Anoikis-related genes linked with patient outcome in pancreatic cancer

生物 失巢 胰腺癌 基因 癌症研究 癌症 列线图 肿瘤科 比例危险模型 小桶 遗传学 生物信息学 转录组 内科学 癌细胞 基因表达 医学
作者
Lizhi Lin,Jing Deng,Jiaye Yu,Monika Bauden,Roland Andersson,Xian Shen,Daniel Ansari,Xiangyang Xue
出处
期刊:Gene [Elsevier BV]
卷期号:930: 148868-148868
标识
DOI:10.1016/j.gene.2024.148868
摘要

Anoikis is programmed cell death occurring upon cell detachment from the extracellular matrix. Cancer cells need to evade anoikis to be able to metastasize to distant sites. However, the molecular features and prognostic value of anoikis-related genes (ARGs) in pancreatic cancer remain unclear. In this study, we utilized transcriptome data from the TCGA and GSE102238 databases to identify 64 ARGs significantly associated with prognosis. We used the "ConsensusClusterPlus" R package to stratify patients into high and low-risk prognostic subgroups. The KEGG and GSEA analyses revealed that the clusters with poor prognosis were enriched for the ECM receptor interaction pathway, the TP53 signaling pathway, and the galactose metabolism pathway, and that the cell cycle pathway was upregulated. A prognostic model consisting of seven ARGs (SERPINE1, EGF, E2F1, MSLN, RAB27B, ETV7, MST1) was constructed using LASSO regression and when combined with clinicopathological parameters using Cox regression, a prognostic Nomogram was created, which demonstrated high prognostic utility. Among the biomarker candidates, we report ETV7 as a novel, independent prognostic marker in pancreatic cancer. ETV7 was highly expressed in KRAS and TP53 co-occurrent mutant TCGA patients, indicating that it may be regulated by the two major driver genes of pancreatic cancer. Therefore, targeting ETV7 could be a potential focus for future therapeutic studies.
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
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
yangcj发布了新的文献求助10
1秒前
1秒前
xiaotudou95发布了新的文献求助30
1秒前
Jen发布了新的文献求助10
1秒前
着急的虔发布了新的文献求助10
2秒前
Clara发布了新的文献求助30
2秒前
5秒前
lalala发布了新的文献求助10
5秒前
6秒前
Drew11完成签到,获得积分10
6秒前
干净机器猫完成签到,获得积分10
7秒前
8秒前
zhangfugui应助冰雪物语采纳,获得10
10秒前
调皮班发布了新的文献求助10
10秒前
10秒前
zxy发布了新的文献求助10
11秒前
无奈曼云完成签到,获得积分10
11秒前
12秒前
烟花应助DOCTORLI采纳,获得10
13秒前
Dr.完成签到 ,获得积分10
18秒前
cc完成签到 ,获得积分10
20秒前
xian林发布了新的文献求助10
21秒前
wanci应助111采纳,获得10
22秒前
无限寄翠完成签到,获得积分10
23秒前
今后应助科研小趴菜采纳,获得10
24秒前
24秒前
25秒前
TigerOvO完成签到,获得积分10
27秒前
EasyNan应助哈哈哈采纳,获得20
27秒前
a1313发布了新的文献求助10
28秒前
28秒前
28秒前
30秒前
DOCTORLI发布了新的文献求助10
31秒前
Tracer发布了新的文献求助30
33秒前
谢晓东完成签到,获得积分10
34秒前
36秒前
田様应助Leo采纳,获得10
37秒前
37秒前
future完成签到 ,获得积分10
38秒前
高分求助中
All the Birds of the World 4000
Production Logging: Theoretical and Interpretive Elements 3000
Les Mantodea de Guyane Insecta, Polyneoptera 2000
Am Rande der Geschichte : mein Leben in China / Ruth Weiss 1500
CENTRAL BOOKS: A BRIEF HISTORY 1939 TO 1999 by Dave Cope 1000
Machine Learning Methods in Geoscience 1000
Resilience of a Nation: A History of the Military in Rwanda 888
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 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3736004
求助须知:如何正确求助?哪些是违规求助? 3279704
关于积分的说明 10017062
捐赠科研通 2996446
什么是DOI,文献DOI怎么找? 1644048
邀请新用户注册赠送积分活动 781753
科研通“疑难数据库(出版商)”最低求助积分说明 749425