Integration of bioinformatics analysis reveals ZNF248 as a potential prognostic and immunotherapeutic biomarker for LIHC: machine learning and experimental evidence

Am J Cancer Res. 2024 Nov 15;14(11):5230-5250. doi: 10.62347/CDUS5096. eCollection 2024.

Abstract

Liver hepatocellular carcinoma (LIHC) is a major contributor to cancer-related mortality worldwide, posing substantial diagnostic and therapeutic challenges. Although zinc finger proteins (ZNFs) are known to play a role in LIHC, the specific function of ZNF248 remains poorly understood. In this study, we analyzed genomic and clinical data from The Cancer Genome Atlas (TCGA) to elucidate the role of ZNF248 through differential expression analysis, bioenrichment, immune response correlation, and drug sensitivity evaluation. Machine learning was employed to identify prognostic signatures derived from ZNF248, which were further validated using Receiver Operating Characteristic (ROC) analysis. Functional assays, including Western blot and rescue experiments, were performed to assess the impact of ZNF248 on the PI3K/AKT signaling pathway. Our results demonstrate that ZNF248 is significantly overexpressed in LIHC patients and is associated with poor prognosis. Bioenrichment analysis revealed activation of oncogenic pathways, and elevated ZNF248 expression correlated with increased immune cell infiltration and enhanced immune scores, thereby influencing both immunotherapy response and drug sensitivity. Functional assays further confirmed that ZNF248 promotes LIHC progression and invasion, while silencing ZNF248 inhibited the PI3K/AKT pathway - a phenomenon reversible by the AKT activator SC79. These findings suggest that ZNF248 contributes to LIHC progression through the PI3K/AKT pathway and may represent a novel immunotherapeutic target and prognostic biomarker for LIHC.

Keywords: LIHC; ZNF248; immune infiltration; immunotherapy; machine learning; prognostic indicator.