Featured intestinal microbiota associated with hepatocellular carcinoma in various liver disease states.
This study aimed to identify distinct intestinal microbiota associated with hepatocellular carcinoma (HCC) and to construct a predictive model for HCC.
A case-control study was conducted including patients with chronic hepatitis B (CHB), liver cirrhosis (LC), HCC, and healthy controls (HC). Fecal 16S rDNA sequences were analyzed using bioinformatics approaches. Specific intestinal microbiota were identified through stratified analysis, and a predictive model was subsequently constructed.
A total of 152 subjects were enrolled, including CHB (n = 33), LC (n = 59; 25 compensated cirrhosis, CC; 34 decompensated cirrhosis, DC), HCC (n = 30; 5 CHB-HCC, 9 CC-HCC, and 16 DC-HCC), and HC (n = 30). A significant overall difference in alpha diversity was observed across the groups (Chao1: P = 0.010,ϵ²= 0.056; ACE: P = 0.016,ϵ²= 0.049). In the CHB-HCC, CC-HCC, and DC-HCC groups, the abundance of Bacteroides, Prevotella, and Faecalibacterium gradually decreased, whereas Klebsiella, Haemophilus, and Streptococcus increased. Comparison of CHB vs. CHB-HCC, CC vs. CC-HCC, and DC vs. DC-HCC revealed consistent microbial shifts across disease stages. In particular, Roseburia, Veillonella, Megasphaera, and Paraprevotella were increased irrespective of liver disease stage. By combining microbiota profiles with clinical indicators, we developed a predictive nomogram that achieved an AUC of 0.865 in the training cohort and 0.848 in the external validation cohort.
Intestinal microbiota were associated not only with liver disease stage but also with the occurrence of HCC itself. Characteristic microbiota may serve as effective biomarkers for predicting HCC.
A case-control study was conducted including patients with chronic hepatitis B (CHB), liver cirrhosis (LC), HCC, and healthy controls (HC). Fecal 16S rDNA sequences were analyzed using bioinformatics approaches. Specific intestinal microbiota were identified through stratified analysis, and a predictive model was subsequently constructed.
A total of 152 subjects were enrolled, including CHB (n = 33), LC (n = 59; 25 compensated cirrhosis, CC; 34 decompensated cirrhosis, DC), HCC (n = 30; 5 CHB-HCC, 9 CC-HCC, and 16 DC-HCC), and HC (n = 30). A significant overall difference in alpha diversity was observed across the groups (Chao1: P = 0.010,ϵ²= 0.056; ACE: P = 0.016,ϵ²= 0.049). In the CHB-HCC, CC-HCC, and DC-HCC groups, the abundance of Bacteroides, Prevotella, and Faecalibacterium gradually decreased, whereas Klebsiella, Haemophilus, and Streptococcus increased. Comparison of CHB vs. CHB-HCC, CC vs. CC-HCC, and DC vs. DC-HCC revealed consistent microbial shifts across disease stages. In particular, Roseburia, Veillonella, Megasphaera, and Paraprevotella were increased irrespective of liver disease stage. By combining microbiota profiles with clinical indicators, we developed a predictive nomogram that achieved an AUC of 0.865 in the training cohort and 0.848 in the external validation cohort.
Intestinal microbiota were associated not only with liver disease stage but also with the occurrence of HCC itself. Characteristic microbiota may serve as effective biomarkers for predicting HCC.
Authors
Sun Sun, Zhou Zhou, Chi Chi, Cheng Cheng, Zhang Zhang, Xu Xu, Hao Hao, Duan Duan, Li Li, Zhao Zhao, Liu Liu, Han Han, Wang Wang, Yang Yang, Pan Pan, Xing Xing
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