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Cancer Chemotherapy and Pharmacology 2018-Feb

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

Watumiaji waliosajiliwa tu ndio wanaweza kutafsiri nakala
Ingia / Ingia
Kiungo kimehifadhiwa kwenye clipboard
Lee Cheng Phua
Shixu Goh
David Wai Meng Tai
Wei Qiang Leow
Syed Muhammad Fahmy Alkaff
Chung Yip Chan
Juinn Huar Kam
Tony Kiat Hon Lim
Eric Chun Yong Chan

Maneno muhimu

Kikemikali

OBJECTIVE

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.

CONCLUSIONS

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.

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