Faculty Collaboration Database

Metabolomic profiling of pancreatic adenocarcinoma reveals key features driving clinical outcome and drug resistance. EBioMedicine 2021 Apr;66:103332

Date

04/17/2021

Pubmed ID

33862584

Pubmed Central ID

PMC8054161

DOI

10.1016/j.ebiom.2021.103332

Scopus ID

2-s2.0-85104049834 (requires institutional sign-in at Scopus site)   23 Citations

Abstract

BACKGROUND: Although significant advances have been made recently to characterize the biology of pancreatic ductal adenocarcinoma (PDAC), more efforts are needed to improve our understanding and to face challenges related to the aggressiveness, high mortality rate and chemoresistance of this disease.

METHODS: In this study, we perform the metabolomics profiling of 77 PDAC patient-derived tumor xenografts (PDTX) to investigate the relationship of metabolic profiles with overall survival (OS) in PDAC patients, tumor phenotypes and resistance to five anticancer drugs (gemcitabine, oxaliplatin, docetaxel, SN-38 and 5-Fluorouracil).

FINDINGS: We identified a metabolic signature that was able to predict the clinical outcome of PDAC patients (p < 0.001, HR=2.68 [95% CI: 1.5-4.9]). The correlation analysis showed that this metabolomic signature was significantly correlated with the PDAC molecular gradient (PAMG) (R = 0.44 and p < 0.001) indicating significant association to the transcriptomic phenotypes of tumors. Resistance score established, based on growth rate inhibition metrics using 35 PDTX-derived primary cells, allowed to identify several metabolites related to drug resistance which was globally accompanied by accumulation of several diacy-phospholipids and decrease in lysophospholipids. Interestingly, targeting glycerophospholipid synthesis improved sensitivity to the three tested cytotoxic drugs indicating that interfering with metabolism could be a promising therapeutic strategy to overcome the challenging resistance of PDAC.

INTERPRETATION: In conclusion, this study shows that the metabolomic profile of pancreatic PDTX models is strongly associated to clinical outcome, transcriptomic phenotypes and drug resistance. We also showed that targeting the lipidomic profile could be used in combinatory therapies against chemoresistance in PDAC.

Author List

Kaoutari AE, Fraunhoffer NA, Hoare O, Teyssedou C, Soubeyran P, Gayet O, Roques J, Lomberk G, Urrutia R, Dusetti N, Iovanna J

Authors

Gwen Lomberk PhD Professor in the Surgery department at Medical College of Wisconsin
Raul A. Urrutia MD Center Director, Professor in the Surgery department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Adenocarcinoma
Animals
Antineoplastic Agents
Computational Biology
Databases, Genetic
Drug Resistance, Multiple
Drug Resistance, Neoplasm
Gene Expression Regulation, Neoplastic
Humans
Lipid Metabolism
Male
Metabolome
Metabolomics
Mice
Pancreatic Neoplasms
Phenotype