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微生物组混杂因素和定量分析方法对预测结直肠癌发展中微生物靶标的挑战。

Microbiome confounders and quantitative profiling challenge predicted microbial targets in colorectal cancer development.

机构信息

Laboratory of Molecular Bacteriology, Department of Microbiology and Immunology, Rega Institute, Katholieke Universiteit Leuven, Leuven, Belgium.

Center for Microbiology, Vlaams Instituut voor Biotechnologie, Leuven, Belgium.

出版信息

Nat Med. 2024 May;30(5):1339-1348. doi: 10.1038/s41591-024-02963-2. Epub 2024 Apr 30.


DOI:10.1038/s41591-024-02963-2
PMID:38689063
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11108775/
Abstract

Despite substantial progress in cancer microbiome research, recognized confounders and advances in absolute microbiome quantification remain underused; this raises concerns regarding potential spurious associations. Here we study the fecal microbiota of 589 patients at different colorectal cancer (CRC) stages and compare observations with up to 15 published studies (4,439 patients and controls total). Using quantitative microbiome profiling based on 16S ribosomal RNA amplicon sequencing, combined with rigorous confounder control, we identified transit time, fecal calprotectin (intestinal inflammation) and body mass index as primary microbial covariates, superseding variance explained by CRC diagnostic groups. Well-established microbiome CRC targets, such as Fusobacterium nucleatum, did not significantly associate with CRC diagnostic groups (healthy, adenoma and carcinoma) when controlling for these covariates. In contrast, the associations of Anaerococcus vaginalis, Dialister pneumosintes, Parvimonas micra, Peptostreptococcus anaerobius, Porphyromonas asaccharolytica and Prevotella intermedia remained robust, highlighting their future target potential. Finally, control individuals (age 22-80 years, mean 57.7 years, standard deviation 11.3) meeting criteria for colonoscopy (for example, through a positive fecal immunochemical test) but without colonic lesions are enriched for the dysbiotic Bacteroides2 enterotype, emphasizing uncertainties in defining healthy controls in cancer microbiome research. Together, these results indicate the importance of quantitative microbiome profiling and covariate control for biomarker identification in CRC microbiome studies.

摘要

尽管癌症微生物组研究取得了重大进展,但公认的混杂因素和绝对微生物组定量的进展仍未得到充分利用;这引起了人们对潜在虚假关联的担忧。在这里,我们研究了 589 名不同结直肠癌(CRC)阶段患者的粪便微生物组,并将观察结果与多达 15 项已发表的研究(总计 4439 名患者和对照)进行了比较。我们使用基于 16S 核糖体 RNA 扩增子测序的定量微生物组分析,结合严格的混杂因素控制,确定了转运时间、粪便钙卫蛋白(肠道炎症)和体重指数是主要的微生物协变量,取代了 CRC 诊断组解释的差异。当控制这些协变量时,诸如具核梭杆菌等已确立的微生物组 CRC 靶标与 CRC 诊断组(健康、腺瘤和癌)没有显著关联。相比之下,当控制这些协变量时,阴道 Anaerococcus、呼吸 Dialister、微小 Parvimonas、厌氧 Peptostreptococcus、无胆甾原体 Porphyromonas 和中间普雷沃氏菌的关联仍然稳健,突出了它们未来的靶标潜力。最后,符合结肠镜检查标准(例如,通过阳性粪便免疫化学试验)但无结肠病变的对照个体(年龄 22-80 岁,平均 57.7 岁,标准差 11.3)富含失调的拟杆菌 2 肠型,强调了在癌症微生物组研究中定义健康对照的不确定性。总之,这些结果表明,在 CRC 微生物组研究中,定量微生物组分析和协变量控制对于生物标志物识别非常重要。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ee1/11108775/698d3c48bc01/41591_2024_2963_Fig9_ESM.jpg
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本文引用的文献

[1]
Accounting for 16S rRNA copy number prediction uncertainty and its implications in bacterial diversity analyses.

ISME Commun. 2023-6-10

[2]
Gut microbiota, inflammatory bowel disease and colorectal cancer.

World J Gastroenterol. 2022-8-14

[3]
Multi-kingdom microbiota analyses identify bacterial-fungal interactions and biomarkers of colorectal cancer across cohorts.

Nat Microbiol. 2022-2

[4]
The gut microbial diversity of colon cancer patients and the clinical significance.

Bioengineered. 2021-12

[5]
Microbiome Analysis of More Than 2,000 NHS Bowel Cancer Screening Programme Samples Shows the Potential to Improve Screening Accuracy.

Clin Cancer Res. 2021-4-15

[6]
The colorectal cancer-associated faecal microbiome of developing countries resembles that of developed countries.

Genome Med. 2021-2-16

[7]
Parvimonas micra, Peptostreptococcus stomatis, Fusobacterium nucleatum and Akkermansia muciniphila as a four-bacteria biomarker panel of colorectal cancer.

Sci Rep. 2021-2-3

[8]
Changes in colorectal cancer incidence by site and age from 1973 to 2015: a SEER database analysis.

Aging Clin Exp Res. 2021-7

[9]
A predictive index for health status using species-level gut microbiome profiling.

Nat Commun. 2020-9-15

[10]
Statin therapy is associated with lower prevalence of gut microbiota dysbiosis.

Nature. 2020-5-6

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