Evidence map›Paper›PMID 42860598›Full record

ArticleCancer science2026

Multi-Omics Integration Reveals Metabolic Reprogramming and EMT-Driven Metastasis in Triple-Negative Breast Cancer.

Yuheng Pang, Yuefeng Shang, Wenjing Wang, Tong Liu, Xiaolong Zou

Abstract read
In one paragraph

Article in Cancer science, 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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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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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.

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4 · The record

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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.

Yuheng PangDepartment of Oncological Surgery, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, China.ORCID https://orcid.org/0009-0004-8119-7200
Yuefeng ShangDepartment of Oncological Surgery, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, China.
Wenjing WangBeijing Institute of Hepatology, Beijing YouAn Hospital, Capital Medical University, Beijing, People's Republic of China.
Tong LiuDepartment of Oncological Surgery, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, China.
Xiaolong ZouPancreatic Disease Diagnosis and Treatment Center, the First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China.

Funding

Beijing Municipal Natural Science Foundation Z230008Heilongjiang Provincial Department of Science and Technology, China JD24D001National Natural Science Foundation of China 82272872
6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) is an aggressive subtype with high metastatic potential and poor prognosis, yet the molecular mechanisms driving metastasis remain incompletely understood. Here, we performed integrated transcriptomic, metabolomic, and imaging mass cytometry (IMC) analyses on tumor tissues from 52 TNBC patients stratified into NonMeta (long-term survival without metastasis, n = 39) and MetaPoor (metastasis-related death within 36 months after metastatic diagnosis, n = 13) groups. Transcriptomic analysis revealed significant enrichment of epithelial-mesenchymal transition (EMT), WNT signaling pathway, and angiogenesis pathways in MetaPoor tumors, with EMT identified as the top enriched hallmark by GSEA. Metabolomic profiling showed decreased branched-chain amino acids (BCAAs) and arginine derivatives, alongside elevated glycerophosphorylcholine (GPC), indicating enhanced metabolic demand and membrane remodeling. IMC-based spatial proteomics identified distinct tumor cell subpopulations, with MetaPoor tumors harboring higher proportions of stem-like and EMT-like cells characterized by upregulated HADHA (BCAA oxidation) and P38, and downregulated ATP5A (oxidative phosphorylation). Multi-omics integration revealed strong correlations between GPC and EMT markers, and between BCAA depletion and HADHA expression. Collectively, our multi-omics study demonstrates that metastatic TNBC is characterized by EMT activation, metabolic reprogramming toward altered BCAA metabolism and oxidative phosphorylation-related protein expression, and remodeling of the tumor immune microenvironment, suggesting candidate molecules that warrant independent validation and further mechanistic investigation.

Indexed as

epithelial‐mesenchymal transitionmetastasistriple‐negative breast cancer

Identifiers

PMID42860598
PMCPMC13655252

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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.