Evidence map›Paper›PMID 30127624›Full record

ArticleOncoTargets and therapy2018

An integrated bioinformatical analysis to evaluate the role of KIF4A as a prognostic biomarker for breast cancer.

Dan Xue, Pu Cheng, Mengjiao Han, Xiyong Liu, Lijun Xue, Chenyi Ye, Ke Wang, Jian Huang

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

20 citing papers in PubMed, 29 citations in OpenAlex.

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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 4 institutions in 3 countries.

Dan XueDepartment of Plastic Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Pu ChengDepartment of Gynaecology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Mengjiao HanDepartment of Medical Oncology, Key Laboratory of Biotherapy in Zhejiang, Sir Run Run Shaw Hospital, Medical School of Zhejiang University, Hangzhou, China.
Xiyong LiuBiomarker Development, California Cancer Institute, Temple City, CA, USA.
Lijun XueDepartment of Pathology, Loma Linda University Medical Center, Loma Linda, CA, USA.
Chenyi YeDepartment of Orthopaedics, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Ke WangDepartment of Surgical Oncology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China, drhuangjian@zju.edu.cn.
Jian HuangDepartment of Surgical Oncology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China, drhuangjian@zju.edu.cn.
Second Affiliated Hospital of Zhejiang University · CNLoma Linda University Medical Center · USSir Run Run Shaw Hospital · CNTaipei Medical University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aim of this study was to investigate the diagnostic and prognostic value of human kinesin family member 4A (KIF4A) as an effective biomarker for breast cancer. MATERIALS AND

methodsCancer Genome Atlas data and 12 independent public breast cancer microarray data sets were downloaded and analyzed using individual and pooled approaches.

resultsThe results of our study revealed a strong and positive correlation between KIF4A expression and malignant features of breast cancer. KIF4A had a strong prognostic value in both ER-positive and ER-negative breast cancers comparable to or even better than tumor size, lymph node invasion, and Elston grade. We also found that KIF4A might be the target gene of microRNA-335, which can suppress KIF4A expression by targeting the 3'-untranslated region of its mRNA.

conclusionKIF4A might serve as a robust prognostic predictor for breast cancer. Targeting KIF4A activity could be a promising therapeutic option in breast cancer treatment.

Indexed as

breast cancerKIF4AmicroarraymicroRNAprognosis

Identifiers

PMID30127624
PMCPMC6091482
OpenAlexW2885281644

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.