Assessment of l-Asparaginase Pharmacodynamics in Mouse Models of Cancer

Thomas D Horvath; Wai Kin Chan; Michael A Pontikos; Leona A Martin; Di Du; Lin Tan; Marina Konopleva; John N Weinstein; Philip L Lorenzi

doi:10.3390/metabo9010010

Assessment of l-Asparaginase Pharmacodynamics in Mouse Models of Cancer

Metabolites. 2019 Jan 9;9(1):10. doi: 10.3390/metabo9010010.

Authors

Thomas D Horvath¹, Wai Kin Chan², Michael A Pontikos³, Leona A Martin⁴, Di Du⁵, Lin Tan⁶, Marina Konopleva^{7

8}, John N Weinstein⁹, Philip L Lorenzi¹⁰

Affiliations

¹ Department of Bioinformatics and Computational Biology and The Proteomics and Metabolomics Core Facility, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. [email protected].
² Department of Bioinformatics and Computational Biology and The Proteomics and Metabolomics Core Facility, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. [email protected].
³ Department of Bioinformatics and Computational Biology and The Proteomics and Metabolomics Core Facility, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. [email protected].
⁴ Department of Bioinformatics and Computational Biology and The Proteomics and Metabolomics Core Facility, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. [email protected].
⁵ Department of Bioinformatics and Computational Biology and The Proteomics and Metabolomics Core Facility, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. [email protected].
⁶ Department of Bioinformatics and Computational Biology and The Proteomics and Metabolomics Core Facility, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. [email protected].
⁷ Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. [email protected].
⁸ Department of Stem Cell Transplantation, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. [email protected].
⁹ Department of Bioinformatics and Computational Biology and The Proteomics and Metabolomics Core Facility, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. [email protected].
¹⁰ Department of Bioinformatics and Computational Biology and The Proteomics and Metabolomics Core Facility, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. [email protected].

Abstract

l-asparaginase (ASNase) is a metabolism-targeted anti-neoplastic agent used to treat acute lymphoblastic leukemia (ALL). ASNase's anticancer activity results from the enzymatic depletion of asparagine (Asn) and glutamine (Gln), which are converted to aspartic acid (Asp) and glutamic acid (Glu), respectively, in the blood. Unfortunately, accurate assessment of the in vivo pharmacodynamics (PD) of ASNase is challenging because of the following reasons: (i) ASNase is resilient to deactivation; (ii) ASNase catalytic efficiency is very high; and (iii) the PD markers Asn and Gln are depleted ex vivo in blood samples containing ASNase. To address those issues and facilitate longitudinal studies in individual mice for ASNase PD studies, we present here a new LC-MS/MS bioanalytical method that incorporates rapid quenching of ASNase for measurement of Asn, Asp, Gln, and Glu in just 10 µL of whole blood, with limits of detection (s:n ≥ 10:1) estimated to be 2.3, 3.5, 0.8, and 0.5 µM, respectively. We tested the suitability of the method in a 5-day, longitudinal PD study in mice and found the method to be simple to perform with sufficient accuracy and precision for whole blood measurements. Overall, the method increases the density of data that can be acquired from a single animal and will facilitate optimization of novel ASNase treatment regimens and/or the development of new ASNase variants with desired kinetic properties.

Keywords: Erwinaze; Kidrolase; asparaginase; glutaminase; pharmacodynamics; targeted metabolomics.

Abstract

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