Prostate cancer-derived anti-GRP78 autoantibodies compromise the blood-brain barrier and accelerate atherosclerosis progression <i>in vivo</i>.
Bibliographic record
Abstract
205 Background: Pathological conditions of prostate cancer (PCa) drive the translocation of the endoplasmic reticulum-resident chaperone, GRP78, to the cell surface (cs) where it acts as an antigenic protein with signaling properties. In PCa, csGRP78 drives the production of anti-GRP78 autoantibodies (AutoAbs) that engage csGRP78 and promote PCa survival/progression. New studies now demonstrate csGRP78 expression on endothelial cells (EC) that line the arterial vasculature and the blood-brain barrier (BBB) suggesting that these AutoAbs can affect other systems in the body. Based on this, we investigated how the engagement of anti-GRP78 AutoAbs to csGRP78 on EC can contribute to EC-dysfunction that can promote atherosclerosis and compromise the integrity of the BBB. Methods: Anti-GRP78 AutoAbs were purified from PCa patients (St. Joseph’s Healthcare Hamilton); human aortic EC and the ApoE -/- mouse model were used for in vitro and in vivo investigations, respectively. EC or mice were treated with anti-GRP78 AutoAbs or IgG control (60µg/mL); EC-dysfunction was investigated by measuring attachment protein expression, in vitro. In vivo evaluation was carried out by studying atherosclerotic plaque progression (immunohistochemistry; aorta); the BBB integrity was examined using the Evans Blue dye. Results: Mice injected with anti-GRP78 AutoAbs, and not human IgG, demonstrated larger atherosclerotic plaque volume and hallmarks of a leaky BBB. In terms of a mechanism, in vitro studies demonstrated that treating EC with anti-GRP78 AutoAbs resulted in activation of the NFκB pathway that led to increased expression of attachment proteins. All these effects were reversed by using a recombinant molecule that interfere with the binding of the AutoAb to csGRP78. Conclusions: We have identified anti-GRP78 AutoAb as a driver of EC-dysfunction that promote atherosclerotic plaque progression and damage to the BBB. Our results indicate that interfering with anti-GRP78 AutoAb:csGRP78 complex can reverse the pathological effects of the AutoAbs. This novel data suggests that patient-derived anti-GRP78 autoantibodies systemically drive pathologies, other than cancer, in vivo.
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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) | 0.001 | 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".