Abstract 36P
Background
Precision medicine is an emerging approach in cancer therapeutics. This approach allows clinicians to select or predict the response of patient’s tumour cells to various available anti-cancer therapeutics. Pre-clinical models that better predict patient outcomes is needed. Patient-derived explants (PDEs) have several advantages as a patient-proximal model. PDEs retain histological 3D architecture and phenotype of the primary tumour. However, the major disadvantage of PDEs is the longevity that is not compatible with the turnaround time (3-4 weeks) associated with receiving the whole exome sequencing results of the patient’s tumour and identification of candidate therapeutic options. Our study aims to establish a PDEs model from preserved samples to assess patients-specific responses to Immune checkpoint blockades.
Methods
A total of 29 Fresh PDEs collected from patients that underwent surgery were cultured on special cell culture inserts for 12 days. We have also investigated the possibility to preserve the explants using cryopreservation or cold-storage methodologies. After 3 weeks of cryopreservation and 7 days of cold-storage, PDEs were cultured following the same experimental set-up as the control. A total of 20 tumours explants from different conditions were chosen to perform ex vivo Immunotherapy treatments based on PD1/PDL1 in situ expression. Then, PDEs were maintained in culture for 7 days prior to antiPD1/antiPDL1 treatment. All slices at different conditions were characterized for cell viability, histopathological architecture, immune cells modulation.
Results
Our study indicate that cryopreservation method was more successful in preserving the original features of the tumours in comparison with the cold-storage. Our analysis to assess tumour kill and T-cell activation indicated that only fresh tumour and cryopreserved slices showed responses to antiPD1/antiPDL1.
Conclusions
Our study demonstrates feasibility of the application of PDEs culture combined with cryopreservation method as a novel ex vivo preclinical platform that helps to predict response to immunotherapy in individual patients and promotes the discovery of novel therapeutic approaches.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
The National Agency of Research Development in Health (ATRSS) Algeria.
Disclosure
All authors have declared no conflicts of interest.