Over previous decades the current landscape of preclinical drug testing and disease modelling of Non-Small Cell Lung Cancer (NSCLC) has progressed from 2-Dimensional plate-based assays, into the more complex and anatomically relevant 3D methodologies of organoids and Patient Derived Xenografts models. While these platforms have delivered many exciting advances in our understanding of NSCLC; these methods fail to contextualise the tissue architecture and microenvironment of human organs, also their disease complexities. Patient Derived Explants (PDEs) involve the ex vivo culture of freshly resected human tissue fragments that retain the histological and anatomical features of their original organ, while retaining a tissue microenvironment.
The use of PDEs in a research context has existed for many years, but the platform has not been widely adopted in translational research facilities, despite the strong evidence for its clinical predictivity. Our research hopes to provide evidence for the clinical relevance of this method, in both patient-specific anti-cancer immunotherapy response and infectious disease modelling using the SARS-CoV-2 variants.
In this study we generated 3 tumour PDEs, proving their ability to uptake immune checkpoint inhibitors Nivolumab (anti-PD1) and Ipilimumab (Anti-CTLA-4) to downregulate the expression of the patients corresponding checkpoint, as assessed by multiplexed spectral flow cytometry. These treatments also showed increased activity when combined. We also applied this same culture technique to 3 healthy lung PDEs, assessing their amenability toward infection by SARS-CoV-2 variants (Wuhan, Alpha, Beta, Delta, Omicron BA.1, Omicron BA.2) as detected by IHC and RNAscope.
We posit that PDEs offer many advantages over organoids and PDXs, including their ability to correlate drug responses with patient pathology, tumour heterogeneity and changes in the tumour microenvironment. PDEs make for a powerful model for personalised cancer drug therapy and biomarker discovery programmes, as well as a unique tool for infectious disease modelling.