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Updated: Sep 25, 2026

Visualizing Surface T-Cell Receptor Dynamics Four-Dimensionally Using Lattice Light-Sheet Microscopy
Published on: January 30, 2020
Molecular Architecture and Clinical Landscape of Immune Checkpoint Receptors and Ligands
Milena Czosnek1,2, Agata Sowa1,2, Łucja Rolek1,2
1Department of Experimental Immunology, Medical University of Lublin, 20-093 Lublin, Poland.
Abstract:
Immune checkpoints (ICPs) are essential regulators of immune homeostasis, maintaining the balance between effective immune responses and tolerance to self-antigens. Dysregulation of ICP signaling may contribute to impaired immune surveillance, immune evasion, chronic inflammation, autoimmunity, persistent infections, and tumor progression. Consequently, ICP molecules are increasingly recognized not only as therapeutic targets but also as potential diagnostic, prognostic, predictive, and treatment-monitoring biomarkers. This review provides a comprehensive overview of the biological functions, signaling mechanisms, and clinical significance of major co-inhibitory and co-stimulatory ICP pathways, including PD-1/PD-L1/PD-L2, CTLA-4/CD28/CD80/CD86, LAG-3, TIM-3, TIGIT, BTLA, VISTA, ICOS, OX40, 4-1BB, GITR, CD27, CD40, and CD2, together with their corresponding ligands. Particular emphasis is placed on their biomarker potential in cancer and immune-mediated diseases. In addition, the review presents a bioinformatic characterization of ICP receptors and ligands based primarily on data available in UniProtKB and complementary bioinformatic resources. The analysis includes protein sequence length, molecular weight, theoretical isoelectric point, amino acid composition, subcellular localization, conserved and functional domains, protein family classification, post-translational modifications, isoforms, and selected structural features. Collectively, the available evidence indicates that ICPs constitute a structurally and functionally diverse group of immunoregulatory molecules with substantial biomarker potential. Integrating their molecular, structural, functional, and bioinformatic characteristics may improve disease classification, prognosis, patient stratification, treatment selection, and therapeutic monitoring. Such an integrated approach may also support the identification of novel biomarkers and therapeutic targets and contribute to the further development of precision and personalized medicine.
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