Metformin induces caspase-dependent and caspase-independent apoptosis in human bladder cancer T24 cells

The anti-inflammatory effect of metformin: The molecular targets

Metformin is an anti-diabetic drug. Metformin mainly inhibits gluconeogenesis in the liver and reduces blood sugar. In addition to the anti-diabetic effects, many studies have revealed that metformin has anti-inflammatory effects. Various molecules were suggested to be the target of the metformin's anti-inflammatory effects. However, the conclusion is not clear. Metformin is related to a number of molecules and the identification of the main target in anti-inflammatory effects leads to the understanding of inflammation and metformin. In this article, I discuss each suggested molecule, involved mechanisms, and their relationship with various diseases.

Synergistic effect of metformin and doxorubicin on the metastatic potential of T24 cells

BACKGROUND

The motor ability of cancer cells to cross the basement membrane contributes to their implantation in a new location. Metastasis is a significant factor that worsens the prognosis of cancer patients. Thus, reducing cell invasiveness is an important aspect of anticancer therapy, also in bladder cancer treatment.

MATERIAL

The study material was the T24 cell line of human urinary bladder cancer. The migratory potential of the cells and the effect of the treatment with individually doses and synergistic combination of doxorubicin and metformin in the 500:1 ratio for 24 h were analyzed.

RESULTS

The results obtained show a compound-initiated decrease in the motor abilities of bladder cancer cells compared to controls. A decrease in the rate of colony formation was observed, as well as inhibition of migration through inserts. The visualized reorganization of the vimentin and actin networks confirms the drug-initiated limitation of the metastatic potential of T24 cells.

CONCLUSION

According to our knowledge, we are the first to show, that combination of doxorubicin and metformin also worth considering in the treatment of bladder cancer. We showed that simultaneous administration of these cytostatic enhances the antiproliferative effect of drugs, but also limits cells' migratory potential.

Metformin as a Potential Antitumor Agent

Some recent findings suggest that metformin, an oral antidiabetic drug, may have antitumor properties. Studies have shown that metformin can alter cell metabolism, both tumor and immune cells, which can greatly influence disease outcome. In this review, we discuss the potential mechanisms in which metformin can directly induce apoptosis of tumor cells as well as mechanisms in which metformin can elicit or enhance antitumor immune response.

A Mini Review on Molecules Inducing Caspase-Independent Cell Death: A New Route to Cancer Therapy

Most anticancer treatments trigger tumor cell death through apoptosis, where initiation of proteolytic action of caspase protein is a basic need. But under certain circumstances, apoptosis is prevented by the apoptosis inhibitor proteins, survivin and Hsp70. Several drugs focusing on classical programmed death of the cell have been reported to have low anti-tumorogenic potency due to mutations in proteins involved in the caspase-dependent programmed cell death with intrinsic and extrinsic pathways. This review concentrates on the role of anti-cancer drug molecules targeting alternative pathways of cancer cell death for treatment, by providing a molecular basis for the new strategies of novel anti-cancer treatment. Under these conditions, active agents targeting alternative cell death pathways can be considered as potent chemotherapeutic drugs. Many natural compounds and other small molecules, such as inorganic and synthetic compounds, including several repurposing drugs, are reported to cause caspase-independent cell death in the system. However, few molecules indicated both caspase-dependent as well caspase-free cell death in specific cancer lines. Cancer cells have alternative methods of caspase-independent programmed cell death which are equally promising for being targeted by small molecules. These small molecules may be useful leads for rational therapeutic drug design, and can be of potential interest for future cancer-preventive strategies.

Characterization of the Lipid Metabolism in Bladder Cancer to Guide Clinical Therapy

Background

Bladder cancer is one of the most common malignancies of the urinary system with an unfavorable prognosis. More and more studies have suggested that lipid metabolism could influence the progression and treatment of tumors. However, there are few studies exploring the relationship between lipid metabolism and bladder cancer. This study aimed to explore the roles that lipid metabolism-related genes play in patients with bladder cancer.

Methods

TCGA_BLCA cohort and GSE13507 cohort were included in this study, and transcriptional and somatic mutation profiles of 309 lipid metabolism-related genes were analyzed to discover the critical lipid metabolism-related genes in the incurrence and progression of bladder cancer. Furthermore, the TCGA_BLCA cohort was randomly divided into training set and validation set, and the GSE13507 cohort was served as an external independent validation set. We performed the LASSO regression and multivariate Cox regression in training set to develop a prognostic signature and further verified this signature in TCGA_BLCA validation set and GSE13507 external validation set. Finally, we systematically investigated the association between this signature and tumor microenvironment, drug response, and potential functions and then verified the differential expression status of signature genes in the protein level by immunohistochemistry.

Results

A novel 6-lipidmetabolism-related gene signature was identified and validated, and this risk score model could predict the prognosis of patients with bladder cancer. In addition, the prognostic model was tightly related to immune cell infiltration and tumor mutation burden. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) showed that mTOR signaling pathway, G2M checkpoint, fatty acid metabolism, and hypoxia were enriched in patients in the high-risk score groups. Furthermore, 3 therapies specific for bladder cancer patients in different risk scores were identified.

Conclusion

s. In conclusion, we investigated the lipid metabolism-related genes in bladder cancer through comprehensive bioinformatic analysis. A novel 6-gene signature associated with lipid metabolism for predicting the outcomes of patients with bladder cancer was conducted and validated. Furthermore, the risk score model could be utilized to indicate the choice of therapy in bladder cancer.