Immune complexome analysis of serum samples from non-small-cell lung cancer patients identifies predictive biomarkers for nivolumab therapy

•We compared immune complex antigens between responders and non-responders for nivolumab therapy.•Combination of immune complex antigens may predict the therapeutic effect of nivolumab.•Immune complexome analysis identifies predictive biomarkers in ICI therapy. Immune checkpoint inhibitors (ICIs) ha...

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Veröffentlicht in:Clinica chimica acta 2022-07, Vol.532, p.84-88
Hauptverfasser: Aizawa, Rika, Nakamura, Yoichi, Ikeda, Takaya, Aibara, Nozomi, Kutsuna, Yuki J., Kurosaki, Tomoaki, Aki, Keisei, Junya, Hashizume, Nakagawa, Hiroo, Sato, Kayoko, Kodama, Yukinobu, Nakashima, Mihoko N., Nakashima, Mikiro, Mukae, Hiroshi, Ohyama, Kaname
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container_title Clinica chimica acta
container_volume 532
creator Aizawa, Rika
Nakamura, Yoichi
Ikeda, Takaya
Aibara, Nozomi
Kutsuna, Yuki J.
Kurosaki, Tomoaki
Aki, Keisei
Junya, Hashizume
Nakagawa, Hiroo
Sato, Kayoko
Kodama, Yukinobu
Nakashima, Mihoko N.
Nakashima, Mikiro
Mukae, Hiroshi
Ohyama, Kaname
description •We compared immune complex antigens between responders and non-responders for nivolumab therapy.•Combination of immune complex antigens may predict the therapeutic effect of nivolumab.•Immune complexome analysis identifies predictive biomarkers in ICI therapy. Immune checkpoint inhibitors (ICIs) have achieved important outcomes in cancer treatment. However, current clinical biomarker tests are not suitable for some patients because they require tumor tissues and have poor predictive value for treatment responses. Therefore, the identification of biomarkers that enable screening tests in all patients is necessary. We performed an immune complexome analysis of non-small cell lung cancer patients treated with nivolumab to comprehensively identify and compare antigens incorporated into immune complexes (IC-antigens) in serum samples from the responders (n = 15) and non-responders (n = 20). Additionally, combinations of IC-antigens characteristic to the responder group were evaluated by logistic regression analysis and receiver operating characteristics curves to examine their predictiveness for ICI treatment responses. The combination of predictive biomarkers detected before treatment was profilin-1, purine nucleoside phosphorylase, alpha-enolase, and nucleoside diphosphate kinase A [p = 0.0043, odds ratio = 2.26, 95% confidence interval (CI) = 1.19–4.28, area under the curve = 0.76]. The combination of predictive biomarkers detected after treatment was peptidyl-prolyl cis–trans isomerase A, ubiquitin-like modifier-activating enzyme 1, complement component C8 beta chain, and apolipoprotein L1 (p = 0.0039, odds ratio = 2.56, 95% CI = 1.25–5.23, area under the curve = 0.77). Combinations of serum IC-antigens may predict the therapeutic effect of nivolumab in non-small cell lung cancer patients.
doi_str_mv 10.1016/j.cca.2022.05.021
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Immune checkpoint inhibitors (ICIs) have achieved important outcomes in cancer treatment. However, current clinical biomarker tests are not suitable for some patients because they require tumor tissues and have poor predictive value for treatment responses. Therefore, the identification of biomarkers that enable screening tests in all patients is necessary. We performed an immune complexome analysis of non-small cell lung cancer patients treated with nivolumab to comprehensively identify and compare antigens incorporated into immune complexes (IC-antigens) in serum samples from the responders (n = 15) and non-responders (n = 20). Additionally, combinations of IC-antigens characteristic to the responder group were evaluated by logistic regression analysis and receiver operating characteristics curves to examine their predictiveness for ICI treatment responses. The combination of predictive biomarkers detected before treatment was profilin-1, purine nucleoside phosphorylase, alpha-enolase, and nucleoside diphosphate kinase A [p = 0.0043, odds ratio = 2.26, 95% confidence interval (CI) = 1.19–4.28, area under the curve = 0.76]. The combination of predictive biomarkers detected after treatment was peptidyl-prolyl cis–trans isomerase A, ubiquitin-like modifier-activating enzyme 1, complement component C8 beta chain, and apolipoprotein L1 (p = 0.0039, odds ratio = 2.56, 95% CI = 1.25–5.23, area under the curve = 0.77). 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Immune checkpoint inhibitors (ICIs) have achieved important outcomes in cancer treatment. However, current clinical biomarker tests are not suitable for some patients because they require tumor tissues and have poor predictive value for treatment responses. Therefore, the identification of biomarkers that enable screening tests in all patients is necessary. We performed an immune complexome analysis of non-small cell lung cancer patients treated with nivolumab to comprehensively identify and compare antigens incorporated into immune complexes (IC-antigens) in serum samples from the responders (n = 15) and non-responders (n = 20). Additionally, combinations of IC-antigens characteristic to the responder group were evaluated by logistic regression analysis and receiver operating characteristics curves to examine their predictiveness for ICI treatment responses. 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subjects Immune complex antigen
Immune complexome analysis
Nivolumab
Non-small-cell lung cancer
Therapeutic predictive biomarker
title Immune complexome analysis of serum samples from non-small-cell lung cancer patients identifies predictive biomarkers for nivolumab therapy
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