Evidence map›Paper›PMID 40747615›Full record

ArticleCancer medicine2025

Development of a Mitochondrial Permeability Transition-Driven Necrosis-Related Prognostic Signature in Cervical Cancer: Integrating Bulk Transcriptomic and Single-Cell Data.

Jiaojiao Niu, Sreenivasan Sasidharan

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In one paragraph

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

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Jiaojiao NiuSchool of Biological Engineering, Xinxiang University, Xinxiang City, Henan Province, China.ORCID https://orcid.org/0000-0001-7101-5654
Sreenivasan SasidharanInstitute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, Gelugor, Pulau Pinang, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCervical cancer (CC) is a prevalent gynecological malignancy with notable heterogeneity. The role of mitochondrial permeability transition (MPT)-driven necrosis, a form of cell death due to mitochondrial dysfunction, in CC progression and prognosis is poorly understood and represents a promising therapeutic target for cancers. This study aimed to create a new prognostic signature linked to MPT-driven necrosis, improving CC prediction and prognosis.

methodsThis study utilized the GSE63514, TCGA-CESC, CGCI-HTMCP-CC, and GSE197641 transcriptome datasets. Firstly, the GSE63514 dataset was utilized to identify differentially expressed genes (DEGs). Differentially expressed MPT-driven necrosis-related genes (DE-MRGs) were obtained by intersecting DEGs with MRGs. Regression analyses were performed to identify genes significantly associated with prognosis. A prognostic model was established in TCGA-CESC, followed by independent validation and nomogram construction. Additional analyses included immune infiltration, enrichment analysis, and drug susceptibility based on high- and low-risk groups. Finally, cell communication analysis was performed to investigate interactions between key cell types.

resultsA total of 156 DE-MRGs were identified. Regression analyses identified three prognostic genes (ICOS, MMP3, and POSTN) to construct a prognostic risk signature. Then, risk score was an independent prognostic factor for CC, and a nomogram demonstrated effective predictive accuracy for CC survival outcomes. The risk signature was linked to immune-associated processes such "Antigen processing and presentation" and immune cell infiltration, especially M0 macrophages and CD8 T cells. Cell communication analysis uncovered a strong interaction between endothelial cells and monocytes. To validate the molecular mechanisms, qRT-PCR, cell proliferation, and wound healing assays were performed. Functional tests showed that MMP3 and POSTN knockdown drastically reduced CC cell growth and migration.

conclusionThis study developed a novel prognostic risk signature based on ICOS, MMP3, and POSTN. MMP3 and POSTN knockdown significantly decrease CC cell growth and migration, highlighting their potential as therapeutic targets.

Indexed as

Biomarkers, TumorTranscriptomeUterine Cervical NeoplasmsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansNecrosisPrognosisSingle-Cell AnalysisBiomarkers, Tumorcell communicationcervical carcinomanomogramprognostic genesregulator network

Identifiers

PMID40747615
PMCPMC12314548

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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.