期刊
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
卷 23, 期 12, 页码 -出版社
MDPI
DOI: 10.3390/ijms23126732
关键词
diffuse large B cell lymphoma (DLBCL); deep neural network; drug discovery; drug combination
资金
- Ministry of Science and Technology [MOST 107-2221-E-007-112-MY3]
This study aims to understand the pathogenesis of DLBCL ABC and DLBCL GCB by constructing a candidate genome-wide genetic and epigenetic network. By identifying core signaling pathways and investigating pathogenic mechanisms, potential drug targets and drug combinations are proposed for the treatment of DLBCL ABC and DLBCL GCB.
Diffuse large B cell lymphoma (DLBCL) is an aggressive heterogeneous disease. The most common subtypes of DLBCL include germinal center b-cell (GCB) type and activated b-cell (ABC) type. To learn more about the pathogenesis of two DLBCL subtypes (i.e., DLBCL ABC and DLBCL GCB), we firstly construct a candidate genome-wide genetic and epigenetic network (GWGEN) by big database mining. With the help of two DLBCL subtypes' genome-wide microarray data, we identify their real GWGENs via system identification and model order selection approaches. Afterword, the core GWGENs of two DLBCL subtypes could be extracted from real GWGENs by principal network projection (PNP) method. By comparing core signaling pathways and investigating pathogenic mechanisms, we are able to identify pathogenic biomarkers as drug targets for DLBCL ABC and DLBCL GCD, respectively. Furthermore, we do drug discovery considering drug-target interaction ability, drug regulation ability, and drug toxicity. Among them, a deep neural network (DNN)-based drug-target interaction (DTI) model is trained in advance to predict potential drug candidates holding higher probability to interact with identified biomarkers. Consequently, two drug combinations are proposed to alleviate DLBCL ABC and DLBCL GCB, respectively.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据