Nima Daneshvar Baghbadorani

Nima Daneshvar Baghbadorani

*This is an algorithmically generated author record based on publicly available information.

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Nima Daneshvar Baghbadorani has a total of 9 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    A 3D Collagen-Based In Vitro Cancer Model Created Through Modular Tissue Engineering

    by Nima Daneshvar Baghbadorani, Mira Bosso, Rowen Greene, Taylor Dzikowski, Breanne Bevelander, Amelia Gagnon, Morgan Johannson, Mohammadreza Javan, Parnaz Soori, Michael Dean Chamberlain

    Background: An emerging tool to better simulate the complexity of tumour biology in vitro is 3D culture models. Several approaches have been introduced, yet many face challenges such as technical complexity or limited ability to reproduce critical tumour traits. Modular tissue engineering is a well-known method in tissue transplantation, where it has been used to develop various healthy tissue constructs. In this study, we set out to adapt this established approach to fabricate cancer microtissues and to assess their effectiveness as a tumour model that can capture essential features of cancer biology and drug-treatment response. Methods: Two triple-negative breast cancer (TNBC) cell lines, HCC1806 and MDA-MB-231, were cultured in microtissues and assessed for viability, cell death, generation of hypoxia and response to chemotherapy. To benchmark our model, we utilized flow cytometry to analyze the CD44+/CD24− cancer stem cell (CSC) phenotype across microtissues, 2D monolayers, and established 3D models, including spheroids, collagen domes, and laminin-rich domes. Results: The cells showed sustained cell viability with minimal cell death, along with natural development of tumour properties, such as hypoxia. Crucially, flow cytometry revealed a cell-line-dependent regulation of the CD44+/CD24− phenotype, underscoring the complex influence of the 3D microenvironment on stem cell regulation. Furthermore, by screening the model with standard anti-breast cancer chemotherapeutics, we observed drug resistance at concentrations comparable to those used in the clinic. Conclusions: Our model offers the unique ability to spontaneously reproduce fundamental features of tumours in vitro, capturing the cellular heterogeneity and reprogramming that drive clinical drug resistance.