Despite several drugs showing promise after testing with standard in vitro assays, including extensive cell line panels, many tumours fail to respond to these drugs at the clinical trial stage. Thus, despite huge monetary investment in trials, the inability of pre-clinical models to predict success is hampering efforts to progress cancer treatment and to personalize cancer chemotherapy. Cell lines have been the work-horse of cancer research for decades, however they do not represent tumour heterogeneity or patient variability. There is a need for a better model to carry out pre-clinical testing in order to give greater chance of success in clinical trials, which would in turn mean benefit for more patients and an overall reduction of wasted funds.
To address this need for more clinically relevant models, the use of primary cell cultures derived from patient tumours is becoming more desirableand more common. We have previously shown that there are resistant subpopulations of cells within patient-derived prostate tumour cultures. Thus, to develop a successful treatment, all cell types must be targeted, and so specific combination treatments are likely to be more successful than monotherapies.
Here, we present the use of ptychography, a label-free imaging technique, to characterise primary prostate epithelial cultures derived from patient tumour tissue. This technique allows segmentation and extraction of individual cell metrics from time-lapse data. These metrics include cell number, area, thickness, dry mass, duration in mitosis, position, speed, orientation, directionality, Euclidean distance, meandering index (Euclidean distance/ total track length) and more. The cells were analysed as a mixed population and also as three separate populations, including transit amplifying cells (TA) (α2β1integrinhi/CD133-) and committed basal cells (CB) (α2β1integrinlo). Alongside this novel imaging technique we used fluorescent labelling of surface markers to confirm cell identity.
Our aim is to use ptychography to carry out real-time analysis of cell response to drug treatments, using docetaxel as the standard of care treatment and comparator. A full characterisation of all types of patient- derived tumour cells, alongside analysis of their response to current and novel drugs will allow assessment of detailed biological effects of the drugs tested as well as identification of resistant cells. This could lead to patient cells becoming part of the drug development pipeline, which will ultimately result in targeted and patient stratified therapies that take into account intra- and inter-tumour heterogeneity.