Evidence map›Paper›PMID 41361281›Full record

ArticleBreast cancer research : BCR2025

Integrative multi-omics reveals common and distinct pathogenic mechanisms and preoperative diagnostic signatures in breast fibroepithelial lesions.

Ming He, Kai Song, Yun Luo, Guie Lai, Liqing Tan, Xiaofang Liu, You Guo, Zicheng Jiang, Jialuo Zou, Weisong Li and 1 more

Abstract read
In one paragraph

Article in Breast cancer research : BCR, 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

11 authors.

Ming He *Medical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Kai Song *School of Medical Information Engineering, Gannan Medical University, Ganzhou, China.
Yun LuoMedical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Guie LaiBreast Disease Comprehensive Center, First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Liqing TanDepartment of Natural Sciences and Computer Science, Ganzhou Teachers College, Ganzhou, China.
Xiaofang LiuMedical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
You GuoMedical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Zicheng JiangFirst Clinical Medical College of Gannan Medical University, Ganzhou, China.
Jialuo ZouBreast Disease Comprehensive Center, First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Weisong LiPathological Diagnosis Center, The Seventh Affilated Hospital Sun Yat-Sen University, Shenzhen, China. fawn27@126.com.
Hao CaiMedical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, China. caihao093@163.com.

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2021A1515110238Key R&D Program of Jiangxi Province 20203BBGL73202Natural Science Foundation of Jiangxi Province 20224BAB206074Science and Technology Research Project of the Education Department of Jiangxi Province GJJ211544
6 · The paper itself

Abstract

Breast fibroepithelial lesions (FELs) comprising fibroadenomas (FAs) and phyllodes tumors (PTs) with varying degrees of malignancy, necessitate tailored surgical approaches. However, preoperative diagnosis of FELs remains challenging and their pathogenesis is not fully elucidated. By integrating methylation and expression data, we revealed substantial molecular deregulation common to FAs and PTs, impacting pathways central to genetic information processing and metabolism. Furthermore, we identified 86 genes exhibiting concurrent differential expression and methylation changes between FAs and PTs, some of which have been implicated in the malignant progression of disease. Subsequently, we constructed two gene-pair signatures: one comprising 158 pairs for distinguishing FAs from PTs, and another with 146 pairs for differentiating benign from malignant PTs. Both signatures achieved AUC exceeding 0.85 in independent surgical and core biopsy datasets. Finally, we identified 99 pathogenic genes exhibiting continuous up-regulation or down-regulation from FAs to malignant PTs. Significant associations were observed between these genes and key cancer-related biological pathways.

Indexed as

Biomarkers, TumorBreast NeoplasmsFibroadenomaPhyllodes TumorDNA MethylationFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMultiomicsTranscriptomeBiomarkers, TumorCore biopsyDiagnostic signatureFibroadenomasFibroepithelial lesionsPathogenic genesPhyllodes tumorsRelative expression orderings

Identifiers

PMID41361281
PMCPMC12683819

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LicenceCC BY-NC-ND
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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.