An Integrative Model of miRNA and mRNA Expression Signature for Patients of Breast Invasive Carcinoma with Radiotherapy Prognosis.
Radiotherapy is widely used in breast cancer treatment. The radiotherapy for breast invasive carcinoma (BRCA) presents challenges with the complex clinical factors, and too many genes have been found to be associated with BRCA radiotherapy prognosis. The aim of this study was to construct an integrative model to combine the clinical data and RNA expression data (including microRNA and mRNA) to predict the survival durations of BRCA patients with radiotherapy. Also, the authors try to find the key regulation pairs between mRNA and miRNA from prediction. They collected mRNA and microRNA expression profiles and gathered the corresponding clinical data of 73 BRCA patients with radiotherapy from The Cancer Genome Atlas (TCGA). According to an integrative model from univariate Cox regression between RNA expression and patient survival, they classified the patients with radiotherapy into low-risk and high-risk groups. The results showed that nine mRNAs were considered as protective genes and five miRNAs and eight mRNAs were considered as high-risk genes. Moreover, the high-risk group has a significantly shorter survival time in comparison with the low-risk group by the log-rank test (p = 0.0039). The reliability of the gene signature was validated by an independent data set from the Gene Expression Omnibus (GEO). Furthermore, three pairs of miRNA-mRNA, closely associated to survival, were identified. These findings and method may prove valuable for improving the clinical management of BRCA patients with radiotherapy.
1 Evidence Based Medicine Center, School of Basic Medical Science of Lanzhou University , Lanzhou, China .|2 Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province , Lanzhou, China .|3 Institute of Modern Physics of Chinese Academy of Sciences , Lanzhou, China .
Zhitong
Z
Bing
1 Evidence Based Medicine Center, School of Basic Medical Science of Lanzhou University , Lanzhou, China .|2 Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province , Lanzhou, China .
Jinhui
J
Tian
1 Evidence Based Medicine Center, School of Basic Medical Science of Lanzhou University , Lanzhou, China .|2 Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province , Lanzhou, China .
Jingyun
J
Zhang
1 Evidence Based Medicine Center, School of Basic Medical Science of Lanzhou University , Lanzhou, China .|2 Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province , Lanzhou, China .
Xiuxia
X
Li
4 Gansu Provincial Cancer Hospital , Lanzhou, China .
Xiaohu
X
Wang
1 Evidence Based Medicine Center, School of Basic Medical Science of Lanzhou University , Lanzhou, China .|2 Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province , Lanzhou, China .
Kehu
K
Yang
D000368:Aged; D001943:Breast Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology / Q000532:radiotherapy*; D005260:Female; D006801:Humans; D035683:MicroRNAs / Q000096:biosynthesis* / Q000235:genetics; D008957:Models, Genetic; D009361:Neoplasm Invasiveness; D011379:Prognosis; D012333:RNA, Messenger / Q000096:biosynthesis* / Q000235:genetics; D012307:Risk Factors; D016019:Survival Analysis; D059467:Transcriptome
D035683:MicroRNAs; D012333:RNA, Messenger
Cox regression; breast invasive carcinoma; gene expression; prognostic; radiotherapy