Prognostic and predictive value of super-enhancer-derived signatures for survival and lung metastasis in osteosarcoma

骨肉瘤 预测值 转移 医学 肿瘤科 价值(数学) 癌症研究 内科学 计算机科学 癌症 机器学习
作者
Guoquan Huang,Xuelin Zhang,Yongan Xu,Shuo Chen,Qinghua Cao,Weihai Liu,Yiwei Fu,Qiang Jia,Jing Shen,Junqiang Yin,Jiajun Zhang
出处
期刊:Journal of Translational Medicine [BioMed Central]
卷期号:22 (1)
标识
DOI:10.1186/s12967-024-04902-8
摘要

Abstract Background Risk stratification and personalized care are crucial in managing osteosarcoma due to its complexity and heterogeneity. However, current prognostic prediction using clinical variables has limited accuracy. Thus, this study aimed to explore potential molecular biomarkers to improve prognostic assessment. Methods High-throughput inhibitor screening of 150 compounds with broad targeting properties was performed and indicated a direction towards super-enhancers (SEs). Bulk RNA-seq, scRNA-seq, and immunohistochemistry (IHC) were used to investigate SE-associated gene expression profiles in osteosarcoma cells and patient tissue specimens. Data of 212 osteosarcoma patients who received standard treatment were collected and randomized into training and validation groups for retrospective analysis. Prognostic signatures and nomograms for overall survival (OS) and lung metastasis-free survival (LMFS) were developed using Cox regression analyses. The discriminatory power, calibration, and clinical value of nomograms were evaluated. Results High-throughput inhibitor screening showed that SEs significantly contribute to the oncogenic transcriptional output in osteosarcoma. Based on this finding, focus was given to 10 SE-associated genes with distinct characteristics and potential oncogenic function. With multi-omics approaches, the hyperexpression of these genes was observed in tumor cell subclusters of patient specimens, which were consistently correlated with poor outcomes and rapid metastasis, and the majority of these identified SE-associated genes were confirmed as independent risk factors for poor outcomes. Two molecular signatures were then developed to predict survival and occurrence of lung metastasis: the SE-derived OS-signature (comprising LACTB , CEP55 , SRSF3 , TCF7L2 , and FOXP1 ) and the SE-derived LMFS-signature (comprising SRSF3 , TCF7L2 , FOXP1 , and APOLD1 ). Both signatures significantly improved prognostic accuracy beyond conventional clinical factors. Conclusions Oncogenic transcription driven by SEs exhibit strong associations with osteosarcoma outcomes. The SE-derived signatures developed in this study hold promise as prognostic biomarkers for predicting OS and LMFS in patients undergoing standard treatments. Integrative prognostic models that combine conventional clinical factors with these SE-derived signatures demonstrate substantially improved accuracy, and have the potential to facilitate patient counseling and individualized management.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
1秒前
科研通AI5应助枕星采纳,获得10
2秒前
小曾应助pakiorder采纳,获得10
8秒前
wxy完成签到,获得积分10
9秒前
分析完成签到 ,获得积分10
9秒前
hulin_zjxu完成签到,获得积分10
9秒前
桃紫完成签到,获得积分10
11秒前
小董不懂完成签到,获得积分10
12秒前
椰子完成签到,获得积分10
12秒前
沐沐溪三清完成签到,获得积分10
12秒前
13秒前
刘丰完成签到 ,获得积分10
15秒前
郑桂庆完成签到 ,获得积分10
16秒前
zhang完成签到 ,获得积分10
16秒前
yuchen完成签到,获得积分10
17秒前
喜悦的水云完成签到 ,获得积分10
17秒前
18秒前
zhaokunfeng完成签到,获得积分10
18秒前
Y123发布了新的文献求助10
18秒前
wu完成签到,获得积分10
18秒前
高高诗柳完成签到 ,获得积分10
18秒前
王金豪完成签到,获得积分10
18秒前
LSS完成签到,获得积分10
18秒前
榜一大哥的负担完成签到 ,获得积分10
19秒前
Lucas应助qi0625采纳,获得10
19秒前
顾矜应助以筱采纳,获得10
20秒前
景清完成签到,获得积分10
20秒前
细心香烟完成签到 ,获得积分10
20秒前
hu完成签到 ,获得积分10
20秒前
HQ完成签到,获得积分10
20秒前
21秒前
水清木华完成签到,获得积分10
21秒前
22秒前
miao完成签到,获得积分20
22秒前
xyp_zjut应助学术乞丐采纳,获得10
22秒前
Lucas应助凉白开采纳,获得10
22秒前
体贴凌柏发布了新的文献求助10
23秒前
23秒前
23秒前
鹿子完成签到 ,获得积分10
23秒前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
徐淮辽南地区新元古代叠层石及生物地层 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Handbook of Industrial Diamonds.Vol2 1100
Global Eyelash Assessment scale (GEA) 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 550
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4038368
求助须知:如何正确求助?哪些是违规求助? 3576068
关于积分的说明 11374313
捐赠科研通 3305780
什么是DOI,文献DOI怎么找? 1819322
邀请新用户注册赠送积分活动 892672
科研通“疑难数据库(出版商)”最低求助积分说明 815029