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Identification of combinatorial miRNA panels derived from extracellular vesicles as biomarkers for esophageal squamous cell carcinoma

MicroRNAs (miRNAs) are relatively stable in blood, emerging as one of the most promising biomarkers in tumor liquid biopsy. Both total and extracellular vesicles (EVs) encapsulated miRNA have been studied for prognostic potential in a variety of cancers. Here, we systematically compared and verified...

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Autores principales: Wang, Yaojie, Li, Xiaoya, Wei, Xiaojian, Li, Lei, Bai, Hanyu, Yan, Xi, Zhang, Hongtao, Zhao, Libo, Zhou, Wei, Zhao, Lianmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507283/
https://www.ncbi.nlm.nih.gov/pubmed/37731947
http://dx.doi.org/10.1002/mco2.377
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author Wang, Yaojie
Li, Xiaoya
Wei, Xiaojian
Li, Lei
Bai, Hanyu
Yan, Xi
Zhang, Hongtao
Zhao, Libo
Zhou, Wei
Zhao, Lianmei
author_facet Wang, Yaojie
Li, Xiaoya
Wei, Xiaojian
Li, Lei
Bai, Hanyu
Yan, Xi
Zhang, Hongtao
Zhao, Libo
Zhou, Wei
Zhao, Lianmei
author_sort Wang, Yaojie
collection PubMed
description MicroRNAs (miRNAs) are relatively stable in blood, emerging as one of the most promising biomarkers in tumor liquid biopsy. Both total and extracellular vesicles (EVs) encapsulated miRNA have been studied for prognostic potential in a variety of cancers. Here, we systematically compared and verified the total and vesicle‐derived miRNA expression profiles from plasma samples in healthy controls and patients with esophageal squamous cell carcinoma (ESCC). In the present study, four miRNA species miR‐636, miR‐7641, miR‐28‐3p, and miR‐1246 that were differentially expressed in ESCC patients were chosen for further study. We first elucidated their essential function in ESCC progression and further explored their preliminary mechanism by identifying target proteins and involving signal pathways. Subsequently, the prognostic miRNA panels including miR‐636, miR‐7641, miR‐1246, and miR‐28‐3p for ESCC diagnosis were constructed and validated using different cohort. Our results showed that the panel including the above four miRNAs derived from plasma EVs was most effective in distinguishing tumor patients from normal subjects, while integrated plasma EVs‐derived miR‐1246, miR‐28‐3p and total plasma miRNAs miR‐636, miR‐7641 showed the best capability in predicting lymph node metastasis. In summary, our studies revealed that plasma EVs‐derived miRNAs could be emerged as promising biomarkers for ESCC diagnosis.
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spelling pubmed-105072832023-09-20 Identification of combinatorial miRNA panels derived from extracellular vesicles as biomarkers for esophageal squamous cell carcinoma Wang, Yaojie Li, Xiaoya Wei, Xiaojian Li, Lei Bai, Hanyu Yan, Xi Zhang, Hongtao Zhao, Libo Zhou, Wei Zhao, Lianmei MedComm (2020) Original Articles MicroRNAs (miRNAs) are relatively stable in blood, emerging as one of the most promising biomarkers in tumor liquid biopsy. Both total and extracellular vesicles (EVs) encapsulated miRNA have been studied for prognostic potential in a variety of cancers. Here, we systematically compared and verified the total and vesicle‐derived miRNA expression profiles from plasma samples in healthy controls and patients with esophageal squamous cell carcinoma (ESCC). In the present study, four miRNA species miR‐636, miR‐7641, miR‐28‐3p, and miR‐1246 that were differentially expressed in ESCC patients were chosen for further study. We first elucidated their essential function in ESCC progression and further explored their preliminary mechanism by identifying target proteins and involving signal pathways. Subsequently, the prognostic miRNA panels including miR‐636, miR‐7641, miR‐1246, and miR‐28‐3p for ESCC diagnosis were constructed and validated using different cohort. Our results showed that the panel including the above four miRNAs derived from plasma EVs was most effective in distinguishing tumor patients from normal subjects, while integrated plasma EVs‐derived miR‐1246, miR‐28‐3p and total plasma miRNAs miR‐636, miR‐7641 showed the best capability in predicting lymph node metastasis. In summary, our studies revealed that plasma EVs‐derived miRNAs could be emerged as promising biomarkers for ESCC diagnosis. John Wiley and Sons Inc. 2023-09-18 /pmc/articles/PMC10507283/ /pubmed/37731947 http://dx.doi.org/10.1002/mco2.377 Text en © 2023 The Authors. MedComm published by Sichuan International Medical Exchange & Promotion Association (SCIMEA) and John Wiley & Sons Australia, Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Wang, Yaojie
Li, Xiaoya
Wei, Xiaojian
Li, Lei
Bai, Hanyu
Yan, Xi
Zhang, Hongtao
Zhao, Libo
Zhou, Wei
Zhao, Lianmei
Identification of combinatorial miRNA panels derived from extracellular vesicles as biomarkers for esophageal squamous cell carcinoma
title Identification of combinatorial miRNA panels derived from extracellular vesicles as biomarkers for esophageal squamous cell carcinoma
title_full Identification of combinatorial miRNA panels derived from extracellular vesicles as biomarkers for esophageal squamous cell carcinoma
title_fullStr Identification of combinatorial miRNA panels derived from extracellular vesicles as biomarkers for esophageal squamous cell carcinoma
title_full_unstemmed Identification of combinatorial miRNA panels derived from extracellular vesicles as biomarkers for esophageal squamous cell carcinoma
title_short Identification of combinatorial miRNA panels derived from extracellular vesicles as biomarkers for esophageal squamous cell carcinoma
title_sort identification of combinatorial mirna panels derived from extracellular vesicles as biomarkers for esophageal squamous cell carcinoma
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507283/
https://www.ncbi.nlm.nih.gov/pubmed/37731947
http://dx.doi.org/10.1002/mco2.377
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