Evidence map›Paper›PMID 41862993›Full record

ArticleGenome medicine2026

Proteomic landscape analysis of undifferentiated pleomorphic sarcoma.

Biqiang Zheng, Yifei Lu, Bingnan Wang, Wenjun Chai, Mingxia Yan, Zhijian Song, Wangjun Yan

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In one paragraph

Article in Genome medicine, 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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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Biqiang ZhengDepartment of Musculoskeletal Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200032, China. zhengsar@163.com.
Yifei LuDepartment of Pediatric Surgery, Children's Hospital of Fudan University, Shanghai, 201102, China.
Bingnan WangDepartment of Musculoskeletal Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200032, China.
Wenjun ChaiDepartment of Animal Experimental Center, Fudan University Shanghai Cancer Center, Shanghai, 201102, China.
Mingxia YanDepartment of Animal Experimental Center, Fudan University Shanghai Cancer Center, Shanghai, 201102, China.
Zhijian SongHuahai Tianheng Pharmaceutical Research Co., Ltd., Shanghai, 201206, China. zhijiansong@126.com.
Wangjun YanDepartment of Musculoskeletal Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200032, China. yanwj@fudan.edu.cn.

Funding

National Natural Science Foundation of China 82473467
6 · The paper itself

Abstract

backgroundProteins represent the dynamic downstream products of genes, and have the potential to substantially increase understanding of the complexities of cancer biology. Undifferentiated pleomorphic sarcoma (UPS) is a rare disease, the proteomic landscape of which has not been fully investigated.

methodsWe performed isobaric TMT-based proteomic analysis for 80 UPS tumor and 28 corresponding adjacent non-tumor muscle tissues. The underlying molecular subtypes, therapeutic targets, local recurrence, and lung metastasis were uncovered. The integration of previous single-cell RNA sequencing data with proteomics was further employed to characterize the specific cell type linked to lung metastasis.

resultsOur analyses revealed a catalog of proteins that were dysregulated in UPS. The UPS cohort was stratified into three molecular subtypes S-I, S-II, and S-III. S-I was characterized by the high expression of spliceosome-related proteins and protumor cytokines, and was associated with the lowest overall rate of survival. S-II was characterized with the highest ImmuneScore. S-III with the highest StromaScore had the best outcomes. Protein-based disease classification was better than the recommended AJCC staging system for UPS. PRMT6 protein was overexpressed, and associated with adverse outcomes. PRMT6 inhibitor significantly inhibited tumor growth in two patient-derived xenograft models. Analysis of local recurrence-associated proteins showed that PAWR was negatively associated with UPS recurrence. Additionally, CD163 was a negative predictive marker for lung metastasis. Combined with scRNA-seq data, CD163 + macrophages represented phagocytosis phenotype with high expression of the signature markers (CD163, MRC1, MERTK, and C1QB). Furthermore, CD163 + macrophages were enriched in the endocytosis, phagocytosis, and lysosome compared with CD163- macrophages.

conclusionsOur study highlights the utility of proteomics for characterizing UPS, providing a framework for understanding the biological basis of its clinical features and paving the way for a new era of proteomics-driven precision medicine in sarcoma research.

Indexed as

ProteomeProteomicsSarcomaAnimalsBiomarkers, TumorFemaleGene Expression Regulation, NeoplasticHumansLung NeoplasmsMaleMiceBiomarkers, TumorProteomeLung metastasisMacrophagesProteomicsRecurrenceSarcoma

Identifiers

PMID41862993
PMCPMC13127049

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