ReviewMolecular cancer2026
Transcriptional networks weaving natural killer anti-tumor immune response.
Review in Molecular cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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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Authors and funding
4 authors.
Funding
Abstract
backgroundNatural killer cells (NKs) are critical effectors of innate immune surveillance, capable of eliminating target cells without prior antigen sensitization. The crucial role of NKs in cancer immunity has largely been highlighted in both hematological and solid tumors. Besides, NK-based cell therapies have gained momentum as a compelling alternative to T cell-based approaches, due to their off-the-shelf availability and lower risk of toxicity. Still, the intrinsic molecular mechanisms driving NK anti-tumor efficacy in different tumor contexts are poorly described, drastically impairing their clinical exploitation.
aimsThis review aims to provide a comprehensive overview of the transcriptional networks defining each step of NK anti-tumor response, from tissue recruitment to target recognition and cytotoxic activation. The molecular mechanisms triggering NK dysfunction in the tumor microenvironment are also highlighted from a transcriptional perspective. The described time- and context-dependent transcriptional machinery is characterized by a constant interplay between activators and repressors, which integrates and balances signals deriving from the surrounding tumor ecosystem.
conclusionsConsidering the relevance of transcription factors in controlling NK functions, their potential exploitation as novel therapeutic targets, through either pharmacological approaches or genome editing, is a new opportunity for cancer treatment.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.