ArticleCancer biomarkers : section A of Disease markers2021
An mRNA characterization model predicting survival in patients with invasive breast cancer based on The Cancer Genome Atlas database.
Article in Cancer biomarkers : section A of Disease markers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Expression Characteristics of PAX7 and Its Prognostic Correlation in Breast Cancer.The breast journal · 2026Article
- USP41 Enhances Epithelial-Mesenchymal Transition of Breast Cancer Cells through Snail Stabilization.International journal of molecular sciences · 2023Article
- High myosin binding protein H expression predicts poor prognosis in glioma patients.Scientific reports · 2022Article
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInvasive breast cancer is a highly heterogeneous tumor, although there have been many prediction methods for invasive breast cancer risk prediction, the prediction effect is not satisfactory. There is an urgent need to develop a more accurate method to predict the prognosis of patients with invasive breast cancer.
objectiveTo identify potential mRNAs and construct risk prediction models for invasive breast cancer based on bioinformaticsMETHODS: In this study, we investigated the differences in mRNA expression profiles between invasive breast cancer and normal breast samples, and constructed a risk model for the prediction of prognosis of invasive breast cancer with univariate and multivariate Cox analyses.
resultsWe constructed a risk model comprising 8 mRNAs (PAX7, ZIC2, APOA5, TP53AIP1,MYBPH, USP41, DACT2, and POU3F2) for the prediction of invasive breast cancer prognosis. We used the 8-mRNA risk prediction model to divide 1076 samples into high-risk groups and low-risk groups, the Kaplan-Meier curve showed that the high-risk group was closely related to the poor prognosis of overall survival in patients with invasive breast cancer. The receiver operating characteristic curve revealed an area under the curve of 0.773 for the 8 mRNA model at 3-year overall survival, indicating that this model showed good specificity and sensitivity for prediction of prognosis of invasive breast cancer.
conclusionsThe study provides an effective bioinformatic analysis for the better understanding of the molecular pathogenesis and prognosis risk assessment of invasive breast cancer.
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