A novel anoikis-related gene signature can predict the prognosis of hepatocarcinoma patients

• Published in: Translational cancer research Vol. 13; no. 4; pp. 1834 - 1847
• Main Authors: Yu, Xiaohan, Feng, Bo, Wu, Jinge, Li, Meng
• Format: Journal Article
• Language: English
• Published: China 30.04.2024
• Subjects: anoikis; nomograms; prognosis; Hepatocellular carcinoma (HCC)
• ISSN: 2218-676X; 2219-6803
• DOI: 10.21037/tcr-23-2096

Hepatocellular carcinoma (HCC) is a major health problem with more than 850,000 cases per year worldwide. This cancer is now the third leading cause of cancer-related deaths worldwide, and the number is rising. Cancer cells develop anoikis resistance which is a vital step during cancer progression and metastatic colonization. However, there is not much research that specifically addresses the role of anoikis in HCC, especially in terms of prognosis. This study obtained gene expression data and clinical information from 371 HCC patients through The Cancer Genome Atlas (TCGA) Program and The Gene Expression Omnibus (GEO) databases. A total of 516 anoikis-related genes (ANRGs) were retrieved from GeneCard database and Harmonizome portal. Differential expression analysis identified 219 differentially expressed genes (DEGs), and univariate Cox regression analysis was utilized to select 99 ANRGs associated with the prognosis of HCC patients. A risk scoring model with seven genes was established using the least absolute shrinkage and selection operator (LASSO) regression model, and internal validation of the model was performed. The identified 99 ANRGs are closely associated with the prognosis of HCC patients. The risk scoring model based on seven characteristic genes demonstrates excellent predictive performance, further validated by receiver operating characteristic (ROC) curves and Kaplan-Meier survival curves. The study reveals significant differences in immune cell infiltration, gene expression, and survival status among different risk groups. The prognosis of HCC patients can be predicted using a unique prognostic model built on ANRGs in HCC.