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Research Paper

A distinct microbiota signature precedes the clinical diagnosis of hepatocellular carcinoma

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Article: 2201159 | Received 12 Jun 2022, Accepted 05 Apr 2023, Published online: 23 Apr 2023
 

ABSTRACT

Oral, gut, and tumor microbiota have been implicated as important regulators in the carcinogenesis and progression of gastrointestinal malignancies. However, few studies focused on the existence and association of resident microbes within different body regions. Herein, we aim to reveal the durability of the oral-gut-tumor microbiome and its diagnostic performance in hepatocellular carcinoma (HCC). Our study included two cohorts: a retrospective discovery cohort of 364 HBV-HCC patients and 160 controls with oral or fecal samples, a prospective validation cohort of 91 cases, and 124 controls for matching samples, as well as 48 HBV, and 39 HBV-cirrhosis patients for gut microbial patterns examined by 16S rRNA gene sequencing. With the random forest analysis, 10 oral and 9 gut genera that could distinguish HCC from controls in the retrospective cohort were validated among the prospective matching participants, with area under the curve (AUC) values of 0.7971 and 0.8084, respectively. When influential taxa were merged, the AUC of the consistent classifier increased to 0.9405. The performance continued to improve to 0.9811 when combined with serum levels of alpha-fetoprotein (AFP). Specifically, microbial biomarkers represented by Streptococcus displayed a constantly increasing trend during the disease transition. Furthermore, the presence of several dominant microbiota species was confirmed in hepatic tumor and non-tumor tissues with fluorescence in situ hybridization (FISH) and 5 R 16S rRNA gene sequencing. Overall, our findings based on the oral-gut-tumor microbiota provide a reliable approach for the early detection of HCC.

Acknowledgments

The authors would like to thank Peng Wu, Qingqing Liang, Wei Wang, and Gaoyang He of Lc-Bio Technologies Co., Ltd (Hangzhou, China) for their technical support in this work. We thank the anonymous reviewers and the editors for their helpful remarks and useful feedback that improved this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data that support the findings of this study are available on request from the corresponding author, Gang Chen. The data are not publicly available due to their containing information that could compromise the privacy of research participants.

List of abbreviations

HCC=

hepatocellular carcinoma

AUC=

area under the curve

AFP=

alpha-fetoprotein

FISH=

fluorescence in situ hybridization

OSCC=

oral squamous cell carcinoma

IBD=

inflammatory bowel disease

PCA=

principal component analysis

PCoA=

principal coordinates analysis

KEGG=

Kyoto Encyclopedia of Genes and Genomes

STAMP=

statistical analysis of metagenomic profiles

SEM=

standard error of mean

LEfSe=

linear discriminant analysis effect size

FDR=

false discovery rate

RDA=

redundancy analysis

ROC=

receiver operating curve

LPS=

lipopolysaccharide

ZO-1=

zonulin-1

ELISA=

enzyme-link immunosorbent assay

LAL=

limulus amebocyte lysate

IHC=

immunohistochemistry

LTA=

lipoteichoic acid

RT=

room temperature

GF=

Germ-free

PPIs=

proton-pump inhibitors

NSAIDs=

nonsteroidal anti-inflammatory drugs

AAPs=

atypical antipsychotics

ARB=

angiotensin II receptor blocker

ACEI=

angiotensin converting enzyme inhibitors

ANOSIM=

analysis of similarities

BMI=

body mass index

CCI=

charlson comorbidity index

MELD=

model for end-stage liver disease

HBV=

hepatitis B virus

INR=

international normalized ratio

PT=

prothrombin time

HDL=

high density lipoprotein

LDL=

low density lipoprotein

ALT=

alanine transaminase

AST=

aspartate transaminase

PLT=

platelet

Tchol=

total cholesterol

TG=

triglyceride

Tbil=

total bilirubin

Cre=

creatinine

Alb=

albumin

GGT=

γ-glutamyl transpeptidase

BAs=

bile acids

SCFAs=

short-chain fatty acids

LCA=

lithocholic acid

DCA=

deoxycholic acid

TLRs=

toll-like receptors

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/19490976.2023.2201159

Additional information

Funding

The work was supported by the National Natural Science Foundation of China [81772628, 81703310, 82072685]; the Research Foundation of the National Health Commission of China–Major Medical and Health Technology Project for Zhejiang Province [WKJ-ZJ-1706]