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Calycosin (Caly), a flavonoid compound, demonstrates a variety of beneficial properties. However, the specific mechanisms behind Caly's anticancer effects remain largely unexplored. Network pharmacology was used to explore the potential targets of Caly in renal cancer. Additionally, RNA-seq sequencing was used to detect changes in genes in renal cancer cells after Caly treatment. Validation was carried out through quantitative reverse transcription-PCR and Western blot analysis. The luciferase reporter assay was applied to pinpoint the interaction site between MAZ and HAS2. Furthermore, the immunoprecipitation assay was utilized to examine the ubiquitination and degradation of MAZ. In vivo experiments using cell line-derived xenograft mouse models were performed to assess Calycosin's impact on cancer growth. Network pharmacology research suggests Caly plays a role in promoting apoptosis and inhibiting cell adhesion in renal cancer. In vitro, Caly has been observed to suppress proliferation, colony formation, and metastasis of renal cancer cells while also triggering apoptosis. Additionally, it appears to diminish hyaluronic acid synthesis by downregulating HAS2 expression. MAZ is identified as a transcriptional regulator of HAS2 expression. Calycosin further facilitates the degradation of MAZ via the ubiquitin-proteasome pathway. Notably, Caly demonstrates efficacy in reducing the growth of renal cell carcinoma xenograft tumors in vivo. Our findings indicate that Caly suppresses the proliferation, metastasis, and progression of renal cell carcinoma through its action on the MAZ/HAS2 signaling pathway. Thus, Caly represents a promising therapeutic candidate for the treatment of renal cell carcinoma., (© 2024 John Wiley & Sons, Ltd.)

Patients with clear cell renal cell carcinoma (ccRCC) typically face aggressive disease progression when metastasis occurs. Here, we screened and identified differentially expressed genes in three microarray datasets from the Gene Expression Omnibus database. We identified 112 differentially expressed genes with functional enrichment as candidate prognostic biomarkers. Lasso Cox regression suggested 10 significant oncogenic hub genes involved in earlier recurrence and poor prognosis of ccRCC. Receiver operating characteristic curves validated the specificity and sensitivity of the Cox regression penalty used to predict prognosis. The area under the curve indexes of the integrated genes scores were 0.758 and 0.772 for overall and disease-free survival, respectively. The prognostic values of ADAMTS9, C1S, DPYSL3, H2AFX, MINA, PLOD2, RUNX1, SLC19A1, TPX2 , and TRIB3 were validated through an analysis of 10 hub genes in 380 patients with ccRCC from a real-world cohort. The expression levels of were of high prognostic value for predicting metastatic potential. These findings will likely significantly contribute to our understanding of the underlying mechanisms of ccRCC, which will enhance efforts to optimize therapy., Competing Interests: None., (AJTR Copyright © 2020.)

Objectives: To analyze the clinical and pathological informations of metastatic prostate cancer patients to find the predictive factors of the survival., Methods: To filter 364 cases of metastatic prostate cancer in the 940 cases of prostate cancer that were treated in Cancer Hospital Fudan University in Shanghai from March 1998 to June 2009, the cases had hormonal therapy and full clinical and pathological records. All the 364 cases were followed up and the clinical and pathological informations were analyzed, to find the predictive factors that related to the prognosis. Statistic software SPSS 15.0 was used for analysis. Cumulative survival was analyzed by the method of Kaplan-Meier. Cox regression was used for univariate and multivariate analysis. Log-rank method was used for the significance test., Results: The last follow-up date was 30th June 2009 and the median follow-up time was 24 months. At the final follow-up, 240 cases were alive, 109 cases were dead and 15 cases were lost to follow up. The median survival time of metastatic prostate cancer was 64 months, and the one-year, two-year, three-year, four-year, five-year survival rate was 92%, 78%, 66%, 60%, 54%. The univariate analysis indicated that Gleason score (P = 0.033), clinical stage (P < 0.001), the effectiveness of hormonal therapy (P < 0.001), the prostate specific antigen (PSA) nadir during hormonal therapy (P < 0.001) and the time from the start of hormonal therapy to the PSA nadir (P = 0.002) were predictive factors for the survival time of metastatic prostate cancer. The multivariate analysis indicated that the PSA nadir during hormonal therapy (P < 0.001) and the time from the start of hormonal therapy to the PSA nadir (P < 0.001) were independent factors that predict the survival time of metastatic prostate cancer., Conclusion: The PSA nadir during hormonal therapy and the time from the start of hormonal therapy to the PSA nadir are independent factors that predict the survival time of metastatic prostate cancer.