结晶紫水溶液（0.1%）

Background Low-grade gliomas (LGG) are a heterogeneous category of brain tumors characterized by a variable clinical course, frequently associated with unfavorable prognosis and therapeutic challenges. Understanding the molecular mechanisms underlying LGG progression is crucial for improving prognosis and therapeutic strategies. This study integrates single-cell RNA sequencing and bioinformatics to explore the role of METCGs (mitochondrial electron transport chain genes) in LGG and construct a predictive model for prognosis, and through in vitro experiments, the feasibility of this model was validated. Methods We analyzed 5,691 cells and 22,947 genes from the GSE117891 dataset. Using cell marker genes from the CellMarker 2.0 database and classical markers, we identified four distinct cell types: oligodendrocytes, T cells, astrocytes, and microglial cells. The METCGs profiles were calculated using various algorithms, including AUCell, UCell, ssGSEA, and others. Differentially expressed genes (DEGs) were identified and enriched for relevant pathways. Machine learning algorithms were employed to construct a prognostic risk model based on five selected METCGs. The model was validated using independent LGG cohorts. Biological pathway analyses, immune infiltration profiles, and potential drug targets were also explored. To validate the reliability of this model through experiments, functional experiments, including Blue native Page (BN-Page), western blotting, immunofluorescence, and cell viability assays, were conducted to validate SDHB expression and its role in LGG progression. Results Astrocytes exhibited the highest METCG scores, indicating their central role in mitochondrial energy regulation. The prognostic model, constructed using the StepCox[forward] + plsRcox approach, included five genes: SDHB, SDHC, SLC25A27, UQCRB, and NDUFA13. The model demonstrated high prognostic accuracy with an average C-index of 0.67 and successfully stratified LGG patients into low- and high-risk groups. High-risk patients had worse survival outcomes, with significant differences observed in KEGG pathways, immune infiltration, and metabolic processes. The low-risk group exhibited higher immune cell infiltration, including follicular helper T and monocyte cells. AZD1208_1449 was identified as a potential drug targeting high-risk patients. Additionally, SDHB expression was significantly higher in LGG cells, and knockdown of SDHB inhibited cell proliferation and invasion, supporting its role in tumor progression. Conclusion This study provides a comprehensive analysis of METCGs in LGG and develops a robust prognostic model for patient stratification. SDHB, a key subunit of Complex II, plays a crucial role in mitochondrial function and tumor progression. Our findings suggest that he high expression of SDHB in LGG contributes to maintaining elevated SDH and Complex II activity, ensuring the structural and functional integrity of mitochondrial ETC complexes. This supports the high ROS production and MMP required for the rapid growth of LGG, thereby promoting its proliferation and invasion. Thus, targeting SDHB and its associated pathways could offer new therapeutic avenues for LGG treatment.

Background Low-grade gliomas (LGG) are known for their slow growth yet retain the potential to progress to more aggressive malignancies. Glioma cells are frequently exposed to stressors such as hypoxia, nutrient deprivation, and oxidative stress, which disrupt protein folding within the endoplasmic reticulum (ER), leading to ER stress and activation of the unfolded protein response (UPR). ER stress plays a complex role in glioma initiation, progression, and resistance to chemotherapy. Dysregulated signaling between mitochondria and the ER can further exacerbate ER stress, impacting glioma cell survival and proliferation. Elucidating the molecular mechanisms by which mitochondrial interactions influence ER stress may reveal novel therapeutic targets for LGG treatment. Methods ER-stress related mitochondrial protein-coding genes (ERSMGs) linked to LGG prognosis were identified using Mitocarta3.0, Genecards, CGGA, and TCGA data. A prognostic model was developed via univariate and LASSO-Cox regression and validated by ROC curves. OMA1's role was assessed through knockdown experiments in LGG cell lines. Results Eleven ERSMGs were significantly associated with LGG prognosis. The model achieved reliable predictive accuracy (AUC > 0.6) and stratified patients into high- and low-risk groups with distinct survival rates. High-risk patients exhibited increased sensitivity to SB505124. OMA1 knockdown in LGG cells induced ER stress by promoting mitochondrial fusion, increasing mtROS, ultimately inhibiting cell proliferation and invasion. Conclusion This study provides a novel prognostic model based on ERSMGs, offering novel insights into LGG progression and invasion. OMA1-mediated mitochondrial dysfunction and ER stress play critical roles in glioma cell growth and survival, representing potential therapeutic targets.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths globally, owing to its high recurrence rate of 50 to 70% within five years. Despite known associations of certain DNA damage and repair (DDR) genes with tumor recurrence and drug resistance, a comprehensive understanding of DDR pathways’ role in predicting HCC recurrence and therapeutic responses remains elusive. Addressing this gap could offer significant advancements in prognostic and therapeutic strategies for HCC. This study used 769 RNA sequencing samples from public datasets and 53 samples from Xiangya Hospital for DDR model training and validation. It came out that DDR pathways were significantly enriched in samples with P53 mutations. Next, among the 173 combinations of algorithms and parameters, CoxBoost + RSF, Lasso [fold = 10] + RSF, and Lasso [fold = 50] + RSF demonstrated the best performance. The average AUC values of 1 to 5 years and the average concordance index (C-index) value were around 0.7. The risk scores were increased in tumors with recurrence, P53 mutation, and higher TNM stages. High-risk groups, characterized by enriched DDR pathways, exhibited lower CD8 + T cell infiltration and poorer responses to immunotherapy using atezolizumab and bevacizumab, emphasizing the potential of DDR signatures as valuable prognostic and therapeutic biomarkers. In conclusion, the DDR signatures associated with P53 mutations can predict recurrence and therapeutic response in HCC, highlighting their potential as prognostic and therapeutic biomarkers.