Abstract 4363
Background
The combination of immune-checkpoint (IC) inhibitors with targeted therapies represent a new goal of immunotherapy, aimed at personalizing and potentiating the self-response against cancer. Organoids as novel 3D cancer models, allow the study in vitro of the tumor microenvironment (TME), including tumor-infiltrating lymphocytes (TILs) and their interaction with tumor cells. In this study we analyzed whether the combination of anti-PD-L1 drugs with MEK inhibitor (MEKi) affect the growth of organoids and TILs obtained from tumor biopsy of NSCLC patients.
Methods
Lung biopsies from 3 NSCLC patients were enzymatically digested. Cells were cultured in matrigel for 6 days and treated with atezolizumab or avelumab, alone or in combination with MEKi. Immunofluorescence (IF) staining for CD3, CD8 and CD45 was conducted; cells were also stained for FACS analysis with anti- CD45, CD3, CD4, CD8, CD14, CD56, CD19, CD11c, PD-1; a staining for EPCAM and PD-L1 allowed a better characterization of tumor cells. After 6 days of treatment, MTT assay verified cell viability; the expression levels of IFNg, IL-10, PD-1, PD-L1, TIM-3, LAG-3 and IDO-1 were analysed through real-time PCR.
Results
IF staining revealed that in organoids the interactions between tumor cells and TILs are preserved. FACS analysis confirmed that TILs were mainly TCD8+ and tumor cells analysed were EPCAM+ for almost 40%. The combination of anti PD-L1 and MEKi is associated with a reduction in organoid’s dimensions and viability, especially in PD-L1+ tumors and with a higher percentage of TCD8+/PD-1+ lymphocytes. The combination of MEKi with anti PD-L1 is also associated to a higher expression of the pro-inflammatory cytokine IFNg and a reduction of the anti-inflammatory IL10. The expression of IC molecules was also modified by this combination; in particular LAG-3 and IDO-1 expression were dramatically reduced.
Conclusions
Organoid models allow to study tumors more realistically, because they show some typical features of the organ they derive. This model become particularly useful for the analysis of TME of each patient and for the testing of combination drugs and the development of precision and personalized immunotherapies.
Clinical trial identification
Legal entity responsible for the study
Università degli Studi della Campania.
Funding
AIRC.
Editorial Acknowledgement
NA
Disclosure
All authors have declared no conflicts of interest.