Evidence map›Paper›PMID 41562071›Full record

ArticleFrontiers in immunology2025

Identify GDPD3 as a key regulator of epithelial-mesenchymal transition and prostate adenocarcinoma progression via the LPA/LPAR1/AKT axis: transcriptomic and experimental study.

Lin Hao, Xiangqiu Chen, Tao He, Tao Wu, Zhiqiang Wen, Ziliang Ji, Xichun Zheng, Qingyou Zheng, Qingchun Zhou, Chengwu He and 2 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. Article
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

12 authors.

Lin Hao *Department of Urology, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Xiangqiu Chen *Department of Urology, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Tao He *Department of Urology, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, Shenzhen, Guangdong, China.
Tao WuDepartment of Urology, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Zhiqiang WenDepartment of Urology, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Ziliang JiDepartment of Urology, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Xichun ZhengDepartment of Urology, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Qingyou ZhengDepartment of Urology, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Qingchun ZhouDepartment of Urology, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Chengwu HeDepartment of Urology, Shenzhen Shockwave Lithotripsy Research Institute, The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong, China.
Qishan LongDepartment of Urology, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, Shenzhen, Guangdong, China.
Donglin SunDepartment of Urology, Shenzhen Hospital, Southern Medical University, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Prostate adenocarcinoma (PRAD) is a common malignancy with marked clinical heterogeneity, complicating prognosis and disease monitoring. Traditional tools like the Gleason score lack molecular and microenvironmental insights, underscoring the need for biomarker-driven predictive models. Methods: Single-cell RNA-seq data from GEO and bulk RNA-seq data from TCGA were analyzed. scRNA-seq processing used the Seurat package, with cluster-specific genes identified via FindAllMarkers. Differentially expressed genes (DEGs) from bulk data were obtained using limma, and key gene modules were identified through WGCNA. Using univariate Cox regression and LASSO analysis, a prognostic model was developed based on cluster-specific genes, key module genes, and differentially expressed genes. Clinical validation included comparison of tumor and adjacent normal tissues, revealing significantly elevated GDPD3 expression, further confirmed by immunohistochemistry. Results: In this study, through integrated single-cell sequencing and Bulk-RNA-seq analyses, we established a 21-gene prognostic model. QPCR confirmed significant upregulation of three candidates, including GDPD3, which was also elevatedin malignant tissues. Knockdown of GDPD3 inhibited tumor cell proliferation, invasion, and migration. Mechanistically, GDPD3 regulated the levels of lysophosphatidic acid (LPA), which in turn induced EMT in tumor cells. Inhibition or knockdown of the LPA receptor LPAR1 suppressed EMT. LPA promoted EMT through activation of the AKT signaling pathway, and inhibition of this pathway reversed LPA-induced EMT. Conclusion: This study underscores key molecular mechanisms underlying prostate cancer progression, with GDPD3 emerging as a potential therapeutic target.

Indexed as

AdenocarcinomaEpithelial-Mesenchymal TransitionLysophospholipidsProstatic NeoplasmsProto-Oncogene Proteins c-aktReceptors, Lysophosphatidic AcidCell Line, TumorCell MovementCell ProliferationDisease ProgressionGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMalePrognosisSignal Transductionlysophosphatidic acidLysophospholipidsProto-Oncogene Proteins c-aktReceptors, Lysophosphatidic Acidepithelial–mesenchymal transitionGDPD3prognosisprostate adenocarcinomatranscriptomic analysis

Identifiers

PMID41562071
PMCPMC12813044

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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.