The impact of PD-L1 expression on lymphocyte subsets and prognosis in advanced non-small cell lung cancer with EGFR mutations

The impact of PD-L1 expression on lymphocyte subsets and prognosis in advanced non-small cell lung cancer with EGFR mutations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The impact of PD-L1 expression on lymphocyte subsets and prognosis in advanced non-small cell lung cancer with EGFR mutations WANG Shanshan, WANG Weiwei, PAN Lei This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7997536/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background To investigate the impact of different programmed cell death-ligand 1 (PD-L1) expression levels on lymphocyte subsets and prognosis in advanced non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations. Methods We collected the clinical data of 276 EGFR-mutant NSCLC patients who were admitted to Affiliated Beijing Shijitan Hospital, Capital Medical University from 1 January 2022 to 1 January 2024 and treated with osimertinib (a third-generation EGFR-tyrosine kinase inhibitor). The patients were divided into three groups based on PD-L1 expression status: high PD-L1 expression group, low PD-L1 expression group, and PD-L1 negative group. Flow cytometry was used to detect peripheral blood lymphocyte subsets in the three groups of patients. The differences in clinical characteristics and lymphocyte subsets among the three groups were analyzed using Pearson's chi-squared test, Fisher's exact test and one-way analysis of variance (ANOVA). Univariate and multivariate Cox regression analyses were used to identify possible factors associated with the prognosis of EGFR-mutant advanced NSCLC. The predictive performance of NK cells was measured using the area under the receiver operating characteristic (ROC) curve. The median progression-free survival (mPFS) was estimated using the Kaplan-Meier method. Results Statistically significant differences were observed in the percentages of CD3 + lymphocytes, CD4 + lymphocytes, CD8 + lymphocytes, the CD4+/CD8 + ratio, and the percentage and absolute count of natural killer (NK) cells across the three PD-L1 expression groups ( P < 0.001). Patients with EGFR exon 19-DEL mutation had a significantly longer mPFS than those with EGFR exon 21-L858R mutation ( P < 0.001). The mPFS in the high PD-L1 expression group was inferior to that in the low or negative PD-L1 expression groups. In addition, the low-NK-cell group had a poorer mPFS than the high-NK-cell group. Furthermore, univariate and multivariate Cox regression analyses showed that EGFR mutation type, high PD-L1 expression, and low NK cell levels were independent adverse prognostic factors for mPFS in patients receiving osimertinib. Conclusions In advanced NSCLC patients with EGFR exon 21-L858R mutation, high PD-L1 expression and low NK cell levels are independent adverse prognostic factors. For these patients, in addition to TKI-targeted therapy, NK cell-based immunotherapy could be an adjuvant treatment. EGFR PD-L1 lymphocyte subsets NK cells Prognosis Figures Figure 1 Figure 2 Introduction Lung cancer is one of the most common malignant tumors. It is the leading cause of tumor-related deaths with a poor prognosis worldwide [ 1 ]. Approximately 85% of the lung cancers are diagnosed as non-small cell lung cancer (NSCLC). A large proportion of patients are diagnosed at advanced-stage. The 5-year survival rate of patients with lung cancer is only 10%-20% [ 2 ]. The standard therapy is systemic drug therapy, which includes cytotoxic agents, targeted therapy, and immune checkpoint inhibitors for advanced NSCLC. Notably, targeted therapy exhibits superior efficacy for treating NSCLC with driver mutations. As a driver oncogene in NSCLC, epidermal growth factor receptor (EGFR) acquires mutations that promote tumorigenesis and neoplastic growth through the aberrant activation of its signaling pathway [ 3 ]. Previous phase III studies have shown that, for EGFR-mutant NSCLC, epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) administered as first-line treatment had superior outcomes than a platinum-based regimen, with advantages observed in both progression-free survival (PFS) and objective response rate (ORR) [ 2 , 4 , 5 ]. EGFR-TKIs therefore represent the current standard first-line therapeutic agents for treating patients with EGFR-mutated advanced NSCLC. However, this type of drug has demonstrated variable efficacy among different patient groups. Clinical data indicate that approximately 20% of patients experience disease progression within 3–6 months post initiation of receiving EGFR-TKI treatment [ 6 , 7 ]. The clinicopathological characteristics of patients may be an important factor leading to the differences in EGFR-TKI efficacy. The over-expression of programmed cell death-ligand 1 (PD-L1) is an important cause of primary drug resistance in tumor cells. The role of PD-L1 in tumors is to bind to programmed cell death receptor 1 on the surface of T cells, inhibit the activation of T lymphocytes and the secretion of inflammatory factors, and mediate tumor immune escape [ 8 , 9 ]. The occurrence, development, treatment and prognosis of NSCLC are closely associated with the patient's immune status. As a vital component of the body's immune system, T lymphocyte subsets exert a significant impact on the progression of NSCLC. Circulating lymphocytes and tumor immunotherapy have been thoroughly studied to determine their prognostic value [ 10 ]. It has been confirmed that baseline circulating specific lymphocyte subsets have important prognostic value for PFS in patients receiving EGFR-TKI treatment [ 11 ]. As a type of lymphocyte in the immune system, NK cells are critical for the body’s defense mechanisms against tumor cells [ 12 ]. It has been reported that the cytotoxicity of peripheral natural killer (NK) cells and the production of interferon-gamma (IFN-γ) are decreased in lung cancer patients [ 13 – 15 ] Infiltration of tumors by NK cells was reported to be linked with a favorable prognosis in lung cancer [ 16 , 17 ]. It was reported that this approach could result in an anti-tumour effect in 75% of patients with lung cancer when NK cells are infused into ththe impact of different programmed cell death-ligand 1 (PD-L1) expression levels on lymphocyte subsets and prognosis in patients with EGFR-mutant advanced NSCLC. In this study, we compared the clinical characteristics and lymphocyte subsets among groups with different levels of PD-L1 expression. This study aimed to examine the prognosis factors in advanced NSCLC with EGFR mutations. Patients and Methods Data collection The present study is a single-center, retrospective, observational study. We collected the clinical data of 276 NSCLC patients who were admitted to Beijing Shijitan Hospital, Capital Medical University from 1 January 2022 to 1 January 2024 and treated with osimertinib (a third-generation EGFR-tyrosine kinase inhibitor). The demographic data are summarized and analyzed in Table 1 . The inclusion criteria were as follows: (1) aged over 18 years; (2) diagnosed with lung adenocarcinoma by histopathology; (3) tumor stage determined as stage Ⅳ according to the TNM Classification of Malignant Tumors (8th edition) by the International Association for the Study of Lung Cancer (IASLC); (4) All patients underwent driver gene detection before treatment and were confirmed to have EGFR classic mutations (19-DEL and 21-L858R), and received PD-L1 expression level testing. (5) Eastern Cooperative Oncology Group (ECOG) performance status score ≤ 2 at the initiation of treatment; (6) All patients received osimertinib. The exclusion criteria were as follows: (1) complicated with other types of tumors; (2) complicated with acute inflammatory response; (3) complicated with other systemic hematological or immunological diseases; (4) long-term use of hormone therapy; (5) complicated with infection with hepatitis B virus (HBV) or hepatitis C virus (HCV). The patients were divided into three groups based on PD-L1 expression status: high PD-L1 expression group (Tumor Proportion Score [TPS] ≥ 50%, n = 150 ), low PD-L1 expression group (1% ≤ TPS < 50%, n = 90), and PD-L1 negative group (TPS ≤ 1%, n = 36). This study comprehensively documented the baseline demographic characteristics and clinical features of patients, encompassing key parameters such as sex, age, smoking history, tumor stage, Eastern Cooperative Oncology Group (ECOG) performance status, and classic mutation types of the EGFR gene. Table 1 Patient characteristics Variable n/% Gender Male 120/43.48 Femal 156/56.52 Age ≤ 60 years 121/43.84 >60 years 155/56.16 Smoking history Never 196/71.01 Yes 80/28.99 EGFR mutation type 19-DEL 171/61.96 21-L858R 105/38.04 ECOG 0–1 score 167/60.51 2 score 109/39.49 PD-L1 TPS<1% 150/54.35 1%≤TPS<50% 90/32.61 TPS ≥ 50% 36/13.04 Flow cytometry Fresh venous blood specimens from patients were collected using EDTA-coated vacutainer tubes before all patients initiated osimertinib treatment. For this experiment, a Beckman Coulter Navios (USA) ten-color flow cytometer was utilized, and its optical path and voltage settings were calibrated prior to the experiment. Cell viability was assessed using the violet amine reactive dye (Invitrogen, USA). In this study, a panel of antibodies directed against the antigen combinations CD3-FITC/CD8-PE/CD45-PerCP/CD4-APC and CD3-FITC/CD16 + 56-PE/CD45-PerCP/CD19-APC (BD Biosciences) was used. The fresh venous blood sample (100 µL) was combined with each antibody. The mixture was then vortexed at high speed for 6–8 seconds and incubated at room temperature for 15 minutes. After incubation, each tube was mixed with 2 mL of erythrolysin (Beckman Coulter, USA) and incubated for 15 minutes at room temperature. Washing procedures were performed at each step with PBS: centrifugation at 210 g for 5 minutes, aspiration of the supernatant, resuspension of the sample in 500 µL of PBS (with 0.1% formaldehyde), and acquisition on the flow cytometer. The analysis included 5,000 gated events, and all data were analyzed using Kaluza software (Beckman, USA). Efficacy Assessment and Follow Up Prior to treatment initiation and throughout the treatment phase, patients need to undergo regular imaging examinations, including brain magnetic resonance imaging (MRI), chest and abdominal computed tomography (CT), color Doppler ultrasound of superficial lymph nodes, and bone scans. Efficacy assessment is conducted in accordance with the RECIST 1.1 criteria. Progression-free survival (PFS) is defined as the time interval from the start of the patient’s EGFR-TKI treatment to the occurrence of progressive disease (PD) or death due to any cause. In the event that no disease progression is identified in the patient by the end of the follow-up period, this case should be categorized as a censored case. Ethics Approval: All patient information was confidentially protected, and this study was approved by the Ethics Committee of Beijing Shijitan Hospital, Capital Medical University. Informed consent was waived because this study is observational and retrospective. Statistical analysis Quantitative data were expressed as mean ± standard deviation, and differences among the three groups were compared with one-way analysis of variance (ANOVA). Categorical variables were summarized as counts and percentages, and the Chi-square test or Fisher’s exact test was used for comparison among groups. Univariate and multivariate Cox regression analyses were used to identify possible factors associated with the prognosis of NSCLC patients. The predictive performance of CD3 + T cell was evaluated using the area under receiver operating characteristic (ROC) curve (AUC) [ 18 ]. The mPFS was estimated using the Kaplan-Meier method, and log rank test was used to assess the significance of differences between groups. All statistical data were analyzed using SPSS software version 26.0 (SPSS Inc., Chicago, IL, USA) and GraphPad Prism software version 10 (GraphPad, La Jolla, CA, USA). A (two-sided) p value < 0.05 was considered statistically significant. Results Patient demographics and clinical characteristics The baseline characteristics of patients are detailed in Table 1 . A total of 276 participants were enrolled in this study, including 36 cases in the PD-L1 negative group, 90 cases in the low expression group, and 150 cases in the high expression group. There were no statistically significant differences in gender, age, EGFR mutation type, and ECOG score among the PD-L1 negative group, low expression group, and high expression group ( P > 0.05). However, a statistically significant difference was observed in smoking history among these groups ( P < 0.05), as shown in Table 2 . Table 2 Clinicopathological Characteristics (n = 276) Variable Tatal The expression of PD-L1(n/%) χ 2 P Value TPS<1% (n = 150) 1%≤TPS60 years 155 74/47.7 57/36.8 24/15.5 Smoking history Never 196 121/61.4 54/27.4 21/10.7 14.906 <0.001 Yes 80 29/36.7 36/45.6 15/18.7 EGFR mutation type 19-DEL 171 100/58.5 50/29.2 21/12.3 1.218 0.544 21-L858R 105 50/47.6 40/38.1 15/14.3 ECOG 0–1 score 167 94/56.3 52/31.1 21/12.6 0.241 0.887 2 score 109 56/51.4 38/34.9 15/13.7 The relationship between the different PD-L1 expression groups and lymphocyte subsets in patients with EGFR-mutant advanced lung adenocarcinoma There were no significant differences in CD3 + lymphocyte count, CD4 + lymphocyte percentage, CD8 + lymphocyte count, B lymphocyte count, and B lymphocyte percentage among PD-L1-negative, low-expression, and high-expression groups ( P > 0.05). However, statistically significant differences were observed in CD3 + lymphocyte percentage, CD4 + lymphocyte count, CD8 + lymphocyte percentage, CD4+/CD8 + ratio, NK cell percentage, and NK cell count among them ( P < 0.001) (Table 3 ). Table 3 Peripheral lymphocyte subsets in different PD-L1 expression groups Variable The expression of PD-L1(n/%) F P P1 P2 P3 TPS<1% (n = 150) 1%≤TPS<50% (n = 90) TPS ≥ 50% (n = 36) CD3+(%) 67.69 ± 8.82 73.67 ± 7.42 79.10 ± 6.71 35.067 <0.001 <0.001 <0.001 <0.001 CD3+(/µL) 657.43 ± 246.95 627.44 ± 246.27 581.33 ± 201.68 1.564 0.211 - - - CD4+(%) 39.19 ± 9.07 39.46 ± 9.05 35.99 ± 10.46 2.016 0.135 - - - CD4+(/µL) 376.69 ± 160.47 330.03 ± 140.18 273.22 ± 156.66 7.493 <0.001 0.024 <0.001 0.062 CD8+(%) 25.46 ± 9.21 30.97 ± 10.36 39.30 ± 14.56 27.892 <0.001 <0.001 <0.001 <0.001 CD8+(/µL) 253.27 ± 126.32 268.09 ± 151.62 289.61 ± 126.09 1.152 0.318 - - - CD4+/CD8+ 1.83 ± 1.04 1.52 ± 0.86 1.19 ± 1.09 7.051 0.001 0.02 <0.001 0.097 B(%) 8.60 ± 6.16 9.99 ± 6.19 8.61 ± 6.02 1.531 0.218 - - - B(/µL) 90.68 ± 79.71 86.67 ± 67.07 70.50 ± 65.42 1.078 0.342 - - - NK(%) 22.93 ± 8.50 16.15 ± 6.08 11.47 ± 3.85 47.539 <0.001 <0.001 0.001 <0.001 NK(/µL) 210.00 ± 89.584 129.20 ± 56.87 78.53 ± 33.74 61.623 <0.001 <0.001 <0.001 <0.001 P , overall inter-group comparison; P 1, comparison between the TPS < 1% group and the 1% ≤ TPS < 50% group; P 2, comparison between the TPS < 1% group and the TPS ≥ 50% group; P 3, comparison between the 1% ≤ TPS < 50% group and the TPS ≥ 50% group. Univariate analysis of factors influencing therapeutic efficacy in patients with EGFR-mutant advanced lung adenocarcinoma To explore the potential independent risk factors of disease progression, univariate Cox regression analysis was performed. Smoking (HR = 2.085, 95% CI: 1.537–2.829, P < 0.001), EGFR mutation subtype (HR = 2.584, 95% CI: 1.951–3.424, P < 0.001), PD-L1 expression level (HR = 2.359, 95% CI: 1.791–3.107, P < 0.001), CD3+ (%) (HR = 1.067, 95% CI: 1.048–1.086, P < 0.001), CD3 + lymphocyte count (HR = 0.999, 95% CI: 0.998–0.999, P < 0.001), CD4+ (%) (HR = 1.026, 95% CI: 1.010–1.042, P = 0.001), CD4 + lymphocyte count (HR = 0.998, 95% CI: 0.997–0.999, P < 0.001), CD8+ (%) (HR = 1.020, 95% CI: 1.007–1.033, P = 0.003), CD8 + lymphocyte count (HR = 0.998, 95% CI: 0.997–0.999, P = 0.002), B cell count (HR = 0.998, 95% CI: 0.996–1.000, P = 0.020), NK (%) (HR = 0.944, 95% CI: 0.926–0.964, P < 0.001), and NK cell count (HR = 0.981, 95% CI: 0.978–0.983, P < 0.001) were identified as potential risk factors for disease progression of lung cancer (Table 4 ). In contrast, gender, age, ECOG score, B cell percentage, and CD4+/CD8 + ratio were not associated with the risk of disease progression ( P > 0.05) (Table 4 ). Table 4 Univariate Cox regression analysis of factors related to mPFS Variable HR 95% CI P value lower limit upper limit Gender 0.795 0.604 1.046 0.101 Age 1.226 0.932 1.613 0.145 Smoking history 2.085 1.537 2.829 <0.001 EGFR mutation subtype 2.584 1.951 3.424 <0.001 ECOG 1.187 0.902 1.562 0.221 PD-L1 2.359 1.791 3.107 <0.001 CD3+(%) 1.067 1.048 1.086 <0.001 CD3+(/µL) 0.999 0.998 0.999 <0.001 CD4+(%) 1.026 1.010 1.042 0.001 CD4+(/µL) 0.998 0.997 0.999 <0.001 CD8+(%) 1.020 1.007 1.033 0.003 CD8+(/µL) 0.998 0.997 0.999 0.002 CD4+/CD8+ 1.005 0.887 1.138 0.939 B(/%) 1.013 0.991 1.036 0.245 B(/µL) 0.998 0.996 1.000 0.020 NK(%) 0.944 0.926 0.964 <0.001 NK(/µL) 0.981 0.978 0.983 <0.001 Multivariate cox regression analysis of factors related to PFS Multivariate Cox regression analysis showed that EGFR mutation subtype (HR = 1.467, 95% CI: 1.076-2.000, P = 0.015), PD-L1 expression level (HR = 2.193, 95% CI: 1.483–3.242, P < 001), and NK cell count (HR = 0.980, 95% CI: 0.974–0.985, P < 0.001) were independent prognostic factors for patients with EGFR-mutant lung adenocarcinoma. Table 4 Correlative factors based on the multivariate Cox regression analysis Variable HR 95% CI P value lower limit upper limit Smoking history 1.374 0.990 1.906 0.057 EGFR mutation subtype 1.467 1.076 2.000 0.015 PD-L1 2.193 1.483 3.242 <0.001 CD3+(%) 1.018 0.961 1.078 0.547 CD3+(/µL) 0.999 0.994 1.004 0.726 CD4+(%) 1.034 0.992 1.079 0.116 CD4+(/µL) 0.999 0.994 1.005 0.805 CD8+(%) 1.025 0.997 1.053 0.083 CD8+(/µL) 0.999 0.993 1.005 0.809 B(/µL) 1.003 0.998 1.008 0.191 NK(%) 1.002 0.994 1.011 0.594 NK(/µL) 0.980 0.974 0.985 <0.001 Survival analysis of patients with NSCLC In this study, we performed ROC analysis to confirm 197.5 cells/µL as the cut-off value of NK cell count according to the survival of patients with NSCLC (Fig. 1 ). According to the optimal threshold of NK cell count, patients were divided into high NK cell count group and low NK cell count group. Patients with NK cell count < 197.5 cells/µL were included in the low NK cell count group, and patients with NK cell count ≥ 197.5 cells/µL were included in the high NK cell count. Survival analysis was performed to identify the factors associated with the prognosis of patients with NSCLC. The Kaplan-Meier analysis demonstrated that patients with EGFR 19-DEL mutation had longer mPFS than those with EGFR 21-L858R mutation (15 months vs 7 months; P < 0.001, Table 5 , Fig. 2 A ). It was shown that mPFS in PD-L1-positive patients was significantly shorter than that in PD-L1-negative patients (8 months vs 16 months; P < 0.001, Table 5 , Fig. 2 B). In PD-L1-positive patients, those with low PD-L1 expression (1% ≤ TPS <50%) had longer mPFS than those with high PD-L1 expression (TPS ≥ 50%) (11 months vs 5 months; P < 0.001, Table 5 , Fig. 2 B ). Similarly, it was demonstrated that both PD-L1-high and PD-L1-low subgroups exhibited shorter mPFS compared to PD-L1-negative subgroup ( P < 0.001, Table 5 , Fig. 2 B ). Patients with NK cell count ≥ 197.5 cells/µL had significantly longer mPFS compared with patients with NK cell count < 197.5 cells/µL (23 months vs 9 months; P < 0.001, Table 5 , Fig. 2 C). Table 5 Progression-free survival analysis Variable mPFS(m) χ 2 value P value EGFR mutation subtype 19-DEL 15 50.391 <0.001 21-L858R 7 PD-L1 TPS<1% 16 67.678 <0.001 1%≤TPS<50% 11 TPS ≥ 50% 5 NK cell count High 23 153.154 <0.001 Low 9 Discussion The focus of this study was to investigate the impact of different PD-L1 expression levels on lymphocyte subsets and prognosis in patients with EGFR-mutant advanced NSCLC. The results showed that the mPFS in the high PD-L1 group was inferior to that in the low or negative PD-L1 groups. The subgroup of patients with 19-DEL had significantly longer mPFS compared with the subgroup of patients with 21-L858R. In addition, the mPFS was poorer in the low-NK-cell group than that in the high-NK-cell group. Furthermore, univariate and multivariate Cox regression analyses showed that EGFR mutation type, high PD-L1 expression, and low NK cell levels were independent adverse prognostic factors for mPFS in patients receiving osimertinib. In current treatments for advanced NSCLC, targeted therapy has emerged as an irreplaceable approach due to its remarkable efficacy and favorable patient tolerability. The EGFR 19-DEL and 21-L858R mutations are two typical variants of the EGFR gene that exhibit high sensitivity to EGFR-TKIs, and they serve as reliable predictors for evaluating treatment outcomes [ 19 ]. Multiple studies have demonstrated that patients with EGFR 19-DEL mutations generally show better responses to EGFR-TKIs than those with EGFR 21-L858R mutations [ 20 ]. The LUX-Lung series of trials revealed that patients with EGFR 19-DEL demonstrate notably better therapeutic responses and survival outcomes compared with those with EGFR 21-L858R point mutations, primarily manifested through prolonged progression-free survival (PFS) and overall survival (OS) [ 21 ]. In our study, among EGFR-mutant patients with advanced lung adenocarcinoma who receiving osimertinib treatment, it was confirmed that the 19-DEL patients subgroup achieved significantly longer mPFS than the 21-L858R patients subgroup. It was observed that the mPFS in patients receiving osimertinib reached 18.9 months when osimertinib was used as the first-line treatment for NSCLC in the FLAURA study [ 6 ]. However, not all lung adenocarcinoma patients with EGFR-sensitive mutations can benefit from from first-line EGFR-TKI therapys. A large body of research evidence indicates that patients with EGFR mutations accompanied by high PD-L1 expression have poor therapeutic responses to EGFR-TKI, which may be because PD-L1 overexpression is an important cause of primary resistance in tumor cells. As a key immune checkpoint protein, PD-L1 is present on both tumors and tumor-infiltrating immune cells. PD-L1 expression is typically classified as negative (TPS < 1%), low ( 1–49% ), and high (≥ 50% ). It has been observed that PD-L1 expression is affected by the presence of EGFR mutations and the use of EGFR-TKI therapy [ 22 – 24 ]. Among EGFR-mutant patients, 44% had a PD-L1 TPS ≥ 1%, while 13% had a PD-L1 TPS ≥ 50% [ 22 ]. Another study in China showed that among non-small cell lung cancer (NSCLC) patients harboring EGFR mutations, 29.5% exhibited PD-L1 TPS in the range of 1–49%, while 14.3% demonstrated PD-L1 TPS ≥ 50% [ 25 ]. The present study showed that 54.35% of NSCLC patients with EGFR mutations had a PD-L1 TPS < 1%, 32.61% had a PD-L1 TPS between 1–49%, and 13.04% had a PD-L1 TPS ≥ 50%. These findings suggest that PD-L1 expression patterns are similar to those in previous studies. PD-L1 serves as a crucial biomarker in immunotherapy, yet its significance in patients receiving EGFR-TKIs is still ambiguous [ 26 ]. A retrospective study showed that patients with high PD-L1 expression who received 1st-generation EGFR-TKIs had a significantly shorter mPFS (6.6 months) than those in the low or negative PD-L1 expression group (13.0 months) [ 27 ]. Another study demenstated that the estimated mPFS of osimertinib in the high PD-L1 group was 10.1 months, which was significantly shorter than that in the low or negative PD-L1 group [ 28 ]. In addition, the study showed that high PD-L1 expression was an independent unfavorable factor associated with mPFS in patients receiving osimertinib therapy. A recent study showed that in patients receiving first-line osimertinib, those with high PD-L1 expression (TPS ≥ 50%) had poorer PFS (5.0 months) than those with low (TPS 1%-49%) or negative (TPS < 1%) PD-L1 expression (17.4 months) [ 29 ]. Numerous studies have shown a correlation between high PD-L1 expression and poor efficacy of EGFR-TKIs [ 22 , 30 – 32 ]. However, some studies present opposite outcomes. For example, it was reported that high PD-L1 expression correlates with prolonged PFS and OS in advanced lung adenocarcinoma patients harboring EGFR mutations after EGFR-TKI therapy [ 25 ]. Similarly, there was a non-significant effect of PD-L1 expression status (positive: ≥ 1% vs. negative) on progression-free survival in the FLAURA study [ 33 ]. In the present study, the mPFS in the PD-L1 high-expression group was 5 months, which was significantly lower than that in the PD-L1 low-expression group (11 months) and PD-L1 negative group (16 months). The present study demonstrated results similar to most previous studies. Thus, PD-L1 expression levels can serve as a biomarker for predicting and evaluating the efficacy of EGFR-TKIs in NSCLC patients with EGFR mutations. High PD-L1 expression is associated with a poor prognosis in patients receiving EGFR-TKI treatment. The development and progression of tumors occur within a microenvironment populated by a variety of immune cells and immune products [ 34 ]. Natural killer (NK) cells are generally considered to constitute the first line of anti-tumor defense, and provide tumor immunosurveillance, tumor lysis, and tumor metastasis elimination [ 35 ]. NK cells are responsible for mediating the release of cytokines and chemokines to counteract cancer cells [ 36 ]. The ability of NK cells to recognize cancer cells is independent of neoantigens or self-antigen overexpression, and tumor cells that lose MHC expression are more susceptible to being killed by NK cells [ 37 ]. A previous study demenstrated that when pembrolizumab was used together with NK cell therapy for advanced NSCLC patients with PD-L1 positive expression, it brought about improved survival benefits [ 38 ]. NK cells also participate in the targeting of tumor antigens by monoclonal antibodies (mAbs), which can destroy tumour cells through NK cell-mediated antibody-dependent cellular cytotoxicity (ADCC)[ 39 , 40 ]. The existence of anti-EGFR auto-antibodies (IgG isotype) in the serum and tumour tissue of lung cancer patients has been documented during the earliest stages of cancer development[ 41 , 42 ]. This observation offers supportive evidence for using the NK cell-mediated ADCC effect against lung cancer adenocarcinomas with EGFR mutation-positive. Although oncogenic driver mutations that activate EGFR in NSCLC predict sensitivity to specific EGFR-TIKs, increasing drug resistance has emerged after the first- or second-line therapy with the EGFR-TKIs gefitinib and erlotinib [ 43 ]. NK cell immunotherapy is able to significantly enhance the prognosis of lung cancers, particularly those with EGFR mutations. A clinical study showed that NK cells combined with afatinib, a second-generation targeted drug, significantly improved the therapeutic effect. The remission rate increased from 16.7% to 75%, and the mPFS prolonged from 6 months to 9 months[ 44 ]. It has been documented that the combination of NK cell therapy and TKI medications enhances the cytotoxic effect on lung cancer cells with EGFR-resistant mutations[ 45 ]. High NK cell density was independent predictor of longer PFS while high NK proved significant predictors of longer OS[ 46 ]. In this study, the mPFS in low NK cells group was 9 months, which was significantly lower than that in high NK cell group (23 months). Meanwhile, NK cells is decreased in high PD-L1 expression than in low or negative PD-L1 group, accompanied by poor mPFS. Conclusion In the present study, the mPFS of patients in the high PD-L1 expression group, which also has lower NK cell levels, is significantly shorter. The EGFR mutation with 21-L858R was associated with significantly shorter mPFS compared to the subgroup with EGFR mutation 19-DEL. For advanced NSCLC patients with low NK cell levels, EGFR mutatation 21- L858R, and high PD-L1 expression, physicians should be aware of the risk of resistance to osimertinib. For these patients, in addition to TKI-targeted therapy, NK cell-based immunotherapy could be an adjuvant treatment. Abbreviations EGFR: Epidermal growth factor receptor; EGFR-TKIs:Epidermal growth factor receptor-tyrosine kinase inhibitors; NSCLC: Non-small cell lung cancer; PD-L1: Programmed death ligand-1; ROC: receiver operating characteristic; mPFS: median progression-free survival; NK: natural killer; ORR: Objective response rate; ECOG, Eastern Cooperative Oncology Group; TPS: Tumor Proportion Score; Declarations Ethics approval and consent to participate This study was approved by the Medical Ethics Committee of Beijing Shijitan Hospital, and informed consent was obtained from all patients prior to their participation in this study. All methods were performed in accordance with relevant guidelines and regulations. Consent for publication Not applicable. Availability of data and materials The datasets used in this study are available from the corresponding author upon reasonable request. Competing interests The authors have declared that no competing interest exists. Funding This study was funded by Beijing Shijtan Hospital’s “14th Five-Year Plan” Leading Talent Training Project (2023LJRCPL). Authors' contributions L.P and S.W contributed to the conception and design of the study. SW and WW contributed to data collection and analysis. SW contributed to manuscript preparation. All authors read and approved the final manuscript. References Siegel RL, Kratzer TB, Giaquinto AN, Sung H, Jemal A. Cancer statistics. 2025. CA Cancer J Clin. 2025;75(1):10-45. Allemani C, Matsuda T, Di Carlo V, Harewood R, Matz M, Niksic M, Bonaventure A, Valkov M, Johnson CJ, Esteve J et al. Global surveillance of trends in cancer survival 2000-14 (CONCORD-3): analysis of individual records for 37513025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries. Lancet. 2018;391(10125):1023-75. Jorissen RN, Walker F, Pouliot N, Garrett TP, Ward CW, Burgess AW. Epidermal growth factor receptor: mechanisms of activation and signalling. 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J Thorac Oncol. 2022;17(9):1098-08. Yoon BW, Chang B, Lee SH: High PD-L1 Expression is Associated with Unfavorable Clinical Outcome in EGFR-Mutated Lung Adenocarcinomas Treated with Targeted Therapy. Onco Targets Ther. 2020;13:8273-85. Isomoto K, Haratani K, Hayashi H, Shimizu S, Tomida S, Niwa T, Yokoyama T, Fukuda Y, Chiba Y, Kato R et al. Impact of EGFR-TKI Treatment on the Tumor Immune Microenvironment in EGFR Mutation-Positive Non-Small Cell Lung Cancer. Clin Cancer Res. 2020;26(8):2037-46. Dietel M, Savelov N, Salanova R, Micke P, Bigras G, Hida T, Antunez J, Guldhammer Skov B, Hutarew G, Sua LF et al. Real-world prevalence of programmed death ligand 1 expression in locally advanced or metastatic non-small-cell lung cancer: The global, multicenter EXPRESS study. Lung Cancer. 2019;134:174-79. Lin C, Chen X, Li M, Liu J, Qi X, Yang W, Zhang H, Cai Z, Dai Y, Ouyang X. Programmed Death-Ligand 1 Expression Predicts Tyrosine Kinase Inhibitor Response and Better Prognosis in a Cohort of Patients With Epidermal Growth Factor Receptor Mutation-Positive Lung Adenocarcinoma. Clin Lung Cancer. 2015;16(5):e25-35. Gao W, Wang L, Zhao Y, Zhu L. The role of PD-L1 in EGFR-mutant non-small cell lung cancer. Discov Oncol. 2025;16(1):307. Liu J, Itchins M, Nagrial A, Cooper WA, De Silva M, Barnet M, Varikatt W, Sivasubramaniam V, Davis A, Gill AJ et al. Relationship between PD-L1 expression and outcome in EGFR-mutant lung cancer patients treated with EGFR tyrosine kinase inhibitors. Lung Cancer. 2021;155:28-33. Shiozawa T, Numata T, Tamura T, Endo T, Kaburagi T, Yamamoto Y, Yamada H, Kikuchi N, Saito K, Inagaki M et al. Prognostic Implication of PD-L1 Expression on Osimertinib Treatment for EGFR-mutated Non-small Cell Lung Cancer. Anticancer Res. 2022; 42(5):2583-90. Yoshimura A, Yamada T, Okuma Y, Fukuda A, Watanabe S, Nishioka N, Takeda T, Chihara Y, Takemoto S, Harada T et al. Impact of tumor programmed death ligand-1 expression on osimertinib efficacy in untreated EGFR-mutated advanced non-small cell lung cancer: a prospective observational study. Transl Lung Cancer Res. 2021;10(8):3582-3593. Inomata M, Azechi K, Takata N, Hayashi K, Tokui K, Taka C, Okazawa S, Kambara K, Imanishi S, Miwa T et al.Association of Tumor PD-L1 Expression with the T790M Mutation and Progression-Free Survival in Patients with EGFR-Mutant Non-Small Cell Lung Cancer Receiving EGFR-TKI Therapy. Diagnostics (Basel) .2020;10(12). Hsu KH, Tseng JS, Yang TY, Chen KC, Su KY, Yu SL, Chen JJW, Huang YH, Chang GC: PD-L1 strong expressions affect the clinical outcomes of osimertinib in treatment naive advanced EGFR-mutant non-small cell lung cancer patients. Sci Rep. 2022;12(1):9753. Yang CY, Liao WY, Ho CC, Chen KY, Tsai TH, Hsu CL, Su KY, Chang YL, Wu CT, Hsu CC et al. PD-L1 expression and immune profiling cannot predict osimertinib efficacy in lung cancer with EGFR T790 M mutation: A translational study. J Formos Med Assoc. 2024;Dec 17:S0929-6646(24)00579-5.doi: 10.1016/j.jfma.2024.12.020. Brown H, Vansteenkiste J, Nakagawa K, Cobo M, John T, Barker C, Kohlmann A, Todd A, Saggese M, Chmielecki J et al. Programmed Cell Death Ligand 1 Expression in Untreated EGFR Mutated Advanced NSCLC and Response to Osimertinib Versus Comparator in FLAURA. J Thorac Oncol. 2020;15(1):138-43. Sasada T, Suekane S. Variation of tumor-infiltrating lymphocytes in human cancers: controversy on clinical significance. Immunotherapy. 2011;3(10):1235-51. Lopez-Soto A, Gonzalez S, Smyth MJ, Galluzzi L. Control of Metastasis by NK Cells. Cancer Cell. 2017;32(2):135-54. Vivier E, Raulet DH, Moretta A, Caligiuri MA, Zitvogel L, Lanier LL, Yokoyama WM, Ugolini S. Innate or adaptive immunity? The example of natural killer cells. Science. 2011; 331(6013):44-49. Lin M, Liang SZ, Wang XH, Liang YQ, Zhang MJ, Niu LZ, Chen JB, Li HB, Xu KC. Clinical efficacy of percutaneous cryoablation combined with allogenic NK cell immunotherapy for advanced non-small cell lung cancer. Immunol Res. 2017; 65(4):880-87. Lin M, Luo H, Liang S, Chen J, Liu A, Niu L, Jiang Y. Pembrolizumab plus allogeneic NK cells in advanced non-small cell lung cancer patients. J Clin Invest. 2020;130(5):2560-69. Wang W, Erbe AK, Hank JA, Morris ZS, Sondel PM. NK Cell-Mediated Antibody-Dependent Cellular Cytotoxicity in Cancer Immunotherapy. Front Immunol. 2015;6:368. Huang AL, Liu SG, Qi WJ, Zhao YF, Li YM, Lei B, Sheng WJ, Shen H. TGF-beta1 protein expression in non-small cell lung cancers is correlated with prognosis. Asian Pac J Cancer Prev. 2014;15(19):8143-47. Bei R, Masuelli L, Moriconi E, Visco V, Moretti A, Kraus MH, Muraro R. Immune responses to all ErbB family receptors detectable in serum of cancer patients. Oncogene. 1999; 18(6):1267-75. Glushkov AN, Anosova TP, Anosov MP, Nebesnaia NG, Zheleznova LI, Kurilov KS. New approaches in evaluating the antitumor immune response in breast cancer. Vopr Onkol. 1996; 42(6):33-36. Faehling M, Schwenk B, Kramberg S, Eckert R, Volckmar AL, Stenzinger A, Strater J. Oncogenic driver mutations, treatment, and EGFR-TKI resistance in a Caucasian population with non-small cell lung cancer: survival in clinical practice. Oncotarget. 2017; 8(44):77897-14. Hong G, Chen X, Sun X, Zhou M, Liu B, Li Z, Yu Z, Gao W, Liu T. Effect of autologous NK cell immunotherapy on advanced lung adenocarcinoma with EGFR mutations. Precis Clin Med. 2019;2(4):235-245. He S, Yin T, Li D, Gao X, Wan Y, Ma X, Ye T, Guo F, Sun J, Lin Z et al. Enhanced interaction between natural killer cells and lung cancer cells: involvement in gefitinib-mediated immunoregulation. J Transl Med. 2013;11:186. Szentkereszty M, Ladanyi A, Galffy G, Tovari J, Losonczy G. Density of tumor-infiltrating NK and Treg cells is associated with 5 years progression-free and overall survival in resected lung adenocarcinoma. Lung Cancer. 2024;192:107824. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 20 Dec, 2025 Reviews received at journal 16 Dec, 2025 Reviewers agreed at journal 15 Dec, 2025 Reviewers agreed at journal 08 Dec, 2025 Reviews received at journal 04 Dec, 2025 Reviewers agreed at journal 01 Dec, 2025 Reviewers invited by journal 28 Nov, 2025 Editor invited by journal 05 Nov, 2025 Editor assigned by journal 03 Nov, 2025 Submission checks completed at journal 03 Nov, 2025 First submitted to journal 31 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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1","display":"","copyAsset":false,"role":"figure","size":42744,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve for confirming 197.5 cells/μL as the cut-off value of NK cell count based on the survival outcomes of patients with NSCLC.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7997536/v1/ebf29373851672b42c6e9979.png"},{"id":97368000,"identity":"7b36f23a-bba4-4fa0-b34b-9bea0b49a79b","added_by":"auto","created_at":"2025-12-03 16:21:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":354260,"visible":true,"origin":"","legend":"\u003cp\u003eProgression-free survival according to (A) the EGFR mutation subtype, (B) PD-L1 expression, (C) NK cell count\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7997536/v1/5a73b896dd519434eab730ab.png"},{"id":97372859,"identity":"dac11c6c-d316-45fe-9395-0408811a1f66","added_by":"auto","created_at":"2025-12-03 16:33:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1626534,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7997536/v1/300a93c6-e3c2-4ba0-8908-652d27acd56b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The impact of PD-L1 expression on lymphocyte subsets and prognosis in advanced non-small cell lung cancer with EGFR mutations","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLung cancer is one of the most common malignant tumors. It is the leading cause of tumor-related deaths with a poor prognosis worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Approximately 85% of the lung cancers are diagnosed as non-small cell lung cancer (NSCLC). A large proportion of patients are diagnosed at advanced-stage. The 5-year survival rate of patients with lung cancer is only 10%-20% [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The standard therapy is systemic drug therapy, which includes cytotoxic agents, targeted therapy, and immune checkpoint inhibitors for advanced NSCLC. Notably, targeted therapy exhibits superior efficacy for treating NSCLC with driver mutations. As a driver oncogene in NSCLC, epidermal growth factor receptor (EGFR) acquires mutations that promote tumorigenesis and neoplastic growth through the aberrant activation of its signaling pathway [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Previous phase III studies have shown that, for EGFR-mutant NSCLC, epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) administered as first-line treatment had superior outcomes than a platinum-based regimen, with advantages observed in both progression-free survival (PFS) and objective response rate (ORR) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. EGFR-TKIs therefore represent the current standard first-line therapeutic agents for treating patients with EGFR-mutated advanced NSCLC. However, this type of drug has demonstrated variable efficacy among different patient groups. Clinical data indicate that approximately 20% of patients experience disease progression within 3\u0026ndash;6 months post initiation of receiving EGFR-TKI treatment [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The clinicopathological characteristics of patients may be an important factor leading to the differences in EGFR-TKI efficacy. The over-expression of programmed cell death-ligand 1 (PD-L1) is an important cause of primary drug resistance in tumor cells. The role of PD-L1 in tumors is to bind to programmed cell death receptor 1 on the surface of T cells, inhibit the activation of T lymphocytes and the secretion of inflammatory factors, and mediate tumor immune escape [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe occurrence, development, treatment and prognosis of NSCLC are closely associated with the patient's immune status. As a vital component of the body's immune system, T lymphocyte subsets exert a significant impact on the progression of NSCLC. Circulating lymphocytes and tumor immunotherapy have been thoroughly studied to determine their prognostic value [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. It has been confirmed that baseline circulating specific lymphocyte subsets have important prognostic value for PFS in patients receiving EGFR-TKI treatment [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. As a type of lymphocyte in the immune system, NK cells are critical for the body\u0026rsquo;s defense mechanisms against tumor cells [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. It has been reported that the cytotoxicity of peripheral natural killer (NK) cells and the production of interferon-gamma (IFN-γ) are decreased in lung cancer patients [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] Infiltration of tumors by NK cells was reported to be linked with a favorable prognosis in lung cancer [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. It was reported that this approach could result in an anti-tumour effect in 75% of patients with lung cancer when NK cells are infused into ththe impact of different programmed cell death-ligand 1 (PD-L1) expression levels on lymphocyte subsets and prognosis in patients with EGFR-mutant advanced NSCLC.\u003c/p\u003e\u003cp\u003eIn this study, we compared the clinical characteristics and lymphocyte subsets among groups with different levels of PD-L1 expression. This study aimed to examine the prognosis factors in advanced NSCLC with EGFR mutations.\u003c/p\u003e"},{"header":"Patients and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData collection\u003c/h2\u003e\u003cp\u003eThe present study is a single-center, retrospective, observational study. We collected the clinical data of 276 NSCLC patients who were admitted to Beijing Shijitan Hospital, Capital Medical University from 1 January 2022 to 1 January 2024 and treated with osimertinib (a third-generation EGFR-tyrosine kinase inhibitor). The demographic data are summarized and analyzed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eThe inclusion criteria were as follows: (1) aged over 18 years; (2) diagnosed with lung adenocarcinoma by histopathology; (3) tumor stage determined as stage Ⅳ according to the TNM Classification of Malignant Tumors (8th edition) by the International Association for the Study of Lung Cancer (IASLC); (4) All patients underwent driver gene detection before treatment and were confirmed to have EGFR classic mutations (19-DEL and 21-L858R), and received PD-L1 expression level testing. (5) Eastern Cooperative Oncology Group (ECOG) performance status score\u0026thinsp;\u0026le;\u0026thinsp;2 at the initiation of treatment; (6) All patients received osimertinib.\u003c/p\u003e\u003cp\u003eThe exclusion criteria were as follows: (1) complicated with other types of tumors; (2) complicated with acute inflammatory response; (3) complicated with other systemic hematological or immunological diseases; (4) long-term use of hormone therapy; (5) complicated with infection with hepatitis B virus (HBV) or hepatitis C virus (HCV).\u003c/p\u003e\u003cp\u003eThe patients were divided into three groups based on PD-L1 expression status: high PD-L1 expression group (Tumor Proportion Score [TPS]\u0026thinsp;\u0026ge;\u0026thinsp;50%, n\u0026thinsp;=\u0026thinsp;150 ), low PD-L1 expression group (1% \u0026le; TPS\u0026thinsp;\u0026lt;\u0026thinsp;50%, n\u0026thinsp;=\u0026thinsp;90), and PD-L1 negative group (TPS\u0026thinsp;\u0026le;\u0026thinsp;1%, n\u0026thinsp;=\u0026thinsp;36). This study comprehensively documented the baseline demographic characteristics and clinical features of patients, encompassing key parameters such as sex, age, smoking history, tumor stage, Eastern Cooperative Oncology Group (ECOG) performance status, and classic mutation types of the EGFR gene.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePatient characteristics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en/%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e120/43.48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e156/56.52\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;60 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e121/43.84\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;60 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e155/56.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSmoking history\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e196/71.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e80/28.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEGFR mutation type\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19-DEL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e171/61.96\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e21-L858R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e105/38.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eECOG\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u0026ndash;1 score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e167/60.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2 score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e109/39.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePD-L1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTPS\u0026lt;1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e150/54.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1%\u0026le;TPS\u0026lt;50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e90/32.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTPS\u0026thinsp;\u0026ge;\u0026thinsp;50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36/13.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eFlow cytometry\u003c/h3\u003e\n\u003cp\u003eFresh venous blood specimens from patients were collected using EDTA-coated vacutainer tubes before all patients initiated osimertinib treatment. For this experiment, a Beckman Coulter Navios (USA) ten-color flow cytometer was utilized, and its optical path and voltage settings were calibrated prior to the experiment. Cell viability was assessed using the violet amine reactive dye (Invitrogen, USA). In this study, a panel of antibodies directed against the antigen combinations CD3-FITC/CD8-PE/CD45-PerCP/CD4-APC and CD3-FITC/CD16\u0026thinsp;+\u0026thinsp;56-PE/CD45-PerCP/CD19-APC (BD Biosciences) was used. The fresh venous blood sample (100 \u0026micro;L) was combined with each antibody. The mixture was then vortexed at high speed for 6\u0026ndash;8 seconds and incubated at room temperature for 15 minutes. After incubation, each tube was mixed with 2 mL of erythrolysin (Beckman Coulter, USA) and incubated for 15 minutes at room temperature. Washing procedures were performed at each step with PBS: centrifugation at 210 g for 5 minutes, aspiration of the supernatant, resuspension of the sample in 500 \u0026micro;L of PBS (with 0.1% formaldehyde), and acquisition on the flow cytometer. The analysis included 5,000 gated events, and all data were analyzed using Kaluza software (Beckman, USA).\u003c/p\u003e\n\u003ch3\u003eEfficacy Assessment and Follow Up\u003c/h3\u003e\n\u003cp\u003ePrior to treatment initiation and throughout the treatment phase, patients need to undergo regular imaging examinations, including brain magnetic resonance imaging (MRI), chest and abdominal computed tomography (CT), color Doppler ultrasound of superficial lymph nodes, and bone scans. Efficacy assessment is conducted in accordance with the RECIST 1.1 criteria. Progression-free survival (PFS) is defined as the time interval from the start of the patient\u0026rsquo;s EGFR-TKI treatment to the occurrence of progressive disease (PD) or death due to any cause. In the event that no disease progression is identified in the patient by the end of the follow-up period, this case should be categorized as a censored case.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics Approval:\u003c/strong\u003e\u003cp\u003e All patient information was confidentially protected, and this study was approved by the Ethics Committee of Beijing Shijitan Hospital, Capital Medical University. Informed consent was waived because this study is observational and retrospective.\u003c/p\u003e\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eQuantitative data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, and differences among the three groups were compared with one-way analysis of variance (ANOVA). Categorical variables were summarized as counts and percentages, and the Chi-square test or Fisher\u0026rsquo;s exact test was used for comparison among groups. Univariate and multivariate Cox regression analyses were used to identify possible factors associated with the prognosis of NSCLC patients. The predictive performance of CD3\u0026thinsp;+\u0026thinsp;T cell was evaluated using the area under receiver operating characteristic (ROC) curve (AUC) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The mPFS was estimated using the Kaplan-Meier method, and log rank test was used to assess the significance of differences between groups. All statistical data were analyzed using SPSS software version 26.0 (SPSS Inc., Chicago, IL, USA) and GraphPad Prism software version 10 (GraphPad, La Jolla, CA, USA). A (two-sided) \u003cem\u003ep\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003ePatient demographics and clinical characteristics\u003c/h2\u003e\u003cp\u003eThe baseline characteristics of patients are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 276 participants were enrolled in this study, including 36 cases in the PD-L1 negative group, 90 cases in the low expression group, and 150 cases in the high expression group. There were no statistically significant differences in gender, age, EGFR mutation type, and ECOG score among the PD-L1 negative group, low expression group, and high expression group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, a statistically significant difference was observed in smoking history among these groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinicopathological Characteristics (n\u0026thinsp;=\u0026thinsp;276)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTatal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eThe expression of PD-L1(n/%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP Value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTPS\u0026lt;1%\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1%\u0026le;TPS\u0026lt;50%\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;90)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTPS\u0026thinsp;\u0026ge;\u0026thinsp;50%\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e59/49.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e41/34.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e20/16.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e3.343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.188\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e91/58.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e49/31.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e16/10.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;60 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e76/62.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e33/27.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12/9.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e5.569\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.062\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;60 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e74/47.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e57/36.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e24/15.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSmoking history\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e121/61.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e54/27.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e21/10.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e14.906\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29/36.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36/45.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e15/18.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEGFR mutation type\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19-DEL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e100/58.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e50/29.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e21/12.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1.218\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.544\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e21-L858R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50/47.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40/38.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e15/14.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eECOG\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u0026ndash;1 score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e167\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94/56.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e52/31.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e21/12.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.241\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.887\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2 score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56/51.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e38/34.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e15/13.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe relationship between the different PD-L1 expression groups and lymphocyte subsets in patients with EGFR-mutant advanced lung adenocarcinoma\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThere were no significant differences in CD3\u0026thinsp;+\u0026thinsp;lymphocyte count, CD4\u0026thinsp;+\u0026thinsp;lymphocyte percentage, CD8\u0026thinsp;+\u0026thinsp;lymphocyte count, B lymphocyte count, and B lymphocyte percentage among PD-L1-negative, low-expression, and high-expression groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, statistically significant differences were observed in CD3\u0026thinsp;+\u0026thinsp;lymphocyte percentage, CD4\u0026thinsp;+\u0026thinsp;lymphocyte count, CD8\u0026thinsp;+\u0026thinsp;lymphocyte percentage, CD4+/CD8\u0026thinsp;+\u0026thinsp;ratio, NK cell percentage, and NK cell count among them (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePeripheral lymphocyte subsets in different PD-L1 expression groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eThe expression of PD-L1(n/%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP1\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP2\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP3\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTPS\u0026lt;1%\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1%\u0026le;TPS\u0026lt;50%\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;90)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTPS\u0026thinsp;\u0026ge;\u0026thinsp;50%\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD3+(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e67.69\u0026thinsp;\u0026plusmn;\u0026thinsp;8.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e73.67\u0026thinsp;\u0026plusmn;\u0026thinsp;7.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e79.10\u0026thinsp;\u0026plusmn;\u0026thinsp;6.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e35.067\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD3+(/\u0026micro;L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e657.43\u0026thinsp;\u0026plusmn;\u0026thinsp;246.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e627.44\u0026thinsp;\u0026plusmn;\u0026thinsp;246.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e581.33\u0026thinsp;\u0026plusmn;\u0026thinsp;201.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.564\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.211\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD4+(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e39.19\u0026thinsp;\u0026plusmn;\u0026thinsp;9.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e39.46\u0026thinsp;\u0026plusmn;\u0026thinsp;9.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e35.99\u0026thinsp;\u0026plusmn;\u0026thinsp;10.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD4+(/\u0026micro;L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e376.69\u0026thinsp;\u0026plusmn;\u0026thinsp;160.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e330.03\u0026thinsp;\u0026plusmn;\u0026thinsp;140.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e273.22\u0026thinsp;\u0026plusmn;\u0026thinsp;156.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.493\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.062\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD8+(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e25.46\u0026thinsp;\u0026plusmn;\u0026thinsp;9.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e30.97\u0026thinsp;\u0026plusmn;\u0026thinsp;10.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e39.30\u0026thinsp;\u0026plusmn;\u0026thinsp;14.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e27.892\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD8+(/\u0026micro;L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e253.27\u0026thinsp;\u0026plusmn;\u0026thinsp;126.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e268.09\u0026thinsp;\u0026plusmn;\u0026thinsp;151.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e289.61\u0026thinsp;\u0026plusmn;\u0026thinsp;126.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.152\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.318\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD4+/CD8+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.051\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.097\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eB(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e8.60\u0026thinsp;\u0026plusmn;\u0026thinsp;6.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e9.99\u0026thinsp;\u0026plusmn;\u0026thinsp;6.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e8.61\u0026thinsp;\u0026plusmn;\u0026thinsp;6.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.531\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.218\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eB(/\u0026micro;L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e90.68\u0026thinsp;\u0026plusmn;\u0026thinsp;79.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e86.67\u0026thinsp;\u0026plusmn;\u0026thinsp;67.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e70.50\u0026thinsp;\u0026plusmn;\u0026thinsp;65.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.342\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNK(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e22.93\u0026thinsp;\u0026plusmn;\u0026thinsp;8.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e16.15\u0026thinsp;\u0026plusmn;\u0026thinsp;6.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e11.47\u0026thinsp;\u0026plusmn;\u0026thinsp;3.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e47.539\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNK(/\u0026micro;L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e210.00\u0026thinsp;\u0026plusmn;\u0026thinsp;89.584\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e129.20\u0026thinsp;\u0026plusmn;\u0026thinsp;56.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e78.53\u0026thinsp;\u0026plusmn;\u0026thinsp;33.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e61.623\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e, overall inter-group comparison; \u003cem\u003eP\u003c/em\u003e1, comparison between the TPS\u0026thinsp;\u0026lt;\u0026thinsp;1% group and the 1% \u0026le; TPS\u0026thinsp;\u0026lt;\u0026thinsp;50% group; \u003cem\u003eP\u003c/em\u003e2, comparison between the TPS\u0026thinsp;\u0026lt;\u0026thinsp;1% group and the TPS\u0026thinsp;\u0026ge;\u0026thinsp;50% group; \u003cem\u003eP\u003c/em\u003e3, comparison between the 1% \u0026le; TPS\u0026thinsp;\u0026lt;\u0026thinsp;50% group and the TPS\u0026thinsp;\u0026ge;\u0026thinsp;50% group.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eUnivariate analysis of factors influencing therapeutic efficacy in patients with EGFR-mutant advanced lung adenocarcinoma\u003c/h3\u003e\n\u003cp\u003eTo explore the potential independent risk factors of disease progression, univariate Cox regression analysis was performed. Smoking (HR\u0026thinsp;=\u0026thinsp;2.085, 95% CI: 1.537\u0026ndash;2.829, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), EGFR mutation subtype (HR\u0026thinsp;=\u0026thinsp;2.584, 95% CI: 1.951\u0026ndash;3.424, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), PD-L1 expression level (HR\u0026thinsp;=\u0026thinsp;2.359, 95% CI: 1.791\u0026ndash;3.107, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), CD3+ (%) (HR\u0026thinsp;=\u0026thinsp;1.067, 95% CI: 1.048\u0026ndash;1.086, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), CD3\u0026thinsp;+\u0026thinsp;lymphocyte count (HR\u0026thinsp;=\u0026thinsp;0.999, 95% CI: 0.998\u0026ndash;0.999, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), CD4+ (%) (HR\u0026thinsp;=\u0026thinsp;1.026, 95% CI: 1.010\u0026ndash;1.042, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), CD4\u0026thinsp;+\u0026thinsp;lymphocyte count (HR\u0026thinsp;=\u0026thinsp;0.998, 95% CI: 0.997\u0026ndash;0.999, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), CD8+ (%) (HR\u0026thinsp;=\u0026thinsp;1.020, 95% CI: 1.007\u0026ndash;1.033, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), CD8\u0026thinsp;+\u0026thinsp;lymphocyte count (HR\u0026thinsp;=\u0026thinsp;0.998, 95% CI: 0.997\u0026ndash;0.999, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), B cell count (HR\u0026thinsp;=\u0026thinsp;0.998, 95% CI: 0.996\u0026ndash;1.000, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020), NK (%) (HR\u0026thinsp;=\u0026thinsp;0.944, 95% CI: 0.926\u0026ndash;0.964, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and NK cell count (HR\u0026thinsp;=\u0026thinsp;0.981, 95% CI: 0.978\u0026ndash;0.983, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were identified as potential risk factors for disease progression of lung cancer (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In contrast, gender, age, ECOG score, B cell percentage, and CD4+/CD8\u0026thinsp;+\u0026thinsp;ratio were not associated with the risk of disease progression (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eUnivariate Cox regression analysis of factors related to mPFS\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003elower limit\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eupper limit\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.795\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.604\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.101\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.226\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.932\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.613\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.145\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSmoking history\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.537\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.829\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEGFR mutation subtype\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.584\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.951\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.424\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eECOG\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.187\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.902\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.562\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.221\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePD-L1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.359\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.791\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD3+(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.067\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD3+(/\u0026micro;L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD4+(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD4+(/\u0026micro;L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD8+(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD8+(/\u0026micro;L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD4+/CD8+\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.887\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.939\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eB(/%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.991\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.245\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eB(/\u0026micro;L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.996\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNK(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.944\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.926\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.964\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNK(/\u0026micro;L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.981\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.978\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.983\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eMultivariate cox regression analysis of factors related to PFS\u003c/h3\u003e\n\u003cp\u003eMultivariate Cox regression analysis showed that EGFR mutation subtype (HR\u0026thinsp;=\u0026thinsp;1.467, 95% CI: 1.076-2.000, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015), PD-L1 expression level (HR\u0026thinsp;=\u0026thinsp;2.193, 95% CI: 1.483\u0026ndash;3.242, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;001), and NK cell count (HR\u0026thinsp;=\u0026thinsp;0.980, 95% CI: 0.974\u0026ndash;0.985, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were independent prognostic factors for patients with EGFR-mutant lung adenocarcinoma.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelative factors based on the multivariate Cox regression analysis\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003elower limit\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eupper limit\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSmoking history\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.374\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.990\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.906\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.057\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEGFR mutation subtype\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.467\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.076\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePD-L1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.483\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD3+(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.547\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD3+(/\u0026micro;L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.726\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD4+(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.034\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.079\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.116\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD4+(/\u0026micro;L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.805\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD8+(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.083\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCD8+(/\u0026micro;L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.993\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.809\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eB(/\u0026micro;L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.191\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNK(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.594\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNK(/\u0026micro;L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.980\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.974\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.985\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eSurvival analysis of patients with NSCLC\u003c/h2\u003e\u003cp\u003eIn this study, we performed ROC analysis to confirm 197.5 cells/\u0026micro;L as the cut-off value of NK cell count according to the survival of patients with NSCLC (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). According to the optimal threshold of NK cell count, patients were divided into high NK cell count group and low NK cell count group. Patients with NK cell count\u0026thinsp;\u0026lt;\u0026thinsp;197.5 cells/\u0026micro;L were included in the low NK cell count group, and patients with NK cell count\u0026thinsp;\u0026ge;\u0026thinsp;197.5 cells/\u0026micro;L were included in the high NK cell count.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSurvival analysis was performed to identify the factors associated with the prognosis of patients with NSCLC. The Kaplan-Meier analysis demonstrated that patients with EGFR 19-DEL mutation had longer mPFS than those with EGFR 21-L858R mutation (15 months vs 7 months; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA ). It was shown that mPFS in PD-L1-positive patients was significantly shorter than that in PD-L1-negative patients (8 months vs 16 months; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). In PD-L1-positive patients, those with low PD-L1 expression (1% \u0026le; TPS \u0026lt;50%) had longer mPFS than those with high PD-L1 expression (TPS\u0026thinsp;\u0026ge;\u0026thinsp;50%) (11 months vs 5 months; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB ). Similarly, it was demonstrated that both PD-L1-high and PD-L1-low subgroups exhibited shorter mPFS compared to PD-L1-negative subgroup ( \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB ). Patients with NK cell count\u0026thinsp;\u0026ge;\u0026thinsp;197.5 cells/\u0026micro;L had significantly longer mPFS compared with patients with NK cell count\u0026thinsp;\u0026lt;\u0026thinsp;197.5 cells/\u0026micro;L (23 months vs 9 months; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eProgression-free survival analysis\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003emPFS(m)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEGFR mutation subtype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19-DEL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e50.391\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e21-L858R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePD-L1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTPS\u0026lt;1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e67.678\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1%\u0026le;TPS\u0026lt;50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTPS\u0026thinsp;\u0026ge;\u0026thinsp;50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNK cell count\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e153.154\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe focus of this study was to investigate the impact of different PD-L1 expression levels on lymphocyte subsets and prognosis in patients with EGFR-mutant advanced NSCLC. The results showed that the mPFS in the high PD-L1 group was inferior to that in the low or negative PD-L1 groups. The subgroup of patients with 19-DEL had significantly longer mPFS compared with the subgroup of patients with 21-L858R. In addition, the mPFS was poorer in the low-NK-cell group than that in the high-NK-cell group. Furthermore, univariate and multivariate Cox regression analyses showed that EGFR mutation type, high PD-L1 expression, and low NK cell levels were independent adverse prognostic factors for mPFS in patients receiving osimertinib.\u003c/p\u003e\u003cp\u003eIn current treatments for advanced NSCLC, targeted therapy has emerged as an irreplaceable approach due to its remarkable efficacy and favorable patient tolerability. The EGFR 19-DEL and 21-L858R mutations are two typical variants of the EGFR gene that exhibit high sensitivity to EGFR-TKIs, and they serve as reliable predictors for evaluating treatment outcomes [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Multiple studies have demonstrated that patients with EGFR 19-DEL mutations generally show better responses to EGFR-TKIs than those with EGFR 21-L858R mutations [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The LUX-Lung series of trials revealed that patients with EGFR 19-DEL demonstrate notably better therapeutic responses and survival outcomes compared with those with EGFR 21-L858R point mutations, primarily manifested through prolonged progression-free survival (PFS) and overall survival (OS) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In our study, among EGFR-mutant patients with advanced lung adenocarcinoma who receiving osimertinib treatment, it was confirmed that the 19-DEL patients subgroup achieved significantly longer mPFS than the 21-L858R patients subgroup.\u003c/p\u003e\u003cp\u003eIt was observed that the mPFS in patients receiving osimertinib reached 18.9 months when osimertinib was used as the first-line treatment for NSCLC in the FLAURA study [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, not all lung adenocarcinoma patients with EGFR-sensitive mutations can benefit from from first-line EGFR-TKI therapys. A large body of research evidence indicates that patients with EGFR mutations accompanied by high PD-L1 expression have poor therapeutic responses to EGFR-TKI, which may be because PD-L1 overexpression is an important cause of primary resistance in tumor cells. As a key immune checkpoint protein, PD-L1 is present on both tumors and tumor-infiltrating immune cells. PD-L1 expression is typically classified as negative (TPS\u0026thinsp;\u0026lt;\u0026thinsp;1%), low ( 1\u0026ndash;49% ), and high (\u0026ge;\u0026thinsp;50% ). It has been observed that PD-L1 expression is affected by the presence of EGFR mutations and the use of EGFR-TKI therapy [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Among EGFR-mutant patients, 44% had a PD-L1 TPS\u0026thinsp;\u0026ge;\u0026thinsp;1%, while 13% had a PD-L1 TPS\u0026thinsp;\u0026ge;\u0026thinsp;50% [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Another study in China showed that among non-small cell lung cancer (NSCLC) patients harboring EGFR mutations, 29.5% exhibited PD-L1 TPS in the range of 1\u0026ndash;49%, while 14.3% demonstrated PD-L1 TPS\u0026thinsp;\u0026ge;\u0026thinsp;50% [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The present study showed that 54.35% of NSCLC patients with EGFR mutations had a PD-L1 TPS\u0026thinsp;\u0026lt;\u0026thinsp;1%, 32.61% had a PD-L1 TPS between 1\u0026ndash;49%, and 13.04% had a PD-L1 TPS\u0026thinsp;\u0026ge;\u0026thinsp;50%. These findings suggest that PD-L1 expression patterns are similar to those in previous studies.\u003c/p\u003e\u003cp\u003ePD-L1 serves as a crucial biomarker in immunotherapy, yet its significance in patients receiving EGFR-TKIs is still ambiguous [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. A retrospective study showed that patients with high PD-L1 expression who received 1st-generation EGFR-TKIs had a significantly shorter mPFS (6.6 months) than those in the low or negative PD-L1 expression group (13.0 months) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Another study demenstated that the estimated mPFS of osimertinib in the high PD-L1 group was 10.1 months, which was significantly shorter than that in the low or negative PD-L1 group [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In addition, the study showed that high PD-L1 expression was an independent unfavorable factor associated with mPFS in patients receiving osimertinib therapy. A recent study showed that in patients receiving first-line osimertinib, those with high PD-L1 expression (TPS\u0026thinsp;\u0026ge;\u0026thinsp;50%) had poorer PFS (5.0 months) than those with low (TPS 1%-49%) or negative (TPS\u0026thinsp;\u0026lt;\u0026thinsp;1%) PD-L1 expression (17.4 months) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Numerous studies have shown a correlation between high PD-L1 expression and poor efficacy of EGFR-TKIs [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. However, some studies present opposite outcomes. For example, it was reported that high PD-L1 expression correlates with prolonged PFS and OS in advanced lung adenocarcinoma patients harboring EGFR mutations after EGFR-TKI therapy [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Similarly, there was a non-significant effect of PD-L1 expression status (positive: \u0026ge; 1% vs. negative) on progression-free survival in the FLAURA study [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In the present study, the mPFS in the PD-L1 high-expression group was 5 months, which was significantly lower than that in the PD-L1 low-expression group (11 months) and PD-L1 negative group (16 months). The present study demonstrated results similar to most previous studies. Thus, PD-L1 expression levels can serve as a biomarker for predicting and evaluating the efficacy of EGFR-TKIs in NSCLC patients with EGFR mutations. High PD-L1 expression is associated with a poor prognosis in patients receiving EGFR-TKI treatment.\u003c/p\u003e\u003cp\u003eThe development and progression of tumors occur within a microenvironment populated by a variety of immune cells and immune products [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Natural killer (NK) cells are generally considered to constitute the first line of anti-tumor defense, and provide tumor immunosurveillance, tumor lysis, and tumor metastasis elimination [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. NK cells are responsible for mediating the release of cytokines and chemokines to counteract cancer cells [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The ability of NK cells to recognize cancer cells is independent of neoantigens or self-antigen overexpression, and tumor cells that lose MHC expression are more susceptible to being killed by NK cells [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. A previous study demenstrated that when pembrolizumab was used together with NK cell therapy for advanced NSCLC patients with PD-L1 positive expression, it brought about improved survival benefits [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eNK cells also participate in the targeting of tumor antigens by monoclonal antibodies (mAbs), which can destroy tumour cells through NK cell-mediated antibody-dependent cellular cytotoxicity (ADCC)[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The existence of anti-EGFR auto-antibodies (IgG isotype) in the serum and tumour tissue of lung cancer patients has been documented during the earliest stages of cancer development[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. This observation offers supportive evidence for using the NK cell-mediated ADCC effect against lung cancer adenocarcinomas with EGFR mutation-positive. Although oncogenic driver mutations that activate EGFR in NSCLC predict sensitivity to specific EGFR-TIKs, increasing drug resistance has emerged after the first- or second-line therapy with the EGFR-TKIs gefitinib and erlotinib [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. NK cell immunotherapy is able to significantly enhance the prognosis of lung cancers, particularly those with EGFR mutations. A clinical study showed that NK cells combined with afatinib, a second-generation targeted drug, significantly improved the therapeutic effect. The remission rate increased from 16.7% to 75%, and the mPFS prolonged from 6 months to 9 months[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. It has been documented that the combination of NK cell therapy and TKI medications enhances the cytotoxic effect on lung cancer cells with EGFR-resistant mutations[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. High NK cell density was independent predictor of longer PFS while high NK proved significant predictors of longer OS[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. In this study, the mPFS in low NK cells group was 9 months, which was significantly lower than that in high NK cell group (23 months). Meanwhile, NK cells is decreased in high PD-L1 expression than in low or negative PD-L1 group, accompanied by poor mPFS.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn the present study, the mPFS of patients in the high PD-L1 expression group, which also has lower NK cell levels, is significantly shorter. The EGFR mutation with 21-L858R was associated with significantly shorter mPFS compared to the subgroup with EGFR mutation 19-DEL. For advanced NSCLC patients with low NK cell levels, EGFR mutatation 21- L858R, and high PD-L1 expression, physicians should be aware of the risk of resistance to osimertinib. For these patients, in addition to TKI-targeted therapy, NK cell-based immunotherapy could be an adjuvant treatment.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eEGFR: Epidermal growth factor receptor; EGFR-TKIs:Epidermal growth factor receptor-tyrosine kinase inhibitors; NSCLC: Non-small cell lung cancer; PD-L1: Programmed death ligand-1; ROC: receiver operating characteristic; mPFS: median progression-free survival; NK: natural killer; ORR: Objective response rate; ECOG, Eastern Cooperative Oncology Group; TPS: Tumor Proportion Score;\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Medical Ethics Committee of Beijing Shijitan Hospital, and informed consent was obtained from all patients prior to their participation in this study. All methods were performed in accordance with relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used in this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have declared that no competing interest exists.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by Beijing Shijtan Hospital\u0026rsquo;s \u0026ldquo;14th Five-Year Plan\u0026rdquo; Leading Talent Training Project (2023LJRCPL).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eL.P and S.W contributed to the conception and design of the study. SW and WW contributed to data collection and analysis. SW contributed to manuscript preparation. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSiegel RL, Kratzer TB, Giaquinto AN, Sung H, Jemal A. Cancer statistics. 2025. CA Cancer J Clin. 2025;75(1):10-45.\u003c/li\u003e\n\u003cli\u003eAllemani C, Matsuda T, Di Carlo V, Harewood R, Matz M, Niksic M, Bonaventure A, Valkov M, Johnson CJ, Esteve J et al. Global surveillance of trends in cancer survival 2000-14 (CONCORD-3): analysis of individual records for 37513025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries. Lancet. 2018;391(10125):1023-75.\u003c/li\u003e\n\u003cli\u003eJorissen RN, Walker F, Pouliot N, Garrett TP, Ward CW, Burgess AW. Epidermal growth factor receptor: mechanisms of activation and signalling. 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Lung Cancer. 2024;192:107824.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"EGFR, PD-L1, lymphocyte subsets, NK cells, Prognosis","lastPublishedDoi":"10.21203/rs.3.rs-7997536/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7997536/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eTo investigate the impact of different programmed cell death-ligand 1 (PD-L1) expression levels on lymphocyte subsets and prognosis in advanced non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe collected the clinical data of 276 EGFR-mutant NSCLC patients who were admitted to Affiliated Beijing Shijitan Hospital, Capital Medical University from 1 January 2022 to 1 January 2024 and treated with osimertinib (a third-generation EGFR-tyrosine kinase inhibitor). The patients were divided into three groups based on PD-L1 expression status: high PD-L1 expression group, low PD-L1 expression group, and PD-L1 negative group. Flow cytometry was used to detect peripheral blood lymphocyte subsets in the three groups of patients. The differences in clinical characteristics and lymphocyte subsets among the three groups were analyzed using Pearson's chi-squared test, Fisher's exact test and one-way analysis of variance (ANOVA). Univariate and multivariate Cox regression analyses were used to identify possible factors associated with the prognosis of EGFR-mutant advanced NSCLC. The predictive performance of NK cells was measured using the area under the receiver operating characteristic (ROC) curve. The median progression-free survival (mPFS) was estimated using the Kaplan-Meier method.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eStatistically significant differences were observed in the percentages of CD3\u0026thinsp;+\u0026thinsp;lymphocytes, CD4\u0026thinsp;+\u0026thinsp;lymphocytes, CD8\u0026thinsp;+\u0026thinsp;lymphocytes, the CD4+/CD8\u0026thinsp;+\u0026thinsp;ratio, and the percentage and absolute count of natural killer (NK) cells across the three PD-L1 expression groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Patients with EGFR exon 19-DEL mutation had a significantly longer mPFS than those with EGFR exon 21-L858R mutation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The mPFS in the high PD-L1 expression group was inferior to that in the low or negative PD-L1 expression groups. In addition, the low-NK-cell group had a poorer mPFS than the high-NK-cell group. Furthermore, univariate and multivariate Cox regression analyses showed that EGFR mutation type, high PD-L1 expression, and low NK cell levels were independent adverse prognostic factors for mPFS in patients receiving osimertinib.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eIn advanced NSCLC patients with EGFR exon 21-L858R mutation, high PD-L1 expression and low NK cell levels are independent adverse prognostic factors. For these patients, in addition to TKI-targeted therapy, NK cell-based immunotherapy could be an adjuvant treatment.\u003c/p\u003e","manuscriptTitle":"The impact of PD-L1 expression on lymphocyte subsets and prognosis in advanced non-small cell lung cancer with EGFR mutations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-02 14:48:52","doi":"10.21203/rs.3.rs-7997536/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-12-21T01:10:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-16T22:17:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"268601319769268708097837321368980492145","date":"2025-12-16T03:35:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"81912269874204221927656585530688268482","date":"2025-12-08T14:48:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-05T03:04:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256456146673585794248370161804510568170","date":"2025-12-01T10:44:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-28T13:43:22+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-05T10:21:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-03T11:43:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-03T11:42:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-10-31T10:32:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f92f2ced-e070-4421-a886-47f33d3f884f","owner":[],"postedDate":"December 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-02T14:48:52+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-02 14:48:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7997536","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7997536","identity":"rs-7997536","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}