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Cited by 150Cancer Immunotherapy and BiomarkersInflammatory Biomarkers in Disease PrognosisImmune cells in cancer

Peripheral blood immune cell dynamics reflect antitumor immune responses and predict clinical response to immunotherapy

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Hwang, Michael, Canzoniero, Jenna Vanliere, Rosner, Samuel, Zhang, Guangfan, White, James R, Belcaid, Zineb, Cherry, Christopher, Balan, Archana +19 more·2022·Journal for ImmunoTherapy of Cancer
DOI 10.1136/jitc-2022-004688PMC PMC9189831
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Abstract

BACKGROUND: Despite treatment advancements with immunotherapy, our understanding of response relies on tissue-based, static tumor features such as tumor mutation burden (TMB) and programmed death-ligand 1 (PD-L1) expression. These approaches are limited in capturing the plasticity of tumor-immune system interactions under selective pressure of immune checkpoint blockade and predicting therapeutic response and long-term outcomes. Here, we investigate the relationship between serial assessment of peripheral blood cell counts and tumor burden dynamics in the context of an evolving tumor ecosystem during immune checkpoint blockade. METHODS: Using machine learning, we integrated dynamics in peripheral blood immune cell subsets, including neutrophil-lymphocyte ratio (NLR), from 239 patients with metastatic non-small cell lung cancer (NSCLC) and predicted clinical outcome with immune checkpoint blockade. We then sought to interpret NLR dynamics in the context of transcriptomic and T cell repertoire trajectories for 26 patients with early stage NSCLC who received neoadjuvant immune checkpoint blockade. We further determined the relationship between NLR dynamics, pathologic response and circulating tumor DNA (ctDNA) clearance. RESULTS: Integrated dynamics of peripheral blood cell counts, predominantly NLR dynamics and changes in eosinophil levels, predicted clinical outcome, outperforming both TMB and PD-L1 expression. As early changes in NLR were a key predictor of response, we linked NLR dynamics with serial RNA sequencing deconvolution and T cell receptor sequencing to investigate differential tumor microenvironment reshaping during therapy for patients with reduction in peripheral NLR. Reductions in NLR were associated with induction of interferon-γ responses driving the expression of antigen presentation and proinflammatory gene sets coupled with reshaping of the intratumoral T cell repertoire. In addition, NLR dynamics reflected tumor regression assessed by pathological responses and complemented ctDNA kinetics in predicting long-term outcome. Elevated peripheral eosinophil levels during immune checkpoint blockade were correlated with therapeutic response in both metastatic and early stage cohorts. CONCLUSIONS: Our findings suggest that early dynamics in peripheral blood immune cell subsets reflect changes in the tumor microenvironment and capture antitumor immune responses, ultimately reflecting clinical outcomes with immune checkpoint blockade.

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  • ICRs have been repeatedly proposed as solid prognostic markers for various additional conditions including low-grade inflammation, rheumatic diseases, sepsis, myocarditis, thrombosis, ischemic and cardiovascular events, autoimmune and systemic diseases, cancer incidence, progression, response and outcome, COVID-19 severity and prognosis, critical illness, and overall mortality.

    “Since then, IRCs have been repeatedly proposed as solid prognostic markers for various additional conditions including low-grade inflammation, rheumatic diseases, sepsis, myocarditis, thrombosis, ischemic and cardiovascular events, autoimmune and systemic diseases, cancer incidence, progression, response and outcome, COVID-19 severity and prognosis, critical illness, and overall mortality [26,27,2”

    From Immune Cell Ratios Are Higher in Bipolar Affective than Unipolar Depressive Disorder and Modulated by Mood Episode: A Retrospective, Cross-Sectional Study (2023) · cites this paper as [33]

    The Background describes the neutrophil–lymphocyte ratio (NLR) as a prognostic or predictive biomarker in lung cancer. The Results section on pathologic response to immunotherapy links NLR changes to tumor regression and recurrence-free survival in patients with non-small cell lung cancer. The paper does not support the sentence’s broader list of conditions, cancer incidence, or overall mortality across populations. Page numbers are unavailable in our copy. (LLM, conf=0.88)

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  1. [1]Onoi K, Chihara Y, Uchino J, et al. Immune checkpoint inhibitors for lung cancer treatment: a review. J Clin Med 2020; 9: 1362. 10.3390/jcm9051362 PMC7290914 32384677 · DOI
  2. [2]Assi HI, Kamphorst AO, Moukalled NM, et al. Immune checkpoint inhibitors in advanced non-small cell lung cancer. Cancer 2018; 124: 248– 61. 10.1002/cncr.31105 29211297 · DOI
  3. [4]Doroshow DB, Sanmamed MF, Hastings K, et al. Immunotherapy in non-small cell lung cancer: facts and hopes. Clin Cancer Res 2019; 25: 4592– 602. 10.1158/1078-0432.CCR-18-1538 30824587 PMC6679805 · DOI
  4. [5]Anagnostou V, Niknafs N, Marrone K, et al. Multimodal genomic features predict outcome of immune checkpoint blockade in non-small-cell lung cancer. Nat Cancer 2020; 1: 99– 111. 10.1038/s43018-019-0008-8 32984843 PMC7514475 · DOI
  5. [6]Anagnostou V, Bruhm DC, Niknafs N, et al. Integrative tumor and immune cell multi-omic analyses predict response to immune checkpoint blockade in melanoma. Cell Rep Med 2020; 1: 100139. 10.1016/j.xcrm.2020.100139 33294860 PMC7691441 · DOI
  6. [7]Chen P-L, Roh W, Reuben A, et al. Analysis of immune signatures in longitudinal tumor samples yields insight into biomarkers of response and mechanisms of resistance to immune checkpoint blockade. Cancer Discov 2016; 6: 827– 37. 10.1158/2159-8290.CD-15-1545 27301722 PMC5082984 · DOI · Paper page
  7. [9]Cristescu R, Mogg R, Ayers M, et al. Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. Science 2018; 362: eaar3593. 10.1126/science.aar3593 30309915 PMC6718162 · DOI · Paper page
  8. [10]Litchfield K, Reading JL, Puttick C, et al. Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition. Cell 2021; 184: 596– 614. 10.1016/j.cell.2021.01.002 33508232 PMC7933824 · DOI · Paper page
  9. [11]Anagnostou V, Forde PM, White JR, et al. Dynamics of tumor and immune responses during immune checkpoint blockade in non-small cell lung cancer. Cancer Res 2019; 79: 1214– 25. 10.1158/0008-5472.CAN-18-1127 30541742 PMC6432636 · DOI
  10. [12]Wang H, Zhou F, Qiao M, et al. The role of circulating tumor DNA in advanced non-small cell lung cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis. Front Oncol 2021; 11: 671874. 10.3389/fonc.2021.671874 34367957 PMC8335591 · DOI
  11. [13]Moschetta M, Uccello M, Kasenda B, et al. Dynamics of neutrophils-to-lymphocyte ratio predict outcomes of PD-1/PD-L1 blockade. Biomed Res Int 2017; 2017: 1506824. 10.1155/2017/1506824 29318140 PMC5727693 · DOI
  12. [14]Passiglia F, Galvano A, Castiglia M, et al. Monitoring blood biomarkers to predict nivolumab effectiveness in NSCLC patients. Ther Adv Med Oncol 2019; 11: 1758835919839928. 10.1177/1758835919839928 31019571 PMC6469277 · DOI
  13. [15]Coffelt SB, Wellenstein MD, de Visser KE. Neutrophils in cancer: neutral no more. Nat Rev Cancer 2016; 16: 431– 46. 10.1038/nrc.2016.52 27282249 · DOI · Paper page
  14. [16]Cedrés S, Torrejon D, Martínez A, et al. Neutrophil to lymphocyte ratio (NLR) as an indicator of poor prognosis in stage IV non-small cell lung cancer. Clin Transl Oncol 2012; 14: 864– 9. 10.1007/s12094-012-0872-5 22855161 · DOI
  15. [17]Scilla KA, Bentzen SM, Lam VK, et al. Neutrophil-lymphocyte ratio is a prognostic marker in patients with locally advanced (stage IIIA and IIIB) non-small cell lung cancer treated with combined modality therapy. Oncologist 2017; 22: 737– 42. 10.1634/theoncologist.2016-0443 28533476 PMC5469587 · DOI
  16. [18]Ameratunga M, Chénard-Poirier M, Moreno Candilejo I, et al. Neutrophil-lymphocyte ratio kinetics in patients with advanced solid tumours on phase I trials of PD-1/PD-L1 inhibitors. Eur J Cancer 2018; 89: 56– 63. 10.1016/j.ejca.2017.11.012 29227818 · DOI
  17. [19]Cao D, Xu H, Xu X, et al. A reliable and feasible way to predict the benefits of nivolumab in patients with non-small cell lung cancer: a pooled analysis of 14 retrospective studies. Oncoimmunology 2018; 7: e1507262. 10.1080/2162402X.2018.1507262 30377569 PMC6205035 · DOI
  18. [21]Nakaya A, Kurata T, Yoshioka H, et al. Neutrophil-to-lymphocyte ratio as an early marker of outcomes in patients with advanced non-small-cell lung cancer treated with nivolumab. Int J Clin Oncol 2018; 23: 634– 40. 10.1007/s10147-018-1250-2 29442281 PMC6097082 · DOI
  19. [23]Reuss JE, Smith KN, Anagnostou V, et al. Neoadjuvant nivolumab in resectable non-small cell lung cancer: extended follow-up and molecular markers of response. JCO 2019; 37: 8524. 10.1200/JCO.2019.37.15_suppl.8524 · DOI
  20. [24]Reuss JE, Anagnostou V, Cottrell TR, et al. Neoadjuvant nivolumab plus ipilimumab in resectable non-small cell lung cancer. J Immunother Cancer 2020; 8. 10.1136/jitc-2020-001282 PMC7488786 32929052 · DOI
  21. [27]Lundberg S, Lee S. A unified approach to interpreting model predictions. arXiv cs 2017.
  22. [28]Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014; 15: 550. 10.1186/s13059-014-0550-8 25516281 PMC4302049 · DOI · Paper page
  23. [30]Korotkevich G, Sukhov V, Budin N. Fast gene set enrichment analysis. bioRxiv 2021: 060012 http://biorxiv.org/content/early/2021/02/01/060012.abstract
  24. [31]Zhang J, Ji Z, Caushi JX, et al. Compartmental analysis of T-cell clonal dynamics as a function of pathologic response to neoadjuvant PD-1 blockade in resectable non-small cell lung cancer. Clin Cancer Res 2020; 26: 1327– 37. 10.1158/1078-0432.CCR-19-2931 31754049 PMC7073288 · DOI
  25. [32]Phallen J, Sausen M, Adleff V, et al. Direct detection of early-stage cancers using circulating tumor DNA. Sci Transl Med 2017; 9: 2415. 10.1126/scitranslmed.aan2415 PMC6714979 28814544 · DOI
  26. [34]Gonzalez H, Hagerling C, Werb Z. Roles of the immune system in cancer: from tumor initiation to metastatic progression. Genes Dev 2018; 32: 1267– 84. 10.1101/gad.314617.118 30275043 PMC6169832 · DOI · Paper page
  27. [35]Casey SC, Baylot V, Felsher DW. The MYC oncogene is a global regulator of the immune response. Blood 2018; 131: 2007– 15. 10.1182/blood-2017-11-742577 29514782 PMC5934797 · DOI
  28. [36]Anagnostou V, Yarchoan M, Hansen AR, et al. Immuno-oncology trial endpoints: capturing clinically meaningful activity. Clin Cancer Res 2017; 23: 4959– 69. 10.1158/1078-0432.CCR-16-3065 28864724 PMC5735844 · DOI
  29. [37]Schalper KA, Carleton M, Zhou M, et al. Elevated serum interleukin-8 is associated with enhanced intratumor neutrophils and reduced clinical benefit of immune-checkpoint inhibitors. Nat Med 2020; 26: 688– 92. 10.1038/s41591-020-0856-x 32405062 PMC8127102 · DOI
  30. [38]Szczerba BM, Castro-Giner F, Vetter M, et al. Neutrophils escort circulating tumour cells to enable cell cycle progression. Nature 2019; 566: 553– 7. 10.1038/s41586-019-0915-y 30728496 · DOI
  31. [39]Gooden MJM, de Bock GH, Leffers N, et al. The prognostic influence of tumour-infiltrating lymphocytes in cancer: a systematic review with meta-analysis. Br J Cancer 2011; 105: 93– 103. 10.1038/bjc.2011.189 21629244 PMC3137407 · DOI
  32. [41]Takahashi A, Kono K, Amemiya H, et al. Elevated caspase-3 activity in peripheral blood T cells coexists with increased degree of T-cell apoptosis and down-regulation of TCR zeta molecules in patients with gastric cancer. Clin Cancer Res 2001; 7: 74– 80. 11205921
  33. [42]Kim R, Emi M, Tanabe K, et al. The role of fas ligand and transforming growth factor beta in tumor progression: molecular mechanisms of immune privilege via fas-mediated apoptosis and potential targets for cancer therapy. Cancer 2004; 100: 2281– 91. 10.1002/cncr.20270 15160330 · DOI
  34. [43]Zhao J, Huang W, Wu Y, et al. Prognostic role of pretreatment blood lymphocyte count in patients with solid tumors: a systematic review and meta-analysis. Cancer Cell Int 2020; 20: 15. 10.1186/s12935-020-1094-5 31938023 PMC6954501 · DOI
  35. [44]Simon SCS, Hu X, Panten J, et al. Eosinophil accumulation predicts response to melanoma treatment with immune checkpoint inhibitors. Oncoimmunology 2020; 9: 1727116. 10.1080/2162402X.2020.1727116 32117594 PMC7028332 · DOI
  36. [46]Varricchi G, Bagnasco D, Borriello F, et al. Interleukin-5 pathway inhibition in the treatment of eosinophilic respiratory disorders: evidence and unmet needs. Curr Opin Allergy Clin Immunol 2016; 16: 186– 200. 10.1097/ACI.0000000000000251 26859368 PMC4768650 · DOI
  37. [47]Reichman H, Itan M, Rozenberg P, et al. Activated eosinophils exert antitumorigenic activities in colorectal cancer. Cancer Immunol Res 2019; 7: 388– 400. 10.1158/2326-6066.CIR-18-0494 30665890 · DOI
  38. [48]Carretero R, Sektioglu IM, Garbi N, et al. Eosinophils orchestrate cancer rejection by normalizing tumor vessels and enhancing infiltration of CD8(+) T cells. Nat Immunol 2015; 16: 609– 17. 10.1038/ni.3159 25915731 · DOI · Paper page
  39. [49]Li H, Xiao Y, Li Q. The allergy mediator histamine confers resistance to immunotherapy in cancer patients via activation of the macrophage histamine receptor H1. Cancer Cell. PMC8779329 34822775
  40. [50]Galdiero MR, Varricchi G, Seaf M, et al. Bidirectional mast cell-eosinophil interactions in inflammatory disorders and cancer. Front Med 2017; 4: 103. 10.3389/fmed.2017.00103 PMC5523083 28791287 · DOI

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Authors
Hwang, M., Canzoniero, J. V., Rosner, S., Zhang, G., White, J. R., Belcaid, Z., Cherry, C., Balan, A., Pereira, G., Curry, A., Niknafs, N., Zhang, J., Smith, K. N., Sivapalan, L., Chaft, J. E., Reuss, J. E., Marrone, K., Murray, J. C., Li, Q. K., Lam, V., Levy, B. P., Hann, C., Velculescu, V. E., Brahmer, J. R., Forde, P. M., Seiwert, T., & Anagnostou, V.
Affiliations
  • Johns Hopkins University (US)
  • Memorial Sloan Kettering Cancer Center (US)
  • Georgetown Lombardi Comprehensive Cancer Center (US)
Corresponding author
Anagnostou, Valsamo
ORCID
Venue
Journal for ImmunoTherapy of Cancer
Publisher
BMJ
Published
2022-06
Volume
10
Issue
6
Pages
e004688
ISSN
2051-1426 (ISSN-L)
DOI
10.1136/jitc-2022-004688
PMC
PMC9189831
OpenAlex
W4281733207
Cited by
150
References
10
Citations by year
2026: 32 · 2025: 41 · 2024: 47 · 2023: 29 · 2022: 1
FWCI
12.35
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal for ImmunoTherapy of Cancer (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Emerson Collective
  • Johns Hopkins Research Program in Quantitative Sciences
  • Maryland Department of Health and Mental Hygiene
  • Swim Across America
  • National Institutes of Health (CA 9071-40, CA121113)
  • LUNGevity Foundation
  • V Foundation for Cancer Research
  • Pearl M. Stetler Research Fund
  • ECOG-ACRIN Thoracic Malignancies Integrated Translational Science Center (UG1CA233259)
  • Bristol-Myers Squibb (International Immuno-Oncology Network)
  • Bloomberg-Kimmel Institute for Cancer Immunotherapy
Topics
  • Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
  • Health Sciences › Medicine › Oncology › Inflammatory Biomarkers in Disease Prognosis
  • Life Sciences › Immunology and Microbiology › Immunology › Immune cells in cancer
Keywords
immune checkpoint blockade, non-small cell lung cancer, neutrophil-to-lymphocyte ratio, circulating tumor DNA, tumor microenvironment, T cell receptor repertoire, interferon-gamma, eosinophils, neoadjuvant immunotherapy, treatment response prediction, tumor regression, tumor mutational burden, PD-L1 expression
MeSH terms
Circulating Tumor DNA, Immune Checkpoint Inhibitors, Carcinoma, Non-Small-Cell Lung, Humans, Immunity, Immunologic Factors, Immunotherapy, Lung Neoplasms, Biomarkers, Tumor, Ecosystem, Tumor Microenvironment, B7-H1 Antigen

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