Characterization of the intestinal fungal microbiome in patients with hepatocellular carcinoma

Abstract

Objective: Gut mycobiota plays a crucial role in benign liver diseases; however, its correlation with hepatocellular carcinoma (HCC) remains elusive. This study aimed to elucidate fungal differences in patients with HCC-associated cirrhosis compared to cirrhotic patients without HCC and healthy controls.

Methods: The 72 fecal samples from 34 HCC patients, 20 cirrhotic patients, and 18 healthy controls were collected and analyzed using ITS2 rDNA sequencing.

Results: Our results revealed the presence of intestinal fungal dysbiosis with significant enrichment of opportunistic pathogenic fungi such as Malassezia, Malassezia sp., Candida, and C. albicans in HCC patients compared with healthy controls and cirrhosis patients. Alpha-diversity analysis demonstrated that patients with HCC and cirrhosis showed decreased fungal diversity compared to healthy controls. Beta diversity analysis indicated that the three groups exhibited significant segregated clustering. Besides, C. albicans was found to be significantly more abundant in the HCC patients with TNM stage III-IV than those with stage I-II, in contrast to the commensal organism S. cerevisiae. We also confirmed that the HCC patients were successfully classified with an area under the curve value of 0.906 based on the fecal fungal signature. Finally, our animal experiments confirm that aberrant colonization of the intestine by C. albicans and M. furfur can promote the development of HCC.

Conclusions: This study indicates that dysbiosis of the gut mycobiome might be involved in HCC development.

Trial registration: ChiCTR, ChiCTR2100054537. Registered 19 December 2021, http://www.chictr.org.cn/edit.aspx?pid=144550&htm=4.

Keywords: Candida albicans; Gut mycobiome; Hepatocellular carcinoma; ITS2 rDNA sequencing; Liver cirrhosis; Malassezia.

Fig. 1

Diversity analysis in the HCC, LC, and HC groups. A Rank abundance curves. B Venn diagram displaying the overlap of OTUs identified among the three groups. Alpha diversity was estimated by the Shannon index C and Simpson index D. The distributional difference of gut mycobiota profiles was assessed using PCoA E and NMDS F based on a weighted_unifrac matrix. HCC hepatocellular carcinoma, LC liver cirrhosis, HC healthy controls

Fig. 2

Differential analysis of fungal communities in the HCC, LC, and HC groups. A Heatmap of fungal abundance clustering at the genus level A and species level B. The eight most abundant of the differential taxonomic units at the genus level C and species level D between HCC patients and healthy controls. The eight most abundant of the differential taxonomic units at the genus level E and species level F between HCC patients and cirrhosis patients. The Wilcoxon rank-sum test was used. HCC hepatocellular carcinoma, LC liver cirrhosis, HC healthy controls

Fig. 3

The differential taxa in the HCC, LC, and HC groups using the linear discriminant analysis effect size (LEfSe) analysis. A LDA scores were computed for differentially abundant taxa in the gut fungi of HCC patients and healthy controls. F LDA scores were computed for differentially abundant taxa in the gut fungi of HCC patients and cirrhosis patients. Length indicates the effect size associated with a taxon. P = 0.05 for the Kruskal-Wallis sum-rank test; LDA score > 4. B–E, G–N The histogram of the relative abundance distribution of each taxon at the species level. HC healthy controls, HCC hepatocellular carcinoma, LC liver cirrhosis, LDA linear discriminant analysis

Fig. 4

Correlation of gut mycobiota with TNM stage and clinical physiological indicators in HCC patients. A Taxonomic cladogram from LEfSe showing differences in fecal taxa of HCC patients with stage III-IV and stage I-II. B LDA scores were computed for differentially abundant taxa in the gut fungi of HCC patients with stage III-IV and stage I-II. Length indicates the effect size associated with a taxon. P = 0.05 for the Kruskal-Wallis sum-rank test; LDA score > 4; C Spearman correlation analysis of fungal taxa and clinical physiological indicators in HCC patients. D Canonical correspondence analysis (CCA) of clinical indicators correlated with the fungal profile of patients with HCC. HCC hepatocellular carcinoma, LDA linear discriminant analysis, ALT alanine aminotransferase, AST aspartate aminotransferase, ALP alkaline phosphatase, GGT gamma-glutamyltransferase, TBIL total bilirubin, DBIL direct bilirubin, TBA total bile acid, RBC red blood cell, Hb hemoglobin, PA prealbumin, TP total protein, ALB albumin, GLB globulin, WBC white blood cell, NeuC neutrophil count, LYMC lymphocyte count, MonoC monocytes count, LMR monocyte-to-lymphocyte ratio, NLR neutrophil-lymphocyte ratio, PLT platelets, PT prothrombin, PT-act prothrombin time activity, PT-INR the international normalized ratio of prothrombin, APTT activated partial thromboplastin time, TT thrombin time, AT-III antithrombin III, *P < 0.05, **P < 0.01

Fig. 5

Classification of the HCC group compared to the non-HCC group. ROC curves of Candida albicans A, Malassezia sp. B, Neocatenulostroma sp. C, Nakaseomyces sp. D, Candida tropicalis E, Alternaria alternata F, and Pichia membranifaciens G. H ROC curves analysis to evaluate the classification ability of the gut mycobiome signature (combined Candida albicans, Malassezia sp., and Neocatenulostroma sp.) in predicting different groups. ROC receiver operating characteristic, AUC area under the curve

Fig. 6

Functional classification predictions. Fungal functional annotations between the HCC and healthy controls A and between the HCC and liver cirrhosis B were performed by FUNGuild. Fungi were divided into different categories at the Guild levels according to the ways of absorption and utilization of environmental resources. HCC hepatocellular carcinoma, LC liver cirrhosis, HC healthy controls

Fig. 7

Abnormal colonization of C. albicans and M. furfur can promote HCC development. A Schematic diagram of the oral gavage intervention protocol using phosphate-buffered saline, C. albicans or M. furfur for C57BL/6 mice (6 mice per group). The images of tumor-bearing mice B and tumor masses C. Tumor volume D and weight E were compared among the three groups at the end of the experiment. F Representative images of subcutaneous tumor among the three groups immunostained with Ki67 (200 ×). G Quantification of Ki67 + cells. *P < 0.05, **P < 0.01, Wilcoxon rank sum test was used