Comprehensive Analysis of Gene Expression Profiles Identifies a P4HA1-Related Gene Panel as a Prognostic Model in Colorectal Cancer Patients

比例危险模型 结直肠癌 接收机工作特性 生存分析 肿瘤科 基因 医学 内科学 Lasso(编程语言) 基因表达 单变量 队列 基因签名 基因表达谱 癌症 生物 多元统计 遗传学 统计 万维网 计算机科学 数学
作者
Zhangxin Chen,Mei-Yan Chen,Zengyan Xue,Xiaosan Zhu
出处
期刊:Cancer Biotherapy and Radiopharmaceuticals [Mary Ann Liebert]
卷期号:36 (8): 693-704 被引量:4
标识
DOI:10.1089/cbr.2021.0242
摘要

Objective: Colorectal cancer (CRC) is the leading cause of mortality worldwide. Growing evidence suggests that the current pathological staging system is inadequate for efficient and accurate prognosis. In this study, we aim to build a prognosis model to predict the survival outcome of CRC patients by using gene expression profiles from The Cancer Genome Atlas (TCGA). Materials and Methods: Univariate and multivariate Cox regression analysis were used to assess the relationship between clinical factors and P4HA1 expression regarding the prognosis of patients with colon adenocarcinoma (COAD). The least absolute shrinkage and selection operator (LASSO) Cox regression model was used to select prognostic differential expression genes (DEGs) for the construction of prognostic risk score model. Kaplan–Meier and receiver operating characteristic (ROC) survival analysis were used to assess the performance of the model on both TCGA cohort and an independent dataset GSE39582. Results: Overexpression of P4HA1 was confirmed to be associated with poor clinical outcome of colon cancer patients in both TCGA and GSE39582 cohorts. Using the TCGA cohort, we identified 1528 DEGs related to elevated P4HA1 expression, and we established a 11-gene panel to construct the prognostic risk score model by LASSO Cox regression analysis based on their expression profiles. The 11-gene signature was further validated in the independent dataset GSE39582. Time-dependent ROC curves indicated good performance of our model in predicting 1, 2, and 3-years overall survival in COAD patients. Additionally, gene set enrichment analysis indicated that the 11-gene signature was related to pathways involved in tumor progression. Conclusions: Together, we have established a 11-gene signature significantly associated with prognosis in COAD patients, which could serve as a promising tool for clinical application in the future.
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
大幅提高文件上传限制,最高150M (2024-4-1)

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
刚刚
炸炸西柚发布了新的文献求助10
1秒前
罐罐儿完成签到,获得积分0
1秒前
念兹在兹完成签到,获得积分10
2秒前
3秒前
呼呼哈哈完成签到,获得积分10
6秒前
合适醉蝶完成签到 ,获得积分10
8秒前
8秒前
8秒前
甜蜜的代容完成签到,获得积分20
8秒前
Carol完成签到,获得积分10
10秒前
浅笑暖暖完成签到,获得积分10
10秒前
Hwen完成签到,获得积分10
10秒前
echo完成签到,获得积分10
11秒前
11秒前
彤航完成签到,获得积分10
12秒前
笨笨平松发布了新的文献求助10
12秒前
14秒前
任梓宁发布了新的文献求助10
15秒前
xbbccc完成签到,获得积分20
15秒前
AAAstf完成签到 ,获得积分10
17秒前
举个栗子完成签到,获得积分10
17秒前
18秒前
yyz发布了新的文献求助10
20秒前
20秒前
开朗娩完成签到 ,获得积分10
21秒前
不知名的呆毛完成签到 ,获得积分10
23秒前
24秒前
科研通AI2S应助Leoniko采纳,获得10
24秒前
hammer完成签到,获得积分10
25秒前
Kyrie完成签到,获得积分10
26秒前
耍酷芙蓉完成签到,获得积分10
26秒前
26秒前
Ling完成签到,获得积分10
26秒前
fengmy完成签到,获得积分10
27秒前
肉哥发布了新的文献求助30
27秒前
打打应助123采纳,获得10
29秒前
周钰波关注了科研通微信公众号
30秒前
斯文棒球完成签到 ,获得积分10
31秒前
充电宝应助bb采纳,获得10
31秒前
高分求助中
Sustainability in Tides Chemistry 2800
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
Rechtsphilosophie 1000
Bayesian Models of Cognition:Reverse Engineering the Mind 888
Very-high-order BVD Schemes Using β-variable THINC Method 568
Chen Hansheng: China’s Last Romantic Revolutionary 500
XAFS for Everyone 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 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 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3137155
求助须知:如何正确求助?哪些是违规求助? 2788182
关于积分的说明 7784837
捐赠科研通 2444146
什么是DOI,文献DOI怎么找? 1299822
科研通“疑难数据库(出版商)”最低求助积分说明 625574
版权声明 601011