Construction of endothelial cell-related and autophagy-related prognostic models for hepatocellular carcinoma based on single-cell data.

Background: We aimed to develop an autophagy-related prognostic model with single-cell RNA sequencing (ScRNA-Seq) data for hepatocellular carcinoma (HCC) patients.

Methods: ScRNA-Seq datasets of HCC patients were analyzed by Seurat. The expression of genes involved in canonical and noncanonical autophagy pathways in scRNA-seq data was also compared. Cox regression was applied to construct an AutRG risk prediction model. Subsequently, we examined the characteristics of AutRG high-risk and low-risk group patients.

Results: Six major cell types (hepatocytes, myeloid cells, T/NK cells, B cells, fibroblast cells, and endothelial cells) were identified in the scRNA-Seq dataset. The results showed that most of the canonical and noncanonical autophagy genes were highly expressed in hepatocytes, with the exception of MAP 1LC3B, SQSTM1, MAP 1LC3A, CYBB, and ATG3. Six AutRG risk prediction models originating from different cell types were constructed and compared. The AutRG prognostic signature (GAPDH, HSP90AA1, and TUBA1C) in endothelial cells had the best overall performance for predicting the overall survival of HCC patients, with 1-year, 3-year, and 5-year AUCs equal to 0.758, 0.68, and 0.651 in the training cohort and 0.760, 0.796, and 0.840 in the validation cohort, respectively. The different tumor mutation burden, immune infiltration, and gene set enrichment characteristics of the AutRG high-risk and low-risk group patients were identified.

Conclusion: We constructed an endothelial cell-related and autophagy-related prognostic model of HCC patients using the ScRNA-Seq dataset for the first time. This model demonstrated the good calibration ability of HCC patients and provided a new understanding of the evaluation of prognosis.