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Record W4416537000 · doi:10.1186/s12957-025-04118-0

Appraising clinicopathological and prognostic significance of circular RNA ubiquitin-associated protein 2 in human cancer

2025· article· en· W4416537000 on OpenAlexaboutno aff
Qunyan Tian, Hulalai Hader, Yihan Li, Jian Zhou

Bibliographic record

VenueWorld Journal of Surgical Oncology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCircular RNAs in diseases
Canadian institutionsnot available
FundersChina Postdoctoral Science Foundation
KeywordsSurgical oncologyHazard ratioOdds ratioConfidence intervalMetastasisCancerMeta-analysisClinical significanceFunnel plot

Abstract

fetched live from OpenAlex

BACKGROUND: Circular RNA ubiquitin-associated protein 2 (circUBAP2) is highly expressed in various human cancers and has been identified as a key contributor to cancer development and progression. We performed this study to explore the clinicopathological and prognostic significance of circUBAP2 in multiple cancers. METHODS: This meta-analysis was conducted according to PRISMA 2020 guidelines. PubMed, Web of Science, CNKI, Wanfang, ClinicalTrials.gov and BioXiv were systematically searched from inception to March 1, 2025 according to the PICO framework. Study quality was appraised using the Newcastle-Ottawa Scale and eventually a total of 12 studies with 905 participants were included. Pooled odds ratios (ORs) and hazard ratios (HRs) with 95% confidence intervals (CIs) were synthesized using fixed- or random-effects models based on heterogeneity (I² statistic) to evaluate the association of circUBAP2 with age, sex, tumor size, stage, differentiation and metastasis. The stability of the results from meta-analysis was estimated via sensitivity analysis. Begg’s funnel plots and Egger’s test were used to appraise the potential publication bias. Subgroup analysis for overall survival (OS) based on follow-up duration, tumor type, case number and survival endpoints were also performed. RESULTS: High expression of circUBAP2 was significantly related to larger tumor size (OR = 3.07, 95% CI: 1.53–6.17, P < 0.05), advanced stage (OR = 2.43, 95% CI: 1.70–3.48, P < 0.05), poor differentiation (OR = 4.47, 95% CI: 2.67–7.48, P < 0.05) and metastasis (OR = 5.77, 95% CI: 3.21–10.40, P < 0.05), but not associated with age or sex. Additionally, circUBAP2 was related to cancer survival (HR = 2.43, 95% CI: 1.96–3.03, P < 0.05), regardless of follow-up duration, tumor type, case number, and survival endpoints. Begg’s funnel plot and Egger’s test showed no publication bias. CONCLUSIONS: High expression of circUBAP2 may predict larger tumor size, poor differentiation, distant metastasis and poor outcome of cancer, highlighting the carcinogenetic role of circUBAP2 in human cancer.

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)0.020
metaresearch head score (Gemma)0.022
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0100.024
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.020
GPT teacher head0.349
Teacher spread0.328 · 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
Published2025
Admission routes1
Has abstractyes

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