Evidence map›Paper›PMID 35392358›Full record

ArticleApplied bionics and biomechanics2022

Bioinformatics Method Was Used to Analyze the Highly Expressed Gene FAM83A of Breast Cancer in Young Women.

Yongzhe Tang, Hao Wang, Qi He, Yuanyuan Chen, Jie Wang

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In one paragraph

Article in Applied bionics and biomechanics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

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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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Yongzhe TangThe International Peace Maternal and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Hao WangTeaching Center of Experimental Medicine, Shanghai Medical College, Fudan University, 138 Yixueyuan Rd, Shanghai 200032, China.
Qi HeThe International Peace Maternal and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Yuanyuan ChenThe International Peace Maternal and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Jie WangThe International Peace Maternal and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.ORCID https://orcid.org/0000-0003-3423-772X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Preliminary analysis of breast cancer related to unknown functional gene FAM83A through bioinformatics knowledge to inform further experimental studies. Select high expression genes for breast cancer and use bioinformatics methods to predict the biological function of FAM83A. Methods: Genes with significant differences in expression between breast tumors and normal breast tissue libraries were selected from CGAP's SAGE Digital Gene Expression Displayer (DGED) database. An unknown functional gene, FAM83A, which is highly expressed in breast cancer, was screened. We performed an analysis of the gene structure, subcellular localization, physicochemical properties of the encoding products, functional sites, protein structure, and functional domains. Results: Through SAGE DGED, a total of 185 genes with expression differences were found. The structure and function of FAM83A have ideal predictions, and it is generally determined that this gene encodes a nuclear protein with a nucleoprotein. The active site of PLDc and the functional domain of DUF1669 can be involved in signal transduction and gene expression regulation in tumorigenesis and metastasis. Digital gene representation of the Tumor Genome Project Data Library was used to select differentially expressed genes in breast cancer tissue and breast benign tumor tissue. Conclusion: Studies show that FAM83A is a potential research target associated with tumorigenesis and metastasis. Initial tests confirmed the expression of this gene. Lay a solid foundation for further research learning. FAM83A is a highly expressed gene in breast cancer and can serve as a target for studying molecular mechanisms in breast cancer.

Identifiers

PMID35392358
PMCPMC8983250

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