Evaluation of estrogenic and anti-estrogenic activity of endocrine disruptors using breast cancer spheroids: a comparative study of T47D and MCF7 cell lines in 2D and 3D models.

Introduction: The estrogenic and anti-estrogenic effects of endocrine disruptors were examined using two-dimensional 2D and three-dimensional 3D estrogen receptor-positive T47D and MCF7 human breast cancer cells.

Methods: The model system was used to test the plasticizer Bisphenol A (BPA), a known endocrine disruptor (EDs) with estrogen-like action, aga inst 17β-Estradiol (E2), the endogenous nuclear estrogen receptor (nERs) ligand, and the anti-estrogenic drug Fulvestrant (FUL). Spheroid formation and gene expression of estrogen-regulated markers (pS2 and TGFβ3) both in 2D and 3D cultures were used to establish the dose-dependent cellular effects of these substances, evaluated cell viability either by separately treating with the individual substances or in co-treatment.

Results: BPA exhibited a dose-dependent estrogenic activity in both 2D and 3D cultures, significantly influencing cell proliferation and gene expression of estrogen-regulated markers (pS2 and TGFβ3). In contrast, FUL displayed anti-estrogenic properties, effectively inhibiting the proliferative effects of E2, thereby highlighting the complex interactions between these compounds and the nERs pathways in human breast cancer cells.

Discussion: Our findings indicate that E2 and BPA significantly increase pS2 expression while decreasing TGFβ3, and that FUL co-treatment reverses these effects. Therefore, the model system could serve to observe the cell-mediated effects caused by the interaction of EDs with nERs. Through the use of these model systems - 2D and especially 3D, the latter of which allow better emulation of complex physiological and pathological processes occurring , the effects caused by EDs on nERs pathways can be detected and studied under various conditions. This approach performs as a preliminary screening tool to identify estrogenic substances, offering the potential to reduce reliance on experiments and contributing to improved environmental and health risk assessments.