The Prognostic Hub Gene POLE2 Promotes BLCA Cell Growth via the PI3K/AKT Signaling Pathway.

BACKGROUND: BLCA is a common urothelial malignancy characterized by a high recurrence rate. Despite its prevalence, the molecular mechanisms underlying its development remain unclear. AIMS: This study aimed to explore new prognostic biomarkers and investigate the underlying mechanism of bladder cancer (BLCA). OBJECTIVE: The objective of this study is to identify key prognostic biomarkers for BLCA and to elucidate their roles in the disease. METHODS: We first collected the overlapping DEGs from GSE42089 and TCGA-BLCA samples for the subsequent weighted gene co-expression network analysis (WGCNA) to find a key module. Then, key module genes were analyzed by the MCODE algorithm, prognostic risk model, expression and immunohistochemical staining to identify the prognostic hub gene. Finally, the hub gene was subjected to clinical feature analysis, as well as cellular function assays. RESULTS: In WGCNA on 1037 overlapping genes, the blue module was the key module. After a series of bioinformatics analyses, POLE2 was identified as a prognostic hub gene in BLCA from potential genes (TROAP, POLE2, ANLN, and E2F8). POLE2 level was increased in BLCA and related to different clinical features of BLCA patients. Cellular assays showed that si-POLE2 inhibited BLCA proliferation, and si-POLE2+ 740Y-P in BLCA cells up-regulated the PI3K and AKT protein levels. CONCLUSION: In conclusion, POLE2 was identified to be a promising prognostic biomarker as an oncogene in BLCA. It was also found that POLE2 exerts a promoting function by the PI3K/AKT signaling pathway in BLCA.

Development and validation of a clinical-radiomics model for prediction of prostate cancer: a multicenter study.

PURPOSE: To develop an early diagnosis model of prostate cancer based on clinical-radiomics to improve the accuracy of imaging diagnosis of prostate cancer. METHODS: The multicenter study enrolled a total of 449 patients with prostate cancer from December 2017 to January 2022. We retrospectively collected information from 342 patients who underwent prostate biopsy at Minhang Hospital. We extracted T2WI images through 3D-Slice, and used mask tools to mark the prostate area manually. The radiomics features were extracted by Python using the "Pyradiomics" module. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for data dimensionality reduction and feature selection, and the radiomics score was calculated according to the correlation coefficients. Multivariate logistic regression analysis was used to develop predictive models. We incorporated the radiomics score, PI-RADS, and clinical features, and this was presented as a nomogram. The model was validated using a cohort of 107 patients from the Xuhui Hospital. RESULTS: In total, 110 effective radiomics features were extracted. Finally, 9 features were significantly associated with the diagnosis of prostate cancer, from which we calculated the radiomics score. The predictors contained in the individualized prediction nomogram included age, fPSA/tPSA, PI-RADS, and radiomics score. The clinical-radiomics model showed good discrimination in the validation cohort (C-index = 0.88). CONCLUSION: This study presents a clinical-radiomics model that incorporates age, fPSA/PSA, PI-RADS, and radiomics score, which can be conveniently used to facilitate individualized prediction of prostate cancer before prostate biopsy.

ARRDC3 regulates the targeted therapy sensitivity of clear cell renal cell carcinoma by promoting AXL degradation.

AXL plays crucial roles in the tumorigenesis, progression, and drug resistance of neoplasms; however, the mechanisms associated with AXL overexpression in tumors remain largely unknown. In this study, to investigate these molecular mechanisms, wildtype and mutant proteins of arrestin domain-containing protein 3 (ARRDC3) and AXL were expressed, and co-immunoprecipitation analyses were performed. ARRDC3-deficient cells generated using the CRISPR-Cas9 system were treated with different concentrations of the tyrosine kinase inhibitor sunitinib and subjected to cell biological, molecular, and pharmacological experiments. Furthermore, immunohistochemistry was used to analyze the correlation between ARRDC3 and AXL protein expressions in renal cancer tissue specimens. The experimental results demonstrated that ARRDC3 interacts with AXL to promote AXL ubiquitination and degradation, followed by the negative regulation of downstream signaling mechanisms, including the phosphorylation of protein kinase B and extracellular signal-regulated kinase. Notably, ARRDC3 deficiency decreased the sunitinib sensitivity of clear cell renal cell carcinoma (ccRCC) cells in a manner dependent on the regulation of AXL stability. Overall, our results suggest that ARRDC3 is a negative regulator of AXL and can serve as a novel predictor of sunitinib therapeutic response in patients with ccRCC.

Downregulation of the lncRNA ASB16-AS1 Decreases LARP1 Expression and Promotes Clear Cell Renal Cell Carcinoma Progression via miR-185-5p/miR-214-3p.

Clear cell renal cell carcinoma (ccRCC) comprises approximately 75% of renal cell carcinomas, which is one of the most common and lethal urologic cancers, with poor quality of life for patients and is a huge economic burden to health care systems. It is imperative we find novel prognostic and therapeutic targets for ccRCC clinical intervention. In this study, we found that the expression of the long noncoding RNA (lncRNA) ASB16-AS1 was downregulated in ccRCC tissues compared with non-diseased tissues and was also associated with advanced tumor stage and larger tumors. By constructing cell and mouse models, it was found that downregulated lncRNA ASB16-AS1 enhanced cell proliferation, migration, invasion, and promoted tumor growth and metastasis. Furthermore, by performing bioinformatics analysis, biotinylated RNA pull-downs, AGO2-RIP, and luciferase reporter assays, our findings showed that downregulated ASB16-AS1 decreased La-related protein 1 (LARP1) expression by inhibiting miR-185-5p and miR-214-3p. Furthermore, it was found that overexpression of LARP1 reversed the promotive effects of downregulated ASB16-AS1 on ccRCC cellular progression. Our results revealed that downregulated ASB16-AS1 promotes ccRCC progression via a miR-185-5p-miR-214-3p-LARP1 pathway. We suggest that this pathway could be used to monitor prognosis and presents therapeutic targets for ccRCC clinical management.

Mechanism and function of decreased FOXO1 in renal cell carcinoma.

BACKGROUND AND OBJECTIVES: Forkhead box O-class 1 (FOXO1), a putative tumor suppressor, is dysregulated in many cancers. Our study aims to reveal the underlying functions and regulation mechanisms of FOXO1 in renal cell carcinoma (RCC). METHODS: The clinical significance of FOXO1 expression in surgically resected specimens was assessed by immunohistochemistry. The siRNAs targeted FOXO1 and miR-27a inhibitor were transfected into RCC cells. QRT-PCR, Western blot, and cell proliferation assay were used to assess the expression and function of FOXO1 and miR-27a. RESULTS: The positive immunostaining for FOXO1 was low in 51 RCC samples compared with 15 normal kidney tissues. And the expression of FOXO1 was related with RCC subtypes and the grade and stage in clear cell RCC (cRCC) (P < 0.05). Inhibition of FOXO1 promoted proliferation of 769-P cells. However, upregulation of FOXO1 by miR-27a inhibitor was accompanied by the anti-proliferative effect in cells of 786-O and Caki-1. Furthermore, the expression of FOXO1 mRNA and miR-27a had inverse relation in eight cRCC samples. CONCLUSION: Reduced expression of FOXO1 is common in RCC and a potentially suitable marker of different histological subtypes and prognosis of cRCC. Increasing expression of FOXO1 by the miR-27a inhibitor could prevent cell growth.

Diagnostic value of human epididymis protein 4 compared with mesothelin for ovarian cancer: a systematic review and meta-analysis.

BACKGROUND AND PURPOSE: Ovarian cancer is the leading cause of death among gynecologic cancers because of the lack of effective early detection methods. Accuracies of the human epididymis protein 4 (HE4) and mesothelin in detecting ovarian cancer have never been systematically assessed. The current systematic review aimed to tackle this issue. METHODS: MEDLINE, EMBASE, and Cochrane databases were searched (September 1995-November 2011) for studies on the diagnostic performances of HE4 and mesothelin in differentiating ovarian cancer from other benign gynecologic diseases. QUADAS items were used to evaluate the qualities of the studies. Meta-DiSc software was used to handle data from the included studies and to examine heterogeneity. All included studies for diagnostic performance were combined with sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratios (DORs) with 95% confidence intervals (CIs), summary receiver operating characteristic (SROC) curves, and areas under the SROC curves (AUC). RESULTS: A total of 18 studies and 3,865 patients were eligible for the final analysis. The pooled sensitivity estimates for HE4 (74.4%) were significantly higher than those for mesothelin (49.3%). The pooled specificity estimates for mesothelin (94.5%) were higher than those for HE4 (85.8%). The pooled DOR estimates for HE4 (26.22) were higher than those for mesothelin (24.01). The SROC curve for HE4 showed better diagnostic accuracy than that for mesothelin. The PLR and NLR of HE4 were 6.33 (95% CI: 3.58 to 11.18) and 0.27 (95% CI: 0.21 to 0.34), respectively. The PLR and NLR for mesothelin were 11.0 (95% CI: 6.21 to 19.59) and 0.51 (95% CI: 0.42 to 0.62), respectively. The combination of the two tumor markers or their combination with CA-125 increased sensitivity and specificity to different extents. CONCLUSION: The diagnostic accuracy of HE4 in differentiating ovarian cancer from other benign gynecologic diseases is better than that of soluble mesothelin-related protein. Combinations of two or more tumor markers show more sensitivity and specificity.

Hsa-let-7a functions as a tumor suppressor in renal cell carcinoma cell lines by targeting c-myc.

Widespread functions of the c-myc pathway play a crucial role in renal cell carcinoma (RCC) carcinogenesis. Thus, we evaluated the connection between proto-oncogenic c-myc and anti-neoplastic hsa-let-7a (let-7a) in RCC cell lines. The levels of c-myc and let-7a in 3 RCC cell lines (769P, Caki-1 and 786O) were measured after transfecting the cells with let-7a mimics or a negative control. The change in c-myc protein level was confirmed by Western blot. The anti-neoplastic function of let-7a was evaluated using cell counting kit-8 (CCK-8) for proliferation analysis and cell flow cytometry for cell cycle analysis. The changes of downstream targets of c-myc were measured using reverse transcription quantitative real-time PCR (qRT-PCR). Our results suggest for the first time that let-7a acts as a tumor suppressor in RCC cell lines by down-regulating c-myc and c-myc target genes such as proliferating cell nuclear antigen (PCNA), cyclin D1 (CCND1) and the miR17-92 cluster, which is accompanied by proliferation inhibition and cell cycle arrest.

Comprehensive analysis of clinical significance of stem-cell related factors in renal cell cancer.

BACKGROUND: C-MYC, LIN28, OCT4, KLF4, NANOG and SOX2 are stem cell related factors. We detected whether these factors express in renal cell carcinoma (RCC) tissues to study their correlations with the clinical and pathological characteristics. METHODS: The expressions of c-MYC, LIN28, SOX2, KLF4, OCT4 and NANOG in 30 RCC patients and 5 non-RCC patients were detected with quantitative real-time reverse transcription-PCR (qRT-PCR). The data were analyzed with Wilcoxon signed rank sum test and x2 test. RESULTS: In RCC group, c-MYC expression was significantly higher in RCC tissues compared with normal tissues (P < 0.05). The expression levels of OCT4, KLF4, NANOG and SOX2 were significantly lower in RCC tissues compared with normal tissues (P < 0.05). LIN28 expression level was not significant. No difference was observed when it comes to clinical and pathological characteristics such as gender, age, tumor size, cTNM classification and differentiation status (P > 0.05). Also the expression levels of all above factors were not significantly changed in non-RCC group (P > 0.05). CONCLUSIONS: The present analysis strongly suggests that altered expression of several stem cell related factors may play different roles in RCC. C-MYC may function as an oncogene and OCT4, KLF4, NANOG and SOX2 as tumor suppressors.