REGULATORYNETWORK-DRIVEN BIOMARKER DISCOVERYFORPANCREATIC DUCTALCARCINOMAANDPANCREATIC PSEUDOCYST

Abstract

Pancreatic ductal carcinoma (PDAC) is one of the most aggressive cancers that impact the pancreas. human pancreas. It has a dismal prognosis which is largely due to the fact that there are no early warning signs of the disease, An insidious course and often confusing diagnosis because of overlap in clinical features with non-malignant conditions. Although benign, pancreatic pseudocyst is a condition that is especially. also challenging in this aspect as it may have imaging and clinical characteristics that are similar to other conditions. Are similar to PDAC, creating diagnostic confusion. This thesis is a continuation of this final. A research paper was converted to a thorough research into systems biology focusing on regulatory Network analysis is proposed as a method to identify biomarkers in the two pancreatic diseases. The genes related to PDAC and pseudocyst of pancreas were obtained indi vidually from the The comparative toxicogenomics database (CTD) was used to determine the degree of overlap and it was evaluated using the Comparative Toxi cogenomics Database. intersection analysis with the other one has resulted in the identification of 31 common genes. These are regular genes, which were the basis for We are building the miRNA-gene and the transcription factor (TF) to gene connections, and also creating data on the pancreas tissue-specific connections between them. The analysis was carried out in regulatory networks with the Net workAnalyst platform. These were topologically examined by examining them as follows: Based on the networks constructed using degree centrality, we identified hsa-miR-34a-5p, hsa-miR-16-5p and hsa-miR-191-5p. The top miRNA hubs are 335-5p, and MYC, CCND1, VEGFA, RELA and CDKN1B. TFs and regulatory genes that stood out as prominent TFs or gene regulation hubs. In functional anal ysis, central nodes like the ones presented here are the ones around which the other nodes revolve. The roles they play in cell cycle control, resistance to apoptosis, inflammatory and antimicrobial response, regulation of metabolism, and matrix remodeling were all highlighted. signaling, the neovascularization process and dynamics of the tumor microenvironment. The results indicate that there may be a possibility of pairing some tumor iv suppressive miRNA hubs with oncogenic TF hubs. Increased levels of these could also predict the nature of the growth, and be included in a multi-marker diagnos tic panel that can distinguish malignant from nonmalignant. Benign pancreatic pseudocyst: PDAC. Because this present work is a completely computational work, experimental validation with patient-derived patient tissue, plasma or serum miRNA samples, An independent clinical datasets is still needed. However, the regulatory network. a biologically-inspired and interpretable starting point for the development of such a framework is provided here. Future work in development of pancreatic disease biomarkers.