SATB1

Colorectal cancer (CRC) is a malignancy with high incidence and poor prognosis. It is urgent to identify valuable biomarkers for early diagnosis and potent therapeutic targets. It has been reported that SATB1 is associated with the malignant progression in CRC. To explore the role of SATB1 in CRC progression and the underlying mechanism, we evaluated the expression of SATB1 in the paired CRC tissues with immunohistochemistry. The results showed that the expression of SATB1 in lymph node metastasis was higher than that in primary lesion, and that in distant organ metastasis was higher than that in primary lesion. The retrospective analysis showed that patients with high expression of SATB1 had a significantly worse prognosis than those with negative and moderate expression. In vitro experiments that employing SATB1 over-expressing and depleted CRC cell lines confirmed that SATB1 contributes to cell proliferation and colonization, while inhibiting cell motility. Furthermore, the tissue immunofluorescence assay, Co-IP and Western blot were conducted to reveal that SATB1 induced translocation of β-catenin and formed a protein complex with it in the nuclei. In conclusion, SATB1 mediated tumor colonization and β-catenin nuclear localization are associated with the malignant progression and poor prognosis of CRC.

Bladder cancer (BLCA) is a malignant tumor associated with unfavorable outcomes. Studies suggest that anoikis plays a crucial role in tumor progression and cancer cell metastasis. However, its specific role in bladder cancer remains poorly understood. Our objective was to identify anoikis-related genes (ARGs) and subsequently construct a risk model to assess their potential for predicting the prognosis of bladder cancer.The transcriptome data and clinical data of BLCA patients were sourced from The Cancer Genome Atlas and GEO database. We then performed the differential expression analysis to screen differentially expressed ARGs. Subsequently, we conducted non-negative matrix factorization (NMF) clustering analysis to establish molecular subtypes based on the differentially expressed ARGs. The CIBERSORT algorithm was used to estimate the quantification of different cell infiltration in BLCA tumor microenviroment. A prognostic risk model containing 7 ARGs was established using Lasso-Cox regression analysis. The nomogram was built for predicting the survival probability of BLCA patients. To determine the drug sensitivity of each sample from the high- and low-risk groups, the R package "pRRophetic" was performed. Finally, the role of LYPD1 was explored in BLCA cell lines.We identified 90 differential expression ARGs and NMF clustering categorizated the BLCA patientss into two distinct groups (cluster A and B). Patients in cluster A had a better prognosis than those in cluster B. Then, we established a ARGs risk model including CALR, FASN, FOSL1, JUN, LYPD1, MST1R, and SATB1, which was validated in the train and test set. The results suggested overall survival rate was much higher in low risk group than high risk group. The cox regression analysis, ROC curve analysis, and nomogram collectively demonstrated that the risk model served as an independent prognostic factor. The high risk group had a higher level TME scores compared to the low risk group. Furthermore, LYPD1 was low expression in BLCA cells and overexpression of LYPD1 inhibits the prolifearation, migration and invasion.In the current study, we have identified differential expression ARGs and constructed a risk model with the promise for guiding prognostic predictions and provided a therapeutic target for patients with BLCA.

Idiopathic Parkinson's disease (PD) is characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta, which is associated with neuroinflammation and reactive gliosis. The underlying cause of PD and the concurrent neuroinflammation are not well understood. In this study, we utilize human and murine neuronal lines, stem cell-derived dopaminergic neurons, and mice to demonstrate that three previously identified genetic risk factors for PD, namely SATB1, MIR22HG, and GBA, are components of a single gene regulatory pathway. Our findings indicate that dysregulation of this pathway leads to the upregulation of glucocerebrosides (GluCer), which triggers a cellular senescence-like phenotype in dopaminergic neurons. Specifically, we discovered that downregulation of the transcriptional repressor SATB1 results in the derepression of the microRNA miR-22-3p, leading to decreased GBA expression and subsequent accumulation of GluCer. Furthermore, our results demonstrate that an increase in GluCer alone is sufficient to impair lysosomal and mitochondrial function, thereby inducing cellular senescence. Dysregulation of the SATB1-MIR22-GBA pathway, observed in both PD patients and normal aging, leads to lysosomal and mitochondrial dysfunction due to the GluCer accumulation, ultimately resulting in a cellular senescence-like phenotype in dopaminergic neurons. Therefore, our study highlights a novel pathway involving three genetic risk factors for PD and provides a potential mechanism for the senescence-induced neuroinflammation and reactive gliosis observed in both PD and normal aging.