Open AccessIdentification of a 4‐ mRNA metastasis‐related prognostic signature for patients with breast cancer
Author(s) -
Xie Xinhua,
Wang Jianwei,
Shi Dingbo,
Zou Yutian,
Xiong Zhenchong,
Li Xing,
Zhou Jianhua,
Tang Hailin,
Xie Xiaoming
Publication year - 2019
Publication title -
journal of cellular and molecular medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.44
H-Index - 130
eISSN - 1582-4934
pISSN - 1582-1838
DOI - 10.1111/jcmm.14049
Subject(s) - nomogram , proportional hazards model , breast cancer , metastasis , oncology , medicine , hazard ratio , cohort , gene signature , gene expression profiling , cancer , gene expression , gene , confidence interval , biology , biochemistry
Metastasis‐related mRNA s have showed great promise as prognostic biomarkers in various types of cancers. Therefore, we attempted to develop a metastasis‐associated gene signature to enhance prognostic prediction of breast cancer ( BC ) based on gene expression profiling. We firstly screened and identified 56 differentially expressed mRNA s by analysing BC tumour tissues with and without metastasis in the discovery cohort ( GSE 102484, n = 683). We then found 26 of these differentially expressed genes were associated with metastasis‐free survival ( MFS ) in the training set ( GSE 20685, n = 319). A metastasis‐associated gene signature built using a LASSO Cox regression model, which consisted of four mRNA s, can classify patients into high‐ and low‐risk groups in the training cohort. Patients with high‐risk scores in the training cohort had shorter MFS (hazard ratio [ HR ] 3.89, 95% CI 2.53‐5.98; P < 0.001), disease‐free survival ( DFS ) ( HR 4.69, 2.93‐7.50; P < 0.001) and overall survival ( HR 4.06, 2.56‐6.45; P < 0.001) than patients with low‐risk scores. The prognostic accuracy of mRNA s signature was validated in the two independent validation cohorts ( GSE 21653, n = 248; GSE 31448, n = 246). We then developed a nomogram based on the mRNA s signature and clinical‐related risk factors (T stage and N stage) that predicted an individual's risk of disease, which can be assessed by calibration curves. Our study demonstrated that this 4‐ mRNA signature might be a reliable and useful prognostic tool for DFS evaluation and will facilitate tailored therapy for BC patients at different risk of disease.