Recent studies indicated that the estrogen receptor beta (ERβ) could affect the progression of prostate and bladder tumors, however, its roles in the renal cell carcinoma (RCC), remain to be elucidated. Here, we provide clinical evidence that ERβ expression is correlated in a negative manner with the overall survival/disease-free survival in RCC patients. Mechanism dissection revealed that targeting ERβ with ERβ-shRNA and stimulating the transactivation of ERβ with 17β-estradiol or environmental endocrine disrupting chemicals, all resulted in altering the lncRNA HOTAIR expression. The ERβ-modulated HOTAIR is able to function via antagonizing several microRNAs, including miR-138, miR-200c, miR-204, or miR-217 to impact various oncogenes, including ADAM9, CCND2, EZH2, VEGFA, VIM, ZEB1, and ZEB2, to promote RCC proliferation and invasion. Together, the identification of the ERβ-HOTAIR axis may provide us new biomarkers and/or therapeutic targets to better suppress RCC progression in the future.

ABSTRACT

No abstract

BackgroundThe present study sought to identify a panel of DNA markers for noninvasive diagnosis using cell‐free DNA (cfDNA) from urine supernatant or cellular DNA from urine sediments of hematuria patients. A panel of 48 bladder cancer‐specific genes was selected. A next‐generation sequencing‐based assay with a cfDNA barcode‐enabled single‐molecule test was employed. Mutation profiles of blood, urine, and tumor sample from 16 bladder cancer patients were compared. Next, urinary cellular DNA and cfDNA were prospectively collected from 125 patients (92 bladder cancer cases and 33 controls) and analyzed using the 48‐gene panel. The individual gene markers and combinations of markers were validated according to the pathology results. The mean areas under the receiver operating characteristic (ROC) curves (AUCs) obtained with the various modeling approaches were calculated and compared. ResultsThis pilot study of 16 bladder cancer patients demonstrated that gene mutations in urine supernatant and sediments had better concordance with cancer tissue as compared with plasma. Logistic analyses suggested two powerful combinations of genes for genetic diagnostic modeling: five genes for urine supernatant (TERT, FGFR3, TP53, PIK3CA, and KRAS) and seven genes for urine sediments (TERT, FGFR3, TP53, HRAS, PIK3CA, KRAS, and ERBB2). The accuracy of the five‐gene panel and the seven‐gene panel in the validation cohort yielded AUCs of 0.94 [95% confidence interval (CI) 0.91–0.97] and 0.91 (95% CI 0.86–0.96), respectively. With the addition of age and gender, the diagnostic power of the urine supernatant five‐gene model and the urine sediment seven‐gene model improved as the revised AUCs were 0.9656 (95% CI 0.9368–0.9944) and 0.9587 (95% CI 0.9291–0.9883). ConclusionscfDNA from urine bears great diagnostic potential. A five‐gene panel for urine supernatant and a seven‐gene panel for urine sediments are promising options for identifying bladder cancer in hematuria patients.