Evidence map›Paper›PMID 41561741›Full record

ArticleFrontiers in oncology2025

Transcriptomics driven identification of hub gene miRNA interactions for biomarker and therapeutic target discovery in gynecological cancers.

Yuanjun Zhu, Sisi Chen, Mei Cao, Wangbo Liu, Hanling Huang, Ke Huang, Lingling Shi

Abstract read
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Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yuanjun ZhuDepartment of Obstetrics and Gynecology, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
Sisi ChenDepartment of Obstetrics and Gynecology, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
Mei CaoDepartment of Obstetrics and Gynecology, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
Wangbo LiuDepartment of Emergency, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
Hanling HuangDepartment of Physical Examination Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
Ke HuangDepartment of Obstetrics and Gynecology, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
Lingling ShiDepartment of Ultrasound Medicine, Taihe Hospital, Hubei University of Medicine, Shiyan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: MicroRNAs (miRNAs) are small, single-stranded noncoding RNAs that play critical roles in disease development, including gynecological cancers like vulvar and cervical cancer. Their high heterogeneity makes achieving an accurate diagnosis difficult in modern clinical practice. Methods: In this study, we used Results: The statistical analysis of GEOR2 yielded 16,344 differentially expressed genes (DEGs), and through robust regression analysis, 229 common DEGs were retrieved. Among them, 94 and 135 genes were downregulated and upregulated, respectively. We retrieved ten hub genes via a protein-protein interaction network and cytohubba, namely CDK1, AURKA, BUB1B, CCNB1, TOP2A, KIF11, BUB1, CCNB2, CDCA8, and BIRC5. Following extensive Discussion: The identified miRNAs exhibit strong regulatory interactions with these hub genes, while serine/threonine protein kinases emerged as the most significantly associated group. Together, these findings highlight promising biomarker candidates and potential therapeutic targets for gynecological cancers.

Indexed as

Cervical cancerhub genesmiRNAnoncoding RNAspotential biomarkerqRT-PCRregression analysisRNA sequence data

Identifiers

PMID41561741
PMCPMC12812593

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