Functional modules analysis based on coexpression network in pancreatic ductal adenocarcinoma

Area of Science:

• Oncology
• Molecular Biology
• Genomics

Background:

• Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent exocrine pancreatic cancer, representing over 80% of pancreatic malignancies.
• Despite advances in understanding its molecular underpinnings, a complete comprehension of PDAC pathogenesis remains elusive.

Purpose of the Study:

• To identify differentially expressed genes (DEGs) in PDAC compared to normal tissue.
• To construct a co-expression network of DEGs and identify functional modules.
• To elucidate the molecular mechanisms underlying PDAC development and progression.

Main Methods:

• Differential gene expression analysis between PDAC and normal tissues.
• Construction of a gene co-expression network using pairwise correlation coefficients of DEGs.
• Application of the MCODE algorithm for identifying functional gene modules within the network.

Main Results:

• Identification of differentially expressed genes (DEGs) in PDAC.
• Construction of a co-expression network revealing ten distinct functional modules.
• Strong evidence suggesting that dysregulation in immune response, homeostasis, and cell adhesion pathways significantly contributes to PDAC.

Conclusions:

• The identified gene modules and pathways provide a foundation for understanding PDAC.
• Dysregulation of immune response, homeostasis, and cell adhesion are implicated in PDAC development and progression.
• Further research is warranted to validate the suggested molecular interactions in PDAC.