Randomized trial develops and validates a prognostic signature for HCC patients undergoing TACE, suggesting personalized treatments.
Background/Aims: Transarterial chemoembolization (TACE) is a key treatment for hepatocellular carcinoma (HCC). However, patient outcomes after TACE are heterogeneous, and robust prognostic biomarkers are needed. This study aimed to develop an efferocytosis-related prognostic signature to stratify HCC patients and others undergoing TACE treatment. Methods: Liver cancer data were obtained from The Cancer Genome Atlas, and the GSE14520 dataset was used for validation. Differential analysis identified five efferocytosis-related genes associated with response to TACE. Consensus clustering of HCC samples revealed molecular subtypes, and differences in immune cell infiltration were analyzed. A prognostic model was developed using univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression, and a nomogram was constructed. Gene expression was validated via quantitative polymerase chain reaction and immunohistochemistry. Single-sample gene set enrichment analysis was performed, a competing endogenous RNA network was constructed, and immune and drug sensitivity differences between risk groups were analyzed. Results: A prognostic signature consisting of TYRO3, CD14, and TREM2 was established and validated for HCC patients, including those who underwent TACE treatment. High-risk patients exhibited significantly lower survival rates than low-risk patients. High-risk patients also exhibited distinct immune characteristics, including differences in immune checkpoint expression, immune cell infiltration, and immune function scores. Additionally, the high-risk group showed higher sensitivity to four drugs, with CD14 expression negatively correlated with sensitivity to vandetanib and cabozantinib. Conclusions: This study developed a model based on efferocytosis-associated characteristics to predict the prognosis of HCC patients and those undergoing TACE treatment, thereby facilitating the formulation of personalized treatment plans.
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Xie et al. (2026) studied this question.
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