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NRF2 restricts SARS-CoV-2 replication (A-B) SARS-CoV-2 <t>permissive</t> <t>786-O</t> cell clone deficient in NRF2 <t>(NRF2-KO)</t> and control cells were infected with SARS-CoV-2 at MOI 0.01 for 24 h. Cell lysates were then prepared for qPCR for viral RNA or for immunoblotting against viral protein NC, NRF2, and loading control VCL (Vinculin). (C–D) SARS-CoV-2 permissive 786-O cells were used for CRISPR-Cas9-mediated elimination of NRF2. Cells were then infected with SARS-CoV-2 at MOI 0.01 for 24 h before cell lysates were prepared for qPCR and cell supernatants harvested for TCID50 analysis. (E–F) SARS-CoV-2 permissive Huh-7 cells were treated with dCas9 alone or dCas9 along with sgRNAs targeting the promoter region of NRF2 or IRF1. Cells were then infected with SARS-CoV-2 at MOI 0.01 for 24 h before cell lysates were prepared for immunoblotting and cell supernatants harvested for TCID50. (G) Graphic representation of CRISPRa for NRF2-driven genes. (H–J) CRISPRa was used to induce endogenous expression of indicated NRF2-driven genes in SARS-CoV-2 permissive Huh-7 cells. Cells were then infected with SARS-CoV-2 at MOI 0.01 for 8 h before lysates were collected for qPCR or immunoblotting. (H) Displays immunoblots for viral protein NC and loading control VCL. (I) Displays expression levels of NC normalized to VCL expression levels for each tested gene based on densitometric quantification of immunoblots. (J) Displays mean SARS-CoV-2 RNA levels by qPCR normalized to beta actin expression levels for each gene tested from two independent experiments. (K) TCID50 was established from cell supernatants harvested from Huh-7 cells where indicated genes were induced by CRISPRa before infection with SARS-CoV-2 at MOI 0.02 for 8 h. (A–F) Are representative of two independent experiments. Each data point represents one biological replicate with bars indicating mean ± s.e.m. (H–I) represents data from one experiment. (K) Each data point indicates mean of three biological replicates. Bars indicate mean ± s.e.m. of two or three independent experiments. p-values were established using Graphpad Prism 10 using the Student's t -test with “∗” indicating p < 0.05.

786 O Nrf2 Ko, supplied by ATCC, used in various techniques. Bioz Stars score: 98/100, based on 2221 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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1) Product Images from "NRF2 controls a diverse network of antiviral effectors with p62 acting as a central restriction factor effective across virus families"

Article Title: NRF2 controls a diverse network of antiviral effectors with p62 acting as a central restriction factor effective across virus families

Journal: Redox Biology

doi: 10.1016/j.redox.2026.104135

NRF2 restricts SARS-CoV-2 replication (A-B) SARS-CoV-2 permissive 786-O cell clone deficient in NRF2 (NRF2-KO) and control cells were infected with SARS-CoV-2 at MOI 0.01 for 24 h. Cell lysates were then prepared for qPCR for viral RNA or for immunoblotting against viral protein NC, NRF2, and loading control VCL (Vinculin). (C–D) SARS-CoV-2 permissive 786-O cells were used for CRISPR-Cas9-mediated elimination of NRF2. Cells were then infected with SARS-CoV-2 at MOI 0.01 for 24 h before cell lysates were prepared for qPCR and cell supernatants harvested for TCID50 analysis. (E–F) SARS-CoV-2 permissive Huh-7 cells were treated with dCas9 alone or dCas9 along with sgRNAs targeting the promoter region of NRF2 or IRF1. Cells were then infected with SARS-CoV-2 at MOI 0.01 for 24 h before cell lysates were prepared for immunoblotting and cell supernatants harvested for TCID50. (G) Graphic representation of CRISPRa for NRF2-driven genes. (H–J) CRISPRa was used to induce endogenous expression of indicated NRF2-driven genes in SARS-CoV-2 permissive Huh-7 cells. Cells were then infected with SARS-CoV-2 at MOI 0.01 for 8 h before lysates were collected for qPCR or immunoblotting. (H) Displays immunoblots for viral protein NC and loading control VCL. (I) Displays expression levels of NC normalized to VCL expression levels for each tested gene based on densitometric quantification of immunoblots. (J) Displays mean SARS-CoV-2 RNA levels by qPCR normalized to beta actin expression levels for each gene tested from two independent experiments. (K) TCID50 was established from cell supernatants harvested from Huh-7 cells where indicated genes were induced by CRISPRa before infection with SARS-CoV-2 at MOI 0.02 for 8 h. (A–F) Are representative of two independent experiments. Each data point represents one biological replicate with bars indicating mean ± s.e.m. (H–I) represents data from one experiment. (K) Each data point indicates mean of three biological replicates. Bars indicate mean ± s.e.m. of two or three independent experiments. p-values were established using Graphpad Prism 10 using the Student's t -test with “∗” indicating p < 0.05.

Figure Legend Snippet: NRF2 restricts SARS-CoV-2 replication (A-B) SARS-CoV-2 permissive 786-O cell clone deficient in NRF2 (NRF2-KO) and control cells were infected with SARS-CoV-2 at MOI 0.01 for 24 h. Cell lysates were then prepared for qPCR for viral RNA or for immunoblotting against viral protein NC, NRF2, and loading control VCL (Vinculin). (C–D) SARS-CoV-2 permissive 786-O cells were used for CRISPR-Cas9-mediated elimination of NRF2. Cells were then infected with SARS-CoV-2 at MOI 0.01 for 24 h before cell lysates were prepared for qPCR and cell supernatants harvested for TCID50 analysis. (E–F) SARS-CoV-2 permissive Huh-7 cells were treated with dCas9 alone or dCas9 along with sgRNAs targeting the promoter region of NRF2 or IRF1. Cells were then infected with SARS-CoV-2 at MOI 0.01 for 24 h before cell lysates were prepared for immunoblotting and cell supernatants harvested for TCID50. (G) Graphic representation of CRISPRa for NRF2-driven genes. (H–J) CRISPRa was used to induce endogenous expression of indicated NRF2-driven genes in SARS-CoV-2 permissive Huh-7 cells. Cells were then infected with SARS-CoV-2 at MOI 0.01 for 8 h before lysates were collected for qPCR or immunoblotting. (H) Displays immunoblots for viral protein NC and loading control VCL. (I) Displays expression levels of NC normalized to VCL expression levels for each tested gene based on densitometric quantification of immunoblots. (J) Displays mean SARS-CoV-2 RNA levels by qPCR normalized to beta actin expression levels for each gene tested from two independent experiments. (K) TCID50 was established from cell supernatants harvested from Huh-7 cells where indicated genes were induced by CRISPRa before infection with SARS-CoV-2 at MOI 0.02 for 8 h. (A–F) Are representative of two independent experiments. Each data point represents one biological replicate with bars indicating mean ± s.e.m. (H–I) represents data from one experiment. (K) Each data point indicates mean of three biological replicates. Bars indicate mean ± s.e.m. of two or three independent experiments. p-values were established using Graphpad Prism 10 using the Student's t -test with “∗” indicating p < 0.05.

Techniques Used: Control, Infection, Western Blot, CRISPR, Expressing

Image Search Results

Journal: Redox Biology

Article Title: NRF2 controls a diverse network of antiviral effectors with p62 acting as a central restriction factor effective across virus families

doi: 10.1016/j.redox.2026.104135

Figure Lengend Snippet: NRF2 restricts SARS-CoV-2 replication (A-B) SARS-CoV-2 permissive 786-O cell clone deficient in NRF2 (NRF2-KO) and control cells were infected with SARS-CoV-2 at MOI 0.01 for 24 h. Cell lysates were then prepared for qPCR for viral RNA or for immunoblotting against viral protein NC, NRF2, and loading control VCL (Vinculin). (C–D) SARS-CoV-2 permissive 786-O cells were used for CRISPR-Cas9-mediated elimination of NRF2. Cells were then infected with SARS-CoV-2 at MOI 0.01 for 24 h before cell lysates were prepared for qPCR and cell supernatants harvested for TCID50 analysis. (E–F) SARS-CoV-2 permissive Huh-7 cells were treated with dCas9 alone or dCas9 along with sgRNAs targeting the promoter region of NRF2 or IRF1. Cells were then infected with SARS-CoV-2 at MOI 0.01 for 24 h before cell lysates were prepared for immunoblotting and cell supernatants harvested for TCID50. (G) Graphic representation of CRISPRa for NRF2-driven genes. (H–J) CRISPRa was used to induce endogenous expression of indicated NRF2-driven genes in SARS-CoV-2 permissive Huh-7 cells. Cells were then infected with SARS-CoV-2 at MOI 0.01 for 8 h before lysates were collected for qPCR or immunoblotting. (H) Displays immunoblots for viral protein NC and loading control VCL. (I) Displays expression levels of NC normalized to VCL expression levels for each tested gene based on densitometric quantification of immunoblots. (J) Displays mean SARS-CoV-2 RNA levels by qPCR normalized to beta actin expression levels for each gene tested from two independent experiments. (K) TCID50 was established from cell supernatants harvested from Huh-7 cells where indicated genes were induced by CRISPRa before infection with SARS-CoV-2 at MOI 0.02 for 8 h. (A–F) Are representative of two independent experiments. Each data point represents one biological replicate with bars indicating mean ± s.e.m. (H–I) represents data from one experiment. (K) Each data point indicates mean of three biological replicates. Bars indicate mean ± s.e.m. of two or three independent experiments. p-values were established using Graphpad Prism 10 using the Student's t -test with “∗” indicating p < 0.05.

Article Snippet: 786-O NRF2-KO and control cells were purchased from ATCC.

Techniques: Control, Infection, Western Blot, CRISPR, Expressing

PDLIM1 knockdown reduces proliferation, clonogenicity, and migration in renal cancer cells in vitro. (A) qPCR validation of siRNA/shRNA‑mediated PDLIM1 knockdown in renal cancer cell lines (786‑O and OSRC-2). (B) CCK‑8 proliferation/viability curves comparing control and PDLIM1‑depleted cells over time. (C-D) Representative images (C) and quantification (D) of wound‑healing assays. (E) Transwell migration assays showing decreased motility/invasiveness after PDLIM1 depletion. (F) Quantification of transwell migration assays. Data are presented as mean ± SEM; statistical significance was determined by two‑sided Student’s t‑test (two groups) or one‑way ANOVA with Tukey’s post hoc test (multiple groups), unless otherwise specified. ns, not significant; * FDR < 0.05; ** FDR < 0.01; *** FDR < 0.001.

Journal: Translational Oncology

Article Title: Integrated spatial and single‑cell transcriptomics maps disulfidptosis in renal cell carcinoma and reveals PDLIM1 as a prognostic biomarker and potential therapeutic target

doi: 10.1016/j.tranon.2026.102765

Figure Lengend Snippet: PDLIM1 knockdown reduces proliferation, clonogenicity, and migration in renal cancer cells in vitro. (A) qPCR validation of siRNA/shRNA‑mediated PDLIM1 knockdown in renal cancer cell lines (786‑O and OSRC-2). (B) CCK‑8 proliferation/viability curves comparing control and PDLIM1‑depleted cells over time. (C-D) Representative images (C) and quantification (D) of wound‑healing assays. (E) Transwell migration assays showing decreased motility/invasiveness after PDLIM1 depletion. (F) Quantification of transwell migration assays. Data are presented as mean ± SEM; statistical significance was determined by two‑sided Student’s t‑test (two groups) or one‑way ANOVA with Tukey’s post hoc test (multiple groups), unless otherwise specified. ns, not significant; * FDR < 0.05; ** FDR < 0.01; *** FDR < 0.001.

Article Snippet: 786O cells and OSRC2 cells were provided by ATCC.

Techniques: Knockdown, Migration, In Vitro, Biomarker Discovery, Control

MUC3A is aberrantly upregulated in ccRCC and associated with poor prognosis. (A) Pan-cancer analysis of MUC3A expression across multiple tumor types based on TCGA data, generated using the GEPIA2 platform. Gene expression values are presented as log2(TPM + 1). (B) Differential expression of MUC3A in tumor and normal samples from the TCGA-KIRC cohort (523 tumor samples vs. 72 normal samples). *P<0.05. (C) Western blotting of MUC3A protein expression in HK-2 and RPTEC/TERT1 non-malignant renal epithelial cell lines and ccRCC cell lines (CAKI-1, OSRC-2, 786-O and ACHN). GAPDH was used as a loading control. (D) Western blotting of MUC3A knockdown efficiency in 786-O and OSRC-2 cells following transient transfection with three independent siRNAs targeting MUC3A. si-2 was selected for subsequent functional experiments due to its superior knockdown efficiency. (E) Kaplan-Meier OS analysis of ccRCC patients stratified into high- and low-MUC3A expression groups using the GEPIA2 platform. (F) Kaplan-Meier DFS analysis of ccRCC patients based on MUC3A expression levels. Data are derived from TCGA unless otherwise indicated. MUC3A, mucin 3A; ccRCC, clear cell renal cell carcinoma; TCGA, The Cancer Genome Atlas; KIRC, kidney renal clear cell carcinoma; GEPIA2, Gene Expression Profiling Interactive Analysis 2; TPM, transcripts per million; KIRC, kidney renal clear cell carcinoma; OS, overall survival; DFS, disease-free survival; siRNA, small interfering RNA; si-MUC3A, MUC3A-targeting siRNA; si-Ctrl, non-targeting control siRNA; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; si-1/si-2/si-3, three independent siRNAs targeting MUC3A.

Journal: Oncology Reports

Article Title: Mechanistic study of MUC3A in promoting progression of clear cell renal cell carcinoma via the JAK-STAT pathway

doi: 10.3892/or.2026.9119

Figure Lengend Snippet: MUC3A is aberrantly upregulated in ccRCC and associated with poor prognosis. (A) Pan-cancer analysis of MUC3A expression across multiple tumor types based on TCGA data, generated using the GEPIA2 platform. Gene expression values are presented as log2(TPM + 1). (B) Differential expression of MUC3A in tumor and normal samples from the TCGA-KIRC cohort (523 tumor samples vs. 72 normal samples). *P<0.05. (C) Western blotting of MUC3A protein expression in HK-2 and RPTEC/TERT1 non-malignant renal epithelial cell lines and ccRCC cell lines (CAKI-1, OSRC-2, 786-O and ACHN). GAPDH was used as a loading control. (D) Western blotting of MUC3A knockdown efficiency in 786-O and OSRC-2 cells following transient transfection with three independent siRNAs targeting MUC3A. si-2 was selected for subsequent functional experiments due to its superior knockdown efficiency. (E) Kaplan-Meier OS analysis of ccRCC patients stratified into high- and low-MUC3A expression groups using the GEPIA2 platform. (F) Kaplan-Meier DFS analysis of ccRCC patients based on MUC3A expression levels. Data are derived from TCGA unless otherwise indicated. MUC3A, mucin 3A; ccRCC, clear cell renal cell carcinoma; TCGA, The Cancer Genome Atlas; KIRC, kidney renal clear cell carcinoma; GEPIA2, Gene Expression Profiling Interactive Analysis 2; TPM, transcripts per million; KIRC, kidney renal clear cell carcinoma; OS, overall survival; DFS, disease-free survival; siRNA, small interfering RNA; si-MUC3A, MUC3A-targeting siRNA; si-Ctrl, non-targeting control siRNA; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; si-1/si-2/si-3, three independent siRNAs targeting MUC3A.

Article Snippet: Human ccRCC cell lines 786-O (cat. no. CL-0010), OSRC-2 (cat. no. CL-0177), Caki-1 (cat. no. CL-0052) and ACHN (cat. no. CL-0021), as well as non-malignant renal epithelial cells HK-2 (cat. no. CL-0109; all from Procell Life Science & Technology Co., Ltd.) and RPTEC/TERT1 (cat. no. CRL-4031; American Type Culture Collection), were used in the present study.

Techniques: Expressing, Generated, Gene Expression, Quantitative Proteomics, Western Blot, Control, Knockdown, Transfection, Functional Assay, Derivative Assay, Small Interfering RNA

MUC3A knockdown suppresses proliferation and promotes apoptosis in ccRCC cells. (A and B) Cell proliferation of 786-O and OSRC-2 cells following transfection with si-MUC3A or si-Ctrl, as assessed by CCK-8 assays at the indicated time points. (C and D) Colony formation assays showing the clonogenic capacity of 786-O and OSRC-2 cells following MUC3A knockdown. Representative images and quantitative analysis are shown. (E and F) Flow cytometric analysis of apoptosis in 786-O and OSRC-2 cells using Annexin V-FITC/PI staining following MUC3A silencing. Representative dot plots and corresponding quantitative results are presented. All experiments were performed with at least three independent biological replicates (n≥3). Data are presented as the mean ± SD. Statistical significance was determined using a two-tailed unpaired Student's t-test. *P<0.05, **P<0.01 and ***P<0.001. MUC3A, mucin 3A; ccRCC, clear cell renal cell carcinoma; CCK-8, Cell Counting Kit-8; si-MUC3A, MUC3A-targeting siRNA; si-Ctrl, non-targeting control siRNA; PI, propidium iodide; SD, standard deviation; ns, not significant.

Journal: Oncology Reports

Article Title: Mechanistic study of MUC3A in promoting progression of clear cell renal cell carcinoma via the JAK-STAT pathway

doi: 10.3892/or.2026.9119

Figure Lengend Snippet: MUC3A knockdown suppresses proliferation and promotes apoptosis in ccRCC cells. (A and B) Cell proliferation of 786-O and OSRC-2 cells following transfection with si-MUC3A or si-Ctrl, as assessed by CCK-8 assays at the indicated time points. (C and D) Colony formation assays showing the clonogenic capacity of 786-O and OSRC-2 cells following MUC3A knockdown. Representative images and quantitative analysis are shown. (E and F) Flow cytometric analysis of apoptosis in 786-O and OSRC-2 cells using Annexin V-FITC/PI staining following MUC3A silencing. Representative dot plots and corresponding quantitative results are presented. All experiments were performed with at least three independent biological replicates (n≥3). Data are presented as the mean ± SD. Statistical significance was determined using a two-tailed unpaired Student's t-test. *P<0.05, **P<0.01 and ***P<0.001. MUC3A, mucin 3A; ccRCC, clear cell renal cell carcinoma; CCK-8, Cell Counting Kit-8; si-MUC3A, MUC3A-targeting siRNA; si-Ctrl, non-targeting control siRNA; PI, propidium iodide; SD, standard deviation; ns, not significant.

Techniques: Knockdown, Transfection, CCK-8 Assay, Staining, Two Tailed Test, Cell Counting, Control, Standard Deviation

MUC3A knockdown inhibits the migration and invasion of ccRCC cells. (A) Transwell migration assays showing the migratory capacity of 786-O and OSRC-2 cells following MUC3A knockdown. Quantitative analysis is shown on the right. (B) Transwell invasion assays performed using Matrigel ® -coated chambers to assess the invasive potential of ccRCC cells after MUC3A silencing. (C) Wound healing assays demonstrating delayed wound closure in 786-O and OSRC-2 cells transfected with si-MUC3A compared with si-Ctrl at 24 h. Representative images and quantitative analyses are shown. Scale bar, 100 µm. All experiments were conducted with at least three independent biological replicates. Data are expressed as the mean ± SD. **P<0.01 and ***P<0.001. MUC3A, mucin 3A; ccRCC, clear cell renal cell carcinoma; si-MUC3A, MUC3A-targeting siRNA; si-Ctrl, non-targeting control siRNA; SD, standard deviation.

Journal: Oncology Reports

Article Title: Mechanistic study of MUC3A in promoting progression of clear cell renal cell carcinoma via the JAK-STAT pathway

doi: 10.3892/or.2026.9119

Figure Lengend Snippet: MUC3A knockdown inhibits the migration and invasion of ccRCC cells. (A) Transwell migration assays showing the migratory capacity of 786-O and OSRC-2 cells following MUC3A knockdown. Quantitative analysis is shown on the right. (B) Transwell invasion assays performed using Matrigel ® -coated chambers to assess the invasive potential of ccRCC cells after MUC3A silencing. (C) Wound healing assays demonstrating delayed wound closure in 786-O and OSRC-2 cells transfected with si-MUC3A compared with si-Ctrl at 24 h. Representative images and quantitative analyses are shown. Scale bar, 100 µm. All experiments were conducted with at least three independent biological replicates. Data are expressed as the mean ± SD. **P<0.01 and ***P<0.001. MUC3A, mucin 3A; ccRCC, clear cell renal cell carcinoma; si-MUC3A, MUC3A-targeting siRNA; si-Ctrl, non-targeting control siRNA; SD, standard deviation.

Techniques: Knockdown, Migration, Transfection, Control, Standard Deviation

MUC3A is associated with the activation of the JAK-STAT signaling pathway in ccRCC. (A) KEGG pathway enrichment analysis of genes associated with MUC3A expression based on TCGA-KIRC transcriptomic data. (B) GSEA showing significant enrichment of the JAK-STAT signaling pathway in ccRCC samples with a high MUC3A expression. (C and D) Western blotting of total and phosphorylated JAK1, JAK2 and STAT3 in 786-O and OSRC-2 cells following MUC3A knockdown. (E) Western blotting showing that STAT3 activation by Colivelin TFA restores p-STAT3 levels in si-MUC3A-transfected 786-O and OSRC-2 cells, accompanied by increased Bcl-2 and decreased cleaved caspase-3 expression. (F) Western blotting of apoptosis-related proteins Bcl-2 and cleaved caspase-3 following MUC3A silencing. GAPDH served as a loading control. All western blotting experiments were repeated independently at least three times. MUC3A, mucin 3A; JAK, Janus kinase; STAT, signal transducer and activator of transcription; ccRCC, clear cell renal cell carcinoma; KEGG, Kyoto Encyclopedia of Genes and Genomes; TCGA, The Cancer Genome Atlas; KIRC, kidney renal clear cell carcinoma; GSEA, gene set enrichment analysis; TFA, trifluoroacetate; p-, phosphorylated.

Journal: Oncology Reports

Article Title: Mechanistic study of MUC3A in promoting progression of clear cell renal cell carcinoma via the JAK-STAT pathway

doi: 10.3892/or.2026.9119

Figure Lengend Snippet: MUC3A is associated with the activation of the JAK-STAT signaling pathway in ccRCC. (A) KEGG pathway enrichment analysis of genes associated with MUC3A expression based on TCGA-KIRC transcriptomic data. (B) GSEA showing significant enrichment of the JAK-STAT signaling pathway in ccRCC samples with a high MUC3A expression. (C and D) Western blotting of total and phosphorylated JAK1, JAK2 and STAT3 in 786-O and OSRC-2 cells following MUC3A knockdown. (E) Western blotting showing that STAT3 activation by Colivelin TFA restores p-STAT3 levels in si-MUC3A-transfected 786-O and OSRC-2 cells, accompanied by increased Bcl-2 and decreased cleaved caspase-3 expression. (F) Western blotting of apoptosis-related proteins Bcl-2 and cleaved caspase-3 following MUC3A silencing. GAPDH served as a loading control. All western blotting experiments were repeated independently at least three times. MUC3A, mucin 3A; JAK, Janus kinase; STAT, signal transducer and activator of transcription; ccRCC, clear cell renal cell carcinoma; KEGG, Kyoto Encyclopedia of Genes and Genomes; TCGA, The Cancer Genome Atlas; KIRC, kidney renal clear cell carcinoma; GSEA, gene set enrichment analysis; TFA, trifluoroacetate; p-, phosphorylated.

Techniques: Activation Assay, Expressing, Western Blot, Knockdown, Transfection, Control

STAT3 activation partially rescues the effects of MUC3A knockdown in ccRCC cells. (A and B) CCK-8 assays showing that treatment with the STAT3 agonist Colivelin TFA partially restored the proliferation of 786-O and OSRC-2 cells following MUC3A knockdown. (C-F) Flow cytometric analysis demonstrating that Colivelin TFA treatment reverses the apoptosis-promoting effect induced by MUC3A silencing in ccRCC cells. Data are presented as the mean ± SD from at least three independent biological replicates. Statistical significance was assessed using Student's t-test or one-way ANOVA as appropriate. *P<0.05, **P<0.01 and ***P<0.001. STAT3, signal transducer and activator of transcription 3; TFA, trifluoroacetate; MUC3A, mucin 3A; CCK-8, Cell Counting Kit-8; si-MUC3A, MUC3A-targeting siRNA; si-Ctrl, non-targeting control siRNA; SD, standard deviation; ANOVA, analysis of variance.

Journal: Oncology Reports

Article Title: Mechanistic study of MUC3A in promoting progression of clear cell renal cell carcinoma via the JAK-STAT pathway

doi: 10.3892/or.2026.9119

Figure Lengend Snippet: STAT3 activation partially rescues the effects of MUC3A knockdown in ccRCC cells. (A and B) CCK-8 assays showing that treatment with the STAT3 agonist Colivelin TFA partially restored the proliferation of 786-O and OSRC-2 cells following MUC3A knockdown. (C-F) Flow cytometric analysis demonstrating that Colivelin TFA treatment reverses the apoptosis-promoting effect induced by MUC3A silencing in ccRCC cells. Data are presented as the mean ± SD from at least three independent biological replicates. Statistical significance was assessed using Student's t-test or one-way ANOVA as appropriate. *P<0.05, **P<0.01 and ***P<0.001. STAT3, signal transducer and activator of transcription 3; TFA, trifluoroacetate; MUC3A, mucin 3A; CCK-8, Cell Counting Kit-8; si-MUC3A, MUC3A-targeting siRNA; si-Ctrl, non-targeting control siRNA; SD, standard deviation; ANOVA, analysis of variance.

Techniques: Activation Assay, Knockdown, CCK-8 Assay, Cell Counting, Control, Standard Deviation

(A) Workflow schematic. Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS) data were processed with standard filtering; proteins were considered candidate interactors when candidate peptides were detected in HIF-2α but not Empty, or the HIF-2α:Empty peptide ratio exceeded 2. A total of n =11 experiments were performed in neuroblastoma SK-N-BE cells at 21% O₂, n =9 at 1% O₂, and n =9 in renal cell carcinoma 786-O cells at 21% O2. ( B ) Venn diagram showing overlap of interactors among the three experimental groups. ( C ) List of shared interactors identified in (B). ( D ) STRING analysis of proximal HIF-2α interactors for each group, displaying high-confidence interactions (score ≥ 0.8). ( E ) Heatmap of log2fold-changes for the 23 common interactors comparing Empty vector vs. HIF-2α overexpression conditions.

Journal: bioRxiv

Article Title: Structural survey of HIF-2α reveals regulation of its subcellular localization and protein interactome

doi: 10.64898/2026.05.04.722697

Figure Lengend Snippet: (A) Workflow schematic. Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS) data were processed with standard filtering; proteins were considered candidate interactors when candidate peptides were detected in HIF-2α but not Empty, or the HIF-2α:Empty peptide ratio exceeded 2. A total of n =11 experiments were performed in neuroblastoma SK-N-BE cells at 21% O₂, n =9 at 1% O₂, and n =9 in renal cell carcinoma 786-O cells at 21% O2. ( B ) Venn diagram showing overlap of interactors among the three experimental groups. ( C ) List of shared interactors identified in (B). ( D ) STRING analysis of proximal HIF-2α interactors for each group, displaying high-confidence interactions (score ≥ 0.8). ( E ) Heatmap of log2fold-changes for the 23 common interactors comparing Empty vector vs. HIF-2α overexpression conditions.

Article Snippet: SK-N-BE( )c, SH-SY5Y, SH-EP, SK-N-SH, SK-N-AS, and 786-O cells were obtained from ATCC; SK-N-BE( ) from DSMZ.

Techniques: Liquid Chromatography, Mass Spectrometry, Liquid Chromatography with Mass Spectroscopy, Plasmid Preparation, Over Expression

(A-C) Dot plots show the top enriched GO terms ranked by significance. Dot size represents number of genes associated with each term, and dot color represents adjusted p-value with Benjamini-Hochberg correction. Only terms meeting significance threshold of p <0.05 were included. GO was performed for biological processes (BP), cellular component (CC), and Molecular function (MF). Neuroblastoma SK-N-BE cells cultured in 1% oxygen (A) or 21% oxygen (B) , and renal cell carcinoma 786-O cells cultured in 21% oxygen (C) .

Journal: bioRxiv

Article Title: Structural survey of HIF-2α reveals regulation of its subcellular localization and protein interactome

doi: 10.64898/2026.05.04.722697

Figure Lengend Snippet: (A-C) Dot plots show the top enriched GO terms ranked by significance. Dot size represents number of genes associated with each term, and dot color represents adjusted p-value with Benjamini-Hochberg correction. Only terms meeting significance threshold of p <0.05 were included. GO was performed for biological processes (BP), cellular component (CC), and Molecular function (MF). Neuroblastoma SK-N-BE cells cultured in 1% oxygen (A) or 21% oxygen (B) , and renal cell carcinoma 786-O cells cultured in 21% oxygen (C) .

Article Snippet: SK-N-BE( )c, SH-SY5Y, SH-EP, SK-N-SH, SK-N-AS, and 786-O cells were obtained from ATCC; SK-N-BE( ) from DSMZ.

Techniques: Cell Culture

(A) STRING analysis of proteins identified as normoxic-specific cell type-independent (proteins listed in ). (B) STRING analysis of proteins identified as oxygen- and cell type-independent (proteins listed in ). (C-D) Gene ontology (GO) enrichment analysis performed for biological processes (BP), cellular component (CC), and Molecular function (MF). Dot plots show the top enriched GO terms ranked by significance. Dot size represents number of genes associated with each term, and dot color represents adjusted p-value with Benjamini-Hochberg correction. Only terms meeting significance threshold of p <0.05 were included. Proteins detected only in neuroblastoma SK-N-BE and renal cell carcinoma 786-O cells cultured in 21% oxygen (C) , and proteins detected only in neuroblastoma SK-N-BE cells cultured in 1% oxygen (D) were analyzed.

Journal: bioRxiv

Article Title: Structural survey of HIF-2α reveals regulation of its subcellular localization and protein interactome

doi: 10.64898/2026.05.04.722697

Figure Lengend Snippet: (A) STRING analysis of proteins identified as normoxic-specific cell type-independent (proteins listed in ). (B) STRING analysis of proteins identified as oxygen- and cell type-independent (proteins listed in ). (C-D) Gene ontology (GO) enrichment analysis performed for biological processes (BP), cellular component (CC), and Molecular function (MF). Dot plots show the top enriched GO terms ranked by significance. Dot size represents number of genes associated with each term, and dot color represents adjusted p-value with Benjamini-Hochberg correction. Only terms meeting significance threshold of p <0.05 were included. Proteins detected only in neuroblastoma SK-N-BE and renal cell carcinoma 786-O cells cultured in 21% oxygen (C) , and proteins detected only in neuroblastoma SK-N-BE cells cultured in 1% oxygen (D) were analyzed.

Article Snippet: SK-N-BE( )c, SH-SY5Y, SH-EP, SK-N-SH, SK-N-AS, and 786-O cells were obtained from ATCC; SK-N-BE( ) from DSMZ.

Techniques: Cell Culture

KAT2B suppressed lipogenesis through FASN (A) Key rate-limiting enzymes in de novo lipogenesis and their expression levels in ccRCC and pRCC using TCGA-KIRC and TCGA-KIRP databases. Red squares and blue squares represented genes whose expression were up-regulated or down-regulated in tumors. (B) Schematic diagram for screening key lipid synthesis factors downstream of KAT2B. (C) Statistical analysis of oil red O stainging in 786O cells following knockdown of 10 key lipogenesis factors (n = 3). (D-E) Representative IHC staining for FASN in RCC cohort and statistical analysis (n = 80, paired t‐test). (F-G) After KAT2B knockdown in 786O and ACHN cells, the mRNA and protein expression of FASN was observed. (H) The cell growth curves of A498 and Caki-1 cells with KAT2B and/or FASN overexpression were determined by CCK8 assays (n = 4, independent‐samples t‐test). (I) The relative TG levels in A498 and Caki-1 cells with KAT2B and/or FASN overexpression (n = 4, independent‐samples t‐test). (J) Representative images of oil red O staining of A498 and Caki-1 cells with KAT2B and/or FASN overexpression and statistical analysis (n = 3, independent‐samples t‐test). Data were analyzed by unpaired t test (G), paired t test (E), one-way ANOVA (H, I, J) or two-way ANOVA (C).

Journal: Journal of Advanced Research

Article Title: Epigenetically silenced KAT2B suppresses de novo lipogenesis through destroying HDAC5/LSD1 complex assembly in renal cell carcinoma

doi: 10.1016/j.jare.2025.08.007

Figure Lengend Snippet: KAT2B suppressed lipogenesis through FASN (A) Key rate-limiting enzymes in de novo lipogenesis and their expression levels in ccRCC and pRCC using TCGA-KIRC and TCGA-KIRP databases. Red squares and blue squares represented genes whose expression were up-regulated or down-regulated in tumors. (B) Schematic diagram for screening key lipid synthesis factors downstream of KAT2B. (C) Statistical analysis of oil red O stainging in 786O cells following knockdown of 10 key lipogenesis factors (n = 3). (D-E) Representative IHC staining for FASN in RCC cohort and statistical analysis (n = 80, paired t‐test). (F-G) After KAT2B knockdown in 786O and ACHN cells, the mRNA and protein expression of FASN was observed. (H) The cell growth curves of A498 and Caki-1 cells with KAT2B and/or FASN overexpression were determined by CCK8 assays (n = 4, independent‐samples t‐test). (I) The relative TG levels in A498 and Caki-1 cells with KAT2B and/or FASN overexpression (n = 4, independent‐samples t‐test). (J) Representative images of oil red O staining of A498 and Caki-1 cells with KAT2B and/or FASN overexpression and statistical analysis (n = 3, independent‐samples t‐test). Data were analyzed by unpaired t test (G), paired t test (E), one-way ANOVA (H, I, J) or two-way ANOVA (C).

Article Snippet: The HK‐2, 293 T, A549, PC9, T47D, MCF7, A498, Caki-1, OSRC-2, 786O, 769P and ACHN cell lines were obtained from the American Type Culture Collection (ATCC, USA) and were cultivated under proper conditions according to the manufacturer’s protocols.

Techniques: Expressing, Knockdown, Immunohistochemistry, Over Expression, Staining

Hypermethylation but not VHL/HIF axis resulted in low expression of KAT2B in RCC Expression levels of HIF2a and KAT2B after hypoxia in RCC cells. (B) Expression level of KAT2B after overexpressing HIF2a in Caki-1 cells. (C) Expression level of KAT2B after overexpressing VHL in A498 cells. (D) RNA stability experiment of KAT2B in RCC and HK2 cells after treated with 20 μg/ml cycloheximide (CHX) for 0 h, 1 h, 2 h, 3 h, and 4 h and statistical diagram. (E-F) Prediction analysis of CpG islands in the sequence range of 3500 bp upstream from the transcriptional start site in the KAT2B promoter region ( http://www.urogene.org/ ). (G-H) The promoter methylation level of KAT2B in ccRCC using online database UCSC Xena ( http://xena.ucsc.edu/ ) and UALCAN ( http://ualcan.path.uab.edu/ ). (I) Scatter plot of the relationship among KAT2B expression and its promoter methylation level. (J) Representative MSP results of KAT2B methylation status in 5 paired adjacent tissues (N) and RCC tissues (T). (K-L) The mRNA and protein levels of KAT2B in RCC cell lines after 5-AZA treatment (n = 3). (M) Scatter plot of the relationship among KAT2B expression and TET1, TET2, and TET3 expression. (N) The KAT2B mRNA expression after knockdown of TET1, TET2, or TET3 in 786O cells. (O) The KAT2B protein expression after TET1 knockdown in RCC cells. Data were analyzed by one-way ANOVA (K,N) or two-way ANOVA (D).

Journal: Journal of Advanced Research

Article Title: Epigenetically silenced KAT2B suppresses de novo lipogenesis through destroying HDAC5/LSD1 complex assembly in renal cell carcinoma

doi: 10.1016/j.jare.2025.08.007

Figure Lengend Snippet: Hypermethylation but not VHL/HIF axis resulted in low expression of KAT2B in RCC Expression levels of HIF2a and KAT2B after hypoxia in RCC cells. (B) Expression level of KAT2B after overexpressing HIF2a in Caki-1 cells. (C) Expression level of KAT2B after overexpressing VHL in A498 cells. (D) RNA stability experiment of KAT2B in RCC and HK2 cells after treated with 20 μg/ml cycloheximide (CHX) for 0 h, 1 h, 2 h, 3 h, and 4 h and statistical diagram. (E-F) Prediction analysis of CpG islands in the sequence range of 3500 bp upstream from the transcriptional start site in the KAT2B promoter region ( http://www.urogene.org/ ). (G-H) The promoter methylation level of KAT2B in ccRCC using online database UCSC Xena ( http://xena.ucsc.edu/ ) and UALCAN ( http://ualcan.path.uab.edu/ ). (I) Scatter plot of the relationship among KAT2B expression and its promoter methylation level. (J) Representative MSP results of KAT2B methylation status in 5 paired adjacent tissues (N) and RCC tissues (T). (K-L) The mRNA and protein levels of KAT2B in RCC cell lines after 5-AZA treatment (n = 3). (M) Scatter plot of the relationship among KAT2B expression and TET1, TET2, and TET3 expression. (N) The KAT2B mRNA expression after knockdown of TET1, TET2, or TET3 in 786O cells. (O) The KAT2B protein expression after TET1 knockdown in RCC cells. Data were analyzed by one-way ANOVA (K,N) or two-way ANOVA (D).

Techniques: Expressing, Sequencing, Methylation, Knockdown

Therapeutic targeting of KAT2B-low RCC with a FASN inhibitor (A-B) Representative images of IHC staining of FASN in RCC cohort and statistical analysis. (C) Representative images of IHC staining for FASN and KAT2B in RCC tissues with high and low KAT2B expression. (D) Scatter plot of the relationship among KAT2B expression and FASN expression in advanced RCC tumors (n = 53). (E) The cell viability of ACHN and Caki-1 cells after treated with TVB-2640 (n = 4). (F) The cell viability of 786O and 769P cells after treated with TVB-2640 (n = 10). Proteins from three independent sites in RCC tissues were extracted to detect KAT2B expression. (H) Representative images of Caki-1 and ACHN organoids after treatment with TVB-2640 (7.5 μM). 15 organoids were randomly selected from each group for statistical analysis. (I) Representative images of Caki-1 and ACHN organoids after treatment with TVB-2640 (7.5 μM) (n = 15). (J) Representative images of two PDOs with different KAT2B expression after treatment with TVB-2640 (n = 10). (K) Representative images of PRO-1 staining of PDOs. (L-M) The cell viability of ACHN cells (L) and case 1 primary RCC cells (M) with KAT2B knockdown after treated with TVB-2640 (n = 4). (N-O) The picture (N) of xenograft using 786O cells with KAT2B knockdown after treated with TVB-2640, and tumor growth curve (n = 4). Data were analyzed by unpaired t test (B, H, I, J), one-way ANOVA (O) or two-way ANOVA (E, F, G, L, M).

Journal: Journal of Advanced Research

Article Title: Epigenetically silenced KAT2B suppresses de novo lipogenesis through destroying HDAC5/LSD1 complex assembly in renal cell carcinoma

doi: 10.1016/j.jare.2025.08.007

Figure Lengend Snippet: Therapeutic targeting of KAT2B-low RCC with a FASN inhibitor (A-B) Representative images of IHC staining of FASN in RCC cohort and statistical analysis. (C) Representative images of IHC staining for FASN and KAT2B in RCC tissues with high and low KAT2B expression. (D) Scatter plot of the relationship among KAT2B expression and FASN expression in advanced RCC tumors (n = 53). (E) The cell viability of ACHN and Caki-1 cells after treated with TVB-2640 (n = 4). (F) The cell viability of 786O and 769P cells after treated with TVB-2640 (n = 10). Proteins from three independent sites in RCC tissues were extracted to detect KAT2B expression. (H) Representative images of Caki-1 and ACHN organoids after treatment with TVB-2640 (7.5 μM). 15 organoids were randomly selected from each group for statistical analysis. (I) Representative images of Caki-1 and ACHN organoids after treatment with TVB-2640 (7.5 μM) (n = 15). (J) Representative images of two PDOs with different KAT2B expression after treatment with TVB-2640 (n = 10). (K) Representative images of PRO-1 staining of PDOs. (L-M) The cell viability of ACHN cells (L) and case 1 primary RCC cells (M) with KAT2B knockdown after treated with TVB-2640 (n = 4). (N-O) The picture (N) of xenograft using 786O cells with KAT2B knockdown after treated with TVB-2640, and tumor growth curve (n = 4). Data were analyzed by unpaired t test (B, H, I, J), one-way ANOVA (O) or two-way ANOVA (E, F, G, L, M).

Techniques: Immunohistochemistry, Expressing, Staining, Knockdown

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