Evidence mapPaperPMID 41840167Full record

ReviewScience China. Life sciences2026

Multi-omic analysis of the liver-breast axis reveals key hepatic mediators of breast cancer progression.

Gao Yuanze, Fei Wang, Kumar Ganesan, Jianping Chen

Abstract readReview
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In one paragraph

Review in Science China. Life 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.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Gao YuanzeSchool of Chinese Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
Fei WangHospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, China.
Kumar GanesanSchool of Chinese Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China. kumarg@hku.hk.
Jianping ChenSchool of Chinese Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China. abchen@hku.hk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emerging evidence establishes hepatic dysfunction as a critical modulator of breast cancer (BC) progression through metabolic, endocrine, and inflammatory crosstalk, yet the molecular mediators remain incompletely characterized. This review systematically examines the liver-BC axis to identify mechanistic drivers and therapeutic opportunities for patients with comorbid conditions. We conducted an integrated analysis combining a comprehensive literature review with computational biology approaches, including protein-protein interaction network analysis, functional pathway enrichment (KEGG/GO), and multi-omics data mining from GEO, TCGA, and CPTAC databases, supplemented by experimental validations from preclinical models. Our analysis revealed hepatic dysfunction promotes BC progression through five interconnected pathways: insulin resistance-driven IGF1-PI3K/AKT activation, estrogen metabolism imbalance via CYP19A1/ESR1, IL6-STAT3/NLRP3-mediated inflammation, HMOX1/APOE-dependent metabolic rewiring, and FAK-Src/MMP9-regulated ECM remodeling. Key molecular mediators include nuclear receptors (ESR1), cytokines (IL-1β), growth factors (HGF), and receptor tyrosine kinases, with SPP1 and PTPN2 emerging as potential circulating biomarkers linking hepatic dysfunction to aggressive BC phenotypes. The crosstalk between hepatic dysfunction and BC is mediated by a network of proteins and pathways, offering potential targets for therapeutic intervention. Future research should focus on translational validation and personalized strategies for BC patients with comorbid liver conditions. This mechanistic insight may advance early diagnosis and precision treatment paradigms.

Indexed as

Breast NeoplasmsLiverMultiomicsAnimalsBreastComputational BiologyDisease ProgressionFemaleHumansProtein Interaction MapsSignal Transductionbreast cancerhepatic dysfunctionnetwork bioinformaticstarget proteins

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.