CPLX2 Regulates Ferroptosis and Apoptosis Through NRF2 Pathway in Human Hepatocellular Carcinoma Cells.

Understanding the principle of regulated cell death (RCD) such as ferroptosis and apoptosis provides opportunities to overcome sorafenib resistance of HCC. Complexin II (CPLX2) is involved in calcium-dependent fusion of vesicles and plasma membrane, and recent studies showed CPLX2 is involved in cancer progression. However, the expression and function of CPLX2 are unclear in hepatocellular carcinoma (HCC). qPCR and western blotting assays were used to detect the levels of CPLX2. MTT and colony formation assays were used to detect cell viability. The contents of iron, ROS, MDA, and GSH were used to evaluate the function of CPLX2 on ferroptosis, while the flow cytometry and TUNEL assays were used to evaluate the role of CPLX2 on apoptosis. Our analysis showed CPLX2 is significantly upregulated in HCC, which predicts poor overall survival (OS), progression-free survival (PFS), relapse-free survival (RFS), and disease-specific survival (DSS) for patients with HCC. Further function enrichment analysis of genes related to CPLX2 showed CPLX2 is involved in the NRF2 pathway. Downregulation of CPLX2 can inhibit NRF2 expression and the transcription of its downstream genes, which confirms that CPLX2 is involved in NRF2 pathway. Cell viability assay showed that ferroptosis and apoptosis inhibitors can reverse the inhibition effect of CPLX2-knockdown on cell survival, respectively. And downregulation of CPLX2 significantly promotes the contents of iron, ROS, and MDA, while inhibiting the GSH level of HCC cell lysate, suggesting CPLX2 involved in ferroptosis. Moreover, downregulation of CPLX2 promotes the apoptosis of HCC cells by flow cytometry and TUNEL assay. And upregulation of NRF2 can partly reverse the inhibitory effect of CPLX2-downregulation on ferroptosis and apoptosis. Finally, we found downregulation of CPLX2 aggravates cell death induced by sorafenib. CPXL2 regulates ferroptosis and apoptosis through NRF2 pathway, and CPLX2 knockdown promotes cell death induced by sorafenib. CPLX2 might be an effective target for therapy patients with HCC.

Screening of a novel autophagy-related prognostic signature and therapeutic targets in hepatocellular carcinoma.

BACKGROUND: Many studies have indicated that autophagy plays an important role in multiple cancers, including hepatocellular carcinoma (HCC). This study aimed to establish a prognostic signature for HCC based on autophagy-related genes (ARGs) to predict the prognosis of patients. METHODS: The list of ARGs was derived from screening National Center for Biotechnology Information (NCBI)-Gene and Molecular Signatures Database (MSigDB) datasets. Differential analysis was conducted via the R limma package in HCC patients based on The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analysis were conducted to identify key prognostic ARGs via the survival package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by clusterProfiler package. The Estimation of Stromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm was used to conduct immune analysis. Finally, the correlation between the prognostic model and clinical characteristics was also assessed, including age, tumor-node-metastasis (TNM) stages, and tumor grades. RESULTS: Firstly, 106 differential ARGs were identified and 10 candidates were further confirmed via Cox regression analysis, including BAMBI, HIF1A, SERPINE1, EZH2, SLC9A3R1, IGFBP3, HSPB8, DAB2, CXCL1 and PRNP. The receiver operating characteristic (ROC) curve analysis revealed that the ARGs risk model had a well diagnostic positive rate with 1-year area under the curve (AUC) =0.688 and 3-year AUC =0.674. Correlation analysis indicated that only advanced tumor stages were positively associated with high ARGs scores with P=0.0227. There were also significant differences in tumor purity (P=6.71e-05), infiltrating cell analysis (P=7.77e-05), immune analysis (P=7.9e-05), and stromal cells analysis (P=0.0015) in high- and low-risk ARGs samples. The genes HIF1A, IGFBP3, and DAB2 were found to have high frequent missense mutations in samples with high-risk ARGs scores. Lastly, we also established a nomogram to predict overall survival (OS) of HCC by integrating ARGs scores and other clinical parameters. CONCLUSIONS: Our study established an autophagy-related signature for predicting the prognosis of HCC patients, providing a thorough understanding of the underlying mechanisms of autophagy in HCC.