Association of Survival and Immune-Related Biomarkers With Immunotherapy in Patients With Non-Small Cell Lung Cancer: A Meta-analysis and Individual Patient-Level Analysis

Abstract

Importance: The beneficial role of immunotherapy and the clinical relevance of current biomarkers in non-small cell lung cancer (NSCLC) remain inconclusive; thus, appropriate strategies and reliable predictors need further definition.

Objectives: To evaluate the association of clinical outcomes with immune checkpoint inhibitors, tumor vaccines, and cellular immunotherapy in patients with advanced NSCLC and to explore appropriate strategies, candidates, and predictors.

Data sources: The PubMed, EMBASE, and Cochrane Central Register of Controlled Trials databases were searched from inception to June 2018, using relevant search keywords and Medical Subject Headings (MeSH) terms, including tumor vaccine, cellular immunotherapy, immune checkpoint inhibitor, cytotoxic T-lymphocyte-associated protein 4, programmed death-ligand 1, programmed death receptor 1, and non-small cell lung carcinoma. Systematic reviews, meta-analyses, references, and conference proceedings were manually searched.

Study selection: English-language randomized clinical trials with available data that measured overall survival (OS), progression-free survival (PFS), or objective response rate comparing immune checkpoint inhibitors, tumor vaccines, or cellular immunotherapy with conventional therapy for patients with advanced or metastatic NSCLC were included. Thirty-one immunotherapy randomized clinical trials were included, and multicohort data included next-generation sequencing data from patients with advanced NCSLC.

Data extraction and synthesis: Hazard ratios and 95% CIs were pooled to estimate the survival increases in OS and PFS. Dichotomous data, such as object response rate data, were analyzed using the risk ratio. Mantel-Haenszel random-effects model was used. I2 was used to assess the heterogeneity between trials; an I2 value exceeding 50% indicated the existence of substantial heterogeneity. Analyses took place from February 1, 2018, to August 31, 2018.

Main outcomes and measures: Primary outcomes were OS and PFS.

Results: In total, 14 395 patients (9500 [66.0%] men) were included in the meta-analysis, and 1833 patients (mean [SD], 65.2 [9.9] years; 1063 [58.0%] men) were included in the individual patient-level study. Compared with conventional therapy, immunotherapy was associated with significantly longer OS (hazard ratio, 0.76; 95% CI, 0.71-0.82; P < .001) and PFS (hazard ratio, 0.76; 95% CI, 0.70-0.83; P < .001). The best checkpoint blockade strategy was first-line pembrolizumab with platinum-based chemotherapy. The combined predictive utility of programmed cell death ligand 1 (PD-L1) expression and tumor mutation burden (TMB) was associated with predictive prognosis (whole-exome sequencing: 1-year PFS area under the receiver operating characteristic curve [AUC], 0.829; 3-year PFS AUC, 0.839; targeted next-generation sequencing: 1-year PFS AUC, 0.826; 3-year PFS AUC, 0.948). Moreover, the addition of CD8+ T-cell tumor-infiltrating lymphocytes was associated with improved prognosis predictions for OS (3-year OS AUC, 0.659; 5-year OS AUC, 0.665). RYR1 or MGAM mutations were significantly associated with concomitantly increased durable clinical benefits (RYR1: durable clinical benefit [DCB], 12 of 51 patients [24%]; no durable benefit [NDB], 2 of 55 patients [4%]; P < .001; MGAM: DCB, 12 of 51 patients [24%]; NDB, 0 patients; P < .001), a higher TMB (RYRI: high TMB, 12 of 53 patients [23%]; low TMB, 2 of 53 patients [38%]; P < .001; MGAM: high TMB, 9 of 53 patients [17%]; low TMB, 0 patients; P < .001), and higher PD-L1 expression (RYRI: high PD-L1 expression, 8 of 30 patients [27%]; low PD-L1 expression, 6 of 85 [7.1%]; P < .001; MGAM: high PD-L1 expression, 6 of 30 patients [20%]; low PD-L1 expression, 5 of 85 patients [6%]; P < .001).

Conclusions and relevance: Immunotherapies showed promising clinical outcomes for patients with NSCLC. Pembrolizumab with platinum-based chemotherapy was found to be the most appropriate first-line immune checkpoint inhibitor regimen for advanced NSCLC, and the combined use of PD-L1 expression and TMB was found to be a promising biomarker to evaluate patients' survival and response to precision immunotherapy. The further combination of CD8+ T-cell tumor-infiltrating lymphocytes, PD-L1 expression, and TMB was associated with reliable prognosis. The predictive value of that combination needs to be prospectively validated in large-scale studies.

Figure 1.. Pooled Hazard Ratios (HRs) for Overall Survival With Immunotherapy vs Conventional Therapy

Size of boxes indicates proportional weight of each trial. Diamonds indicate point estimates and 95% CIs of the combined result. ^aPatients were treated by phased regimen. ^bPatients were treated by concurrent regimen.

Figure 2.. Survival Analysis of Patients Stratified by Programmed Cell Death Ligand 1 (PD-L1) Expression or Tumor Mutation Burden (TMB)

A, Progression-free survival curves were plotted for patients stratified by PD-L1 expression in cohort 1. B, Overall survival curves were plotted for patients stratified by PD-L1 expression in the OAK trial. C, Progression-free survival curves were plotted for patients stratified by tumor mutation burden in cohort 1. D, Overall survival curves were plotted for patients stratified by tumor mutation burden in cohort 2. Crosses indicate censoring of data. HR indicates hazard ratio.

Figure 3.. Joint Association of Programmed Cell Death Ligand 1 (PD-L1) Expression and Tumor Mutation Burden (TMB) With Survival in Checkpoint Blockade

A and B, Patient tumor tissues were quantified by whole-exome sequencing (WES) and receiver operating characteristic curves were plotted for sensitivity vs 1 − specificity of 1-year progression-free survival (A) and 3-year progression-free survival (B). C and D, Patient tumor tissues were quantified by Memorial Sloan Kettering–Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) sequencing and receiver operating characteristic curves were plotted for sensitivity vs 1 − specificity of 1-year progression-free survival (C) and 3-year progression-free survival (D). AUC indicates area under the receiver operating characteristic curve.

Figure 4.. Landscape of the Immune Cells in Non–Small Cell Lung Cancer

A, Cellular interaction of immune cell types. B, The heatmap representation of the unsupervised clustering of immune cells. EGFR indicates epidermal growth factor receptor; KRAS, Kirsten rat sarcoma viral oncogene homologue; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; NK, natural killer; and TMB, tumor mutation burden.

Figure 5.. Individual Gene Alterations Associated With Response and Molecular Features in Checkpoint Blockade

LUAD indicates lung adenocarcinoma; LUSC, lung squamous cell carcinoma; PD-L1, programmed cell death ligand 1; PFS, progression-free survival; SNV, single-nucleotide variants; and TMB, tumor mutation burden.