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Record W1672542447 · doi:10.1158/1538-7445.am2015-4963

Abstract 4963: Prognostic significance of the expression of nuclear EIF5A2 in human melanoma

2015· article· en· W1672542447 on OpenAlexaff
Shahram Khosravi, Magdalena Martinka, Christopher J. Ong

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsMelanomaMedicineNodular melanomaTissue microarrayCancer researchCancerPathologyImmunohistochemistryOncogeneOncologyInternal medicineCell cycle

Abstract

fetched live from OpenAlex

Abstract Eukaryotic translation initiation factor 5A2 (EIF5A2) is an oncogene that is upregulated in several different cancers. We previously showed that cytoplasmic EIF5A2 expression increases with melanoma progression and inversely correlates with melanoma patient survival. In this study, we used immunohistochemistry and tissue microarray (TMA) using a large number of melanocytic lesions (n = 459) to examine the expression profile of nuclear EIF5A2 in melanoma progression in addition to the correlation between nuclear EIF5A2 expression and melanoma patient survival. We found that nuclear EIF5A2 expression was significantly upregulated in primary melanomas compared with normal nevi and dysplastic nevi, as well as in metastatic melanomas compared with primary melanomas, normal nevi and dysplastic nevi. Nuclear EIF5A2 expression had a significant inverse correlation with overall and disease-specific 5-year survival of all and primary melanoma patients. Nuclear EIF5A2 expression was also significantly correlated with melanoma thickness and AJCC stages, suggesting the possible role of nuclear EIF5A2 in melanoma cell invasion. We then investigated the correlation between the expression of nuclear EIF5A2 and MMP-2 which is one of the important factors for promoting cancer cell invasion. Nuclear EIF5A2 expression and strong MMP-2 expression were directly correlated as well, and their concurrent expression was significantly associated with worse overall and disease-specific 5-year survival of all and primary melanoma patients. We also studied the correlation between nuclear and cytoplasmic EIF5A2 expression and found that they were significantly correlated, and simultaneous expression of both was significantly associated with poor overall and diseases-specific 5-year survival of all and primary melanoma patients. Multivariate Cox regression analysis revealed that nuclear expression of EIF5A2 was an adverse independent prognostic factor for melanoma patients. In conclusion, we for the first time demonstrated the nuclear expression of EIF5A2 as an independent prognostic marker in melanoma and its role in melanoma progression and patient survival. As a result, nuclear EIF5A2 may have the potential to serve as a therapeutic marker for melanoma. Citation Format: Shahram Khosravi, Magdalena Martinka, Christopher J Ong. Prognostic significance of the expression of nuclear EIF5A2 in human melanoma. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4963. doi:10.1158/1538-7445.AM2015-4963

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)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.157
GPT teacher head0.438
Teacher spread0.280 · 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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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