Clinical and molecular parameters associated to pneumonitis development in non-small-cell lung cancer patients receiving chemoimmunotherapy from NADIM trial

Belén Sierra-Rodero, Alberto Cruz-Bermúdez, Ernest Nadal, Yago Garitaonaindía, Amelia Insa, Joaquín Mosquera, Joaquín Casal-Rubio, Manuel Dómine, Margarita Majem, Delvys Rodriguez-Abreu, Alex Martinez-Marti, Javier De Castro Carpeño, Manuel Cobo, Guillermo López Vivanco, Edel Del Barco, Reyes Bernabé Caro, Nuria Viñolas, Isidoro Barneto Aranda, Santiago Viteri, Bartomeu Massuti, Raquel Laza-Briviesca, Marta Casarrubios, Aránzazu García-Grande, Atocha Romero, Fernando Franco, Mariano Provencio, Belén Sierra-Rodero, Alberto Cruz-Bermúdez, Ernest Nadal, Yago Garitaonaindía, Amelia Insa, Joaquín Mosquera, Joaquín Casal-Rubio, Manuel Dómine, Margarita Majem, Delvys Rodriguez-Abreu, Alex Martinez-Marti, Javier De Castro Carpeño, Manuel Cobo, Guillermo López Vivanco, Edel Del Barco, Reyes Bernabé Caro, Nuria Viñolas, Isidoro Barneto Aranda, Santiago Viteri, Bartomeu Massuti, Raquel Laza-Briviesca, Marta Casarrubios, Aránzazu García-Grande, Atocha Romero, Fernando Franco, Mariano Provencio

Abstract

Background: Pneumonitis (Pn) is one of the main immune-related adverse effects, having a special importance in lung cancer, since they share affected tissue. Despite its clinical relevance, Pn development remains an unpredictable treatment adverse effect, whose mechanisms are mainly unknown, being even more obscure when it is associated to chemoimmunotherapy.

Methods: In order to identify parameters associated to treatment related Pn, we analyzed clinical variables and molecular parameters from 46 patients with potentially resectable stage IIIA non-small-cell lung cancer treated with neoadjuvant chemoimmunotherapy included in the NADIM clinical trial (NCT03081689). Pn was defined as clinical or radiographic evidence of lung inflammation without alternative diagnoses, from treatment initiation to 180 days.

Results: Among 46 patients, 12 developed Pn (26.1%). Sex, age, smoking status, packs-year, histological subtype, clinical or pathological response, progression-free survival, overall survival and number of nivolumab cycles, were not associated to Pn development. Regarding molecular parameters at diagnosis, Pn development was not associated to programmed death ligand 1, TPS, T cell receptor repertoire parameters, or tumor mutational burden. However, patients who developed Pn had statistically significant lower blood median levels of platelet to monocyte ratio (p=0.012) and teratocarcinoma-derived growth factor 1 (p=0.013; area under the curve (AUC) 0.801), but higher median percentages of natural killers (NKs) (p=0.019; AUC 0.786), monocytes (p=0.017; AUC 0.791), MSP (p=0.006; AUC 0.838), PARN (p=0.017; AUC 0.790), and E-Cadherin (p=0.022; AUC 0.788). In addition, the immune scenario of Pn after neoadjuvant treatment involves: high levels of neutrophils and NK cells, but low levels of B and T cells in peripheral blood; increased clonality of intratumoral T cells; and elevated plasma levels of several growth factors (EGF, HGF, VEGF, ANG-1, PDGF, NGF, and NT4) and inflammatory cytokines (MIF, CCL16, neutrophil gelatinase-associated lipocalin, BMP-4, and u-PAR).

Conclusions: Although statistically underpowered, our results shed light on the possible mechanisms behind Pn development, involving innate and adaptative immunity, and open the possibility to predict patients at high risk. If confirmed, this may allow the personalization of both, the surveillance strategy and the therapeutic approaches to manage Pn in patients receiving chemoimmunotherapy.

Keywords: immune tolerance; immunotherapy; lung neoplasms; programmed cell death 1 receptor; translational medical research.

Conflict of interest statement

Competing interests: EN reports personal fees from Bristol Myers Squibb, personal fees from Merck Sharpe & Dohme, personal fees from AstraZeneca, grants and personal fees from Roche, grants and personal fees from Pfizer, personal fees from Lilly, personal fees from Amgen, personal fees from Boehringer Ingelheim, outside the submitted work; AI reports personal fees from Bristol, personal fees from BOERINGHER, personal fees from MSD, personal fees from PFIZER, personal fees from Roche, personal fees from ASTRA ZENECA, outside the submitted work; MD reports personal fees from Astra-Zeneca, personal fees from BMS, personal fees from Boehringer Ingelheim, personal fees from MSD, personal fees from Pfizer, personal fees from Roche, outside the submitted work; MM reports grants and personal fees from BMS, personal fees and non-financial support from MSD, personal fees and non-financial support from BOEHRINGER INGELHEIM, personal fees, non-financial support and other from ASTRA ZENENCA, personal fees, non-financial support and other from ROCHE, personal fees from KYOWA KYRIN, personal fees from PIERRE FABRE, outside the submitted work; DRA reports grants and personal fees from Bristol-Myers-Squibb, personal fees from GENENTECH/ROCHE, personal fees from MSD, personal fees from ASTRA ZENECA, personal fees from BOEHRINGER INGELHEIM, personal fees from Novartis, personal fees from Lilly, outside the submitted work; AM-M reports personal fees and non-financial support from Bristol-Myers Squibb, personal fees and non-financial support from F. Hoffmann La Roche AG, personal fees and non-financial support from Merck Sharp & Dohme, personal fees and non-financial support from Pfizer, personal fees and non-financial support from Boehringer Ingelheim, personal fees and non-financial support from MSD Oncology, personal fees, non-financial support and other from AstraZeneca, outside the submitted work; JDCC reports personal fees from Astra Zeneca, personal fees from Boehringer Ingelheim, personal fees from Merck Sharp and Dohme, personal fees from Hoffmann-la Roche, personal fees from Bristol-Myers Squibb, personal fees from Takeda, personal fees from Pfizer, personal fees from Novartis, outside the submitted work; EDB reports non-financial support from ROCHE, BMS, PFIZER, ASTRA-ZENECA, MERCK, during the conduct of the study; IBA reports consulting or advisory board for Bristol Myers, Takeda, Roche, Astra Zeneca, Behringer Inngelheim; SV reports personal fees and non-financial support from BMS, personal fees and non-financial support from ROCHE, personal fees from MSD, personal fees from ABBVIE, non-financial support from OSE IMMUNOTHERAPEUTICS, non-financial support from MERCK SERONO, outside the submitted work; BM reports grants and personal fees from Roche, personal fees and other from BMS, personal fees from Takeda, other from MSD, personal fees from Boehringer, other from Takeda, outside the submitted work; AT.R. reports personal fees from Boehringer Ingelheim, outside the submitted work;MP reports grants, personal fees and non-financial support from BMS, grants, personal fees and non-financial support from ROCHE, grants, personal fees and non-financial support from ASTRAZENECA, personal fees from MSD, personal fees from TAKEDA, outside the submitted work; BS-R, AC-B, YG, JM, JC-R, MCo, GLV, RB, NV, RL-B, MC, AG-G and FF declare no conflicts of interest.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
PD-L1, TMB and specific mutations. PD-L1 TPS levels (n=28; p=0.491), TMB (n=29; p=0.298) and specific mutations (n=29; p=0.127 for KEAP1; p=0.068 for ARID1A; p=1 for RB1; p=1 for HNF1A; p=0.622 for TP53 and p=0.553 for KRAS). *P<0.05; **p<0.01; ***p<0.001. n.s., not significant; PD-L1, programmed death ligand 1; TMB, tumor mutational burden.
Figure 2
Figure 2
Total blood counts and blood ratios. (A) Total blood count parameters (n=46 in pretreatment and n=45 in postneoadjuvant treatment samples; p=0.940 and p=0.063 for leucocytes; p=0.881 and p=0.041 for neutrophils; and p=0.079 and p=0.275 for monocytes; in preneoadjuvant and postneoadjuvant samples, respectively). (B) Ratios derived from hemograms (n=46 in pretreatment and n=45 in postneoadjuvant treatment samples; p=0.054 and p=0.270 for PLR, and p=0.012 and p=0.095 for PMR). *P

Figure 3

Flow cytometry immunophenotyping of peripheral…

Figure 3

Flow cytometry immunophenotyping of peripheral mononuclear cells (PMBCs). (n=29 in preneoadjuvant and postneoadjuvant…

Figure 3
Flow cytometry immunophenotyping of peripheral mononuclear cells (PMBCs). (n=29 in preneoadjuvant and postneoadjuvant treatment samples) (A) CD14+ cells (total monocytes, p=0.017 and p=0.329) and AUC curve to predict pneumonitis at baseline. (B) CD3-CD19+ (total B cells, p=0.064 and p=0.002). (C) CD3-CD56+ (total NK cells, p=0.019 and p=0.005), and positive and negative PD1 subpopulations in pretreatment samples (p=0.407 and p=0.032). (D) AUC curve of total NK and PD1—subpopulation to predict pneumonitis in pretreatment samples. *P

Figure 4

T cells immunophenotyping and TCR…

Figure 4

T cells immunophenotyping and TCR repertoire. (A) CD3+ (total T cells, n=29, p=0.064…

Figure 4
T cells immunophenotyping and TCR repertoire. (A) CD3+ (total T cells, n=29, p=0.064 in pretreatment and p=0.001 in postneoadjuvant treatment samples, respectively) and shift in CD3+ population calculated by POST-PRE differences (p=0.045). (B) T cell receptor repertoire evenness at diagnosis and postneoadjuvant treatment in both tissue (n=22; p=0.865 for pretreatment and n=38; p=0.028 for postneoadjuvant treatment) and blood (n=30; p=0.815 for pretreatment and n=35; p=0.827 for posttreatment samples). *P

Figure 5

Cytokine levels and pneumonitis development.…

Figure 5

Cytokine levels and pneumonitis development. (n=30 pretreatment; n=34 posttreatment). (A) Relative levels of…

Figure 5
Cytokine levels and pneumonitis development. (n=30 pretreatment; n=34 posttreatment). (A) Relative levels of TDGF1 (p=0.013 and p=0.076), MSP (p=0.006 and p=0.104), MDC (p=0.055 and p=0.089), E-cadherin (p=0.022 and p=0.364) and PARN (Poly(A)-specific ribonuclease, p=0.017 and p=0.496). (B) AUC curves to predict pneumonitis in pretreatment samples. *P
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References
    1. Finn OJ. Immuno-oncology: understanding the function and dysfunction of the immune system in cancer. Ann Oncol 2012:86–9. 10.1093/annonc/mds256 - DOI - PMC - PubMed
    1. Sharma P, Allison JP. Immune checkpoint targeting in cancer therapy: toward combination strategies with curative potential. Cell 2015;161:205–14. 10.1016/j.cell.2015.03.030 - DOI - PMC - PubMed
    1. Postow MA, Sidlow R, Hellmann MD. Immune-related adverse events associated with immune checkpoint blockade. N Engl J Med 2018;378:158–68. 10.1056/NEJMra1703481 - DOI - PubMed
    1. Forde P, Spicer J, Lu S. Abstract CT003 - Nivolumab (NIVO) + platinum-doublet chemotherapy (chemo) vs chemo as neoadjuvant treatment (tx) for resectable (IB-IIIA) non-small cell lung cancer (NSCLC) in the phase 3 CheckMate 816 trial, 2021. AACR Annu Meet 2021. Available: https://www.abstractsonline.com/pp8/#!/9325/presentation/5134
    1. Martins F, Sofiya L, Sykiotis GP, et al. . Adverse effects of immune-checkpoint inhibitors: epidemiology, management and surveillance. Nat Rev Clin Oncol 2019;16:563–80. 10.1038/s41571-019-0218-0 - DOI - PubMed
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Figure 3
Figure 3
Flow cytometry immunophenotyping of peripheral mononuclear cells (PMBCs). (n=29 in preneoadjuvant and postneoadjuvant treatment samples) (A) CD14+ cells (total monocytes, p=0.017 and p=0.329) and AUC curve to predict pneumonitis at baseline. (B) CD3-CD19+ (total B cells, p=0.064 and p=0.002). (C) CD3-CD56+ (total NK cells, p=0.019 and p=0.005), and positive and negative PD1 subpopulations in pretreatment samples (p=0.407 and p=0.032). (D) AUC curve of total NK and PD1—subpopulation to predict pneumonitis in pretreatment samples. *P

Figure 4

T cells immunophenotyping and TCR…

Figure 4

T cells immunophenotyping and TCR repertoire. (A) CD3+ (total T cells, n=29, p=0.064…

Figure 4
T cells immunophenotyping and TCR repertoire. (A) CD3+ (total T cells, n=29, p=0.064 in pretreatment and p=0.001 in postneoadjuvant treatment samples, respectively) and shift in CD3+ population calculated by POST-PRE differences (p=0.045). (B) T cell receptor repertoire evenness at diagnosis and postneoadjuvant treatment in both tissue (n=22; p=0.865 for pretreatment and n=38; p=0.028 for postneoadjuvant treatment) and blood (n=30; p=0.815 for pretreatment and n=35; p=0.827 for posttreatment samples). *P

Figure 5

Cytokine levels and pneumonitis development.…

Figure 5

Cytokine levels and pneumonitis development. (n=30 pretreatment; n=34 posttreatment). (A) Relative levels of…

Figure 5
Cytokine levels and pneumonitis development. (n=30 pretreatment; n=34 posttreatment). (A) Relative levels of TDGF1 (p=0.013 and p=0.076), MSP (p=0.006 and p=0.104), MDC (p=0.055 and p=0.089), E-cadherin (p=0.022 and p=0.364) and PARN (Poly(A)-specific ribonuclease, p=0.017 and p=0.496). (B) AUC curves to predict pneumonitis in pretreatment samples. *P
Similar articles
Cited by
References
    1. Finn OJ. Immuno-oncology: understanding the function and dysfunction of the immune system in cancer. Ann Oncol 2012:86–9. 10.1093/annonc/mds256 - DOI - PMC - PubMed
    1. Sharma P, Allison JP. Immune checkpoint targeting in cancer therapy: toward combination strategies with curative potential. Cell 2015;161:205–14. 10.1016/j.cell.2015.03.030 - DOI - PMC - PubMed
    1. Postow MA, Sidlow R, Hellmann MD. Immune-related adverse events associated with immune checkpoint blockade. N Engl J Med 2018;378:158–68. 10.1056/NEJMra1703481 - DOI - PubMed
    1. Forde P, Spicer J, Lu S. Abstract CT003 - Nivolumab (NIVO) + platinum-doublet chemotherapy (chemo) vs chemo as neoadjuvant treatment (tx) for resectable (IB-IIIA) non-small cell lung cancer (NSCLC) in the phase 3 CheckMate 816 trial, 2021. AACR Annu Meet 2021. Available: https://www.abstractsonline.com/pp8/#!/9325/presentation/5134
    1. Martins F, Sofiya L, Sykiotis GP, et al. . Adverse effects of immune-checkpoint inhibitors: epidemiology, management and surveillance. Nat Rev Clin Oncol 2019;16:563–80. 10.1038/s41571-019-0218-0 - DOI - PubMed
Show all 61 references
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[x]
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The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

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Figure 4
Figure 4
T cells immunophenotyping and TCR repertoire. (A) CD3+ (total T cells, n=29, p=0.064 in pretreatment and p=0.001 in postneoadjuvant treatment samples, respectively) and shift in CD3+ population calculated by POST-PRE differences (p=0.045). (B) T cell receptor repertoire evenness at diagnosis and postneoadjuvant treatment in both tissue (n=22; p=0.865 for pretreatment and n=38; p=0.028 for postneoadjuvant treatment) and blood (n=30; p=0.815 for pretreatment and n=35; p=0.827 for posttreatment samples). *P

Figure 5

Cytokine levels and pneumonitis development.…

Figure 5

Cytokine levels and pneumonitis development. (n=30 pretreatment; n=34 posttreatment). (A) Relative levels of…

Figure 5
Cytokine levels and pneumonitis development. (n=30 pretreatment; n=34 posttreatment). (A) Relative levels of TDGF1 (p=0.013 and p=0.076), MSP (p=0.006 and p=0.104), MDC (p=0.055 and p=0.089), E-cadherin (p=0.022 and p=0.364) and PARN (Poly(A)-specific ribonuclease, p=0.017 and p=0.496). (B) AUC curves to predict pneumonitis in pretreatment samples. *P
Similar articles
Cited by
References
    1. Finn OJ. Immuno-oncology: understanding the function and dysfunction of the immune system in cancer. Ann Oncol 2012:86–9. 10.1093/annonc/mds256 - DOI - PMC - PubMed
    1. Sharma P, Allison JP. Immune checkpoint targeting in cancer therapy: toward combination strategies with curative potential. Cell 2015;161:205–14. 10.1016/j.cell.2015.03.030 - DOI - PMC - PubMed
    1. Postow MA, Sidlow R, Hellmann MD. Immune-related adverse events associated with immune checkpoint blockade. N Engl J Med 2018;378:158–68. 10.1056/NEJMra1703481 - DOI - PubMed
    1. Forde P, Spicer J, Lu S. Abstract CT003 - Nivolumab (NIVO) + platinum-doublet chemotherapy (chemo) vs chemo as neoadjuvant treatment (tx) for resectable (IB-IIIA) non-small cell lung cancer (NSCLC) in the phase 3 CheckMate 816 trial, 2021. AACR Annu Meet 2021. Available: https://www.abstractsonline.com/pp8/#!/9325/presentation/5134
    1. Martins F, Sofiya L, Sykiotis GP, et al. . Adverse effects of immune-checkpoint inhibitors: epidemiology, management and surveillance. Nat Rev Clin Oncol 2019;16:563–80. 10.1038/s41571-019-0218-0 - DOI - PubMed
Show all 61 references
Publication types
MeSH terms
Associated data
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Full text links [x]
[x]
Cite
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Format: AMA APA MLA NLM
Figure 5
Figure 5
Cytokine levels and pneumonitis development. (n=30 pretreatment; n=34 posttreatment). (A) Relative levels of TDGF1 (p=0.013 and p=0.076), MSP (p=0.006 and p=0.104), MDC (p=0.055 and p=0.089), E-cadherin (p=0.022 and p=0.364) and PARN (Poly(A)-specific ribonuclease, p=0.017 and p=0.496). (B) AUC curves to predict pneumonitis in pretreatment samples. *P

References

    1. Finn OJ. Immuno-oncology: understanding the function and dysfunction of the immune system in cancer. Ann Oncol 2012:86–9. 10.1093/annonc/mds256
    1. Sharma P, Allison JP. Immune checkpoint targeting in cancer therapy: toward combination strategies with curative potential. Cell 2015;161:205–14. 10.1016/j.cell.2015.03.030
    1. Postow MA, Sidlow R, Hellmann MD. Immune-related adverse events associated with immune checkpoint blockade. N Engl J Med 2018;378:158–68. 10.1056/NEJMra1703481
    1. Forde P, Spicer J, Lu S. Abstract CT003 - Nivolumab (NIVO) + platinum-doublet chemotherapy (chemo) vs chemo as neoadjuvant treatment (tx) for resectable (IB-IIIA) non-small cell lung cancer (NSCLC) in the phase 3 CheckMate 816 trial, 2021. AACR Annu Meet 2021. Available:
    1. Martins F, Sofiya L, Sykiotis GP, et al. . Adverse effects of immune-checkpoint inhibitors: epidemiology, management and surveillance. Nat Rev Clin Oncol 2019;16:563–80. 10.1038/s41571-019-0218-0
    1. Wang DY, Salem J-E, Cohen JV, et al. . Fatal toxic effects associated with immune checkpoint inhibitors: a systematic review and meta-analysis. JAMA Oncol 2018;4:1721–8. 10.1001/jamaoncol.2018.3923
    1. Shannon VR. Pneumonitis associated with immune checkpoint inhibitors among patients with non-small cell lung cancer. Curr Opin Pulm Med 2020;26:326–40. 10.1097/MCP.0000000000000689
    1. Paz-Ares L, Luft A, Vicente D, et al. . Pembrolizumab plus chemotherapy for squamous non-small-cell lung cancer. N Engl J Med 2018;379:2040–5110.1056/NEJMoa1810865
    1. Gandhi L, Rodríguez-Abreu D, Gadgeel S, et al. . Pembrolizumab plus chemotherapy in metastatic non-small-cell lung cancer. N Engl J Med 2018;378:2078–9210.1056/NEJMoa1801005
    1. West H, McCleod M, Hussein M, et al. . Atezolizumab in combination with carboplatin plus nab-paclitaxel chemotherapy compared with chemotherapy alone as first-line treatment for metastatic non-squamous non-small-cell lung cancer (IMpower130): a multicentre, randomised, open-label, phase 3 trial. Lancet Oncol 2019;20:924–37. 10.1016/S1470-2045(19)30167-6
    1. Socinski MA, Jotte RM, Cappuzzo F, et al. . Atezolizumab for first-line treatment of metastatic Nonsquamous NSCLC. N Engl J Med 2018;378:2288–301. 10.1056/NEJMoa1716948
    1. Johnson DB, Taylor KB, Cohen JV, et al. . Anti-PD-1-induced pneumonitis is associated with persistent imaging abnormalities in melanoma patients. Cancer Immunol Res 2019;7:1755–9. 10.1158/2326-6066.CIR-18-0717
    1. Provencio M, Nadal E, Insa A, et al. . Neoadjuvant chemotherapy and nivolumab in resectable non-small-cell lung cancer (NADIM): an open-label, multicentre, single-arm, phase 2 trial. Lancet Oncol 2020;21:1413–2210.1016/S1470-2045(20)30453-8
    1. Shu CA, Gainor JF, Awad MM, et al. . Neoadjuvant atezolizumab and chemotherapy in patients with resectable non-small-cell lung cancer: an open-label, multicentre, single-arm, phase 2 trial. Lancet Oncol 2020;21:786–95. 10.1016/S1470-2045(20)30140-6
    1. Zinner R, Axelrod R, Solomides CC, et al. . Neoadjuvant nivolumab (N) plus cisplatin (C)/pemetrexed (P) or cisplatin /gemcitabine (G) in resectable NSCLC. JCO 2020;38:9051. 10.1200/JCO.2020.38.15_suppl.9051
    1. Rothschild S, Zippelius A, Eboulet EI, et al. . SAKK 16/14: Anti-PD-L1 antibody durvalumab in addition to neoadjuvant chemotherapy in patients with stage IIIA(N2) non-small cell lung cancer (NSCLC)—A multicenter single-arm phase II trial. JCO 2020;38:9016. 10.1200/JCO.2020.38.15_suppl.9016
    1. Fujimori K, Yokoyama A, Kurita Y, et al. . Paclitaxel-Induced cell-mediated hypersensitivity pneumonitis. diagnosis using leukocyte migration test, bronchoalveolar lavage and transbronchial lung biopsy. Oncology 1998;55:340–4. 10.1159/000011873
    1. Li L, Mok H, Jhaveri P, et al. . Anticancer therapy and lung injury: molecular mechanisms. Expert Rev Anticancer Ther 2018;18:1041–57. 10.1080/14737140.2018.1500180
    1. 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
    1. Cui P, Liu Z, Wang G, et al. . Risk factors for pneumonitis in patients treated with anti-programmed death-1 therapy: a case-control study. Cancer Med 2018;7:4115–2010.1002/cam4.1579
    1. Sears CR, Peikert T, Possick JD, et al. . Knowledge gaps and research priorities in immune checkpoint Inhibitor-related pneumonitis. An official American thoracic Society research statement. Am J Respir Crit Care Med 2019;200:e31–4310.1164/rccm.201906-1202ST
    1. Mezquita L, Auclin E, Ferrara R, et al. . Association of the lung immune prognostic index with immune checkpoint inhibitor outcomes in patients with advanced non-small cell lung cancer. JAMA Oncol 2018;4:351–7. 10.1001/jamaoncol.2017.4771
    1. Laza-Briviesca R, Cruz-Bermúdez A, Nadal E, et al. . Blood biomarkers associated to complete pathological response on NSCLC patients treated with neoadjuvant chemoimmunotherapy included in NADIM clinical trial. Clin Transl Med 2021;11:e491. 10.1002/ctm2.491
    1. Casarrubios M, Cruz-Bermúdez A, Nadal E, et al. . Pre-Treatment tissue TCR repertoire evenness is associated with complete pathological response in patients with NSCLC receiving neoadjuvant chemoimmunotherapy. Clin Cancer Res 2021:clincanres.1200.2021.10.1158/1078-0432.CCR-21-1200
    1. Yang Y, Pang P, Xie Z, et al. . The safety of first and subsequent lines of PD-1/PD-L1 inhibitors monotherapy in non-small cell lung cancer patients: a meta-analysis. Transl Cancer Res 2020;9:3231–41. 10.21037/tcr.2020.03.82
    1. Pavan A, Calvetti L, Dal Maso A, et al. . Peripheral blood markers identify risk of immune-related toxicity in advanced non-small cell lung cancer treated with Immune-Checkpoint inhibitors. Oncologist 2019;24:1128–36. 10.1634/theoncologist.2018-0563
    1. Liu W, Liu Y, Ma F, et al. . Peripheral blood markers associated with immune-related adverse effects in patients who had advanced non-small cell lung cancer treated with PD-1 inhibitors. Cancer Manag Res 2021;13:765–71. 10.2147/CMAR.S293200
    1. Lefrançais E, Ortiz-Muñoz G, Caudrillier A, et al. . The lung is a site of platelet biogenesis and a reservoir for haematopoietic progenitors. Nature 2017;544:105–9. 10.1038/nature21706
    1. Zamora C, Cantó E, Nieto JC, et al. . Binding of platelets to lymphocytes: a potential anti-inflammatory therapy in rheumatoid arthritis. J Immunol 2017;198:3099–108. 10.4049/jimmunol.1601708
    1. Linke B, Schreiber Y, Picard-Willems B, et al. . Activated platelets induce an anti-inflammatory response of monocytes/macrophages through cross-regulation of PGE2 and cytokines. Mediators Inflamm 2017;2017:1–14. 10.1155/2017/1463216
    1. Liu P, Li P, Peng Z, et al. . Predictive value of the neutrophil-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, platelet-to-neutrophil ratio, and neutrophil-to-monocyte ratio in lupus nephritis. Lupus 2020;29:1031–9. 10.1177/0961203320929753
    1. Ma W-T, Gao F, Gu K, Chen D-K, et al. . The role of monocytes and macrophages in autoimmune diseases: a comprehensive review. Front Immunol 2019;10:1140. 10.3389/fimmu.2019.01140
    1. Suresh K, Naidoo J, Zhong Q, et al. . The alveolar immune cell landscape is dysregulated in checkpoint inhibitor pneumonitis. J Clin Invest 2019;129:4305–15. 10.1172/JCI128654
    1. Chen YQ, Fisher JH, Wang MH. Activation of the RON receptor tyrosine kinase inhibits inducible nitric oxide synthase (iNOS) expression by murine peritoneal exudate macrophages: phosphatidylinositol-3 kinase is required for RON-mediated inhibition of iNOS expression. J Immunol 1998;161:4950–9.
    1. Ekmekcioglu S, Grimm EA, Roszik J. Targeting iNOS to increase efficacy of immunotherapies. Hum Vaccin Immunother 2017;13:1105–8. 10.1080/21645515.2016.1276682
    1. Ritter M, Göggel R, Chaudhary N, et al. . Elevated expression of TARC (CCL17) and MDC (CCL22) in models of cigarette smoke-induced pulmonary inflammation. Biochem Biophys Res Commun 2005;334:254–62. 10.1016/j.bbrc.2005.06.084
    1. Zhang D-mei, Bao Y-L, Yu C-L, et al. . Cripto-1 modulates macrophage cytokine secretion and phagocytic activity via NF-κB signaling. Immunol Res 2016;64:104–14. 10.1007/s12026-015-8724-3
    1. McGuire JK, Li Q, Parks WC. Matrilysin (matrix metalloproteinase-7) mediates E-cadherin ectodomain shedding in injured lung epithelium. Am J Pathol 2003;162:1831–43. 10.1016/S0002-9440(10)64318-0
    1. Blázquez-Prieto J, López-Alonso I, Huidobro C, et al. . The emerging role of neutrophils in repair after acute lung injury. Am J Respir Cell Mol Biol 2018;59:289–94. 10.1165/rcmb.2018-0101PS
    1. Potey PM, Rossi AG, Lucas CD, et al. . Neutrophils in the initiation and resolution of acute pulmonary inflammation: understanding biological function and therapeutic potential. J Pathol 2019;247:672–85. 10.1002/path.5221
    1. Ikezoe K, Handa T, Mori K, et al. . Neutrophil gelatinase-associated lipocalin in idiopathic pulmonary fibrosis. Eur Respir J 2014;43:1807–910.1183/09031936.00192613
    1. Pliyev BK. Activated human neutrophils rapidly release the chemotactically active D2D3 form of the urokinase-type plasminogen activator receptor (uPAR/CD87). Mol Cell Biochem 2009;321:111–22. 10.1007/s11010-008-9925-z
    1. Capucetti A, Albano F, Bonecchi R. Multiple roles for chemokines in neutrophil biology. Front Immunol 2020;11:1–9. 10.3389/fimmu.2020.01259
    1. Croasdell Lucchini A, Gachanja NN, Rossi AG, et al. . Epithelial cells and inflammation in pulmonary wound repair. Cells 2021;10. 10.3390/cells10020339. [Epub ahead of print: 05 Feb 2021].
    1. Barrientos S, Stojadinovic O, Golinko MS, et al. . Growth factors and cytokines in wound healing. Wound Repair Regen 2008;16:585–601. 10.1111/j.1524-475X.2008.00410.x
    1. Helmink BA, Reddy SM, Gao J, et al. . B cells and tertiary lymphoid structures promote immunotherapy response. Nature. 2020;577:549–5510.1038/s41586-019-1922-8
    1. Fillatreau S. Regulatory functions of B cells and regulatory plasma cells. Biomed J 2019;42:233–42. 10.1016/j.bj.2019.05.008
    1. de Jonge K, Tillé L, Lourenco J, et al. . Inflammatory B cells correlate with failure to checkpoint blockade in melanoma patients. Oncoimmunology 2021;10:1873585. 10.1080/2162402X.2021.1873585
    1. Lampropoulou V, Calderon-Gomez E, Roch T, et al. . Suppressive functions of activated B cells in autoimmune diseases reveal the dual roles of Toll-like receptors in immunity. Immunol Rev 2010;233:146–61. 10.1111/j.0105-2896.2009.00855.x
    1. Yuan S, Liu Y, Till B, et al. . Pretreatment peripheral B cells are associated with tumor response to Anti-PD-1-Based immunotherapy. Front Immunol 2020;11:563653. 10.3389/fimmu.2020.563653
    1. Jing Y, Liu J, Ye Y, et al. . Multi-omics prediction of immune-related adverse events during checkpoint immunotherapy. Nat Commun 2020;11. 10.1038/s41467-020-18742-9
    1. Nishimura H, Okazaki T, Tanaka Y, et al. . Autoimmune dilated cardiomyopathy in PD-1 receptor-deficient mice. Science 2001;291:319–22. 10.1126/science.291.5502.319
    1. Lázár-Molnár E, Chen B, Sweeney KA, et al. . Programmed death-1 (PD-1)-deficient mice are extraordinarily sensitive to tuberculosis. Proc Natl Acad Sci U S A 2010;107:13402–7. 10.1073/pnas.1007394107
    1. Berner F, Bomze D, Diem S, et al. . Association of checkpoint inhibitor-induced toxic effects with shared cancer and tissue antigens in non-small cell lung cancer. JAMA Oncol 2019;5:1043–710.1001/jamaoncol.2019.0402
    1. Läubli H, Koelzer VH, Matter MS, et al. . The T cell repertoire in tumors overlaps with pulmonary inflammatory lesions in patients treated with checkpoint inhibitors. Oncoimmunology 2018;7:e1386362–6. 10.1080/2162402X.2017.1386362
    1. Johnson DB, Balko JM, Compton ML, et al. . Fulminant myocarditis with combination immune checkpoint blockade. N Engl J Med 2016;375:1749–55. 10.1056/NEJMoa1609214
    1. Bomze D, Hasan Ali O, Bate A, et al. . Association between immune-related adverse events during anti-PD-1 therapy and tumor mutational burden. JAMA Oncol 2019;5:1633–5. 10.1001/jamaoncol.2019.3221
    1. Li Z, Lin J, Zhang L, et al. . Comprehensive analysis of multiple parameters associated with tumor immune microenvironment in ARID1A mutant cancers. Future Oncol 2020;16:2295–306. 10.2217/fon-2020-0243
    1. Yang Y, Day J, Souza-Fonseca Guimaraes F, et al. . Natural killer cells in inflammatory autoimmune diseases. Clin Transl Immunology 2021;10:e1250. 10.1002/cti2.1250
    1. Hervier B, Russick J, Cremer I, et al. . NK cells in the human lungs. Front Immunol 2019;10:1263. 10.3389/fimmu.2019.01263
    1. Sokhatska O, Padrão E, Sousa-Pinto B, et al. . NK and NKT cells in the diagnosis of diffuse lung diseases presenting with a lymphocytic alveolitis. BMC Pulm Med 2019;19:39. 10.1186/s12890-019-0802-1

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