1 knockout mice, suggesting that the observed mechanism is mediated by the adaptive immune system. A detailed mechanism how the gut microbiome causes metabolic liver changes and thereby growth of liver tumors will be presented. Conclusion: Our results suggest that the gut microbiome affects the liver immune microenvironment and modulates antitumor immunity Citation Format: Chi Ma, Miaojun Han, Bernd Heinrich, Qiong Fu, Qianfei Zhang, Xin W. Wang, Giorgio Trinchieri, Tim Greten. Gut microbiome controls growth of liver tumors [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2017 Oct 1-4; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2018;6(9 Suppl):Abstract nr A02.","PeriodicalId":309751,"journal":{"name":"Cancer and the Microbiome","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130547563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-09-01DOI: 10.1158/2326-6074.TUMIMM17-A04
Chao-peng Zhang, P. Thakkar, F. Schnoll-Sussman, Bridget McClure, Michelle Bigg, Gregory F. Sonnenberg, D. Betel, M. Shah
Gastric cancer carcinogenesis is associated with chronic inflammation, most commonly the result of Helicobacter pylori chronic infection in the stomach antrum. The development of gastric cancer in the context of chronic H. pylori infection is multifactorial, encompassing both bacterial factors and the altered immune microenvironment. However, a comprehensive analysis of the relation between inflammation and host microbial population in patient tissue samples has not previously been explored. We proposed an unbiased study to evaluate the relationships among microbiome composition, host immune response and genomic characterization from next-generation sequencing of gastric biopsy samples. Patients undergoing upper endoscopy without chronic inflammatory disease or chronic NSAID use were eligible for participation. Endoscopic biopsies from gastric fundus, body, and antrum were collected from patients with active H. pylori infection (n=21), prior infection (n=22) and no prior infection (n=26), and were sequenced at 10X to 30X coverage. In total, 77 gastric biopsies from 69 patients were freshly frozen for whole genome sequencing (WGS) and transcriptome (RNASeq) analysis. Detecting the microbiome from human biopsy sequencing data directly is challenging due to the low microbial content. A novel computational pipeline was developed to address this problem specifically (Zhang et al., Genome Biology 2015). A robust H. pylori signal was detected in samples from clinically verified H. pylori infected patients, and the results were further validated by qPCR. In our analysis population, in addition to identification of H. pylori, several bacteria associated with other cancers were also detected in several biopsy samples, such as Prevotella melaninogenica, Veillonella parvula and Fusobacterium nucleatum. H. pylori infection was associated with reduced microbial biodiversity compared to prior infection or control tissue (p=0.02). H. pylori active infection samples have a distinct non-H. pylori microbiome compared to prior infection and control samples. We also identified 5 patients with prior infection and 1 control patient with occult H. pylori infection (e.g., asymptomatic patients). To characterize the immune infiltration in the mucosal biopsy samples, we developed a 176-gene panel, collected from multiple published studies, to define the immune signatures. The expression profile of this immune gene panel was used evaluate the immune infiltration levels of multiple immune cell types. The result of unsupervised clustering revealed a much higher immune infiltration in H. pylori positive samples compared to uninfected samples, especially for CD8+, Th2 and Th17 cell populations. Two orthogonal experimental essays (ELISA and Flow Cytometry) were performed independently to verify the results. ELISA results confirmed the RNAseq-based expression profiling of inflammatory cytokines such as GRO, IL8, TNFa and SCD40L. Importantly, in 2 patients with prior H. pylori inf
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Pub Date : 2018-09-01DOI: 10.1158/2326-6074.TUMIMM17-PR06
D. N. Cook, J. Peled, M. Brink, L. Jayaraman
The human gut microbiome is a diverse, dynamic, and complex ecosystem that modulates host processes including metabolism, inflammation, and cellular and humoral immune responses. Recent studies have suggested that the microbiome may also influence the development of certain cancers such as colorectal cancer, and equally importantly, tumor response to systemic therapy, especially immunotherapy. Multiple groups are exploring the therapeutic utility of the microbiome to enhance clinical response through the use of defined oral therapeutics comprising living commensal bacteria, which would represent a new therapeutic modality. Exploiting the microbiome for therapeutic benefit is not without its challenges due to the heterogeneity of the gut microbiota across healthy donors and patients. In addition, many aspects of conventional small molecule and biologics drug discovery and development do not apply to this novel class of living drugs. We present an approach that leverages the concept of “reverse translation,” using genomic and immunologic characterization of patient samples from interventional studies to define and better understand the organisms and mechanisms that contribute to response or non-response to immunotherapy. We are investigating the relationship between the composition of the gut microbiome prior to therapy and the antitumor response in patients receiving checkpoint inhibitors (CPI), as well as how CPI treatment modulates the microbiome in both responders and nonresponders. Fecal and blood samples are collected before and during therapy from cancer patients who receive approved CPI; tumor types include renal, bladder, and NSCLC. Whole metagenomic shotgun sequencing of patient microbiomes is used to identify higher order (e.g., order- and family-level) “microbial signatures” that associate with response to CPI treatment. We then utilize proprietary algorithms that enable species- and strain-level resolution of microbial signatures. In addition, global and targeted metabolomics are used to identify functional pathways associated with outcome, and these pathways can be linked to species and strains identified by genomic analysis. Our discovery strategy iterates computational analyses and machine learning approaches with empirical in vitro and ex vivo screening of strains and consortia to inform selection and drive drug design. Data from such a comprehensive approach is invaluable for designing compositions of bacteria that form “functional ecological networks” that can impact response to CPI therapy. Finally, our microbial library of >14,000 isolates from healthy human subjects captures the phylogenetic diversity and functional breadth of the gastrointestinal microbiome, and provides a robust platform to build unique compositions. Such compositions, when tested in syngeneic tumor models in germ-free mice, can provide a preliminary readout of the contributions of members of the consortia and enable candidate identification. We present exam
人类肠道微生物群是一个多样化、动态和复杂的生态系统，它调节宿主的代谢、炎症、细胞和体液免疫反应等过程。最近的研究表明，微生物组也可能影响某些癌症的发展，如结肠直肠癌，同样重要的是，肿瘤对全身治疗，特别是免疫治疗的反应。多个研究小组正在探索微生物组的治疗效用，通过使用含有活共生菌的口服疗法来增强临床反应，这将代表一种新的治疗方式。由于健康供体和患者肠道微生物群的异质性，利用微生物群进行治疗并非没有挑战。此外，传统的小分子和生物制剂药物发现和开发的许多方面并不适用于这类新的活药物。我们提出了一种利用“反向翻译”概念的方法，利用来自介入性研究的患者样本的基因组和免疫学特征来定义和更好地理解导致免疫治疗反应或无反应的生物体和机制。我们正在研究接受检查点抑制剂(CPI)的患者治疗前肠道微生物组组成与抗肿瘤反应之间的关系，以及CPI治疗如何调节应答者和无应答者的微生物组。在接受批准的CPI治疗前和治疗期间收集癌症患者的粪便和血液样本;肿瘤类型包括肾、膀胱和非小细胞肺癌。患者微生物组的全宏基因组散弹枪测序用于识别与CPI治疗反应相关的高阶(例如，阶和家族水平)“微生物特征”。然后，我们利用专有算法，使物种和菌株水平的微生物特征的分辨率。此外，全球和靶向代谢组学用于识别与结果相关的功能途径，这些途径可以与基因组分析确定的物种和菌株相关联。我们的发现策略迭代计算分析和机器学习方法，通过体外和离体筛选菌株和联合体，为选择和驱动药物设计提供信息。来自这种综合方法的数据对于设计形成“功能性生态网络”的细菌成分是无价的，可以影响对CPI治疗的反应。最后，我们从健康人类受试者中分离的超过14,000株微生物文库捕获了胃肠道微生物组的系统发育多样性和功能广度，并提供了一个强大的平台来构建独特的组合物。当在无菌小鼠的同基因肿瘤模型中测试这些组合物时，可以初步读出联盟成员的贡献并进行候选识别。我们介绍了在复发性难辨梭菌感染和溃疡性结肠炎(一种炎症性肠病)患者中进行反向翻译的例子，这导致了目前正在临床试验中的三种药物的翻译。该路线图提供了如何在免疫治疗的背景下发现和开发类似药物的见解，通过改变癌症免疫设定点来增强cpi的疗效。此摘要也以海报A06的形式呈现。引文格式:David N. Cook, Jonathan Peled, Marcel van den Brink, Lata Jayaraman。肿瘤免疫治疗联合用药的人体微生物组研究[摘要]。摘自:AACR肿瘤免疫学和免疫治疗特别会议论文集;2017年10月1-4日;波士顿,MA。费城(PA): AACR;癌症免疫，2018;6(9增刊):摘要nr PR06。
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