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Using 22C3 Anti-PD-L1 Antibody Concentrate on Biopsy and Cytology Samples from Non-small Cell Lung Cancer Patients
Published on: September 25, 2018
Age-Associated Targetable Genomic Alterations and PD-L1 Expression in 2509 Patients With Pulmonary Ground-Glass
Wen-Fang Tang1, Si-Qi Huang1, Yi-Duo Lin1
1Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Aim:
To investigate the landscape of targetable genomic alterations and programmed cell death ligand 1 (PD-L1) expression in pulmonary ground-glass opacities (GGOs) and their association with age.
Methods:
A total of 2509 patients with GGOs were retrospectively analyzed. Tumor characteristics, PD-L1 expression, and prevalence of targetable alterations were compared across age groups.
Results:
In GGOs, the mutation rates of EGFR (61.5%) and ERBB2 (12.0%) were relatively high, whereas those of KRAS (8.2%) and ALK rearrangements (2.3%) were relatively low. The patients exhibited a low tumor mutational burden (TMB), and PD-L1 expression was negative in 86.7% of cases. TMB, PD-L1 expression, and the mutation rates of EGFR, KRAS, and MET increased significantly with age, whereas the rates of ERBB2 mutations, ALK rearrangements, and RET rearrangements decreased significantly with age. Age was identified as an independent predictor for the above eight variables. The optimal age cutoff was determined to be 53 years. Compared with the younger age group (< 53 years), the older age group (≥ 53 years) showed a 31.6%, 130.4%, and 800.0% higher likelihood of harboring EGFR, KRAS, and MET mutations, respectively. Conversely, compared with the older age group, the younger age group showed a 289.1%, 94.1%, and 108.7% higher likelihood of harboring ERBB2 mutations, ALK rearrangements, and RET rearrangements, respectively.
Conclusions:
GGOs exhibit a distinct genomic and PD-L1 profile with significant age-related heterogeneity, providing insights for age-stratified therapeutic strategies.
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