Glucose deprivation reduces proliferation and motility, and enhances the anti-proliferative effects of paclitaxel and doxorubicin in breast cell lines in vitro.

BACKGROUND: Breast cancer chemotherapy with high dose alkylating agents is severely limited by their collateral toxicity to crucial normal tissues such as immune and gut cells. Taking advantage of the selective dependence of cancer cells on high glucose and combining glucose deprivation with these agents could produce therapeutic synergy.
METHODS: In this study we examined the effect of glucose as well as its deprivation, and antagonism using the non-metabolized analogue 2-deoxy glucose, on the proliferation of several breast cancer cell lines MCF7, MDA-MB-231, YS1.2 and pII and one normal breast cell line, using the MTT assay. Motility was quantitatively assessed using the wound healing assay. Lactate, as the end product of anaerobic glucose metabolism, secreted into culture medium was measured by a biochemical assay. The effect of paclitaxel and doxorubicin on cell proliferation was tested in the absence and presence of low concentrations of glucose using MTT assay.
RESULTS: In all cell lines, glucose supplementation enhanced while glucose deprivation reduced both their proliferation and motility. Lactate added to the medium could substitute for glucose. The inhibitory effects of paclitaxel and doxorubicin were significantly enhanced when glucose concentration was decreased in the culture medium, requiring 1000-fold lesser concentration to achieve a similar degree of inhibition to that seen in glucose-containing medium.
CONCLUSION: Our data show that a synergy was obtained by combining paclitaxel and doxorubicin with glucose reduction to inhibit cancer cell growth, which in vivo, might be achieved by applying a carbohydrate-restricted diet during the limited phase of application of chemotherapy; this could permit a dose reduction of the cytotoxic agents, resulting in greater tolerance and lesser side effects.

Introduction

Nutritional imbalance, decreased physical activity, infection, stress, advanced age, and the use of chemotherapeutic agents and glucocorticoids may all contribute to the development of an hyperglycemic state in cancer patients [1, 2]. Several studies have reported correlation between various metabolic disorders characterized by hyperglycemia such as diabetes, and increased risk of breast cancer development and mortality [3-6] particularly in post-menopausal women [5]. This link is attributed in part to the increased utilization of glucose by cancer cells, and increase in the circulating levels of insulin-like growth factor-1 (IGF-1), which is also associated with increased risk of cancers [7-9].

Under prevailing aerobic conditions, normal cells derive their energy (ATP) primarily from oxidative phosphorylation of the products of glucose metabolism. Cancer cells however, even in the presence of adequate oxygen supply, seem to rely on the meagre output of ATP from glycolysis alone, with accumulation of lactate that is normally associated with the anaerobic state [10-13]. The upshot of this is that tumours are highly glucose-dependent and characterised by a high rate of glucose uptake and utilisation [14]. This phenomenon has long been known as the Warburg effect; it is the basis for the detection of metastatic tumour deposits by positron emission tomography with 2-deoxy glucose (2-DG). Many explanations have been proposed for this unusual preference, without a convincing resolution [15, 16]. This has not prevented attempts to use this metabolic anaomly to try and target cancer cells through glucose deprivation. Several reports have shown that administration of a low carbohydrate ketogenic diet to mice resulted in significant reduction of blood glucose and insulin levels, reduced breast cancer growth and metastasis and prolonged survival [17, 18]. In human cancer patients the outcome of similar studies has been ambivalent [19, 20], although such diets have been reported to successfully treat refractory drug-resistant epilepsy, obesity and type 2 diabetes [21-23].

Exposure of several breast cancer cell lines (MCF7, SUM-131502, T47D and ZR75-1), as well as cell xenografts grown in nude mice, to sodium-glucose transporter 2 inhibitors (canagliflozin and dapagliflozin) has shown inhibition of cell proliferation, in part through enhanced Amp-activated protein kinase (AMPK) phosphorylation and reduced phosphorylation of p70 ribosomal protein s6 kinase 1 (p70SK1) [24]. Prolonged treatment of mammary epithelial cells with transforming growth factor-beta (TGF-beta) was associated with enhanced expression of the glucose transporter Glut1 and glucose uptake, and subsequently enhanced cell proliferation [25]. This also induced a stable epithelial to mesenchymal transition (EMT), which is known to increase tumour cell aggressiveness [26, 27]. The expression of glucose transporter SLC2A1 and SLC2A3 was upregulated in MCF7 breast cancer cells that had undergone EMT as a result of shRNA induced estrogen receptor (ER) silencing [27]. EMT induced in MCF7 cells by exposure to increasing concentrations of tamoxifen also resulted in increased glucose consumption by the transited cells [28]. Another report suggested that SNAIL-1 (a downstream mediator of EMT) enhanced the gene expression patterns that promote glucose uptake and glycolysis [29]. The balance of these and other observations suggests that glucose deprivation may be an effective metabolic means of reducing tumour growth.

Current treatment of metastatic breast cancer, in particular of patients exhibiting de novo or acquired endocrine resistance, routinely involves the application of high dose chemotherapy with highly toxic agents whose adverse effects often outweigh their beneficial ones. The side effects of chemotherapy are dose-dependent which might be alleviated by reducing the doses, but this will ultimelty comprimise their efficacy.

In this study our aim was to determine whether a dose reduction in chemotherapeutic agents might be achieved by combining them with glucose deprivation, to create conditions most unfavourable to cancer cells.

Materials and methods

Cell lines

MDA-MB-231 human breast carcinoma cell line (ER–ve) was originally obtained from the ATCC (American Type Culture collection, VA, USA; catalogue number CRM-HTB-26). MCF10A normal breast epithelial cells were obtained from Dr. E Saunderson through Dr J Gomm St Bartholomews Hospital, London. pII (ER–ve) cells were generated by shRNA-mediated knockdown of the ER in MCF7 cells (which were also originally obtained from the ATCC, Catalogue number HTB-22). YS1.2 were also derived from similarly transfected MCF-7 cells [27, 30] but failed to down-regulate ER and therefore have been used as ER+ve.

Dulbecco’s modified eagle’s medium (DMEM) containing 25 mM glucose (ThermoFisher, USA, Cat# 12491) was used for regular culture. For experiments testing effects of glucose deprivation RPMI medium without glucose (Sigma-Aldrich, USA, Cat# R1383) was used. Both were supplemented with 5% fetal bovine serum (FBS), 600 mg/mL L-glutamine, 100 U/mL penicillin, 100 mg/mL streptomycin and 6 mL/500 mL 100 x non-essential amino acids. Glucose was obtained from Sigma Life Science, Cat # 49163). MCF10A were cultured in DMEM F12 (Cytiva, Cat# SH30023.01) supplemented with 5% horse serum, 1x Pen/Strep, 20 ng/mL mouse EGF, 0.5 μg/mL hydrocortisone, 100 ng/mL cholera toxin and 10 μg/mL insulin.

All cell lines were routinely grown in monolayer in 25 or 75 cm2 tissue culture flasks (or in microtitre plates for experiments) inside an incubator maintained at 37°C with 5% CO2 atmosphere at 95% humidity. Cell cultures were periodically treated with mycoplasma removal agent from Biorad (USA) and tested with detection kits from Invivogen (CA, USA) and DAPI nuclear staining to ensure they remained free of mycoplasma.

MTT assay

Cells were routinely seeded at 4x104 into 24-well culture plates and allowed to grow to 30–35% confluency. The medium was then removed and replaced with fresh medium and additives according to individual experiments. Cell density was determined either immediately (day zero) or after 1 day and 4 days of cultivation. For the measurement, medium was removed and replaced with 500 μl of MTT reagent (Sigma-Aldrich, USA) (0.5 mg/ml) and left at 37°C for 2 h; MTT solution was removed and 200 μl of acidic isopropanol added to dissolve the blue formazan crystals that had formed. Plates were scanned at 595 and 650 nm (for background subtraction) using a MULTISKAN SPECTRUM spectrophotometer, and absorbance compared between samples as a measure of proliferation. For measurement of growth over 30 days, cells were initially cultured in 24-well culture plates and transferred into larger vessels before confluency was reached. Cell growth in this case was assessed by trypsinising cells, centrifuging them and resuspending in a suitable volume of PBS, with aliquots taken for counting using a haemocytometer. Note that data have been presented directly as comparative OD readings, as the absolute cell number is not relevant for the purpose of this study. The actual cell density is indicated as the starting seeding number.

Apoptosis assay

Cells were cultured in 6 well plates and were then trypsinized, pelleted by centrifugation at 1000g for 3 min and washed twice by re-suspension and centrifugation in ice-cold PBS and once in Annexin-V binding buffer (10 mM HEPES/NaOH (pH 7.4), 0.14 M NaCl, 2.5 mM CaCl2). The final cell pellet was re-suspended in 100μl of Annexin-V binding buffer at 1x106 cells/ml and processed for FACS analysis using the PE Annexin V apoptosis detection kit I from BD Pharmingen (USA). Cells were stained in the following manner: (A), cells only (negative control) (B), with 10 μl of Annexin V-PE (C), with 20μl of 7AAD (D), with 10μl of Annexin V-PE plus 20μl 7AAD. All incubations were performed in the dark at room temperature (RT) for 15 min.

Motility assay

Cells were cultured in 6 well plates with complete DMEM to 80–90% confluence. The medium was then aspirated off and replaced with a), DMEM containing 25 mM glucose (+ glucose) b), DMEM plus various concentrations of 2-DG (0.5–10 mM) c), RPMI without D-glucose (- glucose) d), RPMI without D-glucose plus various concentrations of added glucose (1.67–16.7 mM) or e), RPMI without D-glucose plus L-lactate (20 Mm, Sigma-Aldrich, USA, Cat # 71720). These media all contained FBS. A scratch was then created in the cell monolayer using a sterile p1000 pipette tip and a photograph of the scratched area was taken immediately (0 h). After incubation for 24h, further photographs were taken of the same scratched area. The width of the scratch at 24 h was calculated as a percentage of the width at 0 h; a minimum of 3 three areas along the scratch were measured and averaged, and experiments repeated three times.

Lactate assay

Cells were cultured to a density of approximately 106 in 6-well microtiter plates. The culture medium was carefully aspirated into Eppendorf tubes and protein concentration was estimated using the Bradford assay. Extracellular lactate was measured in aliquots using the EnzyChrom L-Lactate Assay Kit ECLC-100 purchased from BioAssay Systems USA, following the manufacturer’s protocol. Standards were prepared by dilution of a stock solution of 100 mM L-lactate in serum free media, and 20 μl of samples or standards were transferred into wells of a clear bottom 96-well plate. Two reactions were performed for each sample: one with both enzymes A and B, and another without enzyme A (control). The working reagent was prepared freshly by mixing 60 μl Assay Buffer, 1 μl enzyme A, 1 μl enzyme B, 10 μl NAD and 14 μl MTT. For control, enzyme A was omitted from the reagent mix; 80 μl of the working reagent was added to each sample well and mixed by pipetting up and down. The background optical density at 650 was measured in a plate reader at ’zero’ time (OD0) and after 20 min (OD20) incubation at room temperature and subtracted from that at 565nm. For standard curve the corrected OD0 was subtracted from OD20. For samples with no enzyme A control, the ΔOD no enzA value was subtracted from ΔOD sample. The ΔΔOD values were used to determine sample L-lactate concentration from the standard curve.

Statistical analysis

Student’s two tailed unpaired t- test or one-way ANOVA test followed by Bonferroni post hoc test were used to compare means of individual groups using GraphPad Prism software (version 5.0): p < 0.05 was considered statistically significant.

Results

Effect of glucose starvation on cell proliferation

We wanted firstly to determine whether glucose starvation reduces normal and breast cancer cell proliferation. As shown in Fig 1A and 1B, culturing of both ER–ve pII cells as well as ER +ve YS1.2 cells in culture medium without glucose inhibited their proliferation (but did not induce cell apoptosis; S1 Fig) after 4 days (but not 1 day) of culture. This was also seen with the other ER–ve MDA-MB-231 cells (Fig 1C) and the normal breast epithelial cell line MCF10A (Fig 1D). In another set of experiments, performed on the MCF10A and pII cells, we determined the longer-term effect (up to 30 days) of alternating culture medium with or without glucose every 72h. For MCF10A, a significant increase in growth rate was observed over the entire period of 30 days in the presence of glucose, while glucose starvation or intermittent supply of glucose both completely suppressed growth over the whole period but maintained them at around seeding level (Fig 1E). For pII cells, a significant increase in growth rate was also observed over the 30 days when glucose was supplied while complete glucose starvation killed the cells from day 8 onwards (Fig 1F). Periodic supply of glucose to pII cells every 72h allowed limited growth, though to a much lesser extent than with a continuous supply of glucose. These data suggest that glucose starvation from the culture medium inhibited cell proliferation.

Fig 1

Effect of glucose starvation on cell proliferation.

pII (panel A) and YS1.2 (panel B) cell density was determined, using the MTT assay, at seeding day (day 0, hatched bars), and at days 1 and 4 (D 1 and D4) after culture in medium containing glucose (open bars) or without glucose (solid bars). The degree of proliferation of MDA-MB-231 and MCF10A as indicated in panels C-D was determined at day 4 (D 4) after culture in medium with (open bars) or without (closed bars) glucose. Panel E (MCF10A) and panel F (pII), show growth of cells (number of cells were measured using hemocytometer) cultured in + glucose medium (black line),—glucose medium (red line), or these two media alternated every 72 h (green line). Histobars represent means ± SEM of at least 3 independent determinations. * denotes significant difference from cells cultured in + glucose medium with p<0.05.

Effect of glucose concentration on breast cancer cell proliferation and motility

Since glucose starvation significantly inhibited cell proliferation, we determined whether growth could be stimulated by supplying increasing amounts of glucose. As shown in Fig 2, glucose supplementation to cancerous (A-C) and normal (D) breast cell lines increased their proliferative rate in a concentration-dependent manner. Supplying exogenous glucose to concentrations (17 mM) similar to those in DMEM containing glucose (+ glucose) restored cell proliferation to a similar degree. This effect was also seen with cell motility; glucose starvation significantly reduced ER–ve (MDA-MB-231 and pII, Fig 3A–3C) and ER +ve (YS 1.2, Fig 3D) breast cancer cell motility whereas it was enhanced by glucose supplementation in a concentration-dependent manner. These data suggest that glucose supplementation enhances cell proliferation and motility in a concentration-dependent manner.

Fig 2

Effect of glucose concentration on breast cancer cell proliferation.

Proliferation of pII (panel A), MDA-MB-231 (panel B), YS1.2 (panel C), and MCF10A (panel D) cells after culture for 4 days in + glucose medium (open bars) or–glucose medium supplemented with various concentrations of glucose as indicated (solid bars), was determined using the MTT assay. Histobars represent means ± SEM of at least 3 independent determinations. * denotes significant difference from cells cultured in—glucose medium, with p<0.05.

Fig 3

Effect of glucose concentration on breast cancer cell motility.

Cells were cultured to confluency in + glucose medium. The medium was then changed to–glucose medium + glucose additions as indicated. A scratch was made through the cell monolayer and the width measured immediately and after further 24h incubation. Panels A-B for MDA-MB-231 cells, panels C-D for pII cells, and panels E-F for YS1.2 cells. Histobars represent means ± SEM for each condition. * denotes significant difference from cells cultured in—glucose medium, with p<0.05.

Effect of glucose starvation on production of lactate

Herein, we wanted to determine whether extracellular lactate level is modulated in the ER -ve breast cancer cells pII when cultured in medium without glucose. Lactate was measured in the culture medium from the incubation of pII cells grown in medium with or without glucose for 24h. The data in Fig 4 shows that cells cultured in medium without glucose secreted almost no lactate, while cells cultured in medium containing glucose secreted lactate that reached concentrations of approximately 20 mM under the conditions examined.

Fig 4

Effect of glucose starvation on lactate levels.

Extracellular lactate level in pII cells upon culture in + glucose medium (open bar), or—glucose medium (solid bar) for 1 day was determined as described in Methods. Histobars represent means ± SEM of at least 3 independent determinations. * denotes significant difference from cells cultured in + glucose medium, with p<0.05.

Effect of adding glucose or lactate to glucose starved cells on their motility

Next, we wanted to determine the effect of supplying exogenous glucose to cells cultured in medium without glucose, and whether lactate can substitute for glucose in the culture medium to enhance cell motility. The data in Fig 5 show that the motility of pII cells (assessed using the wound closure assay) after 24h in medium without glucose was much reduced (panel B;—glucose,) compared to cells grown in medium with glucose (panel A; + glucose,); however, when incubation was continued for a further 24h after changing the—glucose medium to medium containing glucose or to glucose-free medium containing 20 mM lactate, the cells regained their motility (panel B). Combined data from 3 independent experiments is given in panel C.

Fig 5

Effect of glucose starvation on pII cell motility.

The degree of pII cell motility upon culture in + glucose medium (panel A),—glucose medium (panel B), -glucose medium for 24 h followed by culture in +glucose medium for another 24 h, or -glucose medium in the presence of 20 mM L-lactate was determined (panels B-C) as described in Methods. Histobars represent means ± SEM of at least 3 independent determinations. * denotes significant difference with p<0.05.

Effect of 2-deoxy glucose on cell proliferation and cell motility

2-DG is a D-glucose analogue which inhibits glycolysis through formation and intracellular accumulation of 2-deoxy-D-glucose-6-phosphate, a competitive inhibitor of hexokinase and glucose-6-phosphate isomerase [31]. The breast cancer cell lines were plated in culture medium with glucose and then after 24h exposed to increasing concentrations of 2-DG for 4 days. MTT assay performed on the cells showed that 2-DG dose-dependently inhibited cell proliferation in all cell lines, with significant decrease starting at concentrations from 0.5–1 mM and reaching substantial inhibition by 10 mM, the highest concentration tested (Fig 6). 2-DG also dose-dependently inhibited both ER +ve and ER–ve breast cancer cell motility (performed using scratch assay, Fig 7).

Fig 6

Effect of 2-deoxy glucose on cell proliferation.

Proliferation of the cell lines indicated was measured after 4 days of exposure to either vehicle or various concentrations of 2-DG, using the MTT assay. Histobars represent means ± SEM of at least 3 independent experiments. * denotes significant difference from vehicle-treated cells, with p<0.05.

Fig 7

Effect of 2-deoxy glucose on cell motility.

Motility of the YS1.2 (A), pII (B), and MDA-MB-231 (C) cells in response to treatment with various concentrations of 2-DG or vehicle, was measured using the wound healing assay. Histobars represent means ± SEM of at least 3 independent experiments. * denotes significant difference from vehicle treated cells, with p<0.05.

Glucose depletion significantly enhanced the anti-proliferative effects of paclitaxel and doxorubicin in breast cancer cell lines

We wanted to determine if glucose depletion enhances the sensitivity of paclitaxel or doxorubicin in inhibiting cell proliferation. Paclitaxel (Fig 8) and doxorubicin (Fig 9) treatment significantly reduced cell proliferation in a concentration dependent manner. There was a significant inhibition in pII cell proliferation at 1 μM paclitaxel, which was further increased to 90% with 10–100 μM (Fig 8A). For MDA-MB-231 cells, paclitaxel inhibited cell proliferation (by 50%) with 0.1 μM, which reached 98–99% inhibition with 1–100 μM (Fig 8B). For YS 1.2 cells, paclitaxel (0.1–100 μM) inhibited cell proliferation by 80% (Fig 8C). For MCF10A, 20–25% inhibition was seen with paclitaxel at concentrations of 0.1–1 μM and reached 50% inhibition at concentrations of 10–100 μM (Fig 8D). Of note, breast cancer cells were more sensitive to paclitaxel treatment when compared to the normal epithelial cell line MCF10A. Doxorubicin significantly inhibited pII cell proliferation (by 30%) at a concentration of 100 μM (Fig 9A). For MDA-MB-231 cells, doxorubicin significantly inhibited cell proliferation (by 80–99%) at all the concentrations used (Fig 9B). These data suggest that de novo resistant breast cancer cells are more sensitive to the anti-proliferative effect of doxorubicin when compared to the acquired endocrine resistant cells. For YS 1.2, there was a significant inhibition in cell proliferation (by 50%) at 1 μM, which further increased to 70–80% with 10–100 μM (Fig 9C). For MCF10A, there was a significant inhibition of cell proliferation (by 40–50%) at the concentrations used (Fig 9D).

Fig 8

Effect of glucose depletion on the anti-proliferative effects of paclitaxel in breast cancer cell lines.

The effect of paclitaxel on cell proliferation upon culture in +glucose medium (black line, taken as 100%) or -glucose medium plus 5 mM (red line), or 1.7 mM glucose (blue line) was determined at day 4 using the MTT assay. Histobars represent means ± SEM of at least 3 independent determinations. * denotes significant difference from cells treated with vehicle (normal saline), with p<0.05.

Fig 9

Effect of glucose depletion on the anti-proliferative effects of doxorubicin in breast cancer cell lines.

The effect of doxorubicin on cell proliferation upon culture in +glucose medium (black line, taken as 100%) or—glucose medium plus 5 mM (red line), or 1.7 mM glucose (blue line) was determined at day 4 using the MTT assay. Histobars represent means ± SEM of at least 3 independent determinations. * denotes significant difference from cells treated with vehicle (normal saline), with p<0.05.

To determine whether a synergistic/additive effect could be obtained in low glucose medium, we added these drugs to cells cultured in either medium with/without glucose [vehicle treated cells cultured in glucose containing medium (25mM) was taken as 100%] or supplemented with low (1.7 or 5 mM) glucose. When the tested cell lines were cultured in medium without glucose (for 4 days), there was no evidence of cell proliferation; adding either paclitaxel or doxorubicin was of no benefit (data not shown). Therefore, we next determined the effect of these two agents in a medium supplemented with low glucose.

For pII cells, glucose reduction significantly enhanced the anti-proliferative effects of both paclitaxel and doxorubicin when compared to treatment in the presence of glucose. The addition of 1.7 mM glucose had a greater enhancement effect than the higher amount. In the reduced glucose medium, treatment with 0.1 μM paclitaxel induced a broadly comparable degree of inhibition to that achieved with 100 μM in the presence of glucose in the culture medium (Fig 8A). Also, in reduced glucose medium, treatment with 0.1 μM of doxorubicin induced a greater degree of inhibition than 100 μM concentration in the presence of glucose in the culture medium (Fig 9A).

For MDA-MB-231 cells, glucose reduction enhanced the anti-proliferative effect of paclitaxel (but not doxorubicin) at 0.1 μM (Figs 8B and 9B) and higher concentrations of both agents abolished cell proliferation in all of the tested conditions. For YS1.2, higher degree of inhibition at all paclitaxel concentrations was achieved in cells cultured in glucose reduced medium (Fig 8C), and a similar degree of inhibition with doxorubicin was achieved with 0.1 μM in glucose reduced medium compared with 100 μM in glucose containing medium (Fig 9C). Similar effects were also seen with MCF10A cells (Figs 8D and 9D).

Discussion

In the current report, we present experimental evidence for involvement of glucose in cell proliferation and motility in several breast cell lines. The effect of glucose deprivation on cell proliferation was more profound in ER–ve when compared to ER +ve breast cancer cells. This might be explained by their higher proliferative rate which required higher glucose concentrations (Figs 1 and 6). Both of these processes were significantly enhanced by glucose in a concentration dependent manner in both cancer and normal cells. Conversely, they were inhibited by glucose starvation or competing out the glucose in culture medium by addition of the non-metabolizable analogue 2-DG. Furthermore, we observed a synergistic inhibitory effect on proliferation by combining glucose deprivation (even if applied periodically) with addition of two commonly used agents for breast cancer chemotherapy, paclitaxel and doxorubicin. In low glucose conditions, the concentration of both of these drugs could be reduced several-fold to achieve the same degree of inhibition seen in the high glucose medium. If this can be reproduced in vivo, it would greatly facilitate the utilization of these highly toxic agents by allowing much lower doses to be applied to achieve the same therapeutic effect. This would mean significant reduction in side effects and greater tolerance. Preliminary experiments to explore the mechanism whereby glucose stimulates growth and motility suggest that it may, at least in part, be mediated through lactate secreted into the extracellular environment.

Hyperglycemia has been shown to contribute to enhanced breast cancer cell proliferation, metastasis and chemotherapy resistance [8, 32–34]. Furthermore, glucose and other factors involved in glucose metabolism such as insulin and insulin like growth factors enhance breast cancer cell proliferation and contribute to breast cancer development [35-38]. High glucose concentration (25–50 mM) significantly enhanced MCF-7 and T47D cell proliferation and decreased cell apoptosis and necrosis, while low glucose concentration (2.5 mM) induced cell apoptosis and necrosis [37]. In addition, high glucose concentration (25 mM) in the culture medium of MCF-7 and T47D enhanced IGF-1 induced cell growth; this was not observed when cells were cultured in low glucose containing medium (5 mM) [39]. These data are in agreement with our own observations, where the addition of increasing concentration of glucose to the culture medium significantly enhanced breast cancer cell proliferation (Fig 2) and motility (Fig 3). Adding 2-DG was effective in blocking both proliferation and motility. Several previous reports have demonstrated similar effects of 2-DG on breast cancer cells, with reduction in their migration [40] and proliferation [41-45]. In another recent report, enhanced glucose uptake was correlated with enhanced invasiveness of several breast cancer cell lines, whereas low doses of 2-DG (1 mM) significantly reduced their invasive capacity [46]. Our data is consistent with these reports, in the same concentration range (0.5–1 mM). Chen et al [47] reported that short term glucose deprivation (24 h) in various breast cancer cell lines induced cell death, which was higher in MDA-MB-231 than MCF-7 cells, in part through enhanced AMPK phosphorylation. This was also observed in another report using MCF-7 and T47D cells [48]. We did not see much difference in cell proliferation at 24 h; it was evident at day 4 of glucose starvation in both the cancer lines as well as the normal cells. Periodic re-supply of glucose (every 72 h; Fig 1E and 1F) maintained the cells at the seeding number for MCF10A and facilitated partial growth for pII cells.

The unresolved issue of why cancer cells prefer anaerobic metabolism (and hence the high glucose requirement) has given rise to speculation that this might somehow confer advantages in growth through increased production of precursors of nucleic acid biosynthesis through the pentose phosphate shunt and faster (if less efficient) production of ATP [49]. The accumulation of lactate as the end product of glucose catabolism could also be an important factor but has so far not received quite as much attention. To prevent cellular acidosis, excessive lactate is thought to be secreted into the extracellular environment from where it has been proposed that it may be taken up and used as a metabolic substrate by other aerobically active cells by re-conversion to pyruvate [50]. The concurrent acidification of the extracellular space by co-transport of H+ with the lactate extrusion is where other researchers have focused, leading to suggestions that these acidic conditions promote migration/metastasis [51, 52]. An alternative possibility is that the increased aggressiveness is actually not due to the lowered pH but instead to the elevated extracellular lactate that is formed as a result of excessive glycolytic activity. Thus, the effect of glucose in promoting cancer cell proliferation/motility, which we and many others have observed, could be mediated by lactate. Providing lactate to pII cells deprived of glucose (without any change in pH) had the same effect as giving back glucose. It is uncertain how exactly extracellular lactate exerts its effect although we do have some preliminary data suggesting modulation in the activity of signaling pathways; however, we do not think there is any direct connection between this and the action of Dox/Paclitaxel. It is simply that lactate inhibition allows use of much lower concentrations of CTX drugs (to ‘finish off’ the cancer cells), and that this could be simply achieved by a glucose restrictive diet. We are currently studying this phenomenon further. Somewhat surprisingly, there was no clear difference in dependence on glucose between the cancer cell lines and the normal MCF10A; we had expected the latter to have been less reliant on glucose and possibly have been able to utilise other substrates, principally the glutamine presents in the culture medium, for energy generation through oxidative phosphorylation. Perhaps this highlights a disadvantage of in vitro models. In vivo, normal cells are known to revert to utilisation of fatty acids under glucose limiting conditions [53].

As already discussed, cancer cells mainly utilize aerobic glycolysis as the main route of glucose metabolism after glucose entry into cells through glucose transporters. This results in the generation of various glucose metabolites which may enter other metabolic pathways such as the serine/glycine and pentose phosphate metabolic pathways (termed non-glycolysis metabolic pathways). All the products generated through these various pathways play an important role in cancer metabolism, progression, and metastasis [54, 55]. The pentose shunt provides precursors for nucleic acid biosynthesis that is important for cancer cells to proliferate. It was demonstrated that the expression profile of serine/glycine metabolic pathway is unique to the molecular subtype of breast cancer, with high activity in HER-2 [56] and triple negative types [57], which is correlated with poor clinical prognosis [58]. In addition, enhanced expression profile of the pentose phosphate pathway-related enzymes such is 6PGDH and TKT is also evident in breast cancer [59, 60], especially in HER-2 and triple negative types [61], which is again associated with poor clinical prognosis [62-64].

The other major aspect of this study was to determine whether glucose deprivation could be used to enhance the effectiveness of chemotherapy. Both paclitaxel and doxorubicin are commonly used to kill cancer cells but their wider toxicity at the necessary therapeutically high concentration also affects some normal tissues such as immune, gut and hair cells. Our data shows that if they are added to glucose starved cells, their effective concentration can be very significantly lowered, giving obvious advantages. As a therapeutic approach, depriving the body completely of glucose would of course have serious physiological consequences but lowering it temporarily only whilst chemotherapy was being administered might be tolerated. One way to achieve this situation is through the use of ketogenic diet (KD) for a short period of time. The effect of KD on metabolic parameters is variable depending on the composition of protein, fat, and carbohydrates as well as on the duration of its use. Some reports suggested that KD was shown to reduce fasting blood glucose and HbA1c levels in patients with diabetes [65-68], in normal subjects [69] and in rodents [70]. Interestingly, KD was also shown to reduce glucose metabolism in rodents and humans [71-73]. There is extensive clinical evidence indicating that KD is well tolerated in patients with various forms of cancer, resulting in improvement in quality of life with no serious adverse events or toxicity reported [74-87]. KD was shown to enhance the anti-tumor effects of various agents as well as when combined with radiotherapy. Combination of KD with bevacizumab in an orthotopic U87MG glioblastoma model in nude mice increased survival rate when compared with bevacizumab monotherapy [19]. Two reports suggested that KD significantly enhanced the anti-tumor and anti-angiogenic effects of metronomic cyclophosphamide in neuroblastoma xenografts in a CD1-nu mouse model [88, 89]. Furthermore, another report demonstrated that KD combination with radiation or carboplatin led to slower tumor growth in mice bearing NCI-H292 and A549 lung cancer xenografts; in part through increased oxidative damage mediated by lipid peroxidation [90]. KD was also shown to improve responses to several PI3K inhibitors in tumors with a wide range of genetic aberrations such as in patient-derived xenograft models of advanced endometrial adenocarcinoma (harboring a PTEN deletion and PIK3CA mutation), bladder cancer (FGFR-amplified), in syngeneic allograft models of PIK3CA mutant breast cancer and in a MLL-AF9 driven acute myeloid leukemia. Combination of KD improved the efficacy of several agents which target the PI3K pathway through inhibition of insulin feedback (which limits the efficacy of these agents) in part through decreased cell proliferation and increased apoptosis [17].

Effect of glucose starvation on cell apoptosis.

pII (solid bars) and YS1.2 (open bars) were cultured for 1 and 4 days in medium containing glucose (+ glucose) or without glucose (- glucose). Cell apoptosis was determined by flow cytometry using Annexin-V/7AAD staining as described in the methods. Histobars represent means ± SEM of at least 3 independent determinations.

(TIF)

Click here for additional data file.

26 May 2022

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This work was supported by Kuwait University Research Sector grant PT02/18. Parts of this work were supported by grant SRUL02/13 to the Research Unit for Genomics, Proteomics and Cellomics Studies (OMICS), Kuwait University.

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This work was supported by Kuwait University Research Sector grant PT02/18. Parts of this work were supported by grant SRUL02/13 to the Research Unit for Genomics, Proteomics and Cellomics Studies (OMICS), Kuwait University.

the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Reviewer #1: Yes

Reviewer #2: Partly

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: The authors examined the effect of glucose deprivation on growth and proliferation of breast cells, and the potentiation of Glucose deprivation on anti-proliferative effects of paclitaxel and doxorubicin. The novalty of this manuscript should be improved by exploring the underlying mechanism. As such, it still has some clinical value for drug treatment of tumors. A few of suggestions are shown below:

1. If possible, the author should provide some lines of supportive evidence from animal experiments. However, it is hard to set up a low-glucose condition, because tumor cells have a strong ability of glucose uptake to enter the glycolysis.

2. in Figure 8, different concentrations of 2-DG treatment caused the similar effects to those obtained from Glucose deprivation. Also, addition of lactate or pyruvate could offset the effect of glucose deprivation.

3. The authors should provide some mechanistic evidence to support their conclusion.

Reviewer #2: The manuscript: Glucose deprivation reduces proliferation and motility, and enhances the anti-proliferative effects of paclitaxel and doxorubicin in breast cell line in vitro, brings information already available in the literature on the effects of glucose metabolism on tumor and normal cell proliferation. Tumor cells produce a high level of reactive oxygen species compared to normal cells due to the increased activation of various metabolic pathways. Glycolysis by the Warburg effect maintains redox homeostasis by being independent of mitochondrial oxidative phosphorylation that produces a large amount of ROS, increasing metabolic secondary pathways, NADPH, G6PD and 6-Phosphogluconate dehydrogenase, which produces an effect on tumor metabolic reprogramming.

The data presented on the cytotoxic activity of the conditions of glucose deprivation, addition of lactate, DG2gly, should be normalized, since the data are presented in optical density values ​​and do not represent the biological effects after the different experimental conditions. Thus information about the effects of cytotoxicity can be better interpreted and included in the discussion. The data presented in the supplementary material does not demonstrate the antiproliferative effects of the metabolic effects of glucose deprivation, since no increase in cells in apoptosis or necrosis was found.

Include include in the discussion other aspects of non-glycolytic metabolism (Non-glycolysis Glucose Metabolism Pathway in Breast Cancer). The authors could apply a predictive pharmacological test to demonstrate the synergistic effects of chemotherapeutic combinations in deprivation or supplementation conditions, such as additive, anatoagonic or synergistic effects.

Reviewer #3: Minor Issues:

Materials and methods- Cell lines- second paragraph:

* The authors wrote 100 U/Ml penicillin should be corrected to 100 U/mL

* RPMI medium used (Cat# R1383) contains L-glutamine (0.3 g/L) and you also added L-glutamine as a supplement.

This could be another source of energy for the cells. L-glutamine serves as an auxiliary energy source, especially when

cells are rapidly dividing.

* Why the non-essential amino acids were added to the culture medium? Published research reported that non-essential

amino acids attenuate apoptosis.

* According to the manufacturer’s instructions the concentration of cells for Annexin V apoptosis experiment is 1 x 10*6

cells/ml, why the authors used a concentration of 5 x 10*6 cells/ml.

* Why the authors did not use the same medium for the experiments with glucose and those without glucose?

Figure 1: To denote a significant difference, please insert a line above the bars that are targeted and add a * above the line.

This will make it easier for the readers to follow.

Figure 1: I think the X axis in the figure can be labelled in a more appropriate way.

Figure 3: It is not mentioned in the legend and neither on the figure the type of cells in Fig 3C and Fig 3D. There are also

two graphs which are not mentioned and should be labelled with E and F

Figure 6, Figure 7, Figure 8 & Figure 9: What does the authors mean by “vehicle”?

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Mazen Alzaharna

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5 Jun 2022

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Thank you for stating the following in the Acknowledgments Section of your manuscript:

This work was supported by Kuwait University Research Sector grant PT02/18. Parts of this work were supported by grant SRUL02/13 to the Research Unit for Genomics, Proteomics and Cellomics Studies (OMICS), Kuwait University.

Please note that funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:

This work was supported by Kuwait University Research Sector grant PT02/18. Parts of this work were supported by grant SRUL02/13 to the Research Unit for Genomics, Proteomics and Cellomics Studies (OMICS), Kuwait University.

the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

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Please amend your list of authors on the manuscript to ensure that each author is linked to an affiliation. Authors’ affiliations should reflect the institution where the work was done (if authors moved subsequently, you can also list the new affiliation stating “current affiliation:….” as necessary).

Response: all the authors have the same affiliation which is: Faculty of Pharmacy, Kuwait University, Safat 13110, Kuwait.

Review Comments to the Author

Reviewer #1:

The authors examined the effect of glucose deprivation on growth and proliferation of breast cells, and the potentiation of Glucose deprivation on anti-proliferative effects of paclitaxel and doxorubicin. The novelty of this manuscript should be improved by exploring the underlying mechanism. As such, it still has some clinical value for drug treatment of tumors. A few of suggestions are shown below:

1. If possible, the author should provide some lines of supportive evidence from animal experiments. However, it is hard to set up a low-glucose condition because tumor cells have a strong ability of glucose uptake to enter the glycolysis.

Response: We agree with the reviewer regarding the clinical value of our presented data in terms of reducing the dose of chemotherapeutic agents and their dose-dependent side effects when combined with low-glucose regimen. Our results suggest that it may not be necessary to induce any severe form of glucose deprivation in vivo but just a substantial reduction, which can be achieved. Regarding the underlying mechanism, we have actually discussed this aspect in the last paragraph of the Discussion section of the manuscript citing studies using ketogenic diet. Please see below:

As a therapeutic approach, depriving the body completely of glucose would of course have serious physiological consequences but lowering it temporarily only whilst chemotherapy was being administered might be tolerated. One way to achieve this situation is through the use of ketogenic diet (KD) for a short period of time. The effect of KD on metabolic parameters is variable depending on the composition of protein, fat, and carbohydrates as well as on the duration of its use. Some reports suggested that KD was shown to reduce fasting blood glucose and HbA1c levels in patients with diabetes [1-4], in normal subjects [5] and in rodents [6]. Interestingly, KD was also shown to reduce glucose metabolism in rodents and humans [7-9]. There is extensive clinical evidence indicating that KD is well tolerated in patients with various forms of cancer, resulting in improvement in quality of life with no serious adverse events or toxicity reported [10-23]. KD was shown to enhance the anti-tumor effects of various agents as well as when combined with radiotherapy. Combination of KD with bevacizumab in an orthotopic U87MG glioblastoma model in nude mice increased survival rate when compared with bevacizumab monotherapy[24]. Two reports suggested that KD significantly enhanced the anti-tumor and anti-angiogenic effects of metronomic cyclophosphamide in neuroblastoma xenografts in a CD1-nu mouse model [25, 26]. Furthermore, another report demonstrated that KD combination with radiation or carboplatin led to slower tumor growth in mice bearing NCI-H292 and A549 lung cancer xenografts; in part through increased oxidative damage mediated by lipid peroxidation [27]. KD was also shown to improve responses to several PI3K inhibitors in tumors with a wide range of genetic aberrations such as in patient-derived xenograft models of advanced endometrial adenocarcinoma (harboring a PTEN deletion and PIK3CA mutation), bladder cancer (FGFR-amplified), in syngeneic allograft models of PIK3CA mutant breast cancer and in a MLL-AF9 driven acute myeloid leukemia. Combination of KD improved the efficacy of several agents which target the PI3K pathway through inhibition of insulin feedback (which limits the efficacy of these agents) in part through decreased cell proliferation and increased apoptosis [28].

We also showed that glucose deprivation did not enhance cell apoptosis as indicated in Supplementary Figure 1, suggesting that reduced cell growth under deprived glucose conditions is not due to enhanced apoptotic machinery. In addition, we have published a paper in Frontiers of Pharmacology providing preliminary evidence for the signaling molecules which are modulated upon lactate supplementation to breast cancer cells; this is also related to glucose metabolism (PMID: 34744727).

We are currently initiating further studies in which we aim to perform genomic and proteomic profiling of various markers involved in breast cancer cell proliferation, motility, and invasion to be tested under conditions of glucose or lactate deprivation, and upon exogenous lactate supplementation to breast cancer cells to better understand the underlying mechanism related to this phenomenon.

2. In Figure 8, different concentrations of 2-DG treatment caused the similar effects to those obtained from Glucose deprivation. Also, addition of lactate or pyruvate could offset the effect of glucose deprivation. The authors should provide some mechanistic evidence to support their conclusion.

Response: Presumably the reviewer is referring to Figures 6 and 7 which show 2-DG treatment dose-dependently reduced breast cancer cell proliferation and motility. As indicated in the results section of the manuscript,

Effect of 2-deoxy glucose on cell proliferation and cell motility

2-DG is a D-glucose analogue which inhibits glycolysis through formation and intracellular accumulation of 2-deoxy-D-glucose-6-phosphate, a competitive inhibitor of hexokinase and glucose-6-phosphate isomerase [29].

We used 2-DG to confirm by another method [other than taking glucose out of the culture medium (as shown in Figures 1 and 5)] that glucose deprivation reduced breast cancer cell proliferation and motility. This was a confirmatory experiment to support our findings. We provided mechanistic explanation in the Discussion section of the manuscript of how glucose deprivation can reduce cell motility and proliferation. Please see below:

Several previous reports have demonstrated similar effects of 2-DG on breast cancer cells, with reduction in their migration [30] and proliferation [31-35]. In another recent report, enhanced glucose uptake was correlated with enhanced invasiveness of several breast cancer cell lines, whereas low doses of 2-DG (1 mM) significantly reduced their invasive capacity [36]. Our data is consistent with these reports, in the same concentration range (0.5-1 mM). Chen et al [37] reported that short term glucose deprivation (24 h) in various breast cancer cell lines induced cell death, which was higher in MDA-MB-231 than MCF-7 cells, in part through enhanced AMPK phosphorylation. This was also observed in another report using MCF-7 and T47D cells [38]. We did not see much difference in cell proliferation at 24 h; it was evident at day 4 of glucose starvation in both the cancer lines as well as the normal cells. Periodic re-supply of glucose (every 72 h; Fig 1 E-F) maintained the cells at the seeding number for MCF10A and facilitated partial growth for pII cells.

We also showed that glucose deprivation did not enhance cell apoptosis as indicated in Supplementary Figure 1, suggesting that reduced cell growth under deprived glucose conditions is not due to enhanced apoptotic machinery. In addition, we have a recent publication in Frontiers of Pharmacology providing preliminary evidence for the signaling molecules which are modulated upon lactate supplementation to breast cancer cells; this is also related to glucose metabolism (PMID: 34744727). We showed that cells treated with lactate (20 mM) had increased phosphorylation of ERK1/2 but did not show any change in either p38 MAPK or AKT phosphorylation. Also, the expression profile of focal adhesion kinase (FAK) was not modulated by lactate treatment. Interestingly, E-cadherin expression was significantly reduced by lactate treatment which might lead to loss of cell-cell connection and enhanced degree of motility, which was observed in cancer cells upon lactate supplementation (PMID: 34744727).

We are currently initiating further studies in which we aim to perform genomic and proteomic profiling of various markers involved in breast cancer cell proliferation, motility, and invasion to be tested under conditions of glucose or lactate deprivation, and upon exogenous lactate supplementation to breast cancer cells to better understand the underlying mechanism related to this phenomenon.

Reviewer #2:

The manuscript: Glucose deprivation reduces proliferation and motility, and enhances the anti-proliferative effects of paclitaxel and doxorubicin in breast cell line in vitro, brings information already available in the literature on the effects of glucose metabolism on tumor and normal cell proliferation. Tumor cells produce a high level of reactive oxygen species compared to normal cells due to the increased activation of various metabolic pathways. Glycolysis by the Warburg effect maintains redox homeostasis by being independent of mitochondrial oxidative phosphorylation that produces a large amount of ROS, increasing metabolic secondary pathways, NADPH, G6PD and 6-Phosphogluconate dehydrogenase, which produces an effect on tumor metabolic reprogramming.

The data presented on the cytotoxic activity of the conditions of glucose deprivation, addition of lactate, DG2gly, should be normalized, since the data are presented in optical density values and do not represent the biological effects after the different experimental conditions. Thus, information about the effects of cytotoxicity can be better interpreted and included in the discussion.

Response: Presumably the reviewer is highlighting the manner in which results for MTT assay are presented in Figures 1, 2, and 6. It is quite common practice for MTT data to be presented directly as OD values rather than converting into cell numbers which would need a standard curve each time with different cell numbers. This way of presentation would only change the units in the Y axis (from OD to cell number) but the histobars would be exactly the same relative to each other. We have published several manuscripts where we described MTT data in terms of OD readings (PMID: 34744727, PMID: 31980706, PMID: 30365135, PMID: 28276317, PMID: 26718772). Examples of recent papers where other authors have similarly presented MTT data as OD readings are PMID: 34951409, PMID: 34929154, PMID: 34916844.

Having said that, we have actually also included cell number information at Day 0 (hatched bar) in Figure 1 A-D, and Figure 6 A-D, and at Day 0 in Figure 1 E-F where the number of cells were measured using a hemocytometer as described in the Methods section.

Regarding MTT data presented in Figures 8-9, we measured the degree of inhibition of cell proliferation by paclitaxel or doxorubicin when cells were cultured in medium with no added glucose, low glucose 1.7-5 mM, or high glucose (+ glucose medium, 25 mM). Since the degree of cell proliferation is variable when the cells were cultured in medium with different glucose concentrations (1.7, 5, or 25 mM), we therefore normalized these data by taking the vehicle as 100% for each condition and then compared the degree of inhibition of cell proliferation induced by the addition of either paclitaxel or doxorubicin with its own vehicle. These results are extensively discussed in the manuscript. Please see below:

Glucose depletion significantly enhanced the anti-proliferative effects of paclitaxel and doxorubicin in breast cancer cell lines

We wanted to determine if glucose depletion enhances the sensitivity of paclitaxel or doxorubicin in inhibiting cell proliferation. Paclitaxel (Fig 8) and doxorubicin (Fig 9) treatment significantly reduced cell proliferation in a concentration dependent manner. There was a significant inhibition in pII cell proliferation at 1 µM paclitaxel, which was further increased to 90% with 10-100 µM (Fig 8 A). For MDA-MB-231 cells, paclitaxel inhibited cell proliferation (by 50%) with 0.1 µM, which reached 98-99% inhibition with 1-100 µM (Fig 8 B). For YS 1.2 cells, paclitaxel (0.1-100 µM) inhibited cell proliferation by 80 % (Fig 8 C). For MCF10A, 20-25% inhibition was seen with paclitaxel at concentrations of 0.1-1 µM and reached 50% inhibition at concentrations of 10-100 µM (Fig 8 D). Of note, breast cancer cells were more sensitive to paclitaxel treatment when compared to the normal epithelial cell line MCF10A. Doxorubicin significantly inhibited pII cell proliferation (by 30%) at a concentration of 100 µM (Fig 9 A). For MDA-MB-231 cells, doxorubicin significantly inhibited cell proliferation (by 80-99%) at all the concentrations used (Fig 9 B). These data suggest that de novo resistant breast cancer cells are more sensitive to the anti-proliferative effect of doxorubicin when compared to the acquired endocrine resistant cells. For YS 1.2, there was a significant inhibition in cell proliferation (by 50%) at 1 µM, which further increased to 70-80% with 10-100 µM (Fig 9 C). For MCF10A, there was a significant inhibition of cell proliferation (by 40-50%) at the concentrations used (Fig 9 D).

To determine whether a synergistic/additive effect could be obtained in low glucose medium, we added these drugs to cells cultured in either medium without glucose or supplemented with low (1.7 or 5 mM) glucose. When the tested cell lines were cultured in medium without glucose (for 4 days), there was no evidence of cell proliferation; adding either paclitaxel or doxorubicin was of no benefit (data not shown). Therefore, we next determined the effect of these two agents in a medium supplemented with low glucose.

For pII cells, glucose reduction significantly enhanced the anti-proliferative effects of both paclitaxel and doxorubicin when compared to treatment in the presence of glucose. The addition of 1.7 mM glucose had a greater enhancement effect than the higher amount. In the reduced glucose medium, treatment with 0.1 µM paclitaxel induced a broadly comparable degree of inhibition to that achieved with 100 µM in the presence of glucose in the culture medium (Fig 8 A). Also, in reduced glucose medium, treatment with 0.1 µM of doxorubicin induced a greater degree of inhibition than 100 µM concentration in the presence of glucose in the culture medium (Fig 9 A).

For MDA-MB-231 cells, glucose reduction enhanced the anti-proliferative effect of paclitaxel (but not doxorubicin) at 0.1 µM (Fig 8 B and 9 B) and higher concentrations of both agents abolished cell proliferation in all of the tested conditions. For YS1.2, higher degree of inhibition at all paclitaxel concentrations was achieved in cells cultured in glucose reduced medium (Fig 8 C), and a similar degree of inhibition with doxorubicin was achieved with 0.1 µM in glucose reduced medium compared with 100 µM in glucose containing medium (Fig 9 C). Similar effects were also seen with MCF10A cells (Fig 8 D and 9 D).

The data presented in the supplementary material does not demonstrate the antiproliferative effects of the metabolic effects of glucose deprivation, since no increase in cells in apoptosis or necrosis was found.

Response:

Inhibition of proliferation is simply blocking further growth. It does not have to involve cell death (i.e. apoptosis). We have provided mechanistic explanations in the Discussion section of the manuscript for how glucose deprivation can reduce cell motility and proliferation. Please see below:

Several previous reports have demonstrated similar effects of 2-DG on breast cancer cells, with reduction in their migration [30] and proliferation [31-35]. In another recent report, enhanced glucose uptake was correlated with enhanced invasiveness of several breast cancer cell lines, whereas low doses of 2-DG (1 mM) significantly reduced their invasive capacity [36]. Our data is consistent with these reports, in the same concentration range (0.5-1 mM). Chen et al [37] reported that short term glucose deprivation (24 h) in various breast cancer cell lines induced cell death, which was higher in MDA-MB-231 than MCF-7 cells, in part through enhanced AMPK phosphorylation. This was also observed in another report using MCF-7 and T47D cells [38]. We did not see much difference in cell proliferation at 24 h; it was evident at day 4 of glucose starvation in both the cancer lines as well as the normal cells. Periodic re-supply of glucose (every 72 h; Fig 1 E-F) maintained the cells at the seeding number for MCF10A and facilitated partial growth for pII cells.

We also showed that glucose deprivation did not enhance cell apoptosis as indicated in Supplementary Figure 1, suggesting that reduced cell growth under deprived glucose conditions is not due to enhanced apoptotic activity. In addition, we have a recent publication in Frontiers of Pharmacology providing preliminary evidence for the signaling molecules which are modulated upon lactate supplementation to breast cancer cells; this is also related to glucose metabolism (PMID: 34744727).

We are currently initiating further studies in which we aim to perform genomic and proteomic profiling of various markers involved in breast cancer cell proliferation, motility, and invasion to be tested under conditions of glucose or lactate deprivation, and upon exogenous lactate supplementation to breast cancer cells to better understand the underlying mechanism related to this phenomenon.

Include in the discussion other aspects of non-glycolytic metabolism (Non-glycolysis Glucose Metabolism Pathway in Breast Cancer).

Response: The following paragraph is now included in the Discussion section of the revised version of the manuscript to mention these. Please see below:

As already discussed, cancer cells mainly utilize aerobic glycolysis as the main route of glucose metabolism after glucose entry into cells through glucose transporters. This results in the generation of various glucose metabolites which may enter other metabolic pathways such as the serine/glycine and pentose phosphate metabolic pathways (termed non-glycolysis metabolic pathways). All the products generated through these various pathways play an important role in cancer metabolism, progression, and metastasis [39, 40]. The pentose shunt provides precursors for nucleic acid biosynthesis that is important for cancer cells to proliferate. It was demonstrated that the expression profile of serine/glycine metabolic pathway is unique to the molecular subtype of breast cancer, with high activity in HER-2 [41] and triple negative types [42], which is correlated with poor clinical prognosis [43]. In addition, enhanced expression profile of the pentose phosphate pathway-related enzymes such is 6PGDH and TKT is also evident in breast cancer [44, 45], especially in HER-2 and triple negative types [46], which is again associated with poor clinical prognosis [47-49].

The authors could apply a predictive pharmacological test to demonstrate the synergistic effects of chemotherapeutic combinations in deprivation or supplementation conditions, such as additive, antagonism or synergistic effects.

Response: It is not quite clear what the Reviewer means by “predictive pharmacological test” However, the MTT data presented in Figures 8-9 show the degree of inhibition in cell proliferation by paclitaxel or doxorubicin when cells were cultured in medium with no added glucose, low glucose 1.7-5 mM, or high glucose (+ glucose medium, 25 mM). Since the degree of cell proliferation was variable when the cells were cultured in medium with different glucose concentrations (1.7, 5, or 25 mM), we therefore normalized these data by taking the vehicle as 100% for each condition and then compared the degree of inhibition of cell proliferation induced by the addition of either paclitaxel or doxorubicin with its own vehicle. Since we normalized these data, we cannot calculate the synergistic/additive effects. We tried to represent these data in several different ways, but it became too complicated to present, and this way was the most understandable and clear to the reader.

Reviewer #3:

Minor Issues:

Materials and methods- Cell lines- second paragraph:

The authors wrote 100 U/Ml penicillin should be corrected to 100 U/mL

Response: done.

RPMI medium used (Cat# R1383) contains L-glutamine (0.3 g/L) and you also added L-glutamine as a supplement. This could be another source of energy for the cells. L-glutamine serves as an auxiliary energy source, especially when cells are rapidly dividing. Why the non-essential amino acids were added to the culture medium? Published research reported that non-essential amino acids attenuate apoptosis.

Response: It is not uncommon practice to add supplements to the culture medium for growth of cell lines to optimize their growth, and it is something we do routinely. Sometimes we only add L-glutamine and not the amino acids and it does not seem to make much difference. Regarding LO-glutamine, we have indeed looked to see whether it can support cell growth in low glucose conditions but our experiments in this regard have been rather inconclusive and we have no clear indication that L-glutamine can serve as an alternative energy source although that was our initial expectation. So, we did not alter our culture conditions in that regard as cells do depend on L-glutamine for other nutritional purposes.

According to the manufacturer’s instructions the concentration of cells for Annexin V apoptosis experiment is 1 x 10*6 cells/ml, why the authors used a concentration of 5 x 10*6 cells/ml.

Response: This was a typographical error. This is now corrected in the new version of the manuscript (1x106 cells/ml).

Why the authors did not use the same medium for the experiments with glucose and those without glucose?

Response: We routinely use DMEM, but we were unable to procure DMEM without glucose, and therefore we used RPMI medium that was available without glucose for the glucose deprivation experimental conditions. In fact, we have compared cell behavior when cultured in either DMEM or RPMI media and there appears to be no significant difference.

Figure 1: To denote a significant difference, please insert a line above the bars that are targeted and add a * above the line. This will make it easier for the readers to follow. I think the X axis in the figure can be labelled in a more appropriate way.

Response: A line above the bars is now included in the NEW Fig 1. We would like to keep the X axis label as it is for consistency with the other figures in the manuscript.

Figure 3: It is not mentioned in the legend and neither on the figure the type of cells in Fig 3C and Fig 3D. There are also two graphs which are not mentioned and should be labelled with E and F.

Response: all the suggested changes are now included in the NEW Fig 3, and Fig 3 legend.

Figure 6, Figure 7, Figure 8 & Figure 9: What does the authors mean by “vehicle”?

Response: “Vehicle” is the common term used to refer to the diluent used to dissolve/dilute drugs. In this case for 2-DG, doxorubicin, or paclitaxel the vehicle was saline. This is now clarified in Fig 7 and 8 legends in the revised version of the manuscript.

Note: We also recognized a typo in the Y-axis in Fig 7, panel B. This is now corrected in the NEW Fig 7.

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21 Jun 2022

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors have adequately modified their manuscript. Besides, they also carefully answers the questions. Thereby, this paper could be acceptable for publication in this journal.

Reviewer #2: The authors partially performed the suggested corrections, but the presentation of the cytotoxicity graphs compromises the veracity of the data due to the different optical densities existing between the cells.

The initial difference between the control groups exceeds more than 40%, as suggested the data should be normalized.

The different optical densities found in the graphs reflect the metabolic differences between tumor cell types.

After normalization of optical densities, the values must be expressed in Percentage of Viability (%) in relation to the group of untreated (control cells).

I suggest using a program to normalize the data, for example the Graphic Pad Prism, or similar

Normalize the data to convert Y values from different data sets to a common scale. If you can't get Normalize to do what you want, take a look at the Remove Baseline analysis which can do some kinds of normalizing.

https://www.graphpad.com/scientific-software/prism/

Authors must correct the data presented in the way they are described, compromising their veracity

Reviewer #3: The authors have responded to the addressed comments afrom my sidend corrected the manuscript accordingly. No other comments

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Reviewer #1: No

Reviewer #2: Yes: Prof. Durvanei Augusto Maria

Reviewer #3: No

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29 Jun 2022

Response to reviewer comments

Reviewer #1: The authors have adequately modified their manuscript. Besides, they also carefully answer the questions. Thereby, this paper could be acceptable for publication in this journal.

Response: we thank the reviewer for the positive comment.

Reviewer #2: The authors partially performed the suggested corrections, but the presentation of the cytotoxicity graphs compromises the veracity of the data due to the different optical densities existing between the cells. The initial difference between the control groups exceeds more than 40%, as suggested the data should be normalized. The different optical densities found in the graphs reflect the metabolic differences between tumor cell types. After normalization of optical densities, the values must be expressed in Percentage of Viability (%) in relation to the group of untreated (control cells).

I suggest using a program to normalize the data, for example the Graphic Pad Prism, or similar

Normalize the data to convert Y values from different data sets to a common scale. If you can't get Normalize to do what you want, take a look at the Remove Baseline analysis which can do some kinds of normalizing.

https://www.graphpad.com/scientific-software/prism/

Authors must correct the data presented in the way they are described, compromising their veracity

Response: We thank the reviewer for the valid comments. As per the recommendation we have modified the data presented in Fig 8 and 9 by considering the variability in the seeding density for vehicle treated cells with different glucose concentration in the culture medium. In the NEW modified Figs 8 and 9, vehicle treated cells cultured in glucose containing medium (25 mM, Black lines) is taken as 100% and the data are normalized accordingly.

The appropriate wording changes have been made in the ‘Results’ and ‘figure legends’ sections in the marked version of the manuscript.

We trust this clarifies the data and is what the Reviewer had in mind to be done.

Reviewer #3: The authors have responded to the addressed comments from my side and corrected the manuscript accordingly. No other comments

Response: we thank the reviewer for the positive comment.

Submitted filename: Response to reviewer comments.docx

Click here for additional data file.

5 Jul 2022

6 Jul 2022

Response to editor and reviewer comments

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Response: We do not understand the editorial remark concerning the references, as no issue was raised by any of the Reviewers in this context. Is this perhaps a new routine requirement by the journal to ensure that no retracted papers are cited?. We have double-checked all the references cited in this manuscript and to the best of our knowledge they are correctly cited and do not include any retracted papers that we are aware of. We actually checked each cited paper in PubMed and none of them were retracted.

Reviewer #2:

Old comments:

The authors partially performed the suggested corrections, but the presentation of the cytotoxicity graphs compromises the veracity of the data due to the different optical densities existing between the cells. The initial difference between the control groups exceeds more than 40%, as suggested the data should be normalized. The different optical densities found in the graphs reflect the metabolic differences between tumor cell types. After normalization of optical densities, the values must be expressed in Percentage of Viability (%) in relation to the group of untreated (control cells).

I suggest using a program to normalize the data, for example the Graphic Pad Prism, or similar

Normalize the data to convert Y values from different data sets to a common scale. If you can't get Normalize to do what you want, take a look at the Remove Baseline analysis which can do some kinds of normalizing.

New comments:

To the authors of the manuscript, sorry for the insistence, the cell viability data must be corrected.

In the forwarded version, no changes were made to the figures. Therefore, I do not recommend publication, since the data presented were not analyzed and presented properly.

Response:

We are very surprised by the reviewer’s comments regarding the cell viability data. In fact, we have carefully addressed all the comments previously raised by this and the other reviewers. We have responded to Reviewer two's comments regarding cell viability data presentation in Figures 8 and 9. There is some misunderstanding as we clearly submitted corrected figures as required by this reviewer. We are including in this letter the old and new versions of both figures to demonstrate the differences in the data presentation. We have considered the initial difference between the control (vehicle) groups cultured with different glucose concentration in the culture medium. In the NEW modified Figs 8 and 9, vehicle treated control cells cultured in glucose containing medium (25 mM, Black lines) is taken as 100% and the data are normalized accordingly to a common scale as the Reviewer suggested. This was our understanding of what the Reviewer had requested, and we have complied with it.

Although we do not perceive this to be the case, but if the continued objection is only the fact that the y axis is labelled as OD instead of cell number (?), we would point out that it is quite common practice for MTT data to be presented directly as OD values. We have published several manuscripts where we described MTT data in terms of OD readings (PMID: 34744727, PMID: 31980706, PMID: 30365135, PMID: 28276317, PMID: 26718772). Examples of recent papers where other authors have similarly presented MTT data as OD readings are PMID: 34951409, PMID: 34929154, PMID: 34916844.

But if there is something else that we have missed in his comment we would be grateful if the Reviewer could explain it more precisely and we would be happy to address the concern.

Submitted filename: Response to editor and reviewer comments 3rd round.docx

Click here for additional data file.

20 Jul 2022

Glucose deprivation reduces proliferation and motility, and enhances the anti-proliferative effects of paclitaxel and doxorubicin in breast cell line in vitro

PONE-D-22-03147R3

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Additional Editor Comments (optional):

All comments have been addressed.

Reviewers' comments:

22 Jul 2022

PONE-D-22-03147R3

Glucose deprivation reduces proliferation and motility, and enhances the anti-proliferative effects of paclitaxel and doxorubicin in breast cell line in vitro

Dear Dr. Khajah:

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