RESUMO
BACKGROUND: In hepatocellular carcinoma (HCC), abnormal expression of multiple microRNAs (miRNAs) has been shown to be involved in the malignant biological behavior of liver cancer. The vast majority of liver cancer cases in China are closely related to hepatitis B virus (HBV) infection, but there are few studies on the changes of miRNA expression in the progression from HBV infection to hepatoma. AIM: To explore the role of miRNAs in the progression of HBV infection to cirrhosis and even to liver cancer. METHODS: We screened differentially expressed miRNAs in 40 HBV cirrhosis, 40 normal and 15 HCC tissues by using a TaqMan Low Density Array and real time quantitative polymerase chain reaction. To evaluate the power of the selected miRNAs to predict disease, we calculated the area under the receiver-operating-characteristic curves. The overall survival of HBV cirrhosis patients was analyzed via Kaplan-Meier analysis. RESULTS: The levels of miR-375, miR-122 and miR-143 were significantly lower in HBV cirrhosis tissues, while miR-224 was significantly higher than in the controls (P < 0.0001). The area under the curves of the receiver-operating-characteristic curve for the 4-miRNA panel was 0.991 (95%CI: 0.974-1). Patients with a lower expression level of miR-224 or higher expression levels of miR-375, miR-122 and miR-143 had longer overall survival. CONCLUSION: The four miRNAs (miR-375, miR-122, miR-143 and miR-224) may be helpful for early diagnosis of HBV infection, HBV cirrhosis, and prediction of its overall survival.
RESUMO
BACKGROUND: Early screening for colorectal cancer (CRC) is important in clinical practice. However, the currently methods are inadequate because of high cost and low diagnostic value. AIM: To develop a new examination method based on the serum biomarker panel for the early detection of CRC. METHODS: Three hundred and fifty cases of CRC, 300 cases of colorectal polyps and 360 cases of normal controls. Combined with the results of area under curve (AUC) and correlation analysis, the binary Logistic regression analysis of the remaining indexes which is in accordance with the requirements was carried out, and discriminant analysis, classification tree and artificial neural network analysis were used to analyze the remaining indexes at the same time. RESULTS: By comparison of these methods, we obtained the ability to distinguish CRC from healthy control group, malignant disease group and benign disease group. Artificial neural network had the best diagnostic value when compared with binary logistic regression, discriminant analysis, and classification tree. The AUC of CRC and the control group was 0.992 (0.987, 0.997), sensitivity and specificity were 98.9% and 95.6%. The AUC of the malignant disease group and benign group was 0.996 (0.992, 0.999), sensitivity and specificity were 97.4% and 96.7%. CONCLUSION: Artificial neural network diagnosis method can improve the sensitivity and specificity of the diagnosis of CRC, and a novel assistant diagnostic method was built for the early detection of CRC.
RESUMO
The highly refractory nature of cervical cancer to chemotherapeutic drugs and its epithelial-to-mesenchymal transition (EMT) are the key reasons contributing to the poor prognosis of this disease. Golgi Membrane Protein 1 (GOLM1), a protein involved in the trafficking of proteins through the Golgi apparatus, has been shown to be oncogenic in a variety of human cancers. Herein, we found GOLM1 was markedly up-regulated in cervical cancer and GOLM1 down-expression enhanced the anti-tumor effect of methotrexate. By performing mechanistic studies using both in vitro and in vivo models, we found that GOLM1 could target matrix metallopeptidase 13 (MMP13), a member of the MMPs, and regulate the EMT process. Moreover, altered EMT progression compromised the chemotherapy-enhancing effects of GOLM1 knock-down. Finally, we found significantly higher levels of GOLM1 and MMP13 in cervical cancer tissues compared with adjacent noncancerous tissues, and this was also associated with poor cervical cancer patients' prognosis. Taken together, our results suggest that the GOLM1/MMP13/EMT axis is an important factor involved in regulating methotrexate in cervical cancer, and highlights the potential of novel GOLM1-based clinical modalities as a therapeutic approach in cervical cancer patients.
