ABSTRACT
Renal cell carcinoma (RCC) is the most common form of kidney cancer, with a high recurrence rate and metastasis capacity. Circular RNAs (circRNAs) have been suggested to act as the critical regulator in several diseases. This study is designed to investigate the role of circCSNK1G3 on RCC progression. We observed a highly expression of circCSNK1G3 in RCC tissues compared with normal tissues. The aberrantly circCSNK1G3 promoted the tumour growth and metastasis in RCC. In the subsequent mechanism investigation, we discovered that the tumour-promoting effects of circCSNK1G3 were, at least partly, achieved by up-regulating miR-181b. Increased miR-181b inhibits several tumour suppressor gene, including CYLD, LATS2, NDRG2 and TIMP3. Furthermore, the decreased TIMP3 leads to the enhanced epithelial to mesenchymal transition (EMT) process, thus promoting the cancer metastasis. In conclusion, we identified the oncogenic role of circCSNK1G3 in RCC progression and demonstrated the regulatory role of circCSNK1G3 induced miR-181b expression, which leads to TIMP3-mediated EMT process, thus resulting in tumour growth and metastasis in RCC. This study reveals the promise of circCSNK1G3 to be developed as a potential diagnostic and prognostic biomarker in the clinic. And the roles of circCSNK1G3 in cancer research deserve further investigation.
Subject(s)
Carcinoma, Renal Cell , Casein Kinase I/genetics , Kidney Neoplasms , MicroRNAs , Carcinoma, Renal Cell/genetics , Carcinoma, Renal Cell/pathology , Cell Line, Tumor , Cell Movement/genetics , Cell Proliferation/genetics , Epithelial-Mesenchymal Transition/genetics , Female , Gene Expression Regulation, Neoplastic , Humans , Kidney Neoplasms/genetics , Kidney Neoplasms/pathology , Male , MicroRNAs/genetics , MicroRNAs/metabolism , Protein Serine-Threonine Kinases , Tissue Inhibitor of Metalloproteinase-3/genetics , Tissue Inhibitor of Metalloproteinase-3/metabolism , Tumor Suppressor Proteins/geneticsABSTRACT
BACKGROUND: For the prognosis of patients with early gastric cancer (EGC), lymph node metastasis (LNM) plays a crucial role. A thorough and precise evaluation of the patient for LNM is now required. AIM: To determine the factors influencing LNM and to construct a prediction model of LNM for EGC patients. METHODS: Clinical information and pathology data of 2217 EGC patients downloaded from the Surveillance, Epidemiology, and End Results database were collected and analyzed. Based on a 7:3 ratio, 1550 people were categorized into training sets and 667 people were assigned to testing sets, randomly. Based on the factors influencing LNM determined by the training sets, the nomogram was drawn and verified. RESULTS: Based on multivariate analysis, age at diagnosis, histology type, grade, T-stage, and size were risk factors of LNM for EGC. Besides, nomogram was drawn to predict the risk of LNM for EGC patients. Among the categorical variables, the effect of grade (well, moderate, and poor) was the most significant prognosis factor. For training sets and testing sets, respectively, area under the receiver-operating characteristic curve of nomograms were 0.751 [95% confidence interval (CI): 0.721-0.782] and 0.786 (95%CI: 0.742-0.830). In addition, the calibration curves showed that the prediction model of LNM had good consistency. CONCLUSION: Age at diagnosis, histology type, grade, T-stage, and tumor size were independent variables for LNM in EGC. Based on the above risk factors, prediction model may offer some guiding implications for the choice of subsequent therapeutic approaches for EGC.