Advertisement

PD-L1 score as a prognostic biomarker in asian early-stage epidermal growth factor receptor-mutated lung cancer

  • Stephanie P.L. Saw
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
  • Win Pin Ng
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Genome Institute of Singapore, 60 Biopolis St 138672, Singapore
    Search for articles by this author
  • Siqin Zhou
    Affiliations
    Division of Clinical Trials and Epidemiological Sciences, National Cancer Centre Singapore, 11 Hospital Crescent 169610, Singapore
    Search for articles by this author
  • Gillianne G.Y. Lai
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
  • Aaron C. Tan
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
  • Mei-Kim Ang
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
  • Wan-Teck Lim
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
  • Ravindran Kanesvaran
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
  • Quan Sing Ng
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
  • Amit Jain
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
  • Wan Ling Tan
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
  • Tanujaa Rajasekaran
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
  • Johan W.K. Chan
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
  • Yi Lin Teh
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
  • Mengyuan Pang
    Affiliations
    Genome Institute of Singapore, 60 Biopolis St 138672, Singapore
    Search for articles by this author
  • Jia-Chi Yeo
    Affiliations
    Genome Institute of Singapore, 60 Biopolis St 138672, Singapore
    Search for articles by this author
  • Angela Takano
    Affiliations
    Division of Pathology, Singapore General Hospital, 20 College Road Academia, Level 7 169856, Singapore
    Search for articles by this author
  • Boon-Hean Ong
    Affiliations
    Department of Cardiothoracic Surgery, National Heart Centre, Singapore, 5 Hospital Dr 169609, Singapore
    Search for articles by this author
  • Eng-Huat Tan
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
  • Sze Huey Tan
    Affiliations
    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore

    Division of Clinical Trials and Epidemiological Sciences, National Cancer Centre Singapore, 11 Hospital Crescent 169610, Singapore
    Search for articles by this author
  • Anders J. Skanderup
    Affiliations
    Genome Institute of Singapore, 60 Biopolis St 138672, Singapore
    Search for articles by this author
  • Daniel S.W. Tan
    Correspondence
    Corresponding author: Division of Medical Oncology, National Cancer Centre Singapore, Singhealth Duke-NUS Oncology Academic Clinical Programme, 11 Hospital Crescent, 169610, Singapore.
    Affiliations
    Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, 169610, Singapore

    Duke-NUS Medical School, National University of Singapore, 8 College Rd 169857, Singapore
    Search for articles by this author
Open AccessPublished:November 24, 2022DOI:https://doi.org/10.1016/j.ejca.2022.10.012

      Highlights

      • PD-L1 ≥1% is an independent predictor of worse overall survival in resected epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC).
      • PD-L1 ≥1% is significantly associated with worse disease-free survival regardless of EGFR status.
      • TP53 co-mutations are more common among PD-L1 ≥1% EGFR-mutated NSCLC.
      • PD-L1 should be a stratification factor in adjuvant trials for EGFR-mutated NSCLC.

      Abstract

      Aim

      To determine the prognostic value of programmed death-ligand 1 (PD-L1) score in early-stage epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC), contrasted against EGFR-wildtype NSCLC.

      Methods

      Consecutive patients with Stage IA-IIIA NSCLC diagnosed 1st January 2010–31st December 2019 at National Cancer Centre Singapore with evaluable EGFR and PD-L1 status were included. Co-primary end-points were 2-year disease-free survival (DFS) and 5-year overall survival (OS) by Kaplan–Meier method.

      Results

      455 patients were included (267 EGFR-mutated, EGFR-M+; 188 EGFR-wildtype, wt). Median age at diagnosis was 65 years, 52.3% (238/455) of patients were males, 62.9% (286/455) of patients were never-smokers and 92.5% (421/455) of patients had R0 resection. Stage IA comprised 42.4% (193/455) of patients, Stage IB comprised 23.1% (105/455) of patients, Stage IIA comprised 10.8% of patients (49/455), Stage IIB comprised 5.1% of patients (23/455) and Stage IIIA comprised 18.7% (85/455) of patients. Among EGFR-M+, 45.3% (121/267) were Ex19del and 41.9% (112/267) were L858R. PD-L1 ≥1% among EGFR-M+ and EGFR-wt was 45.3% (121/267) and 54.8% (103/188) respectively (p = 0.047).
      At median follow-up of 47 months, 178 patients had relapsed. Among EGFR-M+, 2-year DFS comparing PD-L1 <1% and PD-L1 ≥1% was 78.1% and 67.6% (p = 0.007) while 5-year OS was 59.5% and 42.8% (p = 0.001), respectively. Controlling for age, gender, lymphovascular invasion, adjuvant therapy and resection margin status, PD-L1 ≥1% (hazard ratio, HR 2.18, 95% CI 1.04–4.54, p = 0.038), stage IIB (HR 7.78, 95% CI 1.72–35.27, p = 0.008) and stage IIIA (HR 4.45, 95% CI 1.44–13.80, p = 0.01) emerged as independent predictors of inferior OS on multivariable analysis.
      In exploratory analysis, genomic analysis of 81 EGFR-M+ tumours was performed. PD-L1 ≥1% tumours had significantly higher rates of TP53 mutations (36.1% versus 15.6%, p = 0.04), with predominantly missense mutations.

      Conclusion

      PD-L1 ≥1% is an independent predictor of worse OS among early-stage EGFR-mutated NSCLC and is associated with inferior DFS regardless of EGFR status. PD-L1 score as a risk stratification factor should be evaluated in prospective adjuvant studies among EGFR-mutated NSCLC.

      Keywords

      1. Introduction

      The adjuvant therapy landscape in early-stage resected epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) has seen significant developments following the landmark approvals of adjuvant osimertinib and atezolizumab, both notably based on disease-free survival (DFS) benefit alone in the absence of mature overall survival (OS) data [
      • Wu Y.L.
      • Tsuboi M.
      • He J.
      • John T.
      • Grohe C.
      • Majem M.
      • et al.
      Osimertinib in resected EGFR-mutated non–small-cell lung cancer.
      ,
      • Felip E.
      • Altorki N.
      • Zhou C.
      • Csőszi T.
      • Vynnychenko I.
      • Goloborodko O.
      • et al.
      Adjuvant atezolizumab after adjuvant chemotherapy in resected stage IB–IIIA non-small-cell lung cancer (IMpower010): a randomised, multicentre, open-label, phase 3 trial.
      ]. Additional trials involving other immune checkpoint inhibitors (ICI) are anticipated, such as adjuvant pembrolizumab in PEARLS/KEYNOTE-091 (3). Although atezolizumab has been granted broad approval in PD-L1 positive stage II-IIIA NSCLC (including EGFR-mutated NSCLC), DFS benefit was mainly driven by PD-L1 ≥50% subgroup [
      • Felip E.
      • Altorki N.
      • Zhou C.
      • Csőszi T.
      • Vynnychenko I.
      • Goloborodko O.
      • et al.
      Adjuvant atezolizumab after adjuvant chemotherapy in resected stage IB–IIIA non-small-cell lung cancer (IMpower010): a randomised, multicentre, open-label, phase 3 trial.
      ]. Notably among the EGFR-mutated subgroup in IMpower010, no DFS benefit was observed with atezolizumab when PD-L1 0% patients were included in the analysis [
      • Felip E.
      • Altorki N.
      • Zhou C.
      • Csőszi T.
      • Vynnychenko I.
      • Goloborodko O.
      • et al.
      Adjuvant atezolizumab after adjuvant chemotherapy in resected stage IB–IIIA non-small-cell lung cancer (IMpower010): a randomised, multicentre, open-label, phase 3 trial.
      ]. On the other hand, preliminary subgroup analysis from PEARLS/KEYNOTE-091 suggests that EGFR-mutated patients may benefit from adjuvant pembrolizumab, although data by PD-L1 status have not been reported [
      • O'Brien M.
      • Paz-Ares L.
      • Marreaud S.
      • Dafni U.
      • Oselin K.
      • Havel L.
      • et al.
      Pembrolizumab versus placebo as adjuvant therapy for completely resected stage IB–IIIA non-small-cell lung cancer (PEARLS/KEYNOTE-091): an interim analysis of a randomised, triple-blind, phase 3 trial.
      ].
      We previously demonstrated that 37% of patients with Stage IB–IIIA EGFR-mutated NSCLC remain disease-free at 5 years without adjuvant osimertinib [
      • Saw S.P.L.
      • Zhou S.
      • Chen J.
      • Lai G.
      • Ang M.K.
      • Chua K.
      • et al.
      Association of clinicopathologic and molecular tumor features with recurrence in resected early-stage epidermal growth factor receptor–positive non–small cell lung cancer.
      ], highlighting the importance of risk stratification. Multiple studies have shown that PD-L1 positivity is associated with inferior survival in advanced NSCLC, albeit this is less established in early-stage disease [
      • Zhou Z.J.
      • Zhan P.
      • Song Y.
      PD-L1 over-expression and survival in patients with non-small cell lung cancer: a meta-analysis.
      ,
      • Soo R.A.
      • Chen Z.
      • Yan Teng R.S.
      • Tan H.L.
      • Iacopetta B.
      • Tai B.C.
      • et al.
      Prognostic significance of immune cells in non-small cell lung cancer: meta-analysis.
      ,
      • Pan Z.K.
      • Ye F.
      • Wu X.
      • An H.X.
      • Wu J.X.
      Clinicopathological and prognostic significance of programmed cell death ligand1 (PD-L1) expression in patients with non-small cell lung cancer: a meta-analysis.
      ]. A meta-analysis comprising 40 studies found PD-L1 expression to be associated with worse OS in early-stage NSCLC but outcomes specific to EGFR-mutated NSCLC and association with DFS were unknown [
      • Tuminello S.
      • Sikavi D.
      • Veluswamy R.
      • Gamarra C.
      • Lieberman-Cribbin W.
      • Flores R.
      • et al.
      PD-L1 as a prognostic biomarker in surgically resectable non-small cell lung cancer: a meta-analysis.
      ]. A smaller meta-analysis of 13 studies found increased PD-L1 expression to be an unfavourable prognostic factor for Asian populations but not for non-Asian populations [
      • Ma J.
      • Chi D.
      • Wang Y.
      • Yan Y.
      • Zhao S.
      • Liu H.
      • et al.
      Prognostic value of PD-L1 expression in resected lung adenocarcinoma and potential molecular mechanisms.
      ]. Considering that none of the patients in IMpower010 or PEARLS/KEYNOTE-091 would have received adjuvant osimertinib, the clinical implications of PD-L1 status among EGFR-mutated NSCLC, especially in a post-ADAURA era remain undefined [
      • Wu Y.L.
      • Tsuboi M.
      • He J.
      • John T.
      • Grohe C.
      • Majem M.
      • et al.
      Osimertinib in resected EGFR-mutated non–small-cell lung cancer.
      ].
      We sought to determine the prognostic value of PD-L1 score in a cohort of patients with early-stage resected EGFR-mutated NSCLC (EGFR-M+) with mature follow-up data predating adjuvant osimertinib, using patients with EGFR-wildtype NSCLC (EGFR-wt) as a comparator cohort. In exploratory analysis, we examined genomic and transcriptomic features associated with PD-L1 score among patients with EGFR-mutated NSCLC.

      2. Material and methods

      2.1 Data collection

      This cohort study was conducted under the approval of SingHealth Centralised Institutional Review Board. All participants provided written informed consent. Clinicopathological information, treatment data and survival outcomes were collated through manual electronic database review managed by the Lung Cancer Consortium Singapore.

      2.2 Study population

      Consecutive patients with AJCC7 Stage IA-IIIA NSCLC diagnosed between 1st January 2010 and 31st December 2019 at National Cancer Centre Singapore, a multidisciplinary tertiary cancer centre, who underwent curative-intent surgery with evaluable EGFR and PD-L1 status were included. EGFR mutations were prospectively detected by Cobas, Sanger sequencing and/or next generation sequencing. Ex19del, L858R and other uncommon EGFR mutations were included. Patients with either Ex19del or L858R mutation in combination with another EGFR co-mutation were classified as Ex19del or L858R accordingly [
      • Wu Y.L.
      • Tsuboi M.
      • He J.
      • John T.
      • Grohe C.
      • Majem M.
      • et al.
      Osimertinib in resected EGFR-mutated non–small-cell lung cancer.
      ]. PD-L1 tumour proportion score was evaluated using SP263 immunohistochemistry as per institutional practice. Exclusion criteria included metastatic disease at diagnosis, mixed small cell lung carcinoma histology and unknown EGFR or PD-L1 status.
      Patients were followed up from diagnosis until death or date of last follow-up. The cut-off for data analysis was 4th February 2022.

      2.3 Outcomes

      Co-primary end-points for this study were 2-year DFS and 5-year OS. DFS was defined as time from diagnosis until disease recurrence or death (whichever occurred first); surviving patients without recurrence were censored at their date of last follow-up. OS was defined as the time from initial diagnosis to date of death, with surviving patients censored at their date of last follow-up.

      2.4 Genomic and transcriptomic analyses

      Whole-exome and RNA-sequencing were performed on a subset of patients with available tissue. Fresh frozen tumour and healthy tissue samples or paired blood samples were subject to whole-exome sequencing at approximately 100x-400x coverage and 100x coverage, respectively, with the mean number of paired-end reads for RNA-sequencing at approximately 30 million. Driver gene alterations that correlate with PD-L1 status were identified, with methods as described elsewhere [
      • Chen J.
      • Yang H.
      • Teo A.S.M.
      • Amer L.B.
      • Sherbaf F.G.
      • Tan C.Q.
      • et al.
      Genomic landscape of lung adenocarcinoma in East Asians.
      ]. Somatic focal copy number alterations (CNA) were identified using GISTIC2.0 and only high level amplifications and homozygous deletions [
      • Mermel C.H.
      • Schumacher S.E.
      • Hill B.
      • Meyerson M.L.
      • Beroukhim R.
      • Getz G.
      GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers.
      ] were included in analysis. To minimise batch effect due to variations in sequencing depth, only lung adenocarcinoma driver genes were analysed [
      • Nahar R.
      • Zhai W.
      • Zhang T.
      • Takano A.
      • Khng A.J.
      • Lee Y.Y.
      • et al.
      Elucidating the genomic architecture of Asian EGFR-M+ lung adenocarcinoma through multi-region exome sequencing.
      ]. For patients with multi-region sequencing data, only clonal mutations or CNA detected in every sequenced sector were used for analysis on a per patient basis. For genes that were mutated in at least 4 patients, mutation frequencies between PD-L1 ≥1% and PD-L1 <1% groups were compared using Fisher exact test. T cell–inflamed gene expression profile (GEP) scores were computed for samples that had RNA-seq data. GEP scores were categorised as high or low using the median as cut-off. Comparisons of PD-L1 tumour proportion score, GEP score [
      • Cristescu R.
      • Mogg R.
      • Ayers M.
      • Albright A.
      • Murphy E.
      • Yearley J.
      • et al.
      Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy.
      ] and tumour mutational burden were conducted using Wilcoxon rank-sum test [
      • Hothorn T.
      • Hornik K.
      • van de Wiel M.A.
      • Zeileis A.
      Implementing a class of permutation tests: the coin package.
      ].

      2.5 Statistical analysis

      Categorical variables were summarised as frequency and percentage, and continuous variables were summarised using median with range or mean with standard deviation and range. We performed χ2 tests or Fisher exact test for categorical variables and Mann–Whitney U test for continuous variables to assess the association between patient characteristics and PD-L1 status. Multivariable logistic regression analysis was performed to assess the association of clinical features and PD-L1 score (≥1%). Survival curves were estimated using Kaplan–Meier method. Differences in survival curves were assessed using log-rank test. Univariable and multivariable Cox regression analyses were performed to assess the association between OS/DFS with clinicopathologic and treatment characteristics. Variable selection for multivariable Cox regression analyses was performed using the backward elimination method, by optimising Akaike information criterion and Harrell's C index. The proportional hazards assumption for the Cox regression models was checked using statistical tests based on the scaled Schoenfeld residuals. A two-sided P < 0.05 was considered statistically significant. All analyses were performed in R software (version 4.2.0) and STATA version 16.0.

      3. Results

      3.1 Characteristics of EGFR-mutated versus EGFR-wildtype

      A total of 1490 patients were screened, of which 455 patients met the inclusion criteria for analysis (267 EGFR-M+ and 188 EGFR-wt). Patient characteristics of all patients are summarised in Table S1. Approximately 83.5% (380/455) of patients had staging positron emission tomography-computed tomography at diagnosis. Median age at diagnosis was 65 years (range 33–86) and distribution by stage was similar between EGFR-M+ and EGFR-wt. Stage IA comprised 42.4% (193/455) of patients, Stage IB 23.1% (105/455) of patients, Stage IIA 10.8% (49/455) of patients, Stage IIB 5.1% (23/455) of patients and Stage IIIA 18.7% (85/455) of patients. There were significantly more males (69.1% versus 40.4%, p < 0.001), non-Chinese ethnicity (18.1% versus 9.7%, p = 0.049) and current or former smokers (60.6% versus 20.6%, p < 0.001) among EGFR-wt than EGFR-M+. For histological features, EGFR-wt was significantly associated with higher incidence of squamous cell carcinomas (12.8% versus 0.7%, p < 0.001), non-acinar adenocarcinoma subtype (66.5% versus 28.8%, p < 0.001) and poorly differentiated tumours (27.1% versus 11.6%, p < 0.001). There was a significantly higher representation of PD-L1 ≥1% among EGFR-wt than EGFR-M+ (54.8% versus 45.3%, p = 0.047), particularly for PD-L1 ≥50% (22.3% versus 6.0%, p < 0.001). There was no significant difference in the methods used to detect EGFR mutation among adenocarcinomas between EGFR-wt and EGFR-M+ (p = 0.613).

      3.2 Patient characteristics of EGFR-mutated cohort by PD-L1 score

      As there were only 16 patients with PD-L1 ≥50% among EGFR-M+ (Table S1), we classified patients into PD-L1 <1% versus ≥1% for subsequent analysis. Patient characteristics of EGFR-M+ distributed by PD-L1 score are summarised in Table 1. There were 4 patients with compound EGFR mutations, of which 3 patients had L858R (2 with T790M, 1 with I759M). The remaining 1 patient had G719A with S768I, which was classified as Others.
      Table 1Patient characteristics of EGFR-M+ by PD-L1 score.
      PD-L1 score, Number (%)
      Total (N = 267)<1% n = 146 (54.7)≥1% n = 121 (45.3)p-value
      Age0.526#
       Mean (SD)64.5 (9.29)64.7 (9.49)64.2 (9.07)
       Range36.0–86.036.0–86.039.0–85.0
      Age at diagnosis0.219
       <65 years old128 (47.9)65 (44.5)63 (52.1)
       ≥65 years old139 (52.1)81 (55.5)58 (47.9)
      Gender0.006
       Female159 (59.6)98 (67.1)61 (50.4)
       Male108 (40.4)48 (32.9)60 (49.6)
      Ethnicity0.542ˆ
       Chinese241 (90.3)131 (89.7)110 (90.9)
       Malay12 (4.5)5 (3.4)7 (5.8)
       Indian4 (1.5)3 (2.1)1 (0.8)
       Others10 (3.7)7 (4.8)3 (2.5)
      Smoking status0.065
       Never smoker212 (79.4)122 (83.6)90 (74.4)
       Current or former55 (20.6)24 (16.4)31 (25.6)
      Histo type0.284
       Adenocarcinoma264 (98.9)143 (97.9)121 (100.0)
       Squamous2 (0.7)2 (1.4)0 (0.0)
       Others1 (0.4)1 (0.7)0 (0.0)
      Adenocarcinoma subtype (n = 264)0.035ˆ
       Acinar190 (72.0)103 (72.0)87 (71.9)
       Pleomorphic/sarcomatoid2 (0.8)1 (0.7)1 (0.8)
       NOS/mixed/unknown23 (8.7)16 (11.2)7 (5.8)
       Lepidic11 (4.2)8 (5.6)3 (2.5)
       Micropapillary6 (2.3)2 (1.4)4 (3.3)
       Minimally invasive2 (0.8)2 (1.4)0 (0.0)
       Papillary12 (4.5)7 (4.9)5 (4.1)
       Solid18 (6.8)4 (2.8)14 (11.6)
      Grade0.024 (0.011)
       Well18 (6.7)13 (8.9)5 (4.1)
       Moderate201 (75.3)115 (78.8)86 (71.1)
       Poor31 (11.6)10 (6.8)21 (17.4)
       Unknown17 (6.4)8 (5.5)9 (7.4)
      Staging (AJCC7)0.110
       IA104 (39.0)65 (44.5)39 (32.2)
       IB71 (26.6)38 (26.0)33 (27.3)
       IIA29 (10.9)14 (9.6)15 (12.4)
       IIB12 (4.5)8 (5.5)4 (3.3)
       IIIA51 (19.1)21 (14.4)30 (24.8)
      Lymphovascular invasion0.021 (0.006)
       No156 (58.4)95 (65.1)61 (50.4)
       Yes89 (33.3)38 (26.0)51 (42.1)
       Unknown22 (8.2)13 (8.9)9 (7.4)
      EGFR mutation0.906
       Ex19del121 (45.3)65 (44.5)56 (46.3)
       L858R112 (41.9)63 (43.2)49 (40.5)
       Others34 (12.7)18 (12.3)16 (13.2)
      P-value estimated using chi-squared test unless otherwise stated.
      P-value within parenthesis excludes the category ‘Unknown/NA'.
      #P-value estimated using Mann–Whitney U test.
      ˆP-value estimated using Fisher's exact test.
      There was no significant association between PD-L1 score and age at diagnosis, ethnicity, smoking status, stage or EGFR mutation subtype. However, PD-L1 ≥1% was significantly associated with male gender (p = 0.006), higher histological grade (p = 0.024), non-acinar adenocarcinoma subtype (p = 0.035) and lymphovascular invasion (LVI) (p = 0.021).
      Multivariable analysis was performed to evaluate the association between clinical features and PD-L1 status (Table S2), which found that only male gender remained significantly associated with PD-L1 ≥1% in the multivariable model comprising of age, ethnicity, smoking status, stage, LVI, grade, adenocarcinoma subtype and EGFR mutation.

      3.3 DFS and OS by PD-L1 score

      At median follow-up of 47 months (range 0–126), 178/455 (39.1%) patients had relapsed. These represented 42.7% (114/267) of EGFR-M+ and 34.0% (64/188) of EGFR-wt cohort. Among EGFR-M+ cohort, 2-year DFS comparing PD-L1 <1% and PD-L1 ≥1% was 78.1% and 67.6% (hazard ratio [HR] 1.67; p = 0.007) while 5-year OS was 59.5% and 42.8% (HR 2.90; p = 0.001), respectively. A similar trend was observed among EGFR-wt cohort, although the difference in 5-year OS did not reach statistical significance (Table 2). DFS and OS by PD-L1 and EGFR mutation status are shown in Fig. 1, showing significantly inferior outcomes of PD-L1 ≥1% except for OS among EGFR-wt cohort. In exploratory analysis, DFS and OS by PD-L1 tertile were analysed (Figure S1), demonstrating consistently worse outcomes with higher PD-L1 score for both EGFR-M+ and EGFR-wt.
      Table 22-year DFS and 5-year OS by PD-L1 score for EGFR-M+ and EGFR-wt.
      2-year DFS (95% CI)HR (95% CI)p value5-year OS (95% CI)HR (95% CI)p value
      EGFR-M+PD-L1 <1% (n = 146)78.1% (70.3%–84.1%)159.5% (48.7%–68.7%)1
      PD-L1 ≥1% (n = 121)67.6% (58.4%–75.1%)1.67 (1.15–2.41)0.00742.8% (32.8%–52.4%)2.90 (1.52–5.54)0.001
      EGFR-wtPD-L1 <1% (n = 146)77.2% (66.6%–84.8%)176.3% (62.8%–85.5%)1
      PD-L1 ≥1% (n = 121)58.2% (47.8%–67.2%)1.80 (1.15–2.79)0.00960.4% (47.4%–71.2%)1.36 (0.79–2.36)0.269
      Fig. 1
      Fig. 1DFS and OS by PD-L1 score and EGFR status. DFS, disease-free survival; EGFR, epidermal growth factor receptor.

      3.4 Clinicopathological features associated with recurrence among EGFR-mutated cohort

      After demonstrating that PD-L1 ≥1% was significantly associated with both inferior DFS and OS among EGFR-M+, we sought to identify clinicopathological features associated with recurrence.
      Univariable and multivariable analysis was performed to identify clinicopathological features associated with DFS and OS. While PD-L1 ≥1%, age ≥65 at diagnosis, smoking status, higher stage at diagnosis, higher histological grade, LVI, solid/micropapillary adenocarcinoma subtype, receiving adjuvant platinum doublet chemotherapy and R1/R2 resection margins were associated with DFS on univariable analysis, only stage IIB (HR 3.67, 95% CI 1.45–9.32, p = 0.006), stage IIIA (HR 2.83, 95% CI 1.41–5.67, p = 0.003) and LVI (HR 1.82, 95% CI 1.13–2.94, p = 0.014) remained significantly associated with inferior DFS on multivariable analysis (Table 3). After controlling for age, gender, LVI, adjuvant therapy and resection margin status, PD-L1 ≥1% (HR 2.18, 95% CI 1.04–4.54, p = 0.038), stage IIB (HR 7.78, 95% CI 1.72–35.27, p = 0.008) and stage IIIA (HR 4.45, 95% CI 1.44–13.80, p = 0.01) were found to be independent predictors of inferior OS on multivariable analysis (Table 4).
      Table 3Univariable and multivariable analysis of DFS for EGFR-M+.
      DFS (Events/Pts = 112/264)UnivariableMultivariable
      HR (95% CI)p-valueAdjusted HR (95% CI)p-value
      PD-L1 TPS
       <1%11
       ≥1%1.72 (1.18–2.50)0.0051.24 (0.81–1.90)0.328
      Age at diagnosis
       <65 years old11
       ≥65 years old0.60 (0.41–0.88)0.0080.70 (0.47–1.06)0.096
      Smoking Status
       Never smoker11
       Current or former smoker1.83 (1.22–2.77)0.0041.33 (0.85–2.10)0.213
      Staging (AJCC7)
       IA11
       IB1.46 (0.84–2.54)0.1761.15 (0.64–2.07)0.646
       IIA2.56 (1.38–4.77)0.0031.28 (0.56–2.91)0.553
       IIB3.37 (1.47–7.75)0.0043.67 (1.45–9.32)0.006
       IIIA4.86 (2.94–8.01)<0.0012.83 (1.41–5.67)0.003
      Lymphovascular invasion
       No11
       Yes2.69 (1.80–4.02)<0.0011.82 (1.13–2.94)0.014
       Unknown3.02 (1.65–5.52)<0.0013.92 (1.68–9.11)0.002
      Grade
       Well/Moderate11
       Poor2.48 (1.50–4.10)<0.0011.29 (0.55–3.08)0.558
       Unknown2.33 (1.27–4.29)0.0071.97 (0.95–4.12)0.07
      Adenocarcinoma Subtype
       Minimally invasive/lepidic11
       Acinar/papillary1.49 (0.55–4.08)0.4360.87 (0.30–2.55)0.797
       Solid/micropapillary3.83 (1.28–11.41)0.0161.11 (0.27–4.50)0.881
       Others2.68 (0.88–8.19)0.0841.18 (0.33–4.24)0.8
      Adjuvant therapy
       No11
       Gefitinib1.78 (0.85–3.75)0.1270.89 (0.39–2.04)0.777
       Platinum doublet chemotherapy2.54 (1.71–3.79)<0.0010.84 (0.47–1.48)0.541
       Single agent chemotherapy8.71 (1.19–63.92)0.0331.19 (0.13–11.40)0.878
      Resection margins
       R011
       R1/R22.40 (1.12–5.18)0.0252.08 (0.85–5.12)0.109
       Unknown1.10 (0.48–2.54)0.8210.23 (0.07–0.75)0.015
      Table 4Univariable and multivariable analysis of OS for EGFR-M+.
      OS (Events/Pts = 43/267)UnivariableMultivariable
      HR (95% CI)p-valueAdjusted HR (95% CI)p-value
      PDL1 TPS
       <1%11
       ≥1%2.90 (1.52–5.54)0.0012.18 (1.04–4.54)0.038
      Age at diagnosis
       <65 years old11
       ≥65 years old1.17 (0.62–2.20)0.6251.78 (0.85–3.73)0.126
      Gender
       Female11
       Male1.91 (1.04–3.51)0.0381.70 (0.87–3.31)0.121
      Staging (AJCC7)
       IA11
       IB1.61 (0.60–4.31)0.3391.42 (0.51–3.92)0.501
       IIA2.64 (0.95–7.32)0.0623.02 (0.92–9.92)0.069
       IIB4.24 (1.12–16.05)0.0337.78 (1.72–35.27)0.008
       IIIA3.82 (1.64–8.94)0.0024.45 (1.44–13.80)0.01
      Lymphovascular invasion
       No11
       Yes2.81 (1.43–5.49)0.0031.78 (0.83–3.84)0.14
       Unknown2.48 (0.94–6.55)0.0662.60 (0.80–8.46)0.113
      Adjuvant therapy
       No11
       Gefitinib1.10 (0.26–4.75)0.8950.57 (0.12–2.79)0.489
       Platinum doublet chemotherapy1.50 (0.78–2.89)0.2260.49 (0.20–1.17)0.109
       Single agent chemotherapy5.95 (0.80–44.38)0.0824.24 (0.20–88.28)0.351
      Resection margins
       R011
       R1/R21.09 (0.26–4.53)0.9080.44 (0.05–3.62)0.448
       Unknown0.94 (0.22–3.92)0.9290.63 (0.11–3.66)0.61

      3.5 Molecular features among EGFR-mutated cohort by PD-L1 score

      In exploratory analysis, genomic and transcriptomic data of 81 patients from EGFR-M+ cohort were analysed to interrogate the relationship between PD-L1 status and molecular correlates. As there were only 2 patients with PD-L1 ≥50%, patients were segregated into PD-L1 <1% (n = 45) and PD-L1 ≥1% (n = 36). We sought to examine differences in lung adenocarcinoma-specific driver genes [
      • Nahar R.
      • Zhai W.
      • Zhang T.
      • Takano A.
      • Khng A.J.
      • Lee Y.Y.
      • et al.
      Elucidating the genomic architecture of Asian EGFR-M+ lung adenocarcinoma through multi-region exome sequencing.
      ] as shown in Fig. 2.
      Fig. 2
      Fig. 2Oncoprint of mutations and copy number alterations comparing PD-L1 <1% and ≥1% among EGFR-M+. EGFR, epidermal growth factor receptor.
      TP53, RBM10 and CTNNB1 were the most frequently mutated genes seen in 24.7% (20/81), 17.3% (14/81) and 6.2% (5/81), respectively. PD-L1 ≥1% tumours had significantly higher rates of TP53 mutations than PD-L1 <1% tumours at 36.1% (13/36) versus 15.6% (7/45) (p = 0.04), whereas PD-L1 <1% tumours had higher rates of RBM10 mutations than PD-L1 ≥1% tumours at 24.4% (11/45) versus 8.3% (3/36) (p = 0.08). Accordingly, PD-L1 scores were significantly higher among tumours with TP53 mutations than TP53-wildtype (p = 0.016) while RBM10-wild type tumours had a non-significant trend towards higher PD-L1 scores (p = 0.11) as shown in Figure S2.
      To further explore the TP53 pathway, we evaluated CNA of MDM2 and MDM4, both key regulators of p53 activity, in relation to PD-L1 status. We observed mutual exclusivity between TP53 mutation and MDM2 or MDM4 amplification (Fig. 2). TP53 mutations were associated with a trend towards higher incidence of disease relapse than TP53-wildtype at 45.0% (9/20) versus 32.8% (20/61), although the difference was not statistically significant (p = 0.42). We then examined the impact of various TP53 mutation subtypes, classified into missense, nonsense and frameshift deletion mutations. TP53 missense mutations were more common among PD-L1 ≥1% tumours than PD-L1 <1% tumours at 27.8% (10/36) versus 11.1% (5/45) (p = 0.08), as shown in Fig. 2.
      Tumour mutational burden, defined as total clonal non-synonymous mutations per megabase of genome sequenced, and GEP scores were also computed, showing no significant difference between PD-L1 <1% and PD-L1 ≥1% (Fig. S3).

      4. Discussion

      Our findings confirm that PD-L1 ≥1% is an independent predictor of worse OS among early-stage EGFR-mutated NSCLC, consistent with what has been reported [
      • Tuminello S.
      • Sikavi D.
      • Veluswamy R.
      • Gamarra C.
      • Lieberman-Cribbin W.
      • Flores R.
      • et al.
      PD-L1 as a prognostic biomarker in surgically resectable non-small cell lung cancer: a meta-analysis.
      ,
      • Ma J.
      • Chi D.
      • Wang Y.
      • Yan Y.
      • Zhao S.
      • Liu H.
      • et al.
      Prognostic value of PD-L1 expression in resected lung adenocarcinoma and potential molecular mechanisms.
      ]. A smaller Japanese study of 280 patients found PD-L1 ≥50% was associated with a significantly higher risk of post-operative recurrence and was more common among EGFR-wildtype and Stage II-IIIA [
      • Kojima K.
      • Sakamoto T.
      • Kasai T.
      • Kagawa T.
      • Yoon H.
      • Atagi S.
      PD-L1 expression as a predictor of postoperative recurrence and the association between the PD-L1 expression and EGFR mutations in NSCLC.
      ], in keeping with our findings. The differential impact of PD-L1 score on long-term outcomes for resected EGFR-mutated NSCLC contrasted against EGFR-wildtype NSCLC has not been well described previously. We demonstrated that higher PD-L1 score is associated with inferior outcomes among resected NSCLC regardless of EGFR status, although this did not reach statistical significance for OS among EGFR-wildtype and the small number of PD-L1 ≥50% EGFR-mutated NSCLC limits interpretation. PD-L1 ≥1% was significantly associated with inferior DFS among both EGFR-mutated and EGFR-wildtype NSCLC on univariable analysis, but strikingly emerged as the only feature apart from higher stage that was associated with inferior OS in EGFR-mutated NSCLC on multivariable analysis.
      The clinical significance of PD-L1 score among oncogene-driven NSCLC remains poorly defined. ICI have limited efficacy in the metastatic setting for EGFR-mutated NSCLC regardless of PD-L1 score [
      • Lee C.K.
      • Man J.
      • Lord S.
      • Links M.
      • Gebski V.
      • Mok T.
      • et al.
      Checkpoint inhibitors in metastatic EGFR-mutated non–small cell lung cancer—a meta-analysis.
      ,
      • Dotsu Y.
      • Horiike A.
      • Yoshizawa T.
      • Sonoda T.
      • Koyama J.
      • Saiki M.
      • et al.
      Programmed death-ligand 1 expression after progressive disease with EGFR-TKI and efficacy of anti-programmed death-1 antibody in non-small cell lung cancer(NSCLC) harboring EGFR mutation.
      ]. In the setting of resectable NSCLC, subset analysis from IMpower010 and PEARLS/KEYNOTE-091 suggest that patients with EGFR mutations could potentially benefit from adjuvant ICI, particularly for PD-L1 ≥1% [
      • Felip E.
      • Altorki N.
      • Zhou C.
      • Csőszi T.
      • Vynnychenko I.
      • Goloborodko O.
      • et al.
      Adjuvant atezolizumab after adjuvant chemotherapy in resected stage IB–IIIA non-small-cell lung cancer (IMpower010): a randomised, multicentre, open-label, phase 3 trial.
      ,
      • O'Brien M.
      • Paz-Ares L.
      • Marreaud S.
      • Dafni U.
      • Oselin K.
      • Havel L.
      • et al.
      Pembrolizumab versus placebo as adjuvant therapy for completely resected stage IB–IIIA non-small-cell lung cancer (PEARLS/KEYNOTE-091): an interim analysis of a randomised, triple-blind, phase 3 trial.
      ]. While these results should be interpreted with caution given the relatively small patient numbers, our data supports evaluating PD-L1 score as risk stratification factor in prospective adjuvant studies among resected EGFR-mutated NSCLC.
      High PD-L1 expression has been shown to predict for poor response and de novo resistance to EGFR tyrosine kinase inhibitors (TKI) including osimertinib in the metastatic setting [
      • Su S.
      • Dong Z.Y.
      • Xie Z.
      • Yan L.X.
      • Li Y.F.
      • Su J.
      • et al.
      Strong programmed death ligand 1 expression predicts poor response and de novo resistance to EGFR tyrosine kinase inhibitors among NSCLC patients with EGFR mutation.
      ,
      • Hsu K.H.
      • Tseng J.S.
      • Yang T.Y.
      • Chen K.C.
      • Su K.Y.
      • Yu S.L.
      • et al.
      PD-L1 strong expressions affect the clinical outcomes of osimertinib in treatment naïve advanced EGFR-M+ non-small cell lung cancer patients.
      ,
      • Peng Z.
      • Lin H.
      • Zhou K.
      • Deng S.
      • Mei J.
      Predictive value of pretreatment PD-L1 expression in EGFR-M+ non-small cell lung cancer: a meta-analysis.
      ]. Proposed mechanisms include activation of the JAK-STAT pathway as well as high MUC16 mutation frequency observed among PD-L1 ≥50% tumours [
      • Kang M.
      • Park C.
      • Kim S.H.
      • Yoon S.W.
      • Suh K.J.
      • Kim Y.J.
      • et al.
      Programmed death-ligand 1 expression level as a predictor of EGFR tyrosine kinase inhibitor efficacy in lung adenocarcinoma.
      ]. In addition, CD8 and PD-L1 dual positivity were detected in 46.7% (7/15) EGFR-mutated tumours with de novo TKI resistance, suggesting that the tumour microenvironment could be influenced by PD-L1 expression and consequently affect TKI sensitivity [
      • Su S.
      • Dong Z.Y.
      • Xie Z.
      • Yan L.X.
      • Li Y.F.
      • Su J.
      • et al.
      Strong programmed death ligand 1 expression predicts poor response and de novo resistance to EGFR tyrosine kinase inhibitors among NSCLC patients with EGFR mutation.
      ]. In view of these considerations, mature survival data from ADAURA analysed by PD-L1 status will be highly relevant [
      • Wu Y.L.
      • Tsuboi M.
      • He J.
      • John T.
      • Grohe C.
      • Majem M.
      • et al.
      Osimertinib in resected EGFR-mutated non–small-cell lung cancer.
      ]. If high PD-L1 expression is found to predict for worse survival outcomes with adjuvant osimertinib, future trials could explore the role of novel therapeutic strategies in this subgroup.
      PD-L1 expression has been reported to be associated with TP53 mutations in NSCLC [
      • Agersborg S.
      • Jiang S.
      • Chen W.
      • Ma W.
      • Albitar M.
      PD-L1 expression correlation with TP53 gene mutation status in lung cancer but not in colorectal cancer.
      ,
      • Liu Y.
      • Wu A.
      • Li X.
      • Wang S.
      • Fang S.
      • Mo Y.
      A retrospective analysis of eleven gene mutations, PD-L1 expression and clinicopathological characteristics in non-small cell lung cancer patients.
      ]. TP53 mutations are a known poor prognostic marker in NSCLC but the significance of the various subtypes is less established. TP53 missense mutations were found to be associated with increased PD-L1 expression and predictive of benefit with ICI, whereas nonsense mutations were more similar to TP53-wildtype tumours [
      • Sun H.
      • Liu S.Y.
      • Zhou J.Y.
      • Xu J.T.
      • Zhang H.K.
      • Yan H.H.
      • et al.
      Specific TP53 subtype as biomarker for immune checkpoint inhibitors in lung adenocarcinoma.
      ]. Our findings support TP53 mutations as being associated with increased relapse risk and missense subtype mutations as being positively correlated with PD-L1 expression. In addition, we observed higher rates of RBM10 mutations among PD-L1 <1% tumours, with majority non-overlapping with TP53 mutations. RBM10 regulates the p53-MDM2-pathway by reducing degradation of p53 via MDM2 binding [
      • Jung J.H.
      • Lee H.
      • Zeng S.X.
      • Lu H.
      RBM10, a new regulator of p53.
      ] and the association between RBM10 mutations with lower PD-L1 scores among EGFR-mutated NSCLC has been previously reported [
      • Zhou Q.
      • Gu W.
      • Fu W.
      • Mai S.
      • Lin D.
      • Zhang S.
      • et al.
      Abstract 1691: the impact of genomic mutational status on PD-L1 expression and tumor mutation burden in non-small cell lung cancer.
      ]. One possible explanation for this observation could be RBM10 mutations prevent inactivation of p53, which consequently reduces PD-L1 expression, although functional studies are needed to confirm this.
      Our study had several limitations. A single-centre study comprising predominantly Asian patients could limit the generalisability of the data. Being retrospective in nature, the sample size was also limited as PD-L1 and EGFR were not routinely tested in early-stage tumours until recent years. The heterogeneous assays used for EGFR testing could have also affected the sensitivity of detecting uncommon and compound mutations. Genomic and transcriptomic data were only available for a small subset of patients, although our findings highlight the potential for molecular risk stratification to complement clinical practice.

      5. Conclusion

      In conclusion, our study confirms PD-L1 score ≥1% as an independent predictor of worse OS among early-stage EGFR-mutated NSCLC. Our findings underscore the importance of personalised risk-stratified adjuvant strategies, which can be enhanced with the integration of molecular features. This is especially relevant given the increasing availability of novel adjuvant therapies with uncertain risk-benefit ratios for each patient subgroup in the absence of long-term survival data. Lastly, the clinical significance of PD-L1 score in resectable EGFR-mutated NSCLC warrants further study and PD-L1 score as a risk stratification factor should be evaluated in prospective adjuvant studies among EGFR-mutated NSCLC.

      Funding

      This work was supported by grants from the National Medical Research Council of Singapore [NMRC/TCR/007-NCC/2013 and NMRC/OFLCG/002–2018], International Lung Cancer Foundation and Duke-NUS Medical School [08/FY2021/P2/14-A95].

      Author contributions section

      Stephanie P.L. Saw: Data curation; Formal analysis; Investigation; Methodology; Project administration; Visualisation; Roles/Writing – original draft; Writing – review & editing.
      Win Pin Ng: Data curation; Formal analysis; Investigation; Visualisation; Roles/Writing – original draft; Writing – review & editing.
      Siqin Zhou: Formal analysis; Methodology; Validation; Visualisation; Writing – review & editing.
      Gillianne G.Y. Lai: Investigation; Project administration; Resources; Writing – review & editing.
      Aaron C. Tan: Investigation; Writing – review & editing.
      Mei-Kim Ang: Investigation; Writing – review & editing.
      Wan-Teck Lim: Investigation; Writing – review & editing.
      Ravindran Kanesvaran: Investigation; Writing – review & editing.
      Quan Sing Ng: Investigation; Writing – review & editing.
      Amit Jain: Investigation; Writing – review & editing.
      Wan Ling Tan: Investigation; Writing – review & editing.
      Tanujaa Rajasekaran: Investigation; Writing – review & editing.
      Johan W.K. Chan: Investigation; Writing – review & editing.
      Yi Lin Teh: Investigation; Writing – review & editing.
      Mengyuan Pang: Validation; Writing – review & editing.
      Jia-Chi Yeo: Validation; Writing – review & editing.
      Angela Takano: Investigation; Writing – review & editing.
      Boon-Hean Ong: Investigation; Writing – review & editing.
      Eng-Huat Tan: Investigation; Writing – review & editing.
      Sze Huey Tan: Data curation; Formal analysis; Methodology; Validation; Visualisation; Writing – review & editing.
      Anders J. Skanderup: Formal analysis; Funding acquisition; Visualisation; Writing – review & editing.
      Daniel S.W. Tan: Conceptualisation; Funding acquisition; Investigation; Methodology; Project administration; Writing – review & editing.

      Conflict of interest statement

      The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
      Dr. Saw reported receiving personal fees from Pfizer, Bayer, AstraZeneca and MSD outside the submitted work. Dr A. Tan reported receiving personal fees from Amgen and Pfizer outside the submitted work. Dr Lai reported receiving personal fees from Amgen and grants from Merck, Astra Zeneca, Pfizer, Bristol Myers Squibb, and Roche outside the submitted work. Dr D.W.T. Lim reported receiving grants from Bristol Myers Squibb and Boehringer-Ingelheim and personal fees from Merck, Roche, Pfizer, Taiho, and Astra-Zeneca outside the submitted work. Dr Kanesvaran reported receiving personal fees from Merck, Bristol Myers Squibb, Astellas, Johnson & Johnson, Eisai, Ipsen and Novartis outside the submitted work. Dr Ng reported serving on advisory boards for Boehringer Ingelheim and Merck outside the submitted work. Dr W.L. Tan reported receiving personal fees from Amgen, Merck and Novartis outside the submitted work. Dr. Ong reported receiving personal fees from AstraZeneca, MSD and Medtronic, non-financial support from Johnson & Johnson, personal fees and non-financial support from Stryker outside the submitted work. Dr D.S.W. Tan reported grants from AstraZeneca and Amgen and personal fees from Novartis, Boehringer Ingelheim, Bayer, GlaxoSmithKline, Janssen, Amgen, and C4 Therapeutics outside the submitted work. No other disclosures were reported.

      Acknowledgements

      Data collection for this study was conducted via the Lung Cancer Consortium Singapore (LCCS).

      Appendix A. Supplementary data

      The following are the Supplementary data to this article:

      References

        • Wu Y.L.
        • Tsuboi M.
        • He J.
        • John T.
        • Grohe C.
        • Majem M.
        • et al.
        Osimertinib in resected EGFR-mutated non–small-cell lung cancer.
        N Engl J Med [Internet]. 2020 Sep; (Available from: http://doi.org/10.1056/NEJMoa2027071)
        • Felip E.
        • Altorki N.
        • Zhou C.
        • Csőszi T.
        • Vynnychenko I.
        • Goloborodko O.
        • et al.
        Adjuvant atezolizumab after adjuvant chemotherapy in resected stage IB–IIIA non-small-cell lung cancer (IMpower010): a randomised, multicentre, open-label, phase 3 trial.
        The Lancet. 2021 Oct 9; 398: 1344-1357
        • O'Brien M.
        • Paz-Ares L.
        • Marreaud S.
        • Dafni U.
        • Oselin K.
        • Havel L.
        • et al.
        Pembrolizumab versus placebo as adjuvant therapy for completely resected stage IB–IIIA non-small-cell lung cancer (PEARLS/KEYNOTE-091): an interim analysis of a randomised, triple-blind, phase 3 trial.
        Lancet Oncol. 2022 Oct 1; 23: 1274-1286
        • Saw S.P.L.
        • Zhou S.
        • Chen J.
        • Lai G.
        • Ang M.K.
        • Chua K.
        • et al.
        Association of clinicopathologic and molecular tumor features with recurrence in resected early-stage epidermal growth factor receptor–positive non–small cell lung cancer.
        JAMA Netw Open. 2021 Nov; 4 (e2131892–e2131892)
        • Zhou Z.J.
        • Zhan P.
        • Song Y.
        PD-L1 over-expression and survival in patients with non-small cell lung cancer: a meta-analysis.
        Transl Lung Cancer Res. 2015 Apr; 4: 203-208
        • Soo R.A.
        • Chen Z.
        • Yan Teng R.S.
        • Tan H.L.
        • Iacopetta B.
        • Tai B.C.
        • et al.
        Prognostic significance of immune cells in non-small cell lung cancer: meta-analysis.
        Oncotarget. 2018 May; 9: 24801-24820
        • Pan Z.K.
        • Ye F.
        • Wu X.
        • An H.X.
        • Wu J.X.
        Clinicopathological and prognostic significance of programmed cell death ligand1 (PD-L1) expression in patients with non-small cell lung cancer: a meta-analysis.
        J Thorac Dis. 2015 Mar; 7: 462-470
        • Tuminello S.
        • Sikavi D.
        • Veluswamy R.
        • Gamarra C.
        • Lieberman-Cribbin W.
        • Flores R.
        • et al.
        PD-L1 as a prognostic biomarker in surgically resectable non-small cell lung cancer: a meta-analysis.
        Transl Lung Cancer Res. 2020 Aug; 9: 1343-1360
        • Ma J.
        • Chi D.
        • Wang Y.
        • Yan Y.
        • Zhao S.
        • Liu H.
        • et al.
        Prognostic value of PD-L1 expression in resected lung adenocarcinoma and potential molecular mechanisms.
        J Cancer. 2018 Sep; 9: 3489-3499
        • Chen J.
        • Yang H.
        • Teo A.S.M.
        • Amer L.B.
        • Sherbaf F.G.
        • Tan C.Q.
        • et al.
        Genomic landscape of lung adenocarcinoma in East Asians.
        Nat Genet. 2020; 52: 177-186
        • Mermel C.H.
        • Schumacher S.E.
        • Hill B.
        • Meyerson M.L.
        • Beroukhim R.
        • Getz G.
        GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers.
        Genome Biol. 2011 Apr 28; 12: R41
        • Nahar R.
        • Zhai W.
        • Zhang T.
        • Takano A.
        • Khng A.J.
        • Lee Y.Y.
        • et al.
        Elucidating the genomic architecture of Asian EGFR-M+ lung adenocarcinoma through multi-region exome sequencing.
        Nat Commun. 2018; 9
        • Cristescu R.
        • Mogg R.
        • Ayers M.
        • Albright A.
        • Murphy E.
        • Yearley J.
        • et al.
        Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy.
        Science. 2018 Oct 12; 362: eaar3593
        • Hothorn T.
        • Hornik K.
        • van de Wiel M.A.
        • Zeileis A.
        Implementing a class of permutation tests: the coin package.
        J Stat Software. 2008 Nov 13; 28: 1-23
        • Kojima K.
        • Sakamoto T.
        • Kasai T.
        • Kagawa T.
        • Yoon H.
        • Atagi S.
        PD-L1 expression as a predictor of postoperative recurrence and the association between the PD-L1 expression and EGFR mutations in NSCLC.
        Sci Rep. 2021 Sep 1; 1117522
        • Lee C.K.
        • Man J.
        • Lord S.
        • Links M.
        • Gebski V.
        • Mok T.
        • et al.
        Checkpoint inhibitors in metastatic EGFR-mutated non–small cell lung cancer—a meta-analysis.
        J Thorac Oncol. 2017 Feb 1; 12: 403-407
        • Dotsu Y.
        • Horiike A.
        • Yoshizawa T.
        • Sonoda T.
        • Koyama J.
        • Saiki M.
        • et al.
        Programmed death-ligand 1 expression after progressive disease with EGFR-TKI and efficacy of anti-programmed death-1 antibody in non-small cell lung cancer(NSCLC) harboring EGFR mutation.
        J Clin Oncol. 2018 May 20; 36 (e21232–e21232)
        • Su S.
        • Dong Z.Y.
        • Xie Z.
        • Yan L.X.
        • Li Y.F.
        • Su J.
        • et al.
        Strong programmed death ligand 1 expression predicts poor response and de novo resistance to EGFR tyrosine kinase inhibitors among NSCLC patients with EGFR mutation.
        J Thorac Oncol. 2018 Nov 1; 13: 1668-1675
        • Hsu K.H.
        • Tseng J.S.
        • Yang T.Y.
        • Chen K.C.
        • Su K.Y.
        • Yu S.L.
        • et al.
        PD-L1 strong expressions affect the clinical outcomes of osimertinib in treatment naïve advanced EGFR-M+ non-small cell lung cancer patients.
        Sci Rep. 2022 Jun 13; 12: 9753
        • Peng Z.
        • Lin H.
        • Zhou K.
        • Deng S.
        • Mei J.
        Predictive value of pretreatment PD-L1 expression in EGFR-M+ non-small cell lung cancer: a meta-analysis.
        World J Surg Oncol. 2021 May 8; 19: 145
        • Kang M.
        • Park C.
        • Kim S.H.
        • Yoon S.W.
        • Suh K.J.
        • Kim Y.J.
        • et al.
        Programmed death-ligand 1 expression level as a predictor of EGFR tyrosine kinase inhibitor efficacy in lung adenocarcinoma.
        Transl Lung Cancer Res. Febr 2021; Vol 10 (Transl Lung Cancer Res [Internet]. 2021 [cited 2021 Jan 1]; Available from:)
        • Agersborg S.
        • Jiang S.
        • Chen W.
        • Ma W.
        • Albitar M.
        PD-L1 expression correlation with TP53 gene mutation status in lung cancer but not in colorectal cancer.
        J Clin Oncol. 2016 May 20; 3411557–11557
        • Liu Y.
        • Wu A.
        • Li X.
        • Wang S.
        • Fang S.
        • Mo Y.
        A retrospective analysis of eleven gene mutations, PD-L1 expression and clinicopathological characteristics in non-small cell lung cancer patients.
        Asian J Surg. 2022 Jan 1; 45: 367-375
        • Sun H.
        • Liu S.Y.
        • Zhou J.Y.
        • Xu J.T.
        • Zhang H.K.
        • Yan H.H.
        • et al.
        Specific TP53 subtype as biomarker for immune checkpoint inhibitors in lung adenocarcinoma.
        eBioMedicine [Internet]. 2020 Oct 1; ([cited 2022 May 21];60. Available from: https://doi.org/10.1016/j.ebiom.2020.102990)
        • Jung J.H.
        • Lee H.
        • Zeng S.X.
        • Lu H.
        RBM10, a new regulator of p53.
        Cells. 2020; 9
        • Zhou Q.
        • Gu W.
        • Fu W.
        • Mai S.
        • Lin D.
        • Zhang S.
        • et al.
        Abstract 1691: the impact of genomic mutational status on PD-L1 expression and tumor mutation burden in non-small cell lung cancer.
        Cancer Res. 2019 Jul 1; 791691–1691