Related Experiment Video
Updated: Aug 17, 2025
Utilizing 18F-FDG PET/CT Imaging and Quantitative Histology to Measure Dynamic Changes in the Glucose Metabolism in Mouse Models of Lung Cancer
Published on: July 21, 2018
Tumor glycolytic profiling through 18F-FDG PET/CT predicts immune checkpoint inhibitor efficacy in advanced NSCLC
Saulo Brito Silva1, Carlos Wagner S Wanderley2, José Flavio Gomes Marin1
1Hospital Sírio-Libanês, Sao Paulo, Brazil.
Background:
A significant proportion of patients with non-small-cell lung cancer (NSCLC) do not respond to immune checkpoint inhibitors (ICIs). Since metabolic reprogramming with increased glycolysis is a hallmark of cancer and is involved in immune evasion, we used 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) to evaluate the baseline glycolytic parameters of patients with advanced NSCLC submitted to ICIs, and assessed their predictive value.
Methods:
18F-FDG PET/CT results in the 3 months before ICIs treatment were included. Maximum standardized uptake values, whole metabolic tumor volume (wMTV), and whole-body total lesion glycolysis (wTLG) were evaluated. Cutoff values for high or low glycolytic categories were determined using receiver-operating characteristic curves. Progression-free survival (PFS) and overall survival (OS) were evaluated. Patients with a complete response and a matching group with resistance to ICIs underwent immunohistochemistry analysis. An unsupervised k-means clustering model integrating programmed cell death ligand 1 (PD-L1) expression, glycolytic parameters, and ICIs therapy was performed.
Results:
In all, 98 patients were included. Lower baseline 18F-FDG PET/CT parameters were associated with responses to ICIs. Patients with low wMTV or wTLG had improved PFS and OS. High wTLG, strong tumor expression of glucose transporter-1, and lack of responses were significantly associated. Patients with low glycolytic parameters benefited from ICIs, regardless of chemotherapy. Conversely, those with high parameters benefited from the addition of chemotherapy. Patients with higher wTLG and lower PD-L1 were associated with progression and worse survival to ICIs monotherapy.
Conclusions:
Glycolytic metabolic profiles established through baseline 18F-FDG PET/CT are useful biomarkers for evaluating ICI therapy in advanced NSCLC.
Insights
Baseline 18F-FDG PET/CT scans can predict non-small-cell lung cancer response to immune checkpoint inhibitors (ICIs). Lower glycolytic parameters indicate better outcomes, guiding personalized treatment strategies for advanced NSCLC patients.
Area of Science:
- Oncology
- Nuclear Medicine
- Radiomics
Background:
- Many non-small-cell lung cancer (NSCLC) patients do not respond to immune checkpoint inhibitors (ICIs).
- Cancer cells exhibit metabolic reprogramming, including increased glycolysis, which aids immune evasion.
- 18F-FDG PET/CT assesses metabolic activity, offering potential insights into treatment response.
Purpose of the Study:
- To evaluate baseline glycolytic parameters using 18F-FDG PET/CT in advanced NSCLC patients undergoing ICIs.
- To determine the predictive value of these metabolic parameters for treatment response and survival outcomes.
Main Methods:
- 18F-FDG PET/CT scans were analyzed for maximum standardized uptake values, whole metabolic tumor volume (wMTV), and whole-body total lesion glycolysis (wTLG) before ICIs treatment.
- Receiver-operating characteristic curves defined high/low glycolytic categories.
- Progression-free survival (PFS) and overall survival (OS) were assessed; immunohistochemistry was performed on responders and non-responders.
Main Results:
- Lower baseline 18F-FDG PET/CT parameters (wMTV, wTLG) correlated with better response to ICIs and improved PFS and OS.
- High wTLG and strong glucose transporter-1 expression were linked to poor response.
- Patients with low glycolytic parameters benefited from ICIs alone, while those with high parameters benefited from combined chemotherapy.
- High wTLG and low PD-L1 expression predicted progression and worse survival with ICIs monotherapy.
Conclusions:
- Baseline 18F-FDG PET/CT glycolytic profiles serve as valuable biomarkers for predicting ICI therapy efficacy in advanced NSCLC.
- Metabolic imaging can help stratify patients for optimal treatment selection, including chemotherapy combinations.
- These findings support the integration of metabolic profiling into NSCLC treatment decision-making.
