The identification of BCL-XL and MCL-1 as key anti-apoptotic proteins in medulloblastoma that mediate distinct roles in chemotherapy resistance

Butein inhibits oral squamous cell carcinoma growth via promoting MCL-1 ubiquitination

Oral squamous cell carcinoma (OSCC) is the most common malignant head and neck carcinoma type. Myeloid cell leukemia-1 (MCL-1), an anti-apoptotic BCL-1 protein, has been verified to be among the most highly upregulated pathologic proteins in human cancers linked to tumor relapse, poor prognosis and therapeutic resistance. Herein, therapeutic targeting MCL-1 is an attractive focus for cancer treatment. The present study found that butein, a potential phytochemical compound, exerted profound antitumor effects on OSCC cells. Butein treatment significantly inhibited cell viability, proliferation capacity and colony formation ability, and activated cell apoptotic process. Further potential mechanism investigation showed that promoting MCL-1 ubiquitination and degradation is the major reason for butein-mediated OSCC cell cytotoxicity. Our results uncovered that butein could facilitate E3 ligase FBW7 combined with MCL-1, which contributed to an increase in the ubiquitination of MCL-1 Ub-K48 and degradation. The results of both in vitro cell experiments and in vivo xenograft models imply a critical antitumor function of butein with the well-tolerated feature, and it might be an attractive and promising agent for OSCC treatment.

Single cell sequencing revealed the mechanism of CRYAB in glioma and its diagnostic and prognostic value

Background

We explored the characteristics of single-cell differentiation data in glioblastoma and established prognostic markers based on CRYAB to predict the prognosis of glioblastoma patients. Aberrant expression of CRYAB is associated with invasive behavior in various tumors, including glioblastoma. However, the specific role and mechanisms of CRYAB in glioblastoma are still unclear.

Methods

We assessed RNA-seq and microarray data from TCGA and GEO databases, combined with scRNA-seq data on glioma patients from GEO. Utilizing the Seurat R package, we identified distinct survival-related gene clusters in the scRNA-seq data. Prognostic pivotal genes were discovered through single-factor Cox analysis, and a prognostic model was established using LASSO and stepwise regression algorithms. Moreover, we investigated the predictive potential of these genes in the immune microenvironment and their applicability in immunotherapy. Finally, in vitro experiments confirmed the functional significance of the high-risk gene CRYAB.

Results

By analyzing the ScRNA-seq data, we identified 28 cell clusters representing seven cell types. After dimensionality reduction and clustering analysis, we obtained four subpopulations within the oligodendrocyte lineage based on their differentiation trajectory. Using CRYAB as a marker gene for the terminal-stage subpopulation, we found that its expression was associated with poor prognosis. In vitro experiments demonstrated that knocking out CRYAB in U87 and LN229 cells reduced cell viability, proliferation, and invasiveness.

Conclusion

The risk model based on CRYAB holds promise in accurately predicting glioblastoma. A comprehensive study of the specific mechanisms of CRYAB in glioblastoma would contribute to understanding its response to immunotherapy. Targeting the CRYAB gene may be beneficial for glioblastoma patients.