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Pancreatic adenocarcinoma (PDAC) is the fourth leading cause of cancer death in Western countries. The PDAC tumour microenvironment (TME) is characterized by a dense stromal reaction, consisting of many cell types including fibroblasts and immune cells. The chemokine receptor, CX3CR1 forms a high-affinity axis with its unique ligand CX3CL1 and is expressed on monocytes, macrophages and T cells. CX3CR1 is also present on pancreatic malignant cells, where it has been associated with metastasis formation. The aim of my project is to investigate the role of CX3CR1 in the progression and development of pancreatic cancer in a genetically engineered mouse model of PDAC, the CX3CR1GFP/GFPLSL-KRASG12D/+LSL-Trp53R172H/+Pdx1-Cre (CKPC) mouse. In these mice, the CX3CR1 protein is not functional but they express GFP. I have found that the absence of CX3CR1 in KPC mice has no effect in their lifespan and response to chemotherapy. Comparison of the immune infiltrate of the tumours revealed that the lack of CX3CR1 causes a significant decrease in T cells and a possible increase in myeloid cells in CKPC mice compared to KPC mice. Expression analysis of several inflammatory cytokines in the TME showed a significant difference in IL-10 between KPC and CKPC mice. There was also a significant increase in levels of, CX3CL1, both locally and in the plasma. Finally, we performed RNA-seq on KPC and CKPC tumours. My analysis revealed 607 differentially-expressed genes, some of which encoded other chemokines or protein regulating the immune system. In particular, I observed the upregulation of Cxcl10 and Cxcl12, and the downregulation of Gata3 and S100a4, which could explain the decrease in T cells in the TME of CKPC mice. In conclusion, although the lack of CX3CR1 modifies the TME in this genetic model of PDAC, these changes do not affect the lifespan or the response to chemotherapy.

Cholangiocarcinoma (CCA) and pancreatic adenocarcinoma (PDAC) may lead to the development of extrahepatic obstructive cholestasis. However, biliary stenoses can also be caused by benign conditions, and the identification of their etiology still remains a clinical challenge. We performed metabolomic and proteomic analyses of bile from patients with benign (n = 36) and malignant conditions, CCA (n = 36) or PDAC (n = 57), undergoing endoscopic retrograde cholangiopancreatography with the aim of characterizing bile composition in biliopancreatic disease and identifying biomarkers for the differential diagnosis of biliary strictures. Comprehensive analyses of lipids, bile acids and small molecules were carried out using mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (1H-NMR) in all patients. MS analysis of bile proteome was performed in five patients per group. We implemented artificial intelligence tools for the selection of biomarkers and algorithms with predictive capacity. Our machine-learning pipeline included the generation of synthetic data with properties of real data, the selection of potential biomarkers (metabolites or proteins) and their analysis with neural networks (NN). Selected biomarkers were then validated with real data. We identified panels of lipids (n = 10) and proteins (n = 5) that when analyzed with NN algorithms discriminated between patients with and without cancer with an unprecedented accuracy

Pancreatic ductal adenocarcinoma, which represents 80% of pancreatic cancers, is mainly diagnosed when treatment with curative intent is not possible. Consequently, the overall five-year survival rate is extremely dismal—around 5% to 7%. In addition, pancreatic cancer is expected to become the second leading cause of cancer-related death by 2030. Therefore, advances in screening, prevention and treatment are urgently needed. Fortunately, a wide range of approaches could help shed light in this area. Beyond the use of cytological or histological samples focusing in diagnosis, a plethora of new approaches are currently being used for a deeper characterization of pancreatic ductal adenocarcinoma, including genetic, epigenetic, and/or proteo-transcriptomic techniques. Accordingly, the development of new analytical technologies using body fluids (blood, bile, urine, etc.) to analyze tumor derived molecules has become a priority in pancreatic ductal adenocarcinoma due to the hard accessibility to tumor samples. These types of technologies will lead us to improve the outcome of pancreatic ductal adenocarcinoma patients.