列线图
小桶
肝细胞癌
肿瘤科
基因签名
医学
小RNA
转移
内科学
比例危险模型
癌症
生物信息学
基因
基因本体论
生物
基因表达
遗传学
作者
Zhihua Zheng,Yi Wen,Kechao Nie,Shiyun Tang,Chen Xu,Shaoyang Lan,Jinglin Pan,Kailin Jiang,Xiaotao Jiang,Peng Liu,Yanhua Yan,Fengbin Liu,Yufeng Liu,Peiwu Li
摘要
Aim Hepatocellular carcinoma (HCC) is a common malignancy associated with a poor prognosis due to difficulties in reliably estimating overall survival (OS). MicroRNAs (miRNAs) play critical roles in HCC initiation, progression, and metastasis and are highly correlated with patient prognosis. Thus, miRNA‐based risk signatures and nomograms are urgently required for predicting OS in patients with HCC. Methods We constructed a 13‐miRNA‐based signature and prognostic nomogram using 408 HCC samples and 58 normal tissues with miRNA sequencing data and clinical data from 323 patients downloaded from The Cancer Genome Atlas. A total of 195 patients were assigned as the internal validation cohort for verification and testing. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was applied to investigate pathway enrichment for the signature. Results We identified and validated a 13‐miRNA risk signature highly associating with the OS of HCC patients. The signature showed good performances by calculating C‐index, area under the curve, and calibration curves. After verification and testing using an internal validation cohort, the results yielded a miRNA‐based signature and a prognostic nomogram with reliable predictive accuracy. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that various genes and multiple pathways were closely related to the mechanisms of HCC proliferation and metastasis. Conclusion We successfully identified a 13‐miRNA‐based signature and prognostic nomogram that are capable of predicting OS in patients with HCC.
科研通智能强力驱动
Strongly Powered by AbleSci AI