Screening feature genes of osteosarcoma with DNA microarray: a bioinformatic analysis

Area of Science:

• Oncology
• Genomics
• Bioinformatics

Background:

• Osteosarcoma (OS) poses significant challenges in early diagnosis and effective treatment.
• Identifying specific molecular markers is crucial for improving patient outcomes.

Purpose of the Study:

• To screen differentially expressed genes (DEGs) in osteosarcoma (OS) tissues compared to normal tissues.
• To identify potential diagnostic and therapeutic targets for OS.

Main Methods:

• Utilized microarray gene expression data (GES16088) from OS patients and healthy controls.
• Employed R language (Affy package) for DEG identification and bioinformatics tools (STRING, DAVID, WebGestalt) for functional analysis.
• Constructed a protein-protein interaction (PPI) network for the identified DEGs.

Main Results:

• Identified three significantly up-regulated genes in OS tissues compared to controls.
• The up-regulated gene COL was identified as a representative DEG.
• Functional analysis indicated these DEGs are associated with transmission signaling pathways and organ/system development.

Conclusions:

• The identified DEGs hold significant potential for understanding OS pathogenesis.
• These genes may serve as biomarkers for distinguishing normal from pathological OS tissues.
• The screened DEGs offer promising targets for OS monitoring, diagnosis, and treatment.