Evidence map›Paper›PMID 39733078›Full record

ArticleScientific reports2024

Identification and validation of KIF20A for predicting prognosis and treatment outcomes in patients with breast cancer.

Mei Yang, Hui Huang, Yan Zhang, Yiping Wang, Junhao Zhao, Peiyao Lee, Yuhua Ma, Shaohua Qu

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

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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

9 citing papers in PubMed.

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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.

Mei Yang *Department of Breast Surgery, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, China.
Hui Huang *Department of Breast Surgery, JiangMen Maternity and Child Health Care Hospital, Jiangmen, China.
Yan ZhangDepartment of Breast Surgery, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, China.
Yiping WangDepartment of Breast Surgery, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, China.
Junhao ZhaoDepartment of Breast Surgery, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, China.
Peiyao LeeDepartment of Breast Surgery, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, China.
Yuhua MaDepartment of Breast Surgery, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, China. mayuhua2110@126.com.
Shaohua QuDepartment of Breast Surgery, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, China. qushaohua2009@163.com.

Funding

Guangdong Basic and Applied Research Foundation 2023A1515010553Science and Technology Projects in Guangzhou 2023A03J1005
6 · The paper itself

Abstract

Breast cancer is a leading cause of cancer-related deaths among women globally. It is imperative to explore novel biomarkers to predict breast cancer treatment response as well as progression. Here, we collected six breast cancer samples and paired normal tissues for high-throughput sequencing. By differential expression analysis, we found 1687 DEGs and identified the top 10 hub genes, including TOP2A, CDK1, BUB1B, KIF11, CCNA2, BUB1, CCNB1, KIF20A, DLGAP5 and CDC20. Univariate and multivariate Cox analyses on the METABRIC database and GSE96058 dataset demonstrated that KIF20A was an independent prognostic predictor for overall survival. KIF20A was positively correlated with cell cycle phases, including the cell cycle process, cycle G2 M phase transition and cell cycle DNA replication initiation. Single-cell analyses revealed that KIF20A was enriched in fibroblasts and endothelial within breast cancer stroma. Meanwhile, multidrug resistance (MDR) genes ABCB1, ABCC1 and ABCG2 were co-expressed with KIF20A in fibroblasts and endothelial cells within the stroma. MTABRIC database confirmed that high expression of KIF20A was positively correlated with treatment efficacy in patients with breast cancer. In conclusion, KIF20A could be served as a predictive biomarker for breast cancer prognosis and treatment outcomes. KIF20A may play a significant role by regulating cell cycle progression and modulating stromal progression in breast cancer. Our findings provided novel molecular insights that can guide personalized treatment strategies in breast cancer.

Indexed as

Biomarkers, TumorBreast NeoplasmsKinesinsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMiddle AgedPrognosisTreatment OutcomeBiomarkers, TumorKIF20A protein, humanKinesinsbreast cancerKIF20Aprognosistreatment resistancetumor microenvironment

Identifiers

PMID39733078
PMCPMC11682246

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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.