Publication Details

AFRICAN RESEARCH NEXUS

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Expression of RUNX1 correlates with poor patient prognosis in triple negative breast cancer

PLoS ONE, Volume 9, No. 6, Article e100759, Year 2014

The RUNX1 transcription factor is widely recognised for its tumour suppressor effects in leukaemia. Recently a putative link to breast cancer has started to emerge, however the function of RUNX1 in breast cancer is still unknown. To investigate if RUNX1 expression was important to clinical outcome in primary breast tumours a tissue microarray (TMA) containing biopsies from 483 patients with primary operable invasive ductal breast cancer was stained by immunohistochemistry. RUNX1 was associated with progesterone receptor (PR)-positive tumours (P<0.05), more tumour CD4+(P<0.05) and CD8+ (P<0.01) T-lymphocytic infiltrate, increased tumour CD138+plasma cell (P<0.01) and more CD68+macrophage infiltrate (P< 0.001). RUNX1 expression did not influence outcome of oestrogen receptor (ER)-positive or HER2-positive disease, however on univariate analysis a high RUNX1 protein was significantly associated with poorer cancer-specific survival in patients with ER-negative (P<0.05) and with triple negative (TN) invasive breast cancer (P<0.05). Furthermore, multivariate Cox regression analysis of cancer-specific survival showed a trend towards significance in ER-negative patients (P<0.1) and was significant in triple negative patients (P<0.05). Of relevance, triple negative breast cancer currently lacks good biomarkers and patients with this subtype do not benefit from the option of targeted therapy unlike patients with ER-positive or HER2- positive disease. Using multivariate analysis RUNX1 was identified as an independent prognostic marker in the triple negative subgroup. Overall, our study identifies RUNX1 as a new prognostic indicator correlating with poor prognosis specifically in the triple negative subtype of human breast cancer. © 2014 Ferrari et al.
Statistics
Citations: 85
Authors: 10
Affiliations: 4
Identifiers
Research Areas
Cancer
Health System And Policy
Study Approach
Quantitative