The data of the present study reveal that the kinetic properties of GDH1 make feasible the reverse reaction under physiological conditions. For instance, the GDH reverse reaction is favored by its higher Vmax value (vs. forward reaction Vmax); that is, GDH1 has a higher catalytic capacity for its reverse reaction. The reverse GDH reaction is also thermodynamically favored in the presence of micromolar ammonium concentrations and physiological mitochondrial matrix Glu/2-OG (1–10) and NADPH/NADP+ (∼1) ratios, despite its high Km values for ammonium, which were above the physiological range of concentrations. In this last regard, it was here determined that cancer mitochondria actively produce ammonium from glutamine, in a reaction catalyzed by glutaminase, leading to higher mitochondrial matrix and extramitochondrial ammonium concentrations, which in turn are sufficient to drive the GDH reverse reaction. An alternative and supplementary source of ammonium might be AMP deamination in the cytosol, which is also enhanced in cancer cells (73). Thus, the emerging scenario for glutamate/glutamine metabolism in cancer mitochondria seems to privilege the conservation and further formation of glutamate as an N-carrier/donor, in which both glutamine and 2-OG are transformed into glutamate.

Interestingly, treatment with the so-called ammoniascavenging drugs (phenylacetate and phenylbutyrate, which in fact conjugate with glutamine to form phenylacetylglutamine and phenylbutyrylglutamine, which are excreted) arrests growth of prostate cancer, renal cancer, and leukemia cell lines (74, 75). Phenylbutyrate also decreases by 35 to 45% the size of tumors in rodents (76). However, phenylacetate has shown a negligible antitumor activity in clinical trials (77).

Total GDH activity in intact cancer cells was approximately one-third of the GDH1 activity determined in isolated hepatoma mitochondria. Likewise, it has also been estimated that the mitochondrial volume within a cell amounts up to ∼30% of total cellular volume. In consequence, the GDH activity determined in cells seemed to mostly correspond to that of the mitochondrial GDH1 isoform.

The in silico simulation of GDH1 activity with physiological concentrations of substrates and modulators, and using the MWC equation for exclusive binding, predicted an activity in the range of 1.1 to 3.3 nmol/min × mg (with 2 mM ADP) in isolated mitochondria. By considering that the mitochondrial fraction corresponds to 30% of cellular protein, the GDH activity scaled up to intact cells might oscillate between 0.33 and 0.99 nmol/min ∗ mg cell protein. This GDH activity range for the reverse reaction is well within the range of fluxes determined for biosynthesis of protein (2.5–8.8 nmol/min ∗ mg protein), glycogen (0.25–0.55 nmol/min ∗ mg protein), urea (2.4–28 nmol/min ∗ mg protein), and fatty acids (0.09–10.7 nmol/min ∗ mg protein), or it is even above those of cholesterol (0.014– 0.025 nmol/min ∗ mg protein) and nucleotides (0.1 nmol/min ∗ mg protein), in normal and tumor cells (78–83). Then, it seems thermodynamically and kinetically feasible that GDH may contribute to accelerate cancer cell proliferation by providing glutamate, through its reverse NH+ 4 fixing reaction.

Ammonium, at millimolar concentrations, induced increased growth rates of metastatic cancer cells, but not of non-cancer cells in which it was toxic. The kinetic properties of GDH, as well as the thermodynamically favorable GDH reverse reaction, when at least micromolar ammonium concentrations are present, support that the physiological GDH role in cancer cells is to catalyze the NH+ 4 fixation to promote proliferation. The MWC equation predicted, at physiological concentrations of substrates and modulators, a rate of ammonium assimilation catalyzed by tumor GDH completely compatible with the anabolic rates required for active cell proliferation.

### MATERIALS AND METHODS

#### Chemicals

Ammonium chloride, ADP, DTT, EDTA, GTP, glutamate, glutamine, 2-OG, 3-phosphoglycerate, L-leucine, NAD+, NADP+, NADPH, NADH, Triton X-100, MgCl2, MOPS, HEPES, Tris, imidazole, acrylamide, GDH (no. G2626), rabbit muscle phosphorylase kinase (no. P2014), and agarose were from Sigma Chem. Co. (St. Louis, MO, USA). Anti-GDH1/2 (no. sc-160383); anti-α-tubulin (no. sc-5286); antiacetylated lysine (no. ab190479); anti-P-Ser (Q5phospho-ser; Qiagen no.37430); and anti-P-Thr (Q7phospho-Thr; Qiagen no.37420) were purchased from Santa Cruz (sc) Biotechnology (Santa Cruz, CA, USA), Abcam (ab) (Cambridge, MA, USA), or Qiagen (Venlo, the Netherlands). Glyceraldehyde-3-phosphate dehydrogenase (GAPDH, no. 105686) and HK (no.<PHONE_NUMBER>1) were from Roche (Mannheim, Germany). Recombinant phosphoglycerate kinase (PGK) was from Entamoeba histolytica (84).

 All cancer and non-cancer cell lines used were purchased from ATCC and cultured in DMEM (Sigma-Aldrich) supplemented with 10% fetal bovine serum (Biowest, Nuaillé, France) and 10,000 U penicillin/streptomycin (Sigma-Aldrich) and placed under a humidified atmosphere of 5% CO2/95% air at 37◦C. Genotyping (INMEGEN, Tlalpan, Mexico city, Mexico) of the cancer cell lines showed >90% of the canonic allelic markers displayed in the ATCC original clones.

For 2-D cultures, 20 × 103 cells/well were grown in 96-well plates in the presence or absence of different ammonium chloride concentrations; the addition of NH4Cl pH 7.0 did not change the pH of the culture medium (DMEM + 25 mM glucose). Cell growth was followed by counting cellular density every 24 h during 7 to 8 days. Viability was determined by the trypan blue assay, which revealed <10% cellular death (54). The duplication time was determined by using the following equation: n = 1 [3.32(log NF−log NI)] (tF−t I ) , where NF representsthe number of cultured cells

at the end of the exponential growth phase; NI represents the number of cells at the beginning of the growth curve; tF is the final time at which cells were harvested, and tI is the initial culture time. The specific growth rate µ was calculated from the slope of a semilogarithmic plot of cell densities in the exponential growth phase vs. time (88).

For tridimensional (3-D) cultures, HeLa and MDA-MB-231 cells (2 × 104 cells/mL) were seeded in 2% (wt/vol) agarosecoated culture dishes in 5 mL DMEM (+ 25 mM glucose) with the indicated ammonium chloride concentrations. After 5 days, the culture medium was refreshed, and the MCTSs formed were placed under slow orbital shaking (20–50 rpm) at 37◦C and 95% air/5% CO2. Fresh culture medium with 25 mM glucose ± NH4Cl was replaced every 3 days, which helped to discard incompletely formed spheroids. The spheroid growth was determined at the indicated times by measuring MCTS diameter with a calibrated reticule (1/10 mm) in an inverted phase contrast microscope (Zeiss, Thornwood, NY, USA) (86).

### Isolation of Mitochondria

Tightly coupled mitochondria were isolated from fed-rat liver (RLM) and AS-30D cells (HepM) as described elsewhere (89, 90). Both mitochondrial preparations were subjected to further dilution in SHE buffer (250 mM sucrose, 10 mM HEPES, 1 mM EGTA, pH 7.3) and centrifugation (12,857 × g for 10 min at 4 ◦C); these steps were repeated thrice to minimize the presence of contaminating cytosolic proteins. The resulting mitochondrial fractions were resuspended at 30 to 80 mg protein/mL in SHE buffer with 1 mM PMSF, 1 mM EDTA, 5 mM DTT, and 10% glycerol, and stored at −70◦C until use for determination of enzyme activity and Western blotting. Animal manipulation was carried out in accordance with the recommendations stated by the Mexican Official Standard NOM-062-ZOO-1999 norm.

# GDH Activity

The GDH activity assay for the reverse reaction was determined at 37◦C in KME (120 mM KCl, 20 mM K-Mops, 1 mM K-EGTA) buffer at pH 7.2, or in KME buffer + 10 mM HEPES at pH 7.5, and in the presence of 0.8 mM MgCl2, 0.02% Triton X-100, 0 to 2.4 mM ADP, 0–0.75 mM 2-OG, 0.15–0.2 mM NADPH, and 0.07–0.1 mg protein for RLM or 0.2–0.3 mg protein for HepM; for the saturation curves with NADPH, 25 to 30% lower protein contents were used. The specific GDH reaction was started by adding 5–100 mM NH4Cl. Negligible spurious consumption of NADPH was attained under the described conditions; presence of significant levels of GDH ligands derived from the mitochondrial matrix can be discarded because of the large dilution of the mitochondrial preparation in the reaction assay (at least 40 times and usually 100 times or more). The decrease in the absorbance at 340 nm was followed for several minutes (∼10 min) to allow for full development of the pronounced enzyme hysteretic behavior, although the initial signal decrease (1–3 min) was taken to calculate the GDH rates. The protein concentration ranges used for each mitochondrial type were well within the linearity range of enzyme activity. To calculate the kinetic parameters, the experimental data were fitted by non-linear regression analysis to the Hill or MWC equation, using the Microcal Origin 5.0 software (OriginLab, Northampton, MA, USA).

## Western Blotting and Immunoprecipitation Assays

Mitochondria were solubilized in RIPA lysis buffer [phosphatebuffered saline 1× pH 7.2, 1% IGEPAL NP40, 0.1% sodium dodecyl sulfate (SDS), and 0.05% sodium deoxycholate] plus 1 mM of PMSF (phenyl methanesulfonyl fluoride) and one tablet of complete protease inhibitors cocktail (Roche) and subjected to SDS–polyacrylamide gel electrophoresis in 12.5% polyacrylamide gels. The proteins were immobilized on polyvinylidene fluoride membranes and immunoblotted with human anti-GDH (1:1000 dilution); specific proteins were revealed with peroxide-conjugated secondary antibodies (anti-goat, no. sc-2768; anti-rabbit, no. sc-2317; anti-mouse, no. sc-2005), followed by chemiluminescence detection as previously described (91). Covalent GDH modification was assessed by initially immunoprecipitating with the specific anti-GDH antibody followed by detection with antibodies anti–phospho-Ser, anti–phospho-Thr, and anti-acetylLys as previously described (27).

#### Determination of Metabolites

Freshly prepared mitochondria (10 mg protein/mL) were incubated in KME buffer + 2 mM K-phosphate at 37◦C under smooth orbital shaking with either 1 mM pyruvate + 2 mM malate or 4 mM glutamine + 1 mM pyruvate + 2 mM malate. After 10 min, aliquots were withdrawn, mixed with ice-cold KME buffer, and centrifuged at 17,000 × g for 1 min at 4◦C. The supernatant was mixed with ice-cold 3% (vol/vol) perchloric acid (PCA) in 1 mM EDTA and kept in ice. The mitochondrial pellet was resuspended in cold KME buffer and centrifuged at 17,000 × g for 1 min at 4◦C. This procedure was repeated once. The final mitochondrial pellet was mixed with ice cold 3% PCA/1 mM EDTA. The two fractions were neutralized with 3 M KOH/0.1 mM Tris and stored at −72◦C until use for determination of ammonium, 2OG, Glu, ADP, and ATP by standard enzymatic methods (92, 93).

The intramitochondrial GTP content was estimated from the difference between the content of ATP + GTP determined by assay with EhPGK (which can take either GTP or ATP as substrate, with 0-fold higher affinity for the first) and ATP content determined by assay with HK. It was assumed that HK does not use GTP as substrate. The stock solutions of GTP, ADP, 2-OG, NH+ 4 , and Glu were also routinely calibrated by standard

#### REFERENCES

enzymatic methods (92, 93). The GTP stock was prepared in presence of 1 mM EDTA, making it stable for several weeks. GTP in the stock solution was determined in a coupled enzymatic assay with EhPGK (2 U) and GAPDH (2 U) in presence of 5 mM MgCl2, 1 mM EDTA, 2 mM DTT, 0.15 mM NADH, and 2 mM 3 phosphoglycerate.

#### Statistical Data Analysis

The data represent the mean ± standard deviation (SD) of at least three independent cell preparations (n). For statistics between two experimental groups, Student ttest analysis was used (94). For statistics between three or more experimental groups, one-way analysis of variance (ANOVA)/post hoc Scheffé analysis was used (94, 95). For both, P < 0.05 was used as statistical significance criterion.

#### DATA AVAILABILITY STATEMENT

All datasets generated for this study are included in the article.

#### AUTHOR CONTRIBUTIONS

RM-S and ÁM-H: conceptualization. RM-S, ÁM-H, JG-P, SP-V, DR-C, and JP-F: investigation. RM-S and ÁM-H writing original draft preparation. RM-S, ÁM-H, ES, and SR-E: writing review and editing.

## FUNDING

This present work was partially supported by CONACyT-Mexico grants Nos. 239930 and 281428 (RM-S), A1-S-40481 (ÁM-H), 283144 (SR-E), and 282663 (ES).

structure. FEBS J. (2014) 281:5292–308. doi: 10.1111/febs. 13069

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Moreno-Sánchez, Marín-Hernández, Gallardo-Pérez, Pacheco-Velázquez, Robledo-Cadena, Padilla-Flores, Saavedra and Rodríguez-Enríquez. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Normal Hematopoetic Stem and Progenitor Cells Can Exhibit Metabolic Flexibility Similar to Cancer Cells

Marija Vlaski-Lafarge1,2 \*, Veronique Labat 1,2, Alexandra Brandy 1,2, Alice Refeyton1,2 , Pascale Duchez 1,2, Laura Rodriguez 1,2, Nyere Gibson1 , Philippe Brunet de la Grange1,2 and Zoran Ivanovic1,2

1 R&D Department, Etablissement Français du Sang Nouvelle Aquitaine, Bordeaux, France, 2 Inserm/U1035, University of Bordeaux, Bordeaux, France

#### Edited by:

Tuuli Käämbre, National Institute of Chemical Physics and Biophysics, Estonia

#### Reviewed by:

Stephen John Ralph, Griffith University, Australia Amilcare Barca, University of Salento, Italy

\*Correspondence: Marija Vlaski-Lafarge<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Cancer Metabolism, a section of the journal Frontiers in Oncology

Received: 29 February 2020 Accepted: 15 April 2020 Published: 12 May 2020

#### Citation:

Vlaski-Lafarge M, Labat V, Brandy A, Refeyton A, Duchez P, Rodriguez L, Gibson N, Brunet de la Grange P and Ivanovic Z (2020) Normal Hematopoetic Stem and Progenitor Cells Can Exhibit Metabolic Flexibility Similar to Cancer Cells. Front. Oncol. 10:713. doi: 10.3389/fonc.2020.00713 It is known that cancer stem cells (CSCs) with the largest proliferative capacity survive the anoxic and/or ischemic conditions present inside tumorous tissue. In this study we test whether normal stem cells can survive under the same conditions due to cancer cell-like metabolic adaptations. We cultivated a CD34+ population with a majority of hematopoietic progenitors, and a CD34+CD38lowCD133+CD90+CD45RA− population, highly enriched in hematopoietic stem cells (HSCs), under anoxic, anoxic/aglycemic ("ischemia-like"), or physiological conditions (3% O2). Results showed, despite a reduction in total cell fold expansion proportionate to the decrease in O2 concentration; CD34+ cells, aldehyde dehydrogenase-expressing primitive cells, and committed progenitors expanded, even in anoxia. Interestingly, under ischemia-like conditions, stem and CD34+ cell populations are maintained at day-0 level. Cell-cycle analysis further revealed an accumulation of cells in the G0/G1 phase in anoxia or anoxia/aglycemia, with a fraction of cells (∼40%) actively cycling (SG2M phases). Also stem cell analysis showed that in these conditions a long-term Scid Repopulating activity was equal to that found with 3% O2. In addition stem cells with the highest proliferative capacity were maintained in anoxia/aglycemia and in anoxia. The estimated ATP profile, active mitochondrial content, and succinate accumulation are indicative of anaerobic mitochondrial respiration in both HSCs and CD34+ progenitors under ischemia-like conditions. We demonstrate here that primitive hematopoietic cells show similar metabolic flexibility to CSCs, allowing them to survive a lack of O2 and O2/glucose. Our study reveals that this feature is not the consequence of malignant transformation, but an attribute of stemness.

Keywords: cancer stem cells, hematopoietic stem cells, metabolism, bioenergetics, mitochondrial respiration

# INTRODUCTION

The concept of cancer stem cells (CSCs) is well-established (1). CSCs display functions similar to normal stem cells, including self-renewal, differentiation potential, migration, a high proportion of cells in G0 phase, and drug resistance. Also, as normal stem cells, CSCs represent the small fraction of tumor cell population capable of self-regeneration as well as of propagation of the malignant cell

**44**

population giving rise to new tumors in tissues other than those from which the cancer originates (2).

In addition, functional, normal, and CSCs share several metabolic traits. Cancer cells show flexible, metabolic reprograming phenotypes which use an array of energetic fuels to enable survival, and proliferation under various conditions (3, 4). Proliferating tumor cells tend toward a glycolytic metabolism, even under aerobic conditions, in order to acquire the precursors necessary for increased biosynthesis (5). This high demand for glycolysis occurs without loss of mitochondrial activity (TCA cycle/respiration) (6). It should be stressed that, contrary to common assumption, the Warburg effect is not in fact specific to malignancy (2). A glycolytic metabolic profile has been shown to be an intrinsic property of hematopoietic stem cells (HSCs), related to stemness, enabling the cells to reside in areas with extremely low O2 (hematopoietic niche). But this metabolic profile is also maintained when HSCs are outside of the physiological niche (2). Indeed, HSCs from bone marrow or mobilized in peripheral blood exhibit a glycolytic metabolic profile even when cultured under non-physiologically high atmospheric air O2 concentrations (7, 8).

However, both HSCs and cancer cells possess active mitochondria that contribute to their maintenance, and retain the ability for oxidative phosphorylation (6, 9). Besides their role in energy production, mitochondria also play a role in recycling NAD+ and maintaining the glycolytic flow, generating intermediates for anabolic pathways, epigenetic control, and protection against oxidative stress. They also have the ability to change swiftly to OXPHOS in order to meet the high energy demands linked to differentiation toward mature somatic cells (10).

In cancer cells, targeted depletion of mitochondrial DNA reduces the tumorigenic potential of cancer cells in vitro and in vivo (11, 12). Also, quiescent and circulating cancer cells rely highly on mitochondrial respiration (11, 13). The tumorous cells' metabolic flexibility between a predominantly biosynthetic or bioenergetic purpose is a result of this apparent dichotomy (glycolysis/mitochondrial respiration). Recent data show that the cancer cells with the greatest stem cell potential are responsible for the durability of the disease and can survive under severe conditions, such as anoxia and/or ischemia, created inside the tumor tissue. This ability to survive also depends on the metabolic consequences of anaerobic mitochondrial respiration. The mechanism described includes the use of fumarate as the final electron acceptor (fumarate respiration or "disproportionation of malate") (14).

We thus want to test the hypothesis that HSCs, unlike mature cells, can survive under extreme conditions (anoxia and ischemia-like) due to metabolic adaptation, including anaerobic mitochondrial activity.

Our study, based on functional and metabolic analysis of HSCs, points to flexible energetic nature and high metabolic adaptability as being features common to stem cells, rather than specific to CSCs.

#### MATERIALS AND METHODS

#### Cell Sorting and Culture CD34+ Cell Isolation

Cord blood (CB) samples delivered (with the mother's approval) to the Cell Therapy Unit of the French Blood Institute, Bordeaux, that had been rejected for banking, were used for the experiments (In compliance with national French regulation, declared to the Ministry of Research: DC-2019-3720). CB CD34+ cells were isolated using an immunomagnetic technique (Miltenyi Biotec, Paris, France) and stored at −80◦C (15).

#### CD34+CD38lowCD133+CD90+CD45RA− Cell Sorting

CD34+ cells were thawed in 4% human serum albumin (Vialebex, LFB-biomedicament, Courtabeuf, France) and labeled with anti-CD34-BV421 (BD Biosciences, San Diego, CA, USA), anti-CD38-PC7, anti-CD133-PE (EXBIO, Vestec, Czech Republic), anti-CD90-APC, and anti-CD45RA-FITC antibodies (Pharmigen, San Diego, CA, USA). The desired cell population was selected using a FACS Aria III cytometer (BD Biosciences, San Diego, CA, USA) (16).

#### Cell Culture

CD34+ or CD34+CD38lowCD133+CD90+CD45RA− cells were plated in Stem-alpha A medium without glucose (Stem Alpha SA, Saint-Genis-l'Argentiere, France), supplemented with penicillin/streptomycin (PS) (100 ng/L), and cytokines: SCF 100 ng/mL, IL-3 0.5 ng/mL, TPO 10 ng/mL. Cells were incubated under physiological conditions (3% O2, with glucose 1 g/L), anoxia (0% O2, with glucose 1 g/L), or anoxia/aglycemia (AA, 0% O2, without glucose) for 5–7 days at 37◦C. The conditions with 3% O2 were obtained in an O2 and CO2 controller-culture chamber (PRO-OX and PRO-CO2, Biospherix, NY) (15). Anoxia was achieved using a hermetically sealed modular incubator chamber (Billups-Rothenberg, CA) in which ambient air was replaced with a mixture of 95% nitrogen and 5% CO2 (Air Liquide, Paris, France). At the end of the incubation period, cell expansion was estimated by cell counting.

#### Apoptosis Assay

Apoptosis was detected with an Annexin V-FITC kit (Beckman Coulter, Carlsbad, CA, USA) according to the manufacturer's protocol. Briefly, 105 cells from each of the experimental conditions were stained with Annexin V-FITC solution (AnnV) and propidium iodide (PI, 250µg/mL) for 15 min at 4◦C in the dark, washed in phosphate buffer saline (PBS), and analyzed with a flow cytometer (BD Bioscience, FACS Canto II) (17). This technique allow to detect: unlabelled viable cell subpopulation (AnnV−/ PI−); early apoptotic cell subpopulation that have

**Abbreviations:** AA, anoxia/aglycemia; ALDH, aldehyde dehydrogenase; Ann/PI, annexin/propidum iodide; ATP, adenosine triphosphate; CB, cord blood; CFC, colony forming cell; CSCs, cancer stem cells; IL-3, interleukin-3; HPCs, hematopoietic progenitor cells; HSCs, hematopoetic stem cells; MFI, Mean fluorescence intensity; MTG, Mitotracker green; NAD, nicotinamide adenine dinucleotide; SCF, stem cell factor; TCA, cycle-tricarboxylic acid cycle; TPO, thrombopoietin.

bound only AnnV (Ann+/PI−); necrotic cell subpopulation (representing the cells in post-apoptosis necrosis or late apoptosis) that have both bound AnnV and have been labeled with PI (Ann+/PI+).

### Cell Cycle Analysis

For cell cycle analysis, 105 cells were washed with PBS, centrifuged at 43 g for 5 min at 4◦C, and the pellets were resuspended in 100 µl of PBS. Cells were then fixed with 900 µl of 70% cold ethanol (added dropwise), and incubated for 1 h at 4 ◦C. Cells were washed and resuspended in PBS with 0.2 mg/mL of bovine RNase A and incubated for 1 h at 37◦C in the dark. PI (10µg/mL) was added, and the analysis was performed using flow cytometry (Bioscience, FACS Canto II) (17). The percentage of cells in each of the different cell cycle phases (G0/G1, S, and G2/M) was calculated from the linear graph on which cell counts were plotted relative to cell DNA content. The reagents were provided by Sigma Aldrich.

#### CFC Assay

The committed hematopoietic progenitors', colony-forming cell (CFC), including colony-forming unit granulocyte, monocyte (CFU-GM), burst-forming unit erythroid (BFU-E), colonyforming unit granulocyte, erythrocyte, monocyte, megakaryocyte (CFU-GEMM) were assayed as described previously (18). Cells (250 cells/mL) were seeded in cytokine-supplemented methylcellulose in a 24-well-plate (MethoCult H4034 Optimum, Stem Cell Technologies, Canada). After 15 days of incubation, CFCs were counted using an inverted microscope.

#### Aldehyde Dehydrogenase (ALDH) Activity

ALDH labeling was undertaken using an Aldefluor reagent (ALDF) (Stem Cell Technologies, Canada) according to the manufacturer's instructions. Activated ALDF substrate was rapidly added to a suspension of 105 cells in 100 µL of ALDF assay buffer and incubated for 30 min at 37◦C in the dark. As a negative control, an aliquot of ALDF-stained cells was incubated with the ALDH inhibitor diethylaminobenzaldehyde. Cells were washed, resuspended in 200 µL of assay buffer, and analyzed with a flow cytometer (BD Bioscience, FACS Canto II) (15).

### Proliferative, Clonogenic, and Differentiation Potential Evaluation by the Single-Cell Culture Method

The method was performed as it was previously published (16, 19).

#### Proliferative Capacity

Single cells selected from each of the experimental conditions were assayed into individual wells of 96-well-plates. Each wellcontained 200 µl of the Stem alpha A medium, supplemented with glucose (1 g/l) and cytokines (see above). Plates were incubated at 20% O2 and 5% CO2 for 14 days at 37◦C. The entire cell content produced in the primary culture from one individual cell was reseeded into 24-well-plates under the same culture conditions. Secondary culture cell content was re-evaluated at Day-28. Clone categories were established according to the number of cells produced: (C1 = 0; C2 = 1,000–4,000; C3 = 5,000–10,000; C4 = 13,500–14,000; C5 = 15,000–15,500 cells).

#### Clonogenic Capacity

Methylcellulose colony formation was assessed by sorting single cells from the different experimental conditions into individual wells of a 96-well-plate, containing 100 µl of methylcellulose (MethoCult H4034). The plates were incubated at 20% O2 and 5% CO2 for 15 days at 37◦C. The colonies from the committed progenitors were then counted. Each colony was harvested, and replated into an individual well of a 24-well-plate containing methylcellulose (250 µl). The plates were incubated for 14 days at 37◦C secondary colony formation was then assessed.

#### Differentiation Potential

For in vitro differentiation assays, cells from each of the experimental conditions were incubated for 14 days in the same manner as described for the proliferative capacity analysis. 24 well-plates had been seeded with murine stromal cells (MS5) in a αMEM medium (Gibco, Thermo Fisher, Langenselbold, Germany) with 10% fetal calf serum and PS (100 ng/L). At the end of the incubation period in liquid culture, hematopoietic cells were co-cultivated on MS5 for 30 days with a complete RPMI medium (Thermo Fisher, Langenselbold, Germany, with SCF 100 ng/mL, IL-3 0.5 ng/mL, G-CSF 100 ng/mL, TPO 10 ng/mL, 10% fetal calf serum, and PS) at 37◦C. At the end of the incubation period, hematopoietic cells from each well were harvested and labeled at 4◦C for 20 min in the dark with anti-CD19-PE, anti-CD33-APC (BD, Biosciences, San Diego, CA, USA), and anti-CD45-FITC antibodies (IOTest, Beckman Coulter, Carlsbad, CA, USA), and analyzed with a flow cytometer.

#### Scid Repopulating Cells (SRC) Assay

All experiments involving animals were performed in compliance with French regulation (License No: 3306002). From each of the experimental conditions, the equivalent of 300 Day-0 CD34+CD38lowCD133+CD90+CD45RA− cells at Day-7 were injected into the retro-orbital vein of 6–10-week-old NOD-Shi-Scid/IL-2Rgnull (NOG) mice (animal-keeping facility, University of Bordeaux, France). The mice had been prepared using an intraperitoneal injection of Busulfan 25 mg/kg (Busilvex, Pierre Fabre, Boulogne, France) (20). Positive control mice (injected with 300 Day-0 CD34+CD38lowCD133+CD90+CD45RAcells) and negative control mice (non-injected) were included. After 12 weeks, animals were euthanized and their femora were extracted. The femoral bone marrow was flushed with 1 ml of RPMI medium (Gibco, Thermo Fisher, Langenselbold, Germany) supplemented with 4% human serum albumin. The cells contained in 100 µl of this cell suspension were stained with anti-human antibodies: CD45-FITC, CD19-PE, and CD33-APC, for 20 min at 4◦C in the dark, washed with PBS and analyzed on a FACS Canto II (21). The positivity threshold for human CD45, CD33, CD19 chimerism was >0.1% of analyzed cells.

#### ATP Content

ATP levels were quantified using the ATP Bioluminescence Assay Kit HS II kit (Roche, Switzerland) in accordance with the manufacturer's recommendations, as it was previously published (15). A total of 103 cells per well were used in a 96-wellplate. Luminescence, directly proportional to the concentration of ATP, was detected using a luminometer at α = 562 nm (Promega GloMax). In order to determine the total cellular and mitochondrial ATP production, cells were incubated for 10 min in the absence of or in the presence of inhibitors of the mitochondrial complexes I and III, rotenone, and antimycin (1µM), respectively. These inhibitors were added simultaneously in order to curb electron flow through the mitochondrial electron transport chain, and so prevent generation of the proton motive force enabling ATP production by ATP synthase. The proportion of cellular ATP produced by mitochondria was calculated using the decrease in total ATP detected in the presence of these inhibitors.

## Mitochondrial Content

Mitochondria were detected using mitochondrial-selective fluorescent labeling with MitoTracker Green, according to the manufacturer's instructions (Molecular Probes). A total of 104 cells were treated with Mitotracker green (100 nM) for 20 min at 37◦C in the dark, then washed in PBS and analyzed using flow cytometry as previously published (17).

#### Succinate Content

The succinate that had accumulated during cell culture was detected in the culture supernatant at the end of the incubation period according to the manufacturer's instructions (Succinate assay kit, Abcam, UK). Cell suspensions were harvested, washed and resuspended in 100 µl of ice-cold succinate assay buffer. The suspensions were centrifuged, and the collected supernatants were filtered using a 10 kDa spin filter. Fifty microliter of each sample or standard dilution were mixed with the same volume of the reaction mix or background control mix and incubated for 30 min at 37◦C. The absorbance intensity was measured at 450 nm using a microplate reader (Evolis, Biorad). Each value was adjusted with the background control, in order to eliminate any non-specific absorbance that may have resulted from the possible presence of reduced nicotinamide adenine dinucleotide (NADH). Succinate concentration was then determined based on the standard curve.

#### Statistical Analysis

The Wilcoxon-Mann–Whitney paired comparison test was used to examine the significance of the difference between the various experimental conditions (p < 0.05, p < 0.01, and p < 0.001 were considered to be statistically significant).

# RESULTS

## Hematopoietic Stem and Progenitor Cell Survival in the Anoxia and AA

In order to test our hypothesis that primitive hematopoietic cells can survive under conditions commonly found in tumor tissue, we assayed both a total CD34+ population (CD34+) with a majority of hematopoietic progenitors (HPCs) and a rare minority of stem cells and a selected CD34+CD38lowCD133+CD90+CD45RA− population highly enriched in hematopoietic stem cells (HSCs, "stem") under anoxic, anoxic/aglycemic (ischemia like, "AA"), or physiological conditions (3% O2) for seven days.

Based on the difference in cell numbers between Day-0 and post-incubation, the results showed that the entire cell population survived under AA conditions, in both the stem and CD34+ total population, with slight expansion in anoxia (**Figure 1A**). We decided to investigate whether this property was associated with the functional characteristics of hematopoietic cells within the heterogeneous CD34+ population. Primitive hematopoietic cells expressing ALDH, as well as committed progenitors incubated in anoxia, yielded a significant level of amplification compared to Day-0. The maintenance in number of both cell populations under AA conditions is indicative of metabolic adaptation to glucose and O2 shortage (**Figure 1B**). As expected, these conditions yielded a significantly lower number of cells than physiological conditions (3% O2), which allow optimal cell expansion (**Figures 1A,B**). Cellular viability was estimated using Annexin V/Propidium iodide labeling (Ann/PI). Similar percentage of apoptotic cells (including the subpopulation expressing Ann+/PI−) or necrotic cells (subpopulation expressing Ann+/PI+). was detected in both stem and CD34+ cells, under all conditions (**Figure 1C**). We further analyzed the cell cycle phase distribution with PI staining (**Figure 1D**). When incubated under restricted conditions, there was a significant accumulation of cells in the non-dividing G0/G1 phase of the cell cycle, compared to physiological conditions. However, a fraction (∼40%) of the cell population was still actively proliferating (S and G2/M phases) in AA and anoxia (**Figure 1D**). This distribution could be responsible for the cultures' maintenance and/or slight expansion in the absence of O2 with/without glucose, allowing for a ∼20% apoptosis rate. The observed survival of primitive hematopoietic cells, irrespective of the conditions (anoxia, AA) indicates their flexible metabolic nature.

# Stem Cell Functions Are Maintained in vitro in Anoxia and AA

The population enriched in stem cells was analyzed by single cell assay in order to detect stem cell traits—self-renewal, proliferation, and multipotency—in vitro at an individual cell level.

In order to estimate the cell's proliferative capacity, we counted the number of cells produced in a secondary culture, having replated the cells descending from a single cell (seeded in a primary liquid culture) (**Figure 2A**). This secondary culture allowed us to detect both the total number of cells per well total progeny of the initial single cell—and the proportion of clones produced by CD34+ cells in the primary culture. They were then sorted into five categories (see above, Material and methods). The more primitive the cell, the greater its progeny in the secondary culture, due to a higher proliferative potential. Our results showed that the cells producing the most proliferative clones (categories 4 and 5) were present only under AA conditions (**Figure 2A**). Using an approach based on

Day-0 (D0). (B) Hematopoietic progenitor amplification. The average fold expansion of committed progenitors (CFC) or aldehyde dehydrogenase (ALDH+)-expressing primitive progenitors within the total CD34+ population relative to D0 is represented with bars. (C) Apoptosis assessment with Ann/PI labeling. The average percentage of apoptotic (Ann+/PI−) or necrotic cells (Ann+/PI+, i.e., cells in post-apoptosis necrosis or late apoptosis) detected amongst stem and CD34+ cells, is represented with bars. (D) Cell cycle analysis. Distribution of the cultivated "stem" cells in G0/G1, S, and G2/M phases of the cell cycle are represented by the average percentage shown with bars. The data are presented using a mean ±SD format over at least six experiments. Asterisks indicate a statistically significant difference between experimental conditions at \*p < 0.05, \*\*p < 0.01, or \*\*\*p<0.001, Wilcoxon-Mann–Whitney test. Ann, Annexin; PI, Propidium iodide.

methylcellulose culture, we found that the number of individual cells giving primary colonies (plating efficiency) was the highest under AA conditions (**Figure 2B**, Primary colonies). All cells from the individual cell-derived colonies (each primary culture well) were harvested, dissociated, and plated in individual wells in the secondary methylcellulose culture in order to assess replating efficiency (in vitro surrogate for "self-renewal"). Secondary colonies only grew from those primary colonies which contained self-renewed primitive progenitors. Replating efficiency was observed under all conditions, but the highest proportion of initially seeded single cells able to produce colonies in secondary culture was detected under AA conditions (**Figure 2B**, Secondary colonies). We then tested if these primary colonies could undergo myeloid or lymphoid lineage differentiation on a mesenchymal stroma layer, proving their multipotency. For this, we ascertained the percentage of human CD45+ cells (a panhematopoietic cell marker) expressing markers of the myeloid (CD33+) or lymphoid (CD19+) lineage differentiation. The proportions detected were equal under all culture conditions (**Supplementary Figure 1**). The results indicate that the basic stem cell functions of self-renewal and multipotency are not comprised by incubation in anoxia or AA.

### Long-Term in vivo Hematopoietic Reconstitution Upon Transplantation of the Cells Cultivated in Anoxia and AA

When assaying stem cells, the most effective method is to track their ability to reconstitute haematopoiesis in immunosuppressed mice 12–16 weeks after transplantation (22, 23). We analyzed the presence of the human cell marker CD45 12 weeks after xeno-transplantation of NOG mice. We found significant human cell engraftment in the mice's bone marrow (**Figure 3**, upper panel). Graft efficiency was defined as the number of mice testing positive for human CD45+ cells relative to the total number of mice injected.

according to the number of cells produced: (C1 = 0; C2 = 1,000–4,000; C3 = 5,000–10,000; C4 = 13,500–14,000; C5 = 15,000–15,500 cells). The data are shown with bars representing the percentage of total identified individual cell clones according to size (B) Clonogenic potential. Methylcellulose colony formation was assayed by sorting single cells from the various experimental conditions into individual wells. Primary colonies were then enumerated, replated individually in methylcellulose-containing wells and the secondary colonies scored. The results are displayed with bars representing the percentage of total identified individual cell cultures giving rise to primary colonies or secondary colonies.

antibodies and the level of human CD45 chimerism was assimilated to the amount of CD45+ cells in the mouse bone marrow. The data are displayed using circles, with each mouse being represented by one circle. Median values of CD45 chimerism are indicated by dashed lines (upper panel). Human myeloid and lymphoid cell differentiation was estimated with the level of expression of human CD45+CD33+ and CD45+CD19+ markers, respectively, in mouse bone marrow. The average percentage of human CD19 and CD33 expression in the human CD45+ population are presented in the pie chart (lower panel).

This ratio was equal for all experimental conditions (**Figure 3**, upper panel). The mean percentage of CD45+ cells—level of CD45 chimerism—was consistent in AA and anoxia as well as under physiological conditions. These results indicate a long-term ability maintained by the stem cell population, throughout incubation, for hematopoietic reconstruction, a trait attributable to the most primitive HSCs. CD45+CD33+ and CD45+CD19+ markers were then used to detect human myeloid or lymphoid differentiation, respectively (**Figure 3**, pie chart). This property was again detected under all conditions. The ratio of CD45+CD33+ to CD45+CD19+ cell subpopulations indicated that cells incubated in AA tend toward lymphoid lineage more than in anoxia and 3% O2 (**Figure 3**, pie chart).

### ATP Production, Active Mitochondrial, and Succinate Content in Hematopoietic Stem and Progenitor Cells in Anoxia and AA

In order to reveal the specific bioenergetic profile enabling hematopoietic cell survival without O2 or glucose, we analyzed the cellular ATP content (**Figure 4A**). Firstly, this showed a significant decrease in the total level of ATP in anoxia and AA compared to 3% O2, indicating a decrease in cellular ATP production. After simultaneous introduction of inhibitors of mitochondrial complexes I and III (rotenone and antimycin, respectively), the decrease in total ATP indicated the fraction of ATP produced by mitochondria. We found that most of the ATP in AA is produced by mitochondria; apart from the observation that anaerobic mitochondrial ATP production is active in AA, the simultaneous addition of inhibitors prevented us from distinguishing the specific effect of either complex (**Figure 4A**). This phenomenon was observed in both the stem and total CD34+ cell populations. To see whether these changes were associated with a difference in mitochondrial mass content, we labeled the cells with Mitotracker green at the end of the incubation period. This is a compound which binds to active polarized mitochondria, indicating cellular mitochondrial mass (24). We found a similar quantity of active mitochondria per cell under all conditions, amongst stem cells as well as the total CD34+ population (**Figure 4B**). This would suggest that mitochondrial content was not affected by the absence of O2 or glucose. Furthermore, compared to HSCs, the mitochondrial content in CD34+ cells was significantly higher under all conditions, indicating that in terms of bioenergetics, progenitor cells are more dependent on mitochondrial respiration than stem cells (**Figure 4B**).

In a recent publication, Tomitsuka et al. described how cancer cells can survive in ischemia where anaerobic mitochondrial fumarate respiration is activated (25). Using this fumarate as the final electron acceptor, then it is reduced into succinate that accumulates during culture. To test if, under our AA conditions, anaerobic mitochondrial respiration works in the same manner as in cancer cells, we measured the level of succinate in culture supernatants. The results show that the succinate content in AA supernatant is significantly higher compared to 3% O2 and anoxia (**Figure 4C**). These results point clearly to succinate accumulation under ischemia-like conditions and suggest the activation of fumarate respiration as an energetic pathway in HSCs/HPCs under these circumstances. Interestingly, this was detected in stem and CD34+ cells, indicating that HSCs as well HPCs can exhibit metabolic adaptions to survive in ischemia-like conditions and activate anaerobic mitochondrial respiration.

#### DISCUSSION

Our study demonstrates that HSCs/HPCs are capable of maintaining their functional traits, high proliferative capacity, and multipotency in the absence of O2 and/or glucose. Although cell numbers were significantly reduced in comparison with physiological conditions, a significant fraction of surviving cells was actively cycling independent of O2 and/or glucose omission (**Figure 1**). Moreover, primitive CB progenitors and stem cells (ALDH+), as well as committed progenitors, were even seen to multiply despite the absence of O2, indicating an oxygenindependent mechanism, which is arrested by glucose shortage. This is consistent with data showing a link between glucose import and cell proliferation in normal as well as cancer cells, in order to provide the carbon intermediates for biosynthesis (4, 26).

Using our method, the greatest capacity to adapt was detected in the stem cell population, wherein SRC (Scid repopulating cell) activity was equivalent to that which was detected under

optimal physiological conditions (**Figure 3**). Notably, under ischemia-like conditions, we identified the cell subpopulation with the highest proliferative capacity, indicating an association between high metabolic robustness and the most primitive of cells.

Various articles describe how O2 is a functional regulator of HSCs/HPCs. Our results are consistent with and could indeed extend, those showing that although low O2 concentration, close to that found in bone marrow stem cell niches (0.1%), induced the return of half of the CB CD34+ cells or murine hematopoietic progenitor non-leukemic factor-depending cell Paternsen (FDCP) mix-cell line to G0 phase, it also selected the small proportion of self-renewing cells in the proliferating phase of cycle, without impairing their functional capacity, SRC activity, or clonogenicity (27, 28). Further, a 1% O2 concentration enables HSC enrichment as well as primitive erythroid progenitors within CB CD34+ cell population (29– 31). In addition, our study confirmed that well-adapted physiologically-relevant low O2 concentration (3%) allows simultaneous HSC maintenance and committed progenitor expansion (18).

These data reflect the behavior of HSCs/HPCs in a physiological environment. Adult or neonatal primitive hematopoietic cells reside in low oxygen areas and develop within a 1–4% gradient of O2 (32, 33). Furthermore, as has been shown, most primitive HSCs reside in areas with very low blood perfusion, implying a limited supply not only of O2 but also of blood-born nutrients (34), i.e., an ischemia-like environment is common to HSCs. In the niche, HSCs are in a quiescent phase, and are occasionally recruited into the cell cycle (35, 36). They must also remain capacity for rapid proliferation in response to extrinsic cues, indicating great metabolic plasticity which enables energetic reprogramming on the basis of various functional demands (2).

These properties are in common to cancer cells. While cell growth is markedly reduced under conditions of very low O2 levels, cancer cells (leukemic cell culture) are capable of expanding significantly compared to Day-0 (37).  Also, severe hypoxia selects ex vivo a cell subset with stem cell potential in a population of myelodysplastic syndrome bone marrow cells (38). The cells that survive under these conditions have been shown to be the leukemic stem cells which are potentially responsible for the disease relapsing (39). We have demonstrated here for CB HSCs/HPCs, as has been shown for cancer cells, that expansion is possible at a low oxygen level until glucose is no longer available in the culture medium. In summary, these data indicate that primitive hematopoietic cells, as well as cancer progenitor and stem cells, adapt to survive anoxia and ischemia, conditions often found in cancerous tissue.

Furthermore, our results show that under ischemia-like conditions, primitive hematopoietic cell mitochondria remain functional, and use anaerobic ATP synthesis in order to sustain cellular homeostasis (**Figure 4**). Recently, evidence has shown fumarate respiration to be an anaerobic energetic pathway utilized by cancer cells in ischemic tumor tissue. In this instance, fumarate is utilized as the final electron acceptor, and fumarate reduction is coupled with an anaerobically-functioning electron transport chain in which electrons are transferred from NADH to fumarate via the complex I, ubiquinone, and a reverse reaction of the complex II (fumarate reductase), resulting in succinate formation. Only complex I functions as a proton pump, generating a proton gradient that drives ATP synthesis (25).

The accumulation of succinate we detected suggests that primitive hematopoietic cells activate fumarate respiration under ischemia-like conditions (**Figure 4**), meaning that HSCs/HPCs could in fact adapt by using the same metabolic energetic solvating pathway as cancer cells. By introducing a fumarate reductase-specific inhibitor, and assessing HSC/HPC population maintenance, we were able to identify activation of the NADH fumarate reductase system. We observed that introducing pyrvinium pamoate (which inhibits NADH fumarate reductase), prevents mesenchymal stem cells surviving under ischemialike conditions, and triggers energetic failure (unpublished data, article in preparation). Based on these findings and the results presented in this article, we propose that this system could be activated under ischemia-like conditions in HSCs/HPCs.

It should be noted that when analyzing the metabolic pathway in anaerobic respiration, such analysis should include fatty acid β-oxidation (a known alternative energetic fuel in the face of a glucose shortage) as fatty acid β-oxidation yields reducing equivalents of nicotinamide adenine dinucleotide (NADH) (40). These could deliver electrons to the electron transport chain (complex I), thereby sustaining anaerobic mitochondrial ATP generation via fumarate respiration in an anoxic and aglycemic environment.

Our study provides evidence that primitive hematopoietic cells exhibit metabolic and energetic flexibility, notably the ability

#### REFERENCES

to shift between aerobic, or anaerobic energetic modes in order to adapt to various environmental conditions. These features, especially "fumarate respiration," were thus far considered to be specific to cancer cells, which is clearly not the case. We propose that since they are common to both, normal and cancer stem cells, these primitive metabolic features should be considered as markers of stemness.

Our work provides findings that could be important in the development of cell therapy procedures.

### DATA AVAILABILITY STATEMENT

All datasets generated for this study are included in the article/**Supplementary Material**.

#### AUTHOR CONTRIBUTIONS

VL, AB, AR, PD, and LR performed the experiments. PB provided intellectual input and helped with data analysis. NG edited the text and corrected the translation. ZI provided the original idea for the project. MV-L and ZI conceived the study and wrote the manuscript. MV-L supervised the experimental work and did the data analysis.

#### FUNDING

This study was supported by the Etablissement Français du Sang Nouvelle Aquitaine Bordeaux, regional research and development budget.

#### ACKNOWLEDGMENTS

Our thanks go to Mrs. Elisabeth Doutreloux-Volkmann (EFS Nouvelle Aquitaine, Bordeaux) and Ms. NG for language corrections.

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc. 2020.00713/full#supplementary-material

Supplementary Figure 1 | in vitro evaluation of the differentiation potential of individual CD34+CD38lowCD133+CD90+CD45RA− cells in single-cell culture. Single cells were selected from the various experimental conditions (AA, anoxia, or 3% O2), and plated into individual wells. Clones produced in primary culture from one individual cell were co-cultivated on a mesenchymal stromal layer for 30 days. Cells were then collected and assayed for myeloid (CD45+CD33+) or lymphoid differentiation (CD45+CD19+). Results are shown with bars representing the mean percentage of CD45+CD33+ or CD45+CD19+-expressing cells obtained per colony developed from one individual cell.

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Vlaski-Lafarge, Labat, Brandy, Refeyton, Duchez, Rodriguez, Gibson, Brunet de la Grange and Ivanovic. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Adenylate Kinase and Metabolic Signaling in Cancer Cells

Aleksandr Klepinin1 \*, Song Zhang2 , Ljudmila Klepinina1 , Egle Rebane-Klemm1 , Andre Terzic2 , Tuuli Kaambre1 and Petras Dzeja2 \*

*1 Laboratory of Chemical Biology, National Institute of Chemical Physics and Biophysics, Tallinn, Estonia, 2 Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States*

A hallmark of cancer cells is the ability to rewire their bioenergetics and metabolic signaling circuits to fuel their uncontrolled proliferation and metastasis. Adenylate kinase (AK) is the critical enzyme in the metabolic monitoring of cellular adenine nucleotide homeostasis. It also directs AK→ AMP→ AMPK signaling controlling cell cycle and proliferation, and ATP energy transfer from mitochondria to distribute energy among cellular processes. The significance of AK isoform network in the regulation of a variety of cellular processes, which include cell differentiation and motility, is rapidly growing. Adenylate kinase 2 (AK2) isoform, localized in intermembrane and intra-cristae space, is vital for mitochondria nucleotide exchange and ATP export. AK2 deficiency disrupts cell energetics, causes severe human diseases, and is embryonically lethal in mice, signifying the importance of catalyzed phosphotransfer in cellular energetics. Suppression of AK phosphotransfer and AMP generation in cancer cells and consequently signaling through AMPK could be an important factor in the initiation of cancerous transformation, unleashing uncontrolled cell cycle and growth. Evidence also builds up that shift in AK isoforms is used later by cancer cells for rewiring energy metabolism to support their high proliferation activity and tumor progression. As cell motility is an energy-consuming process, positioning of AK isoforms to increased energy consumption sites could be an essential factor to incline cancer cells to metastases. In this review, we summarize recent advances in studies of the significance of AK isoforms involved in cancer cell metabolism, metabolic signaling, metastatic potential, and a therapeutic target.

#### Keywords: adenylate kinase, energy metabolism, phosphotransfer, mitochondria, cancer

### INTRODUCTION

The significance of metabolism and metabolic signaling in human diseases is rapidly growing. New features and molecular players that are vital for cell homeostasis and function are being uncovered. Well-organized high-energy phosphoryl transfer systems are required to mediate intracellular communication between ATP-consuming and ATP-producing cellular compartments and thus to maintain normal growth and development of the cell (1–5). The main components of the cellular phosphotransfer system are AK, creatine kinase (CK), and glycolytic networks (1, 2). The significance of organized phosphotransfer was demonstrated by genetic manipulations in animal models, cellular systems, and alterations or mutations in separate phosphotransfer enzymes, which are associated with human diseases (6–16). Studies on Drosophila and mice model demonstrate that deletion of adenylate kinase 2 (AK2) is embryonically lethal, signifying

#### Edited by:

*Stefano Falone, University of L'Aquila, Italy*

#### Reviewed by:

*Daria Capece, Imperial College London, United Kingdom Paul Dent, Virginia Commonwealth University, United States Elisabetta Benedetti, University of L'Aquila, Italy*

\*Correspondence:

*Aleksandr Klepinin<EMAIL_ADDRESS>Petras Dzeja<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Cancer Metabolism, a section of the journal Frontiers in Oncology*

Received: *15 February 2020* Accepted: *08 April 2020* Published: *19 May 2020*

#### Citation:

*Klepinin A, Zhang S, Klepinina L, Rebane-Klemm E, Terzic A, Kaambre T and Dzeja P (2020) Adenylate Kinase and Metabolic Signaling in Cancer Cells. Front. Oncol. 10:660. doi: 10.3389/fonc.2020.00660* the importance of AK phosphotransfer network in cell homeostasis (13, 17–19). In humans, mutations in the mitochondrial AK2 gene are associated with reticular dysgenesis characterized by immunodeficiency and sensorineural deafness, where processes of nucleotide signaling, cell differentiation, and motility are affected (15, 16, 20). So far, nine isoforms of adenylate kinase (AK1–AK9) and several subforms have been found and well characterized in mammalian cells (21). AK, which catalyzes reaction 2ADP↔AMP+ATP, is a recognized facilitator of AMP metabolic signaling, optimizing intracellular energetic communication, and local ATP supply (5, 22). Historically, the function of AK has been ascribed to de novo adenine nucleotide synthesis and cell energy economy through regulation of nucleotide ratios in different intracellular compartments and AMP-sensitive metabolic enzymes (14, 23, 24). The unique properties of AK lie on its ability to deliver γ- and β-phosphoryl groups of ATP, thereby doubling the ATP energetic potential. Moreover, the AK network provides an efficient mechanism for high-energy phosphoryl transport from mitochondria to ATP utilization sites (2). Evolutionary AK isoforms have been positioned to different subcellular compartments (21, 25). AK1, AK7, and AK8 are solely found in the cytosol; AK2, AK3, and AK4 are located in the mitochondria; and AK5 and AK9 can be found in either the cytosol or nucleus. Only AK1 and AK6 are known to be expressed in all tissues, whereas AK5 is expressed only in the brain (21). In the cytosol, the main isoform is AK1, which is predominantly expressed in high energy demand tissues such as the brain, heart, and skeletal muscles. AK2 is strategically located in the mitochondrial intermembrane and cristae space to facilitate high-energy phosphoryl exchange between mitochondria and cytosol (22). Two other AK isoforms, AK3 and AK4, are located in the mitochondrial matrix and are involved in the regulation of mitochondrial Krebs cycle and oxidative phosphorylation (OXPHOS), whereas AK5 and AK6 isoforms that are localized in the nucleus could serve to fulfill the energy needs of nuclear processes. In general, distinct intracellular localization and kinetic properties of AK isoforms favor energy support of specific cellular processes ranging from muscle contraction, electrical activity, cell motility, unfolded protein response, and mitochondrial/nuclear energetics (22). Importantly, reprogramming of energy metabolism has been proposed as one of the hallmarks of cancer (26), which is required to drive biosynthesis pathways necessary for rapid cell replication and proliferation. Cancer cells are believed to have a greater reliance on glycolytic phosphotransfer (27, 28). However, during the last decade, it was found that some tumors contain numerous mitochondria producing ATP predominantly via OXPHOS (29–31). The observed shift in hexokinase (HK) isoforms, upregulation of HK2 in cancer cells (32), indicates a closer integration of mitochondria with glycolytic phosphotransfer (see **Figure 1**). The association of HK2 with mitochondria and expression of pyruvate kinase PKM2 could promote effective yet uncontrolled energy distribution in cancer cells (27, 33, 34). Phosphotransfer enzymes such as CK and AK have been implicated in cancer cell proliferation (35, 36). However, it is not clear whether the redistribution of phosphotransfer enzymes, especially those which are localized in mitochondria, occurs during cancer formation. In this review, we focus on the significance of AK isoforms in the rewiring of cancer cell energy metabolism and AMP signaling. Specifically, we will overview how AK isoforms, localized in mitochondria (AK2 and AK4), and their main communication partners cytosolic AK (AK1 and AK6) are involved in cancer formation and metastasis.

#### ADENYLATE KINASE 2 AND MITOCHONDRIAL CREATINE KINASE INTERPLAY IN MALIGNANT TRANSFORMATION

AK2 and mitochondrial CK (CKmit) are major phosphotransfer enzymes located in the intermembrane/cristae space in mitochondria (3, 14, 22). AK2 and CKmit provide nucleotide exchange and metabolic signaling capacity, allowing mitochondria to export ATP and reception of cytosolic feedback signals such as ADP, AMP, and creatine (22, 23, 37). Phosphotransfer enzymes CK and AK have been implicated in cancer cell proliferation (35, 36). In general, CK is involved in cancerous transformation, as CKB (brain-type CK) is upregulated in a variety of cancers to support growing energy needs (38). The elevation of creatine metabolites was noted in drug-resistant cancer cells (39). However, in other cancer types, the downregulation of CKB and rewiring of metabolism may play an important role in colon cancer progression (40). Moreover, several studies have demonstrated that in colorectal cancer (41), breast cancer (42), neuroblastoma (35), prostate cancer (43), and sarcoma (36, 44), the CKmit was downregulated. The reduction of CKmit in cancer cells was associated with the upregulation of adenylate kinase AK2 isoform in intermembrane space (36, 41, 42, 45, 46) (see **Table 1**). There is evidence that the expression of AK2 on the cell surface could facilitate nucleotide signaling and metastatic potential (60). It was found that Ak2 gene expression is upregulated in the metastatic pancreatic endocrine neoplasms (60), indicating the significance of nucleotide metabolic signaling in cancer invasion (61). Moreover, increased expression of the Ak2 on the surface of the metastatic F9DR murine terato-carcinoma cells compared with the nonmetastatic F9B9 cell line has been demonstrated (53). Furthermore, a recent study showed that AK2 has prognostic and therapeutic potential in lung adenocarcinoma (55). The knockdown of AK2 suppressed proliferation, migration, and invasion, as well as induced apoptosis and autophagy in human lung adenocarcinoma cells.

AMP signaling and AMPK-mediated control of cellular katabolic and anabolic processes. Red color indicates the augmented pathways and gene expression in cancer cells. AMPD, AMP-deaminase; HK2, hexokinase 2; LDHA, lactate dehydrogenase A; ANT2, adenine nucleotide translocase 2; AMPK, AMP-activated protein kinase.

which may contribute to tumor development by preventing apoptosis (62). A recent study indicates that AK2 and FADD are crucial for caspase-10 activation upon metabolic stress, and this activation is independent of death receptors and extrinsic pathway of apoptosis (63). Moreover, the deletion of the Ak2 gene or exit AK2 from mitochondria during apoptosis disrupts nucleotide exchange between mitochondria and cytosol, causing hyperpolarization of mitochondria and reactive oxygen species (ROS) production (20). It was found that the presence of AK2 in mitochondrial cristae nanochannels is critical for ATP export (2, 22). There are evidence that the AK2 upregulation could be used by cancer cells to support energy supply to biosynthetic processes and cellular growth (18, 64). These results, as well as studies on CK and AK knockout mice, demonstrate remarkable plasticity of cellular energetics and phosphotransfer systems, which could be used in cancer cells to promote uncontrolled cell growth (9, 17, 22, 65).

## ADENYLATE KINASE MODULATE TUMOR CELL RESPONSE TO SURVIVE UNDER OXIDATIVE STRESS

The ability to conduct metabolic signaling and rewire metabolism is critical for cell survival. The AK4 isoform increased expression has been associated with a poor clinical outcome marker for lung cancer (56) as well as for glioma patients (57) (see **Table 1**). It was found that AK4 expression is under tight control of noncoding RNA. The AK4 is negatively regulated by micro-RNA miR-556-3p and positively by circular RNA of ATP-binding cassette (ABC) subfamily B member 10, circ-ABCB10 (66). In same study was demonstrated that downregulation of AK4 restrained lung cancer progression and sensitized lung cancer cells to cisplatin (66). Moreover, new data indicate that AK4 was shown to be involved in the radioresistance of esophageal cancer cells (67) and in chemoresistance of other cancers (68, 69). Previously, it was suggested that overexpression of AK4 could protect cells against oxidative stress (70). Other studies on HeLa (68) and HEK293 cells (71) demonstrated that tumor cells respond to a hypoxic condition by upregulating the AK4. However, in HepG2 cells (71), it was found that under oxidative stress, AK4 oppositely was downregulated. Although AK4 might be downregulated, it can still regulate OXPHOS because it retains the nucleotide-binding capability, and it can interact with the mitochondrial adenine nucleotide translocase (ANT) (70). It was found that knockout of AK4 increased cellular ATP through raised OXPHOS activity as well as mitochondrial number (68). Fujisawa and colleagues in 2016 have proposed that there are two mechanisms how AK4 regulates mitochondrial respiration in cancer cells (68). First, in cancer cells, AK4 interacts with ANT, which forms with voltage-dependent anion channel (VDAC) and HK transmembrane complex AK4-ANT-VADC-HK (see **Figure 1**). Under the hypoxic conditions, the TABLE 1 | Adenylate kinase isoforms in cancer.

complex supports the high glycolytic activity of cancer cells. It allows efficient ADP recycling between mitochondrial ATP synthesis and glucose phosphorylation by HK, which interacts with the mitochondrial outer membrane (MOM) (68, 72). In addition, in hepatoma cells (73), it was found that up to 50% of ATP is provided by intramembrane space located AK2 through VDAC binding to HK. Thus, AK2 may also be a member of the metabolic circuit channeling ADP–ATP in and out of mitochondria. The second mechanism is related to the fact that AK4 and AK3 have highly homologous sequences; therefore, they compete with each other for their substrates (68). According to this mechanism, AK4 interferes with AK3 action in supplying of the GDP required for the conversion of succinyl-CoA to succinate. That is why overexpression of AK4 in HeLa cells induces a decrease in Krebs cycle metabolites such as succinate, fumarate, and malate while glutamine and glutamate are increased. In several tumors, it

was shown that the predominate substrate for mitochondria is glutamine (74). However, further studies are needed to confirm the role of AK4 in mitochondria and Krebs cycle substrate metabolism.

# ADENYLATE KINASE NETWORK ROLE IN CANCER STEM CELLS

Traditional therapies against cancer, such as chemotherapy and radiotherapy, have many limitations. The limitation is due to systematic and local toxicity as well as drug resistance of small populations of tumor cells that have self-renewal properties. This small population of cells is called cancer stem cells (CSCs) (75). Previously, studies on CSC have shown that the cancer resistance for chemotherapy is related to increased OXPHOS in CSC. That is why a new generation of cancer chemotherapy could be targeted against pathways that interact with OXPHOS, such as the phosphotransfer system. Lamb and colleagues have shown on the breast cancer model that mitochondrial mass is a new biomarker of CSC, which have increased AK2 expression level (see **Table 1**) (52). In our previous study on neuroblastoma (NB) (46), which contains numerous CSC (76), and embryonal carcinoma cells (36), we also found that those cells have a high activity of AK2 (see **Table 1**). Moreover, another feature of CSC is that mitochondria are localized around the cell nucleus (77). There is evidence that AK2 can play an important role in communication between mitochondria and the nucleus (78). In another study using proteomic analysis of mouse teratocarcinoma cells (53), it was demonstrated that metastatic cancer cells have increased AK2 levels than have nonmetastatic cancer cells (see **Table 1**). As metastasis is related to cell motility, positioning of phosphotransfer enzymes to sites of increased energy consumption could be an important factor of tumor formation (59). The AK4 has been identified as a biomarker of metastasis in lung cancer (56, 79, 80). Overexpression of AK4 promoted lung cancer metastasis by enhancing hypoxiainducible factor HIF-1 stability and epithelial-to-mesenchymal transition under hypoxia (79). Moreover, it was found that aferin-A could suppress AK4-HIF-1a signaling and may serve as a novel anti-metastatic agent in lung cancer (79). The AK4 was also implicated in breast and bladder cancers, where it promoted cell proliferation and invasion (81, 82). Furthermore, it was demonstrated that another AK isoform AK6 could affect colorectal cancer migration and invasion (59). Although significant progress has been made, at this time, the complete role of the AK system in cancer metastasis is still unclear. Moreover, the other reason why CSCs are drug resistant relates to the increased expression of ABC transporters in those cells (83, 84). The model for ABC transporters was proposed (85), which is based on 31P solid-state NMR spectroscopy, suggesting that intrinsic ATPase is coupled with AK activity where AK participates in ATP exchange. It is known that cytosolic and membrane-associated AK can regulate the activity of another ABC protein—K-ATP channel (86, 87). Nevertheless, the exact role of AK in supporting adenylate charge and function of ABC transporters in CSC remains unknown yet. In this respect, the ABC transporters are not unique proteins that possess both ATPase and AK activities; there are other proteins like AK6 (58), also known as transcription factor TAF9, human coilin interacting nuclear ATPase protein (hCINAP), and highly conserved DNA repair complex Rad50 (88).

### PARADOXES REGARDING THE ROLE OF ADENYLATE KINASE IN TUMOR FORMATION

Cancer is a very complex and diverse phenomenon, including tissue specificity and different phases. Enzymatic changes can be different in the initial and advanced stages of tumor growth (89, 90). There are some contradictory studies where it was found that in lung cancer and hepatoma, AK was downregulated compared with that in normal tissue (47, 48) (see **Table 1**), whereas a recent study has shown that high expression of AK2 correlates with a worse prognosis for lung cancer patients (55) (see **Table 1**). In mouse embryonic fibroblasts, it was demonstrated that during their transformation into tumor cells, a significant reduction of AK1 expression occurs (50). More recently, the existence of AK1 additional gene product AK1β has been reported, and it is known that the AK1β expression level is regulated by p53 (91). In some cancers, p53 is mutated or suppressed. In this context, experiments on mouse embryonic fibroblast (50) have shown that during their transformation into tumor cells, augmentation of AK1 might be related to the downregulation of AK1β (see **Table 1**). Also, Kim et al. have postulated that AK2 is a negative regulator of tumor growth (54) (see **Table 1**). They demonstrated that in some cells, the AK2 localized not only in mitochondria but also in the nucleus, where it interacted with dual-specificity phosphatase 26 (DUSP26). This protein complex can dephosphorylate FADD leading to suppressed cell growth. They also suggested that AK2 downregulation was associated with breast cancer formation. In contrast, Speers and colleagues have found that AK2 is overexpressed in ERnegative breast cancer (51) (see **Table 1**). They proposed that AK2 should be a novel target for the treatment of ER-negative breast cancer. Indeed, a diterpene lactone neoandrographolide from extracts of the traditional medicinal herb Andrographis paniculata has been suggested to inhibit AK2 and have strong anticancer properties (92). Nevertheless, studies on human breast cancer and colorectal cancer demonstrated another AK isoform AK6 was overexpressed during cancer formation (58) (see **Table 1**). These data correlate with our previous studies on colorectal and breast cancers (41, 46) (see **Table 1**). It was also shown, that in both colon and breast tissues, AK6 is located not only in nuclear but also in the cytosol. However, only in cytosolic compartmentalized AK6 did expression level increase during tumorogenesis of breast and colorectal cancer cells (58) (see **Table 1**). They have found that AK6's main function is to regulate ribosome assembly and, consequently, protein expression and cancer cell growth. Recently, it was demonstrated that hCINAP or AK6 is a potent modulator of metabolic reprogramming by phosphorylating LDHA, a key player in cancer glycolysis (59) (see **Table 1**). Thus, AK isoform role can be different depending on cancer cell type and development stage.

#### ADENYLATE KINASE-MEDIATED AMP METABOLIC SIGNALING IN CANCER CELLS

In recent years, AK-mediated AMP signaling is emerging as one of the most versatile systems in the regulation of diverse cellular processes (5, 22, 93). Particularly, AMP signaling to AMP-activated protein kinase (AMPK) plays a critical role in adjusting ATP-producing and ATP-consuming processes (90, 94) (**Figure 1**). In several cancers, it has been demonstrated that AMPK, a master regulator of cellular energy homeostasis, possesses tumor suppressor function (95–97). In cells, AMPK activation/suppression is regulated via changes in cellular AMP levels. The principal activator of AMPK is the AK-catalyzed pathway, where it monitors cellular ATP–ADP balance and signals to AMPK by increased AMP cellular level. A recent study indicates that AK and AMPK cooperate to maintain cellular ATP levels (98). On the other end, AMP-deaminase (AMPD) and 5 ′ -nucleotidase (5′ -NT) suppress AMPK via decreasing AMP cellular levels (22, 99, 100). Moreover, the product of AMPD and 5'-NT reactions is adenosine, an immunosuppressive metabolite. At a high level in tumors, adenosine can promote cell growth, invasion, metastasis of cancer cells, and tumor immune evasion (101). Our previous work has demonstrated that in NB and heart adenocarcinoma cells HL-1, their mitochondrial permeability for AMP was increased than in healthy cells (46). It is known that AK2, which has unique localization in mitochondrial space, has a high affinity for AMP among AMP metabolizing enzymes. Therefore, it has been proposed that the AK2's primary function is to regulate intracellular AMP levels and to guard the cellular adenine nucleotide pool (22). Our study also suggested that cancer cells have a high level of AK2 (46) (**Figure 1**). Altogether, in cancer cells, most cellular AMP transport occurs via MOM where it is converted immediately to ADP and channeled into, maintaining a low cytosolic AMP concentration. Recent direct measurements of AK-mediated metabolic flux indicate that cancer cells have suppressed ATP β-phosphoryl energetics and AMP signaling, as indicated from 18O-labeling experiments demonstrating that highly aggressive breast cancer cells MDAMB231 have lower β-ATP[18O] turnover (AMP phosphorylation) than have the control MCF10A cells (Klepinin et al., in preparation). This could be due to the rewiring of energy metabolism and glycolytic takeover. Activated glycolysis usually suppresses AK metabolic flux apparently by scavenging ADP (102) (**Figure 1**). Suppression of AK phosphotransfer, AMP generation, and consequent signaling through AMPK could be the biggest culprit of a cancerous transformation of a cell (**Figure 1**). There is also evidence that other AMP removal pathway enzymes like AMPD2 as well as 5′ -NT are upregulated in colorectal cancer (103, 104). In this regard, the 5′ -NT expression in breast cancer depends on tumor estrogen receptor status, suggesting a coordinated network (105). Our previous work has shown that in several tumors, MOM permeability has also increased for ADP, which may be related with keeping an intracellular ADP level low (41, 42, 49, 106) (see **Figure 1**). It was found that not only AMP but also ADP can regulate the activity of AMPK (107). Further studies are needed to elucidate detailed mechanisms: (1) how increased MOM permeability for ADP and AMP and (2) raised expression of AMP metabolizing enzymes can regulate intracellular nucleotide levels and the activity of AMPK and (3) what the significance is of AMP metabolic signaling in cancer progression.

# CONCLUSIONS

The present review is a snapshot from recent AK studies that focused on the significance of AK network in energetics and metabolic signaling in cancer cells. Of the nine AK isoforms (AK1–AK9), four of them (AK1, AK2, AK4, and AK6) are involved in the progression of malignant transformation. Studies indicate that AK isoforms (AK1, AK2, AK4, and AK6) have an important role in the regulation of cancer cell metabolism, metabolic signaling, and cell migration and invasion. Moreover, at the initial stage, suppression of AK phosphotransfer and AMP generation and consequently signaling through AMPK by a variety of factors could be the biggest culprit of the cancerous transformation of a cell. Downregulation of AK→ AMP→ AMPK signaling can lead to the loss of control of cell cycle, growth, and proliferation. In the later stages, as emerging data suggest, cancer cells may use the shift in AK isoforms and other phosphotransfer enzymes to rewire their energy supply circuits to support proliferation and metastasis. Knockdown of overexpressed AK2 in human lung adenocarcinoma cells suppressed proliferation, migration, and invasion as well as induced apoptosis and autophagy. In this regard, a diterpene lactone neoandrographolide from extracts of the traditional medicinal herb Andrographis paniculata has been suggested to inhibit AK2 and has strong anticancer properties. Further studies that involve all AK isoforms have the potential to bring new understanding and novel therapeutic strategies targeting the AK isoform network to suppress growth and metastasis of cancer cells.

#### AUTHOR CONTRIBUTIONS

AK and SZ performed the study design, development of methodology, data analysis and interpretation, drafting of the manuscript, and critical revision. LK and ER-K analyzed and interpreted data and performed manuscript review. AT, TK, and PD performed the study conception, design, writing, and reviewing of the manuscript.

### FUNDING

This work was supported by the National Institutes of Health/National Heart, Lung, and Blood Institute (HL 85744-09) and U24DK100469 (Mayo Clinic Metabolomics Resource Core); Marriott Foundation and Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA; Institutional Research Funding IUT23-1 of the Estonian Ministry of Education and Research; and Estonia national scholarship program Kristjan Jaak, which is funded and managed by Archimedes Foundation in collaboration with the Estonian Ministry of Education and Research.

#### REFERENCES

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Klepinin, Zhang, Klepinina, Rebane-Klemm, Terzic, Kaambre and Dzeja. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Metabolic Plasticity of Melanoma Cells and Their Crosstalk With Tumor Microenvironment

Angelica Avagliano1 \*, Giuseppe Fiume2 , Alessandra Pelagalli 3,4, Gennaro Sanità5 , Maria Rosaria Ruocco5 , Stefania Montagnani 1 and Alessandro Arcucci 1 \*

1 Department of Public Health, University of Naples Federico II, Naples, Italy, 2 Department of Experimental and Clinical Medicine, University "Magna Graecia" of Catanzaro, Catanzaro, Italy, 3 Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy, 4 Institute of Biostructures and Bioimages, National Research Council, Naples, Italy, 5 Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy

#### Edited by:

Sara Rodriguez-Enriquez, Instituto Nacional de Cardiología, Mexico

#### Reviewed by:

Philippe Marchetti, INSERM U1172 Center de Recherche Jean Pierre Aubert, France Helen Rizos, Macquarie University, Australia

#### \*Correspondence:

Angelica Avagliano<EMAIL_ADDRESS>Alessandro Arcucci<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Cancer Metabolism, a section of the journal Frontiers in Oncology

Received: 03 February 2020 Accepted: 16 April 2020 Published: 22 May 2020

#### Citation:

Avagliano A, Fiume G, Pelagalli A, Sanità G, Ruocco MR, Montagnani S and Arcucci A (2020) Metabolic Plasticity of Melanoma Cells and Their Crosstalk With Tumor Microenvironment. Front. Oncol. 10:722. doi: 10.3389/fonc.2020.00722 Cutaneous melanoma (CM) is a highly aggressive and drug resistant solid tumor, showing an impressive metabolic plasticity modulated by oncogenic activation. In particular, melanoma cells can generate adenosine triphosphate (ATP) during cancer progression by both cytosolic and mitochondrial compartments, although CM energetic request mostly relies on glycolysis. The upregulation of glycolysis is associated with constitutive activation of BRAF/MAPK signaling sustained by BRAFV600E kinase mutant. In this scenario, the growth and progression of CM are strongly affected by melanoma metabolic changes and interplay with tumor microenvironment (TME) that sustain tumor development and immune escape. Furthermore, CM metabolic plasticity can induce a metabolic adaptive response to BRAF/MEK inhibitors (BRAFi/MEKi), associated with the shift from glycolysis toward oxidative phosphorylation (OXPHOS). Therefore, in this review article we survey the metabolic alterations and plasticity of CM, its crosstalk with TME that regulates melanoma progression, drug resistance and immunosurveillance. Finally, we describe hallmarks of melanoma therapeutic strategies targeting the shift from glycolysis toward OXPHOS.

Keywords: cutaneous melanoma, tumor microenvironment, metabolic alterations, OXPHOS, therapeutic strategies

# INTRODUCTION

Cutaneous melanoma (CM) is highly aggressive tumor characterized by an increasing worldwide incidence more distributed in the Eastern than in Western European countries (1). Among the three different CM clinically and histomorphologically steps, Vertical Growth Phase (VGP) represents the tumorigenic and /or mitogenic stage of CM (2). In VGP step, CM can metastasize to lymph nodes, brain, lung, bone, and liver albeit the size of primary tumor is still small (2). The dramatic invasive behavior of melanoma cells depends on neural crest origin of melanocytes (3). Melanoma cells derive from the malignant transformation of melanocytes affected by the constitutive activation of oncogenic signaling and cancer metabolic reprogramming, which are processes interacting each other (4–7). Oncogenic signaling pathways in malignant melanocytes can be activated by mutations in BRAF, NRAS, and neurofibromatosis type 1 (NF1) gene. Based on the genetic mutations, CM is grouped into 4 genomic subtypes represented by BRAF mutants, NRAS mutants, neurofibromatosis type 1 (NF1) mutants, and triple-wild-type tumors (8). BRAF mutations, target of therapeutic strategies, dramatically affect CM metabolism, depending mainly on glycolytic metabolism. Glycolysis leads to production of adenosine triphosphate (ATP) and building block intermediates useful for cancer progression (2, 6, 8). It is important to note that in normoxic microenvironment, melanoma cells metabolize up to 80% of glucose into lactate, and that hypoxia augments this metabolic process (6, 9, 10). This elevated rate of glucose transformation into lactate, even in normoxic microenvironment, has been showed by Otto Warburg and it is termed Warburg effect (11, 12). However, it is noteworthy that also in hypoxic melanoma microenvironment the mitochondria of cancer cells work and thus can sustain melanoma dissemination (13).

Cancer cells successfully are able to adapt to the nutritional changes and restrictions of the tumor microenvironment (TME), through dynamic modulations of both cytosolic and mitochondrial metabolic pathways in order to produce ATP during cancer progression (2). Most relevant molecular drivers that participate to melanoma metabolic plasticity include AKT, BRAF, p14ARF, MYC, NRAS, phosphatidylinositol-4,5 bisphosphate 3 kinase catalytic subunit α (PIK3CA) and phosphatase and tensin homolog (PTEN) (14–20). Anyway, the remarkable metabolic flexibility and reprogramming of melanoma cells account for the impressive aggressiveness of CM and can also sustain resistance response to BRAF/MEK inhibitors (BRAFi/MEKi) and immunotherapy (2, 6). In this scenario the metabolic crosstalk between cancer cells and TME dramatically affects the metabolic choice, the growth and therapeutic resistance of CM (2). Therefore, in this article we discussed the metabolic plasticity of CM and the metabolic interactions of melanoma cells with TME, leading to tumor development, therapeutic resistance and immune escape. Finally, we highlighted the therapeutic strategies targeting the shift from glycolysis toward oxidative phosphorylation (OXPHOS).

## GLYCOLYSIS AND LACTIC FERMENTATION

Rapidly proliferating melanoma cells produce ATP and carbon precursors for cell growth and proliferation mainly through glycolysis and lactic fermentation, independently by oxygen levels. This process is named "Warburg effect" or aerobic glycolysis (21).

Hypoxia-inducible factor 1 (HIF-1), that is a master regulator of numerous hypoxia-inducible genes and of glycolysis in melanoma, is usually inhibited during normoxia due to the rapid degradation of its subunit HIF-1α. However, many experimental evidence showed that HIF-1α and several of its target genes are strongly upregulated in melanoma cells not only during hypoxia, but also in normoxic conditions (22, 23). Additionally, under normoxia, melanoma cells can regulate and stabilize HIF-1α at the translational level, through mTOR and melanoma antigen-11 (MAGE11) (22), that is involved in the inhibition of prolyl hydroxylase domain protein 2 (PHD2), a HIF-1α negative regulator (24). Consequently, the upregulation and the protein stabilization of HIF-1α lead to the glycolysis induction in melanoma cells and to melanoma development and progression both in the presence and in the absence of oxygen (22, 25). Furthermore, it has been reported that the aberrant and constitutively activation of oncogenic signaling pathways, such as MAPK/ERK, phosphatidylinositol 3-kinase (PI3K)/AKT, mutated microphthalmia-associated transcription factor (MITF), endothelin dependent signaling, and ROS/NFkB pathways, are involved in the enhanced expression of HIF-1α in melanoma cells, independently by oxygen levels (22, 26–29). Interestingly, since MITF pathway activation and BRAF mutations, leading to MAPK signaling activation, occur, respectively, in about 10–20% (30) and 50% (31) of melanomas, it is possible to assume that the constitutive expression of HIF-1α is not a rare event in melanoma (32) and strictly correlates with melanoma aggressiveness and malignancy (23). In more detail, it has been reported that BRAFV600E mutation, leading to the constitutive activation of ERK1/2 and MAPK pathway, sustains aerobic glycolysis through the activation of transcriptional factors, including HIF-1α and c-myc (22) (**Figure 1**). HIF-1α by interacting with HIF-1β, that generally is constitutively expressed (34), promotes the transcriptional activation of lactate dehydrogenase (LDH), aldolase, and enolase 1 (ENO1) (35) and consequently leads to an increase of glycolytic fluxes. In addition, HIF-1α turns on pyruvate dehydrogenase kinase (PDK), which prevents the entry of pyruvate in tricarboxylic acid (TCA) cycle by inhibiting pyruvate dehydrogenase (PDH) (33). More specifically, PDH converts pyruvate into acetyl-CoA in the mitochondria and the PDK-mediated inhibition of PDH leads to a lower consumption of pyruvate in the mitochondrion, and consequently, making a higher amount of pyruvate available in the cytosol. The increase of cytosolic pyruvate promotes a sustained lactic fermentation, consequently increasing lactate production (33). Persistent and sustained ERK1/2 activation, induced by mutant BRAF or KRAS, leads to mitochondrial translocation of phosphoglycerate kinase 1 (PGK1) and phosphorylation of PDK1, which in turn inactivates PDH, contributing to aerobic glycolytic switch in cancer (36). Further, glycolytic flux and glucose uptake are also stimulated by MYC, which transcriptionally activates LDH, glucose transporter 1 (GLUT-1), and hexokinase 2 (HK2) (37, 38).

Surprisingly, additional mechanisms promoting glycolysis in melanoma involve both the activation and the inhibition of the transcriptional factor and OXPHOS inducer MITF. As briefly stated before, the activation of MITF can promote the induction of HIF-1α, that is the master regulator of glycolysis (28). Interestingly, also MITF inhibition, via MAPK pathway, leads to glycolysis in melanoma cells. In particular, the constitutive activation of BRAF/MAPK pathway leads to the suppression of MITF, that thereby cannot activate the peroxisome proliferator-activated receptor γ 1-α (PGC1 α), an important driver of mitochondrial biogenesis and respiration. This leads to the metabolic switch toward glycolysis in melanoma cells (39). Even if these findings seem to be contradictory, they greatly highlight the complexity of melanoma pathogenesis: in fact the mutational status of melanoma cells and the microenvironmental signals can activate or inhibit

specific molecular pathways in order to promote the "Warburg phenotype" in melanoma cells.

Furthermore, a sustained PI3K/AKT/mTOR signaling pathway positively acts on HIF-1α transcription and activity, triggering glycolysis through the synthesis of glycolytic enzymes (40, 41). Several mechanisms can activate PI3K/AKT/mTOR signaling in melanoma, including the loss of tumor suppressor PTEN functions, mutations in AKT and PIK3CA, and compensatory signaling through growth factor receptors (19, 42, 43). Interestingly, PTEN loss in melanoma cells increases extracellular acidification rate (ECAR), likely due to an increased production of lactate (44). Pyruvate kinase (PK) is the glycolytic enzyme converting phosphoenolpyruvate (PEP) to pyruvate in the last reaction of glycolysis. PKM2 is the most representative isoenzyme of the glycolytic enzyme PK. In cancer cells the isoform PKM2 is highly expressed (45) but is endowed with a low activity (46). More specifically, tyrosine kinases including FGFR1, BCR-ABL, and Jak2 phosphorylate glycolytic enzymes, such as PKM2. Tyrosine phosphorylation of glycolytic enzymes induces on one hand the activation of most glycolytic enzymes, thus increasing glycolytic rate, while on the other hand reduces the activity of PKM2, promoting paradoxically Warburg Effect (47). Rather than favoring the glycolytic fluxes with ATP production, the low PKM2 activity leads to an increased amount of glycolytic intermediates upstream PK reaction, providing precursors of several biological macromolecules, including nucleotides from glucose-6-phosphate (G6P), amino sugars, glycolipids and glycoproteins from fructose-6-phosphate (F6P), lipids from dihydrogenacetone-phosphate, serine from 3-phosphoglycerate, amino acids, and pyrimidines from PEP (45). Therefore, low PKM2 activity is a pivotal feature of cancer cells needing continuously precursors of biological macromolecules for their sustained and persistently elevated replicative rate (48). Interestingly, the phosphorylation of PKM2 by ERK rapidly transforms active tetrameric PKM2 into inactive monomers. The inactive monomeric form of PKM2 is able to translocate into the nucleus and induces the expression of many glycolytic enzyme genes, through epigenetic modifications of their promoters, by the phosphorylation of histone H3 (49).

The stimulation of aerobic glycolysis is highly depending on glucose uptake. Specifically, the transcription of the glucose transporter GLUT-1 is strictly regulated by HIF-1α (50, 51). The up-regulation of GLUT-1 is a common feature of the metabolic reprogramming in many tumors and can be associated with a high tumor grade (52–54). In particular, in CM compared to melanocytic nevi, it has been reported a higher GLUT-1 protein expression, which is positively associated with mitotic activity, melanoma progression, and metastasis (55, 56). Interestingly, the evaluation of GLUT-1 cellular localization, by immunohistochemistry, in 225 malignant melanomas and 175 benign nevi showed that GLUT-1 is frequently localized at cell membrane in melanoma, while in nevi this localization is infrequent (57). In other studies, GLUT-1 expression inversely correlated with overall survival (OS) or disease free survival (DFS) hence representing a tumor prognostic marker (58).

Lactic fermentation is a fundamental process, which converts pyruvate into lactate, reconstituting all the NAD+ that had been transformed into NADH during glycolysis. Consequently, to remove excess acid and to sustain glycolysis, lactate is secreted into the microenvironment, through monocarboxylate transporters (MCTs) (59). Interestingly, many cancers cells, including melanoma cells, take up lactate through MCT-1 and metabolize it, supplying the TCA cycle. Some evidences show that an increased transport of lactate correlates with worse outcomes (60). Therefore, lactate consumption could represent an useful biomarker of cancer progression. MCT-1 and MCT-4 represent the main bidirectional and ATP-independent transporters of lactate and related monocarboxylates through cell membrane, even though the directionality of transport is dependent on lactate and proton concentration gradients (61, 62). Pinheiro et al. demonstrated that in melanoma, the hyperexpression of GLUT-1 and MCT-4 correlated significantly with progression from primary to metastatic tumors. These data indicated that the glycolytic phenotype and lactate secretion synergistically act in promoting melanoma metastasis (63). In glycolytic tumor cells, HIF-1α and MYC upregulate MCT-4 to promote the secretion of lactate into the TME (64, 65). Recently, Tasdogan et al. showed that metabolic differences among melanoma cells confer a different ability to form metastases, depending on the function of the MCT-1 transporter (66). Specifically, by experiments of metabolites tracing, using13C-labeled nutrients, they identified efficient and inefficient melanoma metastasizers. Efficient melanoma metastasizers were characterized by high ability to uptake lactate, depending on MCT-1 expression. In addition, lactate uptake was strictly associated with a high enrichment in metabolites related to the TCA cycle (citrate, glutamate, and malate), suggesting that carbon atoms were transferred from lactate to TCA. Conversely, MCT-1 inhibition led to reduction of lactate uptake but was barely effective on primary tumors growth (66). Furthermore, inhibition of MCT-1 was linked to reduction of circulating melanoma cells and decreased CM metastatic capability in patient-derived xenografts and in mouse melanomas. Consistently with previous works, they found that inhibition of MCT-1 or MCT-4 in melanoma cells induces oxidative stress, through the inhibition of lactate export, and a reduced glycolysis (66). Additionally, clinical evidences further support the concept that melanoma mostly relies on glycolysis. For example, the positron emission tomography (PET) with an analog of glucose, i.e., the 2-deoxy-2-[fluorine-18]fluoro-D-glucose (18F-FDG), is an excellent imaging tool that exploits the glucose avidity of melanoma cells for the detection of widespread metastasis, for staging and restaging and for the evaluation of therapy response (67). Even if 18F-FDG PET has no role in early cutaneous melanoma (68), it can be considered a sensitive method superior to routine and conventional methods (i.e., ultrasound, radiography, histology or clinical examination, and follow-up, etc.) for the detection of distant metastases from malignant melanomas (69). Indeed, 18FDG-PET scanning shows 100% of sensitivity and 100% of accuracy for detecting visceral and abdominal nodal metastases, and superficial lymph node metastases, respectively (67). Furthermore, glycolytic melanoma cells produce high levels of LDH-5 that is the more effective isoenzyme in the catalysis of pyruvate to lactate, in order to produce ATP (70, 71). LDH-5, that reflects the Warburg phenotype in cancer cells, can be used as an accurate predictor of prognosis and response to treatments in melanoma patients. In fact, it has been reported that LDH-5 expression is easily detected both in histologic melanoma sections and in the serum of melanoma patients, and strongly correlates with prognosis. Particularly, translational studies reported that high LDH blood levels allow the identification of melanoma patients with worse prognosis (72) and that may not benefit from immunotherapy (2).

## PENTOSE PHOSPHATE PATHWAY

The pentose phosphate pathway (PPP) sustains survival and growth of cancer cells through the generation of pentose phosphate sugars, which will be utilized for nucleic acid synthesis and will provide nicotinamide-adenine dinucleotide phosphate (NADPH). On its turn, NADPH will be essential for fatty acid (FA) synthesis and will sustain cell survival (73). The PPP is mainly regulated at glucose-6-phosphate dehydrogenase (G6PD) level, which acts as a "gatekeeper" of this pathway. G6PD catalyses the irreversible reaction of transformation of G6P into 6-phosphogluconolactone in a rate-determining step, generating NADPH (74). Subsequently, G6PD activity determines both the metabolic fate among glycolysis and PPP, and the oxidative PPP flux (75). The hyper-expression of G6PD is frequent in cancer cells and could be considered a biomarker of poor prognosis, indicating that G6PD has a fundamental role in tumorigenesis (76). Another important enzyme in the PPP, playing a pivotal role in melanoma proliferation and progression, is the transketolase (TKT). TKT converts excess of ribose-5-phosphate (R5P) into glyceradehyde-3-phosphate (G3P) and F6P through a number of reactions. Furthermore, G3P is metabolized also in glycolysis, and F6P can be converted into G6P that re-enters the oxidative PPP to produce further NADPH (77). Elevated TKT expression levels were reported in melanoma as well in lung, breast and prostate cancer cells. More specifically, exposure to UVA augments the proliferation of melanoma cells, by increasing the expression levels of TKT in melanoma (78).

#### OXIDATIVE PHOSPHORYLATION AND KREBS CYCLE

To generate ATP, melanoma cells adopt mainly glycolysis. In some cases, to cope energetic and metabolites demand, melanoma cells can also perform a massive OXPHOS. This metabolism is mainly driven by PGC1-α, which contributes to transcriptional induction of several mitochondrial genes (39, 79, 80) involved in specific mitochondrial processes including DNA replication, transcription, fission and fusion. In addition, hyperexpression of PGC1-α correlates with a decreased OS in patients with stage III melanoma (81) and with resistance to MAPK pathway inhibitors (MAPKi) (79, 80). Furthermore, PGC1-αhigh expressing melanoma cells show a reduced sensitivity to reactive oxygen species (ROS), conferring an increased metastatic potential (81). Conversely, PGC1-α knockdown leads to the inhibition of ROS-scavenging gene expression, associated with an increased cell sensitivity to ROS (81) and the inhibition of metastatic spread of B16–F10 melanoma cells (82). MITF is a positive regulator of PGC1-α expression and other OXPHOS genes, including ATP5B, ATP5D (encoding for components of ATP synthase complex), CYC1 (encoding for cytochrome c1), NDUFA8, NDUFA9, NDUFB10, NDUFC2, NDUFS3 (encoding for components of NADH dehydrogenase complex), SDHB (encoding for succinate dehydrogenase subunit B) (39, 79, 83), while HIF-1α reduces PGC1-α expression levels by preventing the transcription of MITF (84, 85). AMP-activated protein kinase (AMPK) is an additional regulator of PGC1-α expression (86). In presence of a high cytoplasmic ratio of AMP/ATP, the kinase LKB1 phosphorylates and activates AMPK, which in its turn suppresses mTORC1 and inhibits anabolic reactions. Moreover, the activation of AMPK promotes mitochondrial gene expression via PGC1-α (86, 87). In glycolytic tumors, phosphorylation of ERK (pERK) prevents the activation of LKB1 and, consequently, reduces PGC1-α expression levels, inhibiting the typical response to energy deficiency (88).

The TCA cycle represents another mitochondrial pathway playing a pivotal role in tumor formation and progression. The TCA cycle occurs in the mitochondrial matrix and is an amphibolic pathway, in which multiple catabolic and anabolic pathways converge. In the last decade, it has been showed that several intermediates of Krebs cycle, including succinate, α-ketoglutarate, itaconate, fumarate, 2-hydroxyglutarate, are characterized by "non-metabolic" functions. These metabolites are involved in epigenetic modifications or post-translational protein modifications, that affect the immune response and contribute to pathological conditions, such as initiation and progression of carcinogenesis (89). α-ketoglutarate and succinate levels can regulate the activity of HIF-1α via prolyl hydroxylases (PHDs), promoting a metabolic switch from OXPHOS to glycolysis (90). Specifically, PHD uses molecular oxygen to hydroxylate HIF-1α, at specific residues of proline. Hydroxylation recruits on HIF-1α the protein Von Hippel-Lindau (VHL) E3 ubiquitin ligase, which ubiquitinates and subsequently promotes the proteasome-dependent degradation of HIF-1α (91). Interestingly, a recent work (92) shows that MITF, through the transcriptional regulation of SDHB, contributes to prolong hypoxia response. Specifically, under hypoxia, by the action of BHLHE40/DEC1, the levels of MITF expression and activity decrease (85). Consequently, because SDHB converts succinate in fumarate, the levels of succinate increase. On its turn, succinate inhibits PHD, preventing HIF-1α degradation (90). In addition, increased amount of succinate can affect the regulation of multiple enzymes through the process of succinylation (93). It has been shown that cytoplasmic aspartate levels can promote tumor progression in melanoma, through the suppression of arginosuccinate synthetase 1 (ASS1), which, in the urea cycle, converts aspartate into arginosuccinate. The increase of intracellular levels of aspartate activates the carbamoyl phosphate synthetase II (CAD), which, consequently, leads to an increased synthesis of nucleotides and promotes melanoma cell proliferation (94).

Glutamine represents the main metabolite able to replenish the TCA cycle of precursors, required for the synthesis of fats, nucleic acids and amino acids (95). Furthermore, glutamine metabolism provides energy and is pivotal for cellular redox homeostasis (96). Differently from melanoma, other glycolytic tumors replenish the TCA cycle of precursors through the action of enzyme pyruvate carboxylase which produces oxaloacetate from pyruvate (97). Interestingly, in melanoma the contribution of pyruvate carboxylase to the TCA cycle is very low (21, 98, 99). After entering the cell through the glutamine receptor SLC1A5, glutamine is deaminated to glutamate by the action of cytosolic glutaminase (6). Consequently, glutamate is converted into αketoglutarate, through reactions catalyzed by either glutamate dehydrogenase 1 (GDH1) or mitochondrial alanine and aspartate aminotransferase (GOT2 and GPT2) and enters the TCA cycle. Interestingly, through a reductive carboxylation of αketoglutarate, tumor cells are able to reverse Krebs cycle, thereby increasing the amount of citrate to be used for FA synthesis. Of note, under low presence of oxygen, α-ketoglutarate, which derives from deamination of glutamate, provides over onethird of total citrate necessary for FA synthesis (21). The main enzymes required for the production of citrate through the carboxylation of α-ketoglutarate are cytosolic and mitochondrial isocitrate dehydrogenases, respectively IDH1 and IDH2. Some works reported that mutations in these genes sporadically arise in melanoma (83, 84) and cause a growth advantage to melanoma cell lines bearing BRAF mutations (85).

#### FATTY ACID OXIDATION

In the last years, fatty acid oxidation (FAO) in cancer has been extensively studied and growing evidences show its contribution in melanoma progression. Comparative analyses between melanoma cells and benign nevi show that carnitine palmitoyltransferase 2 (CPT) 2, an enzyme critical for translocation of long-chain Fas, is one of the most upregulated gene in melanoma (100). Interestingly, melanoma cells treated with MAPKi showed an increase of CD36 levels and fatty acid oxidation (FAO) levels in a manner dependent by peroxisome proliferator-activated receptor (PPAR-α) and CPT1A (101). Of note, the sustained FAO is essential for survival of BRAFV600E-mutant melanoma cells, under the MAPKiinduced metabolic stress prior to acquiring drug resistance (101). Being the metastasis formation a process that require a huge amount of nutrients, FAs can provide an ATP boost for the dissemination of tumor cells. In addition, FAs can provide acetyl-CoA, which, in the TCA cycle, is essential for citrate formation and, consequently, for NADPH production via IDH1, participating to the redox balance in tumor cells (102). Interestingly, some proteins that bind and process lipids, including phospholipase D3 (PLD3), inositol triphosphate protein kinase B (ITPKB), inositol triphosphate receptor 3 (ITPR3), fatty acid binding protein 3 (FABP3), have been found strongly upregulated in melanoma (100). In addition, a recent comparative analysis of proteome of melanoma cells revealed a higher OXPHOS and lipid metabolism in melanoma cells "responder" to immunotherapy (103). More in detail, Harel et al. showed that a higher OXPHOS and lipid metabolism augment the antigen presentation of melanoma cells, through the increase of MHC proteins expression (HLA-A, HLA-C, and B2M which consist MHCI, and CD74, a chaperone of MHCII), of several factors involved in the antigen processing and presentation machinery (including TAP1 and TAP2 which are peptide antigen transporters, TAPBP which acts as a bridge between the MHC and the peptide transporters), and PSME1, a component of proteasome. Consequently, the higher expression of MHC molecules promotes a better response upon immunotherapy by T cells (103).

#### MELANOMA MICROENVIRONMENT ACIDIFICATION AND ITS INFLUENCE ON MELANOMA GROWTH AND THERAPEUTIC RESISTANCE

The acidification of microenvironment is a hallmark of CM (2) (**Figure 2**). In fact, pH gradient of melanoma cells is totally different respect to that of normal cells (104). Cancer cells display an intracellular pH (pHi) > 7.4 and extracellular pH (pHe) ranging from 6.7 to 7.1. Conversely, normal cells display pHi of about 7.2 and pHe of about 7.4 (104). The extracellular acidosis is linked to metabolic changes of melanoma cells and angiogenesis (2). The alterations in cancer cell metabolism are represented mainly by upregulation of glycolysis leading to protons and LDHA-dependent lactate generation (10). Both protons and lactate are transported out of cancer cells by MCT-4, proton exchangers and transporters, in order to elude intracellular acidosis (10, 105). It is noteworthy that stromal cells can take extracellular lactate to produce pyruvate, successively secreted to furnish melanoma cells (106). Furthermore, also PPP and glutaminolysis sustain microenvironment acidification through secretion of carbon dioxide (CO2) (2).

Angiogenesis process generates new blood vessels from already formed vessels (107). In particular, the vasculature affects dramatically the metabolism of solid tumors because the distance of cancer cells from new vessels influences metabolic option between glycolysis and OXPHOS (108). Furthermore, angiogenesis and vascular network, characterized by both hypervascularisation and hypovascularisation, influence the tumorigenic, mitogenic and metastasizing VGP step of CM (2, 3, 109, 110). Both hypervascularisation and hypovascularisation depend on the loss of homeostasis between pro-angiogenic and anti-angiogenic factors (111). This pathological condition leads to migration and proliferation of endothelial cells, whose excess sustains the development of disorganized and hyperpermeable blood vessels (111). Additionally, blood vessels of TME are also compressed by cancer cells. These structural alterations of tumor blood vessels lead to an increase of resistance to blood flow associated with a reduction of blood supply (111). Furthermore, in highly aggressive melanomas, cancer cells can acquire an endothelial phenotype which enables their participation in angiogenesis (112). It is noteworthy that hyperpermeability of cancer vessels generates the lack of pressure gradient modulating the circulation of both fluid and macromolecules and sustains hypoxia by hindering the transport of oxygen. The hypoxia, generated also by high oxygen consumption of cancer and endothelial cells (111), sustains acidosis through up-regulation of glycolytic pathway mostly linked to the stabilization of HIF-1α, the principal inductor of aerobic glycolysis in cancer (113, 114). Therefore, HIF triggers up-regulation of plasma membrane transporters, exchangers, pumps and enzymes, all of which keep pHi of cancer cells around neutral values or even lightly alkaline (114, 115). However, the acidification of melanoma microenvironment can be transient or chronic and is associated with alterations of cancer cells and, as discussed below, of immune cells (**Figure 2**). Furthermore, a recent work of Acker's group indicates that metabolic alterations of melanoma cells, hypoxia, HIF-1 and microenvironment acidosis are regulated by a common positive feedback (116). HIF-1α not only regulates both anaerobic and aerobic glycolysis in melanoma cells, but also enhances the expression of genes involved in both tumor invasion and glycolysis. In particular, under hypoxia (117, 118) and normoxia (119), HIF-1α can increase the expression of urokinase plasminogen activator receptor (uPAR), which in turn leads to a glycolytic and invasive phenotype in melanoma cells in a EGFRdependent manner with involvement of the PI3K/mTOR/HIF-1α pathway (117–119). The binding of the urokinase plasminogen activator (uPA) to its receptor uPAR, expressed in onethird of melanomas (120), sustains the expression of the extracellular matrix metalloproteinases inducer (EMPPRIN) and of ENO1, which both connect lactate homeostasis and glycolysis with the invasive phenotype of melanoma cells (119). Therefore, uPA/uPAR system in melanoma cells could be a molecular connection between invasion capability and glycolytic metabolism (119).

FIGURE 2 | Alterations of cancer and immune cells associated with melanoma microenvironment acidification. Hypoxia (caused by increasing distance from tumor vessels, structural abnormalities of tumor vasculature and high cancer cell O2 consumption) and genetic mutations (such as BRAFV600E, loss of PTEN, etc.) trigger a metabolic reprogramming in melanoma cells, which increase glycolysis. Glycolytic melanoma cells promote an abnormal extracellular accumulation of lactate and protons and thus induce the acidification of TME. In turn, the acidic TME triggers a metabolic reprogramming in melanoma cells, which increase OXPHOS and decrease glycolysis. Additionally, tumor acidity increases melanoma malignancy by enhancing the migratory and invasive capability of melanoma cells and their capability to produce proteases (such as MMP-2/9, cathepsin, etc.) and pro-angiogenic factors (such as VEGF-A, IL-8, etc.). Acidity generates an immunosuppressive milieu, where T cells and NK cells lose their cytotoxic activity, and macrophages acquire the protumorigenic M2-like phenotype. Also glycolytic melanoma cells contribute to the generation of this immunosuppressive environment. In fact, by mediating glucose restriction, melanoma cells alter T cell metabolism and reduce their cytotoxic activity. Therefore, the pH and oxygen gradients in the tumor mass lead to molecular and metabolic changes in cancer and immune cells, which work together and cooperate to sustain melanoma progression.

Furthermore, Laurenzana et al. showed that there is a strong connection between uPAR levels in BRAF mutant melanoma cells and response to BRAF inhibition (121). In fact, melanoma cells, expressing different levels of uPAR, show variable responsiveness to Vemurafenib. These experimental evidences suggest that uPAR levels could predict outcome of targeted therapy in patients affected by BRAF mutant melanoma (121). CM microenvironment acidification can confer a growth advantage to cancer cells by selecting cells resistant to acidic conditions (122), even if cancer cells can respond to acidic microenvironment in different ways. In particular, Peppicelli et al. demonstrated that acidic microenvironment may trigger in melanoma cells a metabolic shift toward OXPHOS and mesenchymal phenotype, associated with high invasiveness and pro-metastatic property (13).

Biguanide metformin, that is a molecule used in the treatment of type 2 diabetes, specifically inhibits the mitochondrial respiratory chain (MRC) complex 1. It leads to NADH oxidation decrease and to reduction of both proton gradient across the inner mitochondrial membrane and oxygen consumption rate (123). Metformin treatment inhibits both epithelialmesenchymal transition (EMT) markers and OXPHOS at concentration of 10 mM, which is non-toxic for cancer cells grown in a standard pH medium. Furthermore, this treatment inhibits remarkably proliferation and colony formation of acidic melanoma cells, grown in acidic microenvironment. Therefore, the capacity of metformin to hinder EMT and OXPHOS supports the supplement of metformin to therapy of advanced melanoma (13, 124).

Transient treatment of A375-M6 melanoma cells with acidic medium increases expression of SOX2 with respect to control cancer cells grown in standard medium (125). Extracellular acidosis induces a metabolic switch toward OXPHOS and a concurrent slowdown of acidic cancer cells to a more glycolytic metabolism (126). The silencing of SOX2 gene shifts the metabolism of acidic melanoma cells toward glycolysis, thus making cancer cells less vulnerable to metformin treatment (125, 126). SOX2 is a transcription factor regulating, under acidic condition, the metabolic shift toward OXPHOS and downregulates HIF-1α by binding to its promoter (125, 126). Recent studies highlighted that the extracellular acidity of melanoma TME may provide an environment sustaining dormancy of melanoma cells, which exhibit low replication rate, high resistance to apoptosis and autophagy (127). Tumor dormancy is an important process implicated in tumor immune escape and drug resistance (128, 129). Jia et al. showed that low levels of SOX2 expression are linked to cycle arrest, melanoma cell stemness and tumor dormancy leading long-term tumor survival, and relapse (130).

Other studies showed that acidosis induces apoptosis and autophagic pathway (131–133). Böhme et al. showed that chronic acidosis triggers in melanoma cells a senescence-like phenotype with MITFlow/AXLhigh signature and cellular translation reprogramming. This phenotype, induced by extracellular acidosis, is associated with therapeutic outcome in CM (134).

Transient or chronic extracellular acidification increases carbonic anhydrase IX (CAIX) expression (135). CAIX is a transmembrane enzyme that is an important regulator of cancer cells pHi (136, 137). CAIX enzymatic activity affects viability of acidic cancer cells in CM, and its inhibition could represent a new therapeutic strategy (135). In particular, Chafe et al. analyzed the expression of CAIX in a cohort of 449 patients affected by CM. They showed that CAIX levels are linked to worse OS (138). CAIX inhibition, through SLC-0011 treatment, reduces extracellular acidosis and improves the response to anti– programmed cell death protein 1 (PD-1) and anti–cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) blockade. These effects are associated with reduction of melanoma growth (138).

Lipid rafts are plasma membrane subdomains containing high concentrations of cholesterol and glycosphingolipids (139). V-type H+-ATPases enzymes are proton pumps, present in lipid rafts, and whose plasma membrane overexpression is correlated with cancer metastasis (140–142). The enzymatic activity of these H+ pumps supports extracellular acidosis that sustains the activity of proteolytic enzymes, such as metalloproteinases (MMPs) and cathepsins, and promotes drug resistance and metastasis (104). Inhibition of V-ATPases in melanoma cells, by using the plant-derived monoterpene Myrtenal, hampers the electrochemical H+ gradient across the cell membranes, triggers cell death and decreases tumor cell migration and invasion in vitro (143). Moreover, V-ATPases inhibition reduces metastasis in vivo (143). Acidic microenvironment induces cancer cells to synthesize and secrete proteases such as MMP9 and 2, cathepsin B and L, all of which can degrade extracellular matrix (ECM) proteins (122). Furthermore, melanoma cells increase the secretion of the proangiogenic factors VEGF-A and IL-8 (144). All these experimental evidences strongly support a relation between extracellular acidosis and malignant progression, higher invasion, and metastasis of melanoma cells. In particular, the dissemination of CM strongly depends on the spreading and propagation of cancer cells to lymphatic vessels and regional lymph nodes, respectively (145). The lymph nodes are the prevalent site of CM metastasis. Both in A375P melanoma cell line and in melanoma cells derived from a human metastatic lesion, extracellular acidosis induces the expression of VEGF-C. This growth factor, that is secreted by both melanoma cells and tumor associated macrophages (TAMs), induces dramatically lymphoangiogenesis (146).

Exosomes could have a significant role in solid tumor progression because they have an unlimited access to the lymphatic system and blood vessels (147–149). Boussadia et al. showed that acidic microenvironment sustains exosome secretion of melanoma cells (150). Consequently, extracellular acidosis trough a massive release and intra-tumoral uptake of exosomes, triggers a more malignant and metastatic phenotype in melanoma cells. In fact, pH naïve melanoma cells, exposed to exosomes generated in an acidic medium, develop migratory and invasive capability probably associated with transfer of metastatic exosomal proteins, sustaining cell motility and angiogenesis (150). Furthermore, exosomes from melanoma cells could contribute to extracellular acidification, by interacting with normal stromal fibroblasts located in distant sites from primary tumors (151). In particular, exposure of human adult dermal fibroblasts to human melanoma-derived exosomes leads to fibroblast metabolic reprogramming associated with increase of aerobic glycolysis, decrease of OXPHOS and extracellular acidification induction (151). In particular, the activity of exosomal miR-155 and miR-210 regulates upregulation of aerobic glycolysis in fibroblasts. Therefore, cancer cell exosomes could influence stromal cell metabolism, thus contributing to the generation of a pre-metastatic niche that sustains metastatic process (151).

It is known that melanoma microenvironment acidification hinders immunotherapy response (2). Additionally, LDH serum level is a well-known prognostic factor of survival in CM (2, 152). In fact, LDH levels significantly affect response, progressionfree survival (PFS) and OS of CM patients treated with antibodies targeting CTLA-4 (ipilimumab) or PD-1 (nivolumab, pembrolizumab), or with ipilimumab plus nivolumab combined therapy (152). Lactate can contribute to tumor escape from immune response by impairing cytotoxic T lymphocytes (CTLs) metabolism and function (153). High levels of lactate are linked to a significant decrease of CD8+ T and NK cell number and activity, both in vitro and in vivo (154). Furthermore, Collegio et al. showed in murine experimental model that lactate induces in macrophages a pro-tumoral M2-like phenotype, characterized by the induction of VEGF and arginase 1 (Arg1) expression (155). Therefore, the efficacy of immunotherapy could be improved by counteracting microenvironment acidification and lactate extracellular accumulation. As stated before, CAIX inhibition though SLC-0011 treatment decreases the acidification of melanoma microenvironment. SLC-0011 treatment combined with immune-checkpoint inhibitors enhances anti–PD-1 and anti–CTLA-4 blockade effectiveness (138). Another possibility to ameliorate immunotherapy outcome could be represented by LDH inhibitors, which however cannot be used in melanoma therapy, because preclinical analyses of anticancer activity have demonstrated their low therapeutic effectiveness associated with harmful side effects (156).

Diclofenac and lumiracoxib are non-steroidal antiinflammatory drugs (NSAIDs), approved for clinical use, that display structural similitude (157). In particular, diclofenac induces apoptosis, associated with mitochondrial dysfunction, and restrains both glucose metabolism and MYC expression in melanoma (158, 159). It is noteworthy that both NSAIDs could be utilized to counteract lactate extracellular accumulation (157).

#### METABOLIC CROSSTALK BETWEEN MELANOMA CELLS AND TME

The TME of solid tumors such as CM is extremely complex. In fact, it includes ECM molecules, represented by laminin and collagen, growth factors, including VEGF, nutrients, such as glucose, blood and lymphatic tumor vessels, various concentrations of oxygen, cancer and stromal cells, that influence each other to sustain tumor growth, progression and metastasis (9, 160, 161). Non-cancer stromal cells are represented by endothelial cells, pericytes, immune cells, fibroblasts, fibroblast aggregates, myofibroblasts, cancer associated fibroblasts (CAFs), activated adipocytes, and mesenchymal stem cells (MSCs) (9, 162–165). In the complex, melanoma microenvironment represents a niche produced and regulated by the bidirectional interactions of melanoma cells with surrounding cells, tumor vessels and ECM (166). This crosstalk dramatically influences the development of disease and therapeutic resistance (2). In solid tumor cancer cells trigger a constitutive wound healing response that provokes an unregulated inflammation and a constitutive stroma activation (167). In particular, during melanoma growth and development, cancer tissue recruits and activates host tissue cells which sustain the development and progression of tumor, by supporting the metabolism of cancer cells (167). Therefore, the several activated stromal cells can differentiate into macrophages, mast cells, adipocytes and CAFs, which in turn begin to secrete cytokines, induce a turnover of ECM thus playing an important role in tumor growth (167).

## Metabolic Crosstalk Between Fibroblasts and Melanoma Cells

Fibroblasts, fibroblast aggregates, myofibroblasts and CAFs represent important constituents of melanoma stromal microenvironment (163, 165, 168). It is known that normal dermal fibroblasts, before CAF differentiation, hamper melanoma formation at its early stage (169). Conversely, senescent fibroblasts support melanoma growth (170). During melanoma development fibroblast aggregates are formed in dermis and their interaction with melanoma cells leads to fibroblast reprogramming linked to CAF differentiation (163). Anyway during melanoma development and progression, skin fibroblasts, through direct contact with malignant melanocytes, and/or the stimulation by humoral mediators and ROS, undergo a metabolic transformation which leads to fibroblast constitutive activation and thus CAF differentiation (9).

Direct contact between melanoma cells and fibroblasts are modulated by cadherins and connexins (171). In CM cancer cells proliferate, penetrate basement membrane and infiltrate into corium. Furthermore, a change from E-cadherin to N-cadherin expression, during melanoma development, not only frees cancer cells from epidermal keratinocytes, but also provides new adhesive characteristics (171). Via N-cadherin and gap junctions regulated by connexins, melanoma cells interact with N-cadherin-positive fibroblasts (171). In particular, connexinsmediated gap junctions regulate TME interactions between melanoma cells among each other and with the stromal cells (172). Connexins belong to a family of transmembrane proteins building gap junctions. These proteins are essential for gap junctional intercellular communication (GJIC) by exchange small molecules such as ions, signaling molecules (cAMP, ATP) and amino acids (172). Furthermore, GJIC mediates also miRNA transfer (173). The expression of connexin-43 (Cx43), over the last few years, has been associated with cancer recurrence, metastatic spread and poor survival (174). Furthermore, it is conceivable that Cx43 mediated connection could couple metabolic profile of melanoma tissue with regulation of cancer growth. In fact, Cx43 hemi channel regulates proliferation by regulating intracellular ATP and Ca2+ levels (175). Notably, inhibition of Cx43 channel activity sustains melanoma cell proliferation, while overexpression of Cx43 increases gap junction GJ coupling and reduces cell growth. Furthermore, Cx43 overexpression in FMS human melanoma cell lines increases apoptosis and is linked to a decrease of melanoma growth and metastatic capability (176).