Risk biomarkers for estrogen receptor (ER)-negative breast cancer have clear value for breast cancer prevention. We previously reported a set of lipid metabolism (LiMe) genes with high expression in the contralateral unaffected breasts (CUBs) of ER-negative cancer cases. We now further examine LiMe gene expression in both tumor and CUB, and investigate the role of Pre-B-cell leukemia homeobox-1 (PBX1) as a candidate common transcription factor for LiMe gene expression. mRNA was extracted from laser-capture microdissected epithelium from tumor and CUB of 84 subjects (28 ER-positive cases, 28 ER-negative cases, 28 healthy controls). Gene expression was quantitated by qRT-PCR. Logistic regression models were generated to predict ER status of the contralateral cancer. Protein expression of HMGCS2 and PBX1 was measured using immunohistochemistry. The effect of PBX1 on LiMe gene expression was examined by overexpressing PBX1 in MCF10A cells with or without ER, and by suppressing PBX1 in MDA-MB-453 cells. The expression of DHRS2, HMGCS2, UGT2B7, UGT2B11, ALOX15B, HPGD, UGT2B28 and GLYATL1 was significantly higher in ER-negative versus ER-positive CUBs, and predicted ER status of the tumor in test and validation sets. In contrast, LiMe gene expression was significantly lower in ER-negative than ER-positive tumors. PBX1 overexpression in MCF10A cells up-regulated most LiMe genes, but not in MCF10A cells overexpressing ER. Suppressing PBX1 in MDA-MB-453 cells resulted in decrease of LiMe gene expression. Four binding sites of PBX1 and cofactor were identified in three lipid metabolism genes using ChIP-qPCR. These data suggest a novel role for PBX1 in the regulation of lipid metabolism genes in benign breast, which may contribute to ER-negative tumorigenesis.
CITATION STYLE
Wang, J., Shidfar, A., Ivancic, D., Ranjan, M., Liu, L., Choi, M. R., … Khan, S. A. (2017). Overexpression of lipid metabolism genes and PBX1 in the contralateral breasts of women with estrogen receptor-negative breast cancer. International Journal of Cancer, 140(11), 2484–2497. https://doi.org/10.1002/ijc.30680
Mendeley helps you to discover research relevant for your work.