Evidence map›Paper›PMID 42353343›Full record

ArticleInternational journal of molecular sciences2026

Comparative Analysis of Serum and Tissue miRNA Expression Profiles and Regulatory Pathways in Early-Stage Ovarian Cancer Using Public Databases.

Shuya Cai, Hui Tan, Xiaoyu Niu, Nirupal Eskar, Zaoling Liu

Abstract readComparative Study
In one paragraph

Article in International journal of molecular sciences, 2026. 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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0citing papers 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

The trial behind it

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3 · Its place in the literature

Who cites it

0 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

5 authors.

Shuya CaiDepartment of Epidemiology and Health Statistics, School of Public Health, Xinjiang Medical University, Urumqi 830011, China.
Hui TanDepartment of Epidemiology and Health Statistics, School of Public Health, Xinjiang Medical University, Urumqi 830011, China.
Xiaoyu NiuDepartment of Epidemiology and Health Statistics, School of Public Health, Xinjiang Medical University, Urumqi 830011, China.
Nirupal EskarDepartment of Epidemiology and Health Statistics, School of Public Health, Xinjiang Medical University, Urumqi 830011, China.
Zaoling LiuDepartment of Epidemiology and Health Statistics, School of Public Health, Xinjiang Medical University, Urumqi 830011, China.

Funding

the Autonomous Region Key Research and Development 2024B03037-1
6 · The paper itself

Abstract

To characterize the distinct expression profiles of microRNAs (miRNAs) in serum and tissue and to delineate the heterogeneity of their regulatory mechanisms in early-stage ovarian cancer (EOC), thereby identifying candidate biomarkers for non-invasive early diagnosis. Differentially expressed miRNAs were identified by integrating publicly available datasets of EOC tissues and serum samples from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Core miRNAs were subsequently screened through integrated differential expression analysis, weighted gene co-expression network analysis (WGCNA), and feature importance ranking derived from optimized machine learning models. Protein-protein interaction (PPI) networks and functional enrichment analyses (GO and KEGG) were performed on predicted target genes to systematically compare the functional discrepancies between serum- and tissue-derived miRNAs. No overlapping core miRNAs were observed between the two compartments. Serum miRNAs exhibited an overall up-regulated trend, whereas tissue miRNAs were predominantly down-regulated. Although the regulatory pathways demonstrated significant heterogeneity, they ultimately converged on the cell cycle and the PI3K-Akt signaling pathway, indicating high functional homology. Furthermore, serum miRNAs are not merely passive leakage products from tissues; current evidence suggests they may be selectively packaged into exosomes to participate in tumor regulation. Despite divergent expression profiles, serum and tissue miRNAs share homologous regulatory functions in EOC. These findings suggest that serum miRNAs accurately reflect the core molecular status of tumor tissues, providing a robust molecular foundation for liquid biopsy-based early detection strategies.

Indexed as

Gene Expression Regulation, NeoplasticGene Regulatory NetworksMicroRNAsOvarian NeoplasmsTranscriptomeBiomarkers, TumorDatabases, GeneticFemaleGene Expression ProfilingHumansNeoplasm StagingProtein Interaction MapsSignal TransductionBiomarkers, TumorMicroRNAsearly-stage ovarian cancerMicroRNApublic databaseregulatory pathwaysserumtissue

Identifiers

PMID42353343
PMCPMC13299059

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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.