Literature DB >> 27610468

An Integrative Model of miRNA and mRNA Expression Signature for Patients of Breast Invasive Carcinoma with Radiotherapy Prognosis.

Zhitong Bing1,2,3, Jinhui Tian1,2, Jingyun Zhang1,2, Xiuxia Li1,2, Xiaohu Wang4, Kehu Yang1,2.   

Abstract

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.

Entities:  

Keywords:  Cox regression; breast invasive carcinoma; gene expression; prognostic; radiotherapy

Mesh:

Substances:

Year:  2016        PMID: 27610468     DOI: 10.1089/cbr.2016.2059

Source DB:  PubMed          Journal:  Cancer Biother Radiopharm        ISSN: 1084-9785            Impact factor:   3.099


  9 in total

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8.  Nomogram Models Based on the Gene Expression in Prediction of Breast Cancer Bone Metastasis.

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9.  Correlations Between the Characteristics of Alternative Splicing Events, Prognosis, and the Immune Microenvironment in Breast Cancer.

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  9 in total

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