Evidence map›Paper›PMID 36046368›Full record

ArticleJournal of oncology2022

KLHL14: A Novel Prognostic Biomarker and Therapeutic Target for Ovarian Cancer.

Xingwei Wang, Ru Sun, Xia Hong, Chen Chen, Yan Ding

Open access · hybridAbstract read
In one paragraph

Article in Journal of oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 6 citations in OpenAlex.

  1. Bioinformatic Approach to Identify PotentialInternational journal of molecular sciences · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. The roles of KLHL family members in human cancers.American journal of cancer research · 2022
    Review
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

5 authors at 2 institutions in 1 country.

Xingwei WangDepartment of Obstetrics and Gynecology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou 225001, China.
Ru SunDepartment of Obstetrics and Gynecology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou 225001, China.
Xia HongDepartment of Obstetrics and Gynecology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou 225001, China.
Chen ChenJiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and the Affiliated Cancer Hospital of Nanjing Medical University, Nanjing 210008, China.
Yan DingDepartment of Obstetrics and Gynecology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou 225001, China.ORCID https://orcid.org/0000-0002-0136-8275
Yangzhou University · CNNanjing Drum Tower Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer (OV) is a gynaecological malignancy that poses a serious risk to the health status of women. To date, effective molecular markers are unavailable for the diagnosis and management of ovarian malignancies. In this study, we aimed to investigate the molecular markers associated with the development of this cancer. We used bioinformatic analysis to determine the molecules and genes related to ovarian cancer using the gene expression profiling interactive analysis (GEPIA) and the cancer genome Atlas (TCGA) databases. In addition, we examined the genes and mechanisms underlying ovarian cancer. Our results showed that the KLHL14 gene is overexpressed in some cancers. An increase in the KLHL14 expression indicates a poor prognosis in patients with ovarian cancer. Results of immune cell infiltration analysis and half-maximal inhibitory concentration (IC50) analysis provide novel insights into the treatment of ovarian cancer. KLHL14 is anticipated to emerge as a novel molecular marker specifically for ovarian carcinoma.

Identifiers

PMID36046368
PMCPMC9423958
OpenAlexW4292674477

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.