Decoding ARF4 and EIF5B-Based Prognostic Signatures and Immune Landscape Following Insufficient Radiofrequency Ablation in Hepatocellular Carcinoma: Through Multi-Omics and Experimental Validation.

Background: Radiofrequency ablation (RFA) is pivotal in non-surgical hepatocellular carcinoma (HCC) treatments but poses a high postoperative recurrence risk, exceeding conventional surgeries. Insufficient tumor ablation may trigger immune responses, promoting tumor progression locally. Hence, this study seeks to pinpoint immune biomarkers to improve treatment precision and prognostic accuracy for RFA patients.

Methods: The study utilized data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and The International Cancer Genome Consortium (ICGC) database to investigate novel immune biomarkers influencing the prognosis of patients undergoing insufficient radiofrequency ablation (IRFA). Subsequently, an IRFA model was developed and validated. Then, we employed Quantitative real time-Polymerase Chain Reaction (qPCR), Western blotting (WB), immunohistochemistry (IHC), and immunofluorescence (IF) techniques on human HCC cell lines and IRFA animal model to validate ADP-ribosylation factor 4 (ARF4) and Eukaryotic translation initiation factor 5B (EIF5B) expression and prognostic relevance post-IRFA. In addition, knockdown of ARF4 and EIF5B was performed to evaluate cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT). Finally, transcriptome sequencing was subsequently performed to confirm and extend our findings.

Results: ARF4 and EIF5B were identified as critical immune targets affecting IRFA patient prognosis, forming the basis of an IRFA risk model. High-risk scores in this model correlated with poorer prognoses and reduced responsiveness to immune checkpoint inhibitors (ICIs) across multiple cancer types. Experimental validations confirmed the protective role of ARF4 and EIF5B in IRFA outcomes, while knockdown experiments suggested their involvement in promoting cell proliferation, migration, invasion, and EMT in IRFA models, potentially through pathways like P53 and Transforming Growth Factor Beta(TGF-β) signaling pathway activation as indicated by transcriptome sequencing.

Conclusion: ARF4 and EIF5B have demonstrated promising potential as biomarkers influencing patient prognosis following RFA in HCC. These findings suggest they could serve as viable therapeutic targets aimed at mitigating HCC recurrence post-RFA.