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Metabolomic and Lipidomic Profiling of Plasma and Cyst Fluid Allows the Detection and Characterization of Pancreatic Intraductal Papillary Mucinous Neoplasms

32 Pages Posted: 10 Nov 2018

See all articles by Rogier Gaiser

Rogier Gaiser

Karolinska Institutet - Division of Clinical Diagnostics and Surgery

Alberto Pessia

Institute for Molecular Medicine Finland (FIMM)

Zeeshan Ateeb

Karolinska Institutet - Karolinska University Hospital

Haleh Davanian

Karolinska Institutet

Carlos Fernández Moro

Karolinska Institutet - Karolinska University Hospital

Sam Ghazi

Karolinska Institutet - Karolinska University Hospital

Roberto Valente

Karolinska Institutet - Karolinska University Hospital

Vidya Velagapudi

University of Helsinki

Margaret Sällberg Chen

Karolinska Institutet

Marco Del Chiaro

Karolinska Institutet - Division of Surgery

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Abstract

Background: Intraductal papillary mucinous neoplasm (IPMNs) of the pancreas may evolve from low- to high-grade dysplasia to invasive cancer. Accurate discrimination of IPMN-associated grade of dysplasia is an unmet clinical need for appropriate patient management and treatment. This study used an integrated metabolomics and lipidomics approach, aiming to define the metabolic profiles of IPMNs.

Methods: Metabolomic and lipidomic profiles of peri-operative pancreatic cyst fluid and pre-operative fasted plasma from IPMN and serous cystic neoplasm (SCN) patients were determined single-blinded in this pancreas resection cohort (n=31). Targeted (semi)quantitative analysis of 100 metabolites from 24 classes and >1000 lipid species spanning 13 classes were performed. The datasets were correlated against histological diagnosis and clinical parameters after correction for confounding factors. Group classification and model performance was done with Partial Least Squares Discriminant Analysis (PLS- DA) and a Leave-One-Out cross validation (LOO-CV) strategy, respectively. Variable Importance in Projection (VIP) ranking scores were used to select the best explanatory molecules.

Findings: Over 1000 different compounds were identified in plasma and cyst fluid. The IPMN biofluid profiles showed significant lipid pathway alterations compared to SCN controls. Integrated metabolomics and lipidomics data modeling allowed accurate discrimination between IPMN and SCN and could determine the IPMN-associated grade of dysplasia. Correlations were found between plasma lipid compounds of free fatty acids, ceramides, and triacylglycerol classes and the circulating levels of CA19-9, albumin and bilirubin (r>0·6, p<0·05).

Interpretation: An integrated metabolomic and lipidomic analysis of plasma or cyst fluid can improve discrimination of IPMN from SCN and within PMNs predict the grade of dysplasia, which is highly relevant for pancreatic surgery management.

Funding Statement: This work was supported by the Swedish Cancer Society (CAN2016/731 to MSC), (CAN 2014/634, CAN 2015/621, CAN 2017/409, CAN 2017/419 to MDC). Ruth och Richard Julins funds and Karolinska Institutet funds, SOF Strategic Odontological Research (to MSC). ALF SLL20150113 (to MDC), Biocenter Finland and HiLIFE, University of Helsinki (to AP and VV).

Declaration of Interests: "None."

Ethics Approval Statement: This study follows the Helsinki convention and good clinical practice with permission of the Ethical Review Board Stockholm and the Karolinska Biobank Board (Dnr 2015/1580- 31/1).

Keywords: Pancreatic cancer, IPMN, Cyst fluid, Metabolomics, Lipidomics, Biomarker, Mass Spectrometry, Metabolic pathway analysis

Suggested Citation

Gaiser, Rogier and Pessia, Alberto and Ateeb, Zeeshan and Davanian, Haleh and Moro, Carlos Fernández and Ghazi, Sam and Valente, Roberto and Velagapudi, Vidya and Chen, Margaret Sällberg and Chiaro, Marco Del, Metabolomic and Lipidomic Profiling of Plasma and Cyst Fluid Allows the Detection and Characterization of Pancreatic Intraductal Papillary Mucinous Neoplasms (September 17, 2018). Available at SSRN: https://ssrn.com/abstract=3280661

Rogier Gaiser (Contact Author)

Karolinska Institutet - Division of Clinical Diagnostics and Surgery ( email )

Granits väg 4
SE-171 77 Stockholm, Stockholm 17171
Sweden

Alberto Pessia

Institute for Molecular Medicine Finland (FIMM)

Helsinki, FIN-00014
Finland

HOME PAGE: http://https://www.fimm.fi/

Zeeshan Ateeb

Karolinska Institutet - Karolinska University Hospital

Solna, 17176
Sweden

Haleh Davanian

Karolinska Institutet

Granits väg 4
Solna, Stockholm 17171
Sweden

Carlos Fernández Moro

Karolinska Institutet - Karolinska University Hospital

Solna, 17176
Sweden

Sam Ghazi

Karolinska Institutet - Karolinska University Hospital

Solna, 17176
Sweden

Roberto Valente

Karolinska Institutet - Karolinska University Hospital

Solna, 17176
Sweden

Vidya Velagapudi

University of Helsinki

University of Helsinki
Helsinki, FIN-00014
Finland

Margaret Sällberg Chen

Karolinska Institutet

Granits väg 4
Solna, Stockholm 17171
Sweden

Marco Del Chiaro

Karolinska Institutet - Division of Surgery ( email )

Granits väg 4
SE-171 77 Stockholm, Stockholm 17171
Sweden

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