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Korean Cell Line Bank human cancer cell lines huh7

(A) Apoptosis was analyzed by Annexin V and propidium iodide (PI) staining in B7-H3–knockdown <t>Huh7</t> cells. (B) Quantification of apoptotic Huh7 cells shown in (A). (C) Expression of apoptosis-related proteins in control and B7-H3–knockdown Huh7 cells was analyzed by Western blotting and quantified using ImageJ software. (D) Apoptosis analysis by Annexin V/PI staining in B7-H3–knockdown HepG2 cells. (E) Quantification of apoptotic HepG2 cells shown in (D).

Human Cancer Cell Lines Huh7, supplied by Korean Cell Line Bank, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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human cancer cell lines huh7 - by Bioz Stars, 2026-06

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1) Product Images from "B7-H3 Modulates Cell Adhesion and Immune Evasion to Promote Tumor Progression and Natural Killer Cell Resistance in Hepatocellular Carcinoma"

Article Title: B7-H3 Modulates Cell Adhesion and Immune Evasion to Promote Tumor Progression and Natural Killer Cell Resistance in Hepatocellular Carcinoma

Journal: bioRxiv

doi: 10.64898/2026.03.28.714951

(A) Apoptosis was analyzed by Annexin V and propidium iodide (PI) staining in B7-H3–knockdown Huh7 cells. (B) Quantification of apoptotic Huh7 cells shown in (A). (C) Expression of apoptosis-related proteins in control and B7-H3–knockdown Huh7 cells was analyzed by Western blotting and quantified using ImageJ software. (D) Apoptosis analysis by Annexin V/PI staining in B7-H3–knockdown HepG2 cells. (E) Quantification of apoptotic HepG2 cells shown in (D).

Figure Legend Snippet: (A) Apoptosis was analyzed by Annexin V and propidium iodide (PI) staining in B7-H3–knockdown Huh7 cells. (B) Quantification of apoptotic Huh7 cells shown in (A). (C) Expression of apoptosis-related proteins in control and B7-H3–knockdown Huh7 cells was analyzed by Western blotting and quantified using ImageJ software. (D) Apoptosis analysis by Annexin V/PI staining in B7-H3–knockdown HepG2 cells. (E) Quantification of apoptotic HepG2 cells shown in (D).

Techniques Used: Staining, Knockdown, Expressing, Control, Western Blot, Software

(A, C) Cell adhesion assays of B7-H3–knockdown Huh7 (A) and HepG2 (C) cells on gelatin-coated plates. Adherent cells were visualized by crystal violet staining. (B, D) Quantification of cell adhesion shown in (A) and (C), respectively. Data are presented as relative adhesion (%) compared with control siRNA (siCon)–transfected cells. (E, G) Flow cytometric analysis of cell adhesion molecule expression in B7-H3–knockdown Huh7 (E) and HepG2 (G) cells. (F, H) Quantification of mean fluorescence intensity (MFI) shown in (E) and (G), respectively, expressed as relative MFI (%) compared with siCon cells. *, p < 0.05; **, p < 0.01; ***, p < 0.005.

Figure Legend Snippet: (A, C) Cell adhesion assays of B7-H3–knockdown Huh7 (A) and HepG2 (C) cells on gelatin-coated plates. Adherent cells were visualized by crystal violet staining. (B, D) Quantification of cell adhesion shown in (A) and (C), respectively. Data are presented as relative adhesion (%) compared with control siRNA (siCon)–transfected cells. (E, G) Flow cytometric analysis of cell adhesion molecule expression in B7-H3–knockdown Huh7 (E) and HepG2 (G) cells. (F, H) Quantification of mean fluorescence intensity (MFI) shown in (E) and (G), respectively, expressed as relative MFI (%) compared with siCon cells. *, p < 0.05; **, p < 0.01; ***, p < 0.005.

Techniques Used: Knockdown, Staining, Control, Transfection, Expressing, Fluorescence

(A, C) Flow cytometric analysis of PD-L1, PD-L2, CD47, and CD24 expression in B7-H3–knockdown Huh7 (A) and HepG2 (C) cells. (B, D) Quantification of immune checkpoint molecule expression shown in (A) and (C), respectively.

Figure Legend Snippet: (A, C) Flow cytometric analysis of PD-L1, PD-L2, CD47, and CD24 expression in B7-H3–knockdown Huh7 (A) and HepG2 (C) cells. (B, D) Quantification of immune checkpoint molecule expression shown in (A) and (C), respectively.

Techniques Used: Expressing, Knockdown

(A, B) Western blot analysis of Akt1/2/3, ERK1/2, FAK, MVP, and S6 in B7-H3–knockdown Huh7 and HepG2 cells. Protein levels were quantified using ImageJ software with β-actin as a loading control. (C) Western blot analysis of Akt1/2/3, ERK1/2, and MVP in control and B7-H3 KO SNU449 cells. (D) Western blot analysis of FAK and Src in control and B7-H3 KO SNU449 cells. (E) Western blot analysis of JAK2 and STAT3 in control and B7-H3 KO SNU449 cells. For (C–E), GAPDH was used as a loading control.

Figure Legend Snippet: (A, B) Western blot analysis of Akt1/2/3, ERK1/2, FAK, MVP, and S6 in B7-H3–knockdown Huh7 and HepG2 cells. Protein levels were quantified using ImageJ software with β-actin as a loading control. (C) Western blot analysis of Akt1/2/3, ERK1/2, and MVP in control and B7-H3 KO SNU449 cells. (D) Western blot analysis of FAK and Src in control and B7-H3 KO SNU449 cells. (E) Western blot analysis of JAK2 and STAT3 in control and B7-H3 KO SNU449 cells. For (C–E), GAPDH was used as a loading control.

Techniques Used: Western Blot, Knockdown, Software, Control

Image Search Results

Journal: bioRxiv

Article Title: B7-H3 Modulates Cell Adhesion and Immune Evasion to Promote Tumor Progression and Natural Killer Cell Resistance in Hepatocellular Carcinoma

doi: 10.64898/2026.03.28.714951

Figure Lengend Snippet: (A) Apoptosis was analyzed by Annexin V and propidium iodide (PI) staining in B7-H3–knockdown Huh7 cells. (B) Quantification of apoptotic Huh7 cells shown in (A). (C) Expression of apoptosis-related proteins in control and B7-H3–knockdown Huh7 cells was analyzed by Western blotting and quantified using ImageJ software. (D) Apoptosis analysis by Annexin V/PI staining in B7-H3–knockdown HepG2 cells. (E) Quantification of apoptotic HepG2 cells shown in (D).

Article Snippet: Human cancer cell lines Huh7 and SNU449 were purchased from the Korean Cell Line Bank (KCLB, Seoul, Korea) and cultured in RPMI-1640 (Biowest, Kansas, MO, USA) medium supplemented with 10% fetal bovine serum (FBS, Corning, Seoul, Korea) and antibiotic-antimycotic solution (AA, Biowest).

Techniques: Staining, Knockdown, Expressing, Control, Western Blot, Software

Journal: bioRxiv

Article Title: B7-H3 Modulates Cell Adhesion and Immune Evasion to Promote Tumor Progression and Natural Killer Cell Resistance in Hepatocellular Carcinoma

doi: 10.64898/2026.03.28.714951

Figure Lengend Snippet: (A, C) Cell adhesion assays of B7-H3–knockdown Huh7 (A) and HepG2 (C) cells on gelatin-coated plates. Adherent cells were visualized by crystal violet staining. (B, D) Quantification of cell adhesion shown in (A) and (C), respectively. Data are presented as relative adhesion (%) compared with control siRNA (siCon)–transfected cells. (E, G) Flow cytometric analysis of cell adhesion molecule expression in B7-H3–knockdown Huh7 (E) and HepG2 (G) cells. (F, H) Quantification of mean fluorescence intensity (MFI) shown in (E) and (G), respectively, expressed as relative MFI (%) compared with siCon cells. *, p < 0.05; **, p < 0.01; ***, p < 0.005.

Techniques: Knockdown, Staining, Control, Transfection, Expressing, Fluorescence

Journal: bioRxiv

Article Title: B7-H3 Modulates Cell Adhesion and Immune Evasion to Promote Tumor Progression and Natural Killer Cell Resistance in Hepatocellular Carcinoma

doi: 10.64898/2026.03.28.714951

Figure Lengend Snippet: (A, C) Flow cytometric analysis of PD-L1, PD-L2, CD47, and CD24 expression in B7-H3–knockdown Huh7 (A) and HepG2 (C) cells. (B, D) Quantification of immune checkpoint molecule expression shown in (A) and (C), respectively.

Techniques: Expressing, Knockdown

Journal: bioRxiv

Article Title: B7-H3 Modulates Cell Adhesion and Immune Evasion to Promote Tumor Progression and Natural Killer Cell Resistance in Hepatocellular Carcinoma

doi: 10.64898/2026.03.28.714951

Figure Lengend Snippet: (A, B) Western blot analysis of Akt1/2/3, ERK1/2, FAK, MVP, and S6 in B7-H3–knockdown Huh7 and HepG2 cells. Protein levels were quantified using ImageJ software with β-actin as a loading control. (C) Western blot analysis of Akt1/2/3, ERK1/2, and MVP in control and B7-H3 KO SNU449 cells. (D) Western blot analysis of FAK and Src in control and B7-H3 KO SNU449 cells. (E) Western blot analysis of JAK2 and STAT3 in control and B7-H3 KO SNU449 cells. For (C–E), GAPDH was used as a loading control.

Techniques: Western Blot, Knockdown, Software, Control

G1 upregulates GPER1 protein expression, improves hepatic lipid deposition, reduces reactive oxygen species (ROS) production, and decreases hepatocyte apoptosis in vitro . (A) CCK8 assay was performed to assess the viability of HepG2 cells treated with varying concentrations of G1. (B) Western blot detection of GPER1 protein expression at different G1 concentrations. The relative intensities of proteins were normalized to β-actin. (C,D) Representative immunofluorescence staining images show GPER1 expression in FFA (1 mM)-induced HepG2 and Huh7 cells treated with G1 (1 µM). Quantitative data represent the mean fluorescence intensity ±SEM of multiple fields from three independent experiments. Scale bar, 20 μm. (E,F) Representative Oil Red O-stained images and quantitative analysis of the lipid droplet accumulation in HepG2 and Huh7 cells following FFA (1 mM) induction and subsequent treatment with various concentrations of G1. Scale bar, 50 µm. (G,H) TG levels in HepG2 and Huh7 cells were measured after FFA (1 mM) induction and treatment with G1. (I,J) TC levels in HepG2 and Huh7 cells were measured after FFA (1 mM) induction and treatment with G1 (1uM). (K) The relative mRNA expression of genes related to fatty acid synthesis, transport, cholesterol synthesis, and cholesterol transport in HepG2 cells induced by FFA (1 mM) and then treated with G1 (1 µM). (L) ROS levels measured by flow cytometry in HepG2 cells. Cells were loaded with the fluorescent probe DCFH-DA. (M) Flow cytometry analysis of apoptosis in HepG2 cells. Cells were stained with Annexin V-FITC and PI. Lower left quadrant: viable cells; upper left quadrant: necrotic cells; lower right quadrant: early apoptotic cells; upper right quadrant: late apoptotic cells. Data are presented as the mean ± SEM of three biologically independent experiments (n = 3). Statistical analyses were performed using one-way ANOVA with post hoc multiple comparisons by Dunnett’s method. Compared with the FFA group, * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001. Compared to treatment without G1 for 10 h, # P < 0.05, ## P < 0.01, ns indicates no statistical significance.

Journal: Frontiers in Pharmacology

Article Title: GPER1 as a therapeutic target in MASLD: evidence for steatosis attenuation by agonist G1 in preclinical models

doi: 10.3389/fphar.2026.1764287

Figure Lengend Snippet: G1 upregulates GPER1 protein expression, improves hepatic lipid deposition, reduces reactive oxygen species (ROS) production, and decreases hepatocyte apoptosis in vitro . (A) CCK8 assay was performed to assess the viability of HepG2 cells treated with varying concentrations of G1. (B) Western blot detection of GPER1 protein expression at different G1 concentrations. The relative intensities of proteins were normalized to β-actin. (C,D) Representative immunofluorescence staining images show GPER1 expression in FFA (1 mM)-induced HepG2 and Huh7 cells treated with G1 (1 µM). Quantitative data represent the mean fluorescence intensity ±SEM of multiple fields from three independent experiments. Scale bar, 20 μm. (E,F) Representative Oil Red O-stained images and quantitative analysis of the lipid droplet accumulation in HepG2 and Huh7 cells following FFA (1 mM) induction and subsequent treatment with various concentrations of G1. Scale bar, 50 µm. (G,H) TG levels in HepG2 and Huh7 cells were measured after FFA (1 mM) induction and treatment with G1. (I,J) TC levels in HepG2 and Huh7 cells were measured after FFA (1 mM) induction and treatment with G1 (1uM). (K) The relative mRNA expression of genes related to fatty acid synthesis, transport, cholesterol synthesis, and cholesterol transport in HepG2 cells induced by FFA (1 mM) and then treated with G1 (1 µM). (L) ROS levels measured by flow cytometry in HepG2 cells. Cells were loaded with the fluorescent probe DCFH-DA. (M) Flow cytometry analysis of apoptosis in HepG2 cells. Cells were stained with Annexin V-FITC and PI. Lower left quadrant: viable cells; upper left quadrant: necrotic cells; lower right quadrant: early apoptotic cells; upper right quadrant: late apoptotic cells. Data are presented as the mean ± SEM of three biologically independent experiments (n = 3). Statistical analyses were performed using one-way ANOVA with post hoc multiple comparisons by Dunnett’s method. Compared with the FFA group, * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001. Compared to treatment without G1 for 10 h, # P < 0.05, ## P < 0.01, ns indicates no statistical significance.

Article Snippet: The HepG2 and Huh7 cell lines were kindly provided by Procell Life Science & Technology Co., Ltd. (Wuhan, China).

Techniques: Expressing, In Vitro, CCK-8 Assay, Western Blot, Immunofluorescence, Staining, Fluorescence, Flow Cytometry

G15 downregulates GPER1 protein expression, exacerbates hepatic lipid accumulation, promotes ROS production, and accelerates hepatocyte apoptosis in vitro . (A) CCK8 assay was performed to assess the viability of HepG2 cells treated with varying concentrations of G15. (B,C) Western blot and RT-qPCR detection of GPER1 after the treatment of G15 (1 µM). (D,E) Representative immunofluorescence staining images and quantitative analysis of GPER1 expression in FFA (1 mM)-induced HepG2 and Huh7 cells treated with G15 (1 µM). Quantitative data represent the mean fluorescence intensity ±SEM of multiple fields from three independent experiments. Scale bar, 20 μm. (F,G) TG and TC levels in HepG2 and Huh7 cells were measured after FFA (1 mM) induction and treatment with G15 (1uM). (H–J) Representative Oil Red O-stained images and quantitative analysis of the lipid droplet accumulation in HepG2 and Huh7 cells following FFA (1 mM) induction and subsequent treatment with various concentrations of G15. Scale bar, 50 µm. (K) The relative mRNA expression of genes related to fatty acid synthesis, transport, and cholesterol synthesis in HepG2 cells induced by FFA (1 mM) and then treated with G15 (1 µM). (L) Western blot analysis was used to assess the effects of G1 and G15 on fatty acid synthesis and fatty acid oxidation-related protein expression in FFA-induced HepG2 cells. (M) ROS levels measured by flow cytometry in HepG2 cells. Cells were loaded with the fluorescent probe DCFH-DA. (N) Flow cytometry analysis of apoptosis in HepG2 cells. Cells were stained with Annexin V-FITC and PI. Lower left quadrant: viable cells; upper left quadrant: necrotic cells; lower right quadrant: early apoptotic cells; upper right quadrant: late apoptotic cells. Data are presented as the mean ± SEM of three biologically independent experiments (n = 3). Statistical analyses were performed using one-way ANOVA with post hoc multiple comparisons by Dunnett’s method. Compared with the FFA group, * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001. Compared to treatment without G1 for 10 h, # P < 0.05, ### P < 0.001, ns indicates no statistical significance.

Journal: Frontiers in Pharmacology

Article Title: GPER1 as a therapeutic target in MASLD: evidence for steatosis attenuation by agonist G1 in preclinical models

doi: 10.3389/fphar.2026.1764287

Figure Lengend Snippet: G15 downregulates GPER1 protein expression, exacerbates hepatic lipid accumulation, promotes ROS production, and accelerates hepatocyte apoptosis in vitro . (A) CCK8 assay was performed to assess the viability of HepG2 cells treated with varying concentrations of G15. (B,C) Western blot and RT-qPCR detection of GPER1 after the treatment of G15 (1 µM). (D,E) Representative immunofluorescence staining images and quantitative analysis of GPER1 expression in FFA (1 mM)-induced HepG2 and Huh7 cells treated with G15 (1 µM). Quantitative data represent the mean fluorescence intensity ±SEM of multiple fields from three independent experiments. Scale bar, 20 μm. (F,G) TG and TC levels in HepG2 and Huh7 cells were measured after FFA (1 mM) induction and treatment with G15 (1uM). (H–J) Representative Oil Red O-stained images and quantitative analysis of the lipid droplet accumulation in HepG2 and Huh7 cells following FFA (1 mM) induction and subsequent treatment with various concentrations of G15. Scale bar, 50 µm. (K) The relative mRNA expression of genes related to fatty acid synthesis, transport, and cholesterol synthesis in HepG2 cells induced by FFA (1 mM) and then treated with G15 (1 µM). (L) Western blot analysis was used to assess the effects of G1 and G15 on fatty acid synthesis and fatty acid oxidation-related protein expression in FFA-induced HepG2 cells. (M) ROS levels measured by flow cytometry in HepG2 cells. Cells were loaded with the fluorescent probe DCFH-DA. (N) Flow cytometry analysis of apoptosis in HepG2 cells. Cells were stained with Annexin V-FITC and PI. Lower left quadrant: viable cells; upper left quadrant: necrotic cells; lower right quadrant: early apoptotic cells; upper right quadrant: late apoptotic cells. Data are presented as the mean ± SEM of three biologically independent experiments (n = 3). Statistical analyses were performed using one-way ANOVA with post hoc multiple comparisons by Dunnett’s method. Compared with the FFA group, * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001. Compared to treatment without G1 for 10 h, # P < 0.05, ### P < 0.001, ns indicates no statistical significance.

Article Snippet: The HepG2 and Huh7 cell lines were kindly provided by Procell Life Science & Technology Co., Ltd. (Wuhan, China).

Techniques: Expressing, In Vitro, CCK-8 Assay, Western Blot, Quantitative RT-PCR, Immunofluorescence, Staining, Fluorescence, Flow Cytometry

Validation of SAE1 as a cancer-enriched prognostic biomarker (A) Expression patterns of the SUMOylation pathway genes among three HCC cell lines (Huh7, MHCC97L, and HCCLM3) with varying metastatic potential, as determined by microarray analysis. The left panel displays expression of genes, while the right panel illustrates correlations of gene expressions with metastatic potential using Pearson’s correlation coefficient ( r ). The coefficients are presented in the right panel if r exceeds 0.9 or falls below −0.9. (B-G) Kaplan-Meier analysis of SAE1 mRNA expression and its association with overall survival (OS) in various pan-cancers. The plot marks representative tumor types (sample number >20) in pan-cancers as follows: (B) LIHC (liver hepatocellular carcinoma) for C26, (C) SKCM (skin cutaneous melanoma)/UVM (uveal melanoma) for C15, (D) ACC (adrenocortical carcinoma)/KICH (kidney chromophobe) for C9, (E) BLCA (bladder urothelial carcinoma)/CESC (cervical squamous cell carcinoma and endocervical adenocarcinoma)/HNSC (head and neck squamous cell carcinoma)/LUSC (lung squamous cell carcinoma) for C27, (F) OV (ovarian cancer) for C6, and (G) CESC (uterine corpus endometrial carcinoma) for C8. (H) Upset diagram demonstrating intersections of driver genes across six pan-cancer subtypes. The top panel presents counts of driver genes shared by each intersection, while the left panel corresponds to the total number of driver genes in each pan-cancer. Gray dots denote the absence of a corresponding intersection, while colored dots show sets participating in the intersection. Yellow, green, red, and black dots represent driver genes shared by six, four, three, and fewer than three pan-cancers, respectively. (I-N) Association of SAE1 mRNA expression levels with mutations in the six significantly driver genes identified in H. Significant correlations between SAE1 expression levels and driver gene mutations are displayed. The black line denotes a patient with having protein sequence-altering mutations, while the white line represents a patient without these mutations (*: P < 0.05, **: P < 1e-3, and ***: P < 1e-6). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Journal: Journal of Advanced Research

Article Title: SAE1 emerges as a pan-cancer driver and key regulator of HCC metastasis

doi: 10.1016/j.jare.2025.06.028

Figure Lengend Snippet: Validation of SAE1 as a cancer-enriched prognostic biomarker (A) Expression patterns of the SUMOylation pathway genes among three HCC cell lines (Huh7, MHCC97L, and HCCLM3) with varying metastatic potential, as determined by microarray analysis. The left panel displays expression of genes, while the right panel illustrates correlations of gene expressions with metastatic potential using Pearson’s correlation coefficient ( r ). The coefficients are presented in the right panel if r exceeds 0.9 or falls below −0.9. (B-G) Kaplan-Meier analysis of SAE1 mRNA expression and its association with overall survival (OS) in various pan-cancers. The plot marks representative tumor types (sample number >20) in pan-cancers as follows: (B) LIHC (liver hepatocellular carcinoma) for C26, (C) SKCM (skin cutaneous melanoma)/UVM (uveal melanoma) for C15, (D) ACC (adrenocortical carcinoma)/KICH (kidney chromophobe) for C9, (E) BLCA (bladder urothelial carcinoma)/CESC (cervical squamous cell carcinoma and endocervical adenocarcinoma)/HNSC (head and neck squamous cell carcinoma)/LUSC (lung squamous cell carcinoma) for C27, (F) OV (ovarian cancer) for C6, and (G) CESC (uterine corpus endometrial carcinoma) for C8. (H) Upset diagram demonstrating intersections of driver genes across six pan-cancer subtypes. The top panel presents counts of driver genes shared by each intersection, while the left panel corresponds to the total number of driver genes in each pan-cancer. Gray dots denote the absence of a corresponding intersection, while colored dots show sets participating in the intersection. Yellow, green, red, and black dots represent driver genes shared by six, four, three, and fewer than three pan-cancers, respectively. (I-N) Association of SAE1 mRNA expression levels with mutations in the six significantly driver genes identified in H. Significant correlations between SAE1 expression levels and driver gene mutations are displayed. The black line denotes a patient with having protein sequence-altering mutations, while the white line represents a patient without these mutations (*: P < 0.05, **: P < 1e-3, and ***: P < 1e-6). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: The Huh7 cell line was obtained from the Japanese Collection of Research Biosources.

Techniques: Biomarker Discovery, Expressing, Microarray, Sequencing

SAE1 enhances YY1 stability in HCC cells (A) Western blot analysis of YY1 expression levels in SAE1-overexpressing PLC and Huh7 cells. (B) SAE1-overexpressing PLC cells and respective controls were treated with 10 μg/ml of CHX at indicated time points. Western blots show YY1 expression levels over time (upper panel), with a line graph indicating relative intensity of YY1 versus GAPDH (below panel). (C) SAE1-overexpressing PLC cells and their controls were transfected with Flag-SUMO-1 plasmid. Cell lysates were then precipitated with anti-Flag antibody, followed by western blotting with anti-YY1 antibody. (D) Detection of YY1 SUMOylation by SUMO-1 and UBC9 via western blot analysis. PLC cells were co-transfected with indicated plasmids. (E) SAE1-overexpressing Huh7 cells and their controls were transfected with HA-Ubi plasmid. Cell lysates were precipitated with anti-HA antibody, followed by western blotting with anti-YY1 antibody. Ubiquitinated YY1 bands are marked. (F) Cell lysates were precipitated with anti-acetyl-histone H3 antibody, followed by western blotting with anti-YY1 and anti-acetyl-histone H3 antibodies. (G) Cell lysates were precipitated with anti-YY1 antibody, followed by western blotting with anti-YY1 and anti-acetyl-histone H3 antibodies.

Journal: Journal of Advanced Research

Article Title: SAE1 emerges as a pan-cancer driver and key regulator of HCC metastasis

doi: 10.1016/j.jare.2025.06.028

Figure Lengend Snippet: SAE1 enhances YY1 stability in HCC cells (A) Western blot analysis of YY1 expression levels in SAE1-overexpressing PLC and Huh7 cells. (B) SAE1-overexpressing PLC cells and respective controls were treated with 10 μg/ml of CHX at indicated time points. Western blots show YY1 expression levels over time (upper panel), with a line graph indicating relative intensity of YY1 versus GAPDH (below panel). (C) SAE1-overexpressing PLC cells and their controls were transfected with Flag-SUMO-1 plasmid. Cell lysates were then precipitated with anti-Flag antibody, followed by western blotting with anti-YY1 antibody. (D) Detection of YY1 SUMOylation by SUMO-1 and UBC9 via western blot analysis. PLC cells were co-transfected with indicated plasmids. (E) SAE1-overexpressing Huh7 cells and their controls were transfected with HA-Ubi plasmid. Cell lysates were precipitated with anti-HA antibody, followed by western blotting with anti-YY1 antibody. Ubiquitinated YY1 bands are marked. (F) Cell lysates were precipitated with anti-acetyl-histone H3 antibody, followed by western blotting with anti-YY1 and anti-acetyl-histone H3 antibodies. (G) Cell lysates were precipitated with anti-YY1 antibody, followed by western blotting with anti-YY1 and anti-acetyl-histone H3 antibodies.

Article Snippet: The Huh7 cell line was obtained from the Japanese Collection of Research Biosources.

Techniques: Western Blot, Expressing, Transfection, Plasmid Preparation

SAE1-mediated upregulation of Wnt3a expression (A) Overview of the strategy used to identify genes co-regulated by SAE1 and YY1. (B) Venn diagram illustrating the numbers of overlapped pathways enriched by GSEA analysis. This analysis stems from comparing RNA-seq data between SAE1-knockdown HCCLM3 cells or YY1-knockdown melanoma cells and their corresponding control cells (upper panel). Details of the 13 overlapped pathways are listed below. (C) Elaboration on detailed running scores from GSEA analysis for genes of the Wnt pathway in SAE1-knockdown HCCLM3 cells and YY1-knockdown melanoma cells. (D) Expression validation of significant differentially expressed genes (DEGs) in the Wnt pathway. SAE1-knockdown HCCLM3 cells and SAE1-overexpressing PLC cells relative to their corresponding control cells were analyzed by qRT-PCR (data presented as mean ± S.E.M.). (E) Western blots analysis of Wnt3a in SAE1-overexpressing PLC and Huh7 cells, SAE-knockdown HCCLM3 and MHCC97H cells, and their control cells. (F) Assessment of Wnt3a expression levels in HCC tissues and corresponding peri -tumor tissue samples from 33 patients by qRT-PCR analysis (data presented as medians and quartiles with student’s t -test). (G) Scatterplot showing expression correlation between SAE1 and Wnt3a in HCC tissue samples (n = 32, r : Pearson correlation coefficient). (H) Kaplan-Meier analysis of mRNA expression levels of SAE1 and Wnt3a with OS in liver cancer TCGA data.

Journal: Journal of Advanced Research

Article Title: SAE1 emerges as a pan-cancer driver and key regulator of HCC metastasis

doi: 10.1016/j.jare.2025.06.028

Figure Lengend Snippet: SAE1-mediated upregulation of Wnt3a expression (A) Overview of the strategy used to identify genes co-regulated by SAE1 and YY1. (B) Venn diagram illustrating the numbers of overlapped pathways enriched by GSEA analysis. This analysis stems from comparing RNA-seq data between SAE1-knockdown HCCLM3 cells or YY1-knockdown melanoma cells and their corresponding control cells (upper panel). Details of the 13 overlapped pathways are listed below. (C) Elaboration on detailed running scores from GSEA analysis for genes of the Wnt pathway in SAE1-knockdown HCCLM3 cells and YY1-knockdown melanoma cells. (D) Expression validation of significant differentially expressed genes (DEGs) in the Wnt pathway. SAE1-knockdown HCCLM3 cells and SAE1-overexpressing PLC cells relative to their corresponding control cells were analyzed by qRT-PCR (data presented as mean ± S.E.M.). (E) Western blots analysis of Wnt3a in SAE1-overexpressing PLC and Huh7 cells, SAE-knockdown HCCLM3 and MHCC97H cells, and their control cells. (F) Assessment of Wnt3a expression levels in HCC tissues and corresponding peri -tumor tissue samples from 33 patients by qRT-PCR analysis (data presented as medians and quartiles with student’s t -test). (G) Scatterplot showing expression correlation between SAE1 and Wnt3a in HCC tissue samples (n = 32, r : Pearson correlation coefficient). (H) Kaplan-Meier analysis of mRNA expression levels of SAE1 and Wnt3a with OS in liver cancer TCGA data.

Article Snippet: The Huh7 cell line was obtained from the Japanese Collection of Research Biosources.

Techniques: Expressing, RNA Sequencing, Knockdown, Control, Biomarker Discovery, Quantitative RT-PCR, Western Blot

SAE1 increases Wnt3a expression by binding with YY1 (A) ChIP-PCR analysis shows YY1 binding to the Wnt3a promoter in HCCLM3 cells (right panel). The top panel displays predicted binding sites of YY1 on the Wnt3a promoter. (B) the cartoon representations of the interface between YY1-CTD and Wnt3a promoter predicted by Alphafold3. (C) ChIP-PCR analysis of YY1 binding to the Wnt3a promoter in SAE1-overexpressing Huh7 cells with or without additional YY1 knockdown. (D) ChIP-PCR analysis of YY1 binding to the Wnt3a promoter in SAE1-knockdown PLC cells with or without additional YY1 overexpression. (E) the cartoon representations of the structure of SAE1:YY1-CTD with YY1 acetylation on lysine 332 bound to the Wnt3a promoter (−729 ∼ -719) predicted by Alphafold3 (left panel). Close-up view shows hydrogen bonds indicated by dashed blue lines between the SAE1 and the YY1-CTD residues (left and below panel) and those between YY1-CTD residues and the Wnt3a promotor deoxynucleotides (right panel). The pTM score is 0.76, and the ipTM score between YY1 and Wnt3a promoter is 0.88. (F-G) qPCR analysis and Western blotting assays of Wnt3a expression levels in SAE1-overexpressing Huh7 cells with or without YY1 downregulation (F) or in SAE1-knockdown PLC cells with or without overexpression of YY1 (G). All data presented as mean ± S.E.M., analyzed with student’s t -test (n.s.: not significant, *: P < 0.05 and **: P < 1e-3). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Journal: Journal of Advanced Research

Article Title: SAE1 emerges as a pan-cancer driver and key regulator of HCC metastasis

doi: 10.1016/j.jare.2025.06.028

Figure Lengend Snippet: SAE1 increases Wnt3a expression by binding with YY1 (A) ChIP-PCR analysis shows YY1 binding to the Wnt3a promoter in HCCLM3 cells (right panel). The top panel displays predicted binding sites of YY1 on the Wnt3a promoter. (B) the cartoon representations of the interface between YY1-CTD and Wnt3a promoter predicted by Alphafold3. (C) ChIP-PCR analysis of YY1 binding to the Wnt3a promoter in SAE1-overexpressing Huh7 cells with or without additional YY1 knockdown. (D) ChIP-PCR analysis of YY1 binding to the Wnt3a promoter in SAE1-knockdown PLC cells with or without additional YY1 overexpression. (E) the cartoon representations of the structure of SAE1:YY1-CTD with YY1 acetylation on lysine 332 bound to the Wnt3a promoter (−729 ∼ -719) predicted by Alphafold3 (left panel). Close-up view shows hydrogen bonds indicated by dashed blue lines between the SAE1 and the YY1-CTD residues (left and below panel) and those between YY1-CTD residues and the Wnt3a promotor deoxynucleotides (right panel). The pTM score is 0.76, and the ipTM score between YY1 and Wnt3a promoter is 0.88. (F-G) qPCR analysis and Western blotting assays of Wnt3a expression levels in SAE1-overexpressing Huh7 cells with or without YY1 downregulation (F) or in SAE1-knockdown PLC cells with or without overexpression of YY1 (G). All data presented as mean ± S.E.M., analyzed with student’s t -test (n.s.: not significant, *: P < 0.05 and **: P < 1e-3). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: The Huh7 cell line was obtained from the Japanese Collection of Research Biosources.

Techniques: Expressing, Binding Assay, Knockdown, Over Expression, Western Blot

SAE1 facilitates cell migration and invasive through activation of the Wnt3a pathway (A) qPCR analysis of relative expression levels of TBX3, GLUL, and LRG5 in SAE1-knockdown HCCLM3 cells and MHCC97H cells, SAE1-overexpressing PLC cells and Huh7 cells, and their corresponding control cells. (B) qRT-PCR analysis of relative expression levels of TBX3, GLUL, and LRG5 in SAE1-overexpressing PLC cells and their control cells. (C) Wound healing assays conducted using SAE1-overexpressing PLC cells treated with or without 1 μM of LGK-974. Representative images were captured at 0 h and 48 h post-scratch creation (magnification: 100×, upper panel). The line graph shows the relative migration distance of cells (below panel). (data presented as mean ± S.E.M., and analyzed using one-way ANOVA, ***: P < 1e-6). (D) Transwell assays performed using SAE1-overexpressing PLC cells treated with or without LGK-974. Histograms show the relative numbers of migratory and invasive cells (Student’s t -test, **: P < 1e-3). Data presented as mean ± S.E.M. in (A-D). (E) Representative H&E images of in situ xenograft injected with SAE1-overexpressing Huh7 cells and control cells (magnification: 100 × ). (F) Representative H&E images of lung metastasis resulting from tail vein injection with SAE1-overexpressing Huh7 cells and control cells (magnification: 200 × ). (G) Representative IHC images of SAE1 and Wnt3a in HCC tissue samples (upper panel). Correlation between SAE1 and Wnt3a expression levels in HCC tissues (table below, analyzed by Pearson χ2 test, n = 17).

Journal: Journal of Advanced Research

Article Title: SAE1 emerges as a pan-cancer driver and key regulator of HCC metastasis

doi: 10.1016/j.jare.2025.06.028

Figure Lengend Snippet: SAE1 facilitates cell migration and invasive through activation of the Wnt3a pathway (A) qPCR analysis of relative expression levels of TBX3, GLUL, and LRG5 in SAE1-knockdown HCCLM3 cells and MHCC97H cells, SAE1-overexpressing PLC cells and Huh7 cells, and their corresponding control cells. (B) qRT-PCR analysis of relative expression levels of TBX3, GLUL, and LRG5 in SAE1-overexpressing PLC cells and their control cells. (C) Wound healing assays conducted using SAE1-overexpressing PLC cells treated with or without 1 μM of LGK-974. Representative images were captured at 0 h and 48 h post-scratch creation (magnification: 100×, upper panel). The line graph shows the relative migration distance of cells (below panel). (data presented as mean ± S.E.M., and analyzed using one-way ANOVA, ***: P < 1e-6). (D) Transwell assays performed using SAE1-overexpressing PLC cells treated with or without LGK-974. Histograms show the relative numbers of migratory and invasive cells (Student’s t -test, **: P < 1e-3). Data presented as mean ± S.E.M. in (A-D). (E) Representative H&E images of in situ xenograft injected with SAE1-overexpressing Huh7 cells and control cells (magnification: 100 × ). (F) Representative H&E images of lung metastasis resulting from tail vein injection with SAE1-overexpressing Huh7 cells and control cells (magnification: 200 × ). (G) Representative IHC images of SAE1 and Wnt3a in HCC tissue samples (upper panel). Correlation between SAE1 and Wnt3a expression levels in HCC tissues (table below, analyzed by Pearson χ2 test, n = 17).

Article Snippet: The Huh7 cell line was obtained from the Japanese Collection of Research Biosources.

Techniques: Migration, Activation Assay, Expressing, Knockdown, Control, Quantitative RT-PCR, In Situ, Injection

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1) Product Images from "B7-H3 Modulates Cell Adhesion and Immune Evasion to Promote Tumor Progression and Natural Killer Cell Resistance in Hepatocellular Carcinoma"

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