Comprehensive Analysis of Gene Expression Profiles in Pancreatic Cancer: Insights into Biomarkers and Therapeutic Targets

Introduction
Pancreatic cancer remains a highly deadly malignancy, with its progression driven by genetic changes and microenvironmental influences. Early lesions like intraductal papillary mucinous neoplasms (IPMNs) offer valuable insights into precursor biology and potential biomarkers for early detection. This research focused on examining gene expression differences across pancreatic IPMN subtypes, IPMA (adenoma), IPMC (carcinoma) and mixed IPMN, by comparing them to normal pancreatic tissues through analysing publicly available microarray data (GSE19650). The main goal was to identify differentially expressed genes and enriched biological pathways, which could shed light on the mechanisms underlying pancreatic tumour development.
Materials and Methods
This retrospective bioinformatics study examined gene expression data from the GEO database (GSE19650), including normal pancreatic tissues and IPMN subtypes. Differential gene expression was determined through standard pre-processing, normalization and statistical testing employing adjusted p-value thresholds to identify significant genes. Functional enrichment analyses, such as Gene Ontology and pathway analysis were conducted to explore biological relevance. The study did not involve any unpublished data or patient-identifiable information. When clinical data were available, survival analysis was performed. All statistical analyses were conducted using R software (version 4.x) with packages like limma and clusterprofiler applying appropriate cut-off thresholds and multiple testing corrections.
Results
Differential expression analysis identified unique molecular signatures among IPMA, IPMC and mixed IPMN groups. Genes like S100P showed increased expression in neoplastic tissues, whereas genes such as CELP and CELA2B were downregulated indicating a loss of normal pancreatic function. Enrichment analyses identified pathways involved in nuclear division and extracellular matrix organisation. However, survival analysis did not find statistically significant correlations.
Discussion
These findings underscore molecular differences among IPMN subtypes, confirming their biological diversity. The increased expression of immune-modulatory and tumour-related genes supports their known roles in pancreatic cancer development, while the reduced expression of digestive enzyme genes indicates a disruption in normal tissue function. Although survival analysis showed limited associations, this may be due to the small dataset and few clinical variables. Overall, the study emphasises the significance of pathway-level changes such as proliferative signalling and extracellular matrix remodelling, which may drive neoplastic transformation and progression.
Conclusions
This study identifies distinct gene expression patterns and enriched pathways across IPMN subtypes, offering insights into early pancreatic tumour development. Although biomarker candidates like S100P show promise, limited survival correlations highlight the complexity of prognostication. Larger datasets with comprehensive clinical information are required to refine molecular markers and advance personalised therapeutic approaches in pancreatic cancer research.