• Bioinformatics Analysis of Circulating Tumor Cells in Pancreatic Ductal Adenocarcinoma Identifies LAMA2 and COMP as Potential Biomarkers in Metastatic Progression
  • Nika Azari,1,*
    1. University of Tehran, Department of Biotechnology


  • Introduction: Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related death globally and accounts for over 90% of pancreatic neoplasms. It is highly aggressive, often presenting with metastasis at diagnosis, which limits surgical options. Even after successful surgery, recurrence is common, with approximately 75% of patients dying from metastatic disease within five years. Research is increasingly focusing on circulating tumor cells (CTCs), which are shed into the bloodstream from the primary tumor and indicate early metastatic activity. Studying the molecular characteristics of CTCs is crucial for understanding metastasis, enhancing prognostic accuracy, and developing more individualized treatment approaches. This study focuses on a bioinformatics analysis of CTCs in PDAC to identify potential biomarkers and key pathways involved in metastasis.
  • Methods: Data were obtained from the Gene Expression Omnibus (GEO) dataset GSE18670. Differentially expressed genes (DEGs) were identified using R (version 4.0.2), with the MAS5 normalization method applied. Selection criteria included a log-fold change >2.5 and a p-value <0.001. The protein-protein interaction (PPI) network was constructed using the STRING database to explore interactions among DEGs. Gene visualization and clustering were performed using Gephi (version 0.10.1). Functional enrichment analysis was conducted using the Enrichr database, focusing on significant pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG 2021).
  • Results: Differential gene expression analysis comparing pancreatic tumor tissues and circulating tumor cells (CTCs) identified 4976 genes that were significantly altered (log₂FC > 2.5, p < 0.001). Clustering in Gephi revealed three major clusters with an eigenvector centrality > 0.3. Functional enrichment analysis using KEGG 2021 revealed significant overexpression of signaling pathways, including ECM-receptor interaction (adjusted p = 2.329E-39), focal adhesion (adjusted p = 8.534E-29), and PI3K-Akt signaling pathway (adjusted p = 1.447E-23). The identified hub genes were FN1, ITGA2, LAMB3, LAMC2, COL1A2, COL6A1, SPP1, ITGA6, ITGAV, LAMA2, and COMP. Among these, LAMA2 (log₂FC = 4.65, eigenvector centrality = 0.4) and COMP (log₂FC = 5.94, eigenvector centrality = 0.33) emerged as potential biomarkers for PDAC.
  • Conclusion: In conclusion, this bioinformatics analysis revealed significant differences in gene expression between pancreatic tumor tissues and CTCs. The results revealed substantial differences that highlight the pivotal signaling pathways implicated in the progression and metastasis of PDAC. The significant overexpression of genes within the ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathways aligns with existing knowledge that changes in expression are central to the metastatic capabilities of pancreatic cancer. The identification of established oncogenes such as FN1 and ITGA2, along with genes encoding collagen and laminin, supports the validity of this analytical approach and highlights the significance of these pathways in PDAC metastasis. This study identified two less-characterized genes, LAMA2 and COMP, as potential biomarkers for PDAC. Their significant upregulation and high network centrality suggest a central role in the molecular mechanisms that drive tumor cell dissemination. These hub genes appear to facilitate metastasis by participating in multiple steps of the metastatic cascade and by integrating signals from the extracellular matrix and intracellular pathways to promote tumor spread. The identification of these genes addresses the urgent need for novel biomarkers that can improve the limited specificity and sensitivity of current clinical options. Although metastasis in PDAC involves complex interactions with the tumor microenvironment and metabolic adaptations, the identification of key genetic drivers in CTCs offers valuable insight into the biology of metastasis. Additional experimental validation is required to confirm the diagnostic and prognostic potential of LAMA2 and COMP and to clarify their functional roles in PDAC metastasis. These findings advance the molecular understanding of PDAC and may support the development of more targeted therapeutic strategies for this aggressive malignancy.
  • Keywords: Pancreatic Ductal Adenocarcinoma, Biomarkers, Systems biology, Bioinformatics, Microarray Analysis