Expression of Glycosylphosphatidylinositol-Anchored CD59 on Target Cells Enhances Human NK Cell-Mediated Cytotoxicity
Bibliographic record
Abstract
NK cell-mediated cytotoxicity of target cells is the result of a balance between the activating and inhibitory signals provided by their respective ligand-receptor interactions. In our current study, we have investigated the significance of CD59 on human target cells in modulating this process. A range of CD59 site-specific Abs were used in NK cytotoxicity blocking studies against the CD59-expressing K562 target cell line. Significantly reduced cytotoxicity was observed in the presence of Abs previously shown to lack blocking capacity for C-mediated lysis. We investigated the consequences for alternative membrane attachment modalities, namely bis-myristoylated-peptidyl (BiMP) and GPI anchoring, on CD59-negative U937 cells. Expression of GPI-anchored CD59 either via transfection or incorporation rendered U937 targets more susceptible to NK cytotoxicity, whereas incorporation of CD59 via a BiMP anchor to similar levels did not alter susceptibility to NK cytotoxicity. Localization of both BiMP- and GPI-anchored CD59 proteins was shown to be within the lipid raft microdomain. A role for the GPI anchor and independence from glycosylation status was confirmed by expression of transmembrane-anchored CD59 or unglycosylated CD59 and by testing in NK cytotoxicity assays. To investigate mechanisms, we compared the signaling capacity of the various forms of expressed and incorporated CD59 following Ab cross-linking in calcium flux assays. GPI-anchored CD59, with or without glycosylation, mediated activation events, whereas CD59 forms lacking the GPI anchor did not. The data show that the increased susceptibility of target cells expressing CD59 to NK cytotoxicity requires GPI anchor-mediating signaling events, likely mediated by interactions between GPI-anchored CD59 on targets and NK receptors.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".