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Cancer Chemother Pharmacol. 2018 Feb;81(2):277-289. doi: 10.1007/s00280-017-3475-6. Epub 2017 Dec 1.

Metabolomic prediction of treatment outcome in pancreatic ductal adenocarcinoma patients receiving gemcitabine.

Author information

1
Department of Clinical Translational Research, Singapore General Hospital, Singapore, Singapore. leecheng.phua@gmail.com.
2
Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore, Singapore.
3
Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore.
4
Department of Pathology, Singapore General Hospital, Singapore, Singapore.
5
Department of Hepato-Pancreato-Biliary and Transplant Surgery, Singapore General Hospital, Singapore, Singapore.
6
Department of Pathology, Singapore General Hospital, Singapore, Singapore. lim.kiat.hon@singhealth.com.sg.
7
Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore, Singapore. phaccye@nus.edu.sg.

Abstract

PURPOSE:

Resistance to gemcitabine remains a key challenge in the treatment of pancreatic ductal adenocarcinoma (PDAC), necessitating the constant search for effective strategies for a priori prediction of clinical outcome. While the existing studies focused on aberration of drug disposition genes and proteins as molecular predictors of gemcitabine treatment outcomes, the metabolic aberration associated with chemoresistance in clinical PDAC has been neglected. This exploratory study investigated the potential role of tissue metabolomics in characterizing the clinical treatment outcome of gemcitabine therapy.

METHODS:

Surgically resected tumors from PDAC patients who underwent gemcitabine-based adjuvant chemotherapy (n = 25) were subjected to metabotyping using gas chromatography/time-of-flight mass spectrometry (GC/TOFMS).

RESULTS:

A partial least-squares discriminant analysis (PLS-DA) model clearly distinguished patients who had favorable survival [overall survival (OS) > 24 months] from those who exhibited poorer survival (OS < 16 months) (Q 2 = 0.302). Receiver-operating characteristic analysis demonstrated the robustness of the PLS-DA model with an area under the curve of 1. PLS-DA revealed 19 marker metabolites (e.g., lactic acid, proline, and pyroglutamate) that shed insights into the chemoresistance of gemcitabine in PDAC. Particularly, tissue levels of lactic acid complemented transcript expression levels of human equilibrative nucleoside transporter 1 in distinguishing patients according to their overall survival.

CONCLUSION:

This work established proof-of-principle for GC/TOFMS-based global metabotyping of PDAC and laid the foundation for future discovery of metabolic biomarkers predictive of gemcitabine resistance in PDAC chemotherapy.

KEYWORDS:

Gas chromatography/time-of-flight mass spectrometry; Gemcitabine; Metabolic profiling; Metabolomics; Metabonomics; Pancreatic ductal adenocarcinoma; Pharmacometabolomics; Pharmacometabonomics

PMID:
29196965
DOI:
10.1007/s00280-017-3475-6
[Indexed for MEDLINE]

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