LncRNA MAGI2-As3 Suppresses the Proliferation and Invasion of Cervical Cancer by Sponging MiR-15b.

BACKGROUND: Cervical cancer is the leading cause of cancer deaths among women, and more than 85% of cervical cancer deaths occur in low and middle-income countries. The purpose of this study is to investigate the functions of MAGI2-AS3 and miR-15b in cervical cancer. MATERIALS AND METHODS: The mRNA levels of MAGI2-AS3, miR-15b, and CCNE1 were evaluated using RT-qPCR assay. Dual-luciferase reporter gene assay was used to confirm whether miR-15b binds to CCNE1. RESULTS: LncRNA MAGI2-AS3 was downregulated, while miR-15b was upregulated in cervical cancer. Cervical cancer patients with low expression of MAGI2-AS3 have a poor prognosis. Upregulation of MAGI2-AS3 inhibited proliferative and invasive abilities of HeLa cells via regulating the expression of miRNA-15b. MiR-15b inhibitor suppressed cell proliferation and invasion. CCNE1 was a direct target gene of miR-15b, which binds to the 3'-UTR of its mRNA. MiR-15b partially reversed the inhibitory effect of overexpression of MAGI2-AS3 on the proliferation and invasion of HeLa cells. MAGI2-AS3 mediated the expression of CCNE1 in HeLa cells. CONCLUSION: LncRNA MAGI2-AS3 inhibits the proliferation and invasion of cervical cancer cells via the miRNA-15/CCNE1 axis. Our results illustrates that MAGI2-AS3 can be used as a useful clinical predictor for early diagnosis and prognosis assessment of cervical cancer.

Effect of Combination of Traditional Chinese Medicine with Western Medicine on Endometrial Carcinoma and Its Influence on Ultrasound, MRI, Tumor Markers HE4 and CA125.

OBJECTIVE: To study the clinical efficacy of integrated traditional Chinese medicine (TCM) and Western medicine (WM) in treating endometrial cancer and the influence on ultrasound, magnetic resonance imaging (MRI), tumor markers, human epididymis protein 4 (HE4) and carbohydrate antigen 125 (CA125). METHOD: A total of 152 cases of patients with endometrial carcinoma were randomly divided into two groups: the TCM + WM group and the WM group. The WM group was treated with megestrol acetate tablets, and the TCM + WM group was treated with Radix Astragali injection on the basis of the control group. The levels of inflammatory factors, HE4 and CA125 in serum, were detected using enzyme-linked immunosorbent assay (ELISA) or radioimmunoassay. The characteristics of ultrasound images and MRI images were observed and recorded. Toxicity, side effects, and the 3-year cumulative survival rate after treatment were assessed. RESULTS: After treatment, the levels of interleukin-4 (IL-4), tumor necrosis factor-alpha (TNF-α), and high-sensitivity C-reactive protein (hs-CRP) in both groups decreased, and the decrease in the TCM + WM group was more obvious than that in the WM group. There were statistically significant differences between the two groups in lesion shape, boundary, blood flow signal, lesion diameter, resistance index (RI), echo, intima thickness, and muscle layer infiltration from transvaginal ultrasound images after treatment. The diameter, echo, boundary, shape, composition, and enhancement degree of lesions between the two groups have a significant difference. Moreover, the levels of serum HE4 and CA125 in both groups decreased after treatment, and the decrease in the TCM + WM group was more obvious than that in the WM group. There were statistically significant differences between the two groups in the occurrence of myelosuppression, abnormal liver function, decreased platelet number, gastrointestinal reactions, leukopenia, and cardiotoxicity. After three years of follow-up, the cumulative survival rate of the TCM + WM group was 76.32%, and the cumulative survival rate of the WM group was 57.89%. CONCLUSION: Radix Astragali injection combined with megestrol acetate tablets has obvious therapeutic effects against endometrial cancer. Through vaginal ultrasonography and MRI, it can significantly improve the size, shape, and blood flow signals of patients' lesions, reduce the level of serum inflammatory factors and tumor markers HE4 and CA125, reduce the incidence of toxic and side reactions, improve the patient's immunity, improve the patient's condition significantly, and prolong the survival time of patients.

Long Non-Coding RNA (LncRNA) HOXA11-AS Promotes Breast Cancer Invasion and Metastasis by Regulating Epithelial-Mesenchymal Transition.

BACKGROUND To detect the expression of lncRNA HOXA11-AS and its biological effect in breast cancer. MATERIAL AND METHODS In this study, fluorescent quantitative real-time PCR (qRT-PCR), MTT assay and clone formation assay, flow cytometry, Transwell assay and wound healing assay, immunofluorescence, and Western blot analysis were conducted to detect the expression of lncRNA HOXA11-AS, cell proliferation activity, cell apoptosis rate and cell cycle distribution, the changes of cell invasion and metastasis capacity, and the expressions of molecular markers of epithelial-mesenchymal transition (EMT), respectively. Additionally, a nude mouse metastatic tumor model was established to study the influence of lncRNA HOXA11-AS on invasion and metastasis capacity of breast cancer cells. RESULTS The qRT-PCR experiment results showed that HOXA11-AS expression in breast cancer tissue of 50 patients was relatively higher than that in tissue adjacent to cancer. MTT assay suggested that tumor cell proliferation capacity was suppressed followed by the knockdown of lncRNA HOXA11-AS expression in MDA-MB-231 and MCF-7 cells; flow cytometry results demonstrated that interfering in lncRNA HOXA11-AS could induce tumor cell apoptosis and promote cell cycle progression to be arrested in G1/G0 stage; experiments in vivo/vitro manifested that interfering in lncRNA HOXA11-AS could inhibit tumor cell invasion and migration capacity by affecting the expressions of EMT-related molecular markers (E-cadherin, N-cadherin, Vimentin). CONCLUSIONS High expression of lncRNA HOXA11-AS promotes breast cancer invasion and metastasis by affecting EMT, and interfering in lncRAN HOXA11-AS expression provides a theoretical basis and important molecular target for inhibiting the distant metastasis of breast cancer in clinical practice.

A Feature-Free 30-Disease Pathological Brain Detection System by Linear Regression Classifier.

AIM: Alzheimer's disease patients are increasing rapidly every year. Scholars tend to use computer vision methods to develop automatic diagnosis system. (Background) In 2015, Gorji et al. proposed a novel method using pseudo Zernike moment. They tested four classifiers: learning vector quantization neural network, pattern recognition neural network trained by Levenberg-Marquardt, by resilient backpropagation, and by scaled conjugate gradient. METHOD: This study presents an improved method by introducing a relatively new classifier-linear regression classification. Our method selects one axial slice from 3D brain image, and employed pseudo Zernike moment with maximum order of 15 to extract 256 features from each image. Finally, linear regression classification was harnessed as the classifier. RESULTS: The proposed approach obtains an accuracy of 97.51%, a sensitivity of 96.71%, and a specificity of 97.73%. CONCLUSION: Our method performs better than Gorji's approach and five other state-of-the-art approaches. Therefore, it can be used to detect Alzheimer's disease.