[Advances in the Influence of EGFR Mutation on the PD-L1 Expression in Non-small Cell Lung Cancer].
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ABSTRACT:
SUBMITTER: Zhi X
PROVIDER: S-EPMC6935036 | biostudies-literature | 2019 Dec
REPOSITORIES: biostudies-literature
Publications
[Advances in the Influence of EGFR Mutation on the PD-L1 Expression in Non-small Cell Lung Cancer].
Zhi Xiaoyu X Li Weiwei W Wang Shaowei S Wang Jinliang J
Zhongguo fei ai za zhi = Chinese journal of lung cancer 20191201 12
Researches on the inhibitors of programmed death-1 (PD-1) and programmed death-1 ligand (PD-L1) enjoy considerable breakthroughs in recent years, which has brought relative changes in the therapeutic model of non-small cell lung cancer (NSCLC) at an unexpected speed. However, it seems that PD-1/PD-L1 inhibitors are less effective in patients with epidermal growth factor receptor (EGFR) mutation than those without. Previous studies have shown that the expression rate of PD-L1 on tumor cells is co ...[more]
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Project description:BackgroundEvidence on the influence of programmed death-ligand 1 (PD-L1) expression on the efficacy of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in EGFR-mutant non-small cell lung cancer (NSCLC) patients is at variance.MethodsA single-center retrospective study was conducted to evaluate the influence of PD-L1 expression on the efficacy of EGFR-TKIs for NSCLC patients with EGFR mutation. Clinical information was retrieved from electronic medical records. The patients were divided into three subgroups according to PD-L1 expression level: PD-L1 < 1% (negative), PD-L1 1%-49% and PD-L1 ≥ 50%. The clinicopathological features, overall response rate (ORR), progression-free survival (PFS) and comutation information were collected and compared between the three subgroups.ResultsA total of 117 patients were included. For PD-L1 < 1%, PD-L1 1%-49% and PD-L1 ≥ 50% group, there were 39 (33.3%), 51 (43.5%) and 27 (23.0%) patients respectively, and the ORR was 43.2%, 64.0%, and 51.9%, respectively (p = 0.162), and the median progression-free survival (mPFS) was 22.0 months (95% CI: 14.0-29.9 months), 15.4 months (95% CI: 8.9-21.8 months) and 13.0 months (95% CI: 10.6-15.3 months), respectively (log-rank, p = 0.01). The mPFS was negatively correlated with PD-L1 expression level (r = -0.264, p = 0.041) and PD-L1 expression was an independent risk factor for worse PFS of EGFR-TKIs in multivariate Cox regression. Patients with concurrent TP53 mutation had shorter PFS (p = 0.039) and the patients harboring both mutant TP53 and positive PD-L1 had the shortest PFS (p = 0.006).ConclusionsThe efficacy of EGFR-TKIs was influenced by the baseline PD-L1 expression. Higher PD-L1 expression was associated with shorter PFS. The combined indicators of TP53 and PD-L1 identified subgroups showing divergent benefits from EGFR-TKIs.
| S-EPMC10447169 | biostudies-literature
Project description:ObjectiveThe detection of epidermal growth factor receptor (EGFR) mutation and programmed death ligand-1 (PD-L1) expression status is crucial to determine the treatment strategies for patients with non-small-cell lung cancer (NSCLC). Recently, the rapid development of radiomics including but not limited to deep learning techniques has indicated the potential role of medical images in the diagnosis and treatment of diseases.MethodsEligible patients diagnosed/treated at the West China Hospital of Sichuan University from January 2013 to April 2019 were identified retrospectively. The preoperative CT images were obtained, as well as the gene status regarding EGFR mutation and PD-L1 expression. Tumor region of interest (ROI) was delineated manually by experienced respiratory specialists. We used 3D convolutional neural network (CNN) with ROI information as input to construct a classification model and established a prognostic model combining deep learning features and clinical features to stratify survival risk of lung cancer patients.ResultsThe whole cohort (N = 1262) was divided into a training set (N = 882, 70%), validation set (N = 125, 10%), and test set (N = 255, 20%). We used a 3D convolutional neural network (CNN) to construct a prediction model, with AUCs of 0.96 (95% CI: 0.94-0.98), 0.80 (95% CI: 0.72-0.88), and 0.73 (95% CI: 0.63-0.83) in the training, validation, and test cohorts, respectively. The combined prognostic model showed a good performance on survival prediction in NSCLC patients (C-index: 0.71).ConclusionIn this study, a noninvasive and effective model was proposed to predict EGFR mutation and PD-L1 expression status as a clinical decision support tool. Additionally, the combination of deep learning features with clinical features demonstrated great stratification capabilities in the prognostic model. Our team would continue to explore the application of imaging markers for treatment selection of lung cancer patients.
| S-EPMC8741343 | biostudies-literature
Project description:Programmed death ligand (PD-L1) expression was associated with tumor immune escape and subsequent poor prognosis in non-small cell lung cancer (NSCLC). This expression was higher in patients with EGFR-mutated NSCLC tumors than in those with EGFR-wild-type (WT) NSCLC tumors. We therefore hypothesized that poor prognosis mediated by higher PD-L1 may be partially through conferring resistance to tyrosine kinase inhibitor (TKI) in NSCLC regardless of EGFR mutation. The change in PD-L1 expression following gene manipulation corresponded with changes in expression of HIF-1α and YAP1. The expression of HIF-1α and YAP1 was concomitantly decreased by PD-L1 silencing or by ROS scavenger treatment (N-acetylcysteine, NAC); however, a ROS inducer treatment (pyocyanin) completely reversed the decreased expression of both genes in EGFR-mutated and -wild-type (WT) NSCLC cells. The MTT assay indicated that the inhibitory concentration of gefitinib yielding 50% cell viability (IC50) depended on PD-L1-mediated YAP1 expression. Mechanistic studies indicated that upregulation of YAP1 by PD-L1 might be responsible for EGFR mutation-independent TKI resistance via the ROS/HIF-1α axis. An unfavorable TKI response was more common in patient tumors with high PD-L1 or YAP1 mRNA expression than in patient tumors with low mRNA expression of these genes. In conclusion, PD-L1 might confer EGFR mutation-independent TKI resistance in NSCLC cells via upregulation of YAP1 expression.
| S-EPMC5797002 | biostudies-literature
Project description:In recent years, immunotherapy has revolutionized and changed the standard of care in patients with advanced non-small cell lung cancer (NSCLC). Immune checkpoint inhibitors, fundamentally those that act by blocking the programmed cell death receptor-1 (PD-1) and its ligand the programmed cell death ligand-1 (PD-L1) have emerged as novel treatment strategies in NSCLC, demonstrating undoubted superiority over chemotherapy in terms of efficacy. Several of these immune checkpoint modulators have recently gained regulatory approval for the treatment of advanced NSCLC, such as nivolumab, atezolizumab and pembrolizumab in first-line (only the latter) and second-line settings, and more recently, durvalumab as maintenance after chemoradiotherapy in locally advanced disease. There is consensus that PD-L1 expression on tumor cells predicts responsiveness to PD-1 inhibitors in several tumor types. Hence PD-L1 expression evaluated by immunohistochemistry (IHC) is currently used as a clinical decision-making tool to support the use of checkpoint inhibitors in NSCLC patients. However, the value of PD-L1 as the 'definitive' biomarker is controversial as its testing is puzzled by multiple unsolved issues such as the use of different staining platforms and antibodies, the type of cells in which PD-L1 is assessed (tumor versus immune cells), thresholds used for PD-L1-positivity, or the source and timing for sample collection. Therefore, newer biomarkers such as tumor mutation burden and neoantigens as well as biomarkers reflecting host environment (microbiome) or tumor inflamed microenvironment (gene expression signatures) are being explored as more reliable and accurate alternatives to IHC for guiding treatment selection with checkpoint inhibitors in NSCLC.
| S-EPMC5898658 | biostudies-literature
Project description:Data are limited on programmed death ligand 1 (PD-L1) expression in epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC).We retrospectively evaluated the relationship between PD-L1 expression and recurrence-free survival (RFS) and overall survival in 319 patients with EGFR-mutant NSCLC who were treated at Samsung Medical Center from 2006 to 2014. Membranous PD-L1 expression on tumor cells was measured using the PD-L1 IHC 22C3 pharmDx antibody and reported as tumor proportion score (TPS). Kaplan-Meier methods, log-rank test, and Cox proportional hazards models were used for survival analysis.All patients had ?1 EGFR mutation-54% in exon 19 and 39% in exon 21. Overall, 51% of patients had PD-L1-positive tumors. The prevalence of PD-L1 positivity was higher among patients with stages II-IV versus stage I disease (64% vs. 44%) and among patients with other EGFR mutations (75%) than with L858R mutation (39%) or exon 19 deletion (52%). PD-L1 positivity was associated with shorter RFS, with an adjusted hazard ratio of 1.52 (95% confidence interval [CI], 0.81 to 2.84; median, 18 months) for the PD-L1 TPS ? 50% group, 1.51 (95% CI, 1.02 to 2.21; median, 31 months) for the PD-L1 TPS 1%-49% group, and 1.51 (95% CI, 1.05 to 2.18) for the combined PD-L1-positive groups (TPS ? 1%) compared with the PD-L1-negative group (median, 35 months).PD-L1 expression is associated with disease stage and type of EGFR mutation. PD-L1 positivity might be associated with worse RFS among patients with surgically treated EGFR-mutant NSCLC.
| S-EPMC5784638 | biostudies-literature
Project description:ObjectiveTo investigate the predictive value of programmed death-ligand 1 (PD-L1) expression in non-small cell lung cancer (NSCLC) patients treated with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs).MethodsWe conducted a systemic search of PubMed, EMBASE, and the Cochrane Library from 1 January 2000 to 30 August 2020, to identify related studies. We combined the hazard ratio (HR) and 95% confidence interval (CI) to assess the correlation of PD-L1 expression with progression-free survival (PFS) and overall survival (OS). We assessed the quality of the included studies by the Newcastle-Ottawa Scale (NOS). We performed subgroup analyses based on immunohistochemistry (IHC) scoring system, IHC antibodies, sample size, countries, and survival analysis mode. Sensitivity analysis and evaluation of publication bias were also performed.ResultsTwelve studies including 991 patients met the criteria. The mean NOS score was 7.42 ± 1.19. Patients with high PD-L1 expression was associated with poorer PFS (HR = 1.90; 95% CI = 1.16-3.10; P = 0.011), while there was no association between PD-L1 expression and OS (HR = 1.19; 95% CI = 0.99-1.43; P = 0.070). Subgroup analysis prompted IHC scoring systems, IHC antibodies, and sample size have important effects on heterogeneity. The pooled results were robust according to the sensitivity analysis.ConclusionsThe result of this meta-analysis suggested that PD-L1 expression might be a predictive biomarker for EGFR-mutant non-small cell lung cancer treated with EGFR-TKIs.
| S-EPMC8106834 | biostudies-literature
Project description:EGFR-mutant non-small cell lung cancer (NSCLC) that developed acquired resistance to EGFR-tyrosine kinase (TKI) are potential candidates for programmed death 1 (PD1) inhibitor.TPS≥1% for PD-L1 and low CD8 + TIL in post-TKI tumor showed a trend for a lower PFS of EGFR-TKIs (14.2 vs 9.9 months; P = 0.060) (cohort A). Only 2 of 22 specimens (9.1%) with an acquired EGFR exon 20 T790M mutation exhibited in post-TKI TPS≥50% for PD-L1. The degree in post-TKI tumor of PD-L1 expression was varied in 19 patients (40.5%), with 10 (21.2%) showing higher levels in the resistant biopsy (cohort B). Among the post-TKI high TPS groups, median PFS with low post- TKI CD8 + TIL scores treated with EGFR-TKIs (6.6 months) was significantly lower than that for the other patients (14.2 months; P = 0.015).The change of PD-L1 expression was accompanied by dynamic change in CD8 + TILs and might reflect diverse mechanism of resistance to EGFR-TKI therapy.We identified 69 patients (cohort A) with sufficient post-TKI tumor tissues and 47 patients (cohort B) with paired tumor tissues available. TPS for PD-L1 expression of tumor cells and CD8 + TILs score in tumor specimens were determined by immunohistochemistry.
| S-EPMC5746096 | biostudies-literature
Project description:BackgroundProgrammed cell death ligand-1 (PD-L1) and ligand-2 (PD-L2) interaction with programmed cell death protein-1 (PD-1) represent an immune-inhibiting checkpoint mediating immune evasion and is, accordingly, an important target for blockade-based immunotherapy in cancer. In non-small-cell lung cancer (NSCLC), improved understanding of PD-1 checkpoint blockade-responsive biology and identification of biomarkers for prediction of a clinical response to immunotherapy is warranted. Thus, in the present study, we systematically described PD-L1 and PD-L2 expression correlated genes in NSCLC.MethodsWe performed comparative retrospective analyses to identify PD-L1 and PD-L2 mRNA expression correlated genes in NSCLC. For this, we examined available datasets from the cancer cell line encyclopedia (CCLE) project lung non-small-cell (Lung_NSC) and the cancer genome atlas (TCGA) projects lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC).ResultsAnalysis of the CCLE dataset Lung_NSC identified expression correlation between PD-L1 and PD-L2. Moreover, we identified expression correlation between 489 genes and PD-L1, 191 genes and PD-L2, and 111 genes for both. PD-L1 and PD-L2 also expression correlated in TCGA datasets LUAD and LUSC. In LUAD, we identified expression correlation between 257 genes and PD-L1, 914 genes and PD-L2, and 211 genes for both. In LUSC, we identified expression correlation between 26 genes and PD-L1, 326 genes and PD-L2, and 13 genes for both. Only a few genes expression correlated with PD-L1 and PD-L2 across the CCLE and TCGA datasets. Expression of Interferon signaling-involved genes converged in particular with the expression correlated genes for PD-L1 in Lung_NSC, for PD-L2 in LUSC, and for both PD-L1 and PD-L2 in LUAD. In LUSC, PD-L1, and to a lesser extent PD-L2, expression correlated with chromosome 9p24 localized genes, indicating a chromosome 9p24 topologically associated domain as an important driver of in particular LUSC PD-L1 expression. Expression correlation analyses of the PD-L1 and PD-L2 receptors programmed cell death protein-1 (PD-1), Cluster of differentiation 80 (CD80), and Repulsive guidance molecule B (RGMB) showed that PD-1 and CD80 expression correlated with both PD-L1 and PD-L2 in LUAD. CD80 expression correlated with PD-L2 in LUSC.ConclusionsWe present gene signatures associated with PD-L1 and PD-L2 mRNA expression in NSCLC which could possess importance in relation to understand PD-1 checkpoint blockade-responsive biology and development of gene signature based biomarkers for predicting clinical responses to immunotherapy.
| S-EPMC6545701 | biostudies-literature
Project description:Lung cancer is the leading cause of cancer death in males and the second leading cause of death in females worldwide. Non-small-cell lung cancer (NSCLC) is the main pathological type of lung cancer, and most newly diagnosed NSCLC patients cannot undergo surgery because the disease is already locally advanced or metastatic. Despite chemoradiotherapy and targeted therapy improving clinical outcomes, overall survival remains poor. Immune checkpoint blockade, especially blockade of programmed death-1 (PD-1) receptor and its ligand PD-L1, achieved robust responses and improved survival for patients with locally advanced/metastatic NSCLC in preclinical and clinical studies. However, with regard to PD-1/PD-L1 checkpoint blockade as monotherapy or in combination with other antitumor therapies, such as chemotherapy, radiotherapy (including conventional irradiation and stereotactic body radiotherapy), and target therapy, there are still many unknowns in treating patients with NSCLC. Despite this limited understanding, checkpoint blockade as a novel therapeutic approach may change the treatment paradigm of NSCLC in the future. Here we review the main results from completed and ongoing studies to investigate the feasibility of PD-1/PD-L1 inhibitors, as monotherapy or combinatorial agents in patients with locally advanced and metastatic NSCLC, and explore optimal strategy in such patients.
| S-EPMC4741366 | biostudies-other
Project description:Expression of the TUSC2 tumor-suppressor gene in TUSC2-deficient NSCLC cells decreased PD-L1 expression and inhibited mTOR activity. Overexpressing TUSC2 or treatment with rapamycin resulted in similar inhibition of PD-L1 expression. Both TUSC2 and rapamycin decreased p70 and SK6 phosphorylation, suggesting that TUSC2 and rapamycin share the same mTOR target. Microarray mRNA expression analysis using TUSC2-inducible H1299 showed that genes that negatively regulate the mTOR pathway were significantly upregulated by TUSC2 compared with control. The presence of IFN-γ significantly increased PD-L1 expression in lung cancer cell lines, but overexpressing TUSC2 in these cell lines prevented PD-L1 from increasing in the presence of IFN-γ. Taken together, these findings show that TUSC2 can decrease PD-L1 expression in lung cancer cells. This ability to modify the tumor microenvironment suggests that TUSC2 could be added to checkpoint inhibitors to improve the treatment of lung cancer.
| S-EPMC5746095 | biostudies-literature