Exosomal Proteome from Hepatocellular Carcinoma Patient-Derived Xenograft Mice Serves as Identity of Liver Cancer

Hepatocellular carcinoma (HCC) constitutes approximately 90% of liver cancers, yet its early detection remains challenging due to the low sensitivity of current diagnostic methods and the difficulty in identifying minimal cancer cells within the body. This study employed a patient-derived xenograft (PDX) mouse model to screen for biomarkers, leveraging its advantage of low background interference compared to human serum exosome studies. Using a novel microextraction technique, exosomes were isolated from just one microliter of serum from HCC PDX mice, followed by proteomic profiling. Analysis revealed that serum exosomal proteins from PDX mice were enriched in cancer-related pathways. The exosomal proteome not only distinguished PDX mice from controls but also differentiated between individual PDX groups, supporting its use as a tumor-specific identifier (tumor ID) and a noninvasive tool for monitoring tumors. Bioinformatics identified a panel of serum exosomal protein biomarkers predictive of HCC patient outcomes, which were validated via targeted proteomics and array-based high-throughput detection. These upregulated biomarkers in HCC patients positively correlate with disease severity and poor prognosis, underscoring their clinical potential.

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Publication Details

Journal
Journal of Proteome Research
Published
2025-09-09
DOI
https://doi.org/10.1021/acs.jproteome.5c00307
Citations
1
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
0.81
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article

Exosomal Proteome from Hepatocellular Carcinoma Patient-Derived Xenograft Mice Serves as Identity of Liver Cancer

Fabao Gao, Zilin Li, Zhenpeng Zhang, Lianghai Hu et al.
1 citations
Journal of Proteome Research
Extracellular vesicles in disease
0.81
article

Exosomal Proteome from Hepatocellular Carcinoma Patient-Derived Xenograft Mice Serves as Identity of Liver Cancer

Fabao Gao, Zilin Li, Zhenpeng Zhang, Lianghai Hu, Yanchang Li, Tao Zuo, Lei Chang, Ping Xu, Fenglong Jiao, Fengsong Liu, Tao Zhang, Yali Zhang, Yangjun Zhang, Yihao Wang, Xin Feng, Yuanyuan Ruan, Zhen Sun, Peiru Chen, Li Yuan, Yao Zhang, Mingsong Mao
article en
1 citations

Abstract

Hepatocellular carcinoma (HCC) constitutes approximately 90% of liver cancers, yet its early detection remains challenging due to the low sensitivity of current diagnostic methods and the difficulty in identifying minimal cancer cells within the body. This study employed a patient-derived xenograft (PDX) mouse model to screen for biomarkers, leveraging its advantage of low background interference compared to human serum exosome studies. Using a novel microextraction technique, exosomes were isolated from just one microliter of serum from HCC PDX mice, followed by proteomic profiling. Analysis revealed that serum exosomal proteins from PDX mice were enriched in cancer-related pathways. The exosomal proteome not only distinguished PDX mice from controls but also differentiated between individual PDX groups, supporting its use as a tumor-specific identifier (tumor ID) and a noninvasive tool for monitoring tumors. Bioinformatics identified a panel of serum exosomal protein biomarkers predictive of HCC patient outcomes, which were validated via targeted proteomics and array-based high-throughput detection. These upregulated biomarkers in HCC patients positively correlate with disease severity and poor prognosis, underscoring their clinical potential.

Journal of Proteome ResearchVol. 24(10)
Guangzhou University of Chinese Medicine (CN), OSRAM (United States) (US), Guizhou University (CN), Jilin University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Fudan University (CN), Second Affiliated Hospital of Guangzhou Medical University (CN), Ministry of Public Health (AF), Institute of Life Sciences (IN), Jilin Medical University (CN), Society of Environmental Toxicology and Chemistry (US), Beijing Proteome Research Center (CN), Hebei University (CN), Indiana University School of Medicine, China Medical University (CN), Guangzhou Medical University (CN)
Openalex Percentile: Top 24%
Extracellular vesicles in disease
0.81
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