Unveiling urinary extracellular vesicle mRNA signature for early diagnosis and prognosis of bladder cancer

<b>Background:</b> Bladder cancer (BC) ranks as one of the most prevalent cancers. Its early diagnosis is clinically essential but remains challenging due to the lack of reliable biomarkers. Extracellular vesicles (EVs) carry abundant biological cargoes from parental cells, rendering them as promising cancer biomarkers. Herein, we revealed that urinary EVs (uEVs) mRNA signature could serve as non-invasive biomarker for the early diagnosis and prognostic assessment for BC. <b>Methods:</b> Transcriptomic sequencing was conducted to reveal the mRNA signature of EVs collected from normal cell line and different grades of BC cell lines. Candidate EV-mRNA biomarkers were further profiled using clinical urine samples (<i>n</i> = 97, including healthy controls, BC patients and post-surgery BC patients) by RT-qPCR. <b>Results:</b> Three mRNAs (SRGN, FLI1, and MACROH2A2) within uEV were identified as potential biomarkers for BC, providing an area under the receiver operating characteristic curve (AUC) of 0.973 for BC diagnosis. Moreover, the uEV-mRNA panel could discriminate early-stage BC patients from healthy controls with an AUC of 0.969. Finally, we found that the uEV-mRNAs were significantly down-regulated in the post-surgery urine samples of BC patients. <b>Conclusions:</b> Given the facile and non-intrusive nature of urine collection, the identified uEV-mRNAs could serve as potential liquid-biopsy biomarkers for the early diagnosis and prognosis of BC.

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Publication Details

Journal
Theranostics
Published
2024-12-31
DOI
https://doi.org/10.7150/thno.107213
Citations
8
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
1.87

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article

Unveiling urinary extracellular vesicle mRNA signature for early diagnosis and prognosis of bladder cancer

Qiang Li, Yongchun Wei, Dingbin Liu, Ning Sun et al.
8 citations
Theranostics
Extracellular vesicles in disease
1.87
article

Unveiling urinary extracellular vesicle mRNA signature for early diagnosis and prognosis of bladder cancer

Qiang Li, Yongchun Wei, Dingbin Liu, Ning Sun, Rui Du, Zhaowei Zhang, Guangming Liu, Xiaoqing Yang, Hongmei Gao, Xiaoxuan Yu, Xiaoqin Hong, Jingqi Li, Jingjing Kang
article en
8 citations

Abstract

<b>Background:</b> Bladder cancer (BC) ranks as one of the most prevalent cancers. Its early diagnosis is clinically essential but remains challenging due to the lack of reliable biomarkers. Extracellular vesicles (EVs) carry abundant biological cargoes from parental cells, rendering them as promising cancer biomarkers. Herein, we revealed that urinary EVs (uEVs) mRNA signature could serve as non-invasive biomarker for the early diagnosis and prognostic assessment for BC. <b>Methods:</b> Transcriptomic sequencing was conducted to reveal the mRNA signature of EVs collected from normal cell line and different grades of BC cell lines. Candidate EV-mRNA biomarkers were further profiled using clinical urine samples (<i>n</i> = 97, including healthy controls, BC patients and post-surgery BC patients) by RT-qPCR. <b>Results:</b> Three mRNAs (SRGN, FLI1, and MACROH2A2) within uEV were identified as potential biomarkers for BC, providing an area under the receiver operating characteristic curve (AUC) of 0.973 for BC diagnosis. Moreover, the uEV-mRNA panel could discriminate early-stage BC patients from healthy controls with an AUC of 0.969. Finally, we found that the uEV-mRNAs were significantly down-regulated in the post-surgery urine samples of BC patients. <b>Conclusions:</b> Given the facile and non-intrusive nature of urine collection, the identified uEV-mRNAs could serve as potential liquid-biopsy biomarkers for the early diagnosis and prognosis of BC.

TheranosticsVol. 15(4)
Nankai University (CN), Tianjin First Center Hospital (CN), Second Hospital of Tianjin Medical University (CN), Tianjin Medical University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 14%
Extracellular vesicles in disease
1.87
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