In vitro efficacy of a first‐generation valosin‐containing protein inhibitor (CB‐5083) against canine lymphoma
Bibliographic record
Abstract
Valosin-containing protein (VCP), through its critical role in the maintenance of protein homeostasis, is a promising target for the treatment of several malignancies, including canine lymphoma. CB-5083, a first-in-class VCP inhibitor, exerts cytotoxicity through the induction of irreversible proteotoxic stress and possesses a broad spectrum of anticancer activity. Here, we determined the cytotoxicity CB-5083 in canine lymphoma cells and its mechanism of action in vitro. Canine lymphoma cell lines were treated with varying concentrations of CB-5083 and assessed for viability by trypan blue exclusion and apoptosis by caspase activity assays. The mechanism of CB-5083 action was determined by immunoblotting and RT-qPCR analyses of Lys48 ubiquitination and markers of ER stress (DDIT3), autophagy (SQSTM1, MAP1LC3A) and DNA damage (γH2AX). Unfolded protein response markers were also evaluated by immunoblotting (eIF2α, P-eIF2α) and RT-qPCR (ATF4). CB-5083 treatment resulted in preferential cytotoxicity in canine lymphoma cell lines over control peripheral blood mononuclear cells. CB-5083 rapidly disrupted the ubiquitin-dependent protein degradation system, inducing sustained ER stress as indicated by a dramatic increase in DDIT3. Activation of the unfolded protein response occurred through the increase eIF2α phosphorylation and increased transcription of ATF4, but did not re-establish protein homeostasis. Cells rapidly underwent apoptosis through activation of the caspase cascade. These results further validate VCP as an attractive target for the treatment of canine lymphoma and identify CB-5083 as a novel therapy with clinical potential for this malignancy.
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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".