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October 30, 2026
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Fra-2 overexpression upregulates pro-metastatic cell-adhesion molecules, promotes pulmonary metastasis, and reduces survival in a spontaneous xenograft model of human breast cancer

Journal of Cancer Research and Clinical Oncology. 2021. Vol. 148. No. 6. P. 1525–1542.
Arnold S., Cortland J., Maltseva D., Nersisyan S., Tonevitsky A., Struken C.

Purpose:

The transcription factor Fra-2 affects the invasive potential of breast cancer cells by dysregulating adhesion molecules in vitro. Previous results suggested that it upregulates the expression of E- and P-selectin ligands. Such selectin ligands are important members of the leukocyte adhesion cascade, which govern the adhesion and transmigration of cancer cells into the stroma of the host organ of metastasis. As so far, no in vivo data are available, this study was designed to elucidate the role of Fra-2 expression in a spontaneous breast cancer metastasis xenograft model.

Methods:

The effect of Fra-2 overexpression in two stable Fra-2 overexpressing clones of the human breast cancer cell line MDA MB231 on survival and metastatic load was studied after subcutaneous injection into scid and E- and P-selectin deficient scid mice.

Results:

Fra-2 overexpression lead to a significantly shorter overall survival and a higher amount of spontaneous lung metastases not only in scid mice, but also in E- and P-deficient mice, indicating that it regulates not only selectin ligands, but also selectin-independent adhesion processes.

Conclusion:

Thus, Fra-2 expression influences the metastatic potential of breast cancer cells by changing the expression of adhesion molecules, resulting in increased adherence to endothelial cells in a breast cancer xenograft model.

Research target: Basic Medicine Biology
Language: English
Full text
DOI
Text on another site
Keywords: Рак молочной железыBreast cancerTranscription factorsMetastasisметастазированиеAP-1Fra-2транскрипционный факторAP-1Fra-2
Publication based on the results of:
Creation of a metastasis-on-chip microphysiological platform for studying the biology of the tumor process (mathematical modeling) (2021)
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