Construction and analysis of competing endogenous RNA network of MCF‑7 breast cancer cells based on the inhibitory effect of 6‑thioguanine on cell proliferation

竞争性内源性RNA 小RNA 乳腺癌 MCF-7型 癌基因 分子医学 生物 癌症 长非编码RNA 细胞周期 癌症研究 核糖核酸 计算生物学 基因 遗传学 人体乳房
作者
Hao Li,Xinglan An,Qi Li,Hao Yu,Ziyi Li
出处
期刊:Oncology Letters [Spandidos Publications]
卷期号:21 (2) 被引量:20
标识
DOI:10.3892/ol.2020.12365
摘要

Previous research has proven that 6‑thioguanine (6‑TG) inhibits the growth of MCF‑7 breast cancer cells. Accumulating evidence indicates that long non‑coding (lnc)RNAs are involved in the development of various cancer types as competitive endogenous (ce)RNA molecules. The present study was conducted to investigate the regulatory mechanism underlying the function of lncRNAs as ceRNA molecules in MCF‑7 cells and to identify more effective prognostic biomarkers for breast cancer treatment. The expression profiles of lncRNAs in untreated MCF‑7 cells and 6‑TG‑treated MCF‑7 cells were compared by RNA‑seq. The regulatory associations among lncRNAs, micro (mi)RNAs and mRNAs were analyzed and verified by the TargetScan, miRDB and miRTarBas databases. The ceRNA networks were constructed by Cytoscape. The expression levels of two lncRNAs and two miRNAs in the ceRNA network were measured by reverse transcription‑quantitative PCR. The OncoLnc and Kaplan‑Meier plotter network databases were utilized to determine the effects of lncRNA and miRNA expression on the survival of patients with breast cancer. A ceRNA network was constructed for MCF‑7 breast cancer cells treated with 6‑TG, and this network may provide valuable information for further research elucidating the molecular mechanism underlying the effects of 6‑TG on breast cancer. Moreover, LINC00324, MIR22HG, miR‑370‑3p and miR‑424‑5p were identified as potential prognostic and therapeutic biomarkers for breast cancer.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Akitten完成签到,获得积分10
刚刚
大海完成签到,获得积分10
刚刚
科研通AI2S应助云浮山海采纳,获得10
1秒前
jananie完成签到,获得积分10
1秒前
rover完成签到,获得积分10
2秒前
王碱完成签到,获得积分10
2秒前
小旭vip完成签到 ,获得积分10
2秒前
烟花应助三岁半采纳,获得10
2秒前
wanci应助阿甘采纳,获得10
2秒前
2秒前
zx完成签到,获得积分10
2秒前
我是老大应助yangwang采纳,获得10
3秒前
沙糖桔发布了新的文献求助10
3秒前
kHz完成签到,获得积分10
3秒前
打打应助儒雅厉采纳,获得10
3秒前
3秒前
弥漫的橘完成签到,获得积分10
4秒前
4秒前
伍号科研怪物完成签到,获得积分10
4秒前
吱吱吱吱完成签到 ,获得积分10
5秒前
林洛沁完成签到,获得积分10
5秒前
5秒前
EgbertW完成签到,获得积分10
5秒前
5秒前
panpan发布了新的文献求助10
5秒前
6秒前
6秒前
8秒前
爆米花应助Minguk采纳,获得10
8秒前
8秒前
chenhouhan发布了新的文献求助10
9秒前
TCR完成签到,获得积分10
9秒前
9秒前
cty完成签到,获得积分10
9秒前
KQ发布了新的文献求助10
9秒前
9秒前
9秒前
9秒前
852应助管管吃饱辣采纳,获得10
10秒前
Eternitymaria完成签到,获得积分10
10秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Encyclopedia of Reproduction Third Edition 3000
《药学类医疗服务价格项目立项指南(征求意见稿)》 1000
花の香りの秘密―遺伝子情報から機能性まで 800
1st Edition Sports Rehabilitation and Training Multidisciplinary Perspectives By Richard Moss, Adam Gledhill 600
Chemistry and Biochemistry: Research Progress Vol. 7 430
Biotechnology Engineering 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5629618
求助须知:如何正确求助?哪些是违规求助? 4720333
关于积分的说明 14970297
捐赠科研通 4787673
什么是DOI,文献DOI怎么找? 2556435
邀请新用户注册赠送积分活动 1517561
关于科研通互助平台的介绍 1478251