Evidence map›Paper›PMID 35949593›Full record

ArticleOncology letters2022

KIF11: A potential prognostic biomarker for predicting bone metastasis-free survival of prostate cancer.

Haoyuan Wang, Sijie Li, Bin Liu, Shufei Wei, Tianyi Wang, Tao Li, Jiahu Lin, Xiaochen Ni

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.9field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Kinesin Spindle Protein (KIF11) in Mitosis and Cancer.International journal of molecular sciences · 2025
    Review
  3. Article
  4. Article
  5. Article
  6. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Haoyuan WangDepartment of Urology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, P.R. China.
Sijie LiDepartment of Urology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, P.R. China.
Bin LiuDepartment of Urology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, P.R. China.
Shufei WeiDepartment of Urology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, P.R. China.
Tianyi WangDepartment of Urology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, P.R. China.
Tao LiDepartment of Urology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, P.R. China.
Jiahu LinDepartment of Urology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, P.R. China.
Xiaochen NiDepartment of Urology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, P.R. China.
Hebei Medical University · CNFourth Hospital of Hebei Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most prostate cancer (PCa) cases remain indolent with a relatively good prognosis. However, bone metastasis of PCa can quickly worsen prognoses and lead to mortality. Metastasis-free survival (MFS), a strong surrogate for overall survival, is widely used in PCa prognosis research. The present study identified molecules that affect bone MFS in PCa, with clinical validation. Three datasets (GSE32269, GSE74367 and GSE77930) were downloaded from the Gene Expression Omnibus database. Hub genes most relevant to clinical traits (bone metastasis-associated morbidity) were identified by weighted gene co-expression network analysis (WGCNA) and subjected to logistic regression analysis. Patient samples were obtained between January 2014 and December 2016, with a clinically annotated follow-up in December 2021. Clinical data and follow-up information for 60 patients with PCa were used in MFS analysis. Tumor samples were retrieved, and immunohistochemistry was performed to detect vascular endothelial growth factor (VEGF). The prognostic potential of the two molecules was assessed using Cox proportional hazards regression analysis. A total of 16 gene modules were obtained via WGCNA, and the tan module, containing 147 genes, was most closely linked to bone metastasis. In total, 877 differentially expressed genes (DEGs) were detected. The DEG-tan module intersection yielded seven hub genes [BUB1, kinesin family member (KIF)2C, RACGAP1, CENPE, KIF11, TTK and KIF20A]. Using univariate and multivariate logistic regression analyses for independent risk factors of bone metastasis, KIF11 and VEGF were found to be significantly associated with a higher T stage, prostate-specific antigen level and Gleason score. In addition, KIF11 and VEGF expression levels were positively correlated (P<0.001). Using univariate Cox analysis, KIF11 and VEGF were found to exhibit a significant association with poor MFS (P<0.05). However, only KIF11 was significantly associated with MFS upon multivariate analysis (P=0.007; hazard ratio, 2.776; 95% confidence interval, 1.315-5.859). Markers of bone metastasis in PCa were identified. Overall, KIF11 is an independent indicator that can predict bone metastasis for patients with PCa, which could be used to guide clinical practice.

Indexed as

kinesin family member 11metastasis-free survivalprostate cancervascular endothelial growth factors

Identifiers

PMID35949593
PMCPMC9353809
OpenAlexW4285593542

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.