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The Prognostic Value of Ephrin Type‐A2 Receptor (EPHA2) and Ki67 in Renal Cell Carcinoma Patients: An Immunohistochemical and Bioinformatical Approach

2019· article· en· W3176950580 on OpenAlexaff
Iman M. Talaat, Israa Okap, Samar Mohamed El Sheikh, Tamer Abou Youssif, Ibrahim Y. Hachim, Mahmood Yaseen Hachim

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldNeuroscience
TopicAxon Guidance and Neuronal Signaling
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineImmunohistochemistryRenal cell carcinomaEPH receptor A2Stage (stratigraphy)Internal medicineOncologyCancerDiseaseReceptor tyrosine kinaseEphrinPathologyReceptorBiology

Abstract

fetched live from OpenAlex

Background The incidence of renal cell carcinoma (RCC), the most common malignant renal epithelial tumour, is increasing worldwide. Patients usually present with advanced disease and mostly have unpredicted clinical behaviour. A variety of prognostic factors have been proposed as useful parameters, however many of them showed limited clinical value. Thus, the discovery of novel prognostic markers, which might help in predicting patients' outcome and additional new targets to treat this disease are still in great demand. EphA2, a receptor tyrosine kinase, was found to be overexpressed in several malignancies and its expression in different tumours was found to be associated with poor prognostic features. In addition, a group of emerging strategies was recently introduced to target this receptor and found to show anti‐tumorigenic activity in various pre‐clinical cancer models. Aim To investigate the prognostic value of EphA2 expression in RCC patients and its association with other clinicopathological parameters as well as Ki67 expression, which is a well‐known proliferative and prognostic marker. Materials and Methods The expression of EphA2 and Ki67 was investigated immunohistochemically, and the results were correlated with the different clinicopathological parameters in 50 primary tumour blocks obtained from RCC cases surgically managed in the Urology Department, Alexandria University Main Hospital, during the period (2012–2015). In addition, the association between the EphA2 mRNA expression and the tumour stage as well as the patient outcome was also evaluated using two large publicly available databases. Results Our results showed a significant association between EphA2 expression and the tumour size, the nuclear grade, the tumour stage, the patient's outcome and the Ki‐67 expression (P < 0.05 for all). The same trend was also observed with EphA2 mRNA expression using larger patients' cohorts in two publicly available databases. Notably, EphA2 protein expression showed higher levels of co‐expression with the proliferative marker Ki67. Conclusion We concluded that higher expression of EphA2 and Ki67 in tumour tissues predicts a locally aggressive behaviour and poor outcome of RCC patients. Moreover, our results give a rationale for the potential benefits of using novel therapeutic strategies with the aim of targeting EphA2 receptor in RCC that might help in improving their outcome. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.015
GPT teacher head0.226
Teacher spread0.212 · 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 designObservational
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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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