ABSTRACT BACKGROUND Glutamine (Gln) is an abundant nutrient used by cancer cells. Breast cancers cells and particularly triple-receptor negative breast cancer (TNBC) are reported to be

dependent on Gln to produce the energy required for survival and proliferation. Despite intense research on the role of the intracellular Gln pathway, few reports have focussed on Gln

transporters in breast cancer and TNBC. METHODS The role and localisation of the Gln transporter SLC38A2/SNAT2 in response to Gln deprivation or pharmacological stresses was examined in a

panel of breast cancer cell lines. Subsequently, the effect of SLC38A2 knockdown in Gln-sensitive cell lines was analysed. The prognostic value of SLC38A2 in a cohort of breast cancer was

expression of SLC38A2 protein was associated with poor breast cancer specific survival in a large cohort of patients (_p_ = 0.004), particularly in TNBC (_p_ = 0.02). CONCLUSIONS These

results position SLC38A2 as a selective target for inhibiting growth of Gln-dependent breast cancer cell lines. SIMILAR CONTENT BEING VIEWED BY OTHERS SLC1A5 IS A KEY REGULATOR OF GLUTAMINE

METABOLISM AND A PROGNOSTIC MARKER FOR AGGRESSIVE LUMINAL BREAST CANCER Article Open access 22 January 2025 METABOLIC STRESS INDUCES GD2+ CANCER STEM CELL-LIKE PHENOTYPE IN TRIPLE-NEGATIVE

BREAST CANCER Article 22 November 2021 DLST-DEPENDENCE DICTATES METABOLIC HETEROGENEITY IN TCA-CYCLE USAGE AMONG TRIPLE-NEGATIVE BREAST CANCER Article Open access 16 November 2021 BACKGROUND

The significance of amino acid (AA) metabolism and glutamine (Gln, the most abundant AA in blood serum) in tumour progression has been well recognised, leading to intense interest in

therapeutic applications.1 The maintenance of high levels of AA in cancer cells provides a ready source of carbon and nitrogen to support biosynthesis, energetics and cellular homoeostasis.

AA levels are critical for regulating the balance between the positive anabolic actions of the mammalian target of rapamycin complex 1 (mTORC1) microenvironmental sensor and the effects of

inhibiting mTORC1, leading to autophagy and catabolism.2 Breast cancer is a heterogeneous disease characterised by different morphology, clinical outcome, and response to treatment. From a

metabolic point of view, Gln-dependent mechanisms also can vary substantially among breast cancer subtypes.3 Triple-negative breast cancer (TNBC), an aggressive form of breast cancer, is

dependent on exogenous Gln for survival and growth4,5 and inhibitors of Gln transport and metabolism have been proposed as potential anti-tumour therapies.6,7 Gln is transported into cells

through many amino acid transporters (AATs).8 A recently proposed classification by Broer et al., suggested that AATs can be divided into loaders, such as SLC38A1/SNAT1, mediating the net

uptake of specific AAs;9 AAT harmonisers, such as SLC1A5/ASCT2 and SLC7A5/LAT1, which rapidly exchange different AAs and ensure that all AAs are present in the cytosol; and rescue AATs, such

as SLC38A2/SNAT2 and SLC1A4/ASCT1 that provide redundant capacity and are upregulated under stress conditions.10,11 The role of Gln metabolism and transporters, including SLC38A2, in

mediating resistance to anti-endocrine therapies has been recently demonstrated.12,13,14 However, despite the high-dependency on Gln for TNBC growth, the role of Gln transporters in this

subtype has been less investigated.15 As there are many Gln transporters, we investigated which were most abundant and their relationship to Gln dependence. We found the Gln transporter

SLC38A2/SNAT2 to have the highest expression level in many breast cancer cell lines. Consequently, we investigated and subsequently demonstrated its role in adaptation to Gln starvation in

Gln-sensitive cell lines, including TNBC cells. High SLC38A2 levels were associated with poor clinical outcome in TNBC patients, suggesting a key metabolic role for this transporter. METHODS

CELL CULTURE Cell lines were obtained from ATCC (MCF7, T47D, SKBR3, HCC1806, MDA-MB-231, MDA-MB-468), and they were authenticated six months prior to the first submission of the manuscript.

All cell lines were maintained in DMEM 25 mM glucose supplemented with 10% FBS and no antibiotics. All the experiments were performed in 5 mM glucose and 10% dialysed FBS was used. For

spheroid culture, we plated 5000 cells into ultra-low–adherent round-bottom 96-well plates (VWR) with Matrigel, except for MDA-MB-231, which did not need Matrigel. CELL PROLIFERATION Cells

(1 × 105 cells per well) were seeded in triplicate on six-well plates. _N_-acetylcysteine was added at 10 mM and replaced every 2 days. Trypsinised cells were counted using the Auto T4 Cell

Counter (Nexcelom Bioscience). We used α-(Methylamino) isobutyric acid (MeAIB) (M2383, Sigma-Aldrich) at 10 mM concentration for 2D and spheroid culture. Treatment was started on day 3 and

renewed every 2–3 days. Images were captured every 2–3 days. RNA EXTRACTION AND QRT-PCR Cells were lysed in Trizol reagent (Invitrogen) and RNA was extracted using ethanol precipitation. The

RNA quality and quantity were confirmed using the NanoDrop ND-1000 spectrophotometer. Reverse transcription (RT) was performed using the High Capacity cDNA RT kit (Applied Biosystems).

qRT-PCR was performed using the SensiFAST SYBR No-ROX Kit (Bioline). Raw data were analysed using _Ribosomal Protein L11 (RPL11)_ and _β-actin_ as housekeeping genes. Each PCR reaction was

performed in triplicate. Primer sequences are reported in Table 1. GENE SILENCING BY RNA INTERFERENCE Reverse transfection of siRNA duplexes (20 nM) was undertaken in Optimem using

Lipofectamine RNAiMax (Invitrogen) according to the manufacturer’s instructions. The siRNA duplexes targeting SLC38A2 (ON-TARGETplus SMARTpool, LQ-007559–01–0002) or scrambled control were

used. IMMUNOFLUORESCENCE Immunostaining was performed as previously reported.12 Samples were incubated overnight with SLC38A2 (G-8, SC166366), LAMP1 (CST9091), LAMP2 (CST49067), proteasome

20S LMP2 (ab3328), Rab5 (CST3547), TGN46 (AHP500G) primary antibodies and then incubated with fluorescently conjugated secondary antibodies or Alexa Fluor® 594 phalloidin (A12381) and DAPI

for 1 h at 37 °C. The samples were imaged on a Zeiss LSM 680 or 780 confocal microscope. DETERMINATION OF GLUTAMINE CONSUMPTION Cells (1 × 104/well) in a 24-well plate were cultured for 5

days, the medium was collected, and cells were lysed with RIPA buffer (Sigma-Aldrich). Concentrations of Gln in the medium and in the cell lysate were determined with the Gln Detection Assay

Kit (ab197011; Abcam) following manufacturer’s guidelines. Gln consumption was calculated as (Gln in normal medium - Gln in the medium after culturing cells) and normalised to the protein

level. MEASUREMENT OF REACTIVE OXYGEN SPECIES Reactive oxygen species (ROS) after SLC38A2 knockdown in normal medium (4 mM) or low-Gln medium (1 mM) was measured after 5 days using the

Cellular ROS Assay Kit (ab186027; Abcam). The procedure was performed following the manufacturer’s protocol and fluorescence was measured at 590 nm emission. IMMUNOBLOTTING Protein

concentrations were quantified using a BCA protein assay kit (ThermoFisher Scientific). Samples containing 35 μg of protein in NuPAGE™ LDS Sample Buffer (4X) were separated using 8–12%

pre-cast SDS-PAGE gels (BioRad). Proteins were transferred to PVDF membranes and blocked for 1 h in 5% TBST/milk. Primary antibodies were all used at 1:1000. Rabbit anti- SLC38A2 (BMP081),

SLC7A5/LAT1 (CST5347), SLC1A5/ASCT2 (CST8057), SLC38A1/SNAT1 (CST36057), xCT/SLC7A11 (CST12691), LAMP1 (CST9091), LAMP2 (CST49067), AMPKα (CST5832), Phospho-Thr172-AMPKα (CST2535),

Acetyl-CoA Carboxylase (ACC; CST3676), Phospho-Ser79-ACC (CST11818), phospho-Ser2448-mTOR (CST2971), Anti-SQSTM1/p62 (ab56416), ULK1 (CST8054), phospho-Ser555-ULK1 (CST5869). Appropriate

secondary horseradish peroxidase–linked antibodies were used (Dako). Blots were developed on ImageQuant LAS4000 using ECL plus reagent (GE Healthcare). TISSUE MICROARRAYS AND

IMMUNOHISTOCHEMICAL ANALYSIS The set (_n_ = 1685) was arrayed as previously described.16 Immunohistochemical (IHC) staining was performed on 4 µm tissue microarrays (TMA) sections using the

Novolink polymer detection system (Leica Biosystems) as previously described.17 Briefly, tissue sections were incubated 1 h at room temperature with the primary SLC38A2 antibody (1:25).

Slides were washed and incubated with post-primary block for 30 min. Novolink polymer was applied for 30 min: 3,3-diaminobenzidine chromogen was applied for 5 min. Slides were then

counterstained with haematoxylin for 6 min. Stained TMA sections were scored using high-resolution digital images (NanoZoomer; Hamamatsu Photonics), at ×20 magnification. Evaluation of

staining for SLC38A2 was based on a semi-quantitative assessment of digital images of the cores using a modified histochemical score (H-score) which included assessment of both the intensity

and the percentage of stained cells. Staining intensity was assessed as follows: 0, negative; 1, weak; 2, medium; 3, strong and the percentage of the positively stained tumour cells was

estimated subjectively. The final H-score was calculated by multiplying the percentage of positive cells (0–100) by the intensity (0–3). Dichotomisation of protein expression in predicting

breast cancer specific survival (BCSS) was determined using x-tile software (http://tissuearray.org). IHC staining and dichotomisation of the other biomarkers were as per previous

publications.18 ER and progesterone receptor (PgR) positivity was defined as ≥1% staining. Immunoreactivity of HER2 was scored using standard HercepTest guidelines (Dako) and by chromogenic

in situ hybridisation in borderline cases. Breast cancer molecular subtypes were defined based on tumour IHC profile and the Elston-Ellis mitotic score as: ER ± HER2- low proliferation

(mitotic score 1), ER ± HER2- high proliferation (mitotic score 2 and 3); HER2-positive class: HER2 + regardless of ER status; triple negative: ER−, PgR− and HER2−. BIOINFORMATICS ANALYSIS

The Metabric breast cancer dataset was pre-processed, summarised and quantile-normalised from the raw expression files generated by Illumina BeadStudio (R packages: beadarray v2.4.2 and

illuminaHuman v3.db_1.12.2). Raw files were downloaded from European genome-phenome archive (Study ID: EGAS00000000083). Correlation analysis and visualisations were performed in R

statistical environment version 3.4.4. STATISTICAL ANALYSIS Statistical analysis and graphs were performed using GraphPad Prism v6.0. Results are plotted as mean values with standard

deviation (SD). Statistical tests and the number of repeats are described in the figure legends. Student’s _t_-test was used for two sample analyses and normal distributions were assumed;

otherwise, the non-parametric Mann–Whitney test was used. Analysis of variance was used for >2 sample analyses. The chi-square test was performed for categorical variables. No samples or

experimental repeats were excluded from analyses. Survival curves were analysed by the Kaplan–Meier and log-rank test. A _p_-value < 0.05 was considered significant. The study endpoints

were 10-year BCSS. RESULTS SLC38A2 MRNA IS HIGHLY EXPRESSED IN BREAST CANCER CELL LINES We examined mRNA and protein levels of several transmembrane Gln transporters such as SLC7A5/LAT1,

SLC1A4/ASCT1, SLC1A5/ASCT2, SLC38A1/SNAT1 and SLC38A2/SNAT2 in a variety of breast cancer cell lines representing the luminal (ER+, HER2−; MCF-7 and T47D), HER2+ (SKBR3), basal-like

(HCC1806; MDA-MB-468, 468) and claudin-low (MDA-MB-231, 231) molecular subtypes of breast cancer (Fig. 1a). Different cell lines displayed heterogeneity in the mRNA and protein levels of

several Gln transporters (Fig. 1a, b). Interestingly, _SLC38A2_ mRNA was the most abundant transcript in many cell lines (Fig. 1b). Similarly, _SLC38A2_ mRNA was also the most abundant

transcript amongst a wide range of AAT in different breast cancer cell lines from the Cancer Cell Line Encyclopaedia (CCLE; Fig. S1A). Amongst the different cell lines, MCF7, MDA-MB-231 and

HCC1806 had the highest levels of expression of several Gln transporters both at mRNA and protein levels (Fig. 1a, b). We then cultured the same cell lines in a growth medium that contained

high (4 mM) or lower levels of Gln (1 mM) and followed their growth for six days. The optimal growth of breast cancer cell lines MCF7, MDA-MB-231 and HCC1806 was dependent on Gln

supplementation (Fig. 1c). In contrast, T47D, SKBR3, and MDA-MB-468 were significantly less dependent on Gln for growth (Fig. 1c). A smaller subgroup of four cell lines were also tested in

0.5 mM Gln levels (Fig. S1B). The results showed an increased sensitivity to lower Gln levels for MCF7, MDA-MB-231 and T47D but not SKBR3 (Fig. S1B) as previously shown.4 We then assessed

whether the variable dependence of cancer cells on Gln could also be a consequence of altered expression of Gln transporter genes. A selected panel of cell lines having a higher sensitivity

to Gln (MCF7, MDA-MB-231 and HCC1806) and the less-sensitive MDA-MB-468 were exposed to low Gln medium for 24 h, and the Gln transporter levels were assessed by qRT-PCR and WB. In two of the

sensitive cell lines (MCF7 and HCC1806), the system A transporters (SLC38A1 and SLC38A2) increased after Gln deprivation both at mRNA and protein level, but levels remained unchanged in the

less Gln-sensitive MDA-MB-468 and in the Gln-sensitive MDA-MB-231 cell line (Fig. 1c and Fig. S1C). Due to its high mRNA abundance, protein expression in Gln-sensitive cell lines and

previous studies showing extensive transcriptional and post-translational regulation of SLC38A2 under microenvironmental stress conditions,12,19 we investigated in more detail the role of

SLC38A2 under glutamine starvation and endoplasmic reticulum (ER) stress in breast cancer cell lines. SLC38A2 IS RE-LOCALISED FROM THE TRANS–GOLGI NETWORK UNDER DIFFERENT STRESSES SLC38A2

induction under extracellular AA deprivation, including Gln deprivation, has been previously linked to ATF4 upregulation (adaptive regulation).20 As different stresses are known to regulate

protein localisation, and SLC38A2 has been demonstrated to undergo re-localisation from a cytosolic compartment towards the cell’s plasma membrane in anabolic conditions (such as insulin

administration)21 and hyperosmotic stress,22 we investigated the localisation patterns of SLC38A2 in response to different stresses able to induce the ATF4 pathway, such as PP242 treatment

(an ATP-competitive mTORC1/mTORC2 inhibitor),23 thapsigargin (TG) and energetic stress (24 h of AA starvation) in different breast cancer cell lines. Firstly, by two-colour super

resolution-stimulated emission depletion (STED) microscopy we showed that SLC38A2 was located predominantly in the Trans–Golgi network (TGN) in MCF7 (Fig. S2A), consistent with previous

analysis in normal and cancer cells.22 SLC38A2 localisation appeared typical of intracellular vesicles, present in proximity to the TGN and also other cytoplasmic regions (Fig. S2A). A

specific antibody against the N-terminus of SLC38A2 was used for these experiments (Fig. S2B). AA deprivation increased _SLC38A2_ mRNA and protein levels, particularly in the Gln-sensitive

cell lines (MCF7 and HCC1806) (Fig. 2a–d) with no re-localisation from the TGN (Fig. 2b). PP242 treatment increased _SLC38A2_mRNA and protein in the ER+ cell lines (MCF7, T47D) but not in

SKBR3 and HCC1806 cell lines (Fig. 2c, d). Moreover, re-localisation from the TGN was seen in MCF7, T47D and HCC1806 cell lines (Fig. 2b). SKBR3 could not be assessed as SLC38A2 is not in

the TGN of that cell line (Fig. 2a, b). Similar results were also confirmed in the MDA-MB-231 TNBC cell line (Fig. S2C). Interestingly, TG treatment induced an increase of _SLC38A2_ mRNA in

MCF7, T47D and SKBR3 (Fig. 2d), but a decrease in SLC38A2 protein in MCF7 and HCC1806, as previously seen,24 with re-localisation from the TGN (Fig. 2b, c). We confirmed that under TG

treatment, a reduction of the SLC38A2 transmembrane pool (co-stained with phalloidin, F-actin) was seen as previously demonstrated (Fig. S2D).24 To identify which intracellular vesicles

contained SLC38A2, we co-stained MCF7 with an early endosome marker protein (RAB5) and the proteasome marker LMP2, where SLC38A2 is degraded.25 We found that SLC38A2 partially colocalised

with these markers in normal conditions (Fig. S2E, F). However, when the cells were exposed to TG, the co-localisation between SLC38A2 and both RAB5 and LMP2 substantially decreased (Fig. 

S2E, F). These data suggest that, despite the mRNA induction of _SLC38A2_ (Fig. 2d), diverse cell lines showed heterogeneous SLC38A2 response at protein levels in response to different

stresses (including TG) and a shift of SLC38A2 protein from the TGN and plasma membrane to another intracellular compartment during induction and degradation (Fig. S2G). SLC38A2 IS DEGRADED

BY AUTOPHAGY VIA LAMP1 RATHER THAN LAMP2 SLC38A2 has been shown to undergo degradation through the proteasome system.25 However, it is known that long-lived transmembrane proteins more

frequently undergo degradation through autophagy.26 Recent work in Hela cells has shown that SLC38A2’s adaptive response to nutrient starvation requires retromer-mediated endosomal sorting,

which prevents SLC38A2 being sequestered in LAMP1-positive lysosomes.27 Considering the heterogeneity of response to the stresses, here we assessed the route of SLC38A2 degradation by

treating MCF7, MDA-MB-231 and HCC1806 with Bafilomycin A1, a pharmacological inhibitor of autophagosome-lysosome fusion.28 The levels of SLC38A2 increased consistently after Bafilomycin A1

treatment in all cell lines, suggesting lysosome-mediated degradation of SLC38A2 was also important in these breast cancer cell lines (Fig. 3a). The levels of SLC38A2 accumulation under

Bafilomycin A1 reached higher levels compared to the induction seen under AA deprivation alone in HCC1806 (Fig. S3A). MCF7 and MDA-MB-231 cells were treated with TG and chloroquine, which is

an inhibitor of autophagy.29 TG treatment caused a decrease of SLC38A2 as previously described, whereas treatment with chloroquine resulted in the accumulation of SLC38A2 and was able to

rescue the TG-induced degradation of endogenous SLC38A2 (Fig. 3b, c). Confocal imaging showed that SLC38A2 partially colocalises with LAMP1 under basal conditions (Fig. 3d), but this

co-localisation was enhanced when the autophagic flux was blocked by Bafilomycin A1 (Fig. 3d, insets). Analysis of Biogrid immunoprecipitation repository confirmed the interaction between

SLC38A2 and LAMP1, as well as other TGN proteins and RAB530 (Fig. S3B). The same pattern of co-localisation upon Bafilomycin A1 treatment was not seen with LAMP2 (Fig. S3C), which has a

predominant role in non-selective autophagy and in chaperone-mediated autophagy (for the LAMP2A isoform).31 As SLC38A2 has been previously reported to act as a transceptor,32 we hypothesised

that SLC38A2 might serve as an AAT sensor in the lysosomes during AA starvation. However, despite an increase in SLC38A2 protein, no differences were seen in SLC38A2 and LAMP1

co-localisation during AA starvation compared to standard medium, apart from HCC1806 (Fig. 3e). These data confirmed the co-localisation of SLC38A2 in the lysosomes, implicating them as a

site of degradation for SLC38A2, but it is unclear whether SLC38A2 acts as an AA sensor in this compartment. SLC38A2 KNOCKDOWN REDUCES GLUTAMINE CONSUMPTION, MTORC1 SIGNALLING AND REGULATES

LYSOSOMAL BIOGENESIS AND AUTOPHAGY IN BREAST CANCER CELL LINES Due to its localisation in the lysosomes and the role of AAT in modulating mTOR,33 we decided to investigate the effect of

SLC38A2 in modulating autophagy and lysosomal function. We knocked down SLC38A2 with a siRNA pool in MCF7, MDA-MB-231 and HCC1806 cells. SLC38A2 knockdown did not cause a compensatory

increase in other AATs, including SLC1A5 (Fig. 4a). However, SLC38A2 silencing caused a heterogeneous response of the cysteine transporter SLC7A11 levels, with an upregulation in MDA-MB-231

and MCF7, but a downregulation in HCC1806 (Fig. 4b). SLC38A2 depletion reduced the levels of lysosomal AMPK and p-AMPK as well as its downstream phospho-Acetyl-CoA carboxylase (p-ACC) and

total ACC (Fig. 4b). The basal AMPK activation noted might be related to the drop-in glucose level in the experimental setting. The level of phosphorylated mTOR (p-mTOR) was also decreased

in all the cell lines (Fig. 4c). This was concomitant with an increase in autophagy assessed by elevated ULK1 and p-ULK1 levels and decreased p62 in all cell lines (Fig. 4c). However,

heterogeneity was seen after SLC38A2 knockdown in modulating the expression levels of LC3I/II with an increase in MCF7, a decrease in MDA-MB-231 and no effect in HCC1806 (Fig. 4c). These

results confirmed the ability of SLC38A2, similar to other AATs, to modulate the mTORC1 signalling cascade as well as autophagy.34 Interestingly SLC38A2 knockdown decreases both the LAMP1

isoform mediating macroautophagy and the LAMP2 isoform mediating chaperone-mediated autophagy in all the breast cancer cell lines (Fig. 4c). These results suggest a role of SLC38A2 in

modulating lysosomal biogenesis. To investigate the role of SLC38A2 in breast cancer growth, we grew spheroids from three Gln- sensitive cell lines (MCF7, MDA-MB-231 and HCC1806) in normal

medium and low Gln medium (Fig. 4d). Spheroids were then treated with system A (SLC38A1 and SLC38A2) inhibitor MeAIB. The pharmacological blockade of System A reduced spheroids growth in

MCF7 and HCC1806 both in normal and in low-Gln medium (with a higher magnitude). The MDA-MB-231 spheroids were sensitive to Gln deprivation but not to System A inhibition, suggesting that

System A is less relevant in this cell line, despite its sensitivity to Gln (Fig. 4d). SNAT2 depletion reduced colony formation, particularly under Gln deprivation in the three cell lines

(Fig. S4A). The effect of SLC38A2 knockdown or MeAIB was tested in 2D in the three different cell lines. The effect of the SNAT1/2 inhibitor showed similar pattern to SNAT2kd. The main

effect for both treatments was mainly seen in low-Gln conditions except in HCC1806 where the SNAT2 levels are higher (Fig. S4B). We then investigated whether the reduced proliferation under

SLC38A2 knockdown was linked to a reduced Gln intake. SLC38A2 knockdown decreased the Gln consumption in standard medium only in HCC1806 but not in MCF7 and MDA-MB-231. However, a clear

effect was seen under lower Gln levels (1 mM) in HCC1806 and MCF7 cell lines, but not MDA-MB-231, after the SLC38A2 knockdown (Fig. S4C). This confirmed lack of a critical role of SLC38A2 in

MDA-MB-231 cells under Gln deprivation. SLC38A2 KNOCKDOWN INCREASES ROS PRODUCTION IN BREAST CANCER CELLS DURING GLUTAMINE DEPRIVATION It has been shown that TNBC cells can increase the

uptake of Gln to indirectly support environmental cysteine acquisition via the SLC7A11/xCT antiporter.4 Glutamate, derived from Gln, and cysteine are substrates for the first and

rate-limiting step in glutathione biosynthesis, a key intracellular anti-oxidant buffer against oxidative stress. We assessed whether SLC38A2 upregulation under Gln deprivation could

maintain the Gln intake to modulate ROS production. Gln deprivation elevated ROS levels in all the three cell lines (Fig. 4e). The increase in ROS induced by low Gln levels was further

elevated after reducing SLC38A2 protein levels by siRNA knockdown, particularly in MCF7 and HCC1806 but not in MDA-MB-231 where SLC38A2 knockdown was associated with an increased level of

SLC7A11 (Fig. 4b). Because the anti-oxidant _N_-acetylcysteine (NAC) was shown to mitigate ROS production in cancer cell lines,35 we postulated that exogenous supplementation of NAC might

reduce the anti-growth effects of SLC38A2 blockade. We cultured MCF7, MDA-MB-231 and HCC1806 in normal and low Gln medium and we then knocked down SLC38A2 in combination with supplementation

in the culture medium of 10 mM NAC. SLC38A2 knockdown reduced cell proliferation in normal medium only in HCC1806, where the SLC38A2 levels are higher, but the inhibitory effect in 2D

culture was present in all the three cell lines in low Gln medium (Fig. S4D). Moreover, NAC supplementation partially rescued the inhibitory effect of SLC38A2 depletion in low Gln medium,

particularly in HCC1806, where there was no compensation by SLC7A11 after SLC38A2 knockdown (Fig. 4b and S4D). Our results showed that the anti-tumour effect of SLC38A2 blockade in breast

cancer cell lines, particularly in the HCC1806 TNBC cell line, in low Gln medium is partially mediated by oxidative stress. _SLC38A2_ MRNA CORRELATES WITH ATF4 AND AUTOPHAGY MARKERS IN THE

_METABRIC_ COHORT As SLC38A2 was upregulated during different stresses and degraded by autophagy, we investigated if the expression of SLC38A2 correlated with ATF4 and autophagic markers in

breast cancer patients. We analysed the gene expression data from 2433 breast cancer patients using the _Metabric_ cohort,36 we found that _SLC38A2_ mRNA abundance significantly correlated

with the expression of _HIF-1α, ATF4_, and _PERK_ and also other genes of the autophagy pathway such as _ATG5_ (Fig. 5a, b) as well Gln metabolic genes such as glutaminase (_GLS_). Also, in

the TNBC cohort of the _Metabric_, _SLC38A2_ clustered with _HIF-1α, ATG5_ and other autophagic genes like _GABARAP_ and _ULK2_ (Fig. S5A). Interestingly, _SLC38A2_ co-expressed with other

SNAT family members such as _SLC38A4/SNAT4_, _SLC38A5/SNAT5_ and _SNAT7_ (Fig. S5B) but not _SLC1A5_ or _SLC7A5_. A significant, but weak, correlation was also seen between _SLC38A2_ and

_SLC7A11_ mRNA expression (Fig. S5C). SLC38A2 PROTEIN IS RELATED TO POOR CLINICAL OUTCOME IN BREAST CANCER AND PARTICULARLY TNBC PATIENTS To examine the role of SLC38A2 in breast cancer

patients, we stained a TMA of 1,685 primary breast cancer samples. SLC38A2 protein expression was observed, predominantly in the cytoplasm of invasive breast cancer cells, with expression

levels varying from absent to high (Fig. S6A). High SLC38A2 expression (>105 H-score) was observed in 153/1685 (9%) of cases, while low expression (≤105 H-score) was observed in 1532/1685

(91%) of cases. High SLC38A2 expression was related to younger patient age, high tumour grade, moderate/poor Nottingham Prognostic Index and TNBC (all _p_ < 0.01), but not with lymph

node status (Fig. 6a and Fig. S6B). Regarding breast cancer metastatic sites, high SLC38A2 protein levels were associated with the development of distant metastases in the brain (_p_ = 

0.005) but not at other sites (Fig. S6C). We then assessed the correlation of SLC38A2 protein with three previously analysed solute carrier (SLC) clusters.37 SLC38A2 protein levels

correlated with the poor prognostic “high SLCs” (SLC1A5+/SLC7A5+/SLC3A2+) but not with the “low SLC” (SLC1A5−/SLC7A5−/SLC3A2−) nor the “high SLC1A5” cluster (SLC1A5+/SLC7A5−/SLC3A2−) (Fig. 

S6D). Moreover, SLC38A2 expression was associated with poor BCSS in the entire cohort of breast cancer patients (Fig. 6b) and particularly in TNBC (_p_ = 0.02) (Fig. 6c). There was no

association between SLC38A2 protein and outcome in ER+ low, high proliferation or in HER2+ tumours (data not shown). DISCUSSION The role of Gln transporters on proliferation has not yet been

studied extensively in TNBC.15 In this study, we showed that the system A transporters (SNAT1 and SLC38A2) are highly expressed in breast cancer cell lines. Interestingly, the cell lines

showing high levels of AATs, including SLC38A2, are more sensitive to Gln deprivation and this dependency is also partially mediated by SLC38A2. We demonstrate that the SLC38A2 anti-tumour

effect is partially mediated by oxidative stress and that high SLC38A2 protein expression in a large clinical cohort correlates with poor BCSS in patients and particularly those with TNBC.

Our results confirmed that Gln sensitivity is overall more prevalent in TNBC subtypes cell lines38 but also ER+ cell lines (MCF7) can show Gln sensitivity.4,39 These data suggest that the

early metabolic responses of cancer cells to microenvironment stresses (such as nutrient deprivation) might be shared by different subtypes and going beyond the given genetic background of

that cell line. We found that cell lines with the highest induction of Gln transporters are also more sensitive to Gln deprivation and System A inhibition. This seems to be reflective of an

upregulation of the whole Gln metabolic pathway, as these Gln-sensitive breast cancer cell lines are also more sensitive to drugs inhibiting this pathway such as aminotransferase

inhibitors39 or glutaminase inhibitors.6 TNBC subtypes have been previously linked to increased Gln sensitivity due to the increased activity of the MYC pathway in this subtype compared to

others.40 However, ER+ breast cancer cell lines with high levels of c-MYC are also dependent on Gln for their survival and growth41 and several c-Myc target AATs, including SLC1A5 and

SLC7A5,42,43 correlate with poor survival in ER+ breast cancer, but not TNBC.17,37 Interestingly, we found that the SLC38A2 protein, which is a target for hypoxia-inducible factor-α (HIF1-

α), but not c-Myc12 correlates with poor survival only in TNBC. A possible explanation could be that the activation of HIF gene networks is particularly robust in TNBC patients.44 Moreover,

the XBP1 transcription factor, one of the main branches of the unfolded protein response (UPR) is specifically activated in TNBC tumours and transcriptionally cooperates with HIF-1α.45 Both

the ATF4 upregulation under ER stress46 and HIF-1α and HIF-2α upregulation under hypoxia can promote the transcription of several AATs including SLC7A5 and SLC38A2.12,47 Moreover, HIF-1α and

c-Myc can modulate adaptive responses to hypoxic environments.48 Thus, TNBC might be more dependent on Gln metabolism, due to the synergy between HIF-1α, XBP1 and c-Myc in modulating Gln

metabolism, as well as AAT upregulation. We showed that _SLC38A2_ mRNA is highly abundant in breast cancer cell lines, as also seen in Hela and osteosarcoma cell lines.10 However, its

abundance is tightly controlled by several mechanisms at the transcriptional49 and post-translational level.50 SLC38A2 protein shows marked heterogeneity in the levels of glycosylation; it

undergoes proteasomal degradation under unsaturated fatty acid stress conditions25 and ubiquitination in response to ER-stress.24 The role of post-translational modifications in the SLC38A2

protein might account for the discrepancy between our previous results showing high _SLC38A2_ mRNA is relevant in ER+ breast cancer tumours,12 while high SLC38A2 protein is relevant in TNBC.

Similarly, this might be the cause of the difference in term of the lack of correlation between _SLC38A2 and SLC1A5 at_ mRNA and the positive correlation seen at protein levels between the

SLC38A2 and SLC1A5. We also confirmed a route for SLC38A2 degradation via autophagy in breast cancer cell lines. The degradation of transporters, such as SLC38A2, through the activation of

macroautophagy, might provide a molecular link between metabolic stress and cell death.51 However, the presence of SLC38A2 in lysosomes may just reflect its abundance and its turnover in the

endocytosis pathway. Due to the similar localisation in LAMP1 vesicles, it would be interesting to investigate whether SLC38A2 might have a potential role also in the lysosomes by supplying

the cytosolic AA derived from intracellular (autophagy) stores, as suggested for SLC38A7/SNAT7.52 Our results suggest that targeting SLC38A2 in Gln-sensitive cells reduces proliferation by

impairing their ability to uptake sufficient Gln and potentially other neutral AA substrates of SLC38A2 from the extracellular environment. Also, the intracellular Gln concentration will

drive the exchange of other AAs, e.g. leucine, isoleucine. However, a lack of anti-tumour effect in spheroids was seen in the Gln-sensitive cell MDA-MB-231 cell line in response to SLC38A2

inhibition. This could be potentially related to the higher utilisation of extracellular (macropinocytosis/necrocytosis) or intracellular AA pool from this cell line. The KRAS-mutant

MDA-MB-231 cells are robustly macropinocytic amongst a wide variety of breast cancer cells53 and the autophagy pathway is still functional under glutamine starvation and SLC38A2 knockdown

(Fig. 4c). We have previously shown that SLC38A2 knockdown can modulate mTORC1 and reduce mitochondrial respiration, particularly in low Gln medium.12 In the present study, targeting SLC38A2

also reduces the lysosome energy sensor AMPK and p-AMPK, probably due to the reduced AA pool,54 and increased ROS production in low Gln medium. The increase in ROS was likely due to

impaired Gln metabolism and cysteine/glutamate exchange, as has previously been seen for SLC1A5.35,55 However, in contrast to SLC1A5, we found an increase in ROS production mainly in low Gln

medium after SLC38A2 knockdown, confirming recent suggestions that SLC38A2 acts as a rescue transporter providing AA intake under stress conditions.9 The role of SLC38A2 in maintaining

mitochondrial function and ROS production in low Gln might be beyond the exchange with cysteine. In pancreatic cancer, SLC38A2 represents the major AAT for alanine, which is then deaminated

to pyruvate (which can maintain the tricarboxylic acid cycle) in the presence of pyruvate carboxylase.56 Finally, our analysis of clinical data from a large breast cancer cohort suggests

that high baseline SLC38A2 protein expression correlates with poor BCSS survival in patients with breast cancer and with TNBC. Moreover, tumours with high SLC38A2 expression were also

commonly represented in the poor prognostic high SLC cluster (SLC1A5+/SLC7A5+/SLC3A2+). Interestingly, no significant association between the high SLC clusters and patient outcome was

previously reported in TNBC.37 The TNBC subtype has still poorer outcome compared to other breast cancer subtypes due to aggressive clinical behaviour and a lack of recognised molecular

targets for therapy.57 Blocking cellular Gln transport would potentially impart a greater impact on Gln metabolism in cancer cells than targeting downstream enzyme activity, given the

extensive biological plasticity leveraged by cancer cells to maintain intracellular AA pools; new inhibitors with high affinity for AATs have been proposed.58 However, redundancy associated

with other AATs after long-term silencing of SLC1A5 has been shown.9 Due to its transmembrane localisation and the vulnerability of the TNBC cell lines to Gln depletion and SLC38A2

knockdown, SLC38A2 is potentially a useful target for this cancer subtype. However, apart from the canonical competitive inhibitor of system A transport, MeAIB, no pharmacological agent

specifically targeting SLC38A2 has been identified so far. Alternatively, SLC38A2 imaging for clinical selection by AA-based positron emission tomography radiotracers is also a promising

approach59 that might inform treatment strategy. In conclusion, this study provides evidence for future investigation of SLC38A2 as a potential target for TNBC breast cancer patients and as

a marker for sensitivity to Gln deprivation. REFERENCES * Martinez-Outschoorn, U. E., Peiris-Pages, M., Pestell, R. G., Sotgia, F. & Lisanti, M. P. Cancer metabolism: a therapeutic

perspective. _Nat. Rev. Clin. Oncol._ 14, 11–31 (2017). Article  CAS  PubMed  Google Scholar  * Jewell, J. L., Russell, R. C. & Guan, K. L. Amino acid signalling upstream of mTOR. _Nat.

Rev. Mol. Cell Biol._ 14, 133–139 (2013). Article  CAS  PubMed  PubMed Central  Google Scholar  * El Ansari, R., McIntyre, A., Craze, M. L., Ellis, I. O., Rakha, E. A. & Green, A. R.

Altered glutamine metabolism in breast cancer; subtype dependencies and alternative adaptations. _Histopathology_ 72, 183–190 (2018). Article  PubMed  Google Scholar  * Timmerman, L. A.,

Holton, T., Yuneva, M., Louie, R. J., Padró, M., Daemen, A. et al. Glutamine sensitivity analysis identifies the xCT antiporter as a common triple-negative breast tumor therapeutic target.

_Cancer Cell_ 24, 450–465 (2013). Article  CAS  PubMed  PubMed Central  Google Scholar  * Mauro-Lizcano, M. & Lopez-Rivas, A. Glutamine metabolism regulates FLIP expression and

sensitivity to TRAIL in triple-negative breast cancer cells. _Cell Death Dis._ 9, 205 (2018). Article  PubMed  PubMed Central  CAS  Google Scholar  * Gross, M. I., Arlt, H., He, T., Ospina,

B., Reeves, J. & Zhang, B. Antitumor activity of the glutaminase inhibitor CB-839 in triple-negative breast cancer. _Mol. Cancer Ther._ 13, 890–901 (2014). Article  CAS  PubMed  Google

Scholar  * Altman, B. J., Stine, Z. E. & Dang, C. V. From Krebs to clinic: glutamine metabolism to cancer therapy. _Nat. Rev. Cancer_ 16, 619–634 (2016). Article  CAS  PubMed  PubMed

Central  Google Scholar  * Bhutia, Y. D., Babu, E., Ramachandran, S. & Ganapathy, V. Amino Acid transporters in cancer and their relevance to “glutamine addiction”: novel targets for the

design of a new class of anticancer drugs. _Cancer Res._ 75, 1782–1788 (2015). Article  CAS  PubMed  Google Scholar  * Bröer, A., Gauthier-Coles, G., Rahimi, F., van Geldermalsen, M.,

Dorsch, D., Wegener, A. et al. Ablation of the ASCT2 (SLC1A5) gene encoding a neutral amino acid transporter reveals transporter plasticity and redundancy in cancer cells. _J. Biol. Chem._

294, 4012–4026 (2019). Article  PubMed  PubMed Central  Google Scholar  * Broer, A., Rahimi, F. & Broer, S. Deletion of amino acid transporter ASCT2 (SLC1A5) reveals an essential role

for transporters SNAT1 (SLC38A1) and SNAT2 (SLC38A2) to sustain glutaminolysis in cancer cells. _J. Biol. Chem._ 291, 13194–13205 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar

  * Broer, S. & Broer, A. Amino acid homeostasis and signalling in mammalian cells and organisms. _Biochem. J._ 474, 1935–1963 (2017). Article  CAS  PubMed  Google Scholar  * Morotti,

M., Bridges, E., Valli, A., Choudhry, H., Sheldon, H., Wigfield, S. et al. Hypoxia-induced switch in SNAT2/SLC38A2 regulation generates endocrine resistance in breast cancer. _Proc. Natl

Acad. Sci. USA_ 116, 12452–12461 (2019). Article  CAS  PubMed  PubMed Central  Google Scholar  * Bacci, M., Lorito, N., Ippolito, L., Ramazzotti, M., Luti, S., Romagnoli, S. et al.

Reprogramming of amino acid transporters to support aspartate and glutamate dependency sustains endocrine resistance in breast cancer. _Cell Rep._ 28, 104–118 e108 (2019). Article  CAS 

PubMed  PubMed Central  Google Scholar  * Demas, D. M., Demo, S., Fallah, Y., Clarke, R., Nephew, K. P., Althouse, S. et al. Glutamine metabolism drives growth in advanced hormone receptor

positive breast cancer. _Front Oncol._ 9, 686 (2019). Article  PubMed  PubMed Central  Google Scholar  * van Geldermalsen, M., Wang, Q., Nagarajah, R., Marshall, A. D., Thoeng, A., Gao, D.

et al. ASCT2/SLC1A5 controls glutamine uptake and tumour growth in triple-negative basal-like breast cancer. _Oncogene_ 35, 3201–3208 (2016). Article  PubMed  CAS  Google Scholar  * Abd

El-Rehim, D. M., Ball, G., Pinder, S. E., Rakha, E., Paish, C., Robertson, J. F. et al. High-throughput protein expression analysis using tissue microarray technology of a large

well-characterised series identifies biologically distinct classes of breast cancer confirming recent cDNA expression analyses. _Int J. Cancer_ 116, 340–350 (2005). Article  CAS  PubMed 

Google Scholar  * El Ansari, R., Craze, M. L., Miligy, I., Diez-Rodriguez, M., Nolan, C. C., Ellis, I. O. et al. The amino acid transporter SLC7A5 confers a poor prognosis in the highly

proliferative breast cancer subtypes and is a key therapeutic target in luminal B tumours. _Breast Cancer Res._ 20, 21 (2018). Article  PubMed  PubMed Central  CAS  Google Scholar  * Green,

A. R., Aleskandarany, M. A., Agarwal, D., Elsheikh, S., Nolan, C. C., Diez-Rodriguez, M. et al. MYC functions are specific in biological subtypes of breast cancer and confers resistance to

endocrine therapy in luminal tumours. _Br. J. Cancer_ 114, 917–928 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  * Hundal, H. S. & Taylor, P. M. Amino acid transceptors:

gate keepers of nutrient exchange and regulators of nutrient signaling. _Am. J. Physiol. Endocrinol. Metab._ 296, E603–E613 (2009). Article  CAS  PubMed  PubMed Central  Google Scholar  *

Palii, S. S., Chen, H. & Kilberg, M. S. Transcriptional control of the human sodium-coupled neutral amino acid transporter system A gene by amino acid availability is mediated by an

intronic element. _J. Biol. Chem._ 279, 3463–3471 (2004). Article  CAS  PubMed  Google Scholar  * Hatanaka, T., Hatanaka, Y., Tsuchida, J., Ganapathy, V. & Setou, M. Amino acid

transporter ATA2 is stored at the trans-Golgi network and released by insulin stimulus in adipocytes. _J. Biol. Chem._ 281, 39273–39284 (2006). Article  CAS  PubMed  Google Scholar  *

Krokowski, D., Guan, B. J., Wu, J., Zheng, Y., Pattabiraman, P. P., Jobava, R. et al. GADD34 function in protein trafficking promotes adaptation to hyperosmotic stress in human corneal

cells. _Cell Rep._ 21, 2895–2910 (2017). Article  CAS  PubMed  PubMed Central  Google Scholar  * Appenzeller-Herzog, C. & Hall, M. N. Bidirectional crosstalk between endoplasmic

reticulum stress and mTOR signaling. _Trends Cell Biol._ 22, 274–282 (2012). Article  CAS  PubMed  Google Scholar  * Jeon, Y. J., Khelifa, S., Ratnikov, B., Scott, D. A., Feng, Y., Parisi,

F. et al. Regulation of glutamine carrier proteins by RNF5 determines breast cancer response to ER stress-inducing chemotherapies. _Cancer Cell_ 27, 354–369 (2015). Article  CAS  PubMed 

PubMed Central  Google Scholar  * Nardi, F., Hoffmann, T. M., Stretton, C., Cwiklinski, E., Taylor, P. M. & Hundal, H. S. Proteasomal modulation of cellular SNAT2 (SLC38A2) abundance and

function by unsaturated fatty acid availability. _J. Biol. Chem._ 290, 8173–8184 (2015). Article  CAS  PubMed  PubMed Central  Google Scholar  * Kaur, J. & Debnath, J. Autophagy at the

crossroads of catabolism and anabolism. _Nat. Rev. Mol. Cell Biol._ 16, 461–472 (2015). Article  CAS  PubMed  Google Scholar  * Curnock, R., Calcagni, A., Ballabio, A. & Cullen, P. J.

TFEB controls retromer expression in response to nutrient availability. _J. Cell Biol._ 218, 3954–3966 (2019). Article  CAS  PubMed  PubMed Central  Google Scholar  * Levine, B. &

Kroemer, G. Autophagy in the pathogenesis of disease. _Cell_ 132, 27–42 (2008). Article  CAS  PubMed  PubMed Central  Google Scholar  * Mauthe, M., Orhon, I., Rocchi, C., Zhou, X., Luhr, M.

& Hijlkema, K. J. Chloroquine inhibits autophagic flux by decreasing autophagosome-lysosome fusion. _Autophagy_ 14, 1435–1455 (2018). Article  CAS  PubMed  PubMed Central  Google Scholar

  * Hein, M. Y., Hubner, N. C., Poser, I., Cox, J., Nagaraj, N. & Toyoda, Y. A human interactome in three quantitative dimensions organized by stoichiometries and abundances. _Cell_ 163,

712–723 (2015). Article  CAS  PubMed  Google Scholar  * Cuervo, A. M. & Dice, J. F. A receptor for the selective uptake and degradation of proteins by lysosomes. _Science_ 273, 501–503

(1996). Article  CAS  PubMed  Google Scholar  * Pinilla, J., Aledo, J. C., Cwiklinski, E., Hyde, R., Taylor, P. M. & Hundal, H. S. SNAT2 transceptor signalling via mTOR: a role in cell

growth and proliferation? _Front Biosci. (Elite Ed.)_ 3, 1289–1299 (2011). Google Scholar  * Goberdhan, D. C., Wilson, C. & Harris, A. L. Amino acid sensing by mTORC1: intracellular

transporters mark the spot. _Cell Metab._ 23, 580–589 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  * Nicklin, P., Bergman, P., Zhang, B., Triantafellow, E., Wang, H.,

Nyfeler, B. et al. Bidirectional transport of amino acids regulates mTOR and autophagy. _Cell_ 136, 521–534 (2009). Article  CAS  PubMed  PubMed Central  Google Scholar  * Zhang, Z., Liu,

R., Shuai, Y., Huang, Y., Jin, R., Wang, X. et al. ASCT2 (SLC1A5)-dependent glutamine uptake is involved in the progression of head and neck squamous cell carcinoma. _Br. J. Cancer_ 122,

82–93 (2020). Article  CAS  PubMed  Google Scholar  * Pereira, B., Chin, S. F., Rueda, O. M., Vollan, H. K., Provenzano, E., Bardwell, H. A. et al. The somatic mutation profiles of 2,433

breast cancers refines their genomic and transcriptomic landscapes. _Nat. Commun._ 7, 11479 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  * El-Ansari, R., Craze, M. L.,

Alfarsi, L., Soria, D., Diez-Rodriguez, M., Nolan, C. C. et al. The combined expression of solute carriers is associated with a poor prognosis in highly proliferative ER+ breast cancer.

_Breast Cancer Res. Treat._ 175, 27–38 (2019). Article  CAS  PubMed  Google Scholar  * Kung, H. N., Marks, J. R. & Chi, J. T. Glutamine synthetase is a genetic determinant of cell

type-specific glutamine independence in breast epithelia. _PLoS Genet_ 7, e1002229 (2011). Article  CAS  PubMed  PubMed Central  Google Scholar  * Korangath, P., Teo, W. W., Sadik, H., Han,

L., Mori, N., Huijts, C. M. et al. Targeting glutamine metabolism in breast cancer with aminooxyacetate. _Clin. Cancer Res._ 21, 3263–3273 (2015). Article  CAS  PubMed  PubMed Central 

Google Scholar  * Horiuchi, D., Kusdra, L., Huskey, N. E., Chandriani, S., Lenburg, M. E., Gonzalez-Angulo, A. M. et al. MYC pathway activation in triple-negative breast cancer is synthetic

lethal with CDK inhibition. _J. Exp. Med_ 209, 679–696 (2012). Article  CAS  PubMed  PubMed Central  Google Scholar  * Wise, D. R., DeBerardinis, R. J., Mancuso, A., Sayed, N., Zhang, X. Y.,

Pfeiffer, H. K. et al. Oncogenic Myc induces expression of glutamine synthetase through promoter demethylation. _Cell Metab._ 22, 1068–1077 (2015). Article  CAS  Google Scholar  * Yue, M.,

Jiang, J., Gao, P., Liu, H. & Qing, G. Oncogenic MYC activates a feedforward regulatory loop promoting essential amino acid metabolism and tumorigenesis. _Cell Rep._ 21, 3819–3832

(2017). Article  CAS  PubMed  Google Scholar  * Wise, D. R., DeBerardinis, R. J., Mancuso, A., Sayed, N., Zhang, X. Y., Pfeiffer, H. K. et al. Myc regulates a transcriptional program that

stimulates mitochondrial glutaminolysis and leads to glutamine addiction. _Proc. Natl Acad. Sci. USA_ 105, 18782–18787 (2008). Article  CAS  PubMed  PubMed Central  Google Scholar  * Cancer

Genome Atlas, N. Comprehensive molecular portraits of human breast tumours. _Nature_ 490, 61–70 (2012). Article  CAS  Google Scholar  * Chen, X., Iliopoulos, D., Zhang, Q., Tang, Q.,

Greenblatt, M. B., Hatziapostolou, M. et al. XBP1 promotes triple-negative breast cancer by controlling the HIF1alpha pathway. _Nature_ 508, 103–107 (2014). Article  CAS  PubMed  PubMed

Central  Google Scholar  * Han, J., Back, S. H., Hur, J., Lin, Y. H., Gildersleeve, R., Shan, J. et al. ER-stress-induced transcriptional regulation increases protein synthesis leading to

cell death. _Nat. Cell Biol._ 15, 481–490 (2013). Article  CAS  PubMed  PubMed Central  Google Scholar  * Elorza, A., Soro-Arnáiz, I., Meléndez-Rodríguez, F., Rodríguez-Vaello, V., Marsboom,

G., de Cárcer, G. et al. HIF2alpha acts as an mTORC1 activator through the amino acid carrier SLC7A5. _Mol. Cell_ 48, 681–691 (2012). Article  CAS  PubMed  Google Scholar  * Gordan, J. D.,

Thompson, C. B. & Simon, M. C. HIF and c-Myc: sibling rivals for control of cancer cell metabolism and proliferation. _Cancer Cell_ 12, 108–113 (2007). Article  CAS  PubMed  PubMed

Central  Google Scholar  * Stretton, C., Lipina, C., Hyde, R., Cwiklinski, E., Hoffmann, T. M., Taylor, P. M. et al. CDK7 is a component of the integrated stress response regulating SNAT2

(SLC38A2)/System A adaptation in response to cellular amino acid deprivation. _Biochim Biophys. Acta Mol. Cell Res._ 1866, 978–991 (2019). Article  CAS  PubMed  PubMed Central  Google

Scholar  * Menchini, R. J. & Chaudhry, F. A. Multifaceted regulation of the system A transporter Slc38a2 suggests nanoscale regulation of amino acid metabolism and cellular signaling.

_Neuropharmacology_ 161, 107789 (2019). Article  CAS  PubMed  Google Scholar  * Xia, H. G., Najafov, A., Geng, J., Galan-Acosta, L., Han, X., Guo, Y. et al. Degradation of HK2 by

chaperone-mediated autophagy promotes metabolic catastrophe and cell death. _J. Cell Biol._ 210, 705–716 (2015). Article  CAS  PubMed  PubMed Central  Google Scholar  * Verdon, Q., Boonen,

M., Ribes, C., Jadot, M., Gasnier, B. & Sagné, C. SNAT7 is the primary lysosomal glutamine exporter required for extracellular protein-dependent growth of cancer cells. _Proc. Natl Acad.

Sci. USA_ 114, E3602–E3611 (2017). Article  CAS  PubMed  PubMed Central  Google Scholar  * Jayashankar, V. & Edinger, A. L. Macropinocytosis confers resistance to therapies targeting

cancer anabolism. _Nat. Commun._ 11, 1121 (2020). Article  PubMed  PubMed Central  Google Scholar  * Dalle Pezze, P., Ruf, S., Sonntag, A. G., Langelaar-Makkinje, M., Hall, P., Heberle, A.

M. et al. A systems study reveals concurrent activation of AMPK and mTOR by amino acids. _Nat. Commun._ 7, 13254 (2016). Article  PubMed  CAS  Google Scholar  * Hassanein, M., Hoeksema, M.

D., Shiota, M., Qian, J., Harris, B. K., Chen, H. et al. SLC1A5 mediates glutamine transport required for lung cancer cell growth and survival. _Clin. Cancer Res._ 19, 560–570 (2013).

Article  CAS  PubMed  Google Scholar  * Parker, S. J., Amendola, C. R., Hollinshead, K. E. R., Yu, Q., Yamamoto, K., Encarnación-Rosado, J., et al. Selective alanine transporter utilization

creates a targetable metabolic niche in pancreatic cancer. _Cancer Discov._ https://doi.org/10.1158/2159-8290.CD-19-0959 (2020). * Bianchini, G., Balko, J. M., Mayer, I. A., Sanders, M. E.

& Gianni, L. Triple-negative breast cancer: challenges and opportunities of a heterogeneous disease. _Nat. Rev. Clin. Oncol._ 13, 674–690 (2016). Article  CAS  PubMed  PubMed Central 

Google Scholar  * Schulte, M. L., Fu, A., Zhao, P., Li, J., Geng, L., Smith, S. T. et al. Pharmacological blockade of ASCT2-dependent glutamine transport leads to antitumor efficacy in

preclinical models. _Nat. Med._ 24, 194–202 (2018). Article  CAS  PubMed  PubMed Central  Google Scholar  * Nishii, R., Higashi, T., Kagawa, S., Arimoto, M., Kishibe, Y., Takahashi, M. et

al. Differential diagnosis between low-grade and high-grade astrocytoma using system A amino acid transport PET imaging with C-11-MeAIB: a comparison study with C-11-Methionine PET imaging.

_Contrast Media Mol. Imaging_ 2018, 1292746 (2018). PubMed  PubMed Central  Google Scholar  Download references ACKNOWLEDGEMENTS We thank Dr Christoffer Lagerholm for the help with confocal

microscopy and the Nottingham Health Science Biobank and Breast Cancer Now Tissue Bank for the provision of tissue samples. This study makes use of data generated by the Molecular Taxonomy

of Breast Cancer International Consortium. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Hypoxia and Angiogenesis Group, Weatherall Institute of Molecular Medicine, Department of Oncology,

University of Oxford, Oxford, OX3 9DS, UK Matteo Morotti, Christos E. Zois, Alessandro Valli, Syed Haider & Adrian L. Harris * Nottingham Breast Cancer Research Centre, Division of

Cancer and Stem Cells, School of Medicine, University of Nottingham Biodiscovery Institute, Nottingham, NG7 2RD, UK Rokaya El-Ansari, Madeleine L. Craze, Emad A. Rakha & Andrew R. Green

* Department of Physiology, Anatomy and Genetics, Le Gros Clark Building, University of Oxford, South Parks Road, Oxford, OX1 3QX, UK Shih-Jung Fan & Deborah C. I. Goberdhan * The Breast

Cancer Now Toby Robins Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, UK Syed Haider Authors * Matteo Morotti View author publications You

can also search for this author inPubMed Google Scholar * Christos E. Zois View author publications You can also search for this author inPubMed Google Scholar * Rokaya El-Ansari View author

publications You can also search for this author inPubMed Google Scholar * Madeleine L. Craze View author publications You can also search for this author inPubMed Google Scholar * Emad A.

Rakha View author publications You can also search for this author inPubMed Google Scholar * Shih-Jung Fan View author publications You can also search for this author inPubMed Google

Scholar * Alessandro Valli View author publications You can also search for this author inPubMed Google Scholar * Syed Haider View author publications You can also search for this author

inPubMed Google Scholar * Deborah C. I. Goberdhan View author publications You can also search for this author inPubMed Google Scholar * Andrew R. Green View author publications You can also

search for this author inPubMed Google Scholar * Adrian L. Harris View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS M.M. and A.L.H. designed

research; M.M., A.V., C.E.Z., R.E-A., M.C., E.A.R. performed research; D.C.I.G., A.G., S-J.F., M.M., A.L.H. contributed to data analysis and interpretation; M.M. and A.L.H. wrote the paper.

CORRESPONDING AUTHORS Correspondence to Matteo Morotti or Adrian L. Harris. ETHICS DECLARATIONS ETHICS APPROVAL AND CONSENT TO PARTICIPATE This work obtained ethics approval by the North

West-Greater Manchester Central Research Ethics Committee under the title: Nottingham Health Science Biobank (NHSB), reference number 15/NW/0685. All patients included were consented to

participate in the study and to use their materials in research. All samples from Nottingham used in this study were pseudo-anonymised and stored in compliance with the UK Human Tissue Act.

The study was performed in accordance with the Declaration of Helsinki CONSENT FOR PUBLICATION Not applicable. DATA AVAILABILITY The data presented in the current study are available upon

reasonable request from the corresponding author. COMPETING INTERESTS The authors declare no competing interests. FUNDING INFORMATION This research was supported by funding from Cancer

Research UK (C19591/A19076; D.C.I.G.), Oxford NIHR Biomedical Research Centre, Breast Cancer Research Foundation (A.L.H.), Kennington Cancer Fund (A.L.H.) and by a Fondazione Veronesi

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permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Morotti, M., Zois, C.E., El-Ansari, R. _et al._ Increased expression of glutamine transporter SNAT2/SLC38A2 promotes glutamine dependence and

oxidative stress resistance, and is associated with worse prognosis in triple-negative breast cancer. _Br J Cancer_ 124, 494–505 (2021). https://doi.org/10.1038/s41416-020-01113-y Download

citation * Received: 10 May 2020 * Revised: 10 September 2020 * Accepted: 17 September 2020 * Published: 08 October 2020 * Issue Date: 19 January 2021 * DOI:

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