Organoid technology has transformed biomedical research by providing novel tools for developing and testing new therapeutic approaches. First described in 2009^1,2, organoids can be generated from adult or pluripotent stem cells using tissue- and organ-specific growth factor cocktails. In culture, stem cells will proliferate and generate self-organising organotypic cell clusters (‘mini-organs’) resembling either the tissue-of-origin (when using adult stem cells) or the tissue defined by the growth factors provided (when using pluripotent stem cells). Protocols to derive organoids from many tissues–mainly of epithelial origin–have been described.³ Also, methods to generate organoids from primary or metastatic tumour tissue have been developed.⁴

Tumour organoids can be derived from primary tumour biopsies or resection specimens. After expansion of the patient-derived cells, organoids can be characterized (which may include genetic and expression profiling) and cryopreserved, thereby allowing the generation of organoid biobanks. From these frozen collections, desired cultures can be thawed for a wide range of applications, including therapy screening. 

In our current publication, we first provide an overview of the different protocols to generate patient-derived organoids from both normal (epithelial) and tumour tissues, as published by various laboratories.  Next, we describe the different approaches used by both others and ourselves to test patient-derived organoids for therapy sensitivity in vitro. Subsequently, we describe–in detail–our previously reported method to generate head and neck squamous cell carcinoma (HNSCC) organoids, and screen these mini-tumours for therapy sensitivity in a semi-automated fashion.⁵ The  drug screening protocol may be widely applicable for other organoid cultures.

Accumulated data indicates that patient-derived organoids hold predictive value when exposed to therapies in a Petri dish.^5–10 It is therefore not surprising that many research groups have established protocols (which are summarised in our current publication) for organoid drug testing. Although a correlation between in vitro and patient response is crucial, it is not sufficient to develop a predictive test for therapy response.  Other factors, including low turn-around time (e.g. high culture expansion rate); minimisation of technical variation; and high reproducibility (i.e. standardization of protocols) are also essential for clinical-grade testing.

The clinical translation of organoid technology poses an exciting challenge, since the therapy response of cultured patient-derived cells is inherently more variable than the more stable and simpler DNA and RNA molecules that are the current subject of investigation in any of the diagnostic, predictive and prognostic molecular tests currently used in the clinic. Therefore, while the much-needed validation of the predictive potential of organoids is ongoing (an issue touched upon in our publication), we feel it is not only relevant, but essential, to start thinking about the next step: translation of organoid technology to a predictive assay that meets the standards of clinical testing.

We hope our current publication will create a starting point for a discussion on a standardised way of organoid screening, by providing both an overview of existing protocols and a detailed description of the protocols we use. We feel that such standardisation will contribute to the required large-scale validation of organoid screening as a predictive test. In addition, it may facilitate the actual implementation of organoid drug testing if, or more likely, when and where, this technology will be introduced in the clinic as a predictive test for therapy response.

References
1. Sato, T. et al. Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche. Nature459, 262–5 (2009).
2. Ootani, A. et al. Sustained in vitro intestinal epithelial culture within a Wnt-dependent stem cell niche. Nat. Med.15, 701–706 (2009).
3. Kretzschmar, K. & Clevers, H. Modeling development and disease with organoids. Cell 165, 1586–1597 (2016).
4. Drost, J. & Clevers, H. Organoids in cancer research. Nat. Rev. Cancer 18, 407–418 (2018).
5. Driehuis, E. et al. Oral mucosal organoids as a potential platform for personalized cancer therapy. Cancer Discov. 9, 852–871 (2019).
6. Vlachogiannis, G. et al. Patient-derived organoids model treatment response of metastatic gastrointestinal cancers. Science (80-. ). 926, 920–926 (2018).
7. Sachs, N. et al. A living biobank of breast cancer organoids captures disease heterogeneity. Cell 172, 373–386 (2018).
8. Driehuis, E. et al. Pancreatic cancer organoids recapitulate disease and allow personalized drug screening. Proc. Natl. Acad. Sci. U. S. A. 116, 26580–26590 (2019).
9. Ooft, S. N. et al. Patient-derived organoids can predict response to chemotherapy in metastatic colorectal cancer patients. Sci. Transl. Med. 11, eaay2574 (2019).
10.Tiriac, H. et al. Organoid profiling identifies common responders to chemotherapy in pancreatic cancer. Cancer Discov. 8, 1112–1129 (2018).