Discriminating the earliest stages of mammary carcinoma using myoepithelial and proliferative markers

Hendrika M. Duivenvoorden, Alex Spurling, Sandra A. O'Toole, Belinda S. Parker

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2 Citations (Scopus)


Mammographic screening has led to increased detection of breast cancer at a pre-invasive state, hence modelling the earliest stages of breast cancer invasion is important in defining candidate biomarkers to predict risk of relapse. Discrimination of pre-invasive from invasive lesions is critically important for such studies. Myoepithelial cells are the barrier between epithelial cells and the surrounding stroma in the breast ductal system. A number of myoepithelial immunohistochemistry markers have been identified and validated in human tissue for use by pathologists as diagnostic tools to distinguish in situ carcinoma from invasive breast cancer. However, robust myoepithelial markers for mouse mammary tissue have been largely under-utilised. Here, we investigated the utility of the myoepithelial markers smooth muscle actin (SMA), smooth muscle myosin heavy chain (SMMHC), cytokeratin-14 (CK14) and p63 to discriminate mammary intraepithelial neoplasia (MIN) from invasive disease in the C57BL/ 6J MMTV-PyMT transgenic model of mammary carcinoma. We identified that SMMHC and CK14 are retained in early in situ neoplasia and are appropriate markers for distinguishing MIN from invasive disease in this model. Additionally, the proliferation marker Ki67 is a superior marker for differentiating between normal and hyperplastic ducts, prior to the development of MIN. Based on this, we developed a scoring matrix for discriminating normal, hyperplasia, MIN and invasive lesions in this spontaneous mammary tumorigenesis model. This study demonstrates heterogeneous expression of myoepithelial proteins throughout tumour development, and highlights the need to characterise the most appropriate markers in other models of early breast cancer to allow accurate classification of disease state.

Original languageEnglish
Article numbere0201370
Number of pages12
JournalPLoS ONE
Issue number7
Publication statusPublished - 1 Jul 2018
Externally publishedYes

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