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与黑色素瘤免疫治疗反应相关的一致粪便宏基因组生物标志物。

Consistent Stool Metagenomic Biomarkers Associated with the Response To Melanoma Immunotherapy.

机构信息

Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russian Federation.

ITMO University, Saint Petersburg, Russian Federation.

出版信息

mSystems. 2023 Apr 27;8(2):e0102322. doi: 10.1128/msystems.01023-22. Epub 2023 Feb 21.

DOI:10.1128/msystems.01023-22
PMID:36809182
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10134792/
Abstract

The human gut microbiome plays an important role in both health and disease. Recent studies have demonstrated a strong influence of the gut microbiome composition on the efficacy of cancer immunotherapy. However, available studies have not yet succeeded in finding reliable and consistent metagenomic markers that are associated with the response to immunotherapy. Therefore, the reanalysis of the published data may improve our understanding of the association between the composition of the gut microbiome and the treatment response. In this study, we focused on melanoma-related metagenomic data, which are more abundant than are data from other tumor types. We analyzed the metagenomes of 680 stool samples from 7 studies that were published earlier. The taxonomic and functional biomarkers were selected after comparing the metagenomes of patients showing different treatment responses. The list of selected biomarkers was also validated on additional metagenomic data sets that were dedicated to the influence of fecal microbiota transplantation on the response to melanoma immunotherapy. According to our analysis, the resulting cross-study taxonomic biomarkers included three bacterial species: Faecalibacterium prausnitzii, Bifidobacterium adolescentis, and Eubacterium rectale. 101 groups of genes were identified to be functional biomarkers, including those potentially involved in the production of immune-stimulating molecules and metabolites. Moreover, we ranked the microbial species by the number of genes encoding functionally relevant biomarkers that they contained. Thus, we put together a list of potentially the most beneficial bacteria for immunotherapy success. , E. rectale, and three species of bifidobacteria stood out as the most beneficial species, even though some useful functions were also present in other bacterial species. In this study, we put together a list of potentially the most beneficial bacteria that were associated with a responsiveness to melanoma immunotherapy. Another important result of this study is the list of functional biomarkers of responsiveness to immunotherapy, which are dispersed among different bacterial species. This result possibly explains the existing irregularities between studies regarding the bacterial species that are beneficial to melanoma immunotherapy. Overall, these findings can be utilized to issue recommendations for gut microbiome correction in cancer immunotherapy, and the resulting list of biomarkers might serve as a good stepping stone for the development of a diagnostic test that is aimed at predicting patients' responses to melanoma immunotherapy.

摘要

人类肠道微生物群在健康和疾病中都起着重要作用。最近的研究表明,肠道微生物群的组成对癌症免疫治疗的疗效有很强的影响。然而,现有的研究尚未成功找到与免疫治疗反应相关的可靠和一致的宏基因组标志物。因此,对已发表数据的重新分析可能会提高我们对肠道微生物群组成与治疗反应之间关联的理解。在这项研究中,我们专注于黑色素瘤相关的宏基因组数据,这些数据比其他肿瘤类型的数据更为丰富。我们分析了之前发表的 7 项研究的 680 个粪便样本的宏基因组。在比较了表现出不同治疗反应的患者的宏基因组后,选择了分类学和功能生物标志物。所选生物标志物的列表也在专门研究粪便微生物群移植对黑色素瘤免疫治疗反应影响的其他宏基因组数据集上进行了验证。根据我们的分析,由此产生的跨研究分类学生物标志物包括三种细菌:普拉梭菌(Faecalibacterium prausnitzii)、青春双歧杆菌(Bifidobacterium adolescentis)和直肠真杆菌(Eubacterium rectale)。鉴定出 101 组基因作为功能生物标志物,包括那些可能参与产生免疫刺激分子和代谢物的基因。此外,我们根据包含功能相关生物标志物的基因数量对微生物物种进行了排名。因此,我们列出了一组对免疫治疗成功最有益的潜在细菌。在这些细菌中,普拉梭菌(F. prausnitzii)、直肠真杆菌(E. rectale)和三种双歧杆菌最为有益,尽管其他细菌也具有一些有用的功能。在这项研究中,我们列出了与黑色素瘤免疫治疗反应性相关的最有益细菌的列表。这项研究的另一个重要结果是免疫治疗反应性的功能生物标志物列表,这些标志物分散在不同的细菌物种中。这一结果可能解释了现有研究中关于对黑色素瘤免疫治疗有益的细菌物种的不一致性。总的来说,这些发现可用于为癌症免疫治疗中的肠道微生物群校正提供建议,并且由此产生的生物标志物列表可能成为开发旨在预测黑色素瘤免疫治疗患者反应的诊断测试的良好起点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0943/10134792/32426d5ead40/msystems.01023-22-f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0943/10134792/aeb44c94f586/msystems.01023-22-f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0943/10134792/17f0f26385fe/msystems.01023-22-f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0943/10134792/1bb770e57fbd/msystems.01023-22-f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0943/10134792/32426d5ead40/msystems.01023-22-f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0943/10134792/aeb44c94f586/msystems.01023-22-f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0943/10134792/17f0f26385fe/msystems.01023-22-f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0943/10134792/1bb770e57fbd/msystems.01023-22-f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0943/10134792/32426d5ead40/msystems.01023-22-f004.jpg

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