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Mechanisms Driving Neutrophil-Induced T-cell Immunoparalysis in Ovarian Cancer.

ABSTRACT: T-cell activation and expansion in the tumor microenvironment (TME) are critical for antitumor immunity. Neutrophils in the TME acquire a complement-dependent T-cell suppressor phenotype that is characterized by inhibition of T-cell proliferation and activation through mechanisms distinct from those of myeloid-derived suppressor cells. In this study, we used ascites fluid supernatants (ASC) from patients with ovarian cancer as an authentic component of the TME to evaluate the effects of ASC on neutrophil function and mechanisms for neutrophil-driven immune suppression. ASC prolonged neutrophil life span, decreased neutrophil density, and induced nuclear hypersegmentation. Mass cytometry analysis showed that ASC induced 15 distinct neutrophil clusters. ASC stimulated complement deposition and signaling in neutrophils, resulting in surface mobilization of granule constituents, including NADPH oxidase. NADPH oxidase activation and phosphatidylserine signaling were required for neutrophil suppressor function, although we did not observe a direct role of extracellular reactive oxygen species in inhibiting T-cell proliferation. Postoperative surgical drainage fluid also induced a complement-dependent neutrophil suppressor phenotype, pointing to this effect as a general response to injury. Like circulating lymphocytes, ASC-activated neutrophils caused complement-dependent suppression of tumor-associated lymphocytes. ASC-activated neutrophils adhered to T cells and caused trogocytosis of T-cell membranes. These injury and signaling cues resulted in T-cell immunoparalysis characterized by impaired NFAT translocation, IL2 production, glucose uptake, mitochondrial function, and mTOR activation. Our results demonstrate that complement-dependent priming of neutrophil effector functions in the TME induces a T-cell nonresponsiveness distinct from established checkpoint pathways and identify targets for immunotherapy.See related Spotlight by Cassatella, p. 725.

SUBMITTER: Emmons TR

PROVIDER: S-EPMC8287091 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionNeutrophils can generate extracellular net-like structures by releasing their DNA-histone complexes and antimicrobial peptides, which is called neutrophil extracellular traps (NETs). Various stimuli can induce NET formation. In particular, neutrophils and NET formation are abundant in tumor tissue. This study investigated how cancer cells induce NET formation and whether this NET formation promotes plasma thrombin generation and cancer progression.MethodsInduction of NET formation by a pancreatic cancer cell line (AsPC-1) was assessed by measuring the histone-DNA complex level. The endogenous thrombin potential (ETP) was measured by thrombin generation assay. In vitro migration, invasion, and tubule formation assays were performed. The circulating levels of NET markers and hypercoagulability markers were assessed in 62 patients with pancreatobiliary malignancy and 30 healthy controls.ResultsAsPC-1 significantly induced NET formation in a dose-dependent manner. Conditioned medium (CM) from AsPC-1 also induced NETs. Interestingly, NET-formation was abolished by heat-inactivated CM, but not by lipid-extracted CM, suggesting an important role of protein components. A reactive oxygen species inhibitor did not inhibit cancer cell-induced NET formation, but prostaglandin E1 (PGE1, cyclic adenosine monophosphate inducer) and antithrombin did. NETs significantly increased ETP of normal plasma. Of note, NETs promoted cancer cell migration and invasion as well as angiogenesis, which were inhibited by histone-binding agents (heparin, polysialic acid), a DNA-degrading enzyme, and Toll-like receptor neutralizing antibodies. In patients with pancreatobiliary malignancy, elevated NET markers correlated well with hypercoagulability makers.ConclusionOur findings indicate that cancer cell-induced NET formation enhances both hypercoagulability and cancer progression and suggest that inhibitors of NET formation such as PGE1 and antithrombin can be potential therapeutics to reduce both hypercoagulability and cancer progression.

Project description:Drug sensitivity prediction models for human cancer cell lines constitute important tools in identifying potential computational biomarkers for responsiveness in a pre-clinical setting. Integrating information derived from a range of heterogeneous data is crucial, but remains non-trivial, as differences in data structures may hinder fitting algorithms from assigning adequate weights to complementary information that is contained in distinct omics data. In order to counteract this effect that tends to lead to just one data type dominating supposedly multi-omics models, we developed a novel tool that enables users to train single-omics models separately in a first step and to integrate them into a multi-omics model in a second step. Extensive ablation studies are performed in order to facilitate an in-depth evaluation of the respective contributions of singular data types and of combinations thereof, effectively identifying redundancies and interdependencies between them. Moreover, the integration of the single-omics models is realized by a range of distinct classification algorithms, thus allowing for a performance comparison. Sets of molecular events and tissue types found to be related to significant shifts in drug sensitivity are returned to facilitate a comprehensive and straightforward analysis of potential computational biomarkers for drug responsiveness. Our two-step approach yields sets of actual multi-omics pan-cancer classification models that are highly predictive for a majority of drugs in the GDSC data base. In the context of targeted drugs with particular modes of action, its predictive performances compare favourably to those of classification models that incorporate multi-omics data in a simple one-step approach. Additionally, case studies demonstrate that it succeeds both in correctly identifying known key biomarkers for sensitivity towards specific drug compounds as well as in providing sets of potential candidates for additional computational biomarkers.

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Mechanisms Driving Neutrophil-Induced T-cell Immunoparalysis in Ovarian Cancer.

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