Comprehensive characterization of a drug-resistance-related ceRNA network across 15 anti-cancer drug categories.
Comprehensive characterization of a drug-resistance-related ceRNA network across 15 anti-cancer drug categories.
复制标题
跨 15 种抗癌药物类别的耐药相关 ceRNA 网络的综合表征
DOI:
10.1016/j.omtn.2021.02.011
复制
发表时间:
2021-06-04
期刊:
影响因子:
--
通讯作者:
Shang D
中科院分区:
文献类型:
--
作者:
Liu B;Zhou X;Wu D;Zhang X;Shen X;Mi K;Qu Z;Jiang Y;Shang D
Cancer is still a major health problem around the world. The treatment failure of cancer has largely been attributed to drug resistance. Competitive endogenous RNAs (ceRNAs) are involved in various biological processes and thus influence the drug sensitivity of cancers. However, a comprehensive characterization of drug-sensitivity-related ceRNAs has not yet been performed. In the present study, we constructed 15 ceRNA networks across 15 anti-cancer drug categories, involving 217 long noncoding RNAs (lncRNAs), 158 microRNAs (miRNAs), and 1,389 protein coding genes (PCGs). We found that these ceRNAs were involved in hallmark processes such as “self-sufficiency in growth signals,” “insensitivity to antigrowth signals,” and so on. We then identified an intersection ceRNA network (ICN) across the 15 anti-cancer drug categories. We further identified interactions between genes in the ICN and clinically actionable genes (CAGs) by analyzing the co-expressions, protein-protein interactions, and transcription factor-target gene interactions. We found that certain genes in the ICN are correlated with CAGs. Finally, we found that genes in the ICN were aberrantly expressed in tumors, and some were associated with patient survival time and cancer stage. The present study constructed 15 ceRNA networks across 15 anti-cancer drug categories and identified an intersection ceRNA network (ICN). A comprehensive analysis of the genes in an ICN highlights their potential clinical utility in cancer therapy.
登录
查看更多内容
影响因子:
12.3
作者:
Ekman D;Light S;Björklund AK;Elofsson A
通讯作者:
Elofsson A
影响因子:
14.9
作者:
Forbes SA;Bindal N;Bamford S;Cole C;Kok CY;Beare D;Jia M;Shepherd R;Leung K;Menzies A;Teague JW;Campbell PJ;Stratton MR;Futreal PA
通讯作者:
Futreal PA
影响因子:
3.7
作者:
Jin G;Zhang S;Zhang XS;Chen L
通讯作者:
Chen L
影响因子:
14.9
作者:
Jiang Q;Wang Y;Hao Y;Juan L;Teng M;Zhang X;Li M;Wang G;Liu Y
通讯作者:
Liu Y
影响因子:
9
作者:
An Y;Zhang Z;Shang Y;Jiang X;Dong J;Yu P;Nie Y;Zhao Q
通讯作者:
Zhao Q