ReviewInternational journal of molecular sciences2026
Beyond PD-1/PD-L1: Reprogramming the Gynecologic Tumor Microenvironment by Targeting TIGIT and Myeloid Suppression.
Review in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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3 authors.
Funding
Abstract
Immune checkpoint inhibitors targeting the PD-1 (Programmed Cell Death Protein 1)/PD-L1 (Programmed Death-Ligand 1) axis have transformed cancer therapeutics, yet their efficacy in gynecologic malignancies particularly high-grade serous ovarian carcinoma remains disappointingly limited. This therapeutic resistance stems from a highly orchestrated, multidimensional immunosuppressive tumor microenvironment (TME) characterized by the convergent actions of regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), and an inhibitory cytokine network (IL-10, TGF-β, VEGF). Emerging evidence positions TIGIT (T-cell immunoreceptor with immunoglobulin and ITIM domain) as a master checkpoint integrator that coordinately regulates CD8+ T-cell exhaustion, NK-cell dysfunction, and Treg-mediated suppression. Dual blockade of PD-1 and TIGIT represents a mechanistically rational strategy to dismantle this immunosuppressive fortress. This review synthesizes current understanding of the gynecologic TME architecture, delineates the molecular and cellular basis for TIGIT/PD-1 synergy, critically evaluates ongoing clinical translation efforts, and proposes an integrative framework leveraging spatial transcriptomics, single-cell resolution immunoprofiling, and patient-derived experimental models to accelerate biomarker-driven therapeutic development.
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