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Record W7036944298

A comparative study of the role EphA2 performs in canine and human osteosarcoma

2023· dissertation· en· W7036944298 on OpenAlexfundno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Languageen
FieldNeuroscience
TopicAxon Guidance and Neuronal Signaling
Canadian institutionsnot available
FundersSaskatchewan Health Research Foundation
KeywordsOsteosarcomaEPH receptor A2Erythropoietin-producing hepatocellular (Eph) receptorGene silencingCancerReceptorDownregulation and upregulationEphrin
DOInot available

Abstract

fetched live from OpenAlex

Osteosarcoma is an aggressive bone cancer in both humans and dogs with a high rate of pulmonary metastasis. Despite the current treatment options including tumor removal or limb amputation combined with chemotherapy, the survival time in both species is low. This highlights a need for more effective treatment options for this disease. Accumulating evidence suggests various biological and clinical similarities of osteosarcoma in humans and dogs, and therefore, this disease represents a suitable model for comparative oncological research with benefits to both parties. The EphA2 receptor, a member of the Eph family of receptor tyrosine kinases, has been shown to be upregulated in different human malignancies and its function has been linked to poor prognosis and tumor aggressive properties. Accordingly, this receptor is emerging as a potential target for the design of novel cancer therapies based on the inhibition of this molecule. However, the role of this receptor in osteosarcoma biology has been poorly studied, and to my knowledge, this receptor has not been studied in canine malignancies. My aim in this study was first to evaluate the expression of EphA2 in both canine and human osteosarcoma cells when compared to normal osteoblasts, and then to assess if silencing EphA2 results in significant alterations in the malignant characteristics of the osteosarcoma cells, including proliferation, migration, invasion, and drug sensitivity. Here, I present my novel findings, demonstrating that EphA2 is overexpressed in multiple canine and human osteosarcoma cell lines. Moreover, stably silencing EphA2 by specific shRNAs significantly and consistently decreased proliferation and migration of both human and canine osteosarcoma cells. I also showed a significant decrease in canine and human osteosarcoma invasion after EphA2 silencing when tested using a Matrigel invasion assay. In addition, I found that silencing EphA2 increased the sensitivity of both human and canine osteosarcoma cells to cisplatin, a common osteosarcoma treatment. Finally, the tumor development capability of osteosarcoma cells after EphA2 silencing was tested in two murine xenograft models of canine osteosarcoma. I observed that EphA2 silencing significantly reduced osteosarcoma tumour growth when compared to that of non-silenced control tumors. Taken together, this work suggests that EphA2 supports the malignant behaviors of both human and dog osteosarcoma, and that the inhibition of EphA2 alone or in combination with chemotherapy could conceptually benefit osteosarcoma cancer patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.019
GPT teacher head0.217
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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