Biomarkers in cancer immunotherapy: Mechanisms, efficacy prediction, and irAE management

Cancer immunotherapy has transformed the landscape of oncology by mobilizing the host immune system to recognize and eradicate malignant cells. Therapeutic approaches such as immune checkpoint inhibitors (ICIs), CAR T-cell therapy, bispecific antibodies, cancer vaccines, and cytokine-based treatments have demonstrated remarkable, long-lasting antitumor responses. Nevertheless, considerable heterogeneity in therapeutic efficacy, low response rates across certain tumor types, and the emergence of unpredictable immune-related adverse events (irAEs) remain key barriers to broader clinical success. Predicting which patients will benefit from immunotherapy, and who may experience severe irAEs, requires the precise identification and mechanistic interpretation of reliable biomarkers. Biomarkers have become indispensable to precision immuno-oncology, facilitating patient selection, dynamic efficacy monitoring, and individualized therapeutic optimization. Understanding the immunological mechanisms that drive biomarker changes and their interaction with the tumor microenvironment is fundamental for advancing the next generation of rational, mechanism-based immunotherapies. This Research Topic aims to advance the understanding of cancer immunotherapy biomarkers from mechanistic and translational perspectives. Biomarkers—including molecular, cellular, histological, and microbial indicators—reflect tumor immune contexture, therapeutic responsiveness, and disease progression. Emerging evidence points to three main categories: tumor tissue biomarkers, peripheral blood non-invasive biomarkers, and gut microbiome-associated biomarkers. Classical tissue biomarkers such as PD-L1 expression, tumor mutational burden (TMB), and microsatellite instability (MSI) are critical for patient selection, while blood- and microbiome-derived markers enable real-time, non-invasive monitoring. Together, these components constitute an integrated, multidimensional biomarker system for efficacy assessment. Pre-treatment biomarkers guide personalized therapy stratification, whereas intra- and post-treatment dynamics predict treatment outcomes, durability of response, recurrence risk, and potential irAE development. By elucidating the immunological networks and mechanisms that underlie these biomarkers, this Research Topic seeks to bridge basic immunology and clinical translation.To gather further insights into the development and application of biomarkers in cancer immunotherapy, we welcome contributions addressing—but not limited to—the following themes:• Novel immune-related biomarkers in the tumor microenvironment and peripheral blood• Mechanistic studies linking biomarker dynamics with immune activation or suppression• Predictive biomarkers of immune-related adverse events (irAEs)• Integration of diagnostic technologies such as liquid biopsy, next-generation sequencing, and multi-omics profiling• Systems immunology or biomarker-based modeling for efficacy prediction• Translational frameworks for biomarker-guided precision immunotherapyPlease note: Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic. Topic editors: Cuiling Zheng, Tao Han, Shengxi Chen Source: https://www.frontiersin.org/research-topics/82572/biomarkers-in-cancer-immunotherapy-mechanisms-efficacy-prediction-and-irae-management