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Feng Z, Chen G, Huang Y, Zhang K, Wu G, Xing W, Wu Y, Zhou Y, Sun C. TAK-242 inhibits glioblastoma invasion, migration, and proneural-mesenchymal transition by inhibiting TLR4 signaling. Exp Cell Res 2024; 439:114091. [PMID: 38740168 DOI: 10.1016/j.yexcr.2024.114091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 04/02/2024] [Accepted: 05/11/2024] [Indexed: 05/16/2024]
Abstract
Resatorvid (TAK-242), a small-molecule inhibitor of Toll-like receptor 4 (TLR4), has the ability to cross the blood-brain barrier (BBB). In this study, we explored the role of TAK-242 on glioblastoma (GBM) invasion, migration, and proneural-mesenchymal transition (PMT). RNA sequencing (RNA-Seq) data and full clinical information of glioma patients were downloaded from the Chinese Glioma Genome Atlas (CGGA) and the Cancer Genome Atlas (TCGA) cohorts and then analyzed using R language; patients were grouped based on proneural (PN) and mesenchymal (MES) subtypes. Bioinformatics analysis was used to detect the difference in survival and TLR4-pathway expression between these groups. Cell viability assay, wound-healing test, and transwell assay, as well as an intracranial xenotransplantation mice model, were used to assess the functional role of TAK-242 in GBM in vitro and in vivo. RNA-Seq, Western blot, and immunofluorescence were employed to investigate the possible mechanism. TLR4 expression in GBM was significantly higher than in normal brain tissue and upregulated the expression of MES marker genes. Moreover, TAK-242 inhibited GBM progression in vitro and in vivo via linking with PMT, which could be a novel treatment strategy for inhibiting GBM recurrence.
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Affiliation(s)
- Zibin Feng
- Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Jiangsu, Suzhou 215006, China; Department of Neurosurgery, Honghui Hospital, Xi'an Jiaotong University, Xi'an 710054, Shaanxi Province, China
| | - Guangliang Chen
- Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Jiangsu, Suzhou 215006, China
| | - Yunfan Huang
- Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Jiangsu, Suzhou 215006, China
| | - Kai Zhang
- Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Jiangsu, Suzhou 215006, China
| | - Guanzhang Wu
- Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Jiangsu, Suzhou 215006, China
| | - Weixin Xing
- Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Jiangsu, Suzhou 215006, China
| | - Yue Wu
- Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Jiangsu, Suzhou 215006, China
| | - Youxin Zhou
- Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Jiangsu, Suzhou 215006, China.
| | - Chunming Sun
- Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Jiangsu, Suzhou 215006, China.
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Wu KL, Chou CY, Chang HY, Wu CH, Li AL, Chen CL, Tsai JC, Chen YF, Chen CT, Tseng CC, Chen JB, Wang IK, Hsu YJ, Lin SH, Huang CC, Ma N. Peritoneal effluent MicroRNA profile for detection of encapsulating peritoneal sclerosis. Clin Chim Acta 2022; 536:45-55. [PMID: 36130656 DOI: 10.1016/j.cca.2022.09.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 08/31/2022] [Accepted: 09/05/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Encapsulating peritoneal sclerosis (EPS) is a catastrophic complication of peritoneal dialysis (PD) with high mortality. Our aim is to develop a novel noninvasive microRNA (miRNA) test for EPS. METHODS We collected 142 PD effluents (EPS: 62 and non-EPS:80). MiRNA profiles of PD effluents were examined by a high-throughput real-time polymerase chain reaction (PCR) array to first screen. Candidate miRNAs were verified by single real-time PCR. The model for EPS prediction was evaluated by multiple logistic regression and machine learning. RESULTS Seven candidate miRNAs were identified from the screening of PCR-array of 377 miRNAs. The top five area under the curve (AUC) values with 5 miRNA-ratios were selected using 127 samples (EPS: 56 vs non-EPS: 71) to produce a receiver operating characteristic curve. After considering clinical characteristics and 5 miRNA-ratios, the accuracies of the machine learning model of Random Forest and multiple logistic regression were boosted to AUC 0.97 and 0.99, respectively. Furthermore, the pathway analysis of miRNA associated targeting genes and miRNA-compound interaction network revealed that these five miRNAs played the roles in TGF-β signaling pathway. CONCLUSION The model-based miRNA expressions in PD effluents may help determine the probability of EPS and provide further therapeutic opinion for EPS.
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Affiliation(s)
- Kun-Lin Wu
- Department of Biomedical Sciences and Engineering, Institute of Systems Biology and Bioinformatics, National Central University, Taoyuan, Taiwan; Division of Nephrology, Department of Internal Medicine, Taoyuan Armed Forces General Hospital, Taoyuan, Taiwan; Division of Nephrology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Che-Yi Chou
- Division of Nephrology, Department of Internal Medicine, Asia University Hospital, Taichung, Taiwan
| | - Hui-Yin Chang
- Department of Biomedical Sciences and Engineering, Institute of Systems Biology and Bioinformatics, National Central University, Taoyuan, Taiwan
| | - Chih-Hsun Wu
- Artificial Intelligence and E-Learning Center, National Chengchi University, Taiwan
| | - An-Lun Li
- Department of Biomedical Sciences and Engineering, Institute of Systems Biology and Bioinformatics, National Central University, Taoyuan, Taiwan
| | - Chien-Lung Chen
- Division of Nephrology, Department of Medicine, Landseed International Hospital, Taoyuan, Taiwan
| | - Jen-Chieh Tsai
- Department of Biomedical Sciences and Engineering, Institute of Systems Biology and Bioinformatics, National Central University, Taoyuan, Taiwan; Institute of Biotechnology, National Tsing Hua University, Hsinchu, Taiwan; Institute of Biotechnology and Pharmaceutical Research, National Health Research Institutes, Miaoli, Taiwan
| | - Yi-Fan Chen
- Interdisciplinary Program of Engineering, National Central University, Taoyuan, Taiwan
| | - Chiung-Tong Chen
- Institute of Biotechnology, National Tsing Hua University, Hsinchu, Taiwan; Institute of Biotechnology and Pharmaceutical Research, National Health Research Institutes, Miaoli, Taiwan
| | - Chin-Chung Tseng
- Division of Nephrology, Department of Internal Medicine, National Cheng Kung University Hospital Dou-Liou Branch, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Jin-Bor Chen
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and College of Medicine, Chang Gung University, Kaohsiung, Taiwan
| | - I-Kuan Wang
- Division of Nephrology and the Kidney Institute, China Medical University and Hospitals, Taichung, Taiwan
| | - Yu-Juei Hsu
- Division of Nephrology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Shih-Hua Lin
- Division of Nephrology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Chiu-Ching Huang
- Division of Nephrology and the Kidney Institute, China Medical University and Hospitals, Taichung, Taiwan.
| | - Nianhan Ma
- Department of Biomedical Sciences and Engineering, Institute of Systems Biology and Bioinformatics, National Central University, Taoyuan, Taiwan.
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