Ceramide kinase confers tamoxifen resistance in estrogen receptor-positive breast cancer by altering sphingolipid metabolism

Sphingomyelin Metabolism Modifies Luminal A Breast Cancer Cell Line under a High Dose of Vitamin C

The role of sphingomyelin metabolism and vitamin C in cancer has been widely described with conflicting results ranging from a total absence of effect to possible preventive and/or protective effects. The aim of this study was to establish the possible involvement of sphingomyelin metabolism in the changes induced by vitamin C in breast cancer cells. The MCF7 cell line reproducing luminal A breast cancer and the MDA-MB-231 cell line reproducing triple-negative breast cancer were used. Cell phenotype was tested by estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2 expression, and proliferation index percentage. Sphingomyelin was localized by an EGFP-NT-Lys fluorescent probe. Sphingomyelin metabolism was analyzed by RT-PCR, Western blotting and UFLC-MS/MS. The results showed that a high dose of vitamin C produced reduced cell viability, modulated cell cycle related genes, and changed the cell phenotype with estrogen receptor downregulation in MCF7 cell. In these cells, the catabolism of sphingomyelin was promoted with a large increase in ceramide content. No changes in viability and molecular expression were observed in MB231 cells. In conclusion, a high dose of vitamin C induces changes in the luminal A cell line involving sphingomyelin metabolism.

Research progress of hyperthermia in tumor therapy by influencing metabolic reprogramming of tumor cells

Cellular metabolic reprogramming is an important feature of malignant tumors. Metabolic reprogramming causes changes in the levels or types of specific metabolites inside and outside the cell, which affects tumorigenesis and progression by influencing gene expression, the cellular state, and the tumor microenvironment. During tumorigenesis, a series of changes in the glucose metabolism, fatty acid metabolism, amino acid metabolism, and cholesterol metabolism of tumor cells occur, which are involved in the process of cellular carcinogenesis and constitute part of the underlying mechanisms of tumor formation. Hyperthermia, as one of the main therapeutic tools for malignant tumors, has obvious effects on tumor cell metabolism. In this paper, we will combine the latest research progress in the field of cellular metabolic reprogramming and focus on the current experimental research and clinical treatment of hyperthermia in cellular metabolic reprogramming to discuss the feasibility of cellular metabolic reprogramming-related mechanisms guiding hyperthermia in malignant tumor treatment, so as to provide more ideas for hyperthermia to treat malignant tumors through the direction of cellular metabolic reprogramming.

Identification of a distinct tumor endothelial cell-related gene expression signature associated with patient prognosis and immunotherapy response in multiple cancers

BACKGROUND

Tumor endothelial cells (TECs) play a significant role in regulating the tumor microenvironment, drug response, and immune cell activities in various cancers. However, the association between TEC gene expression signature and patient prognosis or therapeutic response remains poorly understood.

METHODS

We analyzed transcriptomics data of normal and tumor endothelial cells obtained from the GEO database to identify differentially expressed genes (DEGs) associated with TECs. We then compared these DEGs with those commonly found across five different tumor types from the TCGA database to determine their prognostic relevance. Using these genes, we constructed a prognostic risk model integrated with clinical features to develop a nomogram model, which we validated through biological experiments.

RESULTS

We identified 12 TEC-related prognostic genes across multiple tumor types, of which five genes were sufficient to construct a prognostic risk model with an AUC of 0.682. The risk scores effectively predicted patient prognosis and immunotherapeutic response. Our newly developed nomogram model provided more accurate prognostic estimates of cancer patients than the TNM staging method (AUC = 0.735) and was validated using external patient cohorts. Finally, RT-PCR and immunohistochemical analyses indicated that the expression of these 5 TEC-related prognostic genes was up-regulated in both patient-derived tumors and cancer cell lines, while depletion of the hub genes reduced cancer cell growth, migration and invasion, and enhanced their sensitivity to gemcitabine or cytarabine.

CONCLUSIONS

Our study discovered the first TEC-related gene expression signature that can be used to construct a prognostic risk model for guiding treatment options in multiple cancers.