Integrated bioinformatics analysis reveals upregulated extracellular matrix hub genes in pancreatic cancer: Implications for diagnosis, prognosis, immune infiltration, and therapeutic strategies.

Background: Pancreatic cancer (PC) stands out as one of the most formidable malignancies and exhibits an exceptionally unfavorable clinical prognosis due to the absence of well-defined diagnostic indicators and its tendency to develop resistance to therapeutic interventions. The primary objective of this present study was to identify extracellular matrix (ECM)-related hub genes (HGs) and their corresponding molecular signatures, with the intent of potentially utilizing them as biomarkers for diagnostic, prognostic, and therapeutic applications.

Methods: Three microarray datasets were sourced from the NCBI database to acquire upregulated differentially expressed genes (DEGs), while MatrisomeDB was employed for filtering ECM-related genes.