Evidence map›Paper›PMID 38748636›Full record

ArticleDatabase : the journal of biological databases and curation2024

PMBC: a manually curated database for prognostic markers of breast cancer.

Jiabei Liu, Yiyi Yu, Mingyue Li, Yixuan Wu, Weijun Chen, Guanru Liu, Lingxian Liu, Jiechun Lin, Chujun Peng, Weijun Sun and 2 more

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Jiabei LiuSchool of Automation, Guangdong University of Technology, 100 Outer Ring West Road, Guangzhou University City, Panyu District, Guangzhou 510006, China.
Yiyi YuSchool of Automation, Guangdong University of Technology, 100 Outer Ring West Road, Guangzhou University City, Panyu District, Guangzhou 510006, China.
Mingyue LiSchool of Automation, Guangdong University of Technology, 100 Outer Ring West Road, Guangzhou University City, Panyu District, Guangzhou 510006, China.
Yixuan WuSchool of Automation, Guangdong University of Technology, 100 Outer Ring West Road, Guangzhou University City, Panyu District, Guangzhou 510006, China.
Weijun ChenSchool of Automation, Guangdong University of Technology, 100 Outer Ring West Road, Guangzhou University City, Panyu District, Guangzhou 510006, China.
Guanru LiuSchool of Automation, Guangdong University of Technology, 100 Outer Ring West Road, Guangzhou University City, Panyu District, Guangzhou 510006, China.
Lingxian LiuSchool of Automation, Guangdong University of Technology, 100 Outer Ring West Road, Guangzhou University City, Panyu District, Guangzhou 510006, China.
Jiechun LinSchool of Automation, Guangdong University of Technology, 100 Outer Ring West Road, Guangzhou University City, Panyu District, Guangzhou 510006, China.
Chujun PengSchool of Automation, Guangdong University of Technology, 100 Outer Ring West Road, Guangzhou University City, Panyu District, Guangzhou 510006, China.
Weijun SunSchool of Automation, Guangdong University of Technology, 100 Outer Ring West Road, Guangzhou University City, Panyu District, Guangzhou 510006, China.
Xiaoli WuSchool of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, 100 Outer Ring West Road, Guangzhou University City, Panyu District, Guangzhou 510006, China.
Xin ChenSchool of Automation, Guangdong University of Technology, 100 Outer Ring West Road, Guangzhou University City, Panyu District, Guangzhou 510006, China.

Funding

Basic Research Project (Dengfeng hospital) jointly Funded by Guangzhou City and University 202201020586National Natural Science Foundation of China 62003094 and 82003615Science and Technology Projects in Guangzhou 202102020573 and 202201010147
6 · The paper itself

Abstract

Breast cancer is notorious for its high mortality and heterogeneity, resulting in different therapeutic responses. Classical biomarkers have been identified and successfully commercially applied to predict the outcome of breast cancer patients. Accumulating biomarkers, including non-coding RNAs, have been reported as prognostic markers for breast cancer with the development of sequencing techniques. However, there are currently no databases dedicated to the curation and characterization of prognostic markers for breast cancer. Therefore, we constructed a curated database for prognostic markers of breast cancer (PMBC). PMBC consists of 1070 markers covering mRNAs, lncRNAs, miRNAs and circRNAs. These markers are enriched in various cancer- and epithelial-related functions including mitogen-activated protein kinases signaling. We mapped the prognostic markers into the ceRNA network from starBase. The lncRNA NEAT1 competes with 11 RNAs, including lncRNAs and mRNAs. The majority of the ceRNAs in ABAT belong to pseudogenes. The topology analysis of the ceRNA network reveals that known prognostic RNAs have higher closeness than random. Among all the biomarkers, prognostic lncRNAs have a higher degree, while prognostic mRNAs have significantly higher closeness than random RNAs. These results indicate that the lncRNAs play important roles in maintaining the interactions between lncRNAs and their ceRNAs, which might be used as a characteristic to prioritize prognostic lncRNAs based on the ceRNA network. PMBC renders a user-friendly interface and provides detailed information about individual prognostic markers, which will facilitate the precision treatment of breast cancer. PMBC is available at the following URL: http://www.pmbreastcancer.com/.

Indexed as

Biomarkers, TumorBreast NeoplasmsDatabases, GeneticData CurationFemaleGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansPrognosisRNA, Long NoncodingRNA, MessengerBiomarkers, TumorRNA, Long NoncodingRNA, Messenger

Identifiers

PMID38748636
PMCPMC11095525

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.