PD-L1 mRNA expression correlates with tumor growth rate in giant cell tumor of bone: a volumetric MRI analysis
摘要
Giant cell tumor of bone (GCTB) is a locally aggressive neoplasm with variable biological behavior. Programmed death-ligand 1 (PD-L1) has been implicated in tumor progression across multiple malignancies, but its relationship to growth kinetics in GCTB remains unclear. This study investigated whether PD-L1 mRNA expression correlates with tumor growth rate in extremity GCTB.
MethodsThis single-institution retrospective cohort study included 36 patients with GCTB treated surgically between January 2020 and December 2024. Of these, 18 provided consent for research use of tissue; four were excluded due to lack of serial MRI data, yielding a final cohort of 14 patients. PD-L1 mRNA levels were quantified using real-time PCR. Tumor volumes were segmented from MRI using 3D Slicer, and growth rate (cc/month) was calculated. Patients were stratified into high- and low-PD-L1 groups using the cohort median fold change (2.62) as an exploratory cutoff. Group comparisons used Mann–Whitney U and Fisher’s exact tests, and Spearman’s rank correlation analysis was performed to assess the relationship between continuous PD-L1 expression and tumor growth rate. Exploratory linear regressions were performed adjusting for age, sex, tumor site, and preoperative denosumab use.
ResultsMedian age was 32 years; 57% were male. Tumors with high PD-L1 expression showed faster growth than those with low expression (5.0 [1.3–7.1] vs. 0.8 [0.2–2.1] cc/month; p = 0.038). This relationship was further supported by a significant positive correlation between PD-L1 mRNA levels and tumor growth rate (ρ = 0.6, p = 0.026). The association remained significant in exploratory multivariable and robust regression analyses adjusting for covariates.
ConclusionsHigher PD-L1 mRNA expression correlated with accelerated tumor growth in extremity GCTB. These exploratory findings suggest PD-L1 may serve as a potential biomarker of tumor aggressiveness, warranting validation in larger cohorts.