NEIL3 promotes cell proliferation of ccRCC via the cyclin D1-Rb-E2F1 feedback loop regulation

Nei endonuclease VIII-like 3 (NEIL3), a novel tumor-related gene, is differentially expressed and involved in pathophysiological processes in multiple tumors. However, the potential biological functions and molecular mechanisms of NEIL3 in human clear cell renal cell carcinoma (ccRCC) have not been identified. In this research, we demonstrated that NEIL3, transcriptionally activated by E2F1, served as an oncogene to facilitate cell proliferation and cell cycle progression and contribute to tumorigenesis via the cyclin D1-Rb-E2F1 feedback loop in ccRCC. First, we found that NEIL3 expression was upregulated in ccRCC tissues and cell lines compared with matched adjacent nontumor tissues and renal tubular epithelial cells and was also positively correlated with adverse clinicopathological characteristics, such as advanced cancer stages and higher tumor grades, and acted as an independent prognostic marker in ccRCC. Mechanistically, we demonstrated that NEIL3 promoted cell proliferation, DNA replication and cell cycle progression in vitro and tumor growth in vivo. Furthermore, we found that NEIL3 overexpression activated the cyclin D1-Rb-E2F1 pathway, and the E2F1 upregulation transcriptionally activated NEIL3 expression, thus forming a feedback loop. In addition, there was a positive correlation between NEIL3 and E2F1 expression in clinical specimens of ccRCC. Taken together, our results suggest that NEIL3 serves as a proto-oncogene in ccRCC and presents as a novel candidate for ccRCC diagnosis and treatment.

CircPTEN suppresses human clear cell renal carcinoma progression and resistance to mTOR inhibitors by targeting epigenetic modification

Renal cell carcinoma (RCC) is known to be the most commonly diagnosed kidney cancer. Clear cell RCC (ccRCC) represents approximately 85 % of diagnosed RCC cases. Targeted therapeutics, such as multi-targeted tyrosine kinase inhibitors (TKI) and mTOR inhibitors, are widely used in ccRCC therapy. However, patients treated with mTOR and TKI inhibitors easily acquire drug resistance, making the therapy less effective. Here, we demonstrated that circPTEN inhibits the expression of its parental gene PTEN by reducing methylation of the PTEN promotor and inhibits GLUT1 expression by reducing m6A methylation of GLUT1, which suppresses ccRCC progression and resistance to mTOR inhibitors.

Juxtatumoral perinephric fat analysis in clear cell renal cell carcinoma

PURPOSE

The purpose of the study was to evaluate the feasibility of using contrast-enhanced computed tomography (CECT)-based texture analysis (CTTA) metrics to differentiate between juxtatumoral perinephric fat (JPF) surrounding low-grade (ISUP 1-2) versus high-grade (ISUP 3-4) clear cell renal cell carcinoma (ccRCC).

METHODS

In this IRB-approved study, we retrospectively queried the surgical database between June 2009 and April 2016 and identified 83 patients with pathologically confirmed ccRCC (low grade: n = 54, mean age = 61.5 years, 18F/35M; high grade n = 30, mean age = 61.7 years, 8F/22M) who also had pre-operative multiphase CT acquisitions. CT images were transferred to a 3D workstation, and nephrographic phase JPF regions were manually segmented. Using an in-house developed Matlab program, a CTTA panel comprising of texture metrics extracted using six different methods, histogram, 2D- and 3D-Gray-level co-occurrence matrix (GLCM) and Gray-level difference matrix (GLDM), and 2D-Fast Fourier Transform (FFT) analyses, was applied to the segmented images to assess JPF textural heterogeneity in low- versus high-grade ccRCC. Univariate analysis and receiver-operator characteristics (ROC) analysis were used to assess interclass differences in texture metrics and their prediction accuracy, respectively.

RESULTS

All methods except GLCM consistently revealed increased heterogeneity in the JPF surrounding high- versus low-grade ccRCC. FFT showed increased complexity index (p < 0.01). Histogram analysis showed increased kurtosis and positive skewness in (p < 0.03), and GLDM analysis showed decreased measure of correlation coefficient (MCC) (p < 0.04). Several of the GLCM metrics showed statistically significant (p < 0.04) textural differences between the two groups, but with no consistent trend. ROC analysis showed that MCC in GLCM analysis had an area under the curve of 0.75.

CONCLUSIONS

Our study suggests that CTTA of ccRCC shows statistically significant textural differences in JPF surrounding high- versus low-grade ccRCC.