Bioinformatics analysis of the prognostic biomarkers and predictive accuracy of differentially expressed genes in high-risk multiple myeloma based on Gene Expression Omnibus database mining.

ABSTRACT:

Background

Multiple myeloma (MM) is still an intractable disease for modern clinical system, and more researches are necessary for development of more effective therapeutic strategies. This study attempted to screen and validates the biomarkers in the progression of MM via excavating Gene Expression Omnibus (GEO) database. Identification of a biomarker may help not only facilitate early diagnosis and management but also identify individuals at risk for poor prognosis and development of MM.

Methods

The mRNA expression profile of the GSE87900 dataset was analyzed by GEO2R. Using the SangerBox online program, differentially expressed genes (DEGs) in high-risk MM samples were screened with the filter criteria of P<0.05 and |logFC| >1. The SangerBox online analysis tool was used

SUBMITTER: Du C 

PROVIDER: S-EPMC9843371 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature