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METABOLOMIC CHARACTERIZATION OF PANCREATIC JUICE IN PANCREATIC CANCER: A NOVEL PROGNOSTIC TOOL?
Martina Nebbia*
1, Giovanni Capretti
1, Marialuisa Barbagallo
1, Laura Brunelli
2, Roberta Pastorelli
2, Greta Donisi
1, Federica Marchesi
1, Alessandro Zerbi
11Department of General Surgery, Humanitas Research Hospital & Humanitas University, Milan, Italy; 2Istituto di Ricerche Farmacologiche Mario Negri, Milano, Lombardia, Italy
Introduction: Analysis of metabolites in body fluids through mass spectrometry-based metabolomics is one of the key technologies to identify disease-specific profiles in different malignancies. Pancreatic cancer (PDAC) cells undergo extensive metabolic rearrangement during the process of tumor progression. Previously we demonstrated how metabolomic analysis of pancreatic juice (PJ) discriminated between PDAC and other non- malignant pancreatic lesions. This study aims to clarify whether different metabolic profiles in pancreatic juice of PDAC patients are associated to different clinical behavior.
Patients/Methods: Clinicopathologic data of patients undergoing surgical resection for PDAC at Humanitas Research Hospital were prospectively collected between 2010 and 2020. Pancreatic Juice (PJ) was collected intraoperatively in a subgroup of patients included in the present study. PJ was analyzed with high resolution mass spectrometry. Pre-elaboration of raw mass data was conducted using MATLAB, including metabolic cluster analysis.
Results: 58 patients were included in the analysis. Metabolomic analysis of PJ revealed three different metabolic clusters characterized by different metabolites expression: Cluster 1(C1), 2(C2) and 3(C3) including 22(37.9%), 30(51.7%) and 6(10.3%) cases, respectively. Patients from the three different clusters were homogeneous in term of age(p=0.808), sex(p=0.750), BMI(p=0.828) and preoperative Ca19.9(p=0.458). Out of 6 (10%) of PDAC originated in the context of IPMN and 11(19.0%) patients underwent neoadjuvant therapy (NAT), no difference was observed in metabolic profile between the groups (p=0.540 and p=0.510 respectively). C2 was associated to a lower rate of T3 tumors (C1: 50.0%, C2: 20.0%, C3:50.0%, p=0.056) and a lower rate of nodal metastases (C1: 90.9%, C2: 63.3%, C3:83.3%, p=0.065). No difference in prevalence of R1 margins (p=0.673), G3 tumors (p=0.642), perineural (p=0.226) and lymphovascular (p=0.258) invasion was observed. At multivariate analysis, C2 was independently associated to a lower prevalence of T3 tumors (OR0.17(0.03-0.88),p=0.035) and of nodal metastases (OR0.25(0.07-0.85),p=0.026).
Conclusions: Metabolomic analysis of pancreatic juice of PDAC patients revealed three different metabolic profiles. The correlation to well-known prognostic factors as T stage and nodal metastases suggests that different profiles might be associated with different clinical behaviors. This information might help in the future prognostic stratification of PDAC patients, guiding the selection of a more personalized therapeutic strategy.
Figure 1. Dendrogram of the cluster analysis on pancreatic juices of PC patients. Three clusters have been identified. Cluster 1: blu; Cluster 2: red; Cluster 3: yellow.
Figure 2. Variation of histo-pathological parameters in the three clusters.
A. T stage; B. N stage; C. G grade; D. Margin status; E. Perineural invasion; F. Lympho vascular invasion
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