Fig 1: RNF2 positively correlates with progression and poor prognosis of HCC by recruiting MDSCs into the tumor microenvironment. A Comparison of RNF2 expression between tumor and normal tissues from TCGA database analyzed by TIMER 2.0. B K-M analysis of the OS of HCC patients in the TCGA liver hepatocellular carcinoma (LIHC)cohort based on the expression level of RNF2. Data were analyzed by log-rank test. C Representative images of IHC staining of RNF2. Scale bars: 100 μm (black). Patients were divided into two groups based on RNF2 expression levels. The low expression group consisted of patients exhibiting negative or weak RNF2 expression, while the high expression group included those with moderate to strong expression. Overall survival curves were generated using the log-rank test to assess differences in survival rates between the two groups. (D-E) The expression of RNF2 was positively correlated with the infiltration levels of MDSCs in LIHC analyzed by TIMER 2.0. Correlation analysis indicated that RNF2 expression was positively correlated with CD33 expression. F Representative mIHC staining of CD33 and RNF2 in tissue from human HCC tumors. Multiplexed immunofluorescence staining images showing the expression of RNF2, CD8, CD33 and DAPI in HCC. G High infiltration levels of MDSCs were associated with poor survival. Cox regression analysis of TCGA data demonstrated a significant correlation between increased MDSC infiltration and worse prognosis in HCC patients. Furthermore, elevated RNF2 expression and a high proportion of MDSCs significantly correlated to poorer OS compared to their counterparts, strongly suggesting that RNF2 influenced patient prognosis through an immune-related mechanism
Fig 2: RNF2 promoted HCC growth in murine orthotopic HCC models A Hepa1-6-Ctrl or Hepa1-6-RNF2 KO cells (1 × 10⁶) were resuspended in 15 mL PBS and injected into the hepatic lobule via syringe. Two weeks later, mice were killed, and tumor weight was measured. (B-C) Tumors from Hepa1-6-Ctrl and Hepa1-6-RNF2 KO groups were analyzed for immune cell infiltration. The percentages of tumor-infiltrating MDSCs, CD4 + , and CD8 + T cells, gated on the CD45 + population, are shown with representative flow cytometry plots. D Representative IHC images showing staining for MDSC markers (Gr1, S100A8, and S100A9) in orthotopic HCC models. The right panel displays quantification of MDSCs based on IHC analysis. E Hepa1-6-Ctrl or Hepa1-6-RNF2 KO cells (1 × 10⁶) resuspended in 2.5 mL PBS were injected via the tail vein. Three weeks post-injection, mice were killed, and the weight of tumor-burdened livers was compared between the Hepa1-6-Ctrl and Hepa1-6-RNF2 KO groups. (F-G) Flow cytometric analysis of tumor-infiltrating MDSCs, CD4 + , and CD8 + T cells, gated on the CD45 + population, with representative plots from the indicated tumor models. H IHC analysis for MDSCs markers. Scale bars, 100 μm. The right graph shows the quantification of MDSCs as analyzed by IHC. Significant differences between two groups and among multiple groups were analyzed by t-test and ANOVA, respectively. **p < 0.01
Fig 3: RNF2 induces CXCL1 via the NF-κB pathway A Analysis of the TIMER 2.0 database revealed the relationship between RNF2 and CXCL1, as well as TRAF2 and CXCL1, in tumors of patients with liver hepatocellular carcinoma. B Western blot analysis was performed to determine the expression of p65 in RNF2 KO Hepa1-6 cells and shRNF2 Sk-Hep1 cells. Whole-cell lysates and nuclear protein extracts were subjected to immunoblotting for p65 levels. C Immunofluorescence assays were conducted to detect phosphorylated p65 (p-p65) in RNF2 KO Hepa1-6 cells or shRNF2 Sk-Hep1 cells. DAPI (blue) was used as a nuclear counterstain. Quantification of nuclear p-p65 positive staining in at least 200 counted cells is presented as percentage ± SEM. D RT-qPCR analysis was used to assess CXCL1 mRNA expression in RNF2 KO Hepa1-6 cells or shRNF2 Sk-Hep1 cells. ELISA was then performed to validate CXCL1 levels in cell culture supernatants from these cultured cells. (E–F) Representative immunohistochemistry images and quantification of CXCL1 expression in tumor-burdened livers from the Hepa1-6 syngeneic tumor models. ELISA was used to validate CXCL1 levels in tumor lysates and sera from these models. Scale bar represents 50 μm. G Migration of MDSCs toward conditioned medium from Hepa1-6 cells (control versus RNF2 KO) were analyzed by transwell MDSC migration assays in triplicate. Migration of MDSCs toward conditioned medium (CM) from Hepa1-6 cells treated with Vehicle or immunoglobulin G (IgG) control, CXCL1-neutralizin antibody, or SX-682 H Quantification of the proliferation of CFSE-labeled CD8 + T cells cocultured with MDSCs from tumor-burdened livers of Hepa1-6-Ctrl or Hepa1-6- RNF2 KO tumors, analyzed by flow cytometry. Data are representative of results obtained in three independent experiments. I Western blotting analysis of suppressive activity MDSCs from Hepa1-6 syngeneic tumors. Statistics calculated using one-way ANOVA post hoc Tukey test for multi-group or two-tailed Student’s t-test for two-group comparisons. **p < 0.01.
Fig 4: RNF2 activates NF-κB signaling A HEK-293 cells were co-transfected with the indicated plasmids along with pNF-κB-luc plasmids or the control-luciferase plasmid and subjected to a reporter assay. Luciferase assay indicated that RNF2 but not the ΔR mutant induces the activation of NF-κB signaling. B Western blot analysis of p-IκBα, IκBα, p-IKKα/β, IKKα, IKKβ, and β-actin in RNF2 KO Hepa1-6 cells or shRNF2 Sk-Hep1 cells. C Western blotting analysis of IκBα expression in the indicated cells treated with TNF-α (10 ng/ml) in RNF2 KO Hepa1-6 cells or shRNF2 Sk-Hep1 cells. β-Actin is used as a loading control. D Assay of NF-κB luciferase reporter gene activity in RNF2-overexpressing Hepa1-6 or Sk-Hep1 cells transfected with vector or the IκBα dominant-negative mutant (IκBα-mu). Statistics calculated using one-way ANOVA post hoc Tukey test for multi-group or two-tailed Student’s t-test for two-group comparisons. **p < 0.01
Fig 5: RNF2 inhibition sensitizes HCC to anti-PD-1 therapy by recruiting MDSCs into the tumor microenvironment A Representative dot plots comparing matched pre- and post-treatment melanoma patient RNF2 mRNA levels in melanoma patients. Statistics calculated using two-sided Wilcoxon matched pair rank test with significance at p < 0.05. Kaplan–Meier curves predicting survival of melanoma patients receiving anti-PD-1 therapy based on net changes in RNF2 mRNA levels in the melanoma-GSE91061-anti-PD-1 datasets. (B-C) C57BL/6 J mice were subcutaneously injected with Hepa1-6-Ctrl or Hepa1-6-RNF2 KO cells and treated with either anti-PD-1 or isotype control. Tumor growth was monitored until the experimental endpoints, with data presented as mean ± SEM. Tumor growth curves are shown. D Representative images of IHC for CD8, Gr1, and S100A8 + S100A9 in indicated mouse tumors and IHC quantification. The scale bars represent 50 μm. E Representative H&E staining (upper), immunostaining and quantification of Ki-67- and TUNEL-positive cells (lower). The scale bars represent 50 μm. F A schematic diagram illustrates the RNF2-TRAF2-CXCL1 axis driving MDSC accumulation, leading to suppression of T cell function in HCC. High RNF2 expression is positively correlated with MDSC infiltration in HCC patients. RNF2 enhances NF-κB activation by regulating K63-linked ubiquitination of TRAF2, resulting in elevated CXCL1 expression, a chemoattractant for MDSCs via the CXCL1-CXCR2 axis. RNF2-recruited MDSCs inhibit the activity of effector CD8 + T cells within the tumor immune microenvironment, thereby promoting immunosuppression and tumor progression in HCC. Statistics calculated using one-way ANOVA post hoc Tukey test for multi-group or two-tailed Student’s t-test for two-group comparisons. **p < 0.01
Supplier Page from Sino Biological, Inc. for Human RING2/RING1B/RNF2 Gene Lentiviral ORF cDNA expression plasmid, C-GFPSpark tag