Alternative Splice Transcripts for MHC Class I–like MICA Encode Novel NKG2D Ligands with Agonist or Antagonist Functions
Bibliographic record
Abstract
MHC class I chain-related proteins A and B (MICA and MICB) and UL16-binding proteins are ligands of the activating NKG2D receptor involved in cancer and immune surveillance of infection. Structurally, MICA/B proteins contain an α3 domain, whereas UL16-binding proteins do not. We identified novel alternative splice transcripts for MICA encoding five novel MICA isoforms: MICA-A, -B1, -B2, -C, and -D. Alternative splicing associates with MICA*015 and *017 and results from a point deletion (G) in the 5' splice donor site of MICA intron 4 leading to exon 3 and exon 4 skipping and/or deletions. These changes delete the α3 domain in all isoforms, and the α2 domain in the majority of isoforms (A, B1, C, and D). Endothelial and hematopoietic cells contained endogenous alternative splice transcripts and isoforms. MICA-B1, -B2, and -D bound NKG2D by surface plasmon resonance and were expressed at the cell surface. Functionally, MICA-B2 contains two extracellular domains (α1 and α2) and is a novel potent agonist ligand for NKG2D. We found that MICA-D is a new truncated form of MICA with weak affinity for NKG2D despite lacking α2 and α3 domains. MICA-D may functionally impair NKG2D activation by competing with full-length MICA or MICA-B2 for NKG2D engagement. Our study established NKG2D binding for recombinant MICA-B1 but found no function for this isoform. New truncated MICA isoforms exhibit a range of functions that may drive unexpected immune mechanisms and provide new tools for 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) | 0.002 | 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".