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Record W4396920004 · doi:10.1016/j.heliyon.2024.e31347

The predictive value of PFKFB3 in bladder cancer prognosis

2024· article· en· W4396920004 on OpenAlexaff
Dongxu Qiu, Bin Zhao, Wenda Wang, Guoyang Zheng, Zhan Wang, Xu Wang, Yanan Li, Zhangcheng Liao, Yang Zhao, Yushi Zhang

Bibliographic record

VenueHeliyon · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversity of British Columbia
FundersPeking Union Medical CollegeNatural Science Foundation of Beijing MunicipalityPeking Union Medical College HospitalChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsPredictive valueBladder cancerCancerMedicineValue (mathematics)Internal medicineUrologyOncologyComputer scienceMachine learning

Abstract

fetched live from OpenAlex

6-phosphofructo-2-kinase/fructose-2,6-biphosphatase-3 (PFKFB3) influences cancer progression via participating in tumor aerobic glycolysis. In this study, we aimed to evaluate the prognostic significance of PFKFB3 in bladder cancer (BLCA) patients by analyzing a combination of publicly available databases, clinical patient data, and bladder tumor samples from our hospital. Single-cell and bulk RNA-seq data of bladder cancer, obtained from ENA, GEO, and TCGA databases, were utilized for our analysis. The results indicated that PFKFB3 mRNA expression was markedly elevated in bladder cancer compared to paired normal tissue. Furthermore, BLCA patients with high PFKFB3 expression exhibited a significantly worse prognosis (P < 0.05). To validate these findings, clinical data and immunohistochemistry staining were performed on specimens obtained from 89 BLCA patients who underwent radical cystectomy at either Qingdao University Affiliated Hospital or Peking Union Medical College Hospital. The findings from this verification process confirmed that high expression of PFKFB3 serves as a biomarker for predicting worse prognosis in BLCA patients (OR: 2.462, 95 % CI: 1.202-5.042, P = 0.012). To facilitate clinical application, we developed a nomogram based on four variables, including PFKFB3 expression, to predict the survival of BLCA patients. Importantly, this nomogram demonstrated a low mean prediction error of 0.03. Taken together, our findings suggest that PFKFB3 has the potential to serve as both a prognostic biomarker and a therapeutic target for BLCA 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.008
GPT teacher head0.265
Teacher spread0.257 · 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 teacher head, 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

Citations4
Published2024
Admission routes1
Has abstractyes

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