Construction and validation of a cell-in-cell related prognostic signature for hepatocellular carcinoma

构建和验证肝细胞癌的细胞内相关预后特征

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作者:Hao Zhong #,Dong Wang #,Yisheng Chen #,Danhong Zhan,Chenxi Wang,Rongqi Lin,Wen Li,Qiang Sun,Ruizhi Wang,Meifang He

Abstract

Cell-in-cell structures (CICs) and their biological roles contribute to disease development, particularly in cancer. However, the roles of CIC-associated genes (CICGs) in hepatocellular carcinoma (HCC) are largely unknown. This study sought to establish a a CICGs-linked HCC signature and assess its predictive significance. We acquired gene expression profiling data for tumor and normal tissues of HCC patients from The Cancer Genome Atlas (TCGA) for training and from the International Cancer Genome Consortium (ICGC) for validation. Consensus clustering was employed to delineate patient cohorts with varying prognoses, categorizing HCC patients into two distinct groups. A selection of fifty CICGs was compiled from the literature, revealing their association with CIC development through functional studies. Six predictive genes were ultimately identified through univariate Cox proportional hazards regression (Cox) and least absolute shrinkage and selection operator (LASSO) analyses. This prognostic signature, resulting from a multivariate Cox, subsequently segmented TCGA and ICGC cohort individuals into high- and low-risk categories. Our verification of the signature's precision involved survival analysis contrasts between those at high and low risk. Quantitative real-time PCR (qRT-PCR) analysis revealed markedly elevated expression levels of these six genes in HCC tumors compared to neighboring healthy tissue, underscoring their potential role in tumor development. This experimentally reinforces the accuracy of the genetic profile. We also examined variations in the composition of immune cells and immunological responses across high-risk and low-risk cohorts. This study established and verified prognostic variables connected to cell-in-cell (CIC), potentially improving personalized survival forecasts for patients with HCC.

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