Cell Differentiation Trajectory in Liver Cirrhosis Predicts Hepatocellular Carcinoma Prognosis and Reveals Potential Biomarkers for Progression of Liver Cirrhosis to Hepatocellular Carcinoma.

Zhaobin He,Tianen Li,Jie Li,Cheng Peng

doi:10.3389/fgene.2022.858905

Zhaobin He, Tianen Li + Show 2 more

Open Access

https://doi.org/10.3389/fgene.2022.858905

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Abstract

Most hepatocellular carcinoma (HCC) patients occur on a background of liver cirrhosis, the molecular mechanisms of liver cirrhosis and its progression to HCC remain to be fully elucidated. Single cell differentiation trajectory analysis has been used in cell classification and tumor molecular typing, which correlated with disease progression and patient prognosis. Here we use cell differentiation trajectory analysis to investigate the relevance of liver cirrhosis and HCC. Single-cell RNA sequencing (scRNA-seq) data of liver cirrhosis and bulk RNA-seq and clinical data of HCC were downloaded from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) for analysis. HCC samples were divided into three subtypes, based on differentiation-related genes (DRGs) of liver cirrhosis, each with a different expression profile and overall survival (OS). A two- DRGs (CD34 and RAMP3) based prognostic risk scoring (RS) signature was established which could differentiate OS between high-risk and low-risk groups. And expression levels of CD34 and RAMP3 were predominantly high in endothelial cells. By integrating the RS and clinicopathological features, a nomogram was constructed and can accurately predicted the 1-year, 3-years, and 5-years OS. In conclusion, cell differentiation trajectory of liver cirrhosis can predict the prognosis of HCC, and provides new perspectives on the mechanisms of progression of liver cirrhosis to HCC.

Highlights

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and accounts for 4.7% of newly diagnosed cancer cases and 8.2% of cancer related deaths (Bray et al, 2018)
Pseudotime and trajectory analysis were used to group all cells into 3 subsets (subset I mainly contained endothelial cells, hepatocytes, and smooth muscle cells, subset II mainly contained monocyte, macrophages, and pre-B cells (CD34-), and subset III mainly contained B cells, T cells, and monocyte (Figures 2H,I). (DRGs are shown in Supplementary Table S6)
Using cell differentiation trajectory of scRNA-seq data from liver cirrhosis, we stratified hepatocellular carcinoma (HCC) into three distinct molecular subtypes that differ with regards to expression profiles, clinical features, and outcomes

Summary

Introduction

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and accounts for 4.7% of newly diagnosed cancer cases and 8.2% of cancer related deaths (Bray et al, 2018). Most patients with HCC have underlying liver cirrhosis, of which majority are related to hepatitis B or C virus (Takano et al, 1995; Fattovich et al, 2004). The 5-years cumulative risk of HCC associated to hepatitis C virus (HCV)-related cirrhosis is 30% in Japan and 17% in Western countries (Fattovich et al, 2004). Studies using generation sequencing have elucidated several genetic and epigenetic factors associated with the progression of liver cirrhosis into HCC (Nault et al, 2013; Totoki et al, 2014; Schulze et al, 2015; Devhare et al, 2017; Rashad et al, 2018). Biomarker predictors of treatment responsiveness are urgently needed for patient stratification (Fulgenzi et al, 2021)

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