Identification and Characterization of IMD-0354 as a Glutamine Carrier Protein Inhibitor in Melanoma

Glutamine is a semi-essential and the most abundant amino acid in the vasculature (1). Along with its requirement for protein synthesis, glutamine is essential for the biosynthesis of nucleotides, glutathione, fatty acids, and nonessential amino acids glutamate, aspartate, and asparagine (2). In addition to its biosynthetic activity, glutamine has been shown to facilitate the uptake of essential amino acids, maintenance of mTORC1 activity, and c-MYC translation (3–5). Through its anaplerotic assimilation into the TCA cycle, glutamine also provides the reducing power to fuel mitochondrial respiration and energy production (2, 6).

Following the identification of c-MYC as a regulator of the expression of mitochondrial glutaminase (GLS1; ref. 7) and glutamine transporter SLC1A5 (8), proteins frequently overexpressed in tumors, there has been a considerable interest in targeting glutamine metabolism for therapeutic benefit (9–11). Increase in glutamine dependency was also noted in melanoma tumors that established resistance to BRAF inhibitor therapy (12). Likewise, a shift in glutamine metabolism from oxidation to reductive carboxylation, a change that is catalyzed by HIF-1-SIAH2–mediated targeted degradation of the TCA cycle enzyme α-ketoglutarate dehydrogenase, to promote lipid synthesis, is an important component of reprogrammed metabolism exhibited by tumor cells (13). Our earlier studies have identified increase in glutamine uptake as a mechanism of resistance to taxane therapy in triple-negative breast cancer, highlighting the importance of glutamine carrier proteins in such tumors (14). In all, these studies provided the foundation for exploring the possible use of glutamine uptake inhibitors as means to attenuate tumor growth and tumor support by its microenvironment.

Small-molecule GLS1 inhibitors, including CB-839, which suppress glutamine catalysis to glutamate, have shown some success in the preclinical models of different tumor types (15–17), including possible synthetic lethality with Myc-driven chemoresistant cancers (18). CB-839 has also been evaluated in multiple clinical trials (19). However, given glutaminolysis-independent activities of glutamine, including uptake of essential amino acids for the maintenance of mTORC1 activity (3), biosynthesis of asparagine and nucleotides, and protein synthesis (20), it is expected that attenuation of glutamine uptake would be required to achieve a complete cessation of glutamine-mediated protumorigenic activities.

Among the various glutamine carrier proteins that facilitate glutamine uptake, SLC1A5 has been identified as the most effective glutamine transporter in a number of tumor models (14, 21, 22), prompting the development of small-molecule inhibitors to block SLC1A5-mediated glutamine uptake (23–25). However, demonstrable concerns surrounding the specificity of these inhibitors for SLC1A5, with inhibition of other SLC family of transporters, and potential negative impact on the proliferation of normal tissues, remain to be addressed (26).

In light of the limitations of the current class of SLC1A5 inhibitors (26), we utilized high-content screening to identify IMD-0354, a small molecule that impairs plasma membrane localization of SLC1A5, a unique approach to selectively suppress cellular glutamine uptake. IMD-0354 enhanced glucose metabolism, culminating in increased lactate generation, as a compensatory metabolic route in glutamine-restricted SLC1A5 inhibited cells. IMD-0354 effectively inhibited growth of tumor cells in culture as in preclinical models.

The following cell lines were used in this study: human epidermoid carcinoma cell line A431, lung adenocarcinoma cell line A549, and renal carcinoma cell line A498 were obtained from ATCC and cultured in high-glucose DMEM (HyClone) supplemented with 10% FBS and 1% penicillin–streptomycin. Human fibroblast cell line GM00083 was obtained from Coriell Institute for Medical Research, Inc. (Camden, NJ) and cultured in Eagle MEM (Corning) supplemented with 15% FBS and 1% penicillin–streptomycin. Human melanoma cell lines A375, Mel-501, Lu1205, UACC903, WM1366, WM3629, MeWo, Mel-5, Mel-28, mouse melanoma cell line SW1 (obtained from ATCC, the Wistar Institute, TGen, NCI), and human melanocytes H3A (obtained from the Welcome Trust Functional Genomic Cell Bank; EV Sviderskaya, DC Bennett) were cultured in DMEM described above. Human prostate cancer cell line LNCap, 22RV1, PC3, human colon cancer cell line HCT116, human pancreatic cancer cell line MiaPaCa were grown in RPMI1640 medium (Corning) supplemented with 10% FBS and 1% penicillin–streptomycin. Cell cultures were maintained in cell culture incubator at 37°C in 5% CO₂. Mycoplasma testing was performed regularly using MycoAlert Mycoplasma Detection Kit as per manufacturer's instruction (Lonza). For cell line authentication, short tandem repeat (STR) analysis was performed with the Genomic Shared Resources at SBP. Allele profiles for each line were matched those maintained in the Expasy Cellosaurus STR database (https://web.expasy.org/cellosaurus/) using CLASTR v1.4.4.

IMD-0354, TPCA-1, and baricitinib were purchased from Toronto Research Chemicals. Torin 1, rapamycin, ruxolitinib, and Y-27632 were obtained from Selleckchem. SU11274, CB-839 and (S)-H-1152 were obtained from Cayman Chemical. Human TNFα was purchased from Cell Signaling Technology (R)-GNE-140 was obtained from Medchemexpress. pLX304, pLX304-V5-SLC1A5, and pLX304-V5-SLC38A2 were purchased from DNASU Plasmid Repository. All siRNAs were purchased from Sigma-Aldrich. For SLC1A5, siRNA IDs are SASI_Hs01_00162267 and SASI_Hs01_00162267. For IKK1, siRNA IDs are SASI_Hs01_ 00206921 and SASI_Hs01_00206922. For IKK2, siRNA IDs are SASI_Hs01_00156170 and SASI_Hs01_00156172.

To determine the effect of selected compounds, cells were plated at 50% confluency and grown overnight in 6-well plates. Test compounds at different concentrations were added to the plates and incubated for different time (depends on experiments). For phospho-IKK/phospho-IκB experiments, cells were plated as described above and grown overnight. Compounds were added to cells for 1 hour prior to stimulation with 10 ng/mL TNFα. Cells were then rinsed with PBS and lysed in lysis buffer (50 mmol/L Tris-HCl, pH 7.4, 150 mmol/L NaCl, 1% NP-40, 1 mmol/L EDTA, 10 μg/mL aprotinin, 1 μg/mL pepstatin A, 10 μg/mL leupeptin, 2 mmol/L phenylmethylsulphonyl fluoride, 2.5 mmol/L sodium orthovanadate). Protein concentration was determined using Coomassie Plus Protein Assay Reagent (Thermo Scientific). Equal amounts of cell lysate proteins (50 μg) were separated on SDS-PAGE and transferred to polyvinylidene difluoride membrane. Membranes were blocked with 3% BSA/TBST, incubated with primary antibodies and secondary antibodies. Detection and quantifications were made using Odyssey Infrared Imaging System (LI-COR Biosciences). Antibodies against phospho- IKKα/β (Ser176/180), IKK, phospho-IκB (Ser32), IκB, phospho-p70S6K (Thr389), p70S6K, CHOP, BIP, IRE1, PARP, LC3, p21, p27, SLC1A5, SLC7A5, and E-Cadherin were purchased from Cell Signaling Technology. α-tubulin and GAPDH antibodies were obtained from Santa Cruz Biotechnology. Secondary antibodies were goat anti-rabbit Alexa-680 F(ab')₂ (Molecular Probes) and goat anti-mouse IRDye 800 F(ab')₂ (Rockland Immunochemicals). All antibodies were used according to the manufacturers' recommendations.

For identification of SLC1A5 inhibitors, the benchtop microscope slide-based immunofluorescence SLC1A5 assay was adapted for high-throughput high content screening (HCS) in 384-well plate format. Briefly, A431 cells were seeded in full culture medium at 3,000 cells per well in PerkinElmer CellCarrier-384 Ultra microplates and allowed to attach overnight at 37°C in 5% CO₂. Control and screening library compounds were added using a Labcyte Echo acoustic liquid handler and the plates were returned to the incubator for approximately 18 hours. Cells were fixed in 4% paraformaldehyde for 30 minutes followed by a combined blocking and permeabilization step using PBS with 0.1% Triton-X and 3% BSA for 1 hour. Cells were stained using anti-SLC1A5 (Sigma-Aldrich) primary antibody at 1:1,000 in PBST for 2 hours, and fluorescently labeled with Alexa Fluor 488 (AF488) secondary antibody at 1:400 and HCS CellMask Orange at 1:10,000 in PBST for 1 hour. Finally, the nuclear counterstain DAPI was added at 100 ng/mL and plates were sealed. Plates were imaged on a PerkinElmer Opera Phenix High Content Screening System using a 20× 0.4 NA air objective and four fields per well. Images were analyzed using a custom-built PerkinElmer Harmony software analysis script (details shown in Fig. 2B), and the resulting data were normalized, quality controlled, and further analyzed using Genedata Screener software with HCS extension. Data were deposited in and linked to chemical compound library information using CBIS (ChemInnovation) chemical-biology database software.

Compound libraries selected for screening included the 1,200 approved drugs Prestwick Library (Prestwick Chemical) at 5 μmol/L, SBPs approximately 600 kinase inhibitors collection (Selleck Chemicals, Cayman Chemical, EMD Biosciences) at 0.5 μmol/L, and the 5,000 synthetic natural product inspired compounds NatX library (Analyticon Discovery) at 10 μmol/L screening concentrations. All plates contained a set of positive and negative control wells with 0.05% DMSO utilized as negative (vehicle) control and 150 nmol/L Thapsigargin in 0.05% DMSO as positive control. 6,929 compounds were tested in the screening campaign in singlets as recommended for assay Z'-values > 0.5 (27) and the screen showed good assay performance as indicated by a Z'-value of 0.57 (Fig. 2C). One hundred twenty compound wells with cell counts <20% as compared with vehicle controls (0.05% DMSO) were considered overtly toxic and removed from further consideration. Using a hit criterion for the assay read-out “Fraction Intensity on Plasma Membrane” of % activity < −40% (normalized to 0% = DMSO, -100% = TG controls), 122 initial hits were identified. Further review of cell shape parameters and visual evaluation of the hit images to remove hits significantly affecting cell morphology resulted in a reduced hit set of 32 compounds. Considering the compounds' known mechanisms of action or pathways and number of hits per mechanism/pathway, a subset of nine compounds was selected for further evaluation in functional assays.

1 × 10⁵ cells were seeded overnight per well in 6-well plates. Negative control or siRNA targeting the transcript of interest was transfected utilizing jetPRIME Transfection Reagent, as per the manufacturer's instructions (Polyplus).

Cells were grown in 96-well black plates and treated as indicated in the text. Cells were then fixed with paraformaldehyde in PBS for 10 minutes at room temperature. After fixation, samples were permeabilized with 0.5% Triton X-100 in PBS for 15 minutes and thereafter blocked with 10% FCS in PBS containing 0.1% Triton X-100. Cells were incubated for 1 hour each at 25°C with primary and secondary antibodies and 15 minutes with 4′,6-diamidino-2-phenylindole (DAPI). Cells were then visualized with an inverted fluorescence microscope (Olympus). Anti-SLC1A5 antibody for HCS and IF was obtained from Sigma-Aldrich. Anti-LC3 antibody was obtained from Cell Signaling Technology. Secondary antibodies used were Alexa 594- or 488-labeled anti-rabbit or anti-mouse IgG antibodies (Invitrogen).

Cells were treated with different concentrations of compounds for time periods indicated in the Results section before the radiotracer L-[3,4,3H] glutamine (Perkin Elmer; 5 μCi/mL) was added. Transport measurements were terminated after 15 minutes by three rapid washes with ice-cold PBS. Intracellular glutamine was extracted with PBS containing 0.2% SDS and 0.2 N NaOH. After 1-hour incubation at room temperature, lysates were neutralized with 2 N HCl and quantified using liquid scintillation counter (Beckman LS6500).

All cell lines were seeded (4,000 cells in 100 μL per well) in 96-well plates. Cells were allowed to attach overnight. Tested compounds were serially diluted using media from stock solutions (10 mmol/L) and were added to cells. Tests were performed in triplicate, and each microplate included media and DMSO control wells. Cell viability was assessed using ATPlite according to manufacturer's protocol. Cell growth inhibition was calculated as a percentage of DMSO-treated controls and plotted against the compound concentration.

For colony-formation assays, cells were plated in triplicate (500 cells/well) in 6-well plates or 100 cells/well in 24-well plates and grown overnight before compounds were added. After 1 to 2 weeks, depending on cell line, colonies were stained with Accustain Crystal Violet solution (Sigma-Aldrich) for 30 minutes. Plates were rinsed with water and images were acquired by scanning. Colony formation efficiency was calculated relative to the number of colonies in control (DMSO)-treated wells.

Briefly, cells were resuspended in fresh medium and counted. Cell suspensions of 20 μL (200 cells) were pipetted into each well of the hanging drop plate. Plate was covered with lid and put upside down in a container with wet filter paper to keep the cells hydrated. The plate was maintained at 37°C in humidified incubator with 5% CO₂ to allow the spheroids to form. Cells were imaged after three days to check for aggregation and cell proliferation. After spheroids were formed, they were transferred to a 24-well plate, which was plated with 0.5 mL of medium on top of 0.7% agar layer in each well. Different concentrations of IMD-0354 were added to wells and the growth of spheroids was monitored every two days under microscope.

Total RNA was extracted using a total RNA Miniprep Kit (Sigma) with the On-column DNase I digestion step included. cDNA was synthesized using cDNA kit from Applied Biosystems according to the manufacturer's protocol. Real-time PCR was performed on a Bio-Rad CFX Connect Real-Time System using FastStart Universal SYBR Green Master from Bio-Rad. H3A was used as an internal control. Quantitative PCR reactions were performed in triplicates. PCR primers were designed using PrimerBank (http://pga.mgh.harvard.edu/primerbank).

Cell extraction and gas chromatography-mass spectrometry (GC-MS) analysis for metabolite quantification were performed as described previously (28). For GC-MS analysis, intracellular metabolite amounts are expressed as nmol per cell sample (cells from one well of six-well plates; approximately 0.5 × 10⁶ to 1.0 × 10⁶ cells) and (in Fig. 3E) normalized to controls. Glucose (Glc), lactate, and glutamine (Gln) in culture medium samples were measured using YSI 2950 analyzer (YSI OH, USA). For Glc and Gln estimation in the media, the starting concentrations of Glc and Gln were 24.75 and 4.0 mmol/L, respectively, which is their standard concentration in high-glucose DMEM.

A375 cells were treated as indicated in the text. Cells were trypsinized and fixed in 70% ice-cold ethanol for 60 minutes, washed in PBS, and incubated for 30 minutes at 25°C in propidium iodide (PI) buffer [10 mmol/L Tris-HCl (pH 7.4), 5 mmol/L MgCl₂, 50 μg of PI per mL, and 10 μg of RNase A/mL]. The stained cells were acquired by the FACSort flow cytometer (BD Biosciences), and the DNA content was analyzed using FlowJo software.

A375 cells were treated as indicated in Results. Cell fractionation was performed using Cell Fractionation Kit (No. 9038, Cell Signaling Technology) according to the manufacturer's protocol. Cytoplasmic and membrane proteins were then subjected to Western blotting analysis.

A375 cells were treated as indicated in the text. Total RNA was extracted using a total RNA Miniprep Kit (Sigma) with the On-column DNase I digestion step included. Libraries were prepared from isolated total RNA using the QuantSeq 3′ mRNA-Seq Library Prep Kit FWD for Illumina from Lexogen. Barcoded libraries were pooled and single end sequenced (1×75) on the Illumina NextSeq 500 using the High output V2.5 kit (Illumina Inc.). Read data were processed and multiplexed with the BlueBee Genomics Platform (BlueBee).

Lexogen 3′ mRNA-sequencing reads were processed using cutadapt v1.18 (29) to remove adapter remnants. Sequencing reads were then aligned using STAR aligner version 2.7 (30) to human genome version 38 and Ensemble gene annotation version 84. RSEM v1.3.1 (31) was used to estimate gene expression. Estimated read counts from different groups were compared using the R Bioconductor package DESeq2 following generalized linear model based on negative binomial distribution (32). Genes with Benjamini-Hochberg–corrected P value <0.05 and fold change ≥2 or ≤0.5 were selected as significantly differentially expressed genes.

Differentially expressed genes were uploaded to Ingenuity Pathway Analysis (IPA, November 2019; Qiagen) for further analyses. Top canonical pathways and upstream regulators were exported to illustrate the biological mechanism. Enrichment results of different comparisons were compared with the published datasets using IPA Analysis Match function. RNA-sequencing data have been uploaded to the GEO public database (GSE165899).

All animal studies were conducted in the SBP Medical Discovery Institute Animal Facility in accordance with the Institutional Animal Care and Use Committee guidelines (IACUC No. 18–079). Mice were maintained in a pathogen-free environment with free access to food. Six-week-old male C3H mice were purchased from Charles River Laboratories and allowed to acclimatize for 1 week. SW1 cells (0.5×10⁶, suspended in 150-μL sterile PBS) were injected into the subcutaneous tissue of the flank. When tumors reached approximately 150 mm³, mice were randomized and sorted into treatment groups (n = 8 animal/group). Vehicle or IMD-0354 (20 mg/kg) was administered daily for 3 weeks intraperitoneally. Tumor volume was measured twice a week with Vernier calipers and calculated using the formula: [(length in millimeters × (width in millimeters)²)/2]. After the mice were sacrificed, tumors were frozen or fixed in 10% formalin and embedded in paraffin for IHC. Snap-frozen tumors were utilized for protein and RNA extraction for further analysis.

Statistical significance between two groups was assessed by the unpaired Student t test. Ordinary one-way ANOVA was used to analyze more than two groups. Two-way ANOVA was utilized to analyze cell proliferation at multiple timepoints. GraphPad Prism 7 and 8 software was used for to perform all statistical calculations. All cell culture experiments were performed three times. Data is presented as mean ± SD (unless noted otherwise in the figure legends) and a P value less than 0.05 was considered statistically significant.

All reagents generated in this study are available from the lead contact with a completed Materials Transfer Agreement.

To assess the importance of SLC1A5, a key glutamine carrier protein in melanoma cells, we inhibited its expression in melanoma cell line A375, using two specific siRNA. Efficiency of SLC1A5 inhibition was monitored at the level of RNA and protein expression (Supplementary Fig. S1A and S1B), and glutamine uptake by ³H-labeled glutamine. ³H-glutamine uptake was effectively inhibited in cells transfected with siSLC1A5, compared with control cells (Fig. 1A). At later time points, cells harboring siSLC1A5 exhibited attenuated cell proliferation and colony formation (Fig. 1B and 1C). Because we were interested in identifying small-molecule inhibitors of glutamine uptake that work through perturbation of SLC1A5 membrane localization, we searched for cell lines with high SLC1A5 expression and single-layer clustered or cuboidal growth characteristics. Such cell lines would enable microscopic visualization of the plasma membrane, which is paramount for an image-based HCS quantifying subcellular localization of the membrane protein SLC1A5. Immunofluorescence (IF) analysis of different cell lines identified the skin epidermoid carcinoma cell line A431 as the best candidate for a high throughput screen, displaying pronounced SLC1A5 membrane localization in microscope images (Supplementary Fig. S1C). Consistent with the requirement of SLC1A5 in A375 cells, its silencing in A431 cells (Supplementary Fig. S1D) resulted in reduced expression of the protein (Fig. 1D) and inhibited ³H-glutamine uptake (Fig. 1E), with concomitant decrease in cell growth (Fig. 1F) and colony formation (Fig. 1G). These results demonstrate the important role SLC1A5 plays in cellular glutamine uptake and key cellular functions, reflected in two- and three-dimensional growth, both in melanoma and skin epidermoid carcinoma cells.

The data obtained with A431 cells prompted the design of a microscopy-based high-throughput screen for small-molecule inhibitors that would reduce the localization of SLC1A5 at the plasma membrane without significantly altering cell morphology. Given our findings that thapsigargin (TG) triggers degradation of SLC1A5 (14), we validated its possible use as a positive control in A431 cells. TG led to marked inhibition of SLC1A5 expression (Fig. 2A). To enable a microscopy-based screen, an Opera Phenix HCS system in combination with the Harmony HCS software package was used to determine the cellular fraction of SLC1A5 intensity on the membrane (Fig. 2B). A dose-dependent effect of TG on SLC1A5 membrane localization was established as part of the HCS assay implementation (Supplementary Fig. S2A).

Using approximately 7,000 small molecules from kinase inhibitors and approved drug libraries as well as a natural product–inspired library, a high-content microscopy-based screen was performed to identify those affecting SLC1A5 localization at the plasma membrane in A431 cells (Fig. 2C). Overtly toxic compounds were excluded (Supplementary Fig. S2B) and top hits (SLC1A5 PM Intensity < −40% Activity) that affected SLC1A5 membrane distribution, but not cell morphology, were selected (Fig. 2C; Supplementary Table S1). Of those, nine compounds (marked in red in Supplementary Table S1, structure and reference information of selected compounds in Supplementary Table S2) were subjected to independent validation using IF and ³H-glutamine uptake. Of these, IMD-0354 (Fig. 2D) appeared to exhibit the most striking effect, impairing plasma membrane localization of SLC1A5 (Fig. 2E), without affecting the membrane distribution of plasma membrane marker phalloidin (Supplementary Fig. S2C) and ATP1A1 (Supplementary Fig. S2D). IMD-0354 did not affect plasma membrane localization of other key members of the SLC family of carrier proteins SLC38A2 and SLC7A5 (Fig. 2F), ruling out a general attenuation in membrane localization of SLC carrier proteins. Notably, IMD-0354 was the only compound that inhibited ³H-glutamine uptake in both A375 and A431 cells (Supplementary Fig. S2E). Exposure of A431 cells to IMD0354 showed a dose-dependent dislocation of SLC1A5 from the plasma membrane (Supplementary Fig. S2F), suggesting a direct effect of the drug on its membrane localization. These findings identify IMD-0354 as a small-molecule inhibiting SLC1A5 localization at the plasma membrane in skin epidermoid and melanoma cells.

To verify the effect of IMD-0354 on glutamine uptake, A431 cells were treated with increasing concentrations of IMD-0354 and ³H-glutamine uptake was measured after 1 and 24 hours. Inhibition of glutamine uptake was evidenced 1 hour following IMD-0354 treatment and was sustained after 24 hours (Fig. 3A). Notably, this inhibition could also be seen as early as 15-minute exposure to IMD-0354 (Supplementary Fig. S3). Dose-dependent inhibition of glutamine uptake was also observed in A375 cells (Fig. 3B), as early as 1 and 3 minutes following IMD-0354 treatment of the melanoma cultures UACC903 and A375 (Supplementary Fig. S3B). These observations substantiated the inhibition of glutamine uptake by IMD-0354 in cancer cells.

To determine whether IMD-0354 affects other glutamine carrier proteins, we surveyed the expression of 10 such carrier proteins in A375 melanoma cells. Among those SLC1A5, SLC7A5, and SLC38A2 were the primary expressed carrier proteins (Supplementary Fig. S3C). We next monitored the expression of these proteins in melanoma cells that were subjected to IMD-0354 treatment, finding that the expression of SLC38A2 was unaffected compared with minor changes in the expression of SLC1A5 and SLC7A5 (Supplementary Fig. S3D). To further assess possible changes in the expression of SLC38A2, which is the main glutamine carrier protein expressed in addition to SLC1A5 in these melanoma cells, we monitored possible changes in its expression following KD of SLC1A5. Notably, inhibition of SLC1A5 expression using the corresponding siRNA, did not affect the expression of SLC38A2 (Supplementary Fig. S3E). Inhibition of SLC1A5 expression increased the transcription of SLC7A5, an expected outcome given its ability to compensate for reduced glutamine uptake. These findings substantiate a primary role of SLC1A5 in glutamine uptake in melanoma cells, consistent with its reported role in other cancer cell types (14, 21, 22).

One of the routes intracellular glutamine adopts is its conversion to glutamate, a reaction catalyzed by glutaminase. Expectedly, GC-MS-based analysis of A431 cells treated with IMD-0354 showed decrease in intracellular levels of glutamine and glutamate (Fig. 3C). Correspondingly, consistent with its suppressed intracellular levels, glutamine levels increased in the media (Fig. 3D). IMD-0354 did not induce any significant shift in the intracellular levels of essential amino acids, crucially ruling out any unintended suppression in the activity of other related amino acid transporters (Fig. 3E). Aspartate biosynthesis, catalyzed by glutamic-oxaloacetic transaminase 2 (GOT2), requires oxaloacetate and glutamate as substrates, and aspartate and glutamine are precursors for asparagine biosynthesis. Therefore, suppressed glutamine and glutamate levels in IMD-0354–treated A431 cells (Fig. 3C) decreased intracellular aspartate and asparagine levels (Fig. 3F).

SLC1A5-mediated glutamine uptake is important for the maintenance of mTORC1 activity, an effect that is uncoupled from glutamine metabolism (33). To determine whether IMD-0354 affects mTORC1 function, A375 cells were treated with IMD-0354 (1, 3, and 24 hours) and the phosphorylation of p70S6K, a direct substrate of mTORC1, was examined. Following IMD-0354 treatment, phosphorylation of p70S6K was attenuated (Fig. 4A). Among the initial hits in our screen was a Rho-associated kinase inhibitor ((S)-H-1152), which perturbed plasma membrane localization of SLC1A5, albeit to a lesser extent as seen for IMD-0354 (Supplementary Fig. S2E). Consistently, this inhibitor exhibited less pronounced suppression of mTORC1 activity (Fig. 4A).

IMD-0354 was reported to inhibit IKKβ in human mastocytoma cells (HMC-1; ref. 34). To test the possible effect of IMD-0354 on the NF-κB pathway, IMD-0354 was compared with TPCA-1, an independent IKK inhibitor V (35), also identified in our screen. TNFα stimulation, expectedly, increased IκB phosphorylation, an effect attenuated by TPCA-1 but not by IMD-0354 (Fig. 4B). Correspondingly, TPCA-1, but not IMD-0354, upregulated levels of IκB, a negative regulator of NF-κB signaling (Fig. 4B). Similarly, IMD-0354 failed to suppress NF-κB signaling in A431 cells (Supplementary Fig. S4A). To evaluate a possible link between NF-κB signaling and glutamine uptake, we genetically silenced IKK-1 and IKK-2 using corresponding siRNA in A375 and A431 cells, which were then subjected to ³H-glutamine uptake assay. Knockdown of IKK did not affect glutamine uptake either in A431 or A375 cells (Supplementary Fig. S4B). Moreover, genetic inhibition of NF-κB pathway components failed to enhance attenuation of glutamine uptake elicited by IMD-0354 (Supplementary Fig. S4C). Taken together, these results suggest that inhibition of glutamine uptake by IMD-0354 is independent of NF-κB pathway components.

At higher concentrations, IMD was reported to have an impact on additional protein kinases, including MEK and p38 MAPK (34). Notably, neither of these kinases was affected by IMD-0354 (Supplementary Fig. S4D). Furthermore, neither of these kinase inhibitors, nor inhibitors to other cellular signaling pathways attenuated glutamine uptake, compared with the effect of IMD-0354 (Supplementary Fig. S4E). These findings substantiate the effect of IMD-0354 on glutamine metabolism, independent of previously reported signaling associated with this small molecule.

To further establish the mechanism underlying the effect of IMD-0354 on glutamine uptake, we monitored changes in glutamine uptake upon inhibition or ectopic expression of SLC1A5. Expectedly, siRNA-mediated SLC1A5 knockdown effectively attenuated ³H-glutamine uptake on its own; however, it did not significantly accentuate the inhibition of glutamine uptake elicited by IMD-0354 (Fig. 4C). Moreover, overexpression of SLC1A5 partially restored glutamine uptake inhibited by IMD-0354 (Fig. 4D). Furthermore, ectopic expression of SLC1A5, but not SLC38A2, attenuated the effect of IMD-0354 on melanoma cell viability (Fig. 4E). Taken together, these results suggest that inhibition of glutamine uptake by IMD-0354 is largely mediated by SLC1A5.

To determine whether the effect of IMD-0354 is limited to the melanoma cells studied here, we set to monitor the viability of other cancer and nontransformed cell lines following treatment with this inhibitor. Extending the analyses to additional melanoma, as well as prostate, pancreatic, colon, lung, and kidney tumor–derived cell lines revealed that IMD-0354 effectively inhibited the viability of diverse tumor cell lines, in a dose-dependent manner (Fig. 4F). Studying the effect of IMD-0354 on nontransformed immortalized melanocytes and a fibroblast cell line revealed effective dose-dependent inhibition, albeit, to lesser degree. While a dose of 1.25 μmol/L IMD-0354 caused more than 90% inhibition of A375 cell viability, it was limited to approximately 40% for the nontransformed cells (Fig. 4F). Furthermore, while higher concentrations of IMD-0354 dose dependently suppressed melanoma cell viability, the degree of inhibition in fibroblast cell line GM00038 was limited to 40% (Fig. 4F).

Recognizing the effect of the inhibition of glutamine uptake on melanoma growth (Fig. 1B and C; refs. 28, 36), we further assessed the effect of IMD-0354 on tumor cell growth in two- and three-dimensional cultures. Along with its antiproliferative effect on multiple tumor cell lines (Fig. 4F), IMD-0354 treatment led to a dose-dependent inhibition of cell proliferation and colony formation in both A375 and A431 tumor cell lines (Fig. 5A and B) as well as melanoma spheroid formation (Fig. 5C), representative of tumor architecture in vivo.

Among mechanisms reported to underlie the effect of glutamine uptake inhibition by attenuated SLC1A5 expression on tumor cell growth is cell-cycle suppression, often reflected in G₁ arrest (36–38). Indeed, treatment of melanoma cells with IMD-0354 resulted in an increased fraction of cells in the G₁ phase (from 40% to over 50%, within the range of 0.32 – 1.25 μmol/L), with a corresponding decrease in S and G₂ phases of the cell cycle (Fig. 5D). Consistent with our earlier work showing prolonged attenuation of glutamine uptake by inhibition of SLC1A5 inducing autophagy (14), treatment with IMD-0354 increased staining of LC3 punctae, a key feature of autophagic cells (Fig. 5E). Prolonged deprivation of glutamine or higher concentration of IMD-0354 induced apoptosis, as determined by increased fraction of cells in the sub-G₁ phase (Fig. 5D, at concentration of 2.5–5 μmol/L). Corresponding to these changes was an increase in the expression of cell-cycle–inhibitory proteins p21 and p27, the processed form of LC3 and apoptotic markers, including PARP and CHOP (Supplementary Fig. S4F). Notably, the effect of IMD-0354 was not limited to attenuated growth, as Boyden chamber transwell assay revealed a notable inhibition of A375 cell migration (Fig. 5F), an effect also seen in response to SLC1A5 suppression (39). Collectively, these observations support the inhibitory effect of IMD-0354 on key phenotypic characteristics of tumor cells.

To identify unbiased changes in cellular signaling that are caused by IMD-0354, RNA-sequencing analysis was carried out on A375 cells that were subjected to three different concentrations (0.32 μmol/L, 0.63 μmol/L, and 1.25 μmol/L) of IMD-0354 over 24- and 48-hour periods. This analysis identified 480 genes that were upregulated and 516 genes that were downregulated (FC>2; BHP<0.05; Fig. 6A and B). Because the analysis was performed on cells subjected to distinct conditions (different concentrations of IMD-0354 for different durations), we were able to select for the common changes, narrowing the number of upregulated (n = 59) and downregulated (n = 40) genes (Fig. 6B). Top genes regulated by IMD-0354 treatment are implicated in cell cycle and DNA damage response pathways, as well as unfolded protein response (UPR) signaling (Fig. 6C), changes that were previously linked to curtailed glutamine metabolism (24, 36, 40). Correspondingly, upstream components predicted to impose the changes identified following IMD-0354 treatment are regulatory components of cell cycle (Fig. 6D) as well as central metabolic regulatory proteins, including c-Myc and the UPR signaling component CHOP (DDIT3; Fig. 6E). A vast majority of the final set of IMD-0354–responsive genes were implicated in key cell cycle and ROS/UPR signaling (Fig. 6F). Notably, integration of the major changes identified in this analysis revealed glutamine metabolism as a major downregulated (P = 9.2e-4) and AKT signaling as a key upregulated signaling pathway (P = 2.5e-4), providing independent support for the impact of IMD-0354 on glutamine metabolism (Fig. 6E).

To further understand IMD-0354 mechanism of action, the molecular profiles from RNA-sequencing were compared with public datasets. The signaling pathways and regulators predicted to be associated with response to IMD-0345 were first compared with the small-molecule inhibitor treatment signatures from the Library of Integrated Network-Based Cellular Signatures (LINCS). Small molecules targeting CHK1, PI3K, GSK-3β showed a gene expression signature (suppressed E2F and MYC signaling, and activated TP53, TNF, IL1B, and IL6 pathways) that was similar to the one obtained with IMD-0354 treatment (Supplementary Fig. S5A). Next, IMD-0345 profiles were compared with different skin melanoma subtypes characterized by somatic mutations (Supplementary Fig. S5B). Interestingly, these melanoma subtypes showed opposite z-scores for similar set of genes (listed above), suggesting that IMD-0345 may reverse the signaling pathways important for these tumor subtypes. Interestingly, the small-molecule targets converged on common canonical pathways, including PTEN, STAT3, and cell cycle signaling pathways (Supplementary Fig. S5C), indicating an essential role of IMD-0345 in interrupting these key pathways for tumor development and progression. qRT-PCR analysis confirmed the changes identified by RNA-sequencing in key regulatory nodes (UPR, cell cycle/DNA damage, and ROS; Fig. 7A–C). The transcriptional signature observed following IMD-0354 treatment was also seen upon genetic inhibition of SLC1A5 in A375 cells (Supplementary Fig. S6A) or upon deprivation of glutamine from media of cultured melanoma cells (Supplementary Fig. S6B), further substantiating that the effect of IMD-0354 is consistent with the inhibition of glutamine uptake.

The identification of UPR as key signaling pathway and its key component ATF4, led us to explore the importance of ATF4 for IMD-0354 response. Knockdown of ATF4 effectively attenuated the cytotoxic effect of IMD-0354 (Fig. 8A). Furthermore, activation of UPR components seen following IMD-0354 treatment, was effectively blocked in cells that were subjected to siATF4 (Fig. 8B). These findings substantiate the importance of UPR, with ATF4 as a central player, in glutamine metabolism and the effect of IMD-0354 on this pathway.

Our previous work has shown that inhibition of lactate dehydrogenase isoform A (LDHA), the enzyme responsible for aerobic glycolysis—through catalysis of pyruvate oxidation to lactate—results in an expansive prosurvival response (5). This includes upregulation of SLC1A5 and glutamine uptake in melanoma cells, as part of metabolic reprogramming in response to LDHA inhibition (5). To examine whether suppression of glutamine uptake by IMD-0354 may conversely affect aerobic glycolysis, first, IMD-0354–treated A431 cells were tested for intracellular lactate levels by GC-MS–based analysis. Also, the media in which these cells were cultured and treated with IMD-0354 was analyzed for glucose and lactate levels. IMD-0354 enhanced both intracellular and the media levels of lactate, while curtailing levels of glucose in the media (Fig. 8C). Together, these data suggested glycolytic compensation (glucose utilization) for suppressed glutamine uptake caused by IMD-0354. This observation prompted us to examine whether coinhibition of SLC1A5 and LDHA may have greater impact on tumor cell proliferation. Genetic inhibition of both SLC1A5 and LDHA, using corresponding siRNAs, led to a more effective suppression of melanoma cell proliferation and colony formation (Supplementary Fig. S7A and S7B). Given these observations, we assessed the effect of combined IMD-0354 and GNE-140 (a specific LDHA inhibitor; ref. 41) treatment on the viability of melanoma cells. Treatment of BRAF-mutant human as well as NRas–mutant mouse melanoma cells with the combination of IMD-0354 and GNE-140 led to a more pronounced suppression of their viability as compared with the effect of either treatment alone (Supplementary Fig. S7C).

Given that cellular glutamine metabolism is dependent on its uptake (primarily facilitated by SLC1A5) as well as its assimilation (mediated by GLS1), we asked whether a combination of the glutamine uptake and assimilation inhibitors would achieve more effective inhibition of melanoma cell proliferation. Inhibition of glutamine uptake was performed by either genetic inhibition of SLC1A5 or by using the pharmacologic inhibitor identified and characterized in this study, IMD-0354. Combination of either IMD-0354 or siSLC1A5 with the glutaminase inhibitor CB-839 led to an additive (∼20%) inhibition of melanoma cell growth (Supplementary Fig. S7D). These findings substantiate the importance of IMD-0354 in inhibition of glutamine uptake and its implication for glutamine metabolism in melanoma proliferation.

We next assessed the effect of IMD-0354 on melanoma tumor growth in vivo. SW1 melanoma cells harboring activating NRAS mutation were injected into syngeneic C3H mice, which were treated one week later with IMD-0354 (20 mg/kg) daily for the duration of the study. Treatment of mice with IMD-0354 inhibited SW1 melanoma xenograft growth as compared with the vehicle-treated group (Fig. 8D and E). IHC performed on the tumor sections confirmed that the tumors from IMD-0354–treated animals exhibited inhibition of proliferation (Ki67 staining) and mTOR activity (pS6 expression as a marker), concomitant with increased apoptosis (caspase-3 cleavage staining) compared with the vehicle-treated tumor group (Supplementary Fig. S8). These observations substantiate the findings and the characterization of IMD-0354 in cultured melanoma cell lines.

Cancer cells exhibit high biosynthetic and energetic demands, requiring ample nutrient availability (42). While glucose is the chief source of carbons needed for macromolecular biosynthesis and ATP generation, glutamine has emerged as another key nutrient for cancer cells (2). Studies in a number of cancer types have demonstrated how glutamine uptake and metabolism is upregulated to selectively promote tumor growth and resistance to therapy (12, 43). Our own work has demonstrated the importance of glutamine metabolism for breast cancer responsiveness to taxane therapy, whereby increased glutamine uptake was shown to confer resistance to paclitaxel (14). These observations supported the rationale for identifying novel inhibitors to suppress glutamine metabolism. Although glutaminase inhibitor (CB-839) that blocks anaplerotic entry of glutamine carbons into the TCA cycle is currently being evaluated in a number of clinical trials, attaining durable clinical response is likely to require also overcoming extramitochondrial functions of glutamine. Therefore, we set our focus on possible inhibition of glutamine uptake, searching for small molecules that would inhibit one of the key glutamine carrier proteins, SLC1A5. Here we report a microscopy-based screen of cancer cells for small molecules that can interfere with the membrane localization of SLC1A5 and hence compromise its function in glutamine uptake. IMD-0354 was identified as a top hit, which was confirmed to attenuate the uptake of glutamine in a number of different cancer cell lines. We report the implications of IMD-0354–mediated impairment of SLC1A5 function on (i) melanoma growth in culture and in vivo, using xenografts; (ii) define cellular pathways that are perturbed and causally involved in growth suppression exerted by IMD-0354; and (iii) unveil underlying mechanistic and functional parallels between IMD-0354-mediated and other glutamine metabolism–targeting strategies. While demonstrating the therapeutic benefit of limiting glutamine access of melanoma cells, our studies identify enhanced aerobic glycolysis as the mechanism of cellular metabolic rewiring in IMD-0354–treated cells. Importantly, our investigations go on to show how coinhibiting aerobic glycolysis via LDHA inhibition can overcome metabolic escape of IMD-0354–treated melanoma cells and achieve effective suppression of cell proliferation.

IMD-0354, previously shown to suppress IKKβ activity, blocks nuclear translocation of NF-κB (34). Our screen identified two IKK inhibitors, which initially suggested a putative role of NF-κB signaling in glutamine uptake. Yet, our detailed investigations, utilizing an additional chemical inhibitor of IKK and the latter's genetic inhibition ruled out a putative role of IKK-NF-κB pathway in glutamine uptake. These data suggest that in melanoma alternative pathways are regulated by IMD-0354. Notably, in response to glutamine deprivation, IKKβ was shown to interact with and phosphorylate 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase isoform 3 (PFKFB3), a major driver of aerobic glycolysis. This phosphorylation resulted in inhibition of PFKFB3 activity, and aerobic glycolysis, with co-inhibition of IKKβ and glutamine metabolism resulting in synergistic killing of cancer cells (44). It is, therefore, conceivable that a concomitant suppression of glutamine uptake and alleviation of IKKβ-mediated suppression of glycolysis by IMD-0354, could render glycolysis as a synthetic vulnerability of glutamine-deprived melanoma cells, sensitizing them to the inhibition of aerobic glycolysis. This idea is supported by our studies, showing stronger antiproliferative effect of combined IMD-0354 and LDHA inhibitor. Although glycolytic enhancement through modulation of PFKFB3 activity is plausible, the precise mechanism underlying the ability of IMD-0354 to enhance glycolytic pathway and thus mark it as a potential synthetic lethal partner for concurrent suppression of glutamine uptake remains to be established. A combination of IMD-0354 and CB-839 curtailing both uptake and assimilation of glutamine led to an effective inhibition of melanoma cell proliferation. This further supports the importance of glutamine metabolism block in melanoma growth and the cooperative effect of blocking glutamine uptake and its assimilation.

Our RNA-sequencing studies followed by the validation of gene expression changes implicated cellular processes/pathways previously linked to altered glutamine metabolism, including DNA damage response signaling, cell cycle, autophagy, programmed cell death, and aspartate biosynthesis (45–47). Computational analyses pointed to the importance of UPR and in particular ATF4, with experiments establishing the functional requirement of ATF4 in IMD-0354-mediated growth suppression. As IMD-0354 impairs plasma membrane distribution of SLC1A5, components of the posttranslational machinery, plasma membrane localization, and anchoring stand as likely candidates for IMD-0354 effect.

How specific is IMD-0354 for SLC1A5 and glutamine uptake? Through a number of independent studies, we have demonstrated that IMD-0354 inhibits glutamine uptake, which is primarily mediated by SLC1A5. We have excluded the effect of IMD-0354 on SLC38A2, another key glutamine carrier protein. Within the range of concentrations tested, our studies also exclude the effect of IMD-0354 on the NF-κB and p38/MAPK pathways, that were previously suggested to serve as IMD-0354 targets. Mapping gene expression profiles, coupled with changes in cell death and autophagy programs, seen following IMD-0354 treatment, are consistent with independent studies which reported similar changes following inhibition of glutamine uptake. With these, one cannot exclude the possibility that IMD-0354 may also affect additional cellular targets, which may complement those associated with glutamine inhibition. Targeting of any given metabolic pathway is limited given the dynamic interplay among different metabolic signaling pathways. Thus, targeting glutamine uptake is expected to impact other metabolic pathways, a point we experimentally addressed by combination of glutamine uptake and LDH inhibition. We have also demonstrated a partial rescue of IMD-0354–mediated suppression of melanoma cell proliferation by overexpression of SLC1A5. Notably, such rescue was limited to a narrow range of IMD-0354 concentrations, likely due to nonspecific effects of high IMD-0354 concentrations, an aspect deserving further studies.

Rampant metabolic rewiring in cancer cells poses a major challenge to nutrient restriction approaches. While clearly an impediment to achieving durable therapeutic responses, greater understanding of cellular adaptive mechanisms to amino acid restriction approaches have started to reveal actionable vulnerabilities that are guiding development of effective combination treatments (41, 48, 49). Our studies with IMD-0354 have highlighted the compensatory role of enhanced glucose metabolism (aerobic glycolysis). These findings complement previous reports that show suppression of aerobic glycolysis—by LDHA inhibition—increasing dependence on enhanced glutamine uptake and increased TCA cycle activity, forming rationale for combining LDHA inhibitors with the complex I inhibitors of the mitochondrial electron transport chain (41, 50). While our findings of the interplay between glutamine and glucose metabolism and the effectiveness of combining IMD-0354 with LDHA inhibition, form basis for further preclinical testing of this combination, currently there are no effective LDHA inhibitors for in vivo use. As MAPK pathway is constitutively active in a large majority of melanomas and is a well-established regulator of glucose metabolism (51), in part, through LDHA regulation (5), combining IMD-0354 with FDA-approved MAPK signaling inhibitors presents a potentially viable therapeutic option that should be further investigated in preclinical studies.

G. Pathria reports grants from NCI during the conduct of the study and other from Genentech outside the submitted work. S. Heynen-Genel reports grants from NCI during the conduct of the study. M.R. Jackson reports grants from NIH/NCI during the conduct of the study. B. James reports grants from NCI during the conduct of the study. D.A. Scott reports grants from NCI during the conduct of the study. Z.A. Ronai reports grants from NCI during the conduct of the study and nonfinancial support and other from Pangea Therapeutica outside the submitted work. No disclosures were reported by the other authors.

Y. Feng: Data curation, formal analysis, validation, investigation, methodology, writing–original draft. G. Pathria: Formal analysis, writing–review and editing. S. Heynen-Genel: Data curation, formal analysis, supervision, writing–original draft. M.R. Jackson: Formal analysis, supervision. B. James: Data curation, formal analysis. J. Yin: Data curation, formal analysis. D.A. Scott: Data curation, formal analysis. Z.A. Ronai: Conceptualization, formal analysis, supervision, funding acquisition, investigation, writing–original draft, project administration, writing–review and editing.

We thank members of the Bioinformatic, Metabolomic, and the shared animal facilities as well as the members of the CPCCG for their help in carrying out different aspects of these studies. This work was supported by NCI grant R35CA197465, DOD grant CA1810216, MRA grant 509524 (to Z.A. Ronai) are gratefully acknowledged. This work was also supported through grant P30 CA030199 to Shared Resource Facilities at the Sanford Burnham Prebys NCI designated Cancer Center.

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