Work

Survival impact of a KEAP1-NFE2L2 radiomics model in PDL1 ≥ 50% non-small cell lung cancer treated with pembrolizumab: the PEMBROMIC study

Year: 2025

Type: article

Abstract: New factors predicting response in patients with a PD-L1 tumor proportion score (TPS) ≥ 50% for locally advanced or metastatic non-small cell lung cancer (NSCLC) are needed to better select first-line therapy. Based on the literature, we previously developed a radiomic model predicting the KEAP1/NFE2L2 mutational status. This was a retrospective monocenter study including 94 consecutive patients with advanced or metastatic PD-L1 ≥ 50% NSCLC, treated with pembrolizumab, who underwent a pre-therapeutic FDG-PET/CT and were followed up for 1 year. Seventy-seven patients who did not progress within the first 60 days of treatment were analyzed. Each primary lesion was segmented by 2 physicians on PET and CT scans. Radiomic features were calculated using MIM software on both PET and CT imaging. A previously developed KEAP1/NFE2L2 radiomic prediction model (called MUTPET) was applied to this cohort using the initial FDG-PET/CT. The primary endpoint was the validation of the MUTPET model as a predictive factor of PFS via the non-invasive prediction of KEAP1/NEF2L2 mutation. The main characteristics of this cohort were: median age of 67.0 years [range, 48.0–84.0], sex ratio M/F = 60/17, 74.0% of patients with a histopathology of adenocarcinoma and 85.0% with a stage IV disease. The median follow-up was 20.0 months [range, 15.3–23.9]. Fifty-six (72.2%) patients experienced a disease progression with a median PFS of 11.8 months (CI95% 8.6–15.8) among which 51 (66.2%) died. In univariable analysis, MUTPET model was statistically significant as a predictive factor of improved PFS (HR = 0.51, CI95% 0.30–0.91, p = 0.02) whereas it was not statistically significant regarding OS (HR = 0.61, CI95% 0.34–1.11, p = 0.10). In multivariable analysis, the MUTPET model was associated with a HR of 0.6 (CI95% 0.34–1.06, p = 0.08). Combining the MUTPET prediction, the histology subtype and the existence of liver metastases, a multimodal nomogram was able to predict PFS (chi-test of 39.43, p < 0.0001). In PD-L1 TPS ≥ 50% NSCLC patients treated with pembrolizumab, our results suggest an improved PFS in patients predicted to be KEAP1/NFE2L2 mutated. What is already known on this topic The KEAP1/NFE2L2 axis is of paramount importance for its role in cellular response to oxidative stress. Several studies report the prognostic role of KEAP1/NFE2L2 mutations in patients treated with systemic treatments such as immunotherapy. Genetic testing is rarely to never performed due to its cost and lack of availability. A radiomics model based on PET and CT-extracted features was previously developed for the prediction of the KEAP1/NFE2L2 mutational status. What this study adds Using the previously developped KEAP/NFE2L2 prediction model, we demonstrated the impact of the KEAP1/NFE2L2 pathway on progression-free survival (PFS) in patients with PDL1 ≥ 50% advanced or metastatic non-small cell lung cancer (NSCLC) treated with first line pembrolizumab. Patients harboring a predicted mutation had an increased PFS when compared to non-mutated patients. How this study might affect research, practice or policy Our work validates the role of the KEAP1/NFE2L2 pathway for the prediction of response to pembrolizumab. This tool could be used for the choice between pembrolizumab only vs. chemo-immunotherapy as first-line for PDL1 ≥ 50% advanced or metastatic NSCLC patients.

Source: Cancer Imaging

DOI: 10.1186/s40644-025-00957-y