4.6 Article

Systematic analysis of the oncogenic role of FAM83D across cancers based on data mining

期刊

CELL CYCLE
卷 22, 期 8, 页码 1005-1019

出版社

TAYLOR & FRANCIS INC
DOI: 10.1080/15384101.2023.2171224

关键词

FAM83D; bioinformatics analysis; pan-cancer; differential expression; prognostic value; biomarker

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FAM83D is overexpressed in various cancers and may be associated with mutated TP53 and promoter DNA methylation. It is involved in progesterone-mediated oocyte maturation pathway, cell cycle regulation, and other signaling pathways. Therefore, differential expression of FAM83D could serve as a diagnostic and prognostic biomarker for various cancers.
Family with sequence similarity of 83D (FAM83D) is overexpressed in various cancers. However, no pan-cancer analysis is presently available. In the present study, we used a bioinformatics analysis to explore the diagnostic and prognostic value of FAM83D expression levels in human cancers. The GEPIA 2, TIMER 2.0, ENCORI, and DriverDBV3 databases were used to evaluate FAM83D expression levels. The potential prognostic value of FAM83D expression was analyzed using the GEPIA 2, UALCAN, and TISIB databases. The driver gene and promoter methylation levels regarding FAM83D were evaluated using the TIMER 2.0 and UALCAN databases. To further analyze interactive networks for FAM83D, FAM83D-binding proteins and related genes were determined using STRING and Gene MANIA analytic tools. Highly expressed FAM83D could be associated with mutated TP53 and promoter DNA methylation. Relative network analysis suggested that FAM83D was mainly involved in the progesterone-mediated oocyte maturation pathway, cell cycle regulation, and several other signaling pathways. Therefore, the differential expression of FAM83D could serve as a diagnostic and prognostic biomarker for various cancers. Our study revealed useful information about the differential expression of FAM83D, prognostic values, and potential functional networks in a variety of cancers, providing valuable substantive and methodological information to explore the underlying mechanisms.

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