Tumor Mutation Burden and Efficacy of EGFR-Tyrosine Kinase Inhibitors in Patients with EGFR-Mutant Lung Cancers

Abstract

Purpose: Tumor mutation burden (TMB) is a biomarker of response to immune checkpoint blockade (ICB). The impact of TMB on outcomes with targeted therapies has not been explored.

Experimental design: We identified all patients with metastatic EGFR exon19del or L858R-mutant lung cancers treated with first/second-generation EGFR tyrosine kinase inhibitors (TKIs) with pretreatment next-generation sequencing data (MSK-IMPACT assay). The effect of TMB on time-to-treatment discontinuation (TTD) and overall survival (OS) were evaluated in univariate and multivariate analyses. EGFR wild-type lung adenocarcinoma samples were used for comparison.

Results: Among 153 patients with EGFR-mutant lung cancer, TMB was lower compared with EGFR wild-type (n = 1,849; median 3.77 vs. 6.12 mutations/Mb; P < 0.0001) with a broad range (0.82-17.9 mutations/Mb). Patients with EGFR-mutant lung cancer whose tumors had TMB in the high tertile had shorter TTD (HR, 0.46; P = 0.0008) and OS (HR, 0.40; P = 0.006) compared with patients with low/intermediate TMB. Evaluating by median TMB, there was significantly shorter TTD and OS for patients with higher TMB (TTD, P = 0.006; OS, P = 0.03). In multivariate analysis, TTD and OS remained significantly longer in the low/intermediate tertile compared with high TMB (HR = 0.57, P = 0.01; HR = 0.50, P = 0.02, respectively). In paired pretreatment and postprogression samples, TMB was increased at resistance (median 3.42 vs. 6.56 mutations/Mb; P = 0.008).

Conclusions: TMB is negatively associated with clinical outcomes in metastatic patients with EGFR-mutant lung cancer treated with EGFR-TKI. This relationship contrasts with that seen in lung cancers treated with immunotherapy.See related commentary by Cheng and Oxnard, p. 899.

Conflict of interest statement

Conflict of Interest Statement:

Michael Offin, Hira Rizvi, Megan Tenet, Andy Ni, Francisco Sanchez-Vega, and Nikolaus Schultz have no disclosures to report.

Mark Kris is a consultant for Ariad, AstraZeneca and Genentech Roche and received research funding from Genentech Roche and Puma Biotechnology.

Bob Li is a consultant for Genentech Roche, Thermo Fischer Scientific and Guardant Health.

Alexander Drilon is a consultant for Ignyta, Loxo, TP Therapeutics, AstraZeneca, Pfizer, Blueprint Medicines, Genentech Roche, Takeda, and has received research funding from Foundation Medicine.

Mark G. Kris is a consultant for Genetech Roche, AstraZeneca, and ARIAD.

Charles Rudin is a consultant for Bristol-Myers Squibb, Abbvie, Seattle Genetics, Harpoon Therapeutics, Genentech Roche, and AstraZeneca.

Maria Arcila received speaker’s fees from Raindance Technologies.

Marc Ladanyi is a consultant for NCCN/ Boehringer-Ingelheim Afatinib Targeted Therapy, is on the advisory committee for Foundation Medicine, and has research grant support from LOXO Pharmaceuticals.

Gregory Riely is a consultant for Genentech Roche, received travel funding from Merck Sharp and Dohme, and research funding from Novartis, Genentech Roche, Millennium, GlaxoSmithKline, Pfizer, Infinity Pharmaceuticals, and Ariad.

Helena Yu is a consultant for AstraZeneca, Boehringer Ingelheim, Lilly and has received research funding from Astellas Pharma, AstraZeneca, Clovis Oncology, Incyte and Lilly.

Matthew Hellman is a consultant for Bristol-Myers Squibb, Merck, Genentech Roche AstraZeneca and MedImmune, Novartis and Janssen, and received research funding from Bristol-Myers Squibb.

©2018 American Association for Cancer Research.

Figures

Figure 1:

A: Evaluation of EGFR-mutant (n=153) versus EGFR wild-type (n=1849) lung cancer patients. The horizontal line indicates the median and brackets the TMB inter-tertile range (tertiles: EGFR-mutant ≤ 2.83, 2.84 – 4.85, > 4.85 mutations/Mb; EGFR wild-type ≤ 4.08, 4.09 – 8.49, > 8.49 mutations/Mb). The median TMB for EGFR-mutant patients was 3.77 versus 6.12 mutations/Mb in EGFR wild-type patients (Mann Whitney p < 0.0001); B: TMB in the ever-smoker group (n = 58) was similar to the never-smoker group (n=95) (median 4.08 vs 3.77 mutations/Mb, Mann Whitney p = 0.184). TMB of patients with L858R (n = 59) was higher compared to exon 19 deletion (median 4.72 vs median 3.17 mutations/Mb, Mann Whitney p = 0.003); C: Oncoprint for patients by TMB tertile; D. Time to treatment discontinuation (TTD) evaluated by TMB: (lowest tertile: 16.7 months, intermediate: 16.0 months, high: 9.6 months; Log-rank for trend p=0.002). When evaluated by low/intermediate versus high TMB, the median TTD was 16.7 and 9.6 months respectively (HR 0.46, 95% CI 0.29–0.72, Log-rank p=0.0008); E. OS was significantly different when evaluated by tertiles (median OS of low TMB: 40.6 months, intermediate: 37.3 months, high: 20.6 months; Log-rank for trend p=0.02).

Figure 2:

A: Hazard ratio (Mantel-Haenszel method) and p-value (Log-rank) for subgroups evaluating time to treatment discontinuation (TTD) stratified by low/intermediate versus high TMB. The low/intermediate TMBs for each subgroup analyzed were: TP53-mutant ≤ 5.66, TP53 wild-type ≤ 4.30, ever-smokers ≤ 6.60, never-smoker ≤ 4.72, EGFR L858R ≤ 5.66, EGFR ex19del ≤ 4.10 mutations/Mb. HR for TTD in each cohort were found to be: TP53-mutant 0.49 (95% CI 0.27–0.90, p=0.02), TP53 wild-type 0.75 (95% CI 0.37–1.53, p=0.43), ever-smokers 0.90 (95% CI 0.43–1.88, p=0.78), never-smoker 0.41 (95% CI 0.21–0.78, p=0.006), EGFR L858R 0.33 (95% CI 0.16–0.69, p=0.003), EGFR ex19del 0.81 (95% CI 0.44–1.48, p=0.49); B: HR for OS in each cohort were found to be: TP53-mutant 0.38 (95% CI 0.17–0.88, p=0.02), TP53 wild-type 1.42 (95% CI 0.48–4.23, p=0.52), ever-smokers 0.64 (95% CI 0.22–1.87, p=0.42), never-smoker 0.33 (95% CI 0.13–0.85, p=0.02), EGFR L858R 0.42 (95% CI 0.16–1.12, p=0.08), EGFR ex19del 0.69 (95% CI 0.27–1.76, p=0.43); C and D: Multivariate Cox proportional hazard ratio analysis for TTD and OS examining TMB (low/intermediate vs high TMB), TP53 status, and EGFR-allele.

Figure 3:

A: In 30 patients who underwent next generation sequencing at EGFR-TKI resistance with MSK-IMPACT, TMB was increased on the post-EGFR-TKI sample (median 3.42 pre-TKI vs 6.56 mutation/Mb at resistance, Wilcoxon test p=0.0002). Paired samples are linked by gray lines; B: 84 patients underwent EGFR T790M testing at the time of resistance to first/second-generation EGFR-TKI and 45 were found to have acquired a T790M mutation. The median TMB from the pre-EGFR-TKI sample of those that acquired T790M at resistance versus those that did not was 3.77 versus 4.72 mutations/Mb respectively (Mann Whitney p=0.057).