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Life sciences · Journal article
Biomarker Research · October 31, 2026
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The advent of immunotherapy has profoundly transformed the therapeutic landscape of hematologic malignancies. A broad range of immune-based strategies, including immune checkpoint inhibitors and adoptive cell therapies based on both T cells and natural killer (NK) cells, have achieved unprecedented clinical outcomes in several lymphoid and myeloid neoplasms. Emerging approaches such as genetically engineered immune cells, including chimeric antigen receptor (CAR)-modified T and NK cells, are further expanding therapeutic opportunities. However, substantial heterogeneity in treatment response remains a major challenge, with a significant proportion of patients experiencing primary resistance, relapse, or severe immune-related toxicities. Accurate identification of predictive and prognostic biomarkers is therefore essential to optimize patient selection, improve therapeutic efficacy, and minimize treatment-related toxicity. Numerous biological parameters have been investigated, including clinical prognostic scores, systemic inflammatory indices, tumor burden markers, immune-cell subsets, cytokine profiles, genetic and molecular alterations, and features of the tumor microenvironment. Emerging evidence indicates that both host-related factors and tumor-intrinsic characteristics shape therapeutic responses to immunotherapy across hematologic cancers. Among the most promising biomarkers are inflammatory indices derived from peripheral blood counts, such as the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, systemic immune-inflammation index, prognostic nutritional index, and Glasgow Prognostic Score. In parallel, immune-monitoring approaches assessing the functional competence, phenotype, and activation status of both T and NK cells, together with cytokine signatures, immune checkpoint expression, and other markers of immune competence, are increasingly recognized as valuable tools for predicting therapeutic response, resistance, and immune-related toxicity. This review summarizes the current evidence on prognostic scores and biomarkers associated with immunotherapy outcomes in hematologic malignancies. We discuss their biological rationale, clinical relevance, current limitations, and potential integration into contemporary treatment strategies. Finally, we highlight emerging perspectives, including multi-omics profiling, artificial intelligence-driven predictive models, and dynamic biomarker-guided approaches, which are expected to advance precision immuno-oncology and enable increasingly personalized immune-based treatment algorithms.