Metabolomic Profiling Reveals Cellular Reprogramming of B-Cell Lymphoma by a Lysine Deacetylase Inhibitor through the Choline Pathway

Benet Pera, Jan Krumsiek, Sarit E Assouline, Rossella Marullo, Jayeshkumar Patel, Jude M Phillip, Lidia Román, Koren K Mann, Leandro Cerchietti, Benet Pera, Jan Krumsiek, Sarit E Assouline, Rossella Marullo, Jayeshkumar Patel, Jude M Phillip, Lidia Román, Koren K Mann, Leandro Cerchietti

Abstract

Despite the proven clinical antineoplastic activity of histone deacetylase inhibitors (HDACI), their effect has been reported to be lower than expected in B-cell lymphomas. Traditionally considered as "epigenetic drugs", HDACI modify the acetylation status of an extensive proteome, acting as general lysine deacetylase inhibitors (KDACI), and thus potentially impacting various branches of cellular metabolism. Here, we demonstrate through metabolomic profiling of patient plasma and cell lines that the KDACI panobinostat alters lipid metabolism and downstream survival signaling in diffuse large B-cell lymphomas (DLBCL). Specifically, panobinostat induces metabolic adaptations resulting in newly acquired dependency on the choline pathway and activation of PI3K signaling. This metabolic reprogramming decreased the antineoplastic effect of panobinostat. Conversely, inhibition of these metabolic adaptations resulted in superior anti-lymphoma effect as demonstrated by the combination of panobinostat with a choline pathway inhibitor. In conclusion, our study demonstrates the power of metabolomics in identifying unknown effects of KDACI, and emphasizes the need for a better understanding of these drugs in order to achieve successful clinical implementation.

Keywords: Choline pathway; DLBCL; Metabolomics; PI3K; Panobinostat.

Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Figures

Fig. 1
Fig. 1
Metabolic profiling reveals changes in choline metabolism of DLBCL patients treated with panobinostat. (a) Treatment arms (left) and treatment schedule (right) of the phase 2 trial. Blood samples were collected prior and post panobinostat in both arms. (b) Volcano plot showing circulating metabolites that significantly changed their levels after panobinostat treatment. (c) Box plot of plasma betaine determined for each patient pre and post panobinostat treatment.
Fig. 2
Fig. 2
Panobinostat treatment prompts choline pathway dependency on DLBCL cell lines. (a) Levels of choline intracellular metabolites measured pre and post panobinostat treatment in the DLBCL cell line OCI-Ly1. P-Cho phosphocholine, CDP-Cho cytidine 5′-diphosphocholine, Pht-Cho phosphatidilcholine, SLC4 Solute Carrier Family 44, CHKA choline kinase alpha, PCYT1A Phosphate Cytidylyltransferase 1A, CHPT1 Choline Phosphotransferase 1, CHDH Choline Dehydrogenase, BADH Betaine-aldehyde dehydrogenase. (b) Changes in mRNA levels of choline-related enzymes inOCI-Ly1 cells treated with 120 nM of panobinostat (c) Representative western blots for choline kinase alpha (CHKA), phosphate cytidylyltransferase 1 (PCYT1A) and acetyl-histone H3 (H3-Ac) from OCI-Ly1 cells treated with 120 nM panobinostat for 3 and 6 h (left). Quantification of the CHKA and PCYT1A protein levels after treatment (right). (d) Change of GI50 of the CHKA inhibitor CK37 in four DLBCL cell lines after exposure for 48 h to vehicle (black dots) or panobinostat (blue dots) accordingly to the schedule shown on top. (e) Change in cell growth of OCI-Ly1 cells in medium with and without choline upon treatemnt with vehicle (DMSO) or panobinostat 10 nM according to the schedule shown on top. In panels B, C, D and E, data are represented as median ± SEM.
Fig. 3
Fig. 3
Choline pathway dependency is linked to the activation of the PI3K pathway in the DLBCL cell line OCI-Ly1. (a) Deviation score vs. the effect differential illustrates the distribution and the number of compounds having enhanced susceptibility with (magenta) and without (blue) panobinostat pretreatment (left). Distribution and number of compounds within each category are denoted above the plot. Inset shows key targets representing high differential effect and deviation score (center). Network illustrating key interactions based on the targets of the 48 compounds identified to have greater effect than the CHKA inhibitor CK37 (right). Panobinostat pretreatment consisted in 10 nM exposure for 48 h. All compounds of the library were tested at 10 μM final concentration. (b) GI50 at 48 h of PI3K and MAPK inhibitors in OCI-Ly1 cells pretreated with vehicle (black dots) or 10 nM panobinostat (blue dots) for 48 h. (c) Viability (bottom) of OCI-Ly1 cells transfected with CHKA siRNA, pretreated with vehicle or 10 nM panobinostat, and exposed to 100 μM of the PI3K inhibitor AZD8186 for 24 h after pretreatment (top). (d) Viability (top) and caspase 3/7 activity (bottom) of OCI-Ly1 cells pretreated with vehicle or 10 nM panobinostat for 48 h, and then treated with 10 μM of the CHKA inhibitor CK37 (CHKAi) (left) or 100 μM of the PI3K inhibitor AZD8186 (right), with or without 100 μM phosphatidic acid (Ph. Acid) for the specified times. Data are represented as median ± SEM. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 4
Fig. 4
CUDC-907 effect relies on the induction of PI3K dependency through choline pathway activation. (a) Viability (center) and caspase-3/7 activity (right) of OCI-Ly1 cells after 24 h at the specified treatments (120 nM panobinostat or 10 μM of AZD8186, GDC-0941 or CUDC-907). (b) Viability (left) and caspase-3/7 activity (right) of OCI-Ly1 cells transfected with CHKA siRNA and treated for 24 h with 100 μM of CUDC-907. Data are represented as ± SEM.
Fig. 5
Fig. 5
Combined treatment with panobinostat and CK37 results in tumor growth reduction on OCI-Ly1 xenografts. (a) Treatment doses and schedule (left) and tumor growth curves (right) for mice receiving vehicle, panobinostat, CK37 or both drugs. (b) Mouse weight curves for all the four cohorts. (c) Quantitative plots (top) and representative images (bottom) from the OCI-Ly1 mice tumors at day 16, assayed for apoptosis by TUNEL (left) and for proliferation by Ki67 immunostaining (right). Data are represented as median ± SEM.

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