Unknown

Dataset Information

0

A Five-Gene Signature Predicts Prognosis in Patients with Kidney Renal Clear Cell Carcinoma.


ABSTRACT: Kidney renal clear cell carcinoma (KIRC) is one of the most common cancers with high mortality all over the world. Many studies have proposed that genes could be used to predict prognosis in KIRC. In this study, RNA expression data from next-generation sequencing and clinical information of 523 patients downloaded from The Cancer Genome Atlas (TCGA) dataset were analyzed in order to identify the relationship between gene expression level and the prognosis of KIRC patients. A set of five genes that significantly associated with overall survival time was identified and a model containing these five genes was constructed by Cox regression analysis. By Kaplan-Meier and Receiver Operating Characteristic (ROC) analysis, we confirmed that the model had good sensitivity and specificity. In summary, expression of the five-gene model is associated with the prognosis outcomes of KIRC patients, and it may have an important clinical significance.

SUBMITTER: Zhan Y 

PROVIDER: S-EPMC4619904 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

altmetric image

Publications

A Five-Gene Signature Predicts Prognosis in Patients with Kidney Renal Clear Cell Carcinoma.

Zhan Yueping Y   Guo Wenna W   Zhang Ying Y   Wang Qiang Q   Xu Xin-jian XJ   Zhu Liucun L  

Computational and mathematical methods in medicine 20151011


Kidney renal clear cell carcinoma (KIRC) is one of the most common cancers with high mortality all over the world. Many studies have proposed that genes could be used to predict prognosis in KIRC. In this study, RNA expression data from next-generation sequencing and clinical information of 523 patients downloaded from The Cancer Genome Atlas (TCGA) dataset were analyzed in order to identify the relationship between gene expression level and the prognosis of KIRC patients. A set of five genes th  ...[more]

Similar Datasets

| S-EPMC8206647 | biostudies-literature
| S-EPMC8416991 | biostudies-literature
| S-EPMC8649352 | biostudies-literature
| S-EPMC7333652 | biostudies-literature
| S-EPMC7470605 | biostudies-literature
| S-EPMC7603789 | biostudies-literature
| S-EPMC9921988 | biostudies-literature
| S-EPMC9263547 | biostudies-literature
| S-EPMC9068871 | biostudies-literature