Targeting HSP70 and GRP78 in canine osteosarcoma cells in combination with doxorubicin chemotherapy
Bibliographic record
Abstract
Heat shock proteins (HSPs) are molecular chaperones subdivided into several families based on their molecular weight. Due to their cytoprotective roles, these proteins may help protect cancer cells against chemotherapy-induced cell death. Investigation into the biologic activity of HSPs in a variety of cancers including primary bone tumors, such as osteosarcoma (OSA), is of great interest. Both human and canine OSA tumor samples have aberrant production of HSP70. This study assessed the response of canine OSA cells to inhibition of HSP70 and GRP78 by the ATP-mimetic VER-155008 and whether this treatment strategy could sensitize cells to doxorubicin chemotherapy. Single-agent VER-155008 treatment decreased cellular viability and clonogenic survival and increased apoptosis in canine OSA cell lines. However, combination schedules with doxorubicin after pretreatment with VER-155008 did not improve inhibition of cellular viability, apoptosis, or clonogenic survival. Treatment with VER-155008 prior to chemotherapy resulted in an upregulation of target proteins HSP70 and GRP78 in addition to the co-chaperone proteins Herp, C/EBP homologous transcription protein (CHOP), and BAG-1. The increased GRP78 was more cytoplasmic in location compared to untreated cells. Single-agent treatment also revealed a dose-dependent reduction in activated and total Akt. Based on these results, targeting GRP78 and HSP70 may have biologic activity in canine osteosarcoma. Further studies are required to determine if and how this strategy may impact the response of osteosarcoma cells to chemotherapy.
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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) | 0.001 | 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) | 0.001 | 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".