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A comprehensive meta-analysis of transcriptome data to identify signature genes associated with pancreatic ductal

Shirin Omidvar Kordshouli1, Ahmad Tahmasebi1, Ali Moghadam1

  • 1Institute of Biotechnology, Shiraz University, Shiraz, Iran.

Plos One
|February 7, 2024
PubMed
Summary
This summary is machine-generated.

This study identified key genes for pancreatic cancer by analyzing gene expression data. These identified genes, including EMP1 and RAB11FIP3, show potential as early diagnostic biomarkers and therapeutic targets for pancreatic ductal adenocarcinoma (PDAC).

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis due to late diagnosis and aggressive tumor behavior.
  • Lack of reliable early diagnostic biomarkers contributes to high mortality rates in PDAC patients.

Approach:

  • Integrated transcriptome data from 11 microarrays using meta-analysis to identify differentially expressed genes (DEGs).
  • Performed co-expression analysis, functional enrichment (GO, KEGG), and survival analyses to identify prognostic biomarkers.
  • Identified regulatory factors including transcription factors (TFs), protein kinases (PKs), and miRNAs involved in PDAC.

Key Points:

  • Identified 1074 DEGs, with significant enrichment in HIF-1 signaling and focal adhesion pathways.
  • Discovered 64 protein kinases, with the CAMK family being most abundant, and 23 TF families.
  • Weighted gene co-expression network analysis (WGCNA) highlighted modules enriched in Ras, p53, and MAPK signaling pathways.
  • Identified EMP1 and RAB11FIP3 as genes significantly related to PDAC prognosis.

Conclusions:

  • Identified critical genes for PDAC through meta-analysis and systems biology.
  • These genes represent potential targets for PDAC treatment and prognosis.