Given its high recurrence and rapid progress, bladder cancer (BLCA) treatment has become a major problem for clinicians. BLCA is difficult to control even with surgical resection and extensive use of chemotherapeutic drugs. The non-toxicity and ease of accessibility of natural compounds have attracted much attention in recent years. Flavonoids serve an essential role given their antioxidant, antibacterial, anticancer and cardiovascular properties. They are mainly divided into several subclasses; flavones, flavanones, flavonols, flavanols, anthocyanins isoflavones and chalcones. Over the years, the role of flavonoids in BLCA has been extensively studied. The present review provided a comprehensive overview of the classification of flavonoids and substantiate the role of epithelial-mesenchymal transition, cancer stem cells, angiogenesis, epigenetic regulation and programmed cell death in BLCA. The present review emphasized that flavonoids for BLCA treatment are worthy of further study and anti-BLCA drugs have huge prospects for clinical use. Contents 1. Introduction 2. Mechanism 3. Flavonoids on BLCA 4. Discussion and outlook 5. Conclusion
Background: Clear cell renal cell carcinoma (ccRCC) is a malignancy with a high incidence rate and poor prognosis worldwide. Copper ionophore–induced death (CID) plays an important role in cancer progression.Methods: One training and three validation datasets were acquired from TCGA, GEO and ArrayExpress. K-means clustering was conducted to identify the CID subtypes. The ESTIMATE and CIBERSORT algorithms were employed to illustrate the immune microenvironment of ccRCC. LASSO Cox regression was applied to construct the CID feature-based prognostic model. The immunotherapy cohort was acquired from the literature to explore the potential risk scores for predicting immunotherapy responsiveness.Results: Two CID-related cancer subtypes of ccRCC were identified that performed different immune microenvironment characteristics and prognosis. Based on the identified subtypes, we analyzed the biological heterogeneity and constructed a gene prognostic model. The prognostic model performed well in one training dataset, three validation datasets, and different clinical pathological groups. The prognostic model has a good potential for predicting cancer immune features and immunotherapy responsiveness.Conclusion: CID plays an important role in the tumor microenvironment progression of ccRCC. The robust gene prognostic model developed can help predict cancer prognosis, immune features, and immunotherapy responsiveness.
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