Journal of Southern Medical University ›› 2026, Vol. 46 ›› Issue (5): 1039-1052.doi: 10.12122/j.issn.1673-4254.2026.05.07
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Myricetin inhibits proliferation and migration of bladder cancer cells by inhibiting HSP90AA1-mediated AKT phosphorylation
Ruixu SUN1(
), Yutong LI1, Ling ZUO2, Jiahua TAO1, Xuan DONG1, Hongwei LIU1()
- 1.Laboratory of Urology, Affiliated Hospital of Guangdong Medical University, Zhanjiang 524001, China
2.Department of Traditional Chinese Medicine, Second Affiliated Hospital of Guangdong Medical University, Zhanjiang 524003, China
-
Received:2025-10-31Online:2026-05-20Published:2026-05-27 -
Contact:Hongwei LIU E-mail:2918510253@qq.com;lhwhongwei@gdmu.edu.cn
Cite this article
Ruixu SUN, Yutong LI, Ling ZUO, Jiahua TAO, Xuan DONG, Hongwei LIU. Myricetin inhibits proliferation and migration of bladder cancer cells by inhibiting HSP90AA1-mediated AKT phosphorylation[J]. Journal of Southern Medical University, 2026, 46(5): 1039-1052.
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URL: https://www.j-smu.com/EN/10.12122/j.issn.1673-4254.2026.05.07
Fig.1 Distribution of ADMET characteristics of the compound myricetin.
Fig.1 Distribution of ADMET characteristics of the compound myricetin.
Tab.1 Toxicokinetic simulation analysis of myricetin
| TOPKAT | Prediction* | Bayesian score** | Mahalanobis distance# | P& |
|---|---|---|---|---|
| Aerobic biodegradability | Readily biodegradable | 18.45 | 8.20 | 0.720 |
| Ames mutagenicity | Non-mutagen | 12.35 | 5.15 | 0.945 |
| DTP | Non-toxic | -6.78 | 6.83 | 0.580 |
| Mouse female FDA | ||||
| None vs carcinogen | Non-carcinogen | -3.21 | 9.45 | 0.820 |
| Single vs multiple | - | - | - | - |
| NTP | Non-carcinogen | -7.89 | 7.11 | 0.665 |
| Mouse Male FDA | ||||
| None vs carcinogen | Non-carcinogen | -2.95 | 10.25 | 0.780 |
| Single vs multiple | Non-carcinogen | -8.45 | 9.87 | 0.550 |
| NTP | Non-carcinogen | -5.22 | 8.05 | 0.610 |
| Rat Female FDA | ||||
| None vs carcinogen | Non-carcinogen | -2.15 | 8.75 | 0.750 |
| Single vs multiple | Non-carcinogen | -3.88 | 14.20 | 0.350 |
| NTP | Non-carcinogen | 3.45 | 7.35 | 0.690 |
| Rat Male FDA | ||||
| None vs carcinogen | Non-carcinogen | 2.05 | 12.88 | 0.420 |
| Single vs multiple | Non-carcinogen | -5.67 | 11.95 | 0.480 |
| NTP | Non-carcinogen | -4.12 | 6.90 | 0.710 |
| TD50-mouse (mg·kg-1·day-1) | >500 (non-carcinogenic) | - | 10.25 | 0.210 |
| TD50-rat (mg·kg-1·day-1) | >500 (non-carcinogenic) | - | 12.75 | 0.085 |
| Chronic LOAEL (mg/kg) | 298.0 | - | 18.45 | 0.025 |
| LD50-rat (mg·kg-1·day-1) | >2000 | - | 14.60 | 0.005 |
Tab.1 Toxicokinetic simulation analysis of myricetin
| TOPKAT | Prediction* | Bayesian score** | Mahalanobis distance# | P& |
|---|---|---|---|---|
| Aerobic biodegradability | Readily biodegradable | 18.45 | 8.20 | 0.720 |
| Ames mutagenicity | Non-mutagen | 12.35 | 5.15 | 0.945 |
| DTP | Non-toxic | -6.78 | 6.83 | 0.580 |
| Mouse female FDA | ||||
| None vs carcinogen | Non-carcinogen | -3.21 | 9.45 | 0.820 |
| Single vs multiple | - | - | - | - |
| NTP | Non-carcinogen | -7.89 | 7.11 | 0.665 |
| Mouse Male FDA | ||||
| None vs carcinogen | Non-carcinogen | -2.95 | 10.25 | 0.780 |
| Single vs multiple | Non-carcinogen | -8.45 | 9.87 | 0.550 |
| NTP | Non-carcinogen | -5.22 | 8.05 | 0.610 |
| Rat Female FDA | ||||
| None vs carcinogen | Non-carcinogen | -2.15 | 8.75 | 0.750 |
| Single vs multiple | Non-carcinogen | -3.88 | 14.20 | 0.350 |
| NTP | Non-carcinogen | 3.45 | 7.35 | 0.690 |
| Rat Male FDA | ||||
| None vs carcinogen | Non-carcinogen | 2.05 | 12.88 | 0.420 |
| Single vs multiple | Non-carcinogen | -5.67 | 11.95 | 0.480 |
| NTP | Non-carcinogen | -4.12 | 6.90 | 0.710 |
| TD50-mouse (mg·kg-1·day-1) | >500 (non-carcinogenic) | - | 10.25 | 0.210 |
| TD50-rat (mg·kg-1·day-1) | >500 (non-carcinogenic) | - | 12.75 | 0.085 |
| Chronic LOAEL (mg/kg) | 298.0 | - | 18.45 | 0.025 |
| LD50-rat (mg·kg-1·day-1) | >2000 | - | 14.60 | 0.005 |
Fig.2 Intersecting genes of bladder cancer and myricetin.
Fig.2 Intersecting genes of bladder cancer and myricetin.
Fig.3 Network diagram of the interaction between myricetin and potential target proteins in bladder cancer and screening of the core target genes. The nodes represent the target proteins, and the connections between nodes indicate protein interactions.
Fig.3 Network diagram of the interaction between myricetin and potential target proteins in bladder cancer and screening of the core target genes. The nodes represent the target proteins, and the connections between nodes indicate protein interactions.
Fig.4 Enriched bubble map of GO (A) and KEGG (B) signaling pathways and potential targets of myricetin for bladder cancer treatment.
Fig.4 Enriched bubble map of GO (A) and KEGG (B) signaling pathways and potential targets of myricetin for bladder cancer treatment.
Tab.2 Simulation results of the interaction between myricetin and its target protein molecules
| Protein | CurPocket | Vina score* | Cavity volume (Å3) | Center (x, y, z) | Docking size (x, y, z) |
|---|---|---|---|---|---|
| HSP90AA1 | C2 | -10.9 | 780 | 19, 39, 5 | 21, 21, 21 |
| C1 | -10.4 | 832 | 88, 1, 135 | 21, 21, 21 | |
| C3 | -9.6 | 719 | 85, 66, 54 | 21, 21, 21 | |
| C4 | -6.7 | 661 | 36, 24, 48 | 21, 21, 21 | |
| C5 | -6.6 | 118 | 79, 5, 120 | 21, 21, 21 | |
| TOP2A | C2 | -9.7 | 3,411 | 70, 20, 28 | 31, 21, 21 |
| C3 | -8.6 | 1,437 | 35, -5, 40 | 21, 21, 21 | |
| C1 | -7.7 | 11,445 | 48, 5, 22 | 35, 35, 31 | |
| C5 | -7.0 | 821 | 71, 17, 9 | 21, 21, 21 | |
| C4 | -6.7 | 1,072 | 26, -12, 26 | 21, 21, 21 | |
| CYP1B1 | C1 | -8.2 | 1,549 | -18, 18, -17 | 21, 21, 21 |
| C2 | -7.8 | 651 | -11, 13, -31 | 21, 21, 21 | |
| C3 | -7.7 | 610 | -41, 9, -16 | 21, 21, 21 | |
| C4 | -7.7 | 574 | -23, 5, -9 | 21, 21, 21 | |
| C5 | -5.8 | 387 | -2, 15, -12 | 21, 21, 21 |
Tab.2 Simulation results of the interaction between myricetin and its target protein molecules
| Protein | CurPocket | Vina score* | Cavity volume (Å3) | Center (x, y, z) | Docking size (x, y, z) |
|---|---|---|---|---|---|
| HSP90AA1 | C2 | -10.9 | 780 | 19, 39, 5 | 21, 21, 21 |
| C1 | -10.4 | 832 | 88, 1, 135 | 21, 21, 21 | |
| C3 | -9.6 | 719 | 85, 66, 54 | 21, 21, 21 | |
| C4 | -6.7 | 661 | 36, 24, 48 | 21, 21, 21 | |
| C5 | -6.6 | 118 | 79, 5, 120 | 21, 21, 21 | |
| TOP2A | C2 | -9.7 | 3,411 | 70, 20, 28 | 31, 21, 21 |
| C3 | -8.6 | 1,437 | 35, -5, 40 | 21, 21, 21 | |
| C1 | -7.7 | 11,445 | 48, 5, 22 | 35, 35, 31 | |
| C5 | -7.0 | 821 | 71, 17, 9 | 21, 21, 21 | |
| C4 | -6.7 | 1,072 | 26, -12, 26 | 21, 21, 21 | |
| CYP1B1 | C1 | -8.2 | 1,549 | -18, 18, -17 | 21, 21, 21 |
| C2 | -7.8 | 651 | -11, 13, -31 | 21, 21, 21 | |
| C3 | -7.7 | 610 | -41, 9, -16 | 21, 21, 21 | |
| C4 | -7.7 | 574 | -23, 5, -9 | 21, 21, 21 | |
| C5 | -5.8 | 387 | -2, 15, -12 | 21, 21, 21 |
Fig.5 Visualization of the results of molecular docking analysis. The turquoise ball-and-stick model represents the small molecule ligand myricetin, the white ball-and-stick model represents the amino acid side chain residues of the receptor HSP90AA1 protein, and the green dashed lines represent hydrogen bond interactions.
Fig.5 Visualization of the results of molecular docking analysis. The turquoise ball-and-stick model represents the small molecule ligand myricetin, the white ball-and-stick model represents the amino acid side chain residues of the receptor HSP90AA1 protein, and the green dashed lines represent hydrogen bond interactions.
Fig.6 Results of molecular dynamics calculations on the myricetin-HSP90AAA1-receptor complex. A: Conformational RMSD changes of myricetin during the 50 ns kinetic simulation. B: Conformational change RMSF of the receptor protein residue exceeds 50 ns.
Fig.6 Results of molecular dynamics calculations on the myricetin-HSP90AAA1-receptor complex. A: Conformational RMSD changes of myricetin during the 50 ns kinetic simulation. B: Conformational change RMSF of the receptor protein residue exceeds 50 ns.
Fig.7 HSP90AA1 in bladder cancer and normal tissues and KM survival analysis. A: Heatmap of clinical correlation analysis of high and low HSP90AA1 expression groups. B: Pairwise difference analysis and expression difference analysis of HSP90AA1 in bladder cancer. C: Effect of high and low HSP90AA1 expression on overall survival in bladder cancer patients. D: Effect of high and low HSP90AA1 expression on progression-free survival in bladder cancer patients. **P<0.01, ***P<0.001.
Fig.7 HSP90AA1 in bladder cancer and normal tissues and KM survival analysis. A: Heatmap of clinical correlation analysis of high and low HSP90AA1 expression groups. B: Pairwise difference analysis and expression difference analysis of HSP90AA1 in bladder cancer. C: Effect of high and low HSP90AA1 expression on overall survival in bladder cancer patients. D: Effect of high and low HSP90AA1 expression on progression-free survival in bladder cancer patients. **P<0.01, ***P<0.001.
Fig.8 Validation of the functional essentiality of HSP90AA1 in bladder cancer cells by CRISPR-Cas9 screening. A: Distribution of HSP90AA1 knockout dependency across all examined cancer cell lines and its strong selective label. B: Distribution of Gene Effect values for HSP90AA1 across 34 bladder/urinary tract cancer cell lines. C: Association between Gene Effect values and gene expression levels [log2(TPM+1)] of HSP90AA1 in bladder cancer cell lines. D: IHC map of HSP90AA1 in low-gradeand high-grade bladder cancer tissues (Original magnification: ×200).
Fig.8 Validation of the functional essentiality of HSP90AA1 in bladder cancer cells by CRISPR-Cas9 screening. A: Distribution of HSP90AA1 knockout dependency across all examined cancer cell lines and its strong selective label. B: Distribution of Gene Effect values for HSP90AA1 across 34 bladder/urinary tract cancer cell lines. C: Association between Gene Effect values and gene expression levels [log2(TPM+1)] of HSP90AA1 in bladder cancer cell lines. D: IHC map of HSP90AA1 in low-gradeand high-grade bladder cancer tissues (Original magnification: ×200).
Fig.9 Tumor immune microenvironment remodeling and fluorescence co-localization by flow cytometry technique. A: Univariate and multifactorial regression clinical correlation analysis. B: Immune checkpoint correlation analysis. C: GSEA enrichment analysis. D: Drug susceptibility analysis. E: Immune cell infiltration correlation analysis. F: Fluorescence co-localization by flow cytometry.
Fig.9 Tumor immune microenvironment remodeling and fluorescence co-localization by flow cytometry technique. A: Univariate and multifactorial regression clinical correlation analysis. B: Immune checkpoint correlation analysis. C: GSEA enrichment analysis. D: Drug susceptibility analysis. E: Immune cell infiltration correlation analysis. F: Fluorescence co-localization by flow cytometry.
Fig.10 Myricetin inhibits bladder cancer cell proliferation and migration mediated by HSP90AA1 and PI3K-AKT signaling. A: Viability of UM-UC-3 cells measured using CCK-8 assay. B: Effect of different concentrations of myricetin on UM-UC-3 cell proliferation assessed using clone formation assay. C: Effect of different concentrations of myricetin on UM-UC-3 cell migration assessed using wound healing assay. D: Effect of different concentrations of myricetin on HSP90AA1 mRNA and protein expression in UM-UC-3 cells detected using qRT-PCR and Western blotting; E: Effect of different concentrations of myricetin on protein expression in UM-UC-3 cells detected using Western blotting. *P<0.05, **P<0.01, ****P<0.0001 vs 0 μmol/L.
Fig.10 Myricetin inhibits bladder cancer cell proliferation and migration mediated by HSP90AA1 and PI3K-AKT signaling. A: Viability of UM-UC-3 cells measured using CCK-8 assay. B: Effect of different concentrations of myricetin on UM-UC-3 cell proliferation assessed using clone formation assay. C: Effect of different concentrations of myricetin on UM-UC-3 cell migration assessed using wound healing assay. D: Effect of different concentrations of myricetin on HSP90AA1 mRNA and protein expression in UM-UC-3 cells detected using qRT-PCR and Western blotting; E: Effect of different concentrations of myricetin on protein expression in UM-UC-3 cells detected using Western blotting. *P<0.05, **P<0.01, ****P<0.0001 vs 0 μmol/L.
Fig.11 Single cell transcriptome analysis reveals cell type-specific expression of HSP90AA1 in bladder cancer. A, B: Heat map of HSP90AA1 expression in 3 different bladder cancer single cell data sets (GSE210347, GSE149652, GSE145281). The color depth represents the gene expression level (standardized count), and the bar on the right represents the expression percentage. HSP90AA1 is most expressed in malignant epithelial cells (cancer cells).
Fig.11 Single cell transcriptome analysis reveals cell type-specific expression of HSP90AA1 in bladder cancer. A, B: Heat map of HSP90AA1 expression in 3 different bladder cancer single cell data sets (GSE210347, GSE149652, GSE145281). The color depth represents the gene expression level (standardized count), and the bar on the right represents the expression percentage. HSP90AA1 is most expressed in malignant epithelial cells (cancer cells).
Tab.3 Effect of virtual mutations on binding affinity of myricetin-HSP90AA1
| Protein system | Vina Score (kcal/mol) | ΔΔG (kcal/mol)* | Main interaction changes |
|---|---|---|---|
| Mut (WT) | -10.9 | - | Forming stable hydrogen bonds and hydrophobic interactions |
| V136A | -8.2 | +2.7 | Hydrophobic pocket environment changes, combined with conformational shift |
| Y139F | -9.8 | +1.1 | Retaining aromatic ring stacking, but losing hydrogen bonding interaction |
| Y139A | -7.5 | +3.4 | The key hydrogen bonds are completely destroyed, and the binding mode is significantly altered |
Tab.3 Effect of virtual mutations on binding affinity of myricetin-HSP90AA1
| Protein system | Vina Score (kcal/mol) | ΔΔG (kcal/mol)* | Main interaction changes |
|---|---|---|---|
| Mut (WT) | -10.9 | - | Forming stable hydrogen bonds and hydrophobic interactions |
| V136A | -8.2 | +2.7 | Hydrophobic pocket environment changes, combined with conformational shift |
| Y139F | -9.8 | +1.1 | Retaining aromatic ring stacking, but losing hydrogen bonding interaction |
| Y139A | -7.5 | +3.4 | The key hydrogen bonds are completely destroyed, and the binding mode is significantly altered |
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