Expression of PD-L1 through evolution phase from pre-invasive to invasive lung adenocarcinoma

Zhou, Jiaxin; Hua, Lin; Ni, Zheng; Luo, Rongkui; Yang, Dawei; Feng, Mingxiang; Zhang, Yong

doi:10.1186/s12890-023-02310-0

Cited by 5 publications

(2 citation statements)

References 29 publications

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“…Furthermore, Ki67 was the dominant factor influencing the expression of PD-L1. It was suggested by J. Zhou et al [41] that reduced PD-L1 expression in AIS or MIA was due to the low expression of Ki67 and that advanced stage LUAD corresponded to high expression of Ki67. Meta-analysis has indicated that high Ki-67 expression is a valuable predictor for advanced TNM stages [9].…”

Section: Discussionmentioning

confidence: 99%

Factors correlating the expression of PD-L1

Lu,

Wang,

Liu

2024

BMC Cancer

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Objective PD-L1 was an important biomarker in lung adenocarcinoma. The study was to confirm the most important factor affecting the expression of PD-L1 remains undetermined. Methods The clinical records of 1045 lung adenocarcinoma patients were retrospectively reviewed. The High-Resolution Computed Tomography (HRCT) scanning images of all the participants were analyzed, and based on the CT characteristics, the adenocarcinomas were categorized according to CT textures. Furthermore, PD-L1 expression and Ki67 index were detected by immunohistochemistry. All patients underwent EGFR mutation detection. Results Multivariate logistic regression analysis revealed that smoking (OR: 1.73, 95% CI: 1.04–2.89, p = 0.004), EGFR wild (OR: 1.52, 95% CI: 1.11–2.07, p = 0.009), micropapillary subtypes (OR: 2.05, 95% CI: 1.46–2.89, p < 0.0001), and high expression of Ki67 (OR: 2.02, 95% CI: 1.44–2.82, p < 0.0001) were independent factors which influence PD-L1 expression. In univariate analysis, tumor size > 3 cm and CT textures of pSD showed a correlation with high expression of PD-L1. Further analysis revealed that smoking, micropapillary subtype, and EGFR wild type were also associated with high Ki67 expression. Moreover, high Ki67 expression was observed more frequently in tumors of size > 3 cm than in tumors with ≤ 3 cm size as well as in CT texture of pSD than lesions with GGO components. In addition, multivariate logistic regression analysis revealed that only lesions with micropapillary components correlated with pSD (OR: 3.96, 95% CI: 2.52–5.37, p < 0.0001). Conclusion This study revealed that in lung adenocarcinoma high Ki67 expression significantly influenced PD-L1 expression, an important biomarker for immune checkpoint treatment.

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Section: Discussionmentioning

confidence: 99%

Factors correlating the expression of PD-L1

Lu,

Wang,

Liu

2024

BMC Cancer

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“…High eukaryotic initiation factor 3 (eIF3D) expression is independently associated with lower OS probability in LUAD [ 11 ]. Programmed death-ligand 1 (PD-L1) expression was positively correlated with the emergence of invasiveness and pathological subtype or biological behavior of early-stage lung adenocarcinoma [ 12 ]. However, these biomarkers are currently insufficient for the diagnosis and prognosis prediction of LUAD because of their complex molecular mechanisms and disease heterogenicity.…”

Section: Introductionmentioning

confidence: 99%

NGEF is a potential prognostic biomarker and could serve as an indicator for immunotherapy and chemotherapy in lung adenocarcinoma

Chen,

Zhang,

et al. 2024

BMC Pulm Med

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Background Neuronal guanine nucleotide exchange factor (NGEF) plays a key role in several cancers; however, its role in lung adenocarcinoma (LUAD) remains unclear. The aim of this study was to evaluate the efficacy of NGEF as a prognostic biomarker and potential therapeutic target for LUAD. Methods NGEF expression data for multiple cancers and LUAD were downloaded from multiple databases. The high- and low-NGEF expression groups were constructed based on median NGEF expression in LUAD samples, and then performed Kaplan–Meier survival analysis. Differentially expressed genes (DEGs) from the two NGEF expression groups were screened and applied to construct a protein-protein interaction network. The primary pathways were obtained using gene set enrichment analysis. The associations between NGEF expression and clinical characteristics, immune infiltration, immune checkpoint inhibitors (ICIs), sensitivity to chemotherapy, and tumor mutation burden (TMB) were investigated using R. Levels of NGEF expression in the lung tissue was validated using single-cell RNA sequencing, quantitative polymerase chain reaction (qPCR), immunohistochemical staining, and western blot analysis. Results The expression of NGEF mRNA was upregulated in multiple cancers. mRNA and protein expression levels of NGEF were higher in patients with LUAD than in controls, as validated using qPCR and western blot. High NGEF expression was an independent prognostic factor for LUAD and was associated with advanced tumor stage, large tumor size, more lymph node metastasis, and worse overall survival (OS). A total of 182 overlapping DEGs were screened between The Cancer Genome Atlas and GSE31210, among which the top 20 hub genes were identified. NGEF expression was mainly enriched in the pathways of apoptosis, cell cycle, and DNA replication. Moreover, elevated NGEF expression were associated with a high fraction of activated memory CD4+ T cells and M0 macrophages; elevated expression levels of the ICIs: programmed cell death 1 and programmed cell death 1 ligand 1 expression; higher TMB; and better sensitivity to bortezomib, docetaxel, paclitaxel, and parthenolide, but less sensitivity to axitinib and metformin. Conclusion NGEF expression is upregulated in LUAD and is significantly associated with tumor stages, OS probability, immune infiltration, immunotherapy response, and chemotherapy response. NGEF may be a potential diagnostic and prognostic biomarker and therapeutic target in LUAD.

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Prognostic implications, genomic and immune characteristics of lung adenocarcinoma with lepidic growth pattern

Li,

Chen,

et al. 2024

J Clin Pathol

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AimsConflicting data were provided regarding the prognostic impact and genomic features of lung adenocarcinoma (LUAD) with lepidic growth pattern (LP+A). Delineation of the genomic and immune characteristics of LP+A could provide deeper insights into its prognostic implications and treatment determination.MethodsWe conducted a search of articles in PubMed, EMBASE and the Cochrane Library from inception to January 2024. A domestic cohort consisting of 52 LUAD samples was subjected to whole-exome sequencing as internal validation. Data from The Cancer Genomic Atlas and the Gene Expression Omnibus datasets were obtained to characterise the genomic and immune profiles of LP+A. Pooled HRs and rates were calculated.ResultsThe pooled results indicated that lepidic growth pattern was either predominant (0.35, 95% CI 0.22 to 0.56, p<0.01) or minor (HR 0.50, 95% CI 0.36 to 0.70, p<0.01) histological subtype was associated with favourable disease-free survival. Pooled gene mutation rates suggested higher EGFR mutation (0.55, 95% CI 0.46 to 0.64, p<0.01) and lower KRAS mutation (0.14, 95% CI 0.02 to 0.25, p=0.02) in lepidic-predominant LUAD. Lepidic-predominant LUAD had lower tumour mutation burden and pooled positive rate of PD-L1 expression compared with other subtypes. LP+A was characterised by abundance in resting CD4+memory T cells, monocytes and γδ T cells, as well as scarcity of cancer-associated fibroblasts.ConclusionsLP+A was a unique histological subtype with a higher EGFR mutation rate, lower tumour mutation burden and immune checkpoint expression levels. Our findings suggested potential benefits from targeted therapy over immunotherapy in LP+A.

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Expression of PD-L1 through evolution phase from pre-invasive to invasive lung adenocarcinoma

Cited by 5 publications

References 29 publications

Factors correlating the expression of PD-L1

Factors correlating the expression of PD-L1

NGEF is a potential prognostic biomarker and could serve as an indicator for immunotherapy and chemotherapy in lung adenocarcinoma

Prognostic implications, genomic and immune characteristics of lung adenocarcinoma with lepidic growth pattern

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