Evidence map›Paper›PMID 42484744›Full record

ArticleInternational journal of clinical oncology2026

Identification and functional validation of lipid droplet-associated prognostic biomarkers in breast cancer via integrative multi-omics and machine learning approaches.

Jia Yao, Zhen Liu, Jing Zhang, Xiongzhi Long, Chen Chao, Liqin Yuan

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Article in International journal of clinical oncology, 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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5 · Who and what money

Authors and funding

6 authors.

Jia YaoDepartment of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan Province, People's Republic of China.
Zhen LiuDepartment of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan Province, People's Republic of China.
Jing ZhangDepartment of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan Province, People's Republic of China.
Xiongzhi LongDepartment of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan Province, People's Republic of China.
Chen ChaoNational Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology, Department of Metabolism and Endocrinology, Ministry of Education, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan Province, People's Republic of China.
Liqin YuanDepartment of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan Province, People's Republic of China. yuanliqin@csu.edu.cn.

Funding

China Primary Health Care Foundation(CPHCF) Emerging Oncology Supportive Care Research Grant Program No.cphcf-2023-042Natural Science Foundation of Hunan Province No.2022JJ30863 and No.2023JJ30799
6 · The paper itself

Abstract

backgroundLipid droplet (LD)-associated metabolic reprogramming plays a critical role in breast cancer progression and immune modulation, yet robust prognostic biomarkers and their functional mechanisms remain incompletely understood. This study aimed to identify LD-associated biomarkers with prognostic and therapeutic relevance through multi-omics integration and functional validation.

methodsBulk transcriptomic, single-cell RNA sequencing, and spatial transcriptomic data were integrated using machine learning to construct a prognostic model in the TCGA-BRCA cohort, validated in merged GEO datasets (GSE24450 and GSE42568). Functional enrichment, immune infiltration analyses, and in vitro/in vivo experiments-including 3T3-L1 adipogenesis, co-culture, orthotopic tumor models, and clinical adipose tissue validation were performed to characterize candidate genes.

resultsThe StepCox[both]+plsRcox algorithm generated an optimal prognostic model that independently stratified patients across molecular subtypes, outperforming ER/PR/HER2 status. High-risk patients exhibited reduced immune infiltration and T-cell dysfunction. SQLE and SOCS3 emerged as key LD-associated genes with opposing expression patterns: SQLE enriched in tumor-associated adipocytes and SOCS3 in immune cells. Functional assays confirmed SQLE promoted while SOCS3 inhibited adipogenesis. Modulating these genes in adipocytes suppressed tumor growth and EMT and polarized macrophages toward an M1-dominant phenotype.

conclusionsSQLE and SOCS3 serve as functionally significant LD-associated prognostic biomarkers and represent promising therapeutic targets in breast cancer, revealing novel mechanisms in tumor-adipocyte crosstalk.

Indexed as

Biomarkers, TumorBreast NeoplasmsLipid DropletsAnimalsFemaleGene Expression Regulation, NeoplasticHumansMachine LearningMetabolic ReprogrammingMiceMultiomicsPrognosisBiomarkers, TumorBreast cancerLipid dropletsMachine learningSOCS3SQLETumor microenvironment

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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 Socratic graph.