Multiomics-based analyses of KPNA2 highlight its multiple potentials in hepatocellular carcinoma

Unraveling the underlying pathogenic factors driving nonalcoholic steatohepatitis and hepatocellular carcinoma: an in-depth analysis of prognostically relevant gene signatures in hepatocellular carcinoma

BACKGROUND

Nonalcoholic steatohepatitis (NASH) is a progressive manifestation of nonalcoholic fatty liver disease (NAFLD) that can lead to fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Despite the growing knowledge of NASH and HCC, the association between the two conditions remains to be fully explored. Bioinformatics has emerged as a valuable approach for identifying disease-specific feature genes, enabling advancements in disease prediction, prevention, and personalized treatment strategies.

MATERIALS AND METHODS

In this study, we utilized CellChat, copy number karyotyping of aneuploid tumors (CopyKAT), consensus Non-negative Matrix factorization (cNMF), Gene set enrichment analysis (GSEA), Gene set variation analysis (GSVA), Monocle, spatial co-localization, single sample gene set enrichment analysis (ssGSEA), Slingshot, and the Scissor algorithm to analyze the cellular and immune landscape of NASH and HCC. Through the Scissor algorithm, we identified three cell types correlating with disease phenotypic features and subsequently developed a novel clinical prediction model using univariate, LASSO, and multifactor Cox regression.

RESULTS

Our results revealed that macrophages are a significant pathological factor in the development of NASH and HCC and that the macrophage migration inhibitory factor (MIF) signaling pathway plays a crucial role in cellular crosstalk at the molecular level. We deduced three prognostic genes (YBX1, MED8, and KPNA2), demonstrating a strong diagnostic capability in both NASH and HCC.

CONCLUSION

These findings shed light on the pathological mechanisms shared between NASH and HCC, providing valuable insights for the development of novel clinical strategies.

The role of KPNA2 as a monotonically changing differentially expressed gene in the diagnosis, risk stratification, and chemotherapy sensitivity of chronic hepatitis B-liver cirrhosis-hepatocellular carcinoma

PURPOSE

Chronic hepatitis B-liver cirrhosis-hepatocellular carcinoma (CLH), commonly called the "liver cancer trilogy", is a crucial evolutionary phase in the emergence of hepatocellular carcinoma (HCC) in China. Previous studies on early diagnostic biomarkers of HCC were limited to the end-stage of HCC and did not focus on the evolutionary process of CLH.

METHODS

11 monotonically changing differentially expressed genes (MCDEGs) highly correlated with CLH were screened through bioinformatic analysis and KPNA2 was identified for further research. The serum KPNA2 expression in different CLH states was detected by Enzyme linked immunosorbent assay (ELISA). A nomogram model was constructed using univariate and multivariate Cox regression methods.

RESULTS

The single-cell RNA-seq and bulk RNA-seq revealed that KPNA2 related to immune infiltration in HCC and may participate in cell cycle pathways in HCC. The serum KPNA2 expression was monotonically upregulated in CLH and was valuable for diagnosing different CLH states. Besides, chronic hepatitis B(CHB) patients, liver cirrhosis (LC) patients, and HCC patients were classified into subgroups with distinct serum KPNA2 expressions. Accordingly, patients with different serum KPNA2 expressions displayed various clinicopathological features. The AUC value of the nomogram model was 0.959 in predicting the likelihood of developing HCC in CHB patients or LC patients. Finally, we found that KPNA2 expression was negatively correlated with the IC50 of four chemotherapeutic drugs in HCC.

CONCLUSION

KPNA2 was a novel serum biomarker for diagnosing different CLH states, monitoring the dynamic evolution of CLH, and a new therapeutic target for intervening in the progression of CLH.