B cell receptor signaling regulates metabolism in Chronic ... · 1 Left running head: VANGAPANDU et al Re-Revised Version 1 . B Cell Receptor Signaling Regulates Metabolism in Chronic

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Left running head: VANGAPANDU et al Re-Revised Version 1

B Cell Receptor Signaling Regulates Metabolism in Chronic Lymphocytic Leukemia

Hima V. Vangapandu,1, 4

Ondrej Havranek,3, 4

Mary L. Ayres,1 Benny Abraham Kaipparettu,

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Kumudha Balakrishnan,1,4

William G. Wierda,2 Michael J. Keating,

2 R. Eric Davis,

3,4 Christine

M. Stellrecht,1, 4

and Varsha Gandhi1,2,4

1Department of Experimental Therapeutics and

2Department of Leukemia,

3Department of

Lymphoma/Myeloma, The University of Texas MD Anderson Cancer Center, Houston, TX; 4MD Anderson Cancer Center UT Health Graduate School of Biomedical Sciences, Houston,

Texas 5Department of Molecular and Human Genetics, Baylor College of Medicine, Houston,

Texas

Corresponding Author: Varsha Gandhi, Department of Experimental Therapeutics, The

University of Texas MD Anderson Cancer Center, Unit 1950, 1901 East Road, Houston, TX

77054; Tel. 713-792 2989; Email: [email protected].

Conflict-of-interest disclosure: V.G. received research funding from Infinity Pharmaceuticals

and Gilead Sciences. K.B. received research funding from Infinity Pharmaceuticals. Other

authors do not have a conflict of interest.

Running title: BCR Pathway Impacts CLL Metabolic Flux

Keywords: Leukemia, metabolism, OxPhos, B cell receptor, PI3 Kinase, ATP.

Financial Support: This work was supported in part by grant CLL PO1 CA81534 and by a

Cancer Center Support Grant, P50 CA16672, from the National Cancer Institute, Department of

Health and Human Services; a CLL Global Research Foundation Alliance grant; and Sponsored

Research Agreements from Infinity Pharmaceuticals and Gilead Sciences.

Word count: Abstract (225 words), Text (5298 words)

Figure and Table count: 5 figures; Reference count: 50; Supplementary data: 1 table, 7

figures

Scientific category: Biology of Human Tumors.

on June 15, 2020. © 2017 American Association for Cancer Research. mcr.aacrjournals.org Downloaded from

Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on August 23, 2017; DOI: 10.1158/1541-7786.MCR-17-0026

mailto:[email protected]

http://mcr.aacrjournals.org/

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Abstract

Chronic lymphocytic leukemia (CLL) cells are quiescent but have active transcription and

translation processes, suggesting that these lymphocytes are metabolically active. Based on this

premise, the metabolic phenotype of CLL lymphocytes was investigated by evaluating the two

intracellular ATP generating pathways. Metabolic flux was assessed by measuring glycolysis as

extracellular acidification rate (ECAR) and mitochondrial oxidative phosphorylation as oxygen

consumption rate (OCR) and then correlated with prognostic factors. Further, the impact of B-

cell receptor signaling (BCR) on metabolism was determined by genetic ablation and

pharmacological inhibitors. Compared with proliferative B-cell lines, metabolic fluxes of oxygen

and lactate were low in CLL cells. ECAR was consistently low, but OCR varied considerably in

human patient samples (n=45). Higher OCR was associated with poor prognostic factors such as

ZAP70 positivity, unmutated IGHV, high β2M levels, and higher Rai stage. Consistent with the

association of ZAP70 and IGHV unmutated status with active BCR signaling, genetic ablation of

BCR mitigated OCR in malignant B-cells. Similarly, knocking out PI3Kδ, a critical component

of the BCR pathway, decreased OCR and ECAR. In concert, PI3K pathway inhibitors,

dramatically reduced OCR and ECAR. In harmony with a decline in metabolomics, the

ribonucleotide pools in CLL cells were reduced with duvelisib treatment. Collectively, these data

demonstrate that CLL metabolism, especially OCR, is linked to prognostic factors and is curbed

by BCR and PI3K pathway inhibition.

Implications

This study identifies a relationship between oxidative phosphorylation in CLL and prognostic

factors providing rationale to therapeutically target these processes.




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Introduction

Unlike solid tumors, which are highly proliferative, chronic lymphocytic leukemia (CLL) is an

indolent malignancy characterized by the relentless accumulation of quiescent, immunologically

dysfunctional mature B cells that fail to undergo apoptosis. These cells reside in different

compartments such as bone marrow, spleen, lymph nodes, and peripheral blood which provide

diverse microenvironments. While the population is either slowly proliferating or quiescent (1),

these cells are transcriptionally and translationally active, suggesting that CLL cells are not inert

and should have an active metabolomics profile (2). Furthermore, this metabolomics précis

should correspond to the aggressiveness of the disease, which is categorized based on prognostic

factors such as ZAP 70 positivity (3,4), unmutated nature of immunoglobulin variable region

heavy chain (IGHV) status (5), higher Rai stage (6) and increased abundance of β2

microglobulin (β2M) (7).

Changes in the metabolome, which has been intensively investigated in solid tumors and is

initiated and activated by growth factors through growth-factor-receptor nexus which invariably

includes PI3Kα-isoform specific signal transduction pathway. The maintenance and production

of healthy and malignant B-cells is through B-cell receptor (BCR) axis. A primary node in the

BCR pathway is the PI3K/AKT cassette, which affects downstream activation of survival factors

in CLL cells. Among the four isoforms of PI3K, malignant CLL and other B-cells rely on

PI3Kδ/γ, the primary effector of BCR network. Our recent study suggested that in B-cell

malignancies, PI3Kδ mimicked a signaling pathway which was previously identified in solid

tumors with PI3Kα (8). Several investigations have established that the PI3Kα–mediated

signaling cascade influences the cellular metabolome, including glycolysis and energy

production (9). Newer studies further demonstrated a role for AKT in this pathway and AKT-




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dependent and AKT-independent activation of the cellular metabolome (10,11). However, the

role of PI3Kδ/γ in regulating the metabolome is not yet elucidated.

Based on these reports, we hypothesized that malignant CLL lymphocytes should have an active

metabolism and may show differential metabolome précis that are in line with the aggressiveness

of the disease based on prognostic markers. BCR and PI3K induced changes in the metabolome

should enhance the nucleotide biosynthesis needed for increased gene transcription and protein

translation. In accordance with these expectations, genetic or pharmacological intervention in

this pathway should impact metabolic changes.

To test these hypotheses, we compared the metabolic phenogram in freshly isolated CLL cells

from 45 patients. Bioenergetic profiles of CLL samples suggested diverse range in oxidative

phosphorylation (OxPhos) rates which were associated with prognostic characterization of the

disease. Genetic targeting of BCR pathway or knocking out PI3K resulted in mitigation of both

OxPhos and glycolysis. Corollary to this observation, pharmacological inhibition induced similar

results and correspondingly demonstrated a decrease in bioenergy.




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Materials and methods

CLL patient sample collection

Peripheral blood samples were collected from 77 CLL patients (Supplemental Table 1). All

patients had given written informed consent in accordance with the Declaration of Helsinki and

under a protocol approved by the Institutional Review Board (IRB) of The University of Texas

MD Anderson Cancer Center.

Normal PBMC, normal and malignant B cell collection and isolation

Peripheral blood (100 mL) was obtained in green top tubes from healthy human donors under a

MD Anderson Cancer Center IRB-approved protocol. Peripheral blood mononuclear cells

(PBMCs) were isolated using Ficoll-Hypaque procedure. Normal B cells were purified by

negative selection using Easy SepTM

Human B Cell Enrichment Kit (Stem Cell Technologies,

Vancouver, CA). For optimal comparison, same numbers of normal PBMCs (generally

containing T-lymphocytes), normal B lymphocytes or malignant CLL B cells were used for all

assays.

For CLL cells, cells were isolated from peripheral blood and PBMCs were separated by Ficoll-

Hypaque density centrifugation (Atlanta Biologicals). All experiments were performed using

freshly isolated CLL cells and purity of this cell population was ≥95%. Cells were cultured in

RPMI-1640 medium with L-glutamine + 10% human serum. For CLL and other primary cells to

stabilize in the in vitro conditions, cells were kept for 24 hours in culture. These primary cells

are replicationally quiescent and remain quiescent during the 24 hours of culture.

Drugs




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Duvelisib (IPI-145) was obtained from Infinity Pharmaceuticals and used at 1 μM. Idelalisib

(GS1101) was obtained from Gilead Sciences and MK-2206 from Selleck Chemicals; 1 μM

idelalisib and 2.5 μM MK-2206 were used in the experiments. These concentrations were

selected based on reported plasma concentrations of these drugs during clinical trials. All

compounds were dissolved in DMSO.

B-cell line cultures

Wherever needed, the mantle cell lymphoma (MCL) cell lines (JeKo-1, Sp53, and Mino) were

used either as control or as proliferative cell types. These three mantle cell lymphoma lines were

obtained from Dr. Hesham Amin, MD Anderson Cancer Center and represent BCR-reliant B-cell

lines (12). JeKo-1 and Sp53 were grown in RPMI 1640 with 10% FBS, while Mino was grown

in RPMI 1640 with 20% FBS and were used within six passages. These cell lines were

authenticated by the MD Anderson core facility using Short Tandem Repeat DNA profiling and

were routinely tested for Mycoplasma infection by the same core facility using the Lonza

MycoAlert Kit.

Cytotoxicity assays

To determine apoptotic and necrotic cells, CLL lymphocytes were stained with

annexin/propidium iodide and counted using flow cytometry as described previously (13).

Extracellular flux assays

Extracellular flux assays (Seahorse Bioscience, Chicopee, MA) were used to measure the oxygen

consumption rate (OCR) and extracellular acidification rate (ECAR) of CLL cells. In most cases,




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CLL cells (5 × 105) were plated in RPMI-1640 + 10% human serum in 6-well plates, with or

without duvelisib for 24 hours. For each assay, after treatment, cells were counted and equal

number of viable cells were used and plated onto XF microplates coated with Cell-Tak (BD

Biosciences, San Jose, CA) and allowed to adhere for 4-6 h. RPMI-1640 medium was replaced

with XF base (OCR) or glycolysis base (ECAR) media as recommended by Seahorse Bioscience.

Five technical replicates for each condition were plated. Glycolysis and cell mitochondrial stress

tests were performed as described previously (Supplemental Figure 1) (14). Generally for

OCR, data were expressed as basal OCR, which is the starting level of OCR (Supplemental

Figure 1). Oligomycin, an ATP coupler is added, followed by FCCP which acts as ETC

accelerator. Increase in OCR above basal respiration after FCCP addition is spare respiratory

capacity while total is maximal respiratory capacity. Addition of rotenone and antimycin A

shuts down mitochondrial respiration (Supplemental Figure 1A). ECAR is measured under

basal condition which increases after addition of glucose that provides glycolytic flux. Addition

of oligomycin measures the glycolytic capacity (Supplemental Figure 1B).

Mitochondrial reactive oxygen species, membrane potential, and mass

CLL cells were stained with MitoSOX Red, tetramethylrhodamine ethyl ester perchlorate

(TMRE), and MitoTracker Deep Red FM (Life Technologies, Carlsbad, CA), and analyzed using

FACS for mitochondrial reactive oxygen species (ROS), membrane potential and mass,

respectively. Geometric means of cytometric data were obtained using FlowJo software

(FlowJo, Ashland, OR).

PCR for mtDNA copy number




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QiaAMP DNA mini kit (Qiagen, Venlo, Limberg, Netherlands) was used to extract DNA from

CLL samples according to manufacturer’s protocol. qPCR SYBR green master mix was used to

amplify the mitochondrial DNA from 4 CLL patient samples. All samples were run in triplicate.

These experiments were conducted in collaboration with Dr. Benny Kaiparettu’s laboratory,

Baylor College of Medicine.

Electron transport chain activity analysis

Frozen cell pellets were lysed and then used for electron transport chain (ETC) enzyme assays

according to published procedures (15,16). Briefly, the enzymes were assayed at 30° C using a

temperature-controlled spectrophotometer; Ultraspec 6300 pro, Biochrom Ltd., (Cambridge,

England). Each assay was performed in triplicate. The activities of the five enzymes were

measured using appropriate electron acceptors/donors. These experiments were conducted in

collaboration with Dr. Benny Kaiparettu’s laboratory, Baylor College of Medicine.

Ribonucleotide pools

Perchloric acid was used to extract nucleotide pools, and pools were separated using HPLC as

described previously (14). Standard NTPs were used to quantitate nucleotide pools and the

concentration was determined based on mean cell volume.

Immunoblotting

Cells were washed and protein extracts were probed using an Odyssey Infrared Imaging System

(LI-COR Biosciences, Lincoln, NE) as described previously (14). p-AKT Thr308, AKT, p-

MAPK(44/42), MAPK, GAPDH (Cell Signaling Technology, Danvers, MA) and OxPhos

cocktail (Abcam, Cambridge, UK) primary antibodies were used.




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Glucose/glutamine uptake assays

CLL cells were suspended in glucose free or glutamine-free media and either [3H] 2-deoxy-D-

glucose (0.5 µL, specific activity 28 Ci/mmol) or [3H]L-glutamine (1 µL, specific activity 50.3

Ci/mmol) was added (both reagents from Perkin Elmer, Waltham, Massachusetts). The

radioactivity was quantified using the scintillation counter.

BCR Knock out

CRISPR-Cas9 px330 plasmids with BCR target DNA sequence constructs were donated by Dr.

Davis. JeKo-1 was used for genetic knock out experiments. This cell line expresses the

characteristic MCL proteins including cyclin D1, cyclin E, retinoblastoma (Rb), c-Myc, p21Waf-1

,

p27Kip-1

, Mcl-1, Bcl-2, Bax, and Bcl-xL. JeKo-1 overexpresses cyclin D3 and p16INK4a

, however,

lacks p53 (12). JeKo-1 cells were transfected (10 μg of plasmid DNA/million cells) by

electroporation (Neon® transfection system) according to the manufacturer’s protocol. Seventy-

two hr post transfection, the cells were stained and analyzed by flow cytometry for BCR heavy

chain (IgM) and light chain (κ) expression. The knockout (KO) cells were stained and sorted by

FACS on day 6 (Supplemental Figure 2). Three KO clones were generated, where the Cas9

construct harbored DNA sequences complimentary to different regions of CH2 domain of IGHM

gene which encodes a vital component of the BCR (TS4: CCCCCGCAAGTCCAAGCTCATC;

TS5: CAGGTGTCCTGGCTGCGCGAGGG; TS6: ACCTGCCGCGTGGATCACAGGGG.

Fluorescence Activated Cell Sorting




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For BCR KO experiments, IgM-FITC conjugate and light chain (κ) –PE conjugate antibodies

were obtained from Life Technologies (Carlsbad, CA). The cells were counted by Trypan Blue

staining and 2×107 cells were stained at 1 μL of sterile antibodies (IgM-FITC and light chain-PE)

/million cells in 1 mL of media and sorted by MD Anderson Cancer Center’s FACS facility. The

KO cells were collected in RPMI 1640 containing 20% FBS and 1% penicillin and streptomycin

solution. These cells were then centrifuged at 1500 rpm for 5 minutes and resuspended in RPMI

1640 + 10% FBS + 1% penicillin-streptomycin solution. Similarly, for PIK3CD KO

experiments, the KO cells were sorted based on GFP expression.

PIK3CD Knock in –Knock out

CRISPR-Cas9 mediated “knock-in/knockout” approach (17) was used to create PIK3CD knock

out cells in B-cell lymphoma cell line, JeKo-1. The knock in – knock out approach enabled us to

viably mark the PIK3CD KO cells by expressing the GFP instead of PI3Kδ from its DNA locus

and consequently use the cells for further studies. A cDNA encoding GFP, ending with a stop

codon and polyA signal sequence, was inserted at the translation start site of the PIK3CD gene.

Cells were co-transfected with the pX330 plasmid expressing Cas9 and a PIK3CD guide RNA

sequence, along with a plasmid containing flanking homology arms and the knock-in sequence.

The general approach was to knock in (KI) the GFP-STOP-polyA cassette right after translation

initiation site of the PIK3CD leading to PIK3CD promoter driven expression of GFP instead of

PIK3CD. The px330 plasmid (Addgene plasmid #42230) coding for Cas9 and gRNA targeting

PIK3CD (target site sequence: 5’-CATCTGGGAAGTAACAACGCAGG-3’) was cloned

according to the published protocol (17). The pSC-B-amp/kan plasmid (Agilent Technologies)

was used to carry the KI template sequence that consisted of (from 5’ to 3’): left homology arm




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(400 bp of PIK3CD DNA sequence upstream of translation initiation site), kozak sequence

(GCCACC), GFP with STOP codon, bGH PolyA signal sequence, and right homology arm (300

bp of PI3Kδ sequence downstream of translation initiation site). The PIK3CD KO GFP positive

cells were stained and sorted by FACS on day 6 (Supplemental Figure 3). After sorting, the

cells were placed in DMEM media supplemented with 20 % FBS +1 U Penicillin Streptomycin

solution. As a control for KI specificity, px330 plasmids with non-specific target site were

electroporated together with template plasmid. No GFP positive cells were detected in the

specificity control.

Statistical analysis

Student’s t-tests (paired or unpaired, one-tailed) and ANOVA were performed using Prism 6

software (GraphPad Software, San Diego, CA) with p>0.05 as level of significance. For Figures

1 and 2, data were from 45 CLL subjects. Because they were from different patients, a range

was observed between two variables for each parameter such as Rai stage, ZAP 70 status etc

(Figure 1B-G and 2 A-F). To rigorously analyze these data, we compared each patient data (to

incorporate broad range) rather than medians or averages. We also verified the statistical analysis

using Microsoft Excel software and two sample t-test assuming unequal variances or paired two

sample t-test for means where required. Although absolute p values were slightly different in

Prism versus Excel analyses, significant or non-significant likelihood did not change between

two analyses.




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Results

CLL B cell metabolic flux is comparatively lower than that of proliferating B-cell lines and

is associated with patient prognostic factors

Most cancer cells have high metabolic requirements owing to a high proliferation index. Due to

the indolent nature of CLL lymphocytes and non–adherent culture conditions, not many studies

have been conducted to decipher the bioenergetic profile of CLL B cells. We performed a

comprehensive study, encompassing the metabolic phenotype of CLL cells, its association with

prognostic features, and role of BCR pathway. Glycolysis (measured as ECAR) and oxidative

phosphorylation (OxPhos;measured as OCR) profiles were analyzed in normal peripheral blood

mononuclear cells (PBMC, n=10), normal B-lymphocytes (n=11) and malignant CLL B-

lymphocytes (N=45) as well as malignant B cell lines (three cell lines). In each case, for

appropriate comparison, the number of cells was kept constant and for each data point, five

technical replicate values were obtained. We used normal PBMC and normal B-lymphocytes to

compare them with malignant B-lymphocytes (i.e. CLL cells) as all of these cell types are

replicationally quiescent. We used cell lines to compare replicationally quiescent CLL B-

lymphocytes with proliferating mantle cell lymphoma cell lines. OCR and ECAR were lower in

malignant CLL lymphocytes (n=45), normal B lymphocytes (n=11) and PBMC (n=10) compared

to that in all three B-lymphoma cell lines. The latter were highly metabolic both aerobically and

anaerobically (Figure 1A) and had two to thirty-fold greater values for ECAR and OCR than

that in the quiescent normal or neoplastic lymphocytes.

Among the patients’ malignant lymphocyte samples, there was very little glycolytic disparity,

whereas the mitochondrial respiration varied. This was not due to heterogeneity of the cell

population as all samples have ≥ 95% CLL cells. The ECAR values ranged from 1 to 15




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mpH/min for 5 x 105 (median 5.5; n =45) CLL cells. In contrast, for same number of CLL

lymphocytes, the median for OCR was 19 pMoles/min (range 5 – 190, n = 45; Figure 1A). To

understand the basis for this diversity in oxygen consumption rate, we compared basal OCR with

prognostic markers of the disease. Unpaired student’s t-test was used for statistical analyses and

p values are listed on the graph. Rai and Binet are staging systems used for standard

classification and prognosis in CLL (6,18). Compared to lower Rai stage (n=34), increased

mitochondrial respiration (OCR) was observed at higher Rai stage (n=20) (Figure 1B). In

contrast to low β2M (n=38) the presence of high levels of β2M(>3.5μg/mL; n=15), another poor

prognostic feature (19,20), also showed increased OCR (Figure 1C). Both, ZAP 70-positive

(n=29) and IGHV unmutated samples (n=27) had higher OCR compared to their counterparts

(Figure 1D-E). In contrast to these prognostic characteristics, LDH, gender, age, and CD38

expression did not significantly associate with OCR (Figure 1F-G, Supplemental Figure 4A-

B). Though cytogenetic lesions such as loss of ATM (11q deletion) and p53 (17p deletion) are

associated with adverse prognosis, the OCR values were not significantly different among

diverse cytogenetic cohorts (Figure 1H).

While OCR accounts for mitochondrial metabolism through OxPhos pathway, the extracellular

acidification rate (ECAR) represents glycolysis. Unpaired student’s t-test was used for statistical

analyses and p values are listed on the graph. In comparison to OCR, prognostic factors such as

ZAP 70 and IGHV status, increased β2M and higher Rai stage did not correlate with ECAR

(Figure 2A-D). Level of LDH, also did not affect ECAR (Figure 2E). On the other hand, the

ECAR readings indicated a higher rate in male patients (n=14) compared to female cohorts

(n=12) which needs to be further explored (Figure 2F). In conclusion, CLL lymphocyte

metabolomics précis suggested diversity in oxygen consumption rate which was higher in




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samples from patients with greater Rai stage, increased β2M, unmutated IGHV, and higher level

of ZAP 70.

Genetic deletion of BCR receptor affects mitochondrial respiration in JeKo-1, a mantle cell

lymphoma cell line

CLL subgroups defined by β2M over-expression, ZAP 70 positivity, and unmutated IGHV locus

have been associated with increased B-cell receptor signaling (21) denoting that BCR pathway

manipulation may affect metabolomics. We generated a knockout (KO) of BCR in malignant B

cell line, JeKo-1, to determine if abrogating B cell signaling impacts OxPhos and ECAR.

CRISPR- Cas9 technique was used to generate three clones (MC4, MC5, MC6) of BCR KO by

targeting CH2 region of the gene encoding the heavy chain of the IgM. All three clones

demonstrated significantly reduced OCR levels when compared to WT cells both for basal OCR;

15% decrease (Figure 3A), and spare respiratory capacity; ~50% decline (Figure 3B),

demonstrating that BCR signaling plays an important role in regulating B-cell metabolism. The

BCR KO cell lines were further validated for their lack of ability to respond to IgM stimulation.

BCR WT cells displayed an increase in p-AKT Thr308 and p-MAPK Thr 202/Tyr 204, whereas

in the KO clones, these residues were minimally phosphorylated, compared to WT cells (Figure

3C) confirming abrogation of BCR pathway. The decrease in OCR was not due to change in

growth, as both WT and BCR KO cells had similar population doubling time (Figure 3D).

Similar to OCR, ECAR was also reduced in BCR KO clones (not shown).

PI3K p110δ knockout in mantle cell lymphoma cell line (JeKo-1) affects glycolysis and

OxPhos




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A pivotal node in BCR pathway is PI3K δ. Hence, we further tested if genetic ablation (KO) of

PIK3CD (coding for p110δ) would also impact OxPhos in malignant B cells (JeKo-1). JeKo-1

PIK3CD KO cells were analyzed for glycolysis and OxPhos, along with unmodified cells (WT)

from a parallel culture. The PIK3CD KO cells displayed 20% reduction in both glycolytic flux

(Figure 4A-B) and in glycolytic capacity (Figure 4A and C) as compared to the WT cells. A

more profound decrease in respiration levels, i.e. 25% decline in basal OCR (Figure 4D) and

40% reduction in spare respiratory capacity (Figure 4F) as compared to the PI3Kδ WT cells was

observed. Real time RT-PCR assays in these cells confirmed for reduced transcript levels of

PI3KCD (not shown). Similar to BCR KO cells, compared to PI3K wild type cells, the PIK3CD

KO cells did not differ in proliferation ability (Figure 4G) or cell size (not shown).

Pharmacological inhibition of the PI3K/AKT pathway diminishes CLL mitochondrial

OxPhos and intracellular NTP pools

Since, PI3Kδ knock out isoform demonstrated lowered OxPhos and glycolysis in malignant B

cells, we evaluated if a similar result is obtained in CLL lymphocytes by employing PI3K

isoform-specific pharmacological inhibitors. Unpaired student’s t-test was used for statistical

analyses and p values are listed on the graph (Figure 5). The PI3Kδ/γ inhibitor, duvelisib (IPI-

145), is currently in Phase III clinical trials for CLL (Duo trial, NCT02004522; NCT02049515;

www.clinicaltrials.gov). We tested ability of duvelisib to alter the OxPhos pathway in CLL

cells. Duvelisib treatment of CLL cells mitigated both glycolysis and aerobic respiration (Figure

5A-D). Both glycolytic flux and capacity were mitigated in 4 of 5 samples tested (Figure 5A-

B). Although, there was heterogeneity in reduction of basal OCR (7/9), maximum respiratory

capacity was significantly reduced upon duvelisib treatment in all samples tested (Figure 5C-D).




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Again the most profound effect was on maximum respiratory capacity. Similar to basal OCR

and maximum respiratory capacity, spare respiratory capacity was also reduced after treatment

with duvelisib (Supplemental Figure 5). Decline in ECAR and OCR was not due to duvelisib-

induced modest cell death (data not shown) as equal number of untreated and duvelisib-treated

CLL cells were plated for the assay. Because glycolysis is hampered by inhibition of AKT,

whose role in glucose uptake and utilization is well established, we hypothesized that duvelisib

treatment would inhibit glucose uptake. Surprisingly, an assessment of the uptake of [3H] 2-

deoxy-D-glucose demonstrated that glucose uptake was not significantly impacted by duvelisib

treatment (Supplemental Figure 6A). Furthermore, glutamine uptake (Supplemental Figure

6A), as well as mitochondrial ROS, mitochondrial membrane potential, mitochondrial mass

(Supplemental Figure 6B) and mitochondrial DNA copy number (Supplemental Figure 6C)

were not affected. No significant changes in the protein levels or the enzyme activity of

respiratory chain complexes (I-V) were observed after duvelisib treatment (Supplemental

Figure 6D-E). However, PI3Kδ/ɣ inhibition resulted in 25% to 50% decreases in intracellular

ribonucleotide triphosphate pools measured in 7 patient samples (Figure 5E). Because duvelisib

inhibits both PI3Kδ and ɣ, we tested if a PI3K δ isoform inhibition or downstream AKT is

responsible for the decrease in overall energy metabolism. We, therefore, examined the effects

of a PI3Kδ inhibitor, idelalisib, and an AKT inhibitor, MK-2206. Each of these two inhibitors

were used as single agent. Idelalisib mitigated glycolysis in all samples (5/5) tested (Figure 5F-

G) and lowered basal OCR in 5 of 6 samples and maximum respiration in all samples (Figure

5H-I); similarly MK2206 alone curbed glycolysis (5/6) (Supplementary Figure 7A-B) and

OCR (basal OCR was reduced in 4/6 samples and maximum respiration capacity in 5/6 samples)




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(Supplementary Figure 7C-D), suggesting that inhibition of the AKT pathway at least in part

underlies the mitigation of glycolysis and OxPhos pathways.




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Discussion

Most cancer cells have high metabolic requirements owing to a high proliferation index. Due to

the indolent nature of CLL lymphocytes and non–adherent culture conditions, not many studies

have been conducted to decipher the bioenergetic profile of CLL B-cells. Transcriptome

characterization has found that genes involved in metabolic pathways were upregulated in CLL

cells compared with normal lymphocytes (22). Marked metabolic activity in non-cycling

(quiescent) CLL cells was recently demonstrated (23). Additionally, free oxygen radicals in

cells are heterogeneous among patients with CLL but significantly higher in CLL cells from

patients with prior chemotherapy (24). CLL bioenergetic rewiring is also associated with kinase

sensitivity; for example, CLL was classified into subsets based on the dasatinib-induced

differential dependency on mitochondrial respiration to cope with cellular stress and meet the

ATP demands (25).

Prevalence of oxidative stress resulting in increased ROS production in CLL cells (24) and

targeting this by natural compounds (26) has been reported before. These observations were

further confirmed recently by Jitschin et al., 2014 (27). They further identified that altered

mitochondrial metabolism in CLL contributes to oxidative stress. Focusing on normal versus

malignant B-cell biology, they compared ATP levels (n = 5), as well as ECAR and OCR values

(n = 4) in healthy subjects and CLL patients. Their data suggested that increased oxidative

phosphorylation rather than aerobic glycolysis was coupled to bioenergy synthesis in CLL cells.

Our current investigation evaluated the metabolic characteristic to comprehensively determine

ECAR and OCR profiling of freshly isolated malignant lymphocytes from peripheral blood of 45

CLL patients. We further focused to identify if prognostic factors and cytogenetics are associated




19

with this broad range of OCR values. We extended the work to establish the role of BCR

pathway in CLL mitochondrial metabolism. The bioenergetics phenogram showed a relatively

low metabolic profile for CLL cells compared with proliferating B-lymphoma cells (Figure 1A).

Moreover, the oxidative profile measured as OCR was significantly higher. For OCR, our data

demonstrate a range of 5 to 200 pmoles/min/5 x 105 cells. This range is similar to what was

reported in 4 CLL subjects (27). However, in normal B cells, both OCR and ECAR values were

lower in their investigations compared to what was observed in the present study. This could be

due to highly stressed B-cells as reflected in the abnormally low endogenous ATP pool which is

less than 10% of the malignant CLL cells.

Higher number of CLL samples allowed us to compare OCR and ECAR values based on

prognostic factors. Rai and Binet are staging systems used for standard classification and

prognosis in CLL (6,18). In our study, increased mitochondrial respiration (OCR) was observed

at higher Rai stage (Figure 1B). Higher metabolic state was also reported with increased Binet

stage using an NMR-based metabolic monitoring assay (23). The presence of high levels of β2M,

another poor prognostic feature (19,20), also showed a trend for increased OCR (Figure 1C). In

contrast, the cytogenetic abnormalities did not impact OCR values (Figure 1H). While, we do

not know why cytogenetic lesions did not associate with increased OCR, we can provide some

explanations. For example, the gene p53 or ATM may be fully functional in the second allele.

Also, in vivo in human body, these features are associated with aggressive/more proliferative

tumor. During in vitro culture of blood CLL cells, this characteristic is lost; as more than 98% of

the cells are in G0/G1 phase and do not replicate. Among patients with CLL, there are 2 major

cohorts, one with an indolent course that does not require treatment and with patients surviving

for more than 2 decades and another with aggressive disease that requires immediate therapeutic




20

intervention. Several prognostic factors and risk stratification have been proposed for

therapeutic intervention (19). While genetic lesions such as loss of ATM (11q deletion) and p53

(17p deletion) are associated with adverse prognosis, these anomalies are not common in

previously untreated patient populations (28). Recent genome analyses have revealed limited

additional markers of poor prognosis that were identified in whole exome and genome

sequencing (22,28,29).

Among the molecular markers that consistently surface in risk stratification analyses is the

mutational status of immunoglobulin heavy chain (IGHV) (19). Earlier studies established that

unmutated IGHV was associated with more aggressive disease (5), high CD38 expression (30)

and correlated with ZAP 70 expression (3,31). Patients with unmutated IGHV genes had far

inferior median survival than patients with mutated IGHV genes (32). Gene expression profiling

investigations identified a multitude of genes differentially expressed in these 2 subsets of CLL

(33). Both, ZAP 70-positive and IGHV unmutated samples had higher OCR compared to their

normal counterparts (Figure 1D-E). IGHV unmutated samples showed significantly higher OCR,

which may reflect on the aggressiveness of this subtype of CLL. Serum metabolome analyses

from patients with CLL also suggested differences between these 2 molecular subgroups (34).

ZAP 70 is typically present in normal T-cells and is involved with T-cell signaling (35).

However, its presence in malignant B cells as well as its prognostic importance has been

established for CLL (3). ZAP 70 expression in CLL cells is associated with the BCR signaling

pathway (21) and IGHV unmutated status (33). IGHV unmutated status responded differently to

during B-cell activation with a higher preponderance and increase in nucleotide metabolism

genes. These markers (ZAP 70 positivity and IGHV unmutated status) correlate with

progression-free survival (36). Akin to their role in aggressiveness of the disease, CLL cells




21

from these patients had relatively higher OCR. Because we studied these cells in culture and they

were obtained from peripheral blood, this difference was not due to proliferation index, as all

cells were quiescent. In summary, OCR values showed wide variability in CLL subjects and

this heterogeneous range correlated with prognostic markers such as Rai stage, 2M expression

level, and status of IGHV mutation and ZAP 70.

Presence of ZAP 70 and unmutated IGHV are known to enhance cell signaling through BCR

pathway that is pivotal to the maintenance of B cells (33). Abrogating BCR pathway (via BCR

knockout) impacted OxPhos demonstrating that BCR signaling plays an important role in

regulating CLL cell metabolism (Figure 3A-B). Two major players in the BCR pathway are

PI3K and BTK. Increased active BTK (phosphorylated BTK) has been reported for unmutated

IGHV harboring CLL cohort (37). The PI3K axis is constitutively active in CLL cells that are

influenced by the microenvironment. Inhibiting PI3K signaling by PIK3CD KO mitigated both

glycolysis and OxPhos of malignant B cells (Figure 4A-F). KO of both BCR and PI3K pathway

without much effect on cell growth (Figure 3 and 4) in JeKo cells may be due to presence of

cMyc in this cell line. Furthermore, additional cell lines such as LY19 and Mino did not

proliferate after genetic KO of PIK3CD and such manipulations would be challenging in CLL

lymphocytes. While we are extending data from mantle cell lymphoma cell lines to CLL cells,

we understand that the biology would be different in these two B-cell malignancies. We are

extrapolating mantle cell lymphoma cell line data to CLL given the similarity between the two

for dependence on the BCR signaling. To further evaluate our results, we used three

pharmacological inhibitors in CLL cells. Pharmacological inhibition of PI3Kδ by idelalisib has

shown efficacy in the clinic for patients with B-cell malignancies (38,39). Duvelisib binds to the

ATP-binding site of the kinases, thereby preventing activation of the PI3Kδ/γ isoforms (40).




22

This antagonist mitigated glycolysis as well as mitochondrial OxPhos (Figure 5A-D). PI3Kδ

signals to downstream AKT, which plays a major role in glycolysis by directly regulating

glucose uptake (41), which is in line with duvelisib-mediated diminished ECAR in CLL cells.

However, glucose uptake in CLL malignant lymphocytes was not significantly affected by the

drug (Supplemental Figure 5A). It can be speculated that glucose utilization by CLL cells is

being affected because uptake of glucose did not decrease, and yet glycolysis and OxPhos were

significantly down-regulated.

Decline in the intracellular ATP pool is consistent with mitigation of OxPhos by the drug

(42,43). Decrease in other NTP pools suggest that overall energy metabolism is affected by

inhibiting PI3K pathway (Figure 5E). While we have not evaluated mechanisms for changes in

other intracellular NTP levels, CTP and UTP pools may be affected as pyrimidine nucleotide

biosynthesis is linked to mitochondrial electron transport chain by the enzyme dihydroorotate

dehydrogenase (DHODH) that resides in the inner mitochondrial membrane, the only enzyme in

that pathway that is located in the mitochondria. AKT, downstream effector of PI3K, also

regulates purine nucleotide biosynthesis. It reduces ubiquinone to ubiquitol and converts

dihydroorotate to orotate (44). Additionally, AKT activity promotes mTOR pathway signaling, a

known regulator of pyrimidine and purine synthesis (45).

Not much is known about PI3K/AKT pathway and its role in mitochondrial respiratory function

in CLL cells; however, hyper-activation of AKT leading to increased mitochondrial respiration

and thereby ATP synthesis by the 4E-BP1–mediated protein translation pathway has been

reported (46). Inhibition of this mitochondrial respiration by the above-mentioned target-specific

drugs further supports the notion that mitochondrial respiration is regulated by AKT.

Collectively, our PI3K inhibition data in malignant CLL lymphocytes and its role in




23

metabolomics are in concert with prior reports with healthy mature B-lymphocytes. Survival of

B-lymphocytes was mitigated by BCR knock out but rescued exclusively by PI3K signaling (47).

Suppression of this pathway was pivotal for anergy (48) and anergic or activated B-cells required

a change in metabolic status (49).

The fact that CLL with poor prognostic factors such as IGHV unmutated status, presence of

ZAP70, and higher Rai stage etc. were associated with increased OCR suggest that for this

subgroup, inhibition of oxidative phosphorylation should be tested as a strategy. Inhibitors of

OxPhos have been designed and tested in preclinical setting (50) and one is already in clinic

(NCT02882321; ClinicalTrials.Gov).

In conclusion, the key features of our current investigation are as follows. First, metabolic

phenograms of quiescent CLL cells suggest an active OxPhos pathway, and this was strongly

correlated with the aggressiveness of the disease and adverse prognostic factors such as ZAP 70

positivity, IGHV mutation status, Rai stage and β2M levels. Finally, OxPhos, glycolysis and

nucleotide biosynthesis were abrogated by PI3K/AKT pathway inhibition.




24

Acknowledgments

This work was supported in part by grant CLL PO1 CA81534 and by a Cancer Center Support

Grant, CA16672, from the National Cancer Institute, Department of Health and Human Services;

a CLL Global Research Foundation Alliance grant; and Sponsored Research Agreements from

Infinity Pharmaceuticals and Gilead Sciences. We thank Mr. Michael Worley, for critically

editing the manuscript and Mark Nelson for coordinating the CLL sample distribution.

Authorship

H.V.V. designed the research, performed experiments, analyzed results, and wrote the

manuscript. O. H. supervised laboratory technique to create CRISPSR Cas9 –PIK3CD cell

lines. M.L.A. analyzed samples for nucleotide pools. K.B. supervised some aspect of H.V.V.’s

work. M.J.K. and W.G.W. identified patients to obtain peripheral blood samples, provided

clinical and patient-related input, and reviewed the manuscript. B.A.K. directed research related

to mitochondrial copy number. R.E.D. provided overall direction for CRISPSR Cas9 –gene

edition. C.M.S. directed H.V.V. in starting this project and aided her with various techniques,

and reviewed the manuscript. V.G. conceptualized and supervised the research, obtained

funding, analyzed data, and wrote and reviewed the manuscript.




25

References

1. Chiorazzi N, Rai KR, Ferrarini M. Chronic lymphocytic leukemia. The New England

journal of medicine 2005;352(8):804-15 doi 10.1056/NEJMra041720.

2. Balakrishnan K, Burger JA, Fu M, Doifode T, Wierda WG, Gandhi V. Regulation of

Mcl-1 expression in context to bone marrow stromal microenvironment in chronic

lymphocytic leukemia. Neoplasia 2014;16(12):1036-46 doi 10.1016/j.neo.2014.10.002.

3. Rassenti LZ, Huynh L, Toy TL, Chen L, Keating MJ, Gribben JG, et al. ZAP-70

compared with immunoglobulin heavy-chain gene mutation status as a predictor of

disease progression in chronic lymphocytic leukemia. The New England journal of

medicine 2004;351(9):893-901 doi 10.1056/NEJMoa040857.

4. Orchard JA, Ibbotson RE, Davis Z, Wiestner A, Rosenwald A, Thomas PW, et al. ZAP-

70 expression and prognosis in chronic lymphocytic leukaemia. Lancet

2004;363(9403):105-11 doi 10.1016/S0140-6736(03)15260-9.

5. Hamblin TJ, Davis Z, Gardiner A, Oscier DG, Stevenson FK. Unmutated Ig V(H) genes

are associated with a more aggressive form of chronic lymphocytic leukemia. Blood

1999;94(6):1848-54.

6. Rai KR, Sawitsky A, Cronkite EP, Chanana AD, Levy RN, Pasternack BS. Clinical

staging of chronic lymphocytic leukemia. Blood 1975;46(2):219-34.

7. Wierda WG, O'Brien S, Wang X, Faderl S, Ferrajoli A, Do KA, et al. Prognostic

nomogram and index for overall survival in previously untreated patients with chronic

lymphocytic leukemia. Blood 2007;109(11):4679-85 doi 10.1182/blood-2005-12-051458.

8. Yang Q, Chen LS, Ha MJ, Do KA, Neelapu SS, Gandhi V. Idelalisib impacts cell growth

through inhibiting translation regulatory mechanisms in mantle cell lymphoma. Clinical

cancer research : an official journal of the American Association for Cancer Research

2016 doi 10.1158/1078-0432.CCR-15-3135.

9. Engelman JA, Luo J, Cantley LC. The evolution of phosphatidylinositol 3-kinases as

regulators of growth and metabolism. Nature reviews Genetics 2006;7(8):606-19 doi

10.1038/nrg1879.

10. Arvisais EW, Romanelli A, Hou X, Davis JS. AKT-independent phosphorylation of

TSC2 and activation of mTOR and ribosomal protein S6 kinase signaling by

prostaglandin F2alpha. The Journal of biological chemistry 2006;281(37):26904-13 doi

10.1074/jbc.M605371200.

11. Hahn-Windgassen A, Nogueira V, Chen CC, Skeen JE, Sonenberg N, Hay N. Akt

activates the mammalian target of rapamycin by regulating cellular ATP level and AMPK

activity. The Journal of biological chemistry 2005;280(37):32081-9 doi

10.1074/jbc.M502876200.

12. Amin HM, McDonnell TJ, Medeiros LJ, Rassidakis GZ, Leventaki V, O'Connor SL, et

al. Characterization of 4 mantle cell lymphoma cell lines. Archives of pathology &

laboratory medicine 2003;127(4):424-31.

13. Balakrishnan K, Peluso M, Fu M, Rosin NY, Burger JA, Wierda WG, et al. The

phosphoinositide-3-kinase (PI3K)-delta and gamma inhibitor, IPI-145 (Duvelisib),

overcomes signals from the PI3K/AKT/S6 pathway and promotes apoptosis in CLL.

Leukemia 2015;29(9):1811-22 doi 10.1038/leu.2015.105.

14. Stellrecht CM, Vangapandu HV, Le XF, Mao W, Shentu S. ATP directed agent, 8-

chloro-adenosine, induces AMP activated protein kinase activity, leading to autophagic




26

cell death in breast cancer cells. Journal of hematology & oncology 2014;7:23 doi

10.1186/1756-8722-7-23.

15. Vu TH, Sciacco M, Tanji K, Nichter C, Bonilla E, Chatkupt S, et al. Clinical

manifestations of mitochondrial DNA depletion. Neurology 1998;50(6):1783-90.

16. Enns GM, Hoppel CL, DeArmond SJ, Schelley S, Bass N, Weisiger K, et al.

Relationship of primary mitochondrial respiratory chain dysfunction to fiber type

abnormalities in skeletal muscle. Clinical genetics 2005;68(4):337-48 doi

10.1111/j.1399-0004.2005.00499.x.

17. Ran FA, Hsu PD, Wright J, Agarwala V, Scott DA, Zhang F. Genome engineering using

the CRISPR-Cas9 system. Nature protocols 2013;8(11):2281-308 doi

10.1038/nprot.2013.143.

18. Binet JL, Auquier A, Dighiero G, Chastang C, Piguet H, Goasguen J, et al. A new

prognostic classification of chronic lymphocytic leukemia derived from a multivariate

survival analysis. Cancer 1981;48(1):198-206.

19. Pflug N, Bahlo J, Shanafelt TD, Eichhorst BF, Bergmann MA, Elter T, et al.

Development of a comprehensive prognostic index for patients with chronic lymphocytic

leukemia. Blood 2014;124(1):49-62 doi 10.1182/blood-2014-02-556399.

20. Hallek M, Wanders L, Ostwald M, Busch R, Senekowitsch R, Stern S, et al. Serum

beta(2)-microglobulin and serum thymidine kinase are independent predictors of

progression-free survival in chronic lymphocytic leukemia and immunocytoma.

Leukemia & lymphoma 1996;22(5-6):439-47 doi 10.3109/10428199609054782.

21. Chen L, Widhopf G, Huynh L, Rassenti L, Rai KR, Weiss A, et al. Expression of ZAP-

70 is associated with increased B-cell receptor signaling in chronic lymphocytic


22. Ferreira PG, Jares P, Rico D, Gomez-Lopez G, Martinez-Trillos A, Villamor N, et al.

Transcriptome characterization by RNA sequencing identifies a major molecular and

clinical subdivision in chronic lymphocytic leukemia. Genome research 2014;24(2):212-

26 doi 10.1101/gr.152132.112.

23. Koczula KM, Ludwig C, Hayden R, Cronin L, Pratt G, Parry H, et al. Metabolic

plasticity in CLL: adaptation to the hypoxic niche. Leukemia 2015:1-9 doi

10.1038/leu.2015.187.

24. Zhou Y, Hileman EO, Plunkett W, Keating MJ, Huang P. Free radical stress in chronic

lymphocytic leukemia cells and its role in cellular sensitivity to ROS-generating

anticancer agents. Blood 2003;101(10):4098-104 doi 10.1182/blood-2002-08-2512.

25. Martinez Marignac VL, Smith S, Toban N, Bazile M, Aloyz R. Resistance to Dasatinib in

primary chronic lymphocytic leukemia lymphocytes involves AMPK-mediated energetic

re-programming. Oncotarget 2013;4(12):2550-66 doi 10.18632/oncotarget.1508.

26. Trachootham D, Zhou Y, Zhang H, Demizu Y, Chen Z, Pelicano H, et al. Selective

killing of oncogenically transformed cells through a ROS-mediated mechanism by beta-

phenylethyl isothiocyanate. Cancer cell 2006;10(3):241-52 doi

10.1016/j.ccr.2006.08.009.

27. Jitschin R, Hofmann AD, Bruns H, Giessl A, Bricks J, Berger J, et al. Mitochondrial

metabolism contributes to oxidative stress and reveals therapeutic targets in chronic

lymphocytic leukemia. Blood 2014;123(17):2663-72 doi 10.1182/blood-2013-10-532200.




27

28. Dohner H, Stilgenbauer S, Benner A, Leupolt E, Krober A, Bullinger L, et al. Genomic

aberrations and survival in chronic lymphocytic leukemia. The New England journal of

medicine 2000;343(26):1910-6 doi 10.1056/NEJM200012283432602.

29. Landau DA, Carter SL, Stojanov P, McKenna A, Stevenson K, Lawrence MS, et al.

Evolution and impact of subclonal mutations in chronic lymphocytic leukemia. Cell

2013;152(4):714-26 doi 10.1016/j.cell.2013.01.019.

30. Damle RN, Wasil T, Fais F, Ghiotto F, Valetto A, Allen SL, et al. Ig V gene mutation

status and CD38 expression as novel prognostic indicators in chronic lymphocytic

leukemia. Blood 1999;94(6):1840-7.

31. Wiestner A, Rosenwald A, Barry TS, Wright G, Davis RE, Henrickson SE, et al. ZAP-70

expression identifies a chronic lymphocytic leukemia subtype with unmutated

immunoglobulin genes, inferior clinical outcome, and distinct gene expression profile.

Blood 2003;101(12):4944-51 doi 10.1182/blood-2002-10-3306.

32. Oscier DG, Gardiner AC, Mould SJ, Glide S, Davis ZA, Ibbotson RE, et al. Multivariate

analysis of prognostic factors in CLL: clinical stage, IGVH gene mutational status, and

loss or mutation of the p53 gene are independent prognostic factors. Blood

2002;100(4):1177-84.

33. Rosenwald A, Alizadeh AA, Widhopf G, Simon R, Davis RE, Yu X, et al. Relation of

gene expression phenotype to immunoglobulin mutation genotype in B cell chronic

lymphocytic leukemia. The Journal of experimental medicine 2001;194(11):1639-47.

34. MacIntyre DA, Jimenez B, Lewintre EJ, Martin CR, Schafer H, Ballesteros CG, et al.

Serum metabolome analysis by 1H-NMR reveals differences between chronic

lymphocytic leukaemia molecular subgroups. Leukemia 2010;24(4):788-97 doi

10.1038/leu.2009.295.

35. Chan AC, Iwashima M, Turck CW, Weiss A. ZAP-70: a 70 kd protein-tyrosine kinase

that associates with the TCR zeta chain. Cell 1992;71(4):649-62.

36. Del Principe MI, Del Poeta G, Buccisano F, Maurillo L, Venditti A, Zucchetto A, et al.

Clinical significance of ZAP-70 protein expression in B-cell chronic lymphocytic


37. Guo A, Lu P, Galanina N, Nabhan C, Smith SM, Coleman M, et al. Heightened BTK-

dependent cell proliferation in unmutated chronic lymphocytic leukemia confers

increased sensitivity to ibrutinib. Oncotarget 2016;7(4):4598-610 doi

10.18632/oncotarget.6727.

38. Herman SE, Gordon AL, Wagner AJ, Heerema NA, Zhao W, Flynn JM, et al.

Phosphatidylinositol 3-kinase-delta inhibitor CAL-101 shows promising preclinical

activity in chronic lymphocytic leukemia by antagonizing intrinsic and extrinsic cellular

survival signals. Blood 2010;116(12):2078-88 doi 10.1182/blood-2010-02-271171.

39. Furman RR, Sharman JP, Coutre SE, Cheson BD, Pagel JM, Hillmen P, et al. Idelalisib

and rituximab in relapsed chronic lymphocytic leukemia. The New England journal of

medicine 2014;370(11):997-1007 doi 10.1056/NEJMoa1315226.

40. Winkler DG, Faia KL, DiNitto JP, Ali JA, White KF, Brophy EE, et al. PI3K-delta and

PI3K-gamma inhibition by IPI-145 abrogates immune responses and suppresses activity

in autoimmune and inflammatory disease models. Chemistry & biology

2013;20(11):1364-74 doi 10.1016/j.chembiol.2013.09.017.




28

41. Elstrom RL, Bauer DE, Buzzai M, Karnauskas R, Harris MH, Plas DR, et al. Akt

stimulates aerobic glycolysis in cancer cells. Cancer research 2004;64(11):3892-9 doi

10.1158/0008-5472.CAN-03-2904.

42. Henderson JF, Fraser JH, McCoy EE. Methods for the study of purine metabolism in

human cells in vitro. Clinical biochemistry 1974;7(4):339-58.

43. Carlucci F, Rosi F, Di Pietro C, Marinello E, Pizzichini M, Tabucchi A. Purine

nucleotide metabolism: specific aspects in chronic lymphocytic leukemia lymphocytes.

Biochimica et biophysica acta 1997;1360(3):203-10.

44. Jones ME. Pyrimidine nucleotide biosynthesis in animals: genes, enzymes, and regulation

of UMP biosynthesis. Annual review of biochemistry 1980;49:253-79 doi

10.1146/annurev.bi.49.070180.001345.

45. Ben-Sahra I, Hoxhaj G, Ricoult SJ, Asara JM, Manning BD. mTORC1 induces purine

synthesis through control of the mitochondrial tetrahydrofolate cycle. Science

2016;351(6274):728-33 doi 10.1126/science.aad0489.

46. Goo CK, Lim HY, Ho QS, Too HP, Clement MV, Wong KP. PTEN/Akt signaling

controls mitochondrial respiratory capacity through 4E-BP1. PloS one 2012;7(9):e45806

doi 10.1371/journal.pone.0045806.

47. Srinivasan L, Sasaki Y, Calado DP, Zhang B, Paik JH, DePinho RA, et al. PI3 kinase

signals BCR-dependent mature B cell survival. Cell 2009;139(3):573-86 doi

10.1016/j.cell.2009.08.041.

48. Browne CD, Del Nagro CJ, Cato MH, Dengler HS, Rickert RC. Suppression of

phosphatidylinositol 3,4,5-trisphosphate production is a key determinant of B cell anergy.

Immunity 2009;31(5):749-60 doi 10.1016/j.immuni.2009.08.026.

49. Caro-Maldonado A, Wang R, Nichols AG, Kuraoka M, Milasta S, Sun LD, et al.

Metabolic reprogramming is required for antibody production that is suppressed in

anergic but exaggerated in chronically BAFF-exposed B cells. Journal of immunology

2014;192(8):3626-36 doi 10.4049/jimmunol.1302062.

50. Protopopova M, Bandi M, Bardenhagen J, Bristow C, Carroll C, Chang E, et al. IACS-

10759: A novel OXPHOS inhibitor which selectively kill tumors with metabolic

vulnerabilities. Cancer research 2015;75 doi 10.1158/1538-7445.AM2015-4380.




29

Figure Legends

Figure 1. CLL bioenergetics profile and relationship of CLL OCR with disease prognostic

markers.

Bioenergetics was measured for 5 × 105 freshly-isolated CLL cells after 24hr culture. Five

technical replicates were used for Extracellular Acidification Rate (ECAR) and Oxygen

Consumption Rate (OCR) assays. A, Bioenergetic profile of CLL cells from 45 patients (red

circles) compared with peripheral blood mononuclear cells (PBMCs, n = 10, blue triangles), B

cells from healthy donors (n = 11, inverted green triangles), and B-lymphoma cell lines (JeKo-1

(maroon), Mino (purple) and Sp53 (orange), squares). B, OCR correlation with patient Rai stage.

Basal OCR of CLL cells was compared with disease Rai stage: low grade (stages 0,1, n = 34),

high grade (stages 2-4, n = 20). C, OCR correlation with patient β2 microglobulin (β2M) levels.

Basal OCR from CLL cells was compared according to β2M cut off levels determined by CLL

International Prognostic Index ≤3.5 μg/mL (n=38), >3.5 μg/mL (n=15). D, OCR correlation

with ZAP 70 status. Basal OCR of CLL cells obtained from ZAP 70-negative (neg; n=20) and

positive (pos; n=29) patients was compared. E, OCR correlation with IGHV mutational status.

Basal OCR of CLL cells was compared based on the mutational status of IGHV: mutated (M;

n=19) or unmutated (U; n=27). F, OCR correlation with patient lactate dehydrogenase (LDH)

levels. Basal OCR from CLL cells was compared for patients with different LDH levels: low (L;

300-500 μg/mL, n = 8), medium (M; 501-700 μg/mL, n = 26), high (H; >700 μg/mL, n = 17). G,

OCR correlation with patient gender. Basal OCR of CLL cells was compared based on the

gender of the patient, male (n=27) or female (n=27). Statistical significance was calculated

using unpaired student’s t-test for B-G. H, Basal OCR of CLL cells were compared for patients

with various chromosomal abnormalities by extracellular flux analysis: 11q deletion (n = 8), 13q




30

deletion (n = 9), trisomy 12 (+12) (n = 8), 17p deletion (n = 5). C.K. (n = 7) indicates complex

karyotype with 2 or more of these deletions, O (n = 16) indicates other chromosomal

abnormalities and U (n = 21) indicates unknown karyotype. Statistical significance was

calculated using ANOVA p=0.4.

Figure 2. CLL ECAR correlation with disease prognostic factors.

Glycolytic flux of CLL cells (5 × 105) were compared based on different prognostic factors. A,

ECAR correlation with ZAP 70 status. Glycolytic flux of CLL cells obtained from ZAP 70-

negative (n=9) and positive (n=19) patients was compared. B, ECAR correlation with IGHV

status. Glycolytic flux of CLL cells obtained from IGHV mutated (n=11) and unmutated (n=18)

patients was compared. C, ECAR correlation with patient Rai stage; Glycolytic flux of CLL

cells were compared based on Rai stage: low grade (0, 1, n=25), high grade (2-4, n=11). D,

ECAR correlation with patient β2M levels. Glycolytic flux from CLL cells was compared

according to β2M cut off levels ≤3.5μg/mL (n=18), >3.5 μg/mL (n=7). E, ECAR correlation

with LDH levels. Glycolytic flux from CLL cells was compared for patients with different LDH

levels: low (L) (300-500 μg/mL, n = 5), medium (M) (501-700 μg/mL, n = 11), high (H) (>700

μg/mL, n = 9). F, ECAR correlation with patient gender. Glycolytic flux from CLL cells was

compared for male (n=14), female (n=12) patients. Statistical significance was calculated using

unpaired student’s t-test for A-D and F; one way ANOVA used for E.

Figure 3. Impact of BCR knockout in mantle cell lymphoma on OxPhos and signaling.

A, B, Mitochondrial OxPhos in wild-type (WT) and BCR KO JeKo-1 cells. WT and BCR KO

clones (MC4, MC5, MC6) were analyzed for A, basal OCR and B, spare respiratory capacity

(n=6 technical replicates, n=3 biological replicates; total 18 data points). One-way ANOVA

without pairing, non-parametric, Kruskal-Wallis test was used to compare these data points in

p=0.035

p=0.15

p=0.007




31

WT with that of KO cells. C, Immunoblot analysis of whole-cell extracts of JeKo-1 WT and

BCR KO ± IgM stimulation. WT and BCR KO clones were serum starved (RPMI 1640 media

supplemented with 0.5% serum) for 2 hr followed by addition of 10 μM IgM for 20 min. Lysates

were analyzed by two immunoblot analyses. The p-AKT Thr308 and total AKT were probed

using antibodies from two different species. The p-MAPK p(44/42) Thr202/Tyr204 and total

MAPK were probed using antibodies from two different species followed by GAPDH

immunogenicity. D, WT and BCR KO JeKo-1 clones (MC4, MC5, MC6) were plated at a

concentration of (2×105)/mL in RPMI 1640 media supplemented with 10% FBS and 1%

Penicillin streptomycin solution on day 1 and the cell numbers were measured on days 2, 3, 4

and 5.

Figure 4. Impact of PIK3CD knockout in mantle cell lymphoma on glycolysis and OxPhos.

A, Graphical representation of glycolysis stress profile of Wild-type (WT) and PIK3CD KO

JeKo-1 cells. WT (blue curve) and PIK3CD KO (red curve) cells were analyzed for B, glycolytic

flux and C, glycolytic capacity. D, Mitochondrial OxPhos in wild- type and PIK3CD KO JeKo-

1 cells. Graphical representation of WT (blue curve) and PIK3CD KO (red curve) JeKo cell

mitochondrial stress profile. Wild –type (WT) and PIK3CD KO cells were analyzed for E, basal

OCR and F, spare respiratory capacity. Student’s paired 2-tailed t-test was used in the statistical

analysis for B, C, E, F. G, WT and PIK3CD KO JeKo-1 clones were plated at a concentration

of (2×105)/mL in RPMI 1640 media supplemented with 10% FBS and 1% Penicillin

streptomycin solution on day 1 and the cell numbers were measured on days 2, 3, 4 and 5.

Figure 5. Effect of PI3K inhibitors on cellular metabolism in primary CLL lymphocytes.

CLL cells were assayed for cell survival 24 hrs after drug treatment and equal numbers of

untreated or duvelisib-treated CLL cells were plated for the assay. Five technical replicates were




32

used for Extracellular Acidification Rate (ECAR) and Oxygen Consumption Rate (OCR) assays.

A, Duvelisib–induced changes in glycolytic flux. CLL cells were treated with 1 µM duvelisib for

24 hr (n=5 patient samples) and assayed for glycolytic flux along with untreated controls. B,

Duvelisib treated patient samples in A were analyzed for glycolytic capacity (n = 5 patient

samples). C-D, Duvelisib induced alterations in mitochondrial respiration. C, Basal OCR and

D, maximum respiration capacity were compared in untreated CLL cells and cells treated for 24

hours with 1 μM duvelisib (n = 9 patient samples). E, Influence of duvelisib on the intracellular

nucleotide pools in CLL lymphocytes. NTP pools were extracted from CLL cells either

untreated or treated for 24 hours with duvelisib (n = 7 patient samples) and analyzed using

HPLC. F-G, Effect of PI3Kδ inhibitor on CLL glycolysis. Cells either untreated or treated for

24 hours with PI3Kδ inhibitor 1 μM idelalisib (n = 5 patient samples) and were compared for

changes in F, glycolytic flux and G, glycolytic capacity. H-I, Effect of PI3Kδ inhibition on CLL

OxPhos. CLL cells either untreated or treated for 24 hours with PI3Kδ inhibitor, 1 μM idelalisib,

(n = 6 patient samples) were compared for changes in H, basal OCR (and I, maximum

respiratory capacity. Ctrl, control untreated; IPI, IPI-145 (duvelisib); GS, GS-1101 (idelalisib).



















Published OnlineFirst August 23, 2017.Mol Cancer Res Hima Vangapandu, Ondrej Havranek, Mary Ayres, et al. Lymphocytic Leukemia.B cell receptor signaling regulates metabolism in Chronic

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B cell receptor signaling regulates metabolism in Chronic ... · 1 Left running head: VANGAPANDU et al Re-Revised Version 1 . B Cell Receptor Signaling Regulates Metabolism in Chronic