Oumaima Jaoua
email: oumaima.jaouadi@fst.utm.tn

Inès Lima
email: ines.limam@fmt.utm.tn

Mohamed Abdelkarim
email: mohamed.abdelkarim@fmt.utm.tn

Emna Berred
email: emna.berred@fmt.utm.tn

Ahlem Chahbi
email: ahlem.chahbi@fmt.utm.tn

Mélody Caillot
email: melody.caillot@unicaen.fr

Brigitte Sola
email: brigitte.sola@unicaen.fr

Fatma Ben Aissa-Fennira

5,6-Epoxycholesterol Isomers Induce Oxiapoptophagy in Myeloma Cells

Keywords: apoptosis, autophagy, anti-tumor activity, multiple myeloma, oxiapotophagy, oxidative stress, oxysterols, synergistic interaction

Simple Summary: As the second most frequent hematological malignancy, multiple myeloma remains incurable with recurrent patient relapse due to drug resistance. Therefore, the development of novel and potent therapies is urgently required. Herein, we demonstrated the anti-tumor activity of 5,6 αand 5,6 β-epoxycholesterol isomers against human myeloma cells. Our results highlighted a striking anti-myeloma efficiency of these bioactive molecules and their added value in future potential treatments including combination therapy of multiple myeloma.

Introduction

Multiple myeloma (MM) is a relapsed/refractory malignant hematological disease characterized by a clonal proliferation of tumor plasma cells in the bone marrow and/or extra-medullary sites. It represents the second most common hematological malignancy [START_REF] Rajkumar | Multiple Myeloma Current Treatment Algorithms[END_REF]. Despite the development of novel therapeutic strategies, including proteasome inhibitors, drug resistance occurs with frequent disease relapse and fatal outcome [START_REF] Gonzalez-Santamarta | Resistance to the Proteasome Inhibitors: Lessons from Multiple Myeloma and Mantle Cell Lymphoma[END_REF]. Therefore, there is a crucial need to design more effective anti-myeloma therapies by discovering novel bioactive compounds and combination strategies [START_REF] Ramasamy | Improving Outcomes for Patients with Relapsed Multiple Myeloma: Challenges and Considerations of Current and Emerging Treatment Options[END_REF][START_REF] Moreau | Treatment of Relapsed and Refractory Multiple Myeloma: Recommendations from the International Myeloma Working Group[END_REF].

The metabolism of cholesterol plays a role in tumor development, drug resistance, and drug pharmacology for various cancers including MM [START_REF] De Weille | Oxysterols in Cancer Cell Proliferation and Death[END_REF][START_REF] Choi | Lipid Level, Lipid Variability, and Risk of Multiple Myeloma: A Nationwide Population-Based Study of 3,527,776 Subjects[END_REF]. Among cholesterol metabolites, oxysterols represent a large family of lipids implicated in a plethora of physiological processes [START_REF] De Weille | Oxysterols in Cancer Cell Proliferation and Death[END_REF]. They are produced through enzymatic reactions or by auto-oxidation [START_REF] Poirot | Cholesterol-5,6-Epoxides: Chemistry, Biochemistry, Metabolic Fate and Cancer[END_REF], and can also be provided by food [START_REF] Otaegui-Arrazola | Oxysterols: A World to Explore[END_REF]. Moreover, oxysterols have been shown to interfere with proliferation and cause many types of cell death including oxiapoptophagy in various cancers, such as glioblastoma, colon, breast, prostate cancers and hematologic malignancies [START_REF] De Weille | Oxysterols in Cancer Cell Proliferation and Death[END_REF][START_REF] Nury | Oxiapoptophagy: A Type of Cell Death Induced by Some Oxysterols[END_REF]. Among them, the 5,6-epoxycholesterols [START_REF] De Weille | Oxysterols in Cancer Cell Proliferation and Death[END_REF], isomers α (5,6 α-EC) and β (5,6 β-EC), 27-carbon molecules, are enzymatically generated by cholesterol oxidation at the ∆5 double-bond between C5 and C6 of the B ring of the steroid backbone [START_REF] Mutemberezi | From Cholesterol Metabolites to Key Mediators[END_REF]. The cytotoxic effect of 5,6 β-EC against human U937 promonocytic leukemia cells has been described previously, whereas the corresponding α isomer had no such property [START_REF] Lemaire-Ewing | Comparison of the Cytotoxic, pro-Oxidant and pro-Inflammatory Characteristics of Different Oxysterols[END_REF]. Moreover, both isomers are able to enhance superoxide anions (O 2-) production, suggesting a prooxidative activity. Interestingly, the 5,6-ECs possess both pro-tumor and anti-oncogenic properties the latter through the production of steroidal alkaloids [START_REF] Segala | 5,6-Epoxy-Cholesterols Contribute to the Anticancer Pharmacology of Tamoxifen in Breast Cancer Cells[END_REF]. Tamoxifen, widely used for breast cancer therapy, stimulates the production and accumulation of 5,6-ECs in a reactive oxygen species (ROS)-dependent manner [START_REF] Segala | 5,6-Epoxy-Cholesterols Contribute to the Anticancer Pharmacology of Tamoxifen in Breast Cancer Cells[END_REF]. Moreover, in MM, previous data reported that altering cholesterol metabolism is a means to induce cell death. Indeed, the 4-hydroxy-tamoxifen alters the cholesterol metabolism leading to the accumulation of free sterols, and in turn, MM cell death both in vitro and in vivo [START_REF] Sola | Antiestrogen-Binding Site Ligands Induce Autophagy in Myeloma Cells That Proceeds through Alteration of Cholesterol Metabolism[END_REF]. Importantly, they appear to be non-toxic in normal cells at concentrations that would be cytotoxic in cancer cell lines [START_REF] Travert | Induction of Apoptosis by 25-Hydroxycholesterol in Adult Rat Leydig Cells: Protective Effect of 17β-Estradiol[END_REF][START_REF] Kupferberg | Differential Sensitivity of Astrocyte Primary Cultures and Derived Spontaneous Transformed Cell Lines to 70-Hydroxycholesterol: Effect on Plasma Membrane Lipid Composition and Fluidity, and on Cell Surface Protein Expression[END_REF]. Finally, the 5,6-ECs are unreactive towards neutrophiles, indicating that they are not alkylating agents [START_REF] Paillasse | Surprising Unreactivity of Cholesterol-5,6-Epoxides towards Nucleophiles[END_REF][START_REF] Silvente-Poirot | Cholesterol Epoxide Hydrolase and Cancer[END_REF]. Taken together, these data demonstrated the potential importance of cholesterol metabolism in the pharmacology and/or therapeutic effects of anti-tumor drugs.

The aim of our study was to investigate the ability of 5,6 α-EC and 5,6 β-EC to trigger human myeloma cells death. Herein, we describe for the first time the anti-tumor activity of the two oxysterols against human myeloma cell lines (HMCLs) and primary MM cells purified from patients via oxiapoptophagy. Our data highlight the pharmacological activity of 5,6 α-EC and 5,6 β-EC alone or in combination with existing treatments for developing efficient anti-MM therapies.

Materials and Methods

Drugs

The 5,6 α-EC and 5,6 β-EC isomers were kindly provided by Dr. Gérard Lizard (University of Bourgogne Franche-Comté, Dijon, France).

Cell Lines and Culture

JJN3, U266 HMCLs, and the bone marrow normal stromal HS-5 cell line were obtained from Leibniz Institute DSMZ (Brünswick, Germany). They have been described previously [START_REF] Caillot | ROS Overproduction Sensitises Myeloma Cells to Bortezomib-Induced Apoptosis and Alleviates Tumour Microenvironment-Mediated Cell Resistance[END_REF]. HMCLs were cultured in RPMI 1640 medium supplemented with 10% heat-inactivated fetal bovine serum (FBS, PAN-Biotech, Aidenbach, Germany), 2 mM L-glutamine, and penicillin-streptomycin (PAN-Biotech, Aidenbach, Germany) at 37 • C and 5% CO 2 . HS-5 cells were maintained in complete DMEM medium. Some of HCML characteristics are presented in the Table S1.

Primary Cells Purification from MM Patients

The study was approved by the local ethics committee of our institution (Clinical Research Ethics Committee of La Rabta Hospital, Tunis, Tunisia) and written informed consent was obtained from each patient (Table S2). Bone marrow (BM) samples were freshly aspirated from the sternum of five patients (P1-P5) diagnosed with MM, affiliated to Aziza Othmana Hospital of Tunis. Two to four mL of BM samples were diluted in phosphate-buffered saline (PBS, Sigma-Aldrich, St. Louis, MO, USA), and Ficoll gradient was performed. BM nuclear cells (BMNCs) layer was next carefully collected and washed twice in PBS. For patient P5, BMNCs were analyzed by triple staining with anti-CD38-PE (phycoerythrin, BD Biosciences, San José, CA, USA), -CD138-APC (allophycocyanin, BD Biosciences, Franklin Lakes, NJ, USA) and annexin V-FITC (fluorescein isothiocyanate, Invitrogen, Carlsbad, CA) compounds by flow cytometry with an BD FACSCanto II (BD Biosciences, Franklin Lakes, NJ, USA). For the patients P1-P4, CD138+ malignant plasma Cancers 2021, 13, 3747 3 of 20 cells were isolated from BMNCs and maintained in complete RPMI 1640 medium. The cells were then incubated with CD138-microbeads, passed through LS columns and MiniMACS Separator (Miltenyi Biotec, Bergisch Gladbach, Germany).

MTT Assay

An MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) assay (M5655, Sigma-Aldrich, Saint-Louis, MO, USA) was used to measure the loss of viability of treated cells according to the manufacturer's instructions. HMCLs or HS-5 cells were plated in 96-well culture plates for 24 h at the density of 2 × 10 5 cells/mL/well. Then the MTT test was carried out after a 24 to 72 h period of treatments with 5,6 α-EC or 5,6 β-EC with concentrations ranging from 5 to 80 µg/mL. In each experiment, 0.4% ethanol (EtOH) was used as vehicle control. CD138+ primary human myeloma cells were also plated in 96-well culture plates and incubated with 10-80 µg/mL of 5,6 α-EC or 5,6 β-EC for 24 h. The experiment was performed using three replicates for each culture condition and repeated three times. Cell viability was determined by measuring the absorbance with a microplate reader (EXL800, BioTek, Winooski, VT, USA).

The combinations 5,6 α-EC plus 5,6 β-EC (IC 25 or IC 50 ) and 5,6-ECs with bortezomib (BTZ, CAS 179324-69-7, Calbiochem, San Diego, CA, USA) at the indicated doses were also tested. The IC 50 and IC 25 (index of cytotoxicity) that are the drug concentrations that kill 50% or 25% of the cells, respectively, after a 48 h-treatment, was calculated with the Prism software (v8.0, GraphPad) and verified with the CompuSyn software (http: //www.combosyn.org, accessed on 21 July 2021). This software was also used to calculate the Chou-Talalay combination index (CI).

Assessment of Apoptosis

Cell Cycle Analysis

To determine cell cycle distribution, cells were stained using propidium iodide (PI) and explored by flow cytometry. Following a period of culture of 24 h, JJN3 and U266 cells (2 × 10 5 cells/mL/well) were incubated with 20-80 µg/mL of 5,6 α/β-ECs for 24-72 h. Cells were next fixed in 70% EtOH at -20 • C for 1 h and incubated with 500 µL of FxCycle PI/RNase staining solution (F10797, Molecular Probes, ThermoFisher Scientific, Waltham, MA, USA) for 30 min. At least, 10 4 events were gated for each experiment using a BD FACSCanto II (BD Biosciences, Franklin Lakes, NJ, USA). Data were analyzed using the BD FACSDiva 7 software (BD Biosciences, Franklin Lakes, NJ, USA).

Annexin V-Apoptosis Detection Assay

A double staining with annexin V-FITC/PI was used for evaluating the percentage of apoptotic cells induced by each treatment with the Annexin V/Dead cells apoptosis kit (BMS500-FI-300, Invitrogen, Carlsbad, CA, USA). JJN3 and U266 cells were seeded in 24-well plates at the density of 2 × 10 5 cells/mL, preincubated for 24 h period, then treated with the drugs as described before. CD138+ human myeloma cells were plated in 24-well plates and treated for 24 h with 10-40 µg/mL of 5,6 α-EC or 5,6 β-EC. The cells were then stained with annexin V-FITC/PI according to the manufacturer instructions. At least 10 4 events were analyzed for each sample using the BD FACSCanto II flow cytometer (BD Biosciences, Franklin Lakes, NJ, USA). Data were processed with the BD FACSDiva 7 software (BD Biosciences, Franklin Lakes, NJ, USA). Four cell sub-populations were evaluated: viable cells (AV-/PI-), early apoptotic cells (AV+/PI-), late apoptotic and/or secondary necrotic cells (AV+/PI+), and necrotic/damaged cells (AV-/PI+).

Analysis of Nuclear Morphology by Hoechst 33,342 Staining

The nuclear morphology of control and 5,6 α-EC or 5,6 β-EC-treated cells was analyzed by fluorescence microscopy after staining with 1 µg/mL of Hoechst 33,342 (B2261, Sigma-Aldrich, Saint Louis, MO, USA) [START_REF] Limam | Chetoui Leaf and Stem Hydromethanolic Extracts Suppress Proliferation and Promote Apoptosis via Caspase Signaling on Human Multiple Myeloma Cells[END_REF]. Almost 4 × 10 4 cells were applied to glass slides by 5 min cytocentrifugation with a cytospin Shandon 4 (Thermo Fisher Scientific, Waltham, MA, USA). Slides were mounted with the Dako fluorescent mounting medium (S302380, Dako, Copenhagen, Denmark) and observed under an Olympus BX53 fluorescence microscope (Olympus Corporation, Tokyo, Japan).

Effector Caspase 3/7 Activity

To evaluate the effect of 5,6 α/β-ECs on caspase 3/7 activity, the cleavage of the Ac-DEVD substrate was measured using the CellEvent caspase 3/7 green flow cytometry assay kit (C10740, Molecular Probes, Eugene, OR, USA) [START_REF] Limam | Hydromethanolic Root and Aerial Part Extracts from Echium Arenarium Guss Suppress Proliferation and Induce Apoptosis of Multiple Myeloma Cells through Mitochondrial Pathway[END_REF]. JJN3 and U266 cells were seeded at a density of 2 × 10 5 cells/mL/well in 24-well culture plates for 24 h and treated with 20-80 µg/mL of 5,6 α/β-ECs or with 500 µM H 2 O 2 as positive control for 24-72 h. Next, cells were processed according to the manufacturer instructions. At least 10 4 cells per sample were acquired with BD FACSCanto II and data were analyzed with the BD FACSDiva 7 software (BD Biosciences, Franklin Lakes, NJ, USA).

Measurement of Intracellular ROS and Effect of ROS Production on MM Cell Death

The overproduction of intracellular ROS was measured with dihydroethidium (DHE) staining (D11347, ThermoFisher Scientific, Waltham, MA, USA). JJN3 and U266 cells were seeded at a density of 2 × 10 5 cells/mL/well into 24-well plates and incubated for 24 h before treatments with 20-80 µg/mL of 5,6 α/β-ECs or with 250 or 500 µM H 2 O 2 as positive controls. Cells were further incubated with 2 µM DHE for 15 min at 37 • C. The production of O 2-was monitored by oxidized DHE that exhibits an orange/red fluorescence [START_REF] Lemaire-Ewing | Comparison of the Cytotoxic, pro-Oxidant and pro-Inflammatory Characteristics of Different Oxysterols[END_REF]. The signal was collected from a minimum of 10 4 events for each sample using the BD FACSCanto II flow cytometer (BD Biosciences) and data were processed with the BD FACSDiva 7 software (BD Biosciences).

JJN3 or U266 cells were plated for 24 h in 24-well plates (2 × 10 5 cells/well), treated with 5,6 α-EC or 5,6 β-EC (20-80 µg/mL) alone or after a 2 h-pretreatment with 400 µM vitamin E (Vit E, #258024, Sigma-Aldrich, Saint Louis, MO, USA). After 24 or 48 h of treatment, cells were stained with 1 µg/mL PI (#P4170, Sigma-Aldrich, Saint Louis, MO, USA). At least, 10 4 events per sample were acquired and analyzed by flow cytometry BD FACSCanto II. Data were processed using BD FACSDiva 7 software (BD Biosciences, Franklin Lakes, NJ, USA).

Measurement of Transmembrane Mitochondrial Potential (∆ψ m )

To evaluate ∆Ψ m variations under 5,6 α/β-ECs treatment, the lipophilic fluorescent dye 3,3 -dihexyloxacarbocyanine iodide DiOC 6 -(3) (D273, Invitrogen, Carlsbad, CA, USA) was used [START_REF] Lizard | Kinetics of Plasma Membrane and Mitochondrial Alterations in Cells Undergoing Apoptosis[END_REF]. JJN3 and U266 cells were seeded at the density of 2 × 10 5 cells/mL/well in 24-well plates and incubated for 24 h. Afterward, cells were treated with 20-80 µg/mL of 5,6 α/βECs or with 500 µM H 2 O 2 serving as a positive control for the experiments. Cells were next incubated with 40 nM DiOC 6 -(3) for 15 min at 37 • C. Mitochondrial depolarization was assessed by a decrease of green fluorescence collected by the BD FACSCanto II flow cytometer (BD Biosciences). A minimum of 10 4 events per sample were acquired and samples were carried out in triplicate. The BD FACSDiva 7 software was used for data analysis (BD Biosciences, Franklin Lakes, NJ, USA).

Analysis of Autophagy

Detection of Autophagosomes

The activation of autophagy was assessed by the examination of autophagosomes formation with the Autophagy Assay Kit (MAK138, Sigma-Aldrich, Saint Louis, MO, USA). In brief, U266 cells were seeded in 96-well plates with 5,6-ECs (20 or 40 µg/mL) for 20 h in 37 • C or the vehicle. The autophagosome fluorescent reagent was then added to each well and incubated at 37 • C for 15 min. U266 cells were next observed under an Olympus BX53 fluorescent microscope (Olympus corporation, Tokyo, Japan) (×40, magnification).

Cancers 2021, 13, 3747 5 of 20 2.9.2. Determination of p62 Expression by Indirect Immunofluorescence U266 cells were treated with vehicle, 5,6 α-EC (40 µg/mL) or 5,6 β-EC alone (20 or 40 µg/mL). The cells were cytospun on superfrost glass slides, fixed in 4% paraformaldehyde, and permeabilized in 0.5% Triton-X100. The slides were then stained with an anti-p62 (SQSTM1) as primary antibody (Ab), and with Alexa Fluor 633-(in red) conjugated goat anti-mouse IgG as secondary Ab (Invitrogen, Carlsbad, CA, USA). Slides were counterstained with DAPI in blue (Molecular Probes, Eugene, OR, USA) and observed with a confocal microscope (Fluoview FV100, Olympus, Tokyo, Japan).

Effects of Autophagy Inhibition or Triggering on MM Cell Death and Apoptosis

U266 cells were seeded in 24-well plates (2 × 10 5 cells/well) for 24 h, treated with 5,6 α-EC or 5,6 β-EC (20-80 µg/mL) alone or in combination with 5 µM rapamycin (#R0395) or 10 µM of 3-methyladenine (3-MA) (#M9281), as autophagy inducer and inhibitor, respectively, all from Sigma-Aldrich (Saint Louis, MO, USA). After 24 h of treatment, cells were stained with 1 µg/mL PI for cell death assessment. At least, 10 4 events per sample were acquired and analyzed by flow cytometry BD FACSCanto II. Data were processed using BD FACSDiva 7 software (BD Biosciences, Franklin Lakes, NJ, USA). U266 cells were seeded in 24-well plates (2 × 10 5 cells/well) for 24 h, pre-treated (or not for control) with 50 nM bafilomycin A1 (BafA1, 19-148, Merck, Darmstadt, Germany) then treated with 5,6 β-EC (20 or 40 µg/mL). After 24 h of treatment, the cells were stained with annexin V-FITC/PI for apoptosis assessment as described before. At least, 10 4 events per sample were acquired and analyzed by flow cytometry with the CytoFlex cytometer and the CytExpert software (Beckman Coulter, Pasadena, CA, USA).

Western Blotting

Cell lysis was performed by incubating cells on ice for 30 min in a lysis buffer containing 1% NP-40, 100 mM Tris-HCl and a cocktail of protease inhibitors. Cell lysates were cleared by centrifugation at 20,000× g for 15 min. Proteins (50 µg) were separated by SDS-PAGE, and blotted onto nitrocellulose membranes (Bio-Rad, Hercules, CA, USA). After blocking non-specific binding sites, membranes were incubated with primary antibodies according to the manufacturer instructions. The following antibodies were used: anti-LC3B (#51520) from abcam (Cambrigde, UK); anti-caspase-3 (#9662), -PARP (#9532) and -β-actin (#4970) from Cell Signaling Technology (Danvers, MA, USA). Membranes were incubated with horseradish peroxidase (HRP)-conjugated goat anti-mouse (sc-2005, Santa-Cruz Biotechnology, CA, USA) or HRP-conjugated goat anti-rabbit (#6721, abcam, Cambrigde, UK). Membranes were revealed with a chemiluminescence detection reagent (Western Bright Quantum HRP substrate, Advansta, San Jose, CA, USA) using a ChemiDoc XRS+ imaging system (Bio-Rad).

Statistical Analyses

In vitro experiments were performed three times with samples in triplicate (n = 3). Representative results are shown as means ± standard deviation (SD). Statistical analyses were carried out with the two-tailed unpaired Student's t-test using the Excel software. The differences between two experimental groups were considered to be statistically significant when the obtained p-value was <0.05. To avoid unnecessarily loading the figures, the statistical data are gathered in additional tables in the Supplementary Information file.

Results

5,6 α-EC and 5,6 β-EC Exhibit Cytotoxic Activities on JJN3 and U266 Cell Lines

The cytotoxic activities of 5,6 α-EC and 5,6 β-EC were assessed by multiple in vitro standard tests: MTT assay, FDA (fluorescein diacetate) assay, Trypan blue exclusion, PI staining, and cytometry sorting on a panel of MM cell lines belonging to various molecular subtypes (Table S1). MTT assays were performed after 24, 48, or 72 h treatments with 5,6 α-EC or 5,6 β-EC isomers at various concentrations (5-80 µg/mL). Most of cells were responsive to both isomers as observed on the viability curves (Figure S1). We next focused on U266 and JJN3 cells that were representative.

The results revealed that 5,6 α-EC and 5,6 β-EC compounds significantly decreased HMCLs viability in a dose-dependent manner (Figure 1). JJN3 cells are more sensitive than U266 cells to both α and β isomers according to the calculated IC 50 values at 48 h (11 and 14 µg/mL, respectively, for JJN3 vs. 31 and 21 µg/mL, respectively, for U266 cells (Table 1). The 5,6 α-EC cytotoxic effect was maximal 24 h-post treatment for both cell lines whereas 5,6 β-EC showed a time-dependent cytotoxic effect (Figure 1). Accordingly, the calculated IC 50 decreased in a time dependent manner for JJN3 cells from 21 µg/mL (48 h) to 12 µg/mL (72 h) and for U266 cells, from 14 µg/mL (48 h) to 7 µg/mL (72 h) (Table 1). The cytotoxic effects of 5,6-ECs on JJN3 and U266 were confirmed with the FDA viability assay (Figure S2). An anti-proliferative effect of both compounds on JJN3 and U266 cells was also visualized under an inverted-phase contrast microscope (Figure S3).

5,6 α EC and 5,6 β-EC Exhibit Cytotoxic Activities on JJN3 and U266 Cell Lines

The cytotoxic activities of 5,6 α-EC and 5,6 β-EC were assessed by multiple in vitro standard tests: MTT assay, FDA (fluorescein diacetate) assay, Trypan blue exclusion, PI staining, and cytometry sorting on a panel of MM cell lines belonging to various molecular subtypes (Table S1). MTT assays were performed after 24, 48, or 72 h treatments with 5,6 α-EC or 5,6 β-EC isomers at various concentrations (5-80 µg/mL). Most of cells were responsive to both isomers as observed on the viability curves (Figure S1). We next focused on U266 and JJN3 cells that were representative.

The results revealed that 5,6 α-EC and 5,6 β-EC compounds significantly decreased HMCLs viability in a dose-dependent manner (Figure 1). JJN3 cells are more sensitive than U266 cells to both α and β isomers according to the calculated IC50 values at 48 h (11 and 14 µg/mL, respectively, for JJN3 vs. 31 and 21 µg/mL, respectively, for U266 cells (Table 1). The 5,6 α-EC cytotoxic effect was maximal 24 h-post treatment for both cell lines whereas 5,6 β-EC showed a time-dependent cytotoxic effect (Figure 1). Accordingly, the calculated IC50 decreased in a time dependent manner for JJN3 cells from 21 µg/mL (48 h) to 12 µg/mL (72 h) and for U266 cells, from 14 µg/mL (48 h) to 7 µg/mL (72 h) (Table 1). The cytotoxic effects of 5,6-ECs on JJN3 and U266 were confirmed with the FDA viability assay (Figure S2). An anti-proliferative effect of both compounds on JJN3 and U266 cells was also visualized under an inverted-phase contrast microscope (Figure S3).

5,6 α-EC and 5,6 β-EC Isomers Induce Apoptosis

To investigate whether 5,6 α-EC or 5,6 β-EC impacted cell cycle progression, HMCLs were treated with various concentrations of each 5,6-EC isomers (20-80 µg/mL) for 24 or 48 h. Cell cycle distribution was assessed after PI staining and flow cytometry sorting. For each treatment, cytometry profiles of both JJN3 and U266 cells indicated the emergence of a population of cells having a sub-G1 DNA content representative of apoptotic cells (Figure 2A). Indeed, after a 48 h-treatment, this percentage significantly increased in JJN3 cells of (+ 21.87% and + 3.5%) and in U266 (+ 6.86% and + 20.33%) for 40 µg/mL 5,6 α-EC or 5,6 β-EC, respectively (Figure 2A, Table S3).

AnnexinV/PI staining and cytometry analyses also confirmed that an apoptotic mode of cell death was triggered by 5,6 α-EC and 5,6 β-EC in JJN3 and U266 HMCLs. As exemplified for JJN3 cells, after a treatment with 20 µg/mL 5,6 α-EC for 48 h, 42.7% of cells are apoptotic (12.9% annexin V+/PI-and 29.8% of annexin V+/PI+) (Figure 2B). In the same experimental conditions, after treatment with 40 µg/mL 5,6 β-EC, 75.2% of U266 cells are apoptotic (63.4% annexin V+/PI-, 11.8% annexin V+/PI+), (Figure 2C). Notably, apoptotic cells were also detected in U266 cells treated with 5,6 α-EC and 5,6 β-EC for 24-72 h (Figure 2D, Tables S4 andS5).

Cytometry data showed that 5,6-ECs-treated cells went through apoptosis, and necrosis when treatments duration was extended, and drug doses increased. Thus, both 5,6-ECs compounds triggered an apoptotic cell death; the β isomer being more potent than the α isomer and JJN3 cells more sensitive than U266 cells confirming the data obtained with the viability assays.

Finally, Hoechst 33,342 staining was used to visualize the morphological changes induced by 5,6-ECs treatments in MM cells. Images revealed remarkable morphological changes giving rise to condensed or fragmented nuclei (apoptotic bodies) and diffused nuclei (in necrotic cells) (Figure 2E).

5,6 α-EC and 5,6 β-EC Isomers Activate the Mitochondrial Intrinsic Apoptotic Pathway

To further characterize the type of apoptosis triggered by 5,6 α/β-EC, we investigated the executioner caspase 3/7 activities in the same settings. The enzymatic activities of caspase 3/7significantly increased in a dose and time-dependent manner in 5,6 α-EC or 5,6 β-treated JJN3 and U266 cells (Figure 3A, Table S6).

In agreement with these observations, the treatments with 5,6 α-EC (40 µg/mL) or 5,6 β-EC (20 or 40 µg/mL) led to the cleavage and activation of caspase 3 and/or the cleavage of PARP (Figure S3). Mitochondrial depolarization (∆Ψm) is considered as the point-of-no-return of apoptosis and is essential for the activation of caspase 3/7 [START_REF] Brentnall | Caspase-9, Caspase-3 and Caspase-7 Have Distinct Roles during Intrinsic Apoptosis[END_REF]. Hence, ∆Ψm was measured by flow cytometry after DiOC 6 -(3) staining of JJN3 and U266 cells after exposure to 20-80 µg/mL 5,6 α-EC or 5,6 β-EC for 24-72 h. DiOC 6 -(3) being selective for the mitochondria of living cells, a decrease in ∆Ψm is representative of mitochondria collapse. We used as a positive control a hydrogen peroxide (H 2 O 2 )-treatment (500 µM for 24 h). As shown in Figure 3B,C, H 2 O 2 -treatment significantly decreased the fluorescence intensity correlating with an increase of the fraction of cells having a ∆Ψm loss. For example, JJN3 cells showed a significant loss of ∆Ψm after a 20 µg/mL 5,6 α-EC-treatment Cancers 2021, 13, 3747 8 of 20 (+ 84.1%) or 5,6 β-EC (+ 81.1%) for 48 h. In fine, 5,6 α-EC and 5,6 β-EC compounds induced a significant dose-dependent depolarization of mitochondria compared to vehicletreated cells confirming that both isomers triggered the mitochondrial-dependent apoptotic pathway in MM cells (Table S7). Moreover, 5,6 β-EC was confirmed more efficient than 5,6 α-EC on both cell lines (Figure 3). To determine the ability of 5,6 α-EC and 5,6 β-EC to induce an oxidative stress, we evaluated the production of ROS by flow cytometry after DHE staining of treated cells. Indeed, the percentage of DHE+ (i.e., producing superoxide anions) JJN3 cells significantly increased from 4% (vehicle) to 72.4% and 82.2% when cultured with 40 µg/mL 5,6 α-EC or 5,6 β-EC, respectively (Figure 4A). In agreement, ROS levels also increased in U266 cells cultured in the same conditions from 2.4% (vehicle) to 27.7% and 97.3%, respectively. After a 24 h-treatment with 5,6 α-EC or 5,6 β-EC (20-80 µg/mL), the percentage of DHE+ JJN3 and U266 cells significantly increased in a dose-dependent manner.

Moreover, we used α-tocopherol (or Vit E) to prevent 5,6 ECs-induced ROS. Cell death was evaluated in HMCLs by PI staining after a 24 h-treatment with 40 or 80 µg/mL 5,6 α-EC or 5,6 β-EC in the presence or the absence of Vit E. Results showed that Vit E remarkably reduced 5,6ECs-induced cell death (Figure 4B, Figure S5, Table S8). For example, the percentage of PI+ U266 cells significantly decreased from 33.5% with 40 µg/mL 5,6 α-EC and 40.1% with 40 µg/mL 5,6 β-EC, to 12.8% and 9.8% in combination with Vit E (400 µM), respectively. Flow cytometry data showed similar results for JJN3 cells supporting that Vit E prevented the production of ROS and the induction of an oxidative stress leading to cell death.

Finally, we inhibited ROS generation with a NAC pre-treatment (1 mM for 12 h) and treated U266 cells with 20 or 40 µg/mL 5,6 β-EC for 24 h. Apoptotic cells (annexin V+) were analyzed by flow cytometry. As presented Figure S6, the inhibition of ROS generation protected cells from 5,6-ECs-induced apoptosis. These findings confirmed that oxidative stress is an important event for 5,6-ECs-induced MM cell death and in particular, apoptosis.

5,6 α-EC and 5,6 β-EC Induce Autophagy in Myeloma Cells

To investigate whether 5,6-EC isomers induced autophagy concomitantly to apoptosis, we first assessed the presence of autophagosomes in 5,6-ECs-treated U266 cells stained with a fluorescent autophagosome marker. Microscopic examination of stained cells revealed the presence of autophagosomes. Moreover, their number increased in a dose-dependent manner (Figure 5A). In agreement with a previous report, U266 such as MM cells exhibited a remarkable basal autophagic activity (ref, Milan et al. J Clin Immunol 2016, 36, 18-24). The presence of autophagosomes reminiscent of an active autophagy was also revealed by the confocal microscopic examination of p62 (SQSTM1), the autophagy cargo receptor. As shown Figure 5B, the p62 staining pattern changed from diffuse (control cells) to punctate and cytoplasmic (treated cells) in a dose-dependent manner. S7). S8). No statistically significant difference between control and vehicle (EtOH) was noticed. S8). No statistically significant difference between control and vehicle (EtOH) was noticed.

We next studied by western blotting the conversion of microtubule-associated protein light chain 3 (LC3)-I to LC3-II in U266 treated cells to assess the autophagic flux (Figure 5C, Figure S7). Interestingly, a significant decrease of LC3B-I relative level accompanied by a significant increase of LC3B-II relative levels were observed under treatment with 40 µg/mL 5,6 α-EC or 20 or 40 µg/mL 5,6 β-EC. Additionally, the decrease of relative LC3B-I level was significantly dose-dependent when cells were exposed to 20 or 40 µg/mL 5,6 β-EC.

Moreover, rapamycin (an PI3K inhibitor) and 3-methyladenine (3-MA) (an mTOR inhibitor), the most widely used autophagy inducer or inhibitor, were employed to investigate their ability to modify the autophagic flux in 5,6-ECs treated MM cells. Notably, flow cytometry analysis of PI-stained cells showed that the 5,6-ECs-induced cell death was enhanced in the presence of rapamycin and reduced in the presence of 3-MA (Figure 5D). Moreover, BafA1, an inhibitor of autolysosomes formation, also protected U266 cells from 5,6 β-EC-induced apoptosis (Figure 5E). These results confirmed that all used chemicals modified the autophagic flux in treated MM cells, which is supporting that both isomers triggered an autophagic cell death in MM cells. (× 180, magnification). (C) U266 cells were untreated (U), vehicle-treated (E) or with 5,6 α-EC (40 µg/mL) or 5,6 β-EC (20 or 40 µg/mL). Within 24 h, whole-cell proteins were extracted, separated by SDS-PAGE, and transferred onto membranes then incubated with anti-LC3B or anti-β-actin (as a control) antibodies. Protein levels were estimated by densitometry and collected data from three independent experiments were presented in histograms (means ± SD). (D). The modification of autophagic flux was evaluated by flow cytometry. U266 cells were seeded into 24-well plates for 24 h. The cells were treated with 5,6 α-EC or 5,6 β-EC alone or in combination with 5 µM rapamycin or 10 µM 3-MA for 24 h. The cells were stained with PI and PI positive cells were recorded. At least 10 4 events were gated. The experiment has been done once with triplicate samples. (E) U266 cells were pre-treated with BafA1 (50 nM) for 4 h and then treated with 5,6 β-EC (40 µg/mL).

The cells were stained with annexin V/IP as described before and sorted. Cytometry profiles were presented together with the percentage of cells within each quadrant. The percentage of annexin V+ cells in each culture condition is presented in the histogram. * p <0.05; ** p < 0.01; *** p < 0.001; ns, not significant with the t-test.

3.6. 5,6 α-EC and 5,6 β-EC Reduce Cell Viability and Induce Apoptosis in Primary MM Cells Sorted CD138+ malignant plasma cells isolated from BMNCs of four MM patients (P1 to P4) were exposed to various concentrations (10-80 µg/mL) of 5,6 α-EC or 5,6 β-EC and MTT assays were performed. Due to the limited number of purified MM cells, only the counting with Trypan blue dye was performed with CD138+ cells from P4 patient. MTT results revealed that both molecules strongly reduced cell viability of CD138+ cells from all patients tested (Figure 6A). Indeed, under exposure with the highest dose of 5,6 α-EC, the viability of CD138+ cell was reduced by 81% for patient P2 and totally for patients P1 and P3, compared to vehicle control. The response of MM cells from patients was dose dependent. Regarding 5,6 β-EC, the decrease of CD138+ viability reached 59.2% and 48.2% for MM cells of patients P1 and P3, respectively, for a 40 µg/mL-treatment and remained almost constant for the highest dose of 80 µg/mL. An inhibition of 65.7% of the viability was obtained with the dose of 80 µg/mL for the patient P2.

Additionally, Trypan blue counting of MM cells from patient P4 showed a clear dose-dependent decrease of living cells (Figure 6A). Only 10% and 33% of cells remained viable following 80 µg/mL 5,6 α-EC-or 5,6 β-EC-treatment, respectively. For patient P4, we investigated whether the 5,6-ECs cytotoxic effect was exerted through apoptotic cell death. CD138+ cells isolated from patient P4 were treated with 10 or 40 µg/mL 5,6 α-EC or 5,6 β-EC for 40 h and next stained with annexin V/PI. As shown in Figure 6B, both isomers triggered primary cells apoptosis. The percentage of CD138+ cells in early and late apoptosis (annexin V+/PI-and annexin V+/PI+) increased from 4.9% in the control sample to 13.8% and 10.9% in the samples treated with 10 µg/mL of 5,6 α-EC or 5,6 β-EC, respectively. The percentage of apoptotic cells reached 99.5% when they were treated with 40 µg/mL 5,6 β-EC; the cells were almost all necrotic when treated with the same concentration of 5,6 α-EC.

Further, we examined whether apoptosis was induced by 5,6-ECs in non-tumor CD38-/CD138-BMNCs sub-population from patient P5. For that purpose, BMNCs were cultured in the presence of 5,6 α-EC or 5,6 β-EC (10 or 20 µg/mL) for 24 h. Next, triple staining of BMNCs (CD38, CD138, and annexin V) followed by flow cytometry analysis showed that the percentages of annexin V+ non tumor cells were unchanged after 5,6 α-EC, 5,6 β-EC, or vehicle-treatment (18.8% and 18.4% vs. 17.9%) (Figure 6C). Our results indicated a lack of cytotoxicity of the 5,6-ECscompounds against CD38-/CD138-bone marrow cells. Additionally, 5,6 α-EC or 5,6 β-EC were not cytotoxic toward the normal human bone marrow stromal (HS-5) cell line treated with 10 or 20 µg/mL of each isomer for 24 or 48 h as observed by an MTT assay (Figure 6D). We concluded that both molecules exhibited apoptotic features only toward malignant CD138+ plasma cells and were not toxic against other BMNCs and HS-5 mesenchymal stromal cells.

Overall and by contrast with the results obtained with MM cell lines, although each MM patient possesses her/his own sensitivity towards 5,6 α/β-EC compounds, the α isomer seemed more potent for inhibiting tumor cell proliferation and inducing MM cell death.

5,6 α-EC and 5,6 β-EC Exhibit Synergistic Cytotoxic Effects in MM Cells

Multi-agent therapies are a hallmark of treatment for multiple myeloma. Therefore, we analyzed the combination of the two 5,6-ECs isomers on U266 MM line. Cells were treated with both 5,6 α-EC or 5,6 β-EC with the IC 25 or IC 50 corresponding concentrations for 24 and 48 h (Table 1, Figure S8). Cell viability was assessed by MTT assay, and the results are reported in Figure S8. Interestingly, following the combination treatment with the IC 25 corresponding doses, the cell viability decrease was higher than the sum of the cytotoxic effects taken separately, in a dose-dependent manner. U266 cell death increased from approximately 30% (for each isomer) to 81% (for the combination) after 24 and 48 h of exposure (Figure S8). The trend was also maintained for higher doses (IC 50 ). Moreover, the Chou-Talalay combination index (CI) calculated with the CompuSyn software, indicated a strong (notable) synergistic effect. In fact, the CI value was less than 1 with both IC [START_REF] Fernandes | 7-Ketocholesterol Overcomes Drug Resistance in Chronic Myeloid Leukemia Cell Lines beyond MDR1 Mechanism[END_REF] and IC 50 treatment doses, supporting favorably a synergistic interaction between 5,6 α-EC and 5,6 β-EC on myeloma cells (Table 2). Finally, we analyzed a potential synergic effect of both 5,6-ECs with the gold standard drug in MM: bortezomib. We compared anti-tumor effect of the single treatments with 5,6-ECs and the combined treatments 5,6 α-EC/BTZ or 5,6 β-EC/BTZ with an MTT assay. The concentrations of the drugs that were used are indicated in the Table 3, as well as the Chou-Talalay CI. The dual BTZ/5,6-ECs treatment revealed a strong synergistic effect reinforcing the interest of oxysterol compounds for anti-myeloma therapy.

Discussion

Despite the development of novel successful therapies, MM remains an incurable type of cancer, since relapse and treatment resistance mainly occur with a median overall survival of four years [START_REF] Gonzalez-Santamarta | Resistance to the Proteasome Inhibitors: Lessons from Multiple Myeloma and Mantle Cell Lymphoma[END_REF]. Investigating lipid metabolism, often deregulated in MM patients, is one way to help developing new treatments and/or improving pre-existing ones [START_REF] Choi | Lipid Level, Lipid Variability, and Risk of Multiple Myeloma: A Nationwide Population-Based Study of 3,527,776 Subjects[END_REF]. In human body, oxysterols act as important regulators of physiological, physio-pathological and pharmacological processes [START_REF] Brown | From Physiological Tuners to Pharmacological Opportunities[END_REF].

Herein, we report for the first time the anti-tumor activities of the 5,6-ECs α and β isomers on HMCLs and primary cells isolated from MM patients. Indeed, a significant decrease of cell proliferation was observed for treated HMCLs and primary cells in a dosedependent manner. We note that 5,6 β-EC was more efficient on HMCLs, while the 5,6 α-EC seemed more efficient on patients' malignant cells. Moreover 5,6-ECs α and β isomers demonstrate a high cytotoxicity against JJN3 and U266 cells having various sensitivities towards bortezomib, the gold standard drug [START_REF] Caillot | ROS Overproduction Sensitises Myeloma Cells to Bortezomib-Induced Apoptosis and Alleviates Tumour Microenvironment-Mediated Cell Resistance[END_REF], whereas they have no effects on normal bone marrow mesenchymal HS-5 cells. Our findings are in agreement with previous data reporting that cholesterol derivatives, including 5,6 α-ECs, suppress proliferation and survival of human breast cancer and mouse skin melanoma cell lines in vitro [START_REF] Levy | Oxysterols Selectively Promote Short-Term Apoptosis in Tumor Cell Lines[END_REF].

The type of cell death induced by 5,6-ECs isomers in myeloma cells was further investigated. Using various assays, we demonstrated that 5,6 α/β-ECs trigger apoptosis in HMCLs and malignant primary cells. The activation of the apoptotic pathway leads to morphological changes such as chromatin condensation and generation of apoptotic bodies (Figure 2E). Cellular alterations culminate with DNA fragmentation and PARP cleavage (Figure S3) conductive to cell death. 5,6 α/β-ECs-mediated apoptosis depend on the activation and the cleavage of caspase 3/7 (Figure S3). In agreement with our findings, Fernandes and coworkers reported that 7-ketocholesterol, an oxidized cholesterol derivative, induces an apoptosis-mediated cell death in chronic myeloid leukemia cell lines [START_REF] Fernandes | 7-Ketocholesterol Overcomes Drug Resistance in Chronic Myeloid Leukemia Cell Lines beyond MDR1 Mechanism[END_REF].

Ex vivo preclinical studies on primary patient-derived tumor cells yield results with a high predictive value towards the clinical outcome. To this end, we sought to examine the effects of 5,6-ECs α and β isomers on CD138+ primary cells purified from four MM patients at diagnosis (Figure 6). The inhibition of proliferation and the induction of apoptosis in response to 5,6-ECs were investigated. Both isomers display a significant cytotoxic activity against CD138+ primary cells isolated from MM patients. This effect was mediated via apoptosis cell death as revealed for patient P4. Moreover, both isomers were not cytotoxic against mesenchymal HS-5 cells (Figure 6D) and patient P5 bone marrow mononuclear cells (CD138-/CD38-) (Figure 6C).

Oxysterols induce apoptosis through both the death receptor or extrinsic pathway and the mitochondrial or intrinsic pathway [START_REF] Prunet | Activation of Caspase-3-Dependent and -Independent Pathways during 7-Ketocholesterol-and 7β-Hydroxycholesterol-Induced Cell Death: A Morphological and Biochemical Study[END_REF]. We reported that 5,6-ECs treatment cause a high ∆Ψm loss in both JJN3 and U266 myeloma lines (Figure 3B,C), indicating that the mitochondrial intrinsic pathway is activated. Alterations of ∆Ψm not only result in mitochondrial membrane permeabilization but also in the production of ROS [START_REF] Olkkonen | Oxysterols and Their Cellular Effectors[END_REF]. The 5,6-ECs treatment significantly induces the production of high levels of ROS (especially O 2-) implicated in HMCLs cell death as revealed by vitamin E cytoprotection (Figure 4B, Figure S4). Our previous data supported the interest to promote an oxidative stress in an anti-MM strategy [START_REF] Caillot | ROS Overproduction Sensitises Myeloma Cells to Bortezomib-Induced Apoptosis and Alleviates Tumour Microenvironment-Mediated Cell Resistance[END_REF]. In particular, increasing ROS to high levels may provide a unique tool to kill myeloma cells [START_REF] Caillot | Targeting Reactive Oxygen Species Metabolism to Induce Myeloma Cell Death[END_REF]. Indeed, we recently reported that modulating the redox balance of MM cells could be an effective therapy for refractory or post-treatment patients [START_REF] Caillot | ROS Overproduction Sensitises Myeloma Cells to Bortezomib-Induced Apoptosis and Alleviates Tumour Microenvironment-Mediated Cell Resistance[END_REF].

Besides apoptosis, an autophagic cell death was reported in various cell types treated with oxysterols [START_REF] Sghaier | Biotin Attenuation of Oxidative Stress, Mitochondrial Dysfunction, Lipid Metabolism Alteration and 7β-Hydroxycholesterol-Induced Cell Death in 158N Murine Oligodendrocytes[END_REF]. The generation of ROS induces a protective mechanism of autophagy in MM cells and if the unfolded protein response is chronically compromised, autophagy results in cell death [START_REF] Michallet | Compromising the Unfolded Protein Response Induces Autophagy-Mediated Cell Death in Multiple Myeloma Cells[END_REF]. We therefore investigated this type of cell death in 5,6-ECstreated HMCLs and found an increase of autophagosomes correlated with the treatment (Figure 5A). The microtubule-associated protein 1A/B-light chain 3B (or LC3B) is translocated to autophagosomes and the conversion of LC3B-I into LC3B-II is a robust marker of autophagy [START_REF] Nury | Induction of Oxiapoptophagy, a Mixed Mode of Cell Death Associated with Oxidative Stress, Apoptosis and Autophagy, on 7-Ketocholesterol-Treated 158N Murine Oligodendrocytes: Impairment by α-Tocopherol[END_REF]. Both isomers affect the expression of light chain 3 in increasing the level of the LC3B-II and those of p62, the autophagosome cargo, consistent with an active autophagy (Figure 5B,C). Moreover, both EC isomers modulate the autophagic signaling pathway when cells were pre-incubated with rapamycin or 3-MA. Notably, molecules capable of modulating autophagy are increasingly proposed for therapeutic purposes, including MM [START_REF] Yang | Application and Interpretation of Current Autophagy Inhibitors and Activators[END_REF][START_REF] Levy | Targeting Autophagy in Cancer[END_REF]. For example, betulinic acid was found to induce either apoptotic or autophagic cell death in MM cells [START_REF] Zhou | PP2A Mediates Apoptosis or Autophagic Cell Death in Multiple Myeloma Cell Lines[END_REF]. Similarly, Fu and coworkers reported that the activation of the endoplasmic reticulum stress, using the drug tunicamycin, induced autophagy and apoptosis in MM cells, thereby inhibiting proliferation and chemotherapy resistance [START_REF] Fu | Endoplasmic Reticulum Stress Induces Autophagy and Apoptosis While Inhibiting Proliferation and Drug Resistance in Multiple Myeloma through the PI3K/Akt/MTOR Signaling Pathway[END_REF]. As a whole, the death of MM cells after 5,6-ECs treatment proceeds through oxidative stress, apoptotic and autophagic cell death mechanisms.

Finally, our data showed that the combination of low concentrations (IC 25 ) of the two 5,6 α/β-ECs isomers increased the efficiency of the treatment in a synergistic manner (Table 2), as well the combination with bortezomib (Table 3). The synergy is a benefit over an additive response. In addition to the objective of maximizing efficiency, this could also improve the sensitivity and selectivity of cancer treatment. In MM therapy, synergistic drug combinations are highly sought after due to their multiple advantages, such as optimizing efficacy, reducing toxicity, and delaying or overcoming resistance. Accordingly, it was reported that therapeutic approaches based on the combination of two or more compounds would be more effective by affecting more signaling pathways and overcoming drug resistance mechanism [START_REF] Rejhová | Natural Compounds and Combination Therapy in Colorectal Cancer Treatment[END_REF]. In the literature, there are several examples of anticancer combination therapy using potent molecules [START_REF] Sauter | Cancer Prevention and Treatment Using Combination Therapy with Natural Compounds[END_REF].

5,6-ECs have been described as active biomolecules implicated in the pharmacology and/or therapeutic effects of anti-tumor drugs. In breast cancer cells, the isomers contribute to the anticancer pharmacology of tamoxifen through the inhibition of the enzymatic activity of cholesterol epoxide hydrolase resulting in the accumulation of endogenous 5,6 α/β-ECs [START_REF] Segala | 5,6-Epoxy-Cholesterols Contribute to the Anticancer Pharmacology of Tamoxifen in Breast Cancer Cells[END_REF][START_REF] De Medina | Identification and Pharmacological Characterization of Cholesterol-5,6-Epoxide Hydrolase as a Target for Tamoxifen and AEBS Ligands[END_REF]. We observed the same response in two HMCLs, where antiestrogenbinding site ligands induced apoptosis and autophagy through a mechanism that involve the production and the accumulation of the two isomers 5,6 α/β-ECs [START_REF] Sola | Antiestrogen-Binding Site Ligands Induce Autophagy in Myeloma Cells That Proceeds through Alteration of Cholesterol Metabolism[END_REF].

Investigating lipid metabolic pathway is a novel area in MM with preclinical data suggesting efficacy. Abnormal lipid and lipoprotein profiles have clearly been associated with MM. The level of total cholesterol, LDL-C and HDL-C were significantly lower in MM stages II and III patients than in controls [START_REF] Yavasoglu | Cholesterol Levels in Patients with Multiple Myeloma[END_REF]. Moreover, oxysterols intracellular concentration is correlated to that of cholesterol, and play an active role in cell signaling and cholesterol homeostasis [START_REF] Gill | Sterol Regulators of Cholesterol Homeostasis and beyond: The Oxysterol Hypothesis Revisited and Revised[END_REF]. Therefore, targeting cholesterol metabolism via epoxycholesterols in MM could be a potential approach to enhance anti-myeloma-based therapies.

Conclusions

To conclude, the present study provides evidence for a cytotoxic effect of 5,6-ECs α and β isomers on human myeloma cells. This anti-myeloma activity is concomitantly induced by oxidative stress, apoptosis and autophagy, a complex mode of cell death defined as oxiapoptophagy. The term oxiapoptophagy (OXIdative stress + APOPTOsis + autoPHAGY) firstly reported by Monier and coworkers [START_REF] Monier | Impairment of the Cytotoxic and Oxidative Activities of 7β-Hydroxycholesterol and 7-Ketocholesterol by Esterification with Oleate[END_REF], was later described to be induced by other oxysterols in multiple cell types [START_REF] Nury | Oxiapoptophagy: A Type of Cell Death Induced by Some Oxysterols[END_REF]. Our study is the first to confirm the occurrence of oxiapoptophagy induced by 5,6-ECs in MM cells.

Figure 1 .

 1 Figure 1. Evaluation of 5,6-ECs-induced cytotoxic effects on HMCLs. JJN3 and U266 cells were seeded in 96-well plates at the density of 2 × 10 5 cells/well for 24 h. Then, cells were cultured with 5-80 µg/mL 5,6 α-EC or 5,6 β-EC for 24-72 h and their viability

Figure 1 .

 1 Figure 1. Evaluation of 5,6-ECs-induced cytotoxic effects on HMCLs. JJN3 and U266 cells were seeded in 96-well plates at the density of 2 × 10 5 cells/well for 24 h. Then, cells were cultured with 5-80 µg/mL 5,6 α-EC or 5,6 β-EC for 24-72 h and their viability assayed using a colorimetric MTT assay. Reported values are means ± SD from three independent experiments. No statistically significant difference between control (no treatment) and vehicle (EtOH-treatment) was noticed.

Cancers 2021, 13 , x 8 of 22 Figure 2 . 5 , 6 -of 20 2 ×

 13222562 Figure 2. 5,6-ECs induce apoptosis of HMCLs. (A) JJN3 and U266 cells were seeded at the density of

3. 4

 4 . 5,6 α-EC and 5,6 β-EC Increased ROS Production in JJN3 and U266 Cells

Figure 3 .

 3 Figure 3. The apoptotic intrinsic pathway is triggered by 5,6-ECs treatment in HMCLs. (A) JJN3 and U266 cells were seeded in 24-well plates at a density of 2 × 10 5 cells/well for 24 h and treated with 5,6 α-EC or 5,6 β-EC (20-80 µg/mL) for 24-72 h. Caspase 3/7 enzymatic activity was detected by flow cytometry in both cell lines. The percentage of cells with activated caspase 3/7 was presented in histograms as the mean ± SD (Table S6). The percentages of DiOC 6 -(3) negative (with depolarized mitochondria) JJN3 (B) or U266 (C) cells obtained by flow cytometry are showed in histograms as the means ± SD. H 2 O 2 (500 µM) was used as a positive control. No statistically significant difference between control and vehicle (EtOH) was noticed. * p < 0.05; ** p < 0.01; *** p < 0.001 with the t-test (TableS7).

Figure 4 .

 4 Figure 4. ROS overproduction induced cell death of 5,6 ECs-treated HMCLs. (A) JJN3 and U266 cells were cultured in 24-well plates (2 × 10 5 cells/well) for 24 h. Then, cells were treated with 20-80 µg/mL of 5,6 α-EC or 5,6 β-EC for 24 h or with 500 µM H2O2 used as a positive control. ROS overproduction was evaluated by flow cytometry (upper part). The percentages of DHE+ cells (overproducing superoxide anion O 2-) are indicated by the histograms (lower part). (B) Cells were treated or not with 400 µM Vit E for 2 h then, treated for 24 h with 5,6 α-EC or 5,6 β-EC (40-80 µg/mL). The inhibition of death induced by 5,6-ECs was evaluated by the percentage of PI+ HMCLs presented as means ±SD. Statistical t-tests were used to calculate the p-values between 5,6α/β-ECs-treated cells vs. vehicle-treated cells or between 5,6 α/β-ECs-vs. 5,6 α/β-ECs + Vit E-treated cells (*p < 0.05; ** p < 0.01; *** p < 0.001) (TableS8). No statistically significant difference between control and vehicle (EtOH) was noticed.

Figure 4 .

 4 Figure 4. ROS overproduction induced cell death of 5,6 ECs-treated HMCLs. (A) JJN3 and U266 cells were cultured in 24-well plates (2 × 10 5 cells/well) for 24 h. Then, cells were treated with 20-80 µg/mL of 5,6 α-EC or 5,6 β-EC for 24 h or with 500 µM H 2 O 2 used as a positive control. ROS overproduction was evaluated by flow cytometry (upper part). The percentages of DHE+ cells (overproducing superoxide anion O 2-) are indicated by the histograms (lower part). (B) Cells were treated or not with 400 µM Vit E for 2 h then, treated for 24 h with 5,6 α-EC or 5,6 β-EC (40-80 µg/mL). The inhibition of death induced by 5,6-ECs was evaluated by the percentage of PI+ HMCLs presented as means ±SD. Statistical t-tests were used to calculate the p-values between 5,6 α/β-ECs-treated cells vs. vehicle-treated cells or between 5,6 α/β-ECsvs. 5,6 α/β-ECs + Vit E-treated cells (* p < 0.05; ** p < 0.01; *** p < 0.001) (TableS8). No statistically significant difference between control and vehicle (EtOH) was noticed.

Cancers 2021, 13 , x 14 of 22 Figure 5 . 5 , 6 -

 1322556 Figure 5. 5,6-ECs induce an autophagy-mediated cell death. (A) U266 cells were treated with vehicle or 5,6 α/β-EC (20, 40 µg/mL) for 20 h. Cells were then stained with an autophagosome specific fluorescent probe and analyzed with an Olympus BX53 fluorescent microscope (× 40, magnification) (B) p62 expression was analyzed by IF in EtOH-and 5,6-ECs-treated cells. We used a primary Ab against p62, and a goat Alexa Fluor 488-conjugated anti-rabbit IgG as secondary Ab. Slides were counterstained with DAPI and analyzed with a confocal microscope (Fluoview FV100, Olympus,CA) (× 180, magnification). (C) U266 cells were untreated (U), vehicle-treated (E) or with 5,6 α-EC (40 µg/mL) or 5,6 β-EC (20 or 40 µg/mL). Within 24 h, whole-cell proteins were extracted, separated by SDS-PAGE, and transferred onto membranes then incubated with anti-LC3B or anti-β-actin (as a control) antibodies. Protein levels were estimated by densitometry and collected data from three independent experiments were presented in histograms (means ± SD). (D). The modification of autophagic flux was evaluated by flow cytometry. U266 cells were seeded into 24-well plates for 24 h. The cells were treated with 5,6 α-EC or 5,6 β-EC alone or in combination with 5 µM rapamycin or 10 µM 3-MA for 24 h. The cells were stained with PI and PI positive cells were recorded. At least 10 4 events were gated. The experiment has been done once with triplicate samples. (E) U266 cells were pre-treated with BafA1 (50 nM) for 4 h and then treated with 5,6β-EC (40 µg/mL). The cells were stained with annexin V/IP as described before and sorted. Cytometry profiles were presented together with the percentage of cells within each quadrant. The percentage of annexin V+ cells in each culture condition is presented in the histogram. * p <0.05; ** p < 0.01; *** p < 0.001; ns, not significant with the t-test.

Figure 5 . 5 , 6 -

 556 Figure 5. 5,6-ECs induce an autophagy-mediated cell death. (A) U266 cells were treated with vehicle or 5,6 α/β-EC (20, 40 µg/mL) for 20 h. Cells were then stained with an autophagosome specific fluorescent probe and analyzed with an Olympus BX53 fluorescent microscope (× 40, magnification) (B) p62 expression was analyzed by IF in EtOH-and 5,6-ECs-treated cells. We used a primary Ab against p62, and a goat Alexa Fluor 488-conjugated anti-rabbit IgG as secondary Ab. Slides were counterstained with DAPI and analyzed with a confocal microscope (Fluoview FV100, Olympus, CA, USA)

Figure 6 . 5 , 6 -

 656 Figure 6. 5,6-ECs display selective cytotoxic and apoptotic activities on human primary malignant plasma cells. (A) Cytotoxic activity of compounds was assessed on patient malignant cells of P1, P2 and P3 by MTT and for P4 cells by Trypan blue. For this, mononuclear cells (BMNCs) were purified from bone marrow and cell sorting using CD138 microbeads was assessed for P1-P4. CD138+ malignant plasma cells were cultured for 40 h in the absence or presence of 10-80 µg/mL of 5,6 α-EC or 5,6 β-EC. (B) Annexin V staining and flow sorting was used to detect the apoptotic population in sorted CD138+ cells of P1 after treatments with 10 or 40 µg/mL 5,6 α-EC or 5,6 β-EC. Flow cytometry profiles for all cell compartments (annexin V-/PI-, annexin V+/PI-, annexin V+/PI+ and annexin V-/PI+) with the corresponding percentages are presented. (C) BMNCs of P5 were treated with 10 µg/mL or 20 µg/mL of 5,6 α-EC or 5,6 β-EC for 24 h then labeled simultaneously for CD38, CD138 and annexin V. Annexin V+/CD38-/CD138-population was next evaluated by flow cytometry and presented in the histograms as means ±SD. (D) The effect of 5,6-ECs on HS-5 human non-tumor mesenchymal stromal cells was also evaluated using an MTT assay after 24 or 48 h of treatment. Data are presented as the means ±SD. No statistically significant difference between control and vehicle (EtOH) was noticed; ns, not significant.

Table 1 .

 1 IC 50 values of 5,6 α/β-EC for the different periods of treatment.MM cell lines were seeded in 96-well plates at the density of 2 × 10 4 cells per well, then treated for 24-72 h with vehicle, 5,6 α-EC or 5,6 β-EC (5-80 µg/mL). Cell viability was assessed using an MTT assay. The IC 50 were calculated after drawing the inhibition curves using the Excel software and verified with the CompuSyn software (www.combosyn.com/, accessed on 21 July 2021). The indicated values are means ± SD from three different assays, with triplicate samples for each culture condition.

	24 h	48 h	72 h

Table 2 .

 2 Chou-Talalay index for the various combinations of 5,6-ECs. cell lines were seeded in 24-well plates at the density of 2 × 10 5 cells per well, then treated for 24 h or 48 h the with the indicated concentrations of 5,6 α-EC or 5,6 β-EC corresponding to the IC 25 * and IC 50 **. Cell viability was assessed using an MTT assay. The CI, presented as means ± SD, were calculated with the CompuSyn software (www.combosyn.com/, accessed on 21 July 2021).3.8. 5,6 α-EC and 5,6 β-EC Exhibit Synergistic Cytotoxic Effects with BTZ in MM Cells

	5,6 α-EC (µg/mL)	5,6 β-EC (µg/mL)	CI-24 h	CI-48 h	Effect
	12 *	20 *	0.18 ± 0.03	0.22 ± 0.2	Synergistic
	26 **	27 **	8.52 -4 ± 0.13	9.09 -4 ± 0.24	Synergistic

U266

Table 3 .

 3 Synergistic effect of 5,6-ECs associated with BTZ.

	Cell	BTZ [nM]	5,6 α-EC [µg/mL]	5,6 β-EC [µg/mL]	CI (Mean ± SD)	Effect
		2	10	-	0.35 ± 0.087	Synergistic
		2	20	-	0.60 ± 0.024	Synergistic
		4	5	-	0.16 ± 0.037	Synergistic
		4	10	-	0.31 ± 0.039	Synergistic
		4	20	-	0.59 ± 0.014	Synergistic
		6	5	-	0.16 ± 0.019	Synergistic
		6	10	-	0.31 ± 0.015	Synergistic
		6	20	-	0.61 ± 0.012	Synergistic
	U266	2	-	5	0.12 ± 0.02	Synergistic
		2	-	10	0.24 ± 0.02	Synergistic
		2	-	20	0.41 ± 0.02	Synergistic
		4	-	5	0.12 ± 0.01	Synergistic
		4	-	10	0.23 ± 0.01	Synergistic
		4	-	20	0.51 ± 0.01	Synergistic
		6	-	5	0.11 ± 0.02	Synergistic
		6	-	10	0.23 ± 0.03	Synergistic
		6	-	20	0.2 ± 0.21	Synergistic

Table 3 .

 3 Cont. cell lines were seeded in 96-well plates at the density of 5 × 10 4 cells per well, then treated with the vehicle or 5,6 α-EC (5-30 µg/mL), 5,6 β-EC (5-20 µg/mL), BTZ (1.25-6 nM) alone or with 5,6 α-EC /BTZ, 5,6 β-EC/BTZ combination. Viability was revealed with an MTT assay after 48 h. The results were analyzed by the CompuSyn software to evaluate the combination index. The Chou-Talalay index offers a quantitative definition for additive effects (CI = 1.0), synergism (CI < 1.0), and antagonism (CI > 1.0) for drugs combination.

	Cell	BTZ [nM]	5,6 α-EC [µg/mL]	5,6 β-EC [µg/mL]	CI (Mean ± SD)	Effect
		1.25	15	-	0.84 ± 0.05	Synergistic
		1.25	30	-	0.81 ± 0.02	Synergistic
		2.5	30	-	0.34 ± 0.01	Synergistic
		5	15	-	0.07 ± 0.04	Synergistic
		5	30	-	0.001 ± 0.01	Synergistic
		2	-	5	0.034 ± 0.05	Synergistic
	JJN3	2 2	--	10 20	0.035 ± 0.01 0.001 ± 0.02	Synergistic Synergistic
		4	-	5	0.05 ± 0.01	Synergistic
		4	-	10	0.049 ±0.01	Synergistic
		4	-	20	0.001 ± 0.01	Synergistic
		6	-	5	0.05 ± 0.02	Synergistic
		6	-	10	0.50 ± 0.03	Synergistic
		6	-	20	2.7 -13 ± 0.21	Synergistic

MM

Acknowledgments:

We thank Gérard Lizard from Team 'Biochemistry of the Peroxisome, Inflammation and Lipid Metabolism' EA 7270/Inserm, 21000 Dijon for providing us the 5,6 Epoxycholesterol isomers used in the experimental section. We are grateful to the research platform of Medical Sciences and Technology of the Faculty of Medicine of Tunis (University of Tunis El Manar). We also thank the Structure Fédérative de Recherche ICORE (Université de Caen Normandie) for cytometry facility.

Data Availability Statement:

The data presented in this study are available in the main text and supplementary materials.

Supplementary Materials:

The following are available online at https://www.mdpi.com/article/ 10.3390/cancers13153747/s1, Figure S1: Viability curves of HMCLs to 5,6 α/β-EC; S1: Characteristics of the HMCLs used in the study; Table S2: Clinico-biological parameters of MM patients; Table S3: Statistical analyses of Figure 2A; Table S4: Annexin V/PI assay results; Table S5: Statistical analyses of Figure 2B,D; Table S6: Statistical analyses of Figure 3A; Table S7: Statistical analyses of Figure 3B,C; Supplementary references. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patients to publish this paper.

Conflicts of Interest:

The authors declare no conflict of interest.


Pierre Champion
email: pierre.champion@inria.fr

Denis Jouvet
email: denis.jouvet@inria.fr

Anthony Larcher
email: anthony.larcher@univ-lemans.fr

Evaluating X-vector-based Speaker Anonymization under White-box Assessment

Keywords: Speaker anonymization, VoicePrivacy, Anonymization evaluation

In the scenario of the Voice Privacy challenge, anonymization is achieved by converting all utterances from a source speaker to match the same target identity; this identity being randomly selected. In this context, an attacker with maximum knowledge about the anonymization system can not infer the target identity. This article proposed to constrain the target selection to a specific identity, i.e., removing the random selection of identity, to evaluate the extreme threat under a whitebox assessment (the attacker has complete knowledge about the system). Targeting a unique identity also allows us to investigate whether some target's identities are better than others to anonymize a given speaker.

Introduction

In many applications, such as virtual assistants, speech signal is sent from the user device to the service provider's servers in which data is collected, processed, and stored. Recent regulations, e.g., the General Data Protection Regulation (GDPR) [START_REF] Parliament | Parliament and of the Council of 27 April 2016[END_REF] in the EU, emphasize on privacy preservation and protection of personal data. As speech data can reflect both biological and behavioral characteristics of the speaker, it is qualified as personal data [START_REF] Nautsch | The GDPR & Speech Data: Reflections of Legal and Technology Communities, First Steps Towards a Common Understanding[END_REF]. The research reported in this article has been done using the Voice privacy Challenge framework [START_REF] Tomashenko | Introducing the VoicePrivacy Initiative[END_REF], which is one of the first attempts of the speech community to evaluate research on this topic, by producing dedicated protocols, metrics, datasets and baselines.

Speaker anonymization is performed to suppress the personally identifiable paralinguistic information from a speech utterance while maintaining the linguistic content. This is also referred to as speaker anonymization [START_REF] Fang | Speaker Anonymization Using X-vector and Neural Waveform Models[END_REF] or de-identification [START_REF] Magariños | Reversible speaker de-identification using pre-trained transformation functions[END_REF]. Recently, Fang et al. [START_REF] Fang | Speaker Anonymization Using X-vector and Neural Waveform Models[END_REF] proposed an x-vector-based speaker anonymization system based on voice conversion where one of the hyper-parameters used to transform the voice is a target pseudo-speaker identity. In order to choose the anonymization system and hyper-parameters, for a given use case, we must evaluate and rank the performances of each anonymization method. In this first edition of the Voice privacy Challenge, the quality of anonymization is assessed by using state-of-the-art speaker verification system together with an automatic speech recognition system that is used to evaluate the preservation of the linguistic content. In the context of privacy, a game-theoretic reasoning with two agents is defined as follows: one who wishes to anonymize a user's speech (the service provider) and the other (the attacker) who will do everything possible to "break" this anonymity. Introduced in [START_REF] Srivastava | Evaluating voice conversion-based privacy protection against informed attackers[END_REF], the notion of attacker's knowledge of the anonymization method was introduced, it defines three possible attack scenarios: black-box, white-box, and grey-box. In all approaches, privacy is evaluated by comparing original speech (accessible to the attacker) and anonymous speech published by a service provider. The goal of an effective anonymization system is to allow the publication of speech whose identity is difficult to link to a user's identity, even if the attacker has some knowledge of the anonymization mechanism. In the black-box attacker scenario, privacy is measured by comparing clean, non-anonymized enrollment speech, and anonymized trial speech. In this scenario, the attacker is not aware that speech has been anonymized. In contrast, a white-box attacker is fully aware of the anonymization system and hyper-parameters. Grey-box attackers cover the whole range of possible scenario in-between black and white boxes, when the attacker has a partial knowledge of the anonymization system.

The target pseudo-speaker identity used to anonymize the voices can be generated following multiple strategies [START_REF] Srivastava | Evaluating voice conversion-based privacy protection against informed attackers[END_REF]. In the permanent strategy, used in the VoicePrivacy challenge, all utterances from a speaker are converted using the same target pseudo-speaker. The challenge defines a grey-box attacker that has access to the anonymization toolkit, and thus is able to transform any utterance from her enrollment dataset using the same system and target strategy. However, for a given source speaker, the target pseudo-speaker used by the attacker differs from the one used by the service provider due to the random pseudo-speaker selection process included in the permanent strategy. In case the attacker knows the pseudo-speaker, this grey-box scenario turns into a white-box scenario.

We modify the Voice Privacy Challenge scenario into a white-box assessment by targeting a same speaker identity for all utterances from all speakers. This target selection strategy allows us to evaluate the performance of the x-vectorbased anonymization system on its own, and generate a report that does not assume that the attacker has knowledge deficiencies. Experiments are performed with a large group of target speaker identity in order to investigate the effect of this identity on the quality of the anonymization.

In the remaining of this article, we first describe the baseline system and voice conversion method in Section 2. We then introduce our experimental protocol in Section 3 and present our experimental results in Section 4. Eventually, we draw our conclusions and propose future avenues in Section 5.

Anonymization Technique

The anonymization of speaker's identity can be performed with various methods [START_REF] Bahmaninezhad | Convolutional neural network based speaker de-identification[END_REF][START_REF] Fang | Speaker Anonymization Using X-vector and Neural Waveform Models[END_REF][START_REF] Mcadams | Spectral fusion, spectral parsing and the formation of the auditory image[END_REF][START_REF] Srivastava | Privacy-Preserving Adversarial Representation Learning in ASR: Reality or Illusion?[END_REF][START_REF] Srivastava | Evaluating voice conversion-based privacy protection against informed attackers[END_REF]. In this article, our contributions are based on the Baseline-1 (referred to as the baseline in this article) of the VoicePrivacy challenge that anonymizes speech using x-vectors and neural waveform models [START_REF] Fang | Speaker Anonymization Using X-vector and Neural Waveform Models[END_REF]. The baseline system introduced in [3] aims at separating speaker identity and linguistic content from an input speech utterance. Assuming that those features are disentangled, an anonymized speech waveform can be generated after altering only the features that encode the speaker's identity. The anonymization system illustrated in Figure 1 can be decomposed into three groups of modules. Modules from the group A extract different features from the source signal: the fundamental frequency, the phonetic features encoding articulation of speech sounds (Phoneme Posterior-Grams (PPGs) [START_REF] Sun | Phonetic posteriorgrams for manyto-one voice conversion without parallel data training[END_REF]) and the speaker's x-vector. The module B derives a new pseudo-speaker identity. The x-vector from each source input speaker is compared to a pool of external x-vectors to select the 200 furthest vectors; 100 of them are randomly selected and averaged to create an anonymized pseudo-speaker x-vector identity. Finally, the module C synthesizes a speech waveform from the pseudo-speaker x-vector together with the original PPGs features and F0.

The Voice Conversion System

As an enhancement to this baseline, [START_REF] Champion | A Study of F0 Modification for X-Vector Based Speech Pseudonymization Across Gender[END_REF] proposed to modify the F0 values (cf. module D in Figure 1) using the F0 mean and variance statistics associated with each of the x-vector of the pool.

Design Choices for Anonymization

In the evaluation plan of the VoicePrivacy Challenge, all utterances of a given speaker should be converted to match a single target pseudo-speaker. This strategy, described as permanent in [START_REF] Srivastava | Evaluating voice conversion-based privacy protection against informed attackers[END_REF], ensures that a one-to-one mapping exists between the source speaker identity and the anonymized speaker identity. This requirement allows anonymized voices to be distinguishable from each other. This one-to-one mapping does not apply in-between speech anonymized by the service provider and speech anonymized by the attacker. Speech data anonymized by the service provider corresponds to the trial dataset, and speech available to the attacker corresponds to the enrollment dataset, see Section 3.1 for more detail. Figure 2a shows how the permanent strategy converts enrollment and trial speech to different anonymized pseudo-speakers.

To select the target pseudo-speaker identity, module B (from Figure 1) has many hyper-parameters that affect the selection mechanism. According to [START_REF] Champion | A Study of F0 Modification for X-Vector Based Speech Pseudonymization Across Gender[END_REF][START_REF] Srivastava | Privacy and utility of x-vector based speaker anonymization[END_REF][START_REF] Srivastava | Design choices for x-vector based speaker anonymization[END_REF], the best anonymization results are achieved by picking the pseudo-speaker in a dense region of the x-vector space, randomly targeting male or female gender pseudo-speaker, and modifying the F0 values of the input speech so that it matches the F0 statistics of the real speakers used to generate the pseudoidentity.

The VoicePrivacy challenge's protocol assumes that attackers have access to anonymized trial utterances and original enrollment utterances. During the challenge, two sets of tests are performed following black-box and grey-box attacker scenarios corresponding to situations where the enrollment utterances are original or have been anonymized. In the latter scenario, the attacker has partial knowledge of the system and is able to anonymize the enrollment utterances using the same anonymization system and permanent target selection strategy. The pseudo-speaker chosen for each of the enrollment speakers differs from the pseudo-speaker chosen for the trial speakers as the attacker does not have knowledge of the randomly selected speakers used to generate the pseudospeaker identity. As the voices of the same speakers once anonymized by the service provider (trial) and the attacker (enrollment) are different from each other, this leads to a rather good anonymization performance [START_REF] Tomashenko | Introducing the VoicePrivacy Initiative[END_REF].

Enrollment Trial Anonymized

With the permanent target selection strategy used in the challenge, anonymized voices remain distinguishable and all utterances from the same original speaker are anonymized with the same pseudo-speaker. This process is referred to as pseudonymization. Providing attackers the target's identity of each speaker in the permanent strategy evaluates the quality of the voice conversion system and the preservation of the voice distinctiveness [START_REF] Noé | Speech Pseudonymisation Assessment Using Voice Similarity Matrices[END_REF]. In this paper, we evaluate the privacy of the anonymization technique with the best attacker, that is using the constant selection strategy.

Experimental Setup

In this evaluation, we want to provide a comprehensive assessment of the voice conversion toolkit under a white-box scenario where the attacker has full knowledge about the system. We change the game between the attacker and the service provider to use the constant identity selection strategy defined in [START_REF] Srivastava | Evaluating voice conversion-based privacy protection against informed attackers[END_REF]. In contrast to the anonymization performed in the VoicePrivacy challenge, the constant strategy defines a single pseudo-speaker identity for all speakers in a given dataset. We extend this property to all speakers of the trial and the enrollment datasets so that all of them should have the same anonymized voice identity. We expect good anonymization performance as the voices of all speakers should appear to be spoken by a single identity. This breaks the one-to-one requirement of the challenge, speakers will not be distinguishable from each other. Still, we believe this assessment is complementary to the realistic attacker-based evaluation of the challenge. Figure 2 shows the differences in the target selection strategies between the VoicePrivacy strategy (permanent strategy), and the strategy chosen for this study (our constant strategy). Experiments are performed with different target speaker identities to provide averaged global results about the voice conversion toolkit, and detailed analysis of the target identity effect on multiple source speakers.

Dataset

All evaluation tasks for the experiments follow the conditions presented on the publicly available VoicePrivacy challenge1 . The triphone extractor has been trained on the train-clean-100 and train-other-500 subsets of LibriSpeech. The x-vector extractor has been trained on VoxCeleb-1,2. The speech synthesis system has been trained on the train-clean-100 subset of LibriTTS. Finally, the train-other-500 subset of LibriTTS has been used to create a pool of x-vector and F0 statistics. The evaluation dataset is built from LibriSpeech test-clean. Details about the number of speakers and utterances in the enrollment and trial dataset are reported in Table 1.

Utility and Privacy Metrics

To evaluate the performance of the system in both privacy (speaker's concealing capability) and utility (content intelligibility) two systems and metrics are used. To quantitatively evaluate the privacy, an x-vector-PLDA based Automatic Speaker Verification (ASV) architecture provided by the challenge organizers is used. The privacy protection is measured with the linkability metric: [START_REF] Gomez-Barrero | General framework to evaluate unlinkability in biometric template protection systems[END_REF] introduced two different measures that are calculated based on mated and non-mated likelihood score distributions. In this case, mated scores are computed comparing anonymized speech of the same user. Whereas non-mated scores are computed comparing anonymized speech of different users. The local measure D ↔ is the local score-wise measure depending upon the likelihood ratio between the mated and non-mated sample's score. The global linkability measure D sys ↔ is the average value of D ↔ over all mated scores. To obtain the linkability score for a given speaker, the average is taken from all mated scores of this specific speaker. Work in [START_REF] Maouche | A comparative study of speech anonymization metrics[END_REF] advocate the use of D sys ↔ as a robust privacy metric. The lower the D sys ↔ , the better the speakers are anonymized. As the Equal Error Rate (EER % ) measure is more often used in speaker verification, we present our result in terms of both EER % and D sys ↔ . The higher the EER % , the better the speakers are anonymized. For the utility, the pre-trained Automatic Speech Recognition (ASR) system provided by the challenge organizers is used to decode the anonymized speech and compute the Word Error Rate (WER % ). In this evaluation, the WER % measure is used to evaluate how the content is kept intelligible. The lower the WER % is, the more intelligible the anonymized speech is. Both ASR and ASV systems are trained on LibriSpeech train-clean-360 using Kaldi [START_REF] Povey | The Kaldi Speech Recognition Toolkit[END_REF].

Evaluation Methodology

In this experiment, we run the anonymization and evaluation on 40 real target speaker's identities that cover as best as possible the speaker space. Thus, to select the target speakers, we identify 20 female and 20 male clusters of x-vectors in the anonymization pool (LibriTTS train-other-500 ) using K-Means. We then pick the speaker x-vector that is the closest to the centroid of each cluster. The assessment of the anonymization performances will be done for each of those 40 target speaker identities. Real speaker identities are used instead of pseudospeaker identities derived from multiples speakers.

To evaluate the performances of the anonymization system, we perform the following procedure for the 40 selected target speaker identities. First, we convert all utterances of Librispeech test-clean (data corresponding to enrollment and trial) and Librispeech train-360 to the selected target speaker. Then, we train the ASV model on the anonymized Librispeech train-360 dataset. Lastly, we evaluate the privacy performances for each of the speakers of Librispeech testclean using the specially trained ASV model. As a result, we obtain one score for each trial speaker of Librispeech test-clean and target identities (that is a total of 29 × 40 scores). To evaluate the quality of the conversion process in terms of utility (linked to speech recognition performance), we use a pre-trained ASR model released for the VoicePrivacy Challenge. To study the effectiveness of the F0 anonymization (module D of Figure 1), we perform the anonymization process, and the associated evaluation, with and without the F0 transformation enabled.

Experimental Results

Global Results

Table 2 compares the anonymization performance on a global scale. The first line presents the linkability when no anonymization is performed (i.e., on original speech data), clean speech encapsulates the speaker's information to a high degree (D sys ↔ scores > 0.90). The second and third lines display the linkability when using the voice anonymization system without and with the F0 transformation. In contrast with the original speech results, the anonymized results come from 40 ASV tests, each using a different speaker identity. The mean and standard deviation values are calculated from the 40 evaluations. From the linkability score difference between original and Anon. lines of table 2 we can conclude that speakers are less linkable to their true identity after applying the x-vector base anonymization system. From the original data to the anonymized speech, linkability scores drop by at least 17%, meaning the anonymization system has some effectiveness. The comparison between the last two lines shows that modifying the F0 values does not help to remove speaker information from the speech signal, as shown by the standard deviation values. This means that the transformation applied was not strong enough to actually remove extra speaker information or that the ASV system is quite robust against such modification. The rather low standard deviation values across all scores show that there is no large variation when changing target speaker identity, this indicates that a given target speaker isn't more suited than another to anonymize the whole dataset. As there are not large scores differences between voice conversion without or with F0 values transformation, the following sections will only analyze the results of the anonymization system that includes the F0 linear transformation.

Detailed Analysis

Results on a single test speaker (speaker 5105) Fig. 3. Linkability scores (D sys ↔ ) obtained using the ASV retrained on anonymized data for each of the 40 target speakers (colored solid line) and on original speech (dotted black circle). Each axis corresponds to a target speaker. The anonymization system lowered the linkability scores, meaning better privacy is achieved.

We conducted a detailed analysis to check whether a specific target identity is more suited to anonymize one or more speakers of our test dataset. Figure 3 illustrate the visualization used for this study in the case of a single source speaker. The linkability D sys ↔ scores are computed for speech anonymized with 40 different x-vectors and F0 statistics.

The black-dot circle indicates the linkability of the speaker on clean original speech signal (note that the original speech does not depend on the target speakers, hence the circle). And, for each of the 40 target speakers, the linkability is presented by the colored solid line. After transforming the speech with 40 target speakers, we can observe that none of the 40 targets are significantly better to anonymize this speaker's voice. The variation between the anonymized linkability scores is more likely due to the difference between the ASV model training rather than a better target choice. This observation also applies to the 29 other speakers of our test dataset. It is also noteworthy that, out of the 40 target identities, 20 of them induce cross-gender voice conversion. Results for same-gender and cross-gender voice anonymization were found similar. ↔ scores of two groups to illustrate the common anonymization behavior: one for which the anonymization system did not remove speaker information, and the other for which the anonymization did remove some speaker information. For the poorly anonymized speakers, we observe that the distributions of linkability scores on anonymized speech (colored area) completely overlaps the distribution of linkability scores on original speech (grey area). The anonymization system did not remove any speaker information for half of our test speakers. On the other hand, for the well anonymized speakers, the anonymized speech and original speech scores distributions diverge. The difference is distinct, speaker information was removed by the anonymization system for the other half of our test speakers.

Utility Results

Across all experiments, we evaluated the utility for each 40 target identities. We performed the intelligibility test with the pre-trained ASR system of the VoiecPrivacy challenge. Figure 5 shows the utility scores after anonymization considering each of the 40 target identities. On original clean speech signal, the ASR systems score 4.15 WER % . When using the same model (trained on clean data) the overall WER % on the anonymized data reaches 7.30 WER % (average value over the 40 experiments). Retraining the ASR system on anonymized speech improves the WER % significantly [START_REF] Tomashenko | Introducing the VoicePrivacy Initiative[END_REF]. The very high utility loss yielded when using speaker 2487 is due to a generalization issue of the anonymization system (with happens with and without the F0 modification), in this case, nonintelligible speech was generated at the beginning of some segments. We conducted an additional test using 100 randomly selected target speaker identities, and were able to find 3 target speaker x-vectors that have the same behavior, with the worse case having a score of 59.37 WER % . Informal listening test reported that the original speech that produced the faulty x-vector contained singing segments. Further analysis needs to be conducted.

Conclusion

In this work, we evaluated and analyzed the x-vector-based speaker anonymization system proposed in [START_REF] Fang | Speaker Anonymization Using X-vector and Neural Waveform Models[END_REF] and F0 extension proposed in [START_REF] Champion | A Study of F0 Modification for X-Vector Based Speech Pseudonymization Across Gender[END_REF] under a white-box attack scenario approach and a constant target selection strategy. To assess the long-term performance of the voice conversion system and the impact of each of the hyper-parameters (i.e. the x-vector target identity, the F0 linear transformation, and the random gender selection), the use of a constant target selection strategy is beneficial. This target selection strategy allows the attacker to have complete knowledge about the system, under those circumstances models and hyper-parameters design choices can be compared as the best attacker will be used to evaluate the anonymization performance.

The experiments done in [START_REF] Champion | A Study of F0 Modification for X-Vector Based Speech Pseudonymization Across Gender[END_REF][START_REF] Srivastava | Design choices for x-vector based speaker anonymization[END_REF] showed that black and grey-box attackers can easily be fooled when enrollment speech and trial speech are anonymized in a different manner, i.e. by selecting the x-vector in different regions, applying the F0 linear transformation and random gender selection. On the contrary, we observed that neither the x-vector target, F0 transformation, or cross-gender conversion actually help to remove the speaker information from the speech signal. We showed that regardless of the hyper-parameters used, privacy protection stays the same. The detailed analysis showed that a given set of hyper-parameters does not help the anonymization system to better anonymize a given source speaker. Furthermore, we concluded that the anonymization system performance depends on the speaker to anonymize, half of our test speakers did not have their privacy improved.

We raise caution on the privacy evaluation procedure, as we've shown that system performance varies depending on the attacker's knowledge and ASV system used. In future work, we plan to evaluate the source of the speaker information leakage that occurs through the phonetic features (PPGs).

Fig. 1 .

 1 Fig. 1. The speaker anonymization pipeline. Modules A, B, and C are parts of the baseline model. Module D is an enhancement used to coherently alter the F0 values with respect to the selected pseudo-speaker identity.

Fig. 2 .

 2 Fig.2. Overview of target selection strategies. In the permanent strategy pseudospeakers are randomly selected, first for the trial dataset and then for the enrollment dataset. While our constant strategy, always targets the same pseudo-speaker.

Fig. 4 .

 4 Fig. 4. Mean and standard deviation D sys ↔ scores obtained for N speakers using retrained ASVs on anonymized data for each of the 40 target speakers (mean and standard deviation corresponding to the colored solid line and light area) and on original speech (dotted black circle and grey area). Each axis corresponds to a target speaker.

Figure 4

 4 Figure4shows the linkability D sys ↔ scores of two groups to illustrate the common anonymization behavior: one for which the anonymization system did not remove speaker information, and the other for which the anonymization did remove some speaker information. For the poorly anonymized speakers, we observe that the distributions of linkability scores on anonymized speech (colored area) completely overlaps the distribution of linkability scores on original speech (grey area). The anonymization system did not remove any speaker information for half of our test speakers. On the other hand, for the well anonymized speakers, the anonymized speech and original speech scores distributions diverge. The difference is distinct, speaker information was removed by the anonymization system for the other half of our test speakers.

Fig. 5 .

 5 Fig. 5. WER % scores obtained by the VoicePrivacy ASR evaluation systems for each of the 40 speakers and on original speech (dotted black line).

Table 1 .

 1 Statistics of the evaluation dataset[START_REF] Tomashenko | Introducing the VoicePrivacy Initiative[END_REF].

	Subset		Female Male Total
		Speakers in enrollment	16	13	29
	Librispeech	Speakers in trials	20	20	40
	test-clean	Enrollment utterances	254	184	438
		Trial utterances	734	762 1496

Table 2 .

 2 Linkability (D sys ↔ ) and EER% scores for original and anonymized speech. For the anonymized data, the mean and standard deviation values are calculated over the 40 experiments (i.e., one for each target speaker). Results on anonymized data are given without and with F0 transformation.

		Female speakers	Male speakers
		D sys ↔	EER%	D sys ↔	EER%
	Original	0.90	7.66	0.96	1.11
	Anon. without F0	0.72 ± 0.01	12.1 ± 0.6	0.77 ± 0.01	9.5 ± 0.6
	Anon. with F0	0.74 ± 0.01	11.6 ± 0.6	0.75 ± 0.01	10.6 ± 0.8

https://github.com/Voice-Privacy-Challenge

Acknowledgments. This work was supported in part by the French National Research Agency under project DEEP-PRIVACY (ANR-18-CE23-0018) and Région Grand Est. Experiments were carried out using the Grid'5000 testbed, supported by a scientific interest group hosted by Inria and including CNRS, RENATER and several Universities as well as other organizations.