Construction of a prognostic model based on disulfidptosis-related genes and identification of CCNA2 as a novel biomarker for hepatocellular carcinoma.

BACKGROUND

Disulfidptosis, identified as an innovative form of cellular death subsequent to cuproptosis, is currently under investigation for its mechanisms in oncological contexts. In-depth analyses exploring the relationship between disulfidptosis-related genes (DRGs) and hepatocellular carcinoma (HCC) are currently limited.

METHODS

Transcriptomic data and clinical information were retrieved from the TCGA and GEO databases (GSE76427 and GSE54236), concentrating on the expression levels of 24 DRGs. Subsequently, multifactor and LASSO regression analyses were utilized to construct the 5-DRG prognostic signature. Immunohistochemistry (IHC) was employed to assess Cyclin A2 (CCNA2) protein expression levels. Quantitative real-time PCR (qRT-PCR) and western blot analyses were conducted to detect transcriptomic and protein expression of CCNA2-targeting short interfering RNA (siRNA). The Cell Counting Kit-8 (CCK-8) assay, EdU staining, and scratch experiments were employed to observe the proliferation and migration of hepatoma cell lines subsequent to CCNA2 inhibition.

RESULTS

Three HCC patterns were identified, among which pattern B exhibited the the most unfavorable survival outcomes. Five DRGs (STC2, PBK, CCNA2, SERPINE1, and SLC6A1) were involved to establish the 5-DRG prognostic signature. High-risk groups (HRGs) exhibited prolonged survival durations in comparison to low-risk groups (LRGs). Both bioinformatics analyses and experimental methodologies corroborated the association of CCNA2 with poor prognosis in HCC patients. Functional studies elucidated that interference with CCNA2 significantly inhibited proliferation and migration, while simultaneously promoting apoptosis in hepatoma cells and resulting in the downregulation of epithelial-mesenchymal transition (EMT)-related protein markers.

CONCLUSIONS

The 5-DRG prognostic signature is proficient in predicting clinical outcomes, informing therapeutic strategies, and elucidating the characteristics of the immune microenvironment in HCC patients. Furthermore, this study elucidates the potential of CCNA2 as an innovative biomarker for HCC.