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© 2018 Sasmita AO, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

REVIEW ARTICLE | OPEN ACCESS DOI: 10.23937/ijor-2017/1710008

Organoids as Reliable Breast Cancer Study Models: An Update

Andrew Octavian Sasmita and Ying Pei Wong*

Division of Applied Biomedical Sciences and Biotechnology, School of Health Sciences, International Medical University, Malaysia


Having been identified for centuries, breast cancer still remains one of the leading causes of death in women. Within the United States of America (USA) alone, it is estimated that over 60,000 women would have developed new cases of malignant breast cancer in 2017 alone; thus, calling an attention for the development of a reliable and effective breast cancer model for drug discovery to combat the disease or diagnostics to predict the progression of the disease. Current breast cancer models involve usage of 2D cell cultures and in vivo models which do not recapitulate the entire microenvironment of tumour growth in human cases, and despite some cell lines being derived from patients' own tumour cells, 2D cell cultures are heterogeneous and lack the cell-cell interaction necessary for normal tumour growth in the human body. Many limitations of these conventional models can be resolved using novel 3D organoid cultures produced from tumours of patients themselves or other viable sources. Breast cancer organoids have been proven to predict patient chemotherapeutic outcomes efficiently in the case of primary breast cancer via immunofluorescence or gene expression studies. This study model can also be utilized to discover new biomarkers with clinical implications. The advantages, limitations, and protocols to derive breast cancer organoids are being reviewed here alongside the ethical issues which might arise. Breast cancer organoid research could then open avenues of reliable drug discovery and diagnostics model to ameliorate subtypes of breast cancer which do not provide much options therapy-wise, such as the triple negative subtype.