AUTHOR=Yuan Mengqin , Hu Xue , Yao Lichao , Liu Pingji , Jiang Yingan , Li Lanjuan 

TITLE=Comprehensive bioinformatics and machine learning analysis identify VCAN as a novel biomarker of hepatitis B virus-related liver fibrosis

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2022.1010160

DOI=10.3389/fmolb.2022.1010160

ISSN=2296-889X

ABSTRACT=Hepatitis B virus (HBV) infection remains the leading cause of liver fibrosis worldwide, especially in China. Identifying the vital diagnostic biomarkers of HBV-associated liver fibrosis (HBV-LF) to prevent chronic hepatitis B (CHB) from progressing to liver cancer and to select the best treatment strategy more effectively. We first obtained 43 samples from CHB patients without liver fibrosis (LF) and 81 samples from CHB patients with LF (GSE84044 dataset). Among them, 173 differentially expressed genes (DEGs) were screened out. Functional analysis showed that these DEGs predominantly participated in the immune-, ECM-, and metabolism-related processes. Subsequently, we integrated 4 algorithms (including LASSO regression, SVM-RFE, RF and WGCNA) to determine the diagnostic biomarkers of HBV-LF. Finally, PPAP2C and VCAN were identified as potential diagnostic biomarkers of HBV-LF. Receiver operating characteristic (ROC) curves demonstrated their probability as valuable biomarkers for HBV-LF. Moreover, ssGSEA analysis further confirmed the immune landscape of HBV-LF, and these diagnostic biomarkers were significantly correlated with immune infiltrating cells. In addition, we further analyzed the potential regulatory mechanisms of VCAN underlying the occurrence and development of HBV-LF.