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Drug screening in human physiologic medium identifies uric acid as an inhibitor of rigosertib efficacy
Vipin Rawat, Patrick DeLear, Prarthana Prashanth, Mete Emir Ozgurses, Anteneh Tebeje, Philippa A. Burns, Kelly O. Conger, Christopher Solís, Yasir Hasnain, Anna Novikova, Jennifer E. Endress, Paloma González-Sánchez, Wentao Dong, Greg Stephanopoulos, Gina M. DeNicola, Isaac S. Harris, David Sept, Frank M. Mason, Jonathan L. Coloff
Vipin Rawat, Patrick DeLear, Prarthana Prashanth, Mete Emir Ozgurses, Anteneh Tebeje, Philippa A. Burns, Kelly O. Conger, Christopher Solís, Yasir Hasnain, Anna Novikova, Jennifer E. Endress, Paloma González-Sánchez, Wentao Dong, Greg Stephanopoulos, Gina M. DeNicola, Isaac S. Harris, David Sept, Frank M. Mason, Jonathan L. Coloff
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Research Article Cell biology Oncology

Drug screening in human physiologic medium identifies uric acid as an inhibitor of rigosertib efficacy

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Abstract

The nonphysiological nutrient levels found in traditional culture media have been shown to affect numerous aspects of cancer cell physiology, including how cells respond to certain therapeutic agents. Here, we comprehensively evaluated how physiological nutrient levels affect therapeutic response by performing drug screening in human plasma-like medium. We observed dramatic nutrient-dependent changes in sensitivity to a variety of FDA-approved and clinically trialed compounds, including rigosertib, an experimental cancer therapeutic that recently failed in phase III clinical trials. Mechanistically, we found that the ability of rigosertib to destabilize microtubules is strongly inhibited by the purine metabolism end product uric acid, which is uniquely abundant in humans relative to traditional in vitro and in vivo cancer models. These results demonstrate the broad and dramatic effects nutrient levels can have on drug response and how incorporation of human-specific physiological nutrient medium might help identify compounds whose efficacy could be influenced in humans.

Authors

Vipin Rawat, Patrick DeLear, Prarthana Prashanth, Mete Emir Ozgurses, Anteneh Tebeje, Philippa A. Burns, Kelly O. Conger, Christopher Solís, Yasir Hasnain, Anna Novikova, Jennifer E. Endress, Paloma González-Sánchez, Wentao Dong, Greg Stephanopoulos, Gina M. DeNicola, Isaac S. Harris, David Sept, Frank M. Mason, Jonathan L. Coloff

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Figure 1

Culture in HPLM changes sensitivity to a variety of therapeutic agents.

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Culture in HPLM changes sensitivity to a variety of therapeutic agents.
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(A) Percentage difference in the area under curve (% difference in AUC) data for SUM149 cells cultured in either RPMI or HPLM after treatment with anticancer and metabolic inhibitor libraries. Only compounds with a maximum effect of more than 50% in either medium are shown. (B) The same data as in A categorized based on target pathway. Box plots show the interquartile range, median (line), and minimum and maximum (whiskers). (C–F) Dose-response curves of the purine biosynthesis inhibitors lometrexol (C), azathioprine (D), 6-mercaptopurine (E), and 6-thioguanine (F) on SUM149 cells growing in RPMI versus HPLM. (G and H) Growth curves of HCC1806 (G) and SUM149 (H) cells treated with lometrexol in RPMI versus HPLM. (I) LC-MS analysis to quantify purine nucleotide abundance in HCC1806 cells treated with lometrexol in RPMI versus HPLM. * indicates P < 0.05 for HPLM + lometrexol relative to RPMI + lometrexol (unpaired 2-tailed t test). (J) Schematic representation of purine synthesis and salvage pathways. (K–N) Dose-response curves of the purine biosynthesis inhibitors lometrexol (K), azathioprine (L), 6-mercaptopurine (M), and 6-thioguanine (N) on SUM149 cells grown in RPMI with and without hypoxanthine (HXN). (O–R) Dose-response curves of the purine biosynthesis inhibitors lometrexol (O), azathioprine (P), 6-mercaptopurine (Q), and 6-thioguanine (R) on SUM149 cells grown in HPLM with and without HXN. For all panels data represent the means ± SD of triplicate samples.

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