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The Intratumoral Bacterial Metataxonomic Signature of Hepatocellular Carcinoma

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机构: [1]Fudan Univ, Minhang Hosp, Shanghai, Peoples R China [2]Fudan Univ, Inst Biomed Sci, Shanghai Key Lab Med Epigenet, Int Colab Med Epigenet & Metab,Minist Sci & Techn, Shanghai, Peoples R China [3]Fudan Univ, Dept Liver Surg & Transplantat, Zhongshan Hosp,Minist Educ, Liver Canc Inst,Key Lab Carcinogenesis & Canc Inv, Shanghai, Peoples R China [4]Shanghai TongRen Hosp, Dept Gen Surg, Shanghai, Peoples R China [5]Shanghai Univ Tradit Chinese Med, Shanghai Municipal Hosp Tradit Chinese Med, Dept Cent Lab Med, Shanghai, Peoples R China
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关键词: hepatocellular carcinoma microbiota fluorescence in situ hybridization bacteria machine learning

摘要:
Gut microbiome is an important regulator of hepatic inflammation, detoxification, and immunity, and contributes to the carcinogenesis of liver cancer. Intratumoral bacteria are supposed to be closer to the tumor cells, forming a microenvironment that may be relevant to the pathological process of hepatocellular carcinoma (HCC). Microbiota is implicated in hepatocellular carcinoma (HCC). The spectrum of intratumoral microbiota associated with HCC progression remains elusive. Fluorescence in situ hybridization revealed that microbial DNAs were distributed in the cytosol of liver hepatocytes and erythrocytes. Viable anaerobic or aerobic bacteria were recovered in HCC tissues by fresh tissue culture. We performed a comprehensive DNA sequencing of bacterial 16S rRNA genes in 156 samples from 28 normal liver, 64 peritumoral, and 64 HCC tissues, and the DNA sequencing yielded 4.2 million high-quality reads. Both alpha and beta diversity in peritumor and HCC microbiota were increased compared to normal controls. The most predominant phyla in HCC were Patescibacteria, Proteobacteria, Bacteroidota, Firmicutes, and Actinobacteriota. phyla of Proteobacteria, Firmicutes, and Actinobacteriota, and classes of Bacilli and Actinobacteria, were consistently enriched in peritumor and HCC tissues, while Gammaproteobacteria was especially abundant in HCC tissues compared to normal controls. Streptococcaceae and Lactococcus were the marker taxa of HCC cirrhosis. The Staphylococcus branch and Caulobacter branch were selectively enriched in HBV-negative HCCs. The abundance of Proteobacteria, Gammaproteobacteria, Firmicutes, Actinobacteriota, and Saccharimonadia were associated with the clinicopathological features of HCC patients. The inferred functions of different taxa were changed between the microbiota of normal liver and peritumor/HCC. Random forest machine learning achieved great discriminative performance in HCC prediction (area under the curve [AUC] = 1.00 in the training cohort, AUC = 0.950 for top five class signature, and AUC = 0.943 for the top 50 operational taxonomy units [OTUs] in the validation cohort). Our analysis highlights the complexity and diversity of the liver and HCC microbiota and established a specific intratumoral microbial signature for the potential prediction of HCC. IMPORTANCE Gut microbiome is an important regulator of hepatic inflammation, detoxification, and immunity, and contributes to the carcinogenesis of liver cancer. Intratumoral bacteria are supposed to be closer to the tumor cells, forming a microenvironment that may be relevant to the pathological process of hepatocellular carcinoma (HCC). However, the presence of viable intratumoral bacteria remains unclear. It is worth exploring whether the metataxonomic characteristics of intratumoral bacteria can be used as a potential marker for HCC prediction. Here, we present the first evidence of the existence of viable intratumoral bacteria in HCC using the tissue culture method. We revealed that microbial DNAs were distributed in the cytosol of liver hepatocytes and erythrocytes. We analyzed the diversity, structure, and abundance of normal liver and HCC microbiota. We built a machine learning model for HCC prediction using intratumoral bacterial features. We show that specific taxa represent potential targets for both therapeutic and diagnostic interventions.

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出版当年[2021]版:
大类 | 2 区 生物学
小类 | 2 区 微生物学
最新[2025]版:
大类 | 2 区 生物学
小类 | 3 区 微生物学
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出版当年[2020]版:
Q1 MICROBIOLOGY
最新[2023]版:
Q2 MICROBIOLOGY

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第一作者机构: [1]Fudan Univ, Minhang Hosp, Shanghai, Peoples R China [2]Fudan Univ, Inst Biomed Sci, Shanghai Key Lab Med Epigenet, Int Colab Med Epigenet & Metab,Minist Sci & Techn, Shanghai, Peoples R China
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通讯机构: [1]Fudan Univ, Minhang Hosp, Shanghai, Peoples R China [2]Fudan Univ, Inst Biomed Sci, Shanghai Key Lab Med Epigenet, Int Colab Med Epigenet & Metab,Minist Sci & Techn, Shanghai, Peoples R China
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