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. 2021 Feb 1;12(1):729.
doi: 10.1038/s41467-021-20935-9.

Pretreatment neutrophil-to-lymphocyte ratio and mutational burden as biomarkers of tumor response to immune checkpoint inhibitors

Cristina Valero  1   2   3 , Mark Lee  2   3 , Douglas Hoen  2   3 , Kate Weiss  2   3 , Daniel W Kelly  4 , Prasad S Adusumilli  1 , Paul K Paik  5 , George Plitas  1 , Marc Ladanyi  6 , Michael A Postow  5 , Charlotte E Ariyan  1 , Alexander N Shoushtari  5 , Vinod P Balachandran  1 , A Ari Hakimi  1   2   3 , Aimee M Crago  1 , Kara C Long Roche  1 , J Joshua Smith  1 , Ian Ganly  1   2   3 , Richard J Wong  1 , Snehal G Patel  1 , Jatin P Shah  1 , Nancy Y Lee  7 , Nadeem Riaz  2   3   7 , Jingming Wang  2   3 , Ahmet Zehir  6 , Michael F Berger  6 , Timothy A Chan  8   9   10 , Venkatraman E Seshan  11 , Luc G T Morris  12   13   14
Affiliations

Pretreatment neutrophil-to-lymphocyte ratio and mutational burden as biomarkers of tumor response to immune checkpoint inhibitors

Cristina Valero et al. Nat Commun. .

Abstract

Treatment with immune checkpoint inhibitors (ICI) has demonstrated clinical benefit for a wide range of cancer types. Because only a subset of patients experience clinical benefit, there is a strong need for biomarkers that are easily accessible across diverse practice settings. Here, in a retrospective cohort study of 1714 patients with 16 different cancer types treated with ICI, we show that higher neutrophil-to-lymphocyte ratio (NLR) is significantly associated with poorer overall and progression-free survival, and lower rates of response and clinical benefit, after ICI therapy across multiple cancer types. Combining NLR with tumor mutational burden (TMB), the probability of benefit from ICI is significantly higher (OR = 3.22; 95% CI, 2.26-4.58; P < 0.001) in the NLR low/TMB high group compared to the NLR high/TMB low group. NLR is a suitable candidate for a cost-effective and widely accessible biomarker, and can be combined with TMB for additional predictive capacity.

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Conflict of interest statement

D.H. receives funding from AstraZeneca. M.A.P. reports consulting fees from BMS, Merck, Array BioPharma, Novartis, Incyte, NewLink Genetics, and Aduro, honoraria from BMS and Merck, and research support from RGenix, Infinity, BMS, Merck, Array BioPharma, Novartis, and AstraZeneca. A.N.S. reports advisory board position with BMS, Immunocore, and Castle Biosciences, and institutional research support from BMS, Immunocore, and Xcovery. V.P.B. is a recipient of an immuno-oncology translational research grant from Bristol-Myers Squibb and is an inventor on a patent application related to work on neoantigen modeling. A.M.C. reports advisory board position with Springworks Therapeutics. J.J.S. has received travel support from Intuitive Surgical, Inc. for fellow education and has served as a clinical advisor to Guardant Health, Inc. S.G.P. has a patent PCT/US2016/026717 Methods of Cancer Detection Using PARPI-FL pending, holds equity in Summit Biomedical Imaging, has a patent US 10,016,238B2 Apparatus, system and method for providing laser steering and focusing for incision, excision, and ablation of tissue in minimally invasive surgery, and holds equity in ColdSteel Laser, Inc. N.R. reports research support from Pfizer and BMS, and consulting fees from REPARE Therapeutics, Mirati Therapeutics, and Illumina. A.Z. reports honoraria from Illumina. T.A.C. acknowledges grant funding from Bristol-Myers Squibb, AstraZeneca, Illumina, Pfizer, An2H, and Eisai, has served as an advisor for Bristol-Myers Squibb, Illumina, Eisai, and An2H, holds equity in An2H, and is a co-founder of Gritstone Oncology and holds equity. T.A.C. and L.G.T.M. are inventors on a patent held by Memorial Sloan Kettering related to the use of TMB in cancer immunotherapy. L.G.T.M. reports laboratory research funding from AstraZeneca. All remaining authors have declared no conflicts of interest.

Figures

Fig. 1
Fig. 1. Pan-cancer outcomes based on neutrophil-to-lymphocyte ratio (NLR).
a Overall survival, b progression-free survival, c response, and d clinical benefit at a pan-cancer level based on high vs. low NLR. The cutoff was the top 20th percentile within each cancer type. P-values are according to log-rank test for a and b, and Pearson’s χ2-test for c and d.
Fig. 2
Fig. 2. Outcomes based on neutrophil-to-lymphocyte ratio (NLR) stratified by cancer type.
Forest plots showing hazard ratios (HRs) with 95% CIs for a overall survival and b progression-free survival across cancer types, comparing top 20th NLR percentile within each cancer type to bottom 80th. HRs were calculated with Cox proportional hazard regression. Abreviations: OS, overall survival; Haz. Ratio, hazard ratio; CI, confidence interval; NSCLC, non-small cell lung cancer; SCLC, small cell lung cancer; PFS, progression-free survival.
Fig. 3
Fig. 3. Pan-cancer outcomes according to a combined neutrophil-to-lymphocyte ratio (NLR) and tumor mutational burden (TMB) categorization.
a Overall survival, b progression-free survival, c response, and d clinical benefit at a pan-cancer level. Patients were classified into four categories based on NLR low/high and TMB low/high, using median within cancer type as cutoff for both variables. P-values are according to log-rank test for a and b, and Pearson’s χ2-test for c and d.
Fig. 4
Fig. 4. Outcomes across quartile-based categories of neutrophil-to-lymphocyte ratio (NLR) and tumor mutational burden (TMB).
Heat maps of hazard ratios (HRs) for a overall survival and b progression-free survival, and heat maps of odds ratios (ORs) for c response and d clinical benefit based on 16 within cancer type quartile-based categories of NLR and TMB. HRs were calculated with Cox proportional hazard regression. ORs were calculated with logistic regression.
See this image and copyright information in PMC

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