Le rôle des états interactifs des régulateurs des points de contrôle immunitaires dans le cancer : déterminé par l'imagerie quantitative avancée.

The role of interactive states of immune checkpoint regulators in cancer : determined by advanced quantitative imaging. PD-1/PD-L1 and CTLA-4/CD80 are checkpoints designed to promote self tolerance and avoid autoimmune diseases. Cancers modulate these checkpoints, by upregulating their cognate ligands, to avoid immune destruction. Immune checkpoint blockade therapies have enhanced cancer treatment, however, only a small subset of patients experience durable effects. Most patients are stratified for anti-PD-1 or anti-CTLA-4 treatments based on PD-L1 expression. Ligand expression is currently assessed by immunohistochemistry approaches, which are subjective, lack quantitation and a dynamic range. We developed a novel quantitative imaging platform, underpinned by time-resolved Förster resonance energy transfer (FRET) determined by frequency domain fluorescence lifetime imaging microscopy (FLIM) to spatially quantitate these checkpoint interactions at a <10nm resolution. This assay is termed immune-FRET (iFRET). We validated the ability of iFRET to measure PD-1/PD-L1 and CTLA-4/CD80 engagements in a cell co-culture assay and then applied iFRET to determine PD-1/PD-L1 interactions in a retrospective study with malignant melanoma and malignant non-small cell lung carcinoma (NSCLC). In both melanoma and NSCLC, increased PD-1/PD-L1 interaction, determined by iFRET, correlated with a worsened survival. PD-L1 expression failed to correlate with patient outcome. We applied iFRET to PD-1/PD-L1 and CTLA-4/CD80 in a prospective study. A subset of colorectal cancer patients with lung metastases who fail to respond to classical treatments have their metastases treated by radiofrequency ablation (RFA). Between RFA treatments, it has been documented, that an abscopal effect may occur between the treatment of lungs one and two. We applied iFRET to assess these interactions in pre- and post-RFA treated lung metastases. Whilst we could not directly report on the mechanisms of an abscopal effect, we detected differential PD-1/PD-L1 and CTLA-4/CD80 interaction patterns within patients, which may be used to predict which therapies a patient would respond to. We also detected a negative correlation between PD-1/PD-L1 interaction and intratumoral CD3+ density. Neither checkpoint engagement correlated with ligand expression. This could change the paradigm of immune oncology and the rationale behind selecting patient treatments. Lastly, we sought to apply iFRET and CRISPR/Cas12 to probe the intracellular mechanisms by which the ITSM of PD-1 effects its negative effects. We generated Y248A and Y248E mutations in the ITSM of PD-1 and plan to probe if SHP-2 alone or SHP-1 and SHP-2 are responsible for signal transduction. We also plan to assess whether Y248 phosphorylation state poses a regulatory mechanism that regulates PD-1/PD-L1 interaction state. These results indicate a novel technique by which to assess immune checkpoint engagement in patient samples. This may be applied to a range of immune checkpoints. This gives rise to the notion of quantitative immune surveyance which may monitor the functional proteomics of patients over time. To summarise, utilising iFRET to carry out quantitative immune surveyance may change the way patients are selected for immunotherapies and may provide a mechanism by which to monitor treatment response.