Fig 1: Lysosomal damage as a consequence of SNCA fibril or LLOME treatment elicits an autophagic response in mDA neurons. (A, D) Representative western blot of LAMP1, p-S757 ULK1, t-ULK1, p-T389 RPS6KB1, t-RPS6KB1, LGALS3, LC3-I, LC3-II, and GAPDH for mDA neurons treated with vehicle (0.1% DMSO), rapamycin, LLOME, or SNCA fibrils. (B, C) The quantification of p-T389 RPS6KB1, t-RPS6KB1, p-S757 ULK1, and t-ULK1. (E, F) Quantification of LAMP1, LGALS3, and LC3-II for LLOME (E) and SNCA fibrils treatment (F). The different symbols correspond to paired replicates (B, C). Cells were treated with SNCA fibrils, rapamycin, or vehicle for 24 h; cells were treated with LLOME for 4 h. (G, H) Secreted SNCA concentrations present in unlysed culture media following treatment with the early autophagy inhibitors Wor or 3-MA (G), the late-autophagy inhibitor Baf-A1 (H) or vehicle (0.1% DMSO) for 24 h as measured by SNCA sandwich ELISA. (I) A representative western blot demonstrating KD of ATG7 from mDA neurons and SNCA from unlysed, cultured media by ELISA. Cultured media was collected from 48 to 72 h post-transfection. Data are expressed as M ± SE (B, n = 4; E-F, n = 4; G, n = 5; H, n = 6; I, n = 5). Statistical significance was determined following natural log transformation and one-way ANOVA with Tukey’s post hoc tests. (G-I) Statistical significance was determined by paired two-tailed t-tests. For all statistical tests *, **, ***, ****, p < 0.05, 0.01, 0.001, and 0.0001, respectively.
Fig 2: SNCA is associated with survival outcome. A Overall survival (OS) of SNCA in TCGA BLAC cohort. B-D OS of SNCA analysis from Kaplan–Meier survival curves on GSE13507 (B), GSE 32548 (C), and GSE 32894 (D). The numbers below the figures denote the number of patients at risk in each group. The survival analysis was obtained using log-rank test
Fig 3: Co-expression genes of SNCA in BLCA analyzed by LinkedOmics database. A All genes highly correlated with SNCA as identified by Pearson correlation test in the BLCA cohort. B Heat maps showing the top 50 genes positively and negatively correlated with SNCA in BLCA. Red indicates positively correlated genes, and blue indicates negatively correlated genes. C Survival heat maps of the top 50 significant genes positively and negatively correlated with SNCA in BLCA. The survival heat maps show the hazard ratios in the logarithmic scale (log10) for different genes. The red and blue blocks denote higher and lower risks, respectively. The rectangles with frames indicate the significant unfavorable and favorable results in prognostic analyses (p < 0.05). D – E Significantly enriched GO annotations and KEGG pathways of SNCA in the BLCA cohort
Fig 4: Expression of SNCA detected in BLCA patients. A Representative images for the protein levels of a-Syn investigated by IHC. B The histochemistry score (H-score) of SNCA expression analysis by Image-Pro Plus 6.0 showed that SNCA was significantly downregulated in the BLCA tissue array (n = 63). P -value represents unpaired Student’s t test, **p < 0.01. C Kaplan–Meier analysis of the correlation between SNCA expression and the OS of patients with BLCA in the tissue array (n = 63). D SNCA mRNA expression was significantly downregulated in BCa compared with para-cancer tissues in our cohort, as determined by qRT-PCR (n = 20). SNCA expression was normalized to GAPDH. P-value represents paired Student’s t test, *p < 0.05
Fig 5: Identification of SNCA co-expression key modules by WGCNA in BLCA. A The unsupervised hierarchical cluster dendrogram was used to identify co-expression modules and assign colors to them. A total of 22 modules were identified and represented by different colors. The white circles indicate the top five hub genes. B Spearman correlation matrix heat map of the correlation module MEs and clinical traits (smoking habits, weight, height, and age at diagnosis). The darker the module color, the more significant the relationship. C-D Multivariate hazards models were used to evaluate the effects of the modules on OS and DFS. E GO analysis of genes involved in the brown module in terms of biological process, cellular component, and molecular function. F KEGG analysis of genes involved in the brown module
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