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Updated: May 28, 2026
Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells
Published on: February 8, 2018
Prediction of Patients' Response to Immune Checkpoint Inhibitors Using Fluorescence Lifetime Imaging of Lymphocytes
Diana V Yuzhakova1, Anastasia I Kononova1,2, Anna V Izosimova1
1Institute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 10/1 Minin and Pozharsky Sq., 603005 Nizhny Novgorod, Russia.
Abstract:
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.
Insights
This study introduces a new method using fluorescence lifetime imaging (FLIM) to predict how well patients will respond to cancer immunotherapy by analyzing lymphocyte metabolism. This approach aids in personalized treatment selection for better outcomes.
Area of Science:
- Oncology
- Immunology
- Biophysics
Background:
- Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy but face challenges with patient resistance.
- Predicting immunotherapy response with biomarkers is crucial for effective treatment.
Purpose of the Study:
- To develop a personalized platform for predicting immunotherapy efficacy in melanoma.
- Utilize fluorescence lifetime imaging (FLIM) of lymphocyte autofluorescence for this prediction.
Main Methods:
- Tested FLIM of NAD(P)H autofluorescence on mouse lymphocytes for anti-CTLA-4 response.
- Assessed metabolic shifts in human lymphocytes using FLIM after anti-PD-1 or combined therapy.
- Evaluated T-cell activation and metabolic gene expression in vitro.
Main Results:
- Specific fluorescence decay parameters (α1, τ2) indicated lymphocyte activation by ICIs.
- Activation correlated with metabolic reprogramming including glycolysis, TCA cycle, and FAO.
- In vitro lymphocyte response accurately predicted clinical outcomes.
Conclusions:
- The developed FLIM platform shows promise for patient-specific immunotherapeutic drug screening.
- This technology can optimize personalized cancer treatment strategies.
