Cancer research using organoid technology
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REVIEW
Cancer research using organoid technology Kai Kretzschmar 1 Received: 7 July 2020 / Revised: 14 September 2020 / Accepted: 5 October 2020 # The Author(s) 2020
Abstract Organoid technology has rapidly transformed basic biomedical research and contributed to significant discoveries in the last decade. With the application of protocols to generate organoids from cancer tissue, organoid technology has opened up new opportunities for cancer research and therapy. Using organoid cultures derived from healthy tissues, different aspects of tumour initiation and progression are widely studied including the role of pathogens or specific cancer genes. Cancer organoid cultures, on the other hand, are applied to generate biobanks, perform drug screens, and study mutational signatures. With the incorporation of cellular components of the tumour microenvironment such as immune cells into the organoid cultures, the technology is now also exploited in the rapidly advancing field of immuno-oncology. In this review, I discuss how organoid technology is currently being utilised in cancer research and what obstacles are still to be overcome for its broader use in anti-cancer therapy. Keywords Cancer . Organoids . 3D culture . Pre-clinical models . Personalised medicine . Drug screening . Immuno-oncology
Introduction Cancer remains a major threat to quality of life with significant risks of morbidity and mortality worldwide [1], despite extraordinary progress made in cancer research, prevention, detection, and therapy in the past decades. For example in the USA, incidences of the prominent cancer types of lung or colorectal cancer are decreasing partially due to increased knowledge on cancer biology and, hence, improved prevention, while incidence rates of other cancer types such as liver or oral cancers are increasing [2]. However, cancer is a heterogenous disease with a broad range of types and subtypes, which can be defined based on their anatomical location, histological appearance, and genetical makeup. In order to guide the way to improved targeted therapy, pre-clinical model systems are essential to better capture the inter- and intratumour heterogeneity. For instance, animal cancer models, in particular genetically engineered mouse models (GEMMs), have provided significant insights into * Kai Kretzschmar [email protected] 1
Mildred Scheel Early Career Centre (MSNZ) for Cancer Research Würzburg, University Hospital Würzburg, MSNZ/IZKF, Josef-Schneider-Str. 2, 97080 Würzburg, Germany
the cellular and genetic basis of cancer [3]. However, their application is rather costly, time-consuming, and often cannot be translated into therapy, due to major differences to human pathology and tumourigenesis (reviewed in [4, 5]). Using human cancer models such as cancer cell lines and patient-derived xenografts (PDTXs), some of these limitations were overcome: in principle, these models can be generated from a larger cohort of patients better presenting the inter-tumour heterogeneity [6]. Yet, these models also have si
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