August 26 2020
A new paper exploring the application of patient-derived organoids (PDOs) in the study of novel inhibitors of stem cell activity has recently been published in the journal PLOS ONE (Badder et al., 2020).
The study utilised 3D image-based morphometric analysis to quantify over 600 different features from individual organoids following treatment with inhibitors of the tankyrase protein (TNKSi). While the morphometric analysis approach mirrored the trend seen in traditional biochemical assays, importantly this more sophisticated method was able to detect subtle alterations in growth and morphology in response to TNKSi with much greater accuracy. This leads to the conclusion that whilst traditional biochemical assays still have value in detecting compounds that merit further investigation in early stage drug discovery, combining these with 3D morphological analysis could be the key to unlocking the full potential of organoids in predictive drug testing at a much larger scale.
The study was led by Cellesce founding director Professor Trevor Dale’s Cardiff University-based academic research group working together with Cellesce and other partners. It describes the derivation of a novel set of colorectal cancer PDOs. The PDO models are then used as a platform to test the response of colorectal cancer to Wnt pathway modulation using small molecule TNKSi. The work utilises a range of analysis techniques and highlights 3D quantitative image analysis in particular as having the potential to greatly enhance the high throughput prediction of compound efficacy in pre-clinical testing.
In recent years, there has been a shift within the drug discovery industry to focus on the development of compounds targeting ‘cancer stem cell’ populations within tumours. Historically, conventional chemotherapeutics have aimed to target the tumour bulk, to kill as many tumour cells as possible; the effects of which are usually to drive tumour regression in the short-term, albeit with greater side-effects - and a high chance of patient relapse. It is now widely understood that, in order to permanently prevent tumour growth, the initiating cancer stem cell population must be removed or inhibited. In the patient, this might have a relatively small impact initially on overall tumour size, but a longer term more effective treatment caused not by killing the cells, but by a more subtle change in the behaviour of the cells within the tumour.
The study of such targeted compounds has led to demand for better predictive model systems. While historical drug discovery has relied heavily on the predictive power of 2D cancer cell lines, their lack of cellular heterogeneity and relevant phenotypic behaviour leaves them largely unsuited for the study of Read More
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