Evidence map›Paper›PMID 40658144›Full record

ArticleCellular and molecular life sciences : CMLS2025

Integrative proteomics and metabolomics analyses reveals the regulation of autophagy and ferroptosis by RAB10 through Slc37a2/mTOR pathway in breast cancer.

Yuxin Ji, Ruonan Li, Guohui Tang, Yuhan Xiao, Ruyin Ye, Jiwen Shi, Chenchen Geng, Ruorong Ran, Chengle Zhu, Wenrui Wang and 2 more

Abstract read
In one paragraph

Article in Cellular and molecular life sciences : CMLS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
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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

12 authors.

Yuxin Ji *Anhui Provincial Key Laboratory of Tumor Evolution and Intelligent Diagnosis and Treatment, Bengbu Medical University, Anhui, 233030, China.
Ruonan Li *Anhui Provincial Key Laboratory of Tumor Evolution and Intelligent Diagnosis and Treatment, Bengbu Medical University, Anhui, 233030, China.
Guohui Tang *Anhui Provincial Key Laboratory of Tumor Evolution and Intelligent Diagnosis and Treatment, Bengbu Medical University, Anhui, 233030, China.
Yuhan XiaoAnhui Provincial Key Laboratory of Tumor Evolution and Intelligent Diagnosis and Treatment, Bengbu Medical University, Anhui, 233030, China.
Ruyin YeAnhui Provincial Key Laboratory of Tumor Evolution and Intelligent Diagnosis and Treatment, Bengbu Medical University, Anhui, 233030, China.
Jiwen ShiAnhui Provincial Key Laboratory of Tumor Evolution and Intelligent Diagnosis and Treatment, Bengbu Medical University, Anhui, 233030, China.
Chenchen GengAnhui Provincial Key Laboratory of Tumor Evolution and Intelligent Diagnosis and Treatment, Bengbu Medical University, Anhui, 233030, China.
Ruorong RanAnhui Provincial Key Laboratory of Tumor Evolution and Intelligent Diagnosis and Treatment, Bengbu Medical University, Anhui, 233030, China.
Chengle ZhuAnhui Provincial Key Laboratory of Tumor Evolution and Intelligent Diagnosis and Treatment, Bengbu Medical University, Anhui, 233030, China.
Wenrui WangDepartment of Life Sciences, Bengbu Medical University, Anhui, 233030, China. wenrui-wang1983@163.com.
Changjie ChenDepartment of Biochemistry and Molecular Biology, Bengbu Medical University, Anhui, 233030, China. tochenchangjie@163.com.
Qingling YangDepartment of Biochemistry and Molecular Biology, Bengbu Medical University, Anhui, 233030, China. yqlmimi@163.com.ORCID http://orcid.org/0000-0002-7538-0218

Funding

excellent Scientific Research and Innovation Team of Anhui Universities 2024AH010021the Major Program of Anhui Educational Committee No.: KJ2019ZD28the Program for graduate's research of Bengbu Medical College Byycx22042, Byycx23013,Byycx24035the University Synergy Innovation Program of Anhui Province GXXT-2022-064
6 · The paper itself

Abstract

Breast cancer (BC) is the most prevalent and highly heterogeneous malignancy affecting females worldwide, and its development is closely linked to metabolic reprogramming. In this study, label-free quantification (LFQ) was used to analyze the protein expression in exosomes secreted by BC drug-resistant cells, identifying RAS-associated binding protein (RAB) 10 as the most significantly upregulated protein. RAB10, a member of the small GTPase family with complex biological functions, is highly expressed in BC and is associated with poor prognosis. In this study, we mainly utilized mouse breast cancer 4T-1 cells (wild-type control cells) and tumor-induced 4T-1 cells (isolated from mouse in situ tumor tissues to simulate the phenotype of the in vivo tumor microenvironment), and on this basis, conducted in vitro functional verification and in vivo tumorigenesis experiments. A comprehensive multi-omics analysis, including metabolomics and proteomics, following RAB10 knockdown, demonstrated the crucial role of RAB10 in regulating central carbon metabolism, which is essential for autophagy and ferroptosis in BC cells. Our study further confirmed that RAB10 mediates metabolic reprogramming in BC cells by regulating the Slc37a2/mTOR pathway, leading to enhanced autophagy and inhibition of ferroptosis. This comprehensive multi-omics analysis elucidated the key molecular and regulatory mechanisms underlying RAB10-induced metabolic reprogramming in tumors, providing potential new therapeutic targets and biomarkers for prognostic assessment in BC treatment.

Indexed as

AutophagyBreast NeoplasmsFerroptosisMetabolomicsProteomicsrab GTP-Binding ProteinsTOR Serine-Threonine KinasesAnimalsCell Line, TumorFemaleGene Expression Regulation, NeoplasticHumansMiceSignal TransductionMTOR protein, humanRab10 protein, humanrab GTP-Binding ProteinsTOR Serine-Threonine KinasesAutophagyBreast cancerFerroptosisMetabolismRAB10

Identifiers

PMID40658144
PMCPMC12259503

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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.