Role of FOXC1 in regulation of basal-like/triple-negative breast cancer

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 11016-11016 ◽  
Author(s):  
P. S. Ray ◽  
J. Wang ◽  
Y. Qu ◽  
M. Shin-Sim ◽  
J. Shamonki ◽  
...  

11016 Background: Class identification studies have proposed 3 prognostically relevant molecular subtypes of breast cancer: luminal, HER2 and basal-like. The latter is associated with poor prognosis but its molecular basis is not clear. We hypothesized a direct correlation between FOXC1 expression and basal-like breast cancer. Methods: Expression of FOXC1, CK5, CK14, EGFR, c-Kit, αB-crystallin, ITGB4 and FOXC2 in basal-like breast cancer was examined using publicly available microarray datasets. A molecular signature of 40 genes sharing co-ordinate up or down regulation with FOXC1 was identified on one microarray (49 patients) and validated on 5 other microarrays (1,232 patients). The clinical significance of FOXC1 gene expression and the FOXC1 gene signature was evaluated using censored survival data. FOXC1 protein expression was assessed by immunohistochemistry (IHC) of a 96-sample breast cancer tissue microarray. Normal breast epithelial, luminal and basal breast cancer cells transfected with FOXC1 vectors were evaluated for cell proliferation, migration and invasion. Results: FOXC1 was found to be consistently and exclusively upregulated in basal-like triple negative breast cancer and was associated with poor overall survival (p<0.0001). The FOXC1 gene signature accurately predicted the basal-like phenotype. IHC analysis of FOXC1 protein expression in human breast cancers confirmed its potential to be used as a clinical biomarker of basal-like breast cancer. Normal breast epithelial cells and luminal breast cancer cells with low or no FOXC1 expression underwent epithelial-to-mesenchymal transition and displayed increased cellular proliferation, migration, invasion, and expression of basal cell markers when FOXC1 was overexpressed. In contrast, knockdown of FOXC1 by shRNA in basal-like breast cancer cells conferred luminal phenotype. Breast cancer progression-linked signaling pathways like NF-κB and p38MAPK were significantly stimulated in basal-like breast cancer as well as by in vitro FOXC1 overexpression. Conclusions: FOXC1 is a dominant determinant of the basal-like phenotype of breast cancer. We propose FOXC1 to be the single best molecular marker of and a potential therapeutic target for basal-like / triple negative breast cancer. No significant financial relationships to disclose.

2020 ◽  
Vol 11 (11) ◽  
Author(s):  
Dipayan Bose ◽  
Sagarika Banerjee ◽  
Rajnish Kumar Singh ◽  
Lyn M. Wise ◽  
Erle S. Robertson

AbstractDysbiotic microbiomes are linked to many pathological outcomes including different metabolic disorders like diabetes, atherosclerosis and even cancer. Breast cancer is the second leading cause of cancer associated death in women, and triple negative breast cancer (TNBC) is the most aggressive type with major challenges for intervention. Previous reports suggested that Parapoxvirus signatures are one of the predominant dysbiotic viral signatures in TNBC. These viruses encode several genes that are homologs of human genes. In this study, we show that the VEGF homolog encoded by Parapoxviruses, can induce cell proliferation, and alter metabolism of breast cancer and normal breast cells, through alteration of MAPK-ERK and PI3K-AKT signaling. In addition, the activity of the transcription factor FoxO1 was altered by viral-encoded VEGF through activation of the PI3K-AKT pathway, leading to reprogramming of cellular metabolic gene expression. Therefore, this study provides new insights into the function of viral-encoded VEGFs, which promoted the growth of the breast cancer cells and imparted proliferative phenotype with altered metabolism in normal breast cells.


2017 ◽  
Vol 12 (1) ◽  
pp. 221-229
Author(s):  
Abeer M. Ashmawy ◽  
Mona A. Sheta ◽  
Faten Zahran ◽  
Abdel Hady A. Abdel Wahab

2021 ◽  
Vol 17 (4) ◽  
pp. 513-522
Author(s):  
Xuye Zhao ◽  
Xiangdong Bai ◽  
Weina Li ◽  
Xuezhen Gao ◽  
Xiaoli Wang ◽  
...  

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