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09.02.2019 | Preclinical study | Ausgabe 1/2019

Breast Cancer Research and Treatment 1/2019

Revealing clonality and subclonality of driver genes for clinical survival benefits in breast cancer

Breast Cancer Research and Treatment > Ausgabe 1/2019
Yujia Lan, Erjie Zhao, Shangyi Luo, Yun Xiao, Xia Li, Shujun Cheng
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Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1007/​s10549-019-05153-8) contains supplementary material, which is available to authorized users.
Yujia Lan and Erjie Zhao are Contributed equally to this work.

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Genomic studies have revealed that genomic aberrations play important roles in the progression of this disease. The aim of this study was to evaluate the associations between clinical survival outcomes of the clonality and subclonality status of driver genes in breast cancer.


We performed an integrated analysis to infer the clonal status of 55 driver genes in breast cancer data from TCGA. We used the chi-squared test to assess the relations between clonality of driver gene mutations and clinicopathological factors. The Kaplan–Meier method was performed for the visualization and the differences between survival curves were calculated by log-rank test. Univariate and multivariate Cox proportional hazards regression models were used to adjust for clinicopathological factors.


We identified a high proportion of clonal mutations in these driver genes. Among them, there were 17 genes showing significant associations between their clonality and multiple clinicopathologic factors. Performing survival analysis on BRCA patients with clonal or subclonal driver gene mutations, we found that clonal ERBB2, FOXA1, and KMT2C mutations and subclonal GATA3 and RB1 mutations predicted shorter overall survival compared with those with wild type. Furthermore, clonal ERBB2 and FOXA1 mutations and subclonal GATA3 and RB1 mutations independently predicted for shorter overall survival after adjusting for clinicopathological factors. By longitudinal analysis, the clonality of ERBB2, FOXA1, GATA3, and RB1 significantly predicted patients’ outcome within some specific BRCA tumor stages and histological subtypes.


In summary, these clonal or subclonal mutations of driver genes have implications for diagnosis, prognosis, and treatment with BRCA patients.

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