CIN85 Modulates the Down-regulation of FcγRIIa Expression and Function by c-Cbl in a PKC-dependent Manner in Human Neutrophils
Bibliographic record
Abstract
We previously described a non-classical mechanism that arrests FcγRIIa signaling in human neutrophils once engaged by immune complexes or opsonized pathogens. The engagement of FcγRIIa leads to its ubiquitination by the ubiquitin ligase c-Cbl and degradation by the proteasome. Herein, we further examined some of the events regulating this novel pathway. The adaptor protein CIN85 was described in other systems to be involved in the regulation of the c-Cbl-dependent pathway. We found that CIN85 is expressed in human neutrophils and that it translocates like c-Cbl from the cytosol to the plasma membrane following receptor cross-linking. CIN85 was also recruited to the same subset of high density detergent-resistant membrane fractions in which stimulated FcγRIIa partitioned with c-Cbl. The integrity of these microdomains is essential to the FcγRIIa degradation process because the cholesterol-depleting agent methyl-β-cyclodextrin inhibits this event. Silencing the expression of CIN85 by siRNA in dibutyryl cyclic AMP-differentiated PLB 985 cells prevented FcγRIIa degradation and increased IgG-mediated phagocytosis. Confocal microscopy revealed that the presence of CIN85 is essential to the proper sorting of FcγRIIa during endocytosis. We also provide direct evidence that CIN85 is a substrate of serine/threonine kinase PKCs. Classical PKCs positively regulate FcγRIIa ubiquitination and degradation because these events were inhibited by Gö6976, a classical PKC inhibitor. We conclude that the ubiquitination and degradation of stimulated FcγRIIa mediated by c-Cbl are positively regulated by the adaptor protein CIN85 in a PKC-dependent manner and that these events contribute to the termination of FcγRIIa signaling.
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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".