Predictive biomarkers of response to immune checkpoint inhibitors in non-small cell lung cancer: An integrative review.
DOI:
https://doi.org/10.36557/2674-8169.2026v8n1p684-709Keywords:
Non-Small Cell Lung Cancer, Immunotherapy, Predictive BiomarkersAbstract
Introduction:Non–small cell lung cancer (NSCLC) accounts for the majority of lung cancer cases and is associated with high mortality, mainly due to diagnosis at advanced stages. The incorporation of immunotherapy based on immune checkpoint inhibitors, such as anti–PD-1, anti–PD-L1, and anti–CTLA-4 agents, has led to significant advances in the treatment of this malignancy. However, only a subset of patients achieves sustained clinical benefit, highlighting the need for predictive biomarkers to guide the appropriate selection of candidates for immunotherapy.
Objective:To analyze, through an integrative review of the literature, the main predictive biomarkers of response to immune checkpoint inhibitors in patients with non–small cell lung cancer.
Methodology:This is an integrative review in which searches were conducted in the PubMed/MEDLINE and SciELO databases using descriptors in Portuguese and English related to non–small cell lung cancer, immunotherapy, biomarkers, and survival. Studies published between 2010 and December 2025 were included if they evaluated the association between molecular or immunological biomarkers and clinical outcomes, such as objective response rate, progression-free survival, and overall survival, in patients with NSCLC treated with immune checkpoint inhibitors. Literature reviews, editorials, and duplicate studies were excluded.
Conclusion:The analyzed studies indicate that the response to immunotherapy in NSCLC is predominantly influenced by molecular and immunological tumor characteristics. Biomarkers such as PD-L1 expression, tumor mutational burden, CD8+ T-cell infiltration, HLA system integrity, and genomic signatures associated with tobacco-related mutagenesis showed consistent associations with improved clinical outcomes. Recent evidence suggests that integrative predictive models combining multiple biomarkers are more accurate than isolated markers. The clinical application of these biomarkers may contribute to treatment personalization, reduction of immune-related toxicities, and more rational use of immunotherapy in non–small cell lung cancer.
Keywords: Non-Small Cell Lung Cancer; Immunotherapy; Predictive Biomarkers.
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Copyright (c) 2026 Sarah Rosado, Thays Araújo
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