The Role of Eosinophils, Eosinophil-Related Cytokines and AI in Predicting Immunotherapy Efficacy in NSCLC
Immunotherapy and chemoimmunotherapy are standard treatments for non-oncogene-addicted advanced non-small cell lung cancer (NSCLC). Currently, a limited number of biomarkers, including programmed death-ligand 1 (PD-L1) expression, microsatellite instability (MSI), and tumor mutational burden (TMB),...
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| Format: | Article |
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MDPI AG
2025-03-01
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| Series: | Biomolecules |
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| Online Access: | https://www.mdpi.com/2218-273X/15/4/491 |
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| author | Fausto Omero Desirèe Speranza Giuseppe Murdaca Mariacarmela Cavaleri Mariapia Marafioti Vincenzo Cianci Massimiliano Berretta Marco Casciaro Sebastiano Gangemi Mariacarmela Santarpia |
| author_facet | Fausto Omero Desirèe Speranza Giuseppe Murdaca Mariacarmela Cavaleri Mariapia Marafioti Vincenzo Cianci Massimiliano Berretta Marco Casciaro Sebastiano Gangemi Mariacarmela Santarpia |
| author_sort | Fausto Omero |
| collection | DOAJ |
| description | Immunotherapy and chemoimmunotherapy are standard treatments for non-oncogene-addicted advanced non-small cell lung cancer (NSCLC). Currently, a limited number of biomarkers, including programmed death-ligand 1 (PD-L1) expression, microsatellite instability (MSI), and tumor mutational burden (TMB), are used in clinical practice to predict benefits from immune checkpoint inhibitors (ICIs). It is therefore necessary to search for novel biomarkers that could be helpful to identify patients who respond to immunotherapy. In this context, research efforts are focusing on different cells and mechanisms involved in anti-tumor immune response. Herein, we provide un updated literature review on the role of eosinophils in cancer development and immune response, and the functions of some cytokines, including IL-31 and IL-33, in eosinophil activation. We discuss available data demonstrating a correlation between eosinophils and clinical outcomes of ICIs in lung cancer. In this context, we underscore the role of absolute eosinophil count (AEC) and tumor-associated tissue eosinophilia (TATE) as promising biomarkers able to predict the efficacy and toxicities from immunotherapy. The role of eosinophils and cytokines in NSCLC, treated with ICIs, is not yet fully understood, and further research may be crucial to determine their role as biomarkers of response. Artificial intelligence, through the analysis of big data, could be exploited in the future to elucidate the role of eosinophils and cytokines in lung cancer. |
| format | Article |
| id | doaj-art-959fd959d28c45cb8d817ee48169783d |
| institution | DOAJ |
| issn | 2218-273X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomolecules |
| spelling | doaj-art-959fd959d28c45cb8d817ee48169783d2025-08-20T03:19:20ZengMDPI AGBiomolecules2218-273X2025-03-0115449110.3390/biom15040491The Role of Eosinophils, Eosinophil-Related Cytokines and AI in Predicting Immunotherapy Efficacy in NSCLCFausto Omero0Desirèe Speranza1Giuseppe Murdaca2Mariacarmela Cavaleri3Mariapia Marafioti4Vincenzo Cianci5Massimiliano Berretta6Marco Casciaro7Sebastiano Gangemi8Mariacarmela Santarpia9Medical Oncology Unit, Department of Human Pathology “G. Barresi”, University of Messina, 98125 Messina, ItalyMedical Oncology Unit, Department of Human Pathology “G. Barresi”, University of Messina, 98125 Messina, ItalyDepartment of Internal Medicine, University of Genoa, 16132 Genoa, ItalyMedical Oncology Unit, Department of Human Pathology “G. Barresi”, University of Messina, 98125 Messina, ItalyMedical Oncology Unit, Department of Human Pathology “G. Barresi”, University of Messina, 98125 Messina, ItalyDepartment of Biomedical and Dental Sciences and Morphofunctional Imaging, Section of Legal Medicine, University of Messina, Via Consolare Valeria, 1, 98125 Messina, ItalyMedical Oncology Unit, Department of Clinical and Experimental Medicine, University of Messina, Via Consolare Valeria, 98125 Messina, ItalySchool and Operative Unit of Allergy and Clinical Immunology, Department of Clinical and Experimental Medicine, University of Messina, 98125 Messina, ItalySchool and Operative Unit of Allergy and Clinical Immunology, Department of Clinical and Experimental Medicine, University of Messina, 98125 Messina, ItalyMedical Oncology Unit, Department of Human Pathology “G. Barresi”, University of Messina, 98125 Messina, ItalyImmunotherapy and chemoimmunotherapy are standard treatments for non-oncogene-addicted advanced non-small cell lung cancer (NSCLC). Currently, a limited number of biomarkers, including programmed death-ligand 1 (PD-L1) expression, microsatellite instability (MSI), and tumor mutational burden (TMB), are used in clinical practice to predict benefits from immune checkpoint inhibitors (ICIs). It is therefore necessary to search for novel biomarkers that could be helpful to identify patients who respond to immunotherapy. In this context, research efforts are focusing on different cells and mechanisms involved in anti-tumor immune response. Herein, we provide un updated literature review on the role of eosinophils in cancer development and immune response, and the functions of some cytokines, including IL-31 and IL-33, in eosinophil activation. We discuss available data demonstrating a correlation between eosinophils and clinical outcomes of ICIs in lung cancer. In this context, we underscore the role of absolute eosinophil count (AEC) and tumor-associated tissue eosinophilia (TATE) as promising biomarkers able to predict the efficacy and toxicities from immunotherapy. The role of eosinophils and cytokines in NSCLC, treated with ICIs, is not yet fully understood, and further research may be crucial to determine their role as biomarkers of response. Artificial intelligence, through the analysis of big data, could be exploited in the future to elucidate the role of eosinophils and cytokines in lung cancer.https://www.mdpi.com/2218-273X/15/4/491immunotherapyNSCLClung cancerbiomarkerseosinophilscytokines |
| spellingShingle | Fausto Omero Desirèe Speranza Giuseppe Murdaca Mariacarmela Cavaleri Mariapia Marafioti Vincenzo Cianci Massimiliano Berretta Marco Casciaro Sebastiano Gangemi Mariacarmela Santarpia The Role of Eosinophils, Eosinophil-Related Cytokines and AI in Predicting Immunotherapy Efficacy in NSCLC Biomolecules immunotherapy NSCLC lung cancer biomarkers eosinophils cytokines |
| title | The Role of Eosinophils, Eosinophil-Related Cytokines and AI in Predicting Immunotherapy Efficacy in NSCLC |
| title_full | The Role of Eosinophils, Eosinophil-Related Cytokines and AI in Predicting Immunotherapy Efficacy in NSCLC |
| title_fullStr | The Role of Eosinophils, Eosinophil-Related Cytokines and AI in Predicting Immunotherapy Efficacy in NSCLC |
| title_full_unstemmed | The Role of Eosinophils, Eosinophil-Related Cytokines and AI in Predicting Immunotherapy Efficacy in NSCLC |
| title_short | The Role of Eosinophils, Eosinophil-Related Cytokines and AI in Predicting Immunotherapy Efficacy in NSCLC |
| title_sort | role of eosinophils eosinophil related cytokines and ai in predicting immunotherapy efficacy in nsclc |
| topic | immunotherapy NSCLC lung cancer biomarkers eosinophils cytokines |
| url | https://www.mdpi.com/2218-273X/15/4/491 |
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