Emerging evidence have discovered that circular RNAs (circRNAs) may serve as diagnostic or tumor promising biomarkers. This study aimed to investigate how circular RNA ADAMTS14 (circADAMTS14) regulates microRNA‐572/ regulator of calcineurin 1(miR‐572/ RCAN1) in hepatocellular carcinoma (HCC). The expression profiles of circRNA/microRNA (mRNA) between HCC tissues and paired adjacent tissues were analyzed via microarray analysis. The expressions of circADAMTS14, miR‐572, and RCAN1 were measured by real‐time polymerase chain reaction (PCR). The protein expression level of RCAN1 in HCC cells was detected by western blot. The viability and apoptosis levels of HCC cell lines were measured by the cell counting Kit‐8 (CCK‐8) assay and fluorescence‐activated cell sorter. The invasiveness and migration of cells were detected based on the transwell and wound‐healing assay, respectively. The dual‐luciferase reporter assays were used to reveal circADAMTS14 and RCAN1 as a potential target of miR‐572, which was predicted by TargetScan and miRBase. The effect of circADAMTS14 on HCC cells was demonstrated by tumor formation in nude mice in vivo. CircADAMTS14 and RCAN1 were lowly expressed in HCC clinical specimens and cell lines using microarrays and qRT‐PCR, but miR‐572 inversely. Our study further verified the direct interaction between circADAMTS14 and RCAN1 with miR‐572 via the dual‐luciferase reporter gene assay. Overexpressed circADAMTS14 and RCAN1 induced apoptosis of HCC cells and inhibited cell proliferation and invasion. But overexpressed miR‐572 could decrease apoptosis of HCC cells and promote proliferation and invasion. In vivo, circADAMTS14 inhibited the tumor growth, correlated positively with the protein expression levels of RCAN1. Our results demonstrated that circADAMTS14 might suppress HCC progression through regulating miR‐572/ RCAN1 as the competing endogenous RNA.

Long non‐coding RNA Sox2 overlapping transcript (SOX2OT) was reported to be involved in progression of multiple cancers. However, the role and mechanism of SOX2OT in multiple myeloma (MM) has yet to be unravelled. In the present study, elevated SOX2OT levels are reported in MM cell lines and patient samples as compared to normal plasma cells (nPCs) and healthy donors, respectively. Knock‐down of SOX2OT led to a significant inhibition of cell proliferation, arrested cells at G0/G1 phase and induced cell apoptosis in MM samples in vitro, as well as slowed the growth of tumours in vivo. Additionally, our data indicated that SOX2OT functioned as a competing endogenous RNA (ceRNA) in MM cells that regulated miR‐144‐3p expression. Repression of miR‐144‐3p reversed the inhibition of MM development due to SOX2OT knock‐down. Our data also revealed that SOX2OT regulated the expression of the cellular‐mesenchymal to epithelial transition factor (c‐MET, a known target of miR‐143‐3p) by functioning as a sponge of miR‐144‐3p in MM samples. These data support that SOX2OT promotes MM progression through regulating the miR‐144‐3p/c‐MET axis, suggesting that SOX2OT might be as a potential therapeutic target for MM.

OBJECTIVES: To establish and verify a simple noninvasive model based on the left gastric vein (LGV) to predict the grade of esophageal varices (EV) and high-risk EV (HEV), to facilitate clinical follow-up and timely treatment. METHODS: We enrolled 320 patients with B-viral cirrhosis. All patients underwent endoscopy, laboratory tests, liver and spleen stiffness (SS), and ultrasonography. HEV were analyzed using the χ 2 test/ t test and logistic regression in the univariate and multivariate analyses, respectively. EV grades were analyzed using the variance/rank-sum test and logistic regression. A prediction model was derived from the multivariate predictors. RESULTS: In the training set, multivariate analysis showed that the independent factors of different EV grades were SS, LGV diameter, and platelet count (PLT). We developed the LGV diameter-SS to PLT ratio index (LSPI) and LGV diameter/PLT models without SS. The area under the receiver operating characteristic curve of the LSPI for diagnosis of small EV, medium EV, large EV, and HEV was 0.897, 0.899, 0.853, and 0.954, respectively, and that of the LGV/PLT was 0.882, 0.890, 0.837, and 0.942, respectively. For the diagnosis of HEV, the negative predictive value was 94.07% when LSPI < 19.8 and the positive predictive value was 91.49% when LSPI > 23.0. The negative predictive value was 95.92% when LGV/PLT < 5.15, and the positive predictive value was 86.27% when LGV/PLT > 7.40. The predicted values showed similar accuracy in the validation set. DISCUSSION: Under appropriate conditions, the LSPI was an accurate method to detect the grade of EV and HEV. Alternatively, the LGV/PLT may also be useful in diagnosing the varices when condition limited.