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Identification of a six-gene signature associated with tumor mutation burden for predicting prognosis in patients with invasive breast carcinoma

1 Apr 2020

Abstract excerpt

BACKGROUND: Breast cancer (BC) is one of the most common cancers with high mortality worldwide. In the present study, through bioinformatics analysis, we aimed to identify new biomarkers to predict the survival rate of BC patients. METHODS: Differentially expressed genes (DEGs) between low- and high-tumor mutation burden (TMB) groups were identified by using The Cancer Genome Atlas (TCGA) dataset and integrated...

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PMID: 32395497
DOI: 10.21037/atm.2020.04.02

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