p53 expression and NLR could recognize distinct subtypes of lung adenocarcinoma with high expression of PD-L1 (TPS ≥ 50%), defined with 22C3 antibody
BACKGROUND: Lung adenocarcinoma (LUAD) with high expression of PD-L1 (TPS ≥ 50%) is a distinct subset of NSCLC and a potential immunotherapy candidate. An improved understanding of the heterogeneity of PD-L1-high LUAD patients and the recognition of other biomarkers combined with PD-L1 could facilitate more precise use of PD-1 inhibitors in clinical practice. METHODS: Surgically resected tumour tissues from 69 LUAD patients with a PD-L1 TPS ≥ 50% defined by 22C3 antibody were tested for p53 and IFN-γ protein expression using immunohistochemistry. The densities of CD8 and Granzyme B-positive T cells were evaluated by immunohistochemistry. EGFR mutation was detected by RT‒PCR, ALK rearrangement was examined by a fluorescence in situ hybridization (FISH) assay, and TP53 gene mutations were sequenced using Sanger sequencing. RESULTS: Differences in clinicopathological features, including age and spread through the air space (STAS), were observed between patients with higher PD-L1 expression (TPS ≥ 50%, < 70%) and those with the highest PD-L1 expression (TPS ≥ 70%). LUAD patients whose PD-L1 TPS was ≥ 70% and whose p53 protein abnormal expression or NLR was < 5 had higher densities of CD8-positive tumour-infiltrating lymphocytes (TILs) and Granzyme B-positive T cells as well as higher IFN-γ protein expression than those whose TPS was < 70%, those whose p53 protein expression was normal, or those whose NLR was ≥ 5. CONCLUSIONS: The present study is the first to reveal that distinct subtypes of PD-L1-high LUAD can be identified on the basis of p53 protein expression and the NLR. p53 expression and the NLR can recognize a subtype with brisk immune cell cytotoxicity that might potentially respond better to PD-1 inhibitors.
Authors
- Mengqi Huang (ORCID: https://orcid.org/0000-0002-1675-8575)
- 冯振中
- Yuchen Huang (ORCID: https://orcid.org/0009-0009-3812-7975)
- H B Wu (ORCID: https://orcid.org/0000-0002-0721-9596)
- Xiaoliang Zhang
- Ming Li
Institutions
- University of Science and Technology of China (CN)
- Anhui Medical University (CN)
- Second Affiliated Hospital of Anhui Medical University (CN)
Publication Details
- Journal
- Discover Oncology
- Published
- 2026-05-23
- DOI
- https://doi.org/10.1007/s12672-026-05228-1
- Primary Topic
- Cancer Immunotherapy and Biomarkers
- Type
- article
- Field-Weighted Citation Impact
- 0.00