Differential proteomic analysis of plasma-derived exosomes as diagnostic biomarkers for chronic HBV-related liver disease

Abstract

Hepatitis B virus (HBV) infection is still a major public health problem worldwide. We aimed to identify new, non-invasive biomarkers for the early diagnosis of chronic HBV-related diseases, reveal alterations in the progression of chronic hepatitis B (CHB), liver cirrhosis (LC), and hepatocellular carcinoma (HCC). Here, exosomes were isolated and characterized through size exclusion chromatography and nanoparticle tracking analysis. Profiles of differentially expressed proteins (DEPs) were analyzed through liquid chromatography-tandem mass spectrometry (LC-MS/MS), Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses. Results showed that the DEPs, including CO9, LBP, SVEP1, and VWF levels in extracellular vesicles (EVs) were significantly higher in CHB than in healthy controls (HCs). VWF expression levels in EVs were significantly lower in CHB than in those with LC. KV311 expression levels in EVs were significantly higher, whereas LBP levels were significantly lower in patients with CHB than in those with HCC. All biomarkers seemed to exhibit a high diagnostic capacity for HBV-related liver disease. Patients with HBV-induced chronic liver disease exhibit characteristic protein profiles in their EVs. Thus, serum exosomes may be used as novel, liquid biopsy biomarkers to provide useful clinical information for the diagnosis of HBV-related liver diseases at different stages.

Figure 1

Characterization of plasma-derived exosomes from patients with chronic hepatitis B virus infection (CHB), liver cirrhosis (LC), and hepatocellular carcinoma (HCC) and healthy controls (HCs). The size and morphological distribution of exosomes are shown, and were obtained using nanoparticle tracking analysis (NTA) (A) and transmission electron microscopy (TEM) (B). The samples were positive for the exosome markers CD9, TSG101, and CD63 and negative for calnexin (C).

Figure 2

A Venn diagram showing pairwise comparison of differentially expressed proteins between patients with chronic HBV infection (CHB), liver cirrhosis (LC), and hepatocellular carcinoma (HCC) and healthy controls (HCs). (A) The Venn diagram was drawn by the R package Vennerable. For convenience of description, CHB, LC, HCC, and HCs groups are denoted by CHB, LC, HCC, and HCs, respectively. (B) An UpSet diagram showing pairwise comparison of differentially expressed proteins between CHB, LC, HCC, and HCs. The UpSet diagram was drawn by the R package UpSetR. The figure shows the number of common or unique proteins in different combinations. The lower left corner shows groups with differential expression and the number of different proteins that were screened among each group. The dots on the right show proteins common or specific to the corresponding group. The histogram shows the number of specific or common proteins.

Figure 3

Protein profiles derived from exosome-enriched fractions of chronic hepatitis B (CHB), liver cirrhosis (LC), hepatocellular carcinoma (HCC), and healthy controls (HCs). (A) A Venn diagram showing pairwise comparison of differentially expressed proteins between patients with CHB, LC, and HCC against HCs. The Venn diagram was drawn by the R package VennDiagram. (B) A Venn diagram showing pairwise comparison of differentially expressed proteins among disease groups (CHB, LC, and HCC). The Venn diagram was drawn by the R package VennDiagram. (C) A clustergram of differentially expressed proteins analyzed through pairwise comparison between disease groups (CHB, LC, and HCC) and the HCs group. The clustergram was drawn by the R package Pheatmap. The ordinate represents proteins, and the abscissa represents samples. Clustering was performed using the values of log₁₀ (label-free quantification + 1, LFQ + 1) and then clustering. On the left, lines in black show the hierarchical clustering of proteins. Colored bars at the top represent CHB, LC, HCC and HCs; the corresponding samples are shown at the bottom. Red and green represent proteins with high and low expression, respectively. (D) A clustergram of differentially expressed proteins for pairwise comparison between disease groups (CHB, LC, and HCC). The clustergram was drawn by the R package Pheatmap. The ordinate represents different proteins, and the abscissa represents different samples. Clustering was performed using the values of log₁₀ (LFQ + 1). Red and green represent highly and lowly expressed proteins, respectively.

Figure 4

Comparison of the differentially expressed proteins, namely CO9, LBP, SVEP1, VWF and KV311, between the chronic hepatitis B (CHB), liver cirrhosis (LC), hepatocellular carcinoma (HCC), and healthy control (HC) groups (A–E). The main R package to draw the beeswarm plots was ggbeeswarm.

Figure 5

Diagnostic prediction (Receiver Operating Characteristics (ROC) curves and area under the curve (AUC) values) of the selected serum liquid biopsy biomarkers. AUC values were calculated by stepwise logistic regression algorithm, and then the graphs were drawn by R's own program. CO9, LBP, SVEP1 and VWF levels for diagnosing patients with chronic hepatitis B virus infection (CHB) (A), liver cirrhosis (LC) (B), and hepatocellular carcinoma (HCC) (C) compared with healthy controls (HCs). AUC values of VWF as a marker for diagnosing CHB compared with LC (D). AUC values of CO9 as a marker for diagnosing CHB compared with HCC (E). AUC values of KV311 as a marker for diagnosing LC compared with HCC (F).

Figure 6

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differentially expressed proteins identified in serum EVs (sEVs). The Bubble plots were drawn by the R program. And the R program was written after enrichment significance, which was calculated by Fisher’s exact test. Bubble plots showing enrichment for the GO biological process (A), cellular component (B), and molecular function (C). A bubble plot showing enrichment for KEGG pathways (D).