Abstract
Background
Primary liver cancer has high mortality and morbidity worldwide. However, the characteristic of gut microbiota profile and its correlation with inflammation status in liver cancer patients remains largely unknown, and a gut microbiome-based diagnostic model for liver cancer is still absent.
Methods
Here, we provided a comprehensive analysis based on fecal 16S rRNA sequencing and clinical data in a cohort consisting of 40 healthy volunteers, 143 hepatocellular carcinoma (HCC) patients, and 46 cholangiocarcinoma (CCA) patients.
Results
Our results indicated a distinct shift of gut microbiota composition between two primary liver cancer types and compared with healthy volunteers. Based on the diversity constitute of gut microbiome taxonomy and random forest algorithm, eight genera with mean abundance above 0.1% were selected to construct the classification model with half of the randomly selected cohort. Based on this signature, high diagnostic accuracy in the validation cohort to classify liver cancer types (AUC = 0.989, 0.967, 0.920 for Control, HCC, CCA separately) was achieved. Further analysis showed increased Gram-negative bacteria and elevated inflammatory response markers in CCA group versus HCC group. The correlation analysis between inflammatory response markers and composition of gut microbiome revealed decreased potentially beneficial genus and increased opportunistic pathogens positively correlated with adverse prognostic inflammatory response markers.
Conclusion
Generally, our study established the gut microbiome-based signature for liver cancer prediction and screening and revealed that gut microbiome characteristic in primary liver cancer was correlated with adverse inflammatory response markers in liver cancer.
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Data availability
All data used to support the findings of this study are available from the corresponding author upon reasonable request.
Abbreviations
- HCC:
-
Hepatocellular carcinoma
- CCA:
-
Cholangiocarcinoma
- CIOMS:
-
Council for international organizations of medical sciences
- NCCN:
-
National comprehensive cancer network
- DADA2:
-
Divisive amplicon denoising algorithm 2
- OTU:
-
Operating taxonomic unit
- LEfSe:
-
Linear discriminant analysis effect size
- STAMP:
-
Statistical analysis of metagenomics profile
- PCoA:
-
Principal coordinate analysis
- NMDS:
-
Non-metric multidimensional scaling
- ANOVA:
-
Analysis of variance
- ROC:
-
Receiver operating characteristic
- RDA:
-
Redundancy analysis
- NLR:
-
Neutrophil-to-lymphocyte ratio
- LMR:
-
Lymphocyte-to-monocyte ratio
- PLR:
-
Platelet-to-lymphocyte ratio
- LPS:
-
Lipopolysaccharides
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Funding
This study was supported by the National Natural Science Foundation of China (81772628, 81703310, 82072685), the Research Foundation of National Health Commission of China- Major Medical and Health Technology Project for Zhejiang Province (WKJ-ZJ-1706).
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GC, YW and XLC conceptualized and designed the study. JLL, BJH, FTL, ZYC, performed the experiment and collected the data. TD, BC, JYZ performed the analysis. All authors contributed to results interpretation. ZHS, TZ, LMD verified the data. TD drafted the initial version of the manuscript. All authors critically reviewed many revisions of the manuscript and contributed important intellectual content. GC, YW and XLC had full access to all the data in the study and had responsibility for the integrity of the data, the accuracy of the analyses, and the final decision to submit the manuscript for publication.
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This study was approved by the Ethics Committee in Clinical Research of the First Affiliated Hospital of Wenzhou Medical University, Zhejiang, China (Ref No.3030-074). Written informed consent was obtained from all participants on enrollment. All research was performed according to the declaration of Helsinki and international ethical guidelines for human biomedical research of the Council for International Organizations of Medical Sciences (CIOMS).
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Deng, T., Li, J., He, B. et al. Gut microbiome alteration as a diagnostic tool and associated with inflammatory response marker in primary liver cancer. Hepatol Int 16, 99–111 (2022). https://doi.org/10.1007/s12072-021-10279-3
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DOI: https://doi.org/10.1007/s12072-021-10279-3