亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

The long non-coding RNA CCAT2 is up-regulated in ovarian cancer and associated with poor prognosis

卵巢癌 长非编码RNA 基因敲除 基因沉默 癌症研究 生物 转移 生物标志物 癌症 肿瘤科 内科学 医学 核糖核酸 细胞培养 基因 生物化学 遗传学
作者
Shuying Huang,Qing Cheng,Zikun Huang,Yuanfang Zhu
出处
期刊:Diagnostic Pathology [Springer Nature]
卷期号:11 (1) 被引量:75
标识
DOI:10.1186/s13000-016-0499-x
摘要

Ovarian cancer is a malignant tumor with a poor prognosis. Accumulating evidence demonstrates that long non-coding RNAs (lncRNAs) are emerging regulators in cancer biology, and can be used as potential biomarkers for cancer diagnosis, prognosis and targeted therapy. The lncRNA CCAT2 (colon cancer associated transcript 2) was recently shown to be involved in several cancers; however, its role in ovarian cancer remains unknown.Expression levels of the lncRNA CCAT2 in ovarian cancer tissues, adjacent normal tissues, and cell lines were assessed by quantitative real-time PCR. Then, the associations of CCAT2 expression levels with clinicopathological features and prognosis were evaluated. In addition, CCAT2 functions in tumor progression and invasion were further determined by siRNA-induced CCAT2 silencing in vitro.Expression levels of the lncRNA CCAT2 in ovarian cancer tissues and cell lines were significantly higher compared with values obtained for adjacent non-tumor tissues and normal ovarian epithelial cells. Interestingly, higher CCAT2 expression levels were associated with a shorter overall survival (P = 0.006) and disease-free survival (P = 0.001) in ovarian cancer patients. In addition, CCAT2 expression was positively correlated with FIGO stage (P = 0.002), tumor grade (P = 0.006) and distant metastasis (P < 0.001). Moreover, CCAT2 knockdown in ovarian cancer cells markedly suppressed cell proliferation, migration, and invasion.The lncRNA CCAT2 is a novel factor involved in ovarian cancer progression, and constitutes a potential prognostic biomarker and therapeutic target for patients with ovarian 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
冷酷愚志完成签到,获得积分10
6秒前
精灵夜雨完成签到,获得积分10
7秒前
善学以致用应助三好学生采纳,获得10
9秒前
wbs13521完成签到,获得积分10
14秒前
21秒前
三好学生发布了新的文献求助10
28秒前
53秒前
57秒前
欢欢发布了新的文献求助30
58秒前
1分钟前
卟卟高升完成签到 ,获得积分10
1分钟前
三好学生发布了新的文献求助10
1分钟前
科研通AI2S应助欢欢采纳,获得10
1分钟前
科研通AI5应助Rita采纳,获得10
1分钟前
科研通AI2S应助科研通管家采纳,获得10
1分钟前
1分钟前
清爽天川完成签到 ,获得积分10
1分钟前
欢欢完成签到,获得积分10
1分钟前
完美世界应助KH采纳,获得10
1分钟前
1分钟前
bcc666发布了新的文献求助10
1分钟前
1分钟前
丰富的宛亦完成签到 ,获得积分10
1分钟前
冷傲新柔发布了新的文献求助10
1分钟前
王显鹏发布了新的文献求助10
1分钟前
1分钟前
天天快乐应助bcc666采纳,获得10
1分钟前
内向耷完成签到,获得积分20
1分钟前
今后应助冷傲新柔采纳,获得10
1分钟前
小蘑菇应助三好学生采纳,获得10
1分钟前
common1988发布了新的文献求助10
1分钟前
1分钟前
2分钟前
KH发布了新的文献求助10
2分钟前
三好学生发布了新的文献求助10
2分钟前
王显鹏完成签到,获得积分20
2分钟前
hqh驳回了SciGPT应助
2分钟前
汉堡包应助王显鹏采纳,获得10
2分钟前
沿途有你完成签到 ,获得积分10
2分钟前
fsznc完成签到 ,获得积分0
2分钟前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Mechanistic Modeling of Gas-Liquid Two-Phase Flow in Pipes 2500
Structural Load Modelling and Combination for Performance and Safety Evaluation 800
Conference Record, IAS Annual Meeting 1977 610
Interest Rate Modeling. Volume 3: Products and Risk Management 600
Interest Rate Modeling. Volume 2: Term Structure Models 600
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3555693
求助须知:如何正确求助?哪些是违规求助? 3131341
关于积分的说明 9390757
捐赠科研通 2831039
什么是DOI,文献DOI怎么找? 1556299
邀请新用户注册赠送积分活动 726483
科研通“疑难数据库(出版商)”最低求助积分说明 715803