Journal: Molecular Therapy. Nucleic Acids

Article Title: Combining anti-gene γPNA with small molecules and RNA inhibitors: A strategy to enhance anti-tumor efficacy

doi: 10.1016/j.omtn.2025.102804

Figure Lengend Snippet: Anti-transcription activity of γPNA1 with HDACi in lymphoma cells Relative fold change of c-Myc levels in U2932 cells measured by real-time PCR on day 2 after treatment with (A) γPNA1 and (B) ScR-γPNA2 in combination with romidepsin, entinostat, vorinostat, panobinostat, and belinostat. Results are presented as mean ± SEM and two-way ANOVA was used to determine the statistically significant difference between groups. Western blot analysis representing the change in c-MYC protein on day 2 after treatment with γPNA1 and ScR-γPNA2 in combination with (C) romidepsin, (D) entinostat, (E) vorinostat, (F) panobinostat, and (G) belinostat. ∗∗(C–F) Cyclophilin B was used as an endogenous control, and the same blots are presented in C–S3G. c-MYC, EZH2, and cyclophilin B were probed from the same blot. Results are presented as mean ± SEM, and the p value between groups was determined using one-way ANOVA.

Article Snippet: Taqman gene expression assay for c-Myc (Thermo Fisher Scientific, Hs00153408), GAPDH (Thermo Fisher Scientific, Hs02758991), and EZH2 (Thermo Fisher Scientific, Hs00544830) was used to amplify the respective mRNAs using the specified cycling conditions in the QuantStudio 5 real-time PCR detection system (Thermo Fisher Scientific, USA).

Techniques: Activity Assay, Real-time Polymerase Chain Reaction, Western Blot, Control

Journal: Molecular Therapy. Nucleic Acids

Article Title: Combining anti-gene γPNA with small molecules and RNA inhibitors: A strategy to enhance anti-tumor efficacy

doi: 10.1016/j.omtn.2025.102804

Figure Lengend Snippet: MYC/MAX inhibitors in combination with anti-transcription γPNA1 Cell viability of (A) U2932 and (B) Raji cells treated with increasing doses of MYC/MAX inhibitors (Myci975, EN4, 10058-F4, and sAJM589) alone and in combination with γPNA1 and ScR-γPNA2 (8 μM) for 72 h. Results are presented as mean ± SEM. The IC 50 (95% CI) values of MYC/MAX inhibitors alone and combination treatment of MYC/MAX with γPNA1 in (C) U2932 and (D) Raji cells. (E) Cell viability of γPNA1-treated U2932 and Raji cells at 8 μM concentration. Western blot analysis representing the change in c-MYC protein 72 h after treatment with γPNA1 and ScR-γPNA2 in combination with (F) Myci975, (G) EN4, (H) 10058-F4, and (I) sAJM589. ∗∗(F–I) Cyclophilin B was used as an endogenous control, and the same blots are presented in A–S7D. c-MYC, EZH2, and cyclophilin B were probed from the same blot. Results are presented as mean ± SEM, p value for one-way ANOVA.

Article Snippet: Taqman gene expression assay for c-Myc (Thermo Fisher Scientific, Hs00153408), GAPDH (Thermo Fisher Scientific, Hs02758991), and EZH2 (Thermo Fisher Scientific, Hs00544830) was used to amplify the respective mRNAs using the specified cycling conditions in the QuantStudio 5 real-time PCR detection system (Thermo Fisher Scientific, USA).

Techniques: Concentration Assay, Western Blot, Control

Journal: Frontiers in Immunology

Article Title: Integrative bulk and single-cell transcriptomics link EZH2 to immunosuppressive programs and tumor–Treg crosstalk in castration-resistant prostate cancer

doi: 10.3389/fimmu.2026.1725097

Figure Lengend Snippet: EZH2 is upregulated in PCa and associates with an immunosuppressive microenvironment and poor prognosis. (A) Study workflow integrating TCGA/GEO bulk datasets and single-cell analyses: immune-signature scoring, correlation with EZH2, derivation of EZH2-related IMDEGs, risk modeling and subtyping, cell-type–specific interrogation (malignant cells and Treg), cell–cell interaction profiling, and planned validation in EZH2-inhibitor–treated cell lines. (B) Paired tumor–normal comparison of EZH2 across TCGA cancers (Wilcoxon paired tests; *BH-adjusted P < 0.05, **BH-adjusted P < 0.01, ***BH-adjusted P < 0.001). Red and blue dots indicate tumor and matched normal samples, respectively. The red/blue panel background indicates whether EZH2 is upregulated or downregulated in tumors relative to matched normal tissues. PRAD is highlighted. (C) In TCGA-PRAD, EZH2 expression in lymph-node–positive tumors (N1) versus N0 tumors (Wilcoxon rank-sum test; BH-adjusted P = 2.42×10 -6 ; N0: n=393, N1: n=80). (D) Independent GEO cohort comparing EZH2 expression between HD-PCa and mCRPC (Wilcoxon rank-sum test; BH-adjusted P = 9×10 - ¹³; HD-PCa: n=22, mCRPC: n=29). (E) Kaplan–Meier analysis of PFI in TCGA-PRAD comparing EZH2-high (n=275) vs. EZH2-low (n=276) tumors (log-rank test; two-sided nominal P<0.0001). (F) Correlations between EZH2 and immune/stromal signatures in TCGA-PRAD. Enrichment scores for 29 curated signatures were calculated by ssGSEA and z-scored within cohort; associations with EZH2 were assessed by Spearman correlation, and only signatures with nominal P < 0.05 are shown. Asterisks denote significance (*P < 0.05, **P < 0.01, ***P < 0.001). Color indicates Spearman correlation coefficient (ρ), with red denoting positive and blue denoting negative correlations. (G) Kaplan–Meier analysis of progression-free interval (PFI) stratified by EZH2, Treg, and TAM (M2) status in TCGA-PRAD (cutoffs as defined in Methods; log-rank test). Tick marks indicate censored observations; numbers at risk are shown below the plot. The x-axis is truncated at 5 years for clarity.

Article Snippet: Cells were treated with the EZH2 inhibitor tazemetostat (MedChemExpress, HY-13803) dissolved in DMSO; vehicle controls received an equivalent volume of DMSO.

Techniques: Single Cell, Biomarker Discovery, Comparison, Expressing

Journal: Frontiers in Immunology

Article Title: Integrative bulk and single-cell transcriptomics link EZH2 to immunosuppressive programs and tumor–Treg crosstalk in castration-resistant prostate cancer

doi: 10.3389/fimmu.2026.1725097

Figure Lengend Snippet: EZH2-linked IMDEGs enable risk modeling and immune subtyping of PCa. (A) Analysis workflow. Tumors were stratified by EZH2 (top 30 vs bottom 30; left), followed by DEG identification (center) and correlation with Treg/TAM signatures (Spearman; |r| ≥ 0.4, nominal P < 0.05) to derive IMDEGs (right; schematic network). (B) GO Biological Process enrichment of IMDEGs. The x-axis shows −log10(nominal P). Dot size denotes gene count; color indicates BH-adjusted P values. (C) Non-zero model coefficients of the final gene signature. Coefficients were obtained from the selected survival model fitted in the training cohort, and the risk score was computed as a weighted linear sum of gene expression levels using these coefficients. (D) Kaplan–Meier analysis of PFI in the training cohort. Patients were stratified into high- and low-risk groups based on the median risk score. The P value from the log-rank test is shown. Tick marks indicate censored observations. (E) Consensus Non-negative Matrix Factorization (NMF) clustering of IMDEGs with k=6. The consensus matrix shows pairwise sample co-clustering frequencies (0–1). Sample annotations indicate assigned subtype and silhouette width (range shown). Rank-selection diagnostics are provided in . (F) Heatmap of prognosis-associated IMDEGs (row-scaled expression) across assigned subtypes. Rows represent individual IMDEGs and columns represent patients ordered by NMF-derived immune subtype. Expression values are row-wise z-scores, with red indicating higher-than-average and blue indicating lower-than-average expression within the cohort. (G) Heatmap of immune modulators across subtypes. The color scale represents row-wise z-scored expression, and column ordering is the same as in (F) . The left annotation indicates immune-modulator categories.

Article Snippet: Cells were treated with the EZH2 inhibitor tazemetostat (MedChemExpress, HY-13803) dissolved in DMSO; vehicle controls received an equivalent volume of DMSO.

Techniques: Gene Expression, Selection, Expressing, Derivative Assay

Journal: Frontiers in Immunology

Article Title: Integrative bulk and single-cell transcriptomics link EZH2 to immunosuppressive programs and tumor–Treg crosstalk in castration-resistant prostate cancer

doi: 10.3389/fimmu.2026.1725097

Figure Lengend Snippet: Single-cell transcriptomics identifies a malignant EZH2^high program marked by proliferation and suppression of interferon/immune-response pathways. (A) UMAP of scRNA-seq from CSPC and CRPC tumors with major lineages annotated. (B) Dot plot of EZH2 across lineages in CSPC and CRPC; color indicates average expression and dot size the percent of cells expressing, with significance denoted by asterisks (two-sided Wilcoxon rank-sum test; BH-adjusted P; ***q<0.001). (C, D) Malignant cell calling by copy-number inference: scatter of CNA correlation versus CNA signal separates malignant (red) from non-malignant (green) cells (C) ; corresponding heatmap of inferred CNAs across cells (D, E) Feature plots of EZH2 expression distribution across malignant and non-malignant cell clusters. (F) Volcano plot of DEGs between malignant EZH2^high and EZH2^low cells (two-sided Wilcoxon; min.pct = 0.1, logfc.threshold = 0.25, BH-adjusted P < 0.05). (G) Hallmark gene set enrichment analysis (GSEA) comparing malignant EZH2^high versus EZH2^low cells; bars show normalized enrichment scores (NES), with positive NES enriched in EZH2^high and negative NES enriched in EZH2^low.

Article Snippet: Cells were treated with the EZH2 inhibitor tazemetostat (MedChemExpress, HY-13803) dissolved in DMSO; vehicle controls received an equivalent volume of DMSO.

Techniques: Single-cell Transcriptomics, Expressing

Journal: Frontiers in Immunology

Article Title: Integrative bulk and single-cell transcriptomics link EZH2 to immunosuppressive programs and tumor–Treg crosstalk in castration-resistant prostate cancer

doi: 10.3389/fimmu.2026.1725097

Figure Lengend Snippet: Treg expansion and EZH2-linked malignant–Treg communication in CRPC. (A) UMAP of T cells from CSPC and CRPC ( GSE264573 ) with major subsets annotated. (B) Fractional composition of T-cell subsets. For each sample, the proportion of each T-cell subset was calculated as the number of cells assigned to that subset divided by the total number of T cells in the sample. Group differences in T-cell subtype proportions (CSPC vs CRPC) were tested using the propeller method (speckle), a limma empirical Bayes moderated t-test (two-sided) on transformed proportions, with BH FDR correction. Asterisks denote significance (* q < 0.05). (C) Dot plots of EZH2 and FOXP3 expression in Tregs from CSPC and CRPC samples. Dot size indicates percent expressed and color indicates average scaled expression. (D, E) GO Biological Process enrichment of genes positively (D) or negatively (E) correlated with EZH2 in Tregs. Correlations were assessed by metacell-based correlation analysis (see Methods; |r| ≥ 0.4, nominal P < 0.05) and GO enrichment significance is shown as BH-adjusted P (q values) in the color scale; dot size denotes gene count. (F) CellPhoneDB ligand–receptor analysis (mean>2; permutation P<0.05) for malignant–Treg pairs in CSPC and CRPC. Dot size and color indicate interaction mean expression level (as defined by CellPhoneDB). Significant interactions were identified by permutation testing (* P < 0.05, ** P < 0.01, *** P < 0.001). (G) Metacell-based correlation heatmaps linking EZH2 with malignant-cell ligands (left) and Treg receptors (right) (Pearson; ** nominal P < 0.01, *** nominal P < 0.001).

Article Snippet: Cells were treated with the EZH2 inhibitor tazemetostat (MedChemExpress, HY-13803) dissolved in DMSO; vehicle controls received an equivalent volume of DMSO.

Techniques: Transformation Assay, Expressing

Journal: Frontiers in Immunology

Article Title: Integrative bulk and single-cell transcriptomics link EZH2 to immunosuppressive programs and tumor–Treg crosstalk in castration-resistant prostate cancer

doi: 10.3389/fimmu.2026.1725097

Figure Lengend Snippet: EZH2 inhibitor perturbation analysis and cross-validation with malignant-cell programs. (A) Immunoblot of H3K27me3 and total H3 in C42 cells treated with EZH2 inhibitor (EZH2i) at the indicated concentrations, with densitometric quantification shown as the H3K27me3/H3 ratio (line plot). (B) Principal component analysis (PCA) of RNA-seq expression profiles (all expressed genes) comparing C42_Control and C42_EZH2i groups. (C) Volcano plot of differentially expressed genes (DEGs) between C42_EZH2i and C42_Control. Upregulated genes are shown in red, downregulated genes in blue, and non-significant genes in gray (two-sided Wald test in DESeq2; BH-adjusted P < 0.05 and |log2FC| ≥ 0.585). The top 5 upregulated (NEAT1, MALAT1, CYP1A1, SOX8, MUC3A) and top 5 downregulated (TXNRD2, ALDH1B1, PMPCA, PCCB, CPT2) genes are labeled (ranked by BH-adjusted P among significant DEGs). (D) Venn diagram showing overlap between malignant-cell DEGs from single-cell analysis (EZH2^high vs EZH2^low) and genes downregulated by EZH2i in C42 cells; representative overlapping genes are listed. (E) Venn diagram showing overlap between genes downregulated in EZH2^high malignant cells and genes upregulated by EZH2i in C42 cells; top3 enriched KEGG pathways for the overlapping set are shown on the right. (F) RNA-seq expression (TPM) of selected genes in Control versus EZH2i conditions. Box plots show median and IQR; points represent biological replicates. Differential expression was assessed using the two-sided Wald test in DESeq2 with BH-adjusted P values; significance is indicated as **q < 0.01 and ***q < 0.001. (G) RT–qPCR validation of selected genes in Control versus EZH2i conditions. Data are shown as mean ± SD (n = 3 biological replicates); between-group comparisons were performed using two-sided Student’s t-test; ***P < 0.001. GAPDH was used as the internal control and relative expression was calculated using the 2^-ΔΔCt method.

Article Snippet: Cells were treated with the EZH2 inhibitor tazemetostat (MedChemExpress, HY-13803) dissolved in DMSO; vehicle controls received an equivalent volume of DMSO.

Techniques: Biomarker Discovery, Western Blot, RNA Sequencing, Expressing, Control, Labeling, Single-cell Analysis, Quantitative Proteomics, Quantitative RT-PCR