Full Breakdown
Analysis of Differential Gene Expression in PDAC and T2D Patients
10/25/2025, 11:10:59 AM
Core Event: RNA-seq Data Analysis for PDAC and T2D
Recent research has focused on analyzing RNA-seq transcriptome data to identify differentially expressed genes (DEGs) in patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) and type 2 diabetes (T2D). The study utilized data from the European Genome-Phenome Archive (EGA) and the Gene Expression Omnibus (GEO) to compare gene expression profiles between PDAC patients, T2D patients, and healthy controls.
Methodology and Data Sources
The RNA-seq data for PDAC patients and healthy controls were sourced from the EGA with accession number EGAD00001006915. For T2D patients, data were obtained from GEO under accession GSE114192. The analysis was conducted using the Galaxy platform, employing tools such as HISAT2 for read alignment and DESeq2 for differential expression analysis. Significant DEGs were identified based on a log fold change (|logFC| > 0.58) and an adjusted p-value < 0.05.
Co-Expression Network Construction
To further understand the relationships between genes, a weighted gene co-expression network was constructed using the WGCNA software. The analysis involved calculating pairwise correlations and applying a soft-thresholding power to create an adjacency matrix. Modules of co-expressed genes were identified through hierarchical clustering, and module preservation analysis was performed to evaluate unique modules in the PDAC and T2D networks compared to control data.
Identification of Hub Genes and lncRNA Networks
The study identified hub genes within the co-expression network, which were further analyzed for their interactions using the STRING database and Cytoscape software. Long non-coding RNAs (lncRNAs) that correlated with these hub genes were also visualized, contributing to a comprehensive understanding of the gene interactions involved in PDAC and T2D.
Sample Collection and Ethical Considerations
Blood samples were collected from 100 participants, including 25 PDAC patients, 25 PDAC patients with T2D, 25 T2D patients, and 25 healthy controls, at Milad and Zahraye Marzieh hospitals in Isfahan, Iran, between June 2022 and September 2024. The study adhered to ethical guidelines as per the Helsinki declaration and received approval from the medical ethics committee of the University of Isfahan. Informed consent was obtained from all participants.
Statistical Analysis and Results
The analysis included various statistical tests to evaluate gene expression differences among the groups. The comparative Ct method was used for quantifying gene expression, and receiver operating characteristic (ROC) curve analyses were conducted to assess the diagnostic value of specific genes, such as CEBPZ, compared to traditional markers like CA19-9.
Conclusion and Future Directions
This study highlights the significant differences in gene expression between PDAC and T2D patients compared to healthy controls, providing insights into the molecular mechanisms underlying these diseases. Future research may focus on validating the identified DEGs and exploring their potential as biomarkers for early diagnosis and therapeutic targets.
