Background/Objectives: Although immune checkpoint inhibitors (ICIs) have dramatically transformed the landscape of cancer treatment, a significant percentage of patients are resistant to therapy. Identifying biomarkers to accurately predict patient response prior to treatment remains one of the key challenges in this field. Our study aimed to develop a platform for personalized prediction of immunotherapy efficacy for melanoma using isolated lymphocytes and fluorescence lifetime imaging (FLIM) of their autofluorescence. Methods: At the first stage, the ability of FLIM of the autofluorescent coenzyme NAD(P)H to resolve cellular response to anti-CTLA-4 was tested on lymphocytes isolated from lymphatic nodes (LNs) of mice with the B16 melanoma model. Then, cellular metabolic shifts in response to treatment with anti-PD-1 or its combination with anti-CTLA-4 were assessed via FLIM of patients’ blood lymphocytes. Activation of T-cells and alterations in the expression of metabolic genes after the treatment in vitro were additionally evaluated. Results: Fluorescence decay parameters α1 (free NAD(P)H fraction) and τ2 (protein-bound NAD(P)H lifetime) were identified as sensitive markers of lymphocyte activation after the treatment with immune checkpoint inhibitors. Responsive samples exhibited an increase in these parameters, which was associated with metabolic reprogramming toward more active glycolysis, the TCA cycle, fatty acid oxidation (FAO) and synthesis, the pentose phosphate pathway (PPP) and mitochondrial biogenesis. Importantly, the in vitro response of primary lymphocytes isolated prior to treatment correlated well with subsequent clinical outcomes. Conclusions: The proposed platform represents a promising solution for patient-specific immunotherapeutic drug screening and personalized treatment optimization.
Yuzhakova et al. (Tue,) studied this question.