NK Cell Adoptive Transfer Suppresses Metastasis and Prolongs Survival in Pancreatic Cancer

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Abstract

Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest malignancies, with metastatic disease accounting for nearly 90% of these deaths and no therapies that effectively prevent metastatic progression. Here, we identify natural killer (NK) cells as central regulators of metastatic competence in PDAC, actively constraining dissemination and preventing tumor-intrinsic reprogramming toward a metastasis-permissive state. Genetic and antibody-mediated NK cell depletion markedly increased liver and lung metastasis. In vivo tracking of fluorescently labeled PDAC cells revealed that NK cells restrict multiple early steps of the metastatic cascade, limiting intravasation, promoting clearance of circulating tumor cells (CTCs), and suppressing survival and seeding at distant sites. Mechanistically, NK cell loss induced coordinated remodeling of both the tumor microenvironment and tumor cell state. NK depletion reduced myeloid lineage diversity while enhancing phagocytic polarization and drove tumor-intrinsic activation of epithelial-mesenchymal transition (EMT) and metastasis-associated transcriptional programs, indicating that NK surveillance actively restrains metastatic plasticity. Consistent with this model, aggressive human basal-like PDACs exhibited reduced NK cell infiltration and enrichment of EMT-associated gene signatures. Therapeutically, adoptive NK cell transfer reversed these phenotypes across immunocompetent and immunodeficient models, reducing CTC burden, suppressing metastatic outgrowth, and extending survival. In patient-derived xenograft (PDX) models, systemic NK-92 cell administration reduced metastatic recurrence following primary tumor resection. Moreover, NK-92 cells demonstrated robust cytotoxicity against patient-derived PDAC organoids. Concordantly, human tumors enriched for activated or activation-prone NK cell states were associated with improved clinical outcomes. Collectively, these findings redefine NK cells as central regulators of metastatic competence in PDAC and provide a mechanistic and translational framework for NK-based immunotherapy aimed at preventing metastatic progression.

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  1. This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/20787998.

    Major Issues

    1- Heterogeneous and insufficiently defined experimental backgrounds The study employs multiple and inconsistently defined genetic and immune backgrounds across experiments (including KPC and "wild-type" controls), without clear specification of the exact wild-type strain or its immunological baseline. In addition, the KPC model itself represents a complex and partially uncontrolled immune background, which introduces variability in tumor–immune interactions. This lack of clarity and standardization limits interpretability and cross-experimental comparability.

    2- Confounded immune backgrounds in key comparative analyses Critical comparisons rely on KPC versus KPC Rag2⁻/⁻ Il2rg⁻/⁻ models, which differ not only in NK cell presence but also in broad adaptive and innate immune compartments. This creates a highly confounded immune context, where observed phenotypes cannot be specifically attributed to NK cell activity due to simultaneous disruption of multiple immune lineages and systemic immune remodeling.

    3- Endpoint-based rather than longitudinal analysis of metastasis progression Metastatic outcomes are primarily assessed at terminal endpoints, without continuous or stage-resolved tracking of metastatic progression (e.g., CTC dynamics, seeding efficiency, early micrometastasis formation, and outgrowth). This limits the ability to define the temporal window and causal sequence of NK cell-mediated effects during the metastatic cascade.

    Minor Issues

    1- Limited NK cell functional profiling NK cell activity is not comprehensively characterized across models. Key functional readouts such as CD107a degranulation, cytokine production (e.g., IFN-γ, TNF-α), and exhaustion markers (e.g., PD-1, NKG2A) are not consistently assessed.

    2- Heterogeneity in experimental model usage across assays Different experimental readouts are performed using non-uniform genetic backgrounds (e.g., KPC versus immunodeficient strains), which may introduce variability and reduce cross-assay consistency.

    3- Partial mechanistic validation in in vitro systems Co-culture experiments (e.g., NK-92 or organoid systems) support cytotoxic effects but do not fully resolve the mechanistic basis of proposed pathways, which remain largely descriptive rather than causally validated.

    4- Lack of integrated multi-parametric analysis The study does not integrate key variables (e.g., CTC burden, NK cell functional state, transcriptomic signatures, and metastatic load) into a unified analytical framework to strengthen systems-level interpretation.

    5- Inconsistent spatial immune profiling Spatial characterization of immune infiltration is not uniformly applied across models and timepoints, limiting insight into spatial-temporal immune dynamics within the tumor microenvironment.

    Competing interests

    The author declares that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The author declares that they used generative AI to come up with new ideas for their review.