التفاصيل البيبلوغرافية
| العنوان: |
Identifying and characterizing drug sensitivity-related lncRNA-TF-gene regulatory triplets. |
| المؤلفون: |
Hu, Congxue1 (AUTHOR), Xu, Yingqi1 (AUTHOR), Li, Feng1 (AUTHOR), Mi, Wanqi1 (AUTHOR), Yu, He1 (AUTHOR), Wang, Xinran1 (AUTHOR), Wen, Xin1 (AUTHOR), Chen, Shuaijun1 (AUTHOR), Li, Xia1,2 (AUTHOR), Xu, Yanjun1 (AUTHOR) zhangyp@hrbmu.edu.cn, Zhang, Yunpeng1 (AUTHOR) zhangyp@hrbmu.edu.cn |
| المصدر: |
Briefings in Bioinformatics. Sep2022, Vol. 23 Issue 5, p1-13. 13p. |
| مصطلحات موضوعية: |
*RANDOM walks, DRUG laws, PROGNOSIS, DRUG resistance, SURVIVAL analysis (Biometry) |
| مستخلص: |
Recently, many studies have shown that lncRNA can mediate the regulation of TF-gene in drug sensitivity. However, there is still a lack of systematic identification of lncRNA-TF-gene regulatory triplets for drug sensitivity. In this study, we propose a novel analytic approach to systematically identify the lncRNA-TF-gene regulatory triplets related to the drug sensitivity by integrating transcriptome data and drug sensitivity data. Totally, 1570 drug sensitivity-related lncRNA-TF-gene triplets were identified, and 16 307 relationships were formed between drugs and triplets. Then, a comprehensive characterization was performed. Drug sensitivity-related triplets affect a variety of biological functions including drug response-related pathways. Phenotypic similarity analysis showed that the drugs with many shared triplets had high similarity in their two-dimensional structures and indications. In addition, Network analysis revealed the diverse regulation mechanism of lncRNAs in different drugs. Also, survival analysis indicated that lncRNA-TF-gene triplets related to the drug sensitivity could be candidate prognostic biomarkers for clinical applications. Next, using the random walk algorithm, the results of which we screen therapeutic drugs for patients across three cancer types showed high accuracy in the drug-cell line heterogeneity network based on the identified triplets. Besides, we developed a user-friendly web interface-DrugSETs (http://bio-bigdata.hrbmu.edu.cn/DrugSETs/) available to explore 1570 lncRNA-TF-gene triplets relevant with 282 drugs. It can also submit a patient's expression profile to predict therapeutic drugs conveniently. In summary, our research may promote the study of lncRNAs in the drug resistance mechanism and improve the effectiveness of treatment. [ABSTRACT FROM AUTHOR] |
|
Copyright of Briefings in Bioinformatics is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Business Source Index |
Full Text Finder