STEAP4 with copper reductase activity suppresses tumorigenesis by regulating the cell cycle in hepatocellular carcinoma cells

Abstract

Background: Abnormal expression of six-transmembrane epithelial antigen of prostate 4 (STEAP4) has been implicated in the carcinogenesis of hepatocellular carcinoma (HCC). However, the biological role and regulatory mechanisms of STEAP4 in HCC remain unclear.

Methods and results: Here, we analyzed STEAP4 expression levels and differentially expressed genes (DEGs) between STEAP4 high- and low-expression groups using multiple databases. Proliferation assays, 5-ethynyl-2'-deoxyuridine (EdU) assays, propidium iodide (PI) flow cytometry, and colony formation assays were conducted to assess the effects of STEAP4 on HCC cell proliferation, cell cycle progression, and clonogenic capacity. STEAP4 was downregulated in HCC tumor tissues, with lower expression associated with poorer overall survival (OS) and disease-free survival (DFS) in patients. Functional network analysis suggested that STEAP4 regulates cell cycle signaling, with tumor sections showing a negative correlation between STEAP4 and cell cycle proteins. Overexpression of STEAP4, combined with non-cytotoxic copper exposure in the HepG2 cell line, reduced proliferation and clonogenicity, induced cell cycle arrest, and downregulated the mRNA and protein levels of cell cycle-regulating genes. A predictive model based on STEAP4 and cell cycle gene demonstrated prognostic value in HCC patients.

Conclusions: Our results lay a foundation for further study of the cell cycle regulatory role of STEAP4 with Cu²⁺ reductase activity in HCC, indicating that STEAP4 may be a promising therapeutic target for HCC.

Keywords: Cell cycle; Copper reductase activity; Hepatocellular carcinoma; STEAP4; Tumorigenesis.

Fig. 1

STEAP4 expression in HCC cohorts. A Box plots showing STEAP4 mRNA expression in liver hepatocellular carcinoma (LIHC) tumor cohort versus TCGA normal and GTEx data, analyzed by t-test in the GEPIA database (*, p < 0.01). B Scatter plots of STEAP4 mRNA expression in tumor and non-tumor samples from HCC patients, as presented in the Oncomine database across multiple datasets, including Chen Liver, Roessler Liver, Roessler Liver 2, Wurmbach Liver, and Mas Liver (*, p < 0.05; ****, p < 0.0001). C Representative IHC images (10X and 40X) illustrating STEAP4 protein expression in HCC and adjacent non-tumor tissue. Scale bar = 50 µm for 40X images. Overall statistical analysis of STEAP4 protein expression in HCC patient samples based on IHC staining (****, p < 0.0001)

Fig. 2

Prognostic evaluation of STEAP4 in HCC patients. A, B Analysis of overall survival (OS) and disease-free survival (DFS) based on high and low STEAP4 expression in LIHC patients using the GEPIA database. C Kaplan–Meier analysis of OS for high and low STEAP4 expression in TCGA-LIHC samples. D Multivariate Cox proportional hazards analysis of OS, visualized through a forest plot

Fig. 3

DEGs of key cell cycle-related genes in high and low STEAP4 expression groups in LIHC cohort. A Volcano plots display differentially expressed genes (DEGs). B KEGG pathway enrichment analysis of DEGs, conducted using DAVID, is visualized in bubble plots, with the y-axis showing significantly enriched KEGG pathways and the x-axis showing various gene ratios. DEGs, differentially expressed genes; KEGG, Kyoto Encyclopedia of Genes and Genomes. C The top 5 negatively correlated cell cycle-related genes with STEAP4, analyzed using TIMER

Fig. 4

Representative IHC images showing the expression of STEAP4, PLK1, CDC25C, CDC20, CCNB2, CCNB1, and CDK1 proteins in HCC and adjacent non-tumor tissues. Compared to peritumoral tissues, HCC tissues exhibit lower STEAP4 expression and higher levels of PLK1, CDC20, CDC25C, and CDK1 (n = 7). T: tumor; P: peritumoral tissue. Scale bar: 100 µm

Fig. 5

Efficacy of STEAP4 overexpression in Hep G2 Cells via copper reductase activity. A STEAP4 overexpression in Hep G2 cells shows no significant cytotoxicity. B, C Copper incubation induces a dose-dependent cytotoxic effect on Hep G2 cells, with 50 μM copper identified as a non-cytotoxic concentration. D Co-treatment with STEAP4 overexpression and 50 μM copper decreases cell viability in Hep G2 cells. E, F Co-treatment with STEAP4 overexpression and 50 μM copper reduces colony formation in Hep G2 cells. *p < 0.05, **p < 0.01, ***p < 0.001, ^##p < 0.0001

Fig. 6

Inhibition of Hep G2 cell proliferation by STEAP4 with copper reductase activity. A, B The 5-Ethynyl-2′-deoxyuridine (EdU) staining reveals reduced cell proliferation rates following STEAP4 overexpression with 50 μM copper co-treatment. C GSEA of the LICH-TCGA cohort highlights STEAP4 co-expressed genes linked to cell cycle regulation. * p < 0.05

Fig. 7

Effects of STEAP4 overexpression and 50 μM copper on cell cycle distribution in Hep G2 cells. A–C Cell cycle distribution analysis shows that co-treatment with STEAP4 overexpression and 50 μM copper increases the percentage of Hep G2 cells in sub-G1 and G2/M phases. The synergistic effect is eliminated by STEAP4 knockdown via siRNA, indicating G2/M cell cycle arrest associated with STEAP4 copper reductase activity. * p < 0.05

Fig. 8

STEAP4 and 50 μM Copper co-treatment downregulates indicated cell cycle genes in Hep G2 cells. A STEAP4 with copper reductase activity reduces PLK1, CDK1, CDC20, CDC25C, and CCNB2 mRNA expression in Hep G2 cells. This synergistic effect is abolished by STEAP4 knockdown via siRNA. * p < 0.05, ** p < 0.01. B STEAP4 with copper reductase activity reduces PLK1, CDK1, CDC20, CDC25C, and CCNB2 protein expression in Hep G2 cells as indicated by representative western blot results

Fig. 9

Prognostic model construction and subgroup analysis. A Kaplan–Meier curves and log-rank test show OS differences in high- vs. low-risk groups (TCGA-LIHC). B Scatter plots showing gene distribution in the signature. C ROC curves evaluating the signature's predictive performance in TCGA-LIHC. D Identification of signature as an independent prognostic factor. E Subgroup analysis across different clinical factors: early-stage, advanced stage, male, female, < 60-year and ≥60 years, respectively

Fig. 10

Signature validation in ICGC-HCC dataset and nomogram development. A Kaplan–Meier curves and log-rank test of OS in high- and low-risk groups (ICGC-HCC). B Scatter plots of gene expression in the signature. C ROC curves assessing prediction performance (ICGC-HCC). D Identification of the signature as an independent prognostic factor. E Nomogram integrating TNM stage and signature. F Calibration plots for survival rates at 1, 3, and 5 years

Fig. 11

Schematic diagram of proposed mechanism of STEAP4-mediated copper reductase activity in HCC tumorigenesis suppression via cell cycle regulation. This schematic illustrates STEAP4's functional impact on HCC cells in vitro. STEAP4-mediated copper reduction leads to downregulation of key cell cycle genes, inhibiting G2/M progression in HCC cells. Further investigation into the underlying mechanisms of STEAP4-mediated regulation of cell cycle genes is warranted. (Figure created with Figdraw)