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Updated: Sep 12, 2026

Monitoring PD-1-Blocking Antibodies Bound to T Cells Derived from a Drop of Peripheral Blood
Published on: February 5, 2020
Peripheral blood biomarkers in PD-1/PD-L1 immunotherapy: distinguishing predictive from prognostic biomarkers
Xuejun Guo1,2, Yanhui Wei3, Zhaoxu Miao1
1Department of Hematology, Puyang Oilfield General Hospital Affiliated to Henan Medical University, Puyang, Henan, China.
Abstract:
Immune checkpoint inhibitors targeting the programmed cell death protein 1 (PD-1) and programmed death ligand 1 (PD-L1) axis have transformed cancer therapy, yet reliable biomarkers for accurately predicting therapeutic benefit remain limited. Peripheral blood biomarkers have emerged as attractive candidates because of their minimally invasive accessibility, feasibility for serial monitoring, and potential to capture dynamic systemic immune responses during treatment. However, their clinical translation has been hindered by inconsistent findings, biological heterogeneity, and the frequent conflation of prognostic associations with true predictive value. Many commonly reported biomarkers, including circulating tumor DNA (ctDNA), blood-based tumor mutational burden (bTMB), inflammatory indices, and conventional serum markers, primarily reflect tumor burden, systemic inflammation, or host physiological status rather than genuine sensitivity to PD-1/PD-L1 blockade. In contrast, immune cell-derived biomarkers, particularly dynamic indicators of CD8+ T-cell activation and immune reinvigoration, offer stronger mechanistic relevance to checkpoint inhibitor responsiveness, although their predictive utility remains highly context dependent. In this review, we critically evaluate peripheral blood biomarkers using a mechanistically informed framework to distinguish predictive from prognostic biomarkers, integrating evidence from tumor-derived biomarkers, immune cell phenotyping, soluble inflammatory mediators, emerging immune repertoire and extracellular vesicle (EV) biomarkers, and composite longitudinal models. We further discuss translational barriers, clinical implementation challenges, and future priorities for biomarker development, aiming to provide a more rigorous framework for biomarker-guided precision immunotherapy.
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