Evidence map›Paper›PMID 41291728›Full record

ArticleJournal of translational medicine2025

A macro-micro-macro radiogenomic framework identifies FIBCD1 as a key immune-modulating biomarker in breast cancer.

Minping Hong, Xiaobo Chen, Xiaowen Huang, Wenjing Jiang, Jie He, Jie Hou, Yujie Ying, Bing Zhou, Zhenyi Ma, Haitao Sun and 1 more

Abstract read
In one paragraph

Article in Journal of translational medicine, 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

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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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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Minping Hong *Department of Radiology, Jiaxing Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medical University, Jiaxing, China.
Xiaobo Chen *Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China.
Xiaowen HuangDepartment of Radiology, Jiaxing Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medical University, Jiaxing, China.
Wenjing JiangGuangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China.
Jie HeDepartment of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Jie HouCancer Center, Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China.
Yujie YingThe First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China.
Bing ZhouDepartment of Radiology, Jiaxing Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medical University, Jiaxing, China.
Zhenyi MaDepartment of Radiology, Jiaxing Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medical University, Jiaxing, China. 172702978@qq.com.
Haitao SunDepartment of Radiology, Zhongshan Hospital, Shanghai Institute of Medical Imaging, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China. sht1720@163.com.
Keng LingDepartment of Clinical Laboratory, Jiaxing Maternity and Children Health Care Hospital, Jiaxing, China. 450620239@qq.com.ORCID 0000-0003-0081-5069

Funding

Health and Family Planning Commission of Sichuan Province 20244Y0003Medical Science and Technology Project of Zhejiang Province 2024KY454Medical Science and Technology Project of Zhejiang Province 2025KY1626Medical Science and Technology Project of Zhejiang Province 2025KY1627Medical Science and Technology Project of Zhejiang Province 2025KY366Natural Science Foundation of Zhejiang Province LQN25H180008Public Welfare Research Project of Jiaxing 2024AY10026
6 · The paper itself

Abstract

backgroundBreast cancer prognosis remains challenging due to tumor heterogeneity and the limited predictive power of conventional clinical models. Integrating imaging features with molecular data may improve individualized risk stratification and clinical decision-making.

methodsWe developed a closed-loop prognostic model based on a macro-micro-macro radiogenomic framework that combines MRI-based radiomics with transcriptomic and proteomic data. A total of 788 radiomics-guided candidate genes were screened. Prognostic gene signatures were identified using multiple machine learning algorithms and validated in TCGA and GEO cohorts. We further analyzed immune infiltration, drug sensitivity, and gene enrichment profiles across risk groups. Causal relationships between gene expression and survival were assessed using Mendelian randomization. Hub gene expression was validated in patient plasma using ELISA, and Olink proteomics and radiomic information was conducted for biological association analysis.

resultsXGBoost-Cox prognostic model was constructed integrating 10 consensus genes identified by stepwise Cox regression and Elastic Net, achieving the concordance index 0.703 in GEO validation cohort. High-risk patients showed reduced immune activation, increased expression of pro-inflammatory cytokines, and worse survival. Among consensus genes, FIBCD1 was demonstrated as a hub gene with a significant causal association with survival. Its expression was significantly elevated in high-risk plasma samples, positively correlated with inflammatory proteins (e.g., OSM, and TNFSF14), and associated with MRI phenotype, including tumor sphericity and inverse difference normalized feature.

conclusionsOur findings establish a novel radiogenomic strategy that bridges MRI-derived imaging phenotypes with molecular mechanisms. FIBCD1 may serve as an immune-modulating prognostic biomarker linked to imaging characteristics, providing new insights into non-invasive breast cancer risk assessment and therapeutic targeting.

Indexed as

Biomarkers, TumorBreast NeoplasmsGenomicsFemaleGene Expression Regulation, NeoplasticHumansMagnetic Resonance ImagingPrognosisProportional Hazards ModelsBiomarkers, TumorBreast cancerFIBCD1Immune tumor microenvironmentProteomicsRadiomicsTranscriptomics

Identifiers

PMID41291728
PMCPMC12649031

What OpenQuestion holds

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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.