Single-cell RNA sequencing analysis reveals potential key prognostic markers in hepatocellular carcinoma.

BACKGROUND

Hepatocellular carcinoma (HCC) is the sixth most frequently diagnosed cancer worldwide accompanied by a low 5-year survival rate. In our study, we aimed to analyze relevant genetic features that can predict the prognosis of HCC patients by single-cell RNA sequencing (scRNA-seq).

METHODS

Single-cell RNA-seq data of HCC were analyzed from the Gene Expression Omnibus (GEO) database. Using the Seurat package, we performed quality control to remove cells with low quality. After normalization, we detected highly variable genes across the single cells. Then, cell clustering and Cell type annotation were performed using highly variable genes. Then, functional enrichment analyses were performed by GO and KEGG, and cell-cell communication analysis, trajectory analysis were conducted. LASSO-Cox regression analysis was used to perform Survival analysis and ROC evaluation for high and low-risk groups. Validation of the expressions and survival prognosis of the screened genes in HCC. Expression levels of the genes were analyzed by RT-qPCR and western blot in normal liver cell line THLE-3 and HCC cell lines (HuH7, HCCLM9, and HCCLM13).

RESULTS

A total of 2208 up-regulated and 1447 down-regulated genes were identified in HCC samples. These differentially expressed genes (DEGs) were enriched in several cytokine-related pathways and the MIF-CD74/CXCR4 signaling pathway. By integrating large amounts of RNA sequencing data, we identified 566 prognostic genes associated with HCC cells. Eleven genes were screened using the LASSO-COX risk factor model. Stratifying patients into high- or low-risk groups based on these genes allowed us to effectively predict their survival and ROC curve. Five genes were further found to be associated with poor survival prognosis in HCC and were notably overexpressed in HCC cell lines compared to normal liver cell line.

CONCLUSION

This study revealed potential prognostic marker genes in HCC patients, providing insights into predicting patients' survival rates.