Hypoxia Increases Tumor Cell Shedding of MHC Class I Chain-Related Molecule: Role of Nitric Oxide
Bibliographic record
Abstract
The MHC class I chain-related (MIC) molecules play important roles in tumor immune surveillance through their interaction with the NKG2D receptor on natural killer and cytotoxic T cells. Thus, shedding of the MIC molecules from the tumor cell membrane represents a potential mechanism of escape from NKG2D-mediated immune surveillance. Tumor hypoxia is associated with a poor clinical outcome for cancer patients. We show that hypoxia contributes to tumor cell shedding of MIC through a mechanism involving impaired nitric oxide (NO) signaling. Whereas hypoxia increased MIC shedding in human prostate cancer cells, activation of NO signaling inhibited hypoxia-mediated MIC shedding. Similar to incubation in hypoxia, pharmacologic inhibition of endogenous NO signaling increased MIC shedding. Parallel studies showed hypoxia-mediated tumor cell resistance to lysis by interleukin 2-activated peripheral blood lymphocytes (PBL) and NO-mediated attenuation of this resistance to lysis. Inhibition of NO production also led to resistance to PBL-mediated lysis. Interference of MIC-NKG2D interaction with a blocking anti-MIC antibody abrogated the effect of hypoxia and NO signaling on tumor cell sensitivity to PBL-mediated lysis. Finally, continuous transdermal delivery of the NO mimetic glyceryl trinitrate (7.3 mug/h) attenuated the growth of xenografted MIC-expressing human prostate tumors. These findings suggest that the hypoxic tumor microenvironment contributes to resistance to immune surveillance and that activation of NO signaling is of potential use in cancer immunotherapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".