ExoBCD: a comprehensive database for exosomal biomarker discovery in breast cancer.


Journal

Briefings in bioinformatics
ISSN: 1477-4054
Titre abrégé: Brief Bioinform
Pays: England
ID NLM: 100912837

Informations de publication

Date de publication:
20 05 2021
Historique:
received: 13 12 2019
revised: 08 03 2020
accepted: 26 04 2020
pubmed: 28 6 2020
medline: 18 11 2021
entrez: 28 6 2020
Statut: ppublish

Résumé

Effective and safe implementation of precision oncology for breast cancer is a vital strategy to improve patient outcomes, which relies on the application of reliable biomarkers. As 'liquid biopsy' and novel resource for biomarkers, exosomes provide a promising avenue for the diagnosis and treatment of breast cancer. Although several exosome-related databases have been developed, there is still lacking of an integrated database for exosome-based biomarker discovery. To this end, a comprehensive database ExoBCD (https://exobcd.liumwei.org) was constructed with the combination of robust analysis of four high-throughput datasets, transcriptome validation of 1191 TCGA cases and manual mining of 950 studies. In ExoBCD, approximately 20 900 annotation entries were integrated from 25 external sources and 306 exosomal molecules (49 potential biomarkers and 257 biologically interesting molecules). The latter could be divided into 3 molecule types, including 121 mRNAs, 172 miRNAs and 13 lncRNAs. Thus, the well-linked information about molecular characters, experimental biology, gene expression patterns, overall survival, functional evidence, tumour stage and clinical use were fully integrated. As a data-driven and literature-based paradigm proposed of biomarker discovery, this study also demonstrated the corroborative analysis and identified 36 promising molecules, as well as the most promising prognostic biomarkers, IGF1R and FRS2. Taken together, ExoBCD is the first well-corroborated knowledge base for exosomal studies of breast cancer. It not only lays a foundation for subsequent studies but also strengthens the studies of probing molecular mechanisms, discovering biomarkers and developing meaningful clinical use.

Identifiants

pubmed: 32591816
pii: 5860692
doi: 10.1093/bib/bbaa088
pii:
doi:

Substances chimiques

Biomarkers, Tumor 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Auteurs

Xuanyi Wang (X)

Key Laboratory of Clinical Laboratory Diagnostics, College of Laboratory Medicine, Chongqing Medical University, Chongqing, China.

Zixuan Chai (Z)

Key Laboratory of Clinical Laboratory Diagnostics, College of Laboratory Medicine, Chongqing Medical University, Chongqing, China.

Guizhi Pan (G)

Key Laboratory of Clinical Laboratory Diagnostics, College of Laboratory Medicine, Chongqing Medical University, Chongqing, China.

Youjin Hao (Y)

College of Life Sciences, Chongqing Normal University, Chongqing, China.

Bo Li (B)

College of Life Sciences, Chongqing Normal University, Chongqing, China.

Ting Ye (T)

Key Laboratory of Clinical Laboratory Diagnostics, College of Laboratory Medicine, Chongqing Medical University, Chongqing, China.

Yinghong Li (Y)

Key Laboratory of Clinical Laboratory Diagnostics, College of Laboratory Medicine, Chongqing Medical University, Chongqing, China.

Fei Long (F)

Key Laboratory of Clinical Laboratory Diagnostics, College of Laboratory Medicine, Chongqing Medical University, Chongqing, China.

Lixin Xia (L)

Key Laboratory of Clinical Laboratory Diagnostics, College of Laboratory Medicine, Chongqing Medical University, Chongqing, China.

Mingwei Liu (M)

Key Laboratory of Clinical Laboratory Diagnostics, College of Laboratory Medicine, Chongqing Medical University, Chongqing, China.

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Classifications MeSH