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Record W2918038432 · doi:10.1002/jcb.28415

Exonuclease 1 expression is associated with clinical progression, metastasis, and survival prognosis of prostate cancer

2019· article· en· W2918038432 on OpenAlexaff
Fei Luo, Yuzhuo Wang, Dong Lin, Jian Li, Kuo Yang

Bibliographic record

VenueJournal of Cellular Biochemistry · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsVancouver General HospitalBC Cancer Agency
FundersNational Natural Science Foundation of China
KeywordsProstate cancerMetastasisCancerCancer researchOncologyProstateMedicineInternal medicine

Abstract

fetched live from OpenAlex

Prostate cancer (PCa) is the most prevalent malignancy and the second leading cause of cancer-related deaths in the male population in western countries, and we explored the association between exonuclease 1 (EXO1) expression and clinical progression, metastasis (Met), and survival prognosis of PCa. EXO1 expression of high/low-metastatic patient-derived xenografts model was investigated and clinical correlation and prognosis outcomes were validated. EXO1 in high-metastatic models was significantly increased compared with low-metastatic lines. In memorial sloan-kettering cancer center (MSKCC) cohort, EXO1 expression positively correlated with PCa Met, and patients with high EXO1 had poor biochemical recurrence-free survival in primary PCa cohort. Validation in The Cancer Genome Atlas primary cohort indicated EXO1 expression was significantly associated with lymph node Met and disease-free survival. The overexpression of EXO1 is significantly associated with PCa poor survival outcome, and is a promising biomarker for PCa, especially for primary PCa. A prospective study is clearly needed to validate these findings.

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: Observational · Consensus signal: Observational
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 head0.012
GPT teacher head0.284
Teacher spread0.272 · 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

Citations37
Published2019
Admission routes1
Has abstractyes

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