Decoding ADGRE5: How Proteolytic Cleavage and Mechanical Forces Unleash Cellular Signals
Bibliographic record
Abstract
The adhesion G protein-coupled receptor ADGRE5/CD97 is upregulated in many cancers, representing a potential drug target in oncology/immuno-oncology. Yet, ADGRE5's activation and signaling mechanisms remain poorly understood. Here, we used enhanced bystander bioluminescence resonance energy transfer (ebBRET)-based biosensors and three strategies to characterize human (h) ADGRE5 signaling. First, a synthetic tobacco etch virus (TEV) protease-cleavable receptor chimera enabling controlled tethered agonist (TA) exposure at the GPCR proteolysis site (GPS) revealed signaling through Gα12 and Gα13, along with the recruitment of β-Arrestins 1/2 (β-Arrs). Second, we investigated WT hADGRE5 signaling elicited by Gingipain K (Kgp), an endopeptidase that cleaves hADGRE5 upstream of the GAIN domain. Kgp mirrored TEV-induced signaling but also promoted Gαz and Gα11 activity. The abolition of hADGRE5's GPS did not block Kgp-induced receptor activation, revealing a GPS cleavage-independent mechanism of action. Finally, we developed an assay to study hADGRE5 mechanical stimulation (MS) using β-Arr2 as a readout. MS promoted β-Arr2 recruitment in hADGRE5-expressing cells, and this response was lost upon abolition of the GPS. A neutralizing antibody to the hADGRE5 ligand CD55 significantly dampened MS-induced β-Arr2 engagement. Overall, this study advances our understanding of hADGRE5's signaling and highlights the receptor's plasticity in activating pathways via both GPS cleavage-dependent and -independent mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".