---
title: "Predictive biomarkers for immune checkpoint inhibitors in lung cancer — Editorial"
id: "frontiers-in-immunology-16-editorial-predictive-biomarkers-to-immune-checkpoint-inhibitors-in-lung-cancer"
canonical_url: "https://medichelpline.com/clinical-feed/frontiers-in-immunology-16-editorial-predictive-biomarkers-to-immune-checkpoint-inhibitors-in-lung-cancer"
content_type: "clinical_feed_article"
specialty: "Infectious Disease"
source_name: "Frontiers in Immunology"
source_url: "https://www.frontiersin.org/articles/10.3389/fimmu.2026.2011872"
published_at: "2026-10-20T00:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Predictive biomarkers for immune checkpoint inhibitors in lung cancer — Editorial
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/frontiers-in-immunology-16-editorial-predictive-biomarkers-to-immune-checkpoint-inhibitors-in-lung-cancer
- **Specialty:** [Infectious Disease](https://medichelpline.com/clinical-feed/infectious-disease.md)
- **Primary Source:** Frontiers in Immunology
- **Source URL:** [Original Journal Publication](https://www.frontiersin.org/articles/10.3389/fimmu.2026.2011872)
- **Published At:** 2026-10-20T00:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- The source provided is an editorial titled "Predictive biomarkers to immune checkpoint inhibitors in lung cancer" published in Frontiers in Immunology; the page metadata identifies it as an EDITORIAL article. - The publicly accessible content included only site navigation elements and journal sections; investigators, authors, study cohorts, and specific data were not present on the captured page. - The document did not report any primary clinical findings, numerical results, endpoints, or methodological details such as cohort size, biomarker assays, or treatment regimens. - No information on immune checkpoint inhibitors by agent name, dosing, schedule, or comparative effectiveness appeared in the source material. - The source did not present validated predictive **biomarkers** or performance metrics (sensitivity, specificity, predictive values) for response or toxicity in lung cancer. - There was no discussion recorded of regulatory status, guideline recommendations, or prospective/retrospective study designs within the captured content. - Key translational elements—tissue vs. blood biomarkers, assay platforms, cutoff thresholds, and reproducibility data—were absent from the available source. - The captured page offered no explicit trial limitations, next-step recommendations, or author-specified research gaps; therefore any clinical interpretation beyond noting these absences would be speculative. - Readers should consult the full Frontiers in Immunology editorial page or the published article PDF for complete text; the excerpt used here does not contain substantive editorial content or clinical evidence.
## Clinical Analysis & Structured Key Points
Frontiers | Editorial: Predictive biomarkers to immune checkpoint inhibitors in lung cancer EDITORIAL article Front. Immunol. , 20 October 2026 Sec. Cancer Immunity and Immunotherapy Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.2011872 Published in Frontiers in Immunology Cancer Immunity and Immunotherapy 7 impact factor 11.3 citescore Part of a Research Topic Predictive Biomarkers to Immune Checkpoint Inhibitors in Lung Cancer 70k views 20 articles Editor & Reviewers Edited and reviewed by P B Peter Brossart Outline Figures and Tables Figure 1 View in article EDITORIAL article Front. Immunol. , 20 October 2026 Sec. Cancer Immunity and Immunotherapy Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.2011872 Editorial: Predictive biomarkers to immune checkpoint inhibitors in lung cancer A R Alessandro Russo 1,2 C R Christian Rolfo 3 * M S Mariacarmela Santarpia 4,5 1. Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy 2. Medical Oncology Department, Humanitas Istituto Clinico Catanese, Misterbianco, Catania, Italy 3. Department of Internal Medicine, Division of Medical Oncology, The Arthur G. James Comprehensive Cancer Center, Columbus, OH, United States 4. Division of Medical Oncology, “Gaetano Martino” Hospital, Messina, Italy 5. Department of Human Pathology “G. Barresi”, University of Messina, Messina, Italy See more Article metrics View details Editorial on the Research Topic Predictive biomarkers to immune checkpoint inhibitors in lung cancer Immune checkpoint inhibitors (ICIs) have revolutionized the therapeutic landscape of lung cancer with unprecedented survival gains in the majority of clinical settings. After initial signs of effectiveness in pretreated non-small cell lung cancer (NSCLC) in the early 2010s ( 1 , 2 ), the use of ICIs has progressively changed the standard of care in first-line metastatic settings, locally advanced disease, and, more recently, early-stage NSCLC ( 3 , 4 ). However, except for programmed death ligand 1 (PD-L1) tumor expression (tumor proportion score, TPS), due to the inherent biological limitations of this biomarker, no other predictive factor has been approved to guide patient selection for these agents ( 5 ), posing several challenges in clinical practice. Furthermore, the use of ICIs in small cell lung cancer (SCLC), whether in the extensive stage or limited stage of the disease, is independent of PD-L1 status or any other predictive biomarker ( 6 ). The identification of predictive biomarkers is essential to reducing the cost of these treatments and avoiding unnecessary toxicities in patients who cannot benefit from these drugs. In this rapidly evolving therapeutic scenario, it is crucial to understand the basis of tumor response and resistance to drive a more rational development of novel immunotherapy-based strategies. The Research Topic “Predictive Biomarkers to Immune Checkpoint Inhibitors in Lung Cancer” aimed to identify novel, reliable predictive biomarkers for ICIs that could drive therapeutic decision-making in lung cancer more effectively. The clinical and scientific relevance of the topic is further highlighted by the success of this collection, with 19 published articles, including 9 original research studies, 5 systematic reviews, 3 literature reviews, and 2 case reports. More than 130 authors from different countries contributed to this special issue. Circulating biomarkers are particularly appealing in this context, due to their minimally invasive nature and, in some cases, low evaluation cost. Examples include the derived neutrophil-to-lymphocyte ratio (dNLR), lactate dehydrogenase (LDH), and the Lung Immune Prognostic Index (LIPI) score. Their prognostic value is well known ( 7 ) and was further explored in some of the research studies presented here, including in largely underexplored settings, such as SCLC. In addition to the prognostic value of these circulating biomarkers, others have explored their potential use in serial assessments of laboratory results, such as the absolute lymphocyte count, or their correlation with immunosuppressive circulating cytokine levels. Growing evidence suggests a pivotal role of the microbiome in ICI response within solid tumors, including lung cancer. The microbiome may be influenced by concomitant therapies, such as antibiotics or proton pump inhibitors (PPIs) ( 8 ). The microbiome represents a potential therapeutic target in patients treated with ICIs, and fecal transplantation has been reported to potentially impact their therapeutic efficacy ( 9 ). Overall, this Special Issue contributes to the significant efforts made in the last few years to understand ICI response in lung cancer, adding another piece to the complex puzzle of immunotherapy effects in solid tumors. The articles included in this Research Topic reflect the field’s rapid progress, moving beyond the conventional PD-L1-centric model toward a more comprehensive view of the complex interactions between the immune system and lung cancer. Future challenges will be to combine and integrate several layers of information, from tumor genomics and transcriptomics to liquid biopsies, the tumor microenvironment, and the microbiome ( Figure 1 ), and validate them in prospective studies. Figure 1 Beyond PD-L1: toward integrated biomarkers for immunotherapy in lung cancer. Created with BioRender.com . Statements Author contributions AR: Writing – review & editing, Writing – original draft, Conceptualization. CR: Writing – review & editing. MS: Writing – review & editing. Conflict of interest AR has received personal fees for advisory board membership, speaker bureau honoraria, or consultancy from AstraZeneca, MSD, Novartis, Pfizer, BMS, Takeda, Amgen, Regeneron, Daiichi Sankyo, Merck, Johnson & Johnson, AbbVie, Roche, Boehringer Ingelheim, PharmaMar, BeOne, and Lilly; he reports receiving personal fees for advisory board participation from Novocure, and institutional fees for advisory board participation from AstraZeneca, Imagene, MedStar, Amgem, Boehringer-Ingelheim, Hoffmann-La Roche Ltd., Janssen Pharmaceuticals, NeoGenomics, Pfizer, Inc. and Regeneron; he has non-remunerated research collaborations with Guardant and FoundationOne; he has also received institutional fees as an invited speaker from COR2ED, HPM Education, IDEOlogy, Merck, Roche, and OneCell Dx. CR holds non-remunerated leadership positions as a scientific board member of the European School of Oncology ESO, as former Chair of the educational committee of the International Association for Study of Lung Cancer IASLC, as President of the International Society of Liquid Biopsy ISLB and as Educational Chair of the Oncology Latin American Association OLA; he serves in a remunerated role as Editor-in-Chief of Critical Reviews in Oncology Hematology CROH; he holds non-remunerated roles as ESMO Faculty Group/Specialty and Faculty Coordinator for metastatic non-small cell lung cancer at the European Society for Medical Oncology ESMO, as a Scientific Board Member at ESO European School of Oncology, as an external advisory Board member of Centro Pfizer-Universidad de Granada-Junta de Andalucía de Genómica e Investigación Oncológica GENYO, as an external Advisor to the School of Public Health, University of Granada, Spain, as a member of the Scientific Committee of the Fondazione Siciliana di Oncologia, and performs non-remunerated analysis of liquid biopsies for a lung cancer trial conducted by Guardant Health. MS has received personal fees for speaker bureau honoraria or advisory board membership from AstraZeneca, MSD, Novartis, Pfizer, BMS, Johnson & Johnson, Pierre Fabre and Sun Pharma. The remaining author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author AR declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision. Generative AI statement The author(s) declared that generative AI was not used in the creation of this manuscript. Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us. Publisher’s note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. References 1 Topalian SL Hodi FS Brahmer JR Gettinger SN Smith DC McDermott DF et al . Safety, activity, and immune correlates of anti-PD-1 antibody in cancer . N Engl J Med . ( 2012 ) 366 : 2443–54 . doi: 10.1056/NEJMoa1200690 Pubmed Abstract CrossRef Google Scholar View reference in article 2 Brahmer JR Tykodi SS Chow LQM Hwu W-J Topalian SL Hwu P et al . Safety and activity of anti-PD-L1 antibody in patients with advanced cancer . N Engl J Med . ( 2012 ) 366 : 2455–65 . doi: 10.1056/NEJMoa1200694 Pubmed Abstract CrossRef Google Scholar View reference in article 3 Russo A McCusker MG Scilla KA Arensmeyer KE Mehra R Adamo V et al . Immunotherapy in lung cancer: From a minor god to the Olympus . Adv Exp Med Biol . ( 2020 ) 1244 : 69 – 92 . doi: 10.1007/978-3-030-41008-7_4 Pubmed Abstract CrossRef Google Scholar View reference in article 4 Mountzios G Remon J Hendriks LEL García-Campelo R Rolfo C Van Schil P et al . Immune-checkpoint inhibition for resectable non-small-cell lung cancer - opportunities and challenges . Nat Rev Clin Oncol . ( 2023 ) 20 : 664–77 . doi: 10.1038/s41571-023-00794-7 Pubmed Abstract CrossRef Google Scholar View reference in article 5 Mino-Kenudson M Schalper K Cooper W Dacic S Hirsch FR Jain D et al . Predictive biomarkers for immunotherapy in lung cancer: Perspective from the International Association for the Study of Lung Cancer Pathology Committee . J Thorac Oncol . ( 2022 ) 17 : 1335–54 . doi: 10.1016/j.jtho.2022.09.109 Pubmed Abstract CrossRef Google Scholar View reference in article 6 Rolfo C Russo A . In search of lost biomarker for immunotherapy in small cell lung cancer . Clin Cancer Res . ( 2024 ) 30 : 652–4 . doi: 10.1158/1078-0432.CCR-23-3087 Pubmed Abstract CrossRef Google Scholar View reference in article 7 Rebuzzi SE Prelaj A Friedlaender A Cortellini A Addeo A Genova C et al . Prognostic scores including peripheral blood-derived inflammatory indices in patients with advanced non-small-cell lung cancer treated with immune checkpoint inhibitors . Crit Rev Oncol Hematol . ( 2022 ) 179 : 103806 . doi: 10.1016/j.critrevonc.2022.103806 Pubmed Abstract CrossRef Google Scholar View reference in article 8 Cortellini A Tucci M Adamo V Stucci LS Russo A Tanda ET et al . Integrated analysis of concomitant medications and oncological outcomes from PD-1/PD-L1 checkpoint inhibitors in clinical practice . J Immunother Cancer . ( 2020 ) 8 . doi: 10.1136/jitc-2020-001361 Pubmed Abstract CrossRef Google Scholar View reference in article 9 Duttagupta S Messaoudene M Hunter S Desilets A Jamal R Mihalcioiu C et al . Fecal microbiota transplantation plus immunotherapy in non-small cell lung cancer and melanoma: The phase 2 FMT-LUMINate trial . Nat Med . ( 2026 ) 32 : 1337–50 . doi: 10.1038/s41591-025-04186-5 Pubmed Abstract CrossRef Google Scholar View reference in article Summary Keywords immunotherapy , liquid biopsy , NSCLC , PD-L1 , predictive biomarker Citation Russo A, Rolfo C and Santarpia M (2026) Editorial: Predictive biomarkers to immune checkpoint inhibitors in lung cancer . Front. Immunol. 17:2011872. doi: 10.3389/fimmu.2026.2011872 Received 27 September 2026 Accepted 30 September 2026 Published 20 October 2026 Volume 17 - 2026 Edited and reviewed by Peter Brossart , University of Bonn, Germany Updates Check for updates Copyright © 2026 Russo, Rolfo and Santarpia. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. * Correspondence: Christian Rolfo, christian.rolfo@osumc.edu Disclaimer All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher. 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