Sun Yat-sen University

About: Sun Yat-sen University is a education organization based out in Guangzhou, Guangdong, China. It is known for research contribution in the topics: Population & Cancer. The organization has 115149 authors who have published 113763 publications receiving 2286465 citations. The organization is also known as: Zhongshan University & SYSU.

Knockdown of miR-21 in human breast cancer cell lines inhibits proliferation, in vitro migration and in vivo tumor growth

Abstract: MicroRNAs (miRNAs) are a class of small non-coding RNAs (20 to 24 nucleotides) that post-transcriptionally modulate gene expression. A key oncomir in carcinogenesis is miR-21, which is consistently up-regulated in a wide range of cancers. However, few functional studies are available for miR-21, and few targets have been identified. In this study, we explored the role of miR-21 in human breast cancer cells and tissues, and searched for miR-21 targets. We used in vitro and in vivo assays to explore the role of miR-21 in the malignant progression of human breast cancer, using miR-21 knockdown. Using LNA silencing combined to microarray technology and target prediction, we screened for potential targets of miR-21 and validated direct targets by using luciferase reporter assay and Western blot. Two candidate target genes (EIF4A2 and ANKRD46) were selected for analysis of correlation with clinicopathological characteristics and prognosis using immunohistochemistry on cancer tissue microrrays. Anti-miR-21 inhibited growth and migration of MCF-7 and MDA-MB-231 cells in vitro, and tumor growth in nude mice. Knockdown of miR-21 significantly increased the expression of ANKRD46 at both mRNA and protein levels. Luciferase assays using a reporter carrying a putative target site in the 3' untranslated region of ANKRD46 revealed that miR-21 directly targeted ANKRD46. miR-21 and EIF4A2 protein were inversely expressed in breast cancers (rs = -0.283, P = 0.005, Spearman's correlation analysis). Knockdown of miR-21 in MCF-7 and MDA-MB-231 cells inhibits in vitro and in vivo growth as well as in vitro migration. ANKRD46 is newly identified as a direct target of miR-21 in BC. These results suggest that inhibitory strategies against miR-21 using peptide nucleic acids (PNAs)-antimiR-21 may provide potential therapeutic applications in breast cancer treatment.

Upregulated IL-23 and IL-17 in Behçet patients with active uveitis.

Abstract: PURPOSE. Behcet disease (BD) is a systemic inflammatory dis- ease presumably caused by an autoimmune response. The interleukin (IL)-23/IL-17 pathway has been demonstrated to be involved in the development and maintenance of certain in- flammatory diseases. This study was designed to investigate the role of IL-23 and IL-17 in BD. METHODS. IL-23p19 mRNA in peripheral blood mononuclear cells (PBMCs) was examined using RT-PCR. The levels of IL-23, IL-17, and IFN- in sera or PBMCs were detected by ELISA. Flow cytometry was used to evaluate the frequencies of IL-17- producing and IFN--producing T cells and the expression of CD45RO. RESULTS. Results showed that the expression of IL-23p19 mRNA, IL-23, IL-17, and IFN- was markedly elevated in BD patients with active uveitis. The frequencies of IL-17-produc- ing and IFN--producing T cells from PBMCs were significantly upregulated in BD patients with active uveitis. The increased IL-17 (3.10% 0.53%) in BD patients with active uveitis was primarily produced by CD45RO memory T cells. Recombi- nant (r) IL-23 could upregulate IL-17 production by poly- clonally stimulated PBMCs, whereas interferon (IFN)- down- regulated IL-17 production. CONCLUSIONS. These findings reveal that the levels of IL-23, IL-17, and IFN- are elevated in BD patients with active uveitis, and they suggest that the IL-23/IL-17 pathway together with IFN- is associated with the active intraocular inflammation in BD patients. (Invest Ophthalmol Vis Sci. 2008;49:3058 -3064)

Antineoplastic Mechanisms of Niclosamide in Acute Myelogenous Leukemia Stem Cells: Inactivation of the NF-κB Pathway and Generation of Reactive Oxygen Species

Abstract: NF-kappaB may be a potential therapeutic target for acute myelogenous leukemia (AML) because NF-kappaB activation is found in primitive human AML blast cells. In this report, we initially discovered that the potent antineoplastic effect of niclosamide, a Food and Drug Administration-approved antihelminthic agent, was through inhibition of the NF-kappaB pathway in AML cells. Niclosamide inhibited the transcription and DNA binding of NF-kappaB. It blocked tumor necrosis factor-induced IkappaBalpha phosphorylation, translocation of p65, and expression of NF-kappaB-regulated genes. Niclosamide inhibited the steps TAK1-->IkappaB kinase (IKK) and IKK-->IkappaBalpha. Niclosamide also increased the levels of reactive oxygen species (ROS) in AML cells. Quenching ROS by the glutathione precursor N-acetylcysteine attenuated niclosamide-induced apoptosis. Our results together suggest that niclosamide inhibited the NF-kappaB pathway and increased ROS levels to induce apoptosis in AML cells. On translational study of the efficacy of niclosamide against AML, niclosamide killed progenitor/stem cells from AML patients but spared those from normal bone marrow. Niclosamide was synergistic with the frontline chemotherapeutic agents cytarabine, etoposide, and daunorubicin. It potently inhibited the growth of AML cells in vitro and in nude mice. Our results support further investigation of niclosamide in clinical trials of AML patients.

Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation

Abstract: Domain adaptation enables the learner to safely generalize into novel environments by mitigating domain shifts across distributions. Previous works may not effectively uncover the underlying reasons that would lead to the drastic model degradation on the target task. In this paper, we empirically reveal that the erratic discrimination of the target domain mainly stems from its much smaller feature norms with respect to that of the source domain. To this end, we propose a novel parameter-free Adaptive Feature Norm approach. We demonstrate that progressively adapting the feature norms of the two domains to a large range of values can result in significant transfer gains, implying that those task-specific features with larger norms are more transferable. Our method successfully unifies the computation of both standard and partial domain adaptation with more robustness against the negative transfer issue. Without bells and whistles but a few lines of code, our method substantially lifts the performance on the target task and exceeds state-of-the-arts by a large margin (11.5% on Office-Home and 17.1% on VisDA2017). We hope our simple yet effective approach will shed some light on the future research of transfer learning. Code is available at https://github.com/jihanyang/AFN.