Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/107484
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dc.contributorSchool of Optometryen_US
dc.contributorDepartment of Applied Biology and Chemical Technologyen_US
dc.contributorResearch Centre for SHARP Visionen_US
dc.creatorXu, Gen_US
dc.creatorHuang, Ren_US
dc.creatorWumaier, Ren_US
dc.creatorLyu, Jen_US
dc.creatorHuang , Men_US
dc.creatorZhang, Yen_US
dc.creatorChen, Qen_US
dc.creatorLiu, Wen_US
dc.creatorTao, Men_US
dc.creatorLi, Jen_US
dc.creatorTao, Zen_US
dc.creatorYu, Ben_US
dc.creatorXu, Een_US
dc.creatorWang, Len_US
dc.creatorYu, Gen_US
dc.creatorGires, Oen_US
dc.creatorZhou, Len_US
dc.creatorZhu, Wen_US
dc.creatorDing, Cen_US
dc.creatorWang, Hen_US
dc.date.accessioned2024-06-27T01:33:45Z-
dc.date.available2024-06-27T01:33:45Z-
dc.identifier.issn0008-5472en_US
dc.identifier.urihttp://hdl.handle.net/10397/107484-
dc.language.isoenen_US
dc.publisherAmerican Association for Cancer Researchen_US
dc.rights© 2024 The Authors; Published by the American Association for Cancer Researchen_US
dc.rightsThis open access article is distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Ganfei Xu, Rui Huang, Reziya Wumaier, Jiacheng Lyu, Minjing Huang, Yaya Zhang, Qingjian Chen, Wenting Liu, Mengyu Tao, Junjian Li, Zhonghua Tao, Bo Yu, Erxiang Xu, Lingfeng Wang, Guoying Yu, Olivier Gires, Lei Zhou, Wei Zhu, Chen Ding, Hongxia Wang; Proteomic Profiling of Serum Extracellular Vesicles Identifies Diagnostic Signatures and Therapeutic Targets in Breast Cancer. Cancer Res 1 October 2024; 84 (19): 3267–3285 is available at https://doi.org/10.1158/0008-5472.CAN-23-3998.en_US
dc.subjectBreast canceren_US
dc.subjectExtracellular vesiclesen_US
dc.subjectProteomicsen_US
dc.subjectTALDO1en_US
dc.subjectTarget therapyen_US
dc.titleProteomic profiling of serum extracellular vesicles identifies diagnostic signatures and therapeutic targets in breast canceren_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage3267en_US
dc.identifier.epage3285en_US
dc.identifier.volume84en_US
dc.identifier.issue19en_US
dc.identifier.doi10.1158/0008-5472.CAN-23-3998en_US
dcterms.abstractAnalysis of extracellular vesicles (EVs) is a promising noninvasive liquid biopsy approach for breast cancer (BC) detection, prognosis, and therapeutic monitoring. A comprehensive understanding of the characteristics and proteomic composition of BC-specific EVs from human samples is required to realize the potential of this strategy. In this study, we applied a mass spectrometry-based, data-independent acquisition (DIA) proteomic approach to characterize human serum EVs derived from patients with BC (n = 126) and healthy donors (HDs, n = 70) in a discovery cohort and validated the findings in five independent cohorts. Examination of the EV proteomes enabled construction of specific EV protein classifiers for diagnosing BC and distinguishing patients with metastatic disease. Of note, TALDO1 was found to be an EV biomarker of distant metastasis of BC. In vitro and in vivo analysis confirmed the role of TALDO1 in stimulating BC invasion and metastasis. Finally, high-throughput molecular docking and virtual screening of a library consisting of 271,380 small molecules identified a potent TALDO1 allosteric inhibitor, AO-022, which could inhibit BC migration in vitro and tumor progression in vivo. Together, this work elucidates the proteomic alterations in the serum EVs of BC patients to guide development of improved diagnosis, monitoring, and treatment strategies.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationCancer research, 1 Oct. 2024, v. 84, no. 19, p. 3267-3285en_US
dcterms.isPartOfCancer researchen_US
dcterms.issued2024-10-01-
dc.identifier.eissn1538-7445en_US
dc.description.validate202406 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera2890-n01-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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