Anticancer composition comprising inhibitor of SLC1a5 variant mitochondrial glutamine transporter

Abstract

The present invention relates to an anticancer composition comprising an inhibitor of a mitochondrial glutamine transporter, which is an SLC1A5 variant. A material capable of selectively inhibiting the mitochondrial glutamine transporter, which is an SLC1A5 variant, according to the present invention selectively inhibits the mitochondrial glutamine transporter without affecting the function of a plasma membrane glutamine transporter, and inhibits the mitochondrial transport of glutamine, thus having the effect of inducing metabolic crisis in cancer cell survival and inhibiting the growth of cancer cells.

Description

Anticancer composition comprising an inhibitor of the SLC1A5 mutant mitochondrial glutamine transporter

[0001] The present invention relates to an anticancer composition comprising an inhibitor of the mitochondrial glutamine transporter, which is a SLC1A5 mutant.

[0002]

[0003] Glutamine is the most abundant amino acid in the blood and plays a crucial role in cellular functions, including the synthesis of metabolites that maintain mitochondrial function, the production of antioxidants, the synthesis of nonessential amino acids, nucleotides, and fatty acids, and the activation of growth signaling. In particular, the mitochondrial glutamine metabolic pathway is a crucial supplemental pathway for energy and lipid production in rapidly proliferating cells. Therefore, its importance has been highlighted by the high dependence of rapidly proliferating cancer cells on glutamine for growth. Specifically, cancer cells utilize glutamine instead of glucose through the reductive carboxylation pathway to generate acetyl-CoA for lipid synthesis under hypoxic conditions, and pancreatic cancer cells are known to generate reducing power in the form of NADPH from glutamine. Glutamine has been reported to be a major source of high-energy electrons for oxidative phosphorylation, particularly following Ras activation. Its role as a signaling molecule in vivo is also important, as glutamine activates the mTORC1 pathway and promotes cell growth. Thus, glutamine is an essential element in cancer cell metabolism, and the fact that cancer cells are sometimes addicted to glutamine highlights its importance. Cancer cells uptake glutamine through several glutamine transporters belonging to the SLC1, 6, 7, and 38 protein families. Among these, SLC1A5 (or ASCT2) is an essential sodium-dependent transporter for neutral amino acids such as alanine, serine, threonine, asparagine, and glutamine. SLC1A5 is known to be involved in various cancers, including lung, colon, stomach, kidney, ovarian, breast, tongue, and pancreatic cancers. Inhibition of SLC1A5 expression interferes with glutamine uptake, leading to impaired mTORC1 signaling and activation of autophagy.Inhibition of SLC1A5 expression in lung cancer cells has been reported to decrease glutamine uptake and cell proliferation. These effects have also been reported in acute myeloid leukemia and multiple solid tumors. Therefore, mitochondrial glutamine metabolism is crucial for cancer cell metabolism. This process requires cytosolic glutamine to cross the mitochondrial membrane via mitochondrial glutamine transporters, necessitating in-depth research on glutamine transporters.

[0004] Accordingly, the inventors of the present invention have made efforts to discover a new substance that can selectively inhibit the mitochondrial glutamine transporter, which is a SLC1A5 mutant, and as a result, they have confirmed through experiments that the selected compound selectively inhibits the mitochondrial glutamine transporter without affecting the function of the plasma membrane glutamine transporter, and inhibits the transport of glutamine into the mitochondria, thereby inducing a metabolic crisis in cancer cell survival and inhibiting cancer cell growth.

[0005]

[0006] The technical problem to be achieved by the present invention is to provide a composition for preventing or treating cancer that selectively inhibits the mitochondrial glutamine transporter, which is a SLC1A5 mutant.

[0007]

[0008] In order to achieve the above technical task, the technical task to be achieved by the present invention is to provide a composition for preventing or treating cancer comprising one selected from the following chemical formulas 1 to 5:

[0009] [Chemical Formula 1]

[0010]

[0011] (Here, R1 is , , , , , , , and ) is selected from

[0012]

[0013] [Chemical Formula 2]

[0014]

[0015] (Here, R1 is , , , , , , , , , , , , , , , , and , and R2 is methyl or hydrogen)

[0016]

[0017] [Chemical Formula 3]

[0018]

[0019] (So ​​R1 is and ) is selected from

[0020]

[0021] [Chemical Formula 4]

[0022]

[0023] (Here R1 is , , , , , , , , , , , and , and R2 is methyl or hydrogen)

[0024]

[0025] [Chemical Formula 5]

[0026]

[0027] (Here R1 is lim)

[0028] In the present invention, the composition may be characterized by inhibiting a mitochondrial glutamine transporter, SLC1A5 mutant, and not inhibiting a plasma membrane glutamine transporter.

[0029] In the present invention, the composition may be characterized by inhibiting transport of glutamine into mitochondria.

[0030] In the present invention, the composition may be characterized by inducing a metabolic crisis in cancer cells.

[0031] In the present invention, the composition may be characterized in that it is formulated in the form of a tablet, capsule, pill, granule, powder, injection or liquid.

[0032] In the present invention, the composition may include a compound represented by the following chemical formula:

[0033] [chemical formula]

[0034]

[0035] In the present invention, the compound is 6-(5-chloro-2-fluoro-4-hydroxyphenyl)quinazoline-2,4(1H,3H)-dione, 6-(2-fluoro-4-hydroxy-5-methylphenyl)quinazoline-2,4(1H,3H)-dione, 6-(2-fluoro-6-methoxyphenyl)quinazoline-2,4(1H,3H)-dione, 6-(4-hydroxy-2,6-dimethylphenyl)quinazoline-2,4(1H,3H)-dione, 6-(3,4-dimethoxyphenyl)quinazoline-2,4(1H,3H)-dione, 6-{4-[1-(morpholin-4-yl)ethyl]phenyl}quinazoline-2,4(1H,3H)-dione, 6-[2-(aminomethyl)-2,3-dihydro-1-benzofuran-7-yl]quinazolin-2,4(1H,3H)-dione, 4-(2,4-dioxo-1,2,3,4-tetrahydroquinazolin-6-yl)-N-methyl-N-(2-methylpropyl)benzamide, 6-{4-[2-(methoxymethyl)pyrrolidine-1-carbonyl]phenyl}quinazolin-2,4(1H,3H)-dione, 7-{4-[(2-ethylpiperidin-1-yl)carbonyl]phenyl}isoquinolin-1(2H)-one, 7-[4-(1-morpholin-4-ylethyl)phenyl]isoquinolin-1(2H)-one, 3-(1-Oxo-1,2-dihydroisoquinolin-7-yl)-N-(tetrahydro-2H-pyran-4-ylmethyl)benzamide, 7-[3-hydroxy-5-(2-piperidin-2-ylethyl)phenyl]isoquinolin-1(2H)-one, 7-(2-methoxy-5-methylphenyl)isoquinolin-1(2H)-one, 7-(2-fluoro-6-methoxyphenyl)isoquinolin-1(2H)-one, 7-[2-hydroxy-5-(trifluoromethyl)phenyl]isoquinolin-1(2H)-one, 7-(8-methylquinolin-5-yl)isoquinolin-1(2H)-one, 7-(2-chloro-6-methoxyphenyl)isoquinolin-1(2H)-one, 7-{5-[(4-butyl-1-piperazinyl)methyl]-2-methoxyphenyl}-1(2H)-isoquinolinone, 7-(8-methoxyquinolin-5-yl)isoquinolin-1(2H)-one, 7-[3-(azepan-1-ylcarbonyl)phenyl]isoquinolin-1(2H)-one, 6-(3-{[3-(hydroxymethyl)morpholin-4-yl]carbonyl}phenyl)isoquinolin-1(2H)-one, N-[3-(dimethylamino)propyl]-N-methyl-3-(1-oxo-1,2-dihydroisoquinolin-7-yl)benzamide,[3-(1-oxo-1,2-dihydro-7-isoquinolinyl)phenyl]acetic acid, 4-methyl-6-(3,4,5-trimethoxyphenyl)quinolin-2(1H)-one, N-ethyl-N-(4-hydroxybutyl)-4-(4-methyl-2-oxo-1,2-dihydroquinolin-6-yl)benzamide, 4-methyl-6-{4-[(4-methylpiperazin-1-yl)carbonyl]phenyl}quinolin-2(1H)-one, 6-(2,5-dimethoxyphenyl)-4-methoxyquinazoline trifluoroacetate, [4-(4-methoxy-6-quinazolinyl)phenyl]methanol, 6-[4-(2-aminoethyl)phenyl]quinazolin-4(3H)-one, 6-{3-[(4-methylpiperazin-1-yl)carbonyl]phenyl}quinazolin-4(3H)-one, 6-(5-chloro-2-fluoro-4-hydroxyphenyl)-4(3H)-quinazolinone, 6-{4-[(dimethylamino)methyl]phenyl}-4(3H)-quinazolinone, 6-[4-(2-methoxyethoxy)phenyl]quinazolin-4(3H)-one, 6-[4-(5-oxo-3-pyrrolidinyl)phenyl]-4(3H)-quinazolinone, 6-(2,3-dihydro-1,4-benzodioxin-6-yl)-4(3H)-quinazolinone, 6-[3-(methylthio)phenyl]quinazolin-4(3H)-one, It may be characterized by being any one selected from the group consisting of 6-[4-(4-isopropylpiperazin-1-yl)phenyl]quinazolin-4(3H)-one, 6-[4-(azocan-1-ylcarbonyl)phenyl]quinazolin-4(3H)-one, 6-(4-methoxy-3,5-dimethylphenyl)quinazolin-4(3H)-one, 2-methyl-6-[3-(1H-pyrazol-3-yl)phenyl]quinazolin-4(3H)-one, 6-(4-hydroxyphenyl)-2-methylquinazolin-4(3H)-one, and 3-[2-(4-amino-6-hydroxypyrimidin-2-yl)ethyl]-6-(4-fluorophenyl)quinazolin-4(3H)-one.

[0036] In the present invention, the cancer may be selected from the group consisting of leukemia, lymphoma, hematopoietic malignancy, cervical cancer, sarcoma, testicular cancer, malignant melanoma, endocrine tumor, bone cancer, prostate cancer, uterus cancer, breast cancer, bladder cancer, brain cancer, liver cancer, stomach cancer, pancreatic cancer, skin cancer, lung cancer, larynx cancer, head and neck cancer, esophageal cancer, colorectal cancer, and ovarian cancer.

[0037] As another example, the present invention provides a health functional food for preventing or improving cancer comprising the composition.

[0038] In addition, another embodiment of the present invention provides a method for screening a pharmaceutical composition for preventing or treating cancer, comprising the steps of: a) confirming the degree of binding of a candidate substance to positions F97, I104, and L105 of a mitochondrial glutamine transporter protein; b) treating a candidate substance with an excellent degree of binding to a mitochondrial glutamine transporter protein to confirm a change in the amount or biological activity of the protein; and c) treating a candidate substance that reduces the amount or activity of the mitochondrial glutamine transporter protein to a plasma membrane glutamine transporter to determine that the candidate substance is a substance for preventing or treating cancer when it is confirmed that the candidate substance has no effect.

[0039]

[0040] The substance capable of selectively inhibiting the mitochondrial glutamine transporter, which is an SLC1A5 mutant according to the present invention, selectively inhibits the mitochondrial glutamine transporter without affecting the function of the plasma membrane glutamine transporter, and inhibits the transport of glutamine into the mitochondria, thereby inducing a metabolic crisis in cancer cell survival and inhibiting the growth of cancer cells.

[0041]

[0042] Figure 1 confirms the homotrimeric structure and function of mitochondrial SLC1A5_var.

[0043] Specifically, (A) Endogenous SLC1A5_var, (B) exogenous SLC1A5_var, and (C) purified SLC1A5_var cross-linked using formaldehyde were analyzed on gradient gels. Monomeric, dimeric, and trimeric bands are indicated by arrows. (D) Two-step immunoprecipitations were performed for Myc-tagged, His-tagged, and Flag-tagged SLC1A5_var. The first step immunoprecipitation was performed with Flag antibody and eluted with 3X Flag peptide. The eluate was immunoprecipitated with His antibody in the second step to reveal interactions between the three different monomers of SLC1A5_var. (E) Mutants were generated by sequentially deleting amino acids from the C-terminus of SLC1A5_var. The deletion mutants were immunoprecipitated with Myc-tagged antibody and their interactions were analyzed. Interactions with HP1 del and TM3 del SLC1A5_var mutants were significantly inhibited. (F) Residues Phe97, Ala98, Gly101, Lys102, Iso104, and Leu105 are conserved in interactions between different SLC1A5_vars. (G) Immunoprecipitation of SLC1A5_var_WT and SLC1A5_var_FIL / AAA mutants was performed. While a strong interaction between the wild type was maintained, the interaction between the wild type and the FIL / AAA mutants was inhibited, and the interaction between the FIL / AAA mutants was significantly reduced. (H) Interactions of other mutants of SLC1A5_var with SLC1A5_var_WT were analyzed. Mutations in the FIL / AAA and GK / AA residues, which are key residues for the interaction, decreased the interaction. Mutations in the D / A domain and mutations in the predicted interaction site LRKY / AAAA did not alter the interactions between monomers.(IL) (I) Tritium-labeled glutamine uptake in mitochondria, (J) relative cell viability, (K) basal oxygen consumption rate, and (L) αKG levels were measured in EV, SLC1A5_var_WT, and SLC1A5_var_FIL / AAA mutants after siCon and siSLC1A5_var treatment (n=3). All data are expressed as mean ± standard deviation. P values ​​were determined by Student's unequal variance unbiased t test. *** p<0.001, ** p<0.01, * p<0.05, ns not significant.

[0044] Figure 2 confirms the iMQT_020 compound as an allosteric inhibitor of SLC1A5_var.

[0045] Specifically, Figure 2 (A) The structure of SLC1A5_var, a mitochondrial glutamine transporter, was predicted using RoseTTAFold2 and MZ-Dock using the amino acid sequence and information on the interactions between three monomers (cyan, green, and magenta). Inter-monomer interaction sites were identified as chemical binding sites, and 1.2 million compounds were docked to the allosteric site of the SLC1A5_var (magenta) monomer. Among them, 103 hit compounds were identified, and iMQT_020 was discovered through visual inspection, mitochondrial glutamine transport screening, protein interaction inhibition rate, and metabolic effect analysis. (B) Representative structural model of the homotrimeric SLC1A5_var. The inter-monomer interaction site is enlarged to show the interactions between residues Phe97, Ala98, Gly101, Lys102, Iso104, and Leu105 of each monomer. (C) Levels of mitochondrial glutamine transport, as measured by tritium-labeled glutamine, were monitored with 103 chemical compounds. iMQT_020 exhibited the highest inhibitory effect. (D) Chemical structure of iMQT_020. (E) Virtual docking structure of residues in SLC1A5_var that are important for interactions with other monomers upon binding of iMQT_020. The ΔG value was -6.42 kJ / mol, indicating binding of iMQT_020, and the inhibition constant (Ki) was 19.77 μM. (F) Virtual docking of iMQT_020 into the allosteric site of SLC1A5_var. iMQT_020 binds to the cavity containing the transmembrane domain of SLC1A5_var. The chemical binding residues (white) in SLC1A5_var are indicated. (G) Protein amounts of His-tagged SLC1A5_var and immunoprecipitated Myc-tagged SLC1A5_var, and HA-tagged SLC1A5 and immunoprecipitated Flag-tagged SLC1A5 in a concentration-dependent manner (n=3). Protein interactions were determined by IC inhibition of the interaction of SLC1A5_var. 50The value was 1.594 μM, and SLC1A5 was not calculated. (H) Size exclusion chromatography of eGFP-tagged SLC1A5_var WT and FIL / AAA mutant incubated with or without iMQT_020. Fractions of 8 to 13 mL were collected and blotted. (I) Concentration-dependent mitochondrial glutamine transport rate measured via tritium-labeled glutamine (n=3). The IC50 value was 6.156 μM. (J) Lineweaver-Burk plot of iMQT_020 (n=3). 3H-Glutamine was used as a substrate for competition assays. iMQT_020 exhibited noncompetitive inhibitor properties. (K) Inhibition of mitochondrial (top) and cellular (bottom) amino acid uptake by iMQT_020. Tritium-labeled glutamine, asparagine, serine, leucine, and proline were incubated with vesicles or iMQT_020 in the medium of isolated mitochondria or MIA PaCa-2 cells (n=3). Amino acid uptake was calculated relative to amino acid uptake by vesicles (n=3). (L) Microthermophoresis analysis of SLC1A5_var WT or SLC1A5_var FIL / AAA interacting with iMQT_020 at various concentrations. The interaction of SLC1A5_var WT and iMQT_020 was confirmed by a large difference in fluorescence. SLC1A5_var FIL / AAA did not interact with iMQT_020, as no difference in fluorescence was observed at various concentrations. (M) Normalized fluorescence values ​​of SLC1A5_var WT (red) and FIL / AAA (black) were checked, and the binding constant of iMQT_020 to SLC1A5_var WT was calculated to be 4.473 μM. (N) Circular dichroism spectra of SLC1A5_var WT and FIL / AAA. Spectra of SLC1A5_var WT and FIL / AAA at different concentration ratios were recorded. The spectral values ​​are corrected values ​​for the spectral values ​​in the base solvent.(O) Circular dichroism spectra of SLC1A5_var WT and FIL / AAA were incubated with vesicles or iMQT_020, and the spectra were recorded. The spectra are corrected for the base solvent. All data are expressed as mean ± standard deviation.

[0046] Figure 3 confirms that iMQT_020 selectively binds to mitochondrial SLC1A5_var.

[0047] Specifically, Fig. 3 (A,B) (A) Chemical properties of iMQT_020 and (B) energy levels of iMQT_020 docked onto the SLC1A5_var protein model in in-silico binding. (C) Activity assay of SLC1A5, SLC38A1, SLC38A2, SLC6A14, SLC6A19, SLC26A3, SLC26A4, SLC26A6, SLC26A7, SLC26A9, and ANO1 proteins according to the concentration of V-9302 and iMQT_020. Analysis of YFP protein-based activity was performed with control group: 0%, vesicle: 100% (n=3). (D) Western blotting analysis of thermal stability tests for SLC1A5_var, SLC1A5, SLC38A1, SLC38A2, SLC6A14, SLC6A19, SLC25A22, SLC26A3, SLC26A4, SLC26A6, SLC26A7, SLC26A9, and ANO1, treated with vesicles, IMQT_020, and V-9302. (E) Thermal stability tests comparing the normalized stabilities of each protein. The Tm value of SLC1A5_var was significantly different from that of iMQT_020. All data are expressed as mean ± standard deviation. P values ​​were determined by Student's unbiased t test with unequal variance; *** p < 0.001, ** p < 0.01, ns not significant.

[0048] Figure 4 confirms that mitochondrial SLC1A5_var inhibition impairs glutamine anaplerosis and redox balance in pancreatic cancer cells.

[0049] Specifically, Figure 4 (A) Representative illustration of the 13C isotope pattern using glutamine as a tracer. The integration of 13C atoms is represented as m+n, where n is the number of 13C atoms. (B,C) Metabolic abundance of [U-13C] glutamine-derived metabolites in MIA PaCa-2 cells treated with vesicles or iMQT_020 (B) glutamic acid, (C) αKG, calculated relative to unlabeled glutamine-derived metabolites in vesicles (n=3). (D-H) Metabolic abundance of [U-13C] glutamine-derived TCA metabolites (D) succinate, (E) fumarate, (F) malate, (G) oxaloacetate, (H) citrate, calculated relative to unlabeled glutamine-derived metabolites in MIA PaCa-2 cells treated with vesicles or iMQT_020 (n=3). (I-K) Metabolic abundance of [U-13C] glutamine-derived downstream glutaminolytic metabolites (I) glutathione, (J) proline, (K) palmitate, calculated relative to unlabeled glutamine-derived metabolites in MIA PaCa-2 cells treated with vesicles or iMQT_020 (n=3). The restorative effects of iMQT_020 and αKG on (LO) intracellular (L) GSH levels, (M) intracellular ROS levels, (N) mitochondrial ROS levels, and (O) ATP levels were observed (n=3). All data are expressed as mean ± standard deviation. P values ​​were determined by student's asymmetric two-tailed t-test; *** p<0.001, ** p<0.01, ns not significant.

[0050] Figure 5 confirms that mitochondrial SLC1A5_var inhibition induces mitochondrial damage without altering localization.

[0051] Specifically, Fig. 5 (A,B) (A) Fluorescence microscopy images of MIA PaCa-2 cells treated with vesicles or iMQT_020, labeled with Myc-tagged SLC1A5_var construct, and immunostained with anti-Myc, a mitochondrial marker (MitoTracker), and nuclei (Hoescht). Fluorescence intensity profiles of SLC1A5_var and mitochondria in vesicles and iMQT_020-treated cells are shown in the graph (B). (C) Submitochondrial fractions of MIA PaCa-2 cells treated with vesicles and iMQT_020 were performed and immunoblotted with the corresponding antibodies to localize SLC1A5_var to the mitochondrial outer membrane (OM), inner membrane (IM), and matrix. (D) Quantification of the images in (A). (A) The relative proportion of cells was classified into three categories based on mitochondrial morphology: fragmented, intermediate, and elongated / tubular. More than 100 cells were counted in each of three independent studies. (E) iMQT_020 altered mitochondrial membrane potential in MIA PaCa-2 cells. Cells from each condition were treated with 100 nM tetramethylrhodamine (TMRE) and analyzed using flow cytometry (n=5). All data are presented as mean ± standard deviation. P values ​​were determined by Student's unbiased t test with unequal variance; *p<0.05.

[0052] Figure 6 confirms that mitochondrial SLC1A5_var inhibition induces metabolic reprogramming of pancreatic cancer cells.

[0053] Specifically, Fig. 6 (A,B) OCR in MIA PaCa-2 cells overexpressing Con, SLC1A5_var WT, or SLC1A5_var FIL / AAA in the presence or absence of vesicles or iMQT_020 (n=3) as indicated by (A) or bar graph (B) over time. (C,D) Effect of glutamine on OCR in MIA PaCa-2 cells overexpressing SLC1A5_var WT or FIL / AAA in the presence or absence of vesicles or iMQT_020 (n=3) as indicated by (C) or bar graph (D) over time. (E,F) Effect of αKG on OCR of vesicles or iMQT_020 overexpressing Con, SLC1A5_var WT, or SLC1A5_var FIL / AAA overexpressed in MIA PaCa-2 cells (E) or as bar graphs (F) over time (n=3). (G,H) Effect of SLC1A5_var WT or FIL / AAA overexpressing vesicles or iMQT_020 in the presence or absence of glutamine overexpressing SLC1A5_var WT or FIL / AAA overexpressing MIA PaCa-2 cells (G) or as bar graphs (H) over time (n=3). (I,J) Effect of SLC1A5_var WT or FIL / AAA overexpressing vesicles or iMQT_020 in the presence or absence of glucose overexpressing SLC1A5_var WT or FIL / AAA overexpressing MIA PaCa-2 cells (I) or as bar graphs (J) over time (n=3). (K,L) Effect of vesicles or iMQT_020 overexpressing SLC1A5_var WT or FIL / AAA on ECAR in the presence or absence of glucose (K) or as a bar graph (L) in MIA PaCa-2 cells (n=3). (M, N) Effect of vesicles or iMQT_020 on OCR in isolated mitochondria of MIA PaCa-2 cells overexpressing Con, SLC1A5_var WT or FIL / AAA in siCon or siSLC1A5_var expressed in MIA PaCa-2 cells overexpressing Con, SLC1A5_var WT or FIL / AAA in the presence or absence of glutamine (n=3) or as a bar graph (M).(O) Changes in oxygen consumption rate in 25 human cancer cell lines with high OCR following iMQT_020 treatment and αKG supplementation (n=3). (P) Effects of vesicles or iMQT_020, or iMQT_020 plus αKG, on metabolic phenotypes in 25 human cancer cell lines with high OCR. Significant shifts from an energy metabolism phenotype (blue) to a resting state (red) and back to an energy metabolism phenotype (green). All data are presented as mean ± standard deviation. P values ​​were determined by Student's unpaired two-tailed t test; significance was indicated as p<0.0001 and p<0.001. P values ​​were determined by Student's unpaired two-tailed t test; **** p<0.0001, *** p<0.001, ** p<0.01, * p<0.05.

[0054] Figure 7 confirms that mitochondrial SLC1A5_var inhibition resets the metabolic fate of cytosolic glucose and glutamine in pancreatic cancer cells.

[0055] Specifically, Figure 7 (A) Diagram of the 13C isotope pattern using [U-13C] glucose as a tracer. The incorporation of 13C atoms is represented as m+n, where n is the number of 13C atoms. (B,C) Metabolic abundance of [U-13C] glucose-derived glycolytic metabolites (B) fructose-1,6-bisphosphate and (C) lactate, relative to unlabeled glutamine-derived metabolites in vesicles-treated MIA PaCa-2 cells (n=3). (D-F) Metabolic abundance of [U-13C] glucose-derived TCA cycle metabolites (D) citrate, (E) αKG, and (F) succinate, relative to unlabeled glutamine-derived metabolites in vesicles-treated MIA PaCa-2 cells (n=3). (G) Metabolic abundance of [U-13C] glucose-derived pentose phosphate pathway metabolites in MIA PaCa-2 cells treated with vesicles or iMQT_020. (G) 6-phosphogluconate, relative to unlabeled glutamine-derived metabolites in vesicles (n=3). (H,I) Metabolic abundance of [U-13C] glucose-derived hexosamine biosynthetic pathway metabolites in MIA PaCa-2 cells treated with vesicles or iMQT_020. (H) GlcNAc-1-P and (I) UDP-GlcNAc, relative to unlabeled glutamine-derived metabolites in vesicles (n=3). (J) Diagram of the 15N isotope pattern using [U-15N] glutamine as a tracer. Integration of 15N atoms is represented as m+n, where n is the number of 15N atoms. (KP) Metabolic abundance of cytosolic glutamine pathways. Nitrogen atoms in [U-15N] glutamine-derived (K) purines, AMP, and (L) pyrimidines, and UMP (n=3). Nitrogen atoms in [U-15N] glutamine-derived (M) asparagine and (N) UDP-GlcNAc, and non-[U-15N] glutamine-derived (O) asparagine and (P) UDP-GlcNAc, relative to unlabeled glutamine-derived metabolites treated with vesicles (n=3).All data are presented as mean ± SD. P values ​​were determined by Student's unpaired two-tailed t test; *** p < 0.001, ** p < 0.01, * p < 0.05.

[0056] Figure 8 confirms that mitochondrial SLC1A5_var inhibition causes metabolic crisis in pancreatic cancer cells.

[0057] Specifically, Figure 8 (A) GSEA-based KEGG pathway analysis of gene expression data from MIA PaCa-2 cells treated with Vesicle and iMQT_020 in RNAseq analysis. KEGG pathways related to amino acid, carbohydrate, energy, lipid, and nucleotide metabolism are analyzed by normalized abundance scores, p-values, and gene sizes from RNAseq data. (B) Western blotting analysis of protein expression. Proteins related to SLC1A5_var, p-S6K, S6K, amino acid metabolism, carbohydrate metabolism, lipid metabolism, and nucleotide metabolism. Band intensities were quantified under each band (n=3). (C) Metabolomic pathway analysis of metabolites identified by the compound finder. Metabolites are distributed across six superpathways, including exogenous, nucleotide, lipid, coenzyme and vitamin, and carbohydrate metabolism pathways. Welch's two-sample t-test; p<0.05.

[0058] Figure 9 shows the results of gene set enrichment profiles by inhibition of mitochondrial SLC1A5_var.

[0059] Specifically, Figure 9 (A) GSEA-based gene abundance plots represent two of the top 10 datasets in the GSEA KEGG pathway analysis, showing ES scores and the rank-ordered position of gene set members. Abundance plots for KEGG oxidative phosphorylation and KEGG glycolysis gluconeogenesis are shown. (B,C) GSEA Gene Ontology - Biological Process for gene expression data derived from RNAseq analysis of MIA PaCa-2 cells treated with vesicles and iMQT_020. (B) Gene Ontology - Biological Process for genomic processes related to metabolic processes is analyzed by normalized abundance scores, p-values, and gene sizes of RNAseq data. (C) GSEA Gene Ontology - Biological Process-based gene abundance plots represent two of the top 10 datasets in the GSEA Gene Ontology - Biological Process analysis, showing ES scores and the rank-ordered position of gene set members. The GOBP glycolysis process and GOBP oxidative phosphorylation abundance plots are shown. (D) HALLMARK gene sets derived from RNAseq analysis of MIA PaCa-2 cells treated with vesicles and iMQT_020. The top 16 HALLMARK gene sets are analyzed by normalized abundance scores, p-values, and gene sizes of RNAseq data. HALLMARK glycolysis and HALLMARK oxidative phosphorylation abundance plots are shown. (E) Metabolite set abundance analysis of metabolites extracted from MIA PaCa-2 cells treated with vesicles and iMQT_020.

[0060] Figure 10 confirms the induction of pancreatic cancer cell death by inhibition of mitochondrial SLC1A5_var.

[0061] Specifically, Figure 10 (A) Expression of SLC1A5_var, SLC1A5, SLC38A1, SLC38A2, and GAPDH in human pancreatic cell lines measured by RT-PCR. (B) A panel of 10 human pancreatic cancer cell lines and normal human epithelial pancreatic cell lines were exposed to a single concentration of iMQT_020 (10 μM, 48 h), and WST1-based viability measurements after treatment are shown (n=3). Cell lines with a Student's t-test p < 0.05 relative to the vesicle control are indicated below the dashed line. (C) Direct comparison of iMQT_020 on the viability of normal human pancreatic epithelial cells and human pancreatic cancer cells (n=3). Cells were incubated with the indicated concentrations of iMQT_020 for 48 h. The percentage of viability relative to vesicle exposure is shown. (D) Evaluation of SLC1A5_var expression levels in 11 cells for iMQT_020 sensitivity. Pearson r value was -0.7351, and p-value was less than 0.01. (E) Effect of iMQT_020 and αKG supplementation on cell viability in MIA PaCa-2, Panc-1, Capan2, and HPAF-II cells (n=3). (F) Expression of SLC1A5_var, SLC1A5, SLC38A1, SLC38A2, and GAPDH in PDAC patient-derived organoids measured by RT-PCR. (G) Effect of iMQT_020 exposure (10 μM, 48 h) on the viability of PDAC patient-derived organoids. Representative bright-field micrographs are shown at 10×. (H) Cells were cultured with the indicated concentrations of iMQT_020 for 48 h (n=3). The relative viability ratios are shown in the venipuncture. (J) Evaluation of SLC1A5_var expression levels in 10 organoids for iMQT_020 sensitivity. The Pearson r value was -0.6740, with a p-value of 0.0163. All data are presented as mean ± SD. Data are presented as mean ± SD. P values ​​were determined by Student's unpaired two-tailed t test; *** p < 0.001, ** p < 0.01, * p < 0.05.

[0062] Figure 11 confirms that mutations in SLC1A5_var expression and its genetic suppression throughout cells induce selective cancer cell death.

[0063] Specifically, in Fig. 11 (A), the expression of SLC1A5_var, SLC1A5, SLC38A1, SLC38A2, and GAPDH was measured by RT-PCR in lung, colon, brain, breast, and ovarian cell lines. (B) Cell viability was measured by WST1 assay after delivery of siCon or siSLC1A5_var to pancreatic, colon, lung, normal, and cancer cells (n=3). (C) Thirty-three cancer cell lines and six normal epithelial cell lines were exposed to a single concentration of iMQT_020 (10 μM, 48 h), and the results of WST1-based viability analysis after these treatments are shown (n=3). Colors are indicated in brown (brain), red (breast), blue (ovary), orange (lung), and magenta (colon). Cell lines with p < 0.05 versus the vesicle control in a Student's t-test are indicated below the dotted line. (D) The correlation between SLC1A5_var expression levels in 50 cells and iMQT_020 sensitivity was evaluated. The Pearson r value was -0.6881 with a p value less than 0.0001. All data are expressed as mean ± standard deviation; *** p < 0.001, ** p < 0.01.

[0064] Figure 12 confirms that mitochondrial SLC1A5_var inhibition selectively restricts cancer growth.

[0065] Specifically, Fig. 12. (A-E) The effects of iMQT_020 on human normal and cancer cells were directly compared. Cells were cultured with the indicated concentrations of iMQT_020 for 48 h. Percentage survival was plotted against survival for vesicle exposure. (A) Lung normal and cancer cells, (B) colon normal and cancer cells, (C) neural normal and cancer cells, (D) breast normal and cancer cells, (E) ovarian normal and cancer cells (n=3), ND (not determined).

[0066] Figure 13 confirms that mitochondrial SLC1A5_var inhibition exhibits low toxicity in vitro and in vivo.

[0067] Specifically, Figure 13. (A) Pharmacokinetic data showing trends in whole blood iMQT_020 concentrations after a single dose in healthy C57BL / 6 mice (IV: 5 mpk, IP: 75 mpk). (B,C) The IC50 for hERG toxicity for iMQT_020 was not determined in a concentration-dependent manner (n=4). (D) Mini-Ames assay of iMQT_020 against TA98 and TA100 at different concentrations (n=3). iMQT_020 did not introduce mutations greater than 2-fold baseline values ​​at different concentrations. (E) Biological evaluation of mice showing trends in body weight treated daily with vesicles, iMQT_020, or V-9302 (75 mpk per day) (n=6). (F,G) Plasma (F) glucose and (G) glutamine assessments following chronic daily exposure to 75 mpk of iMQT_020 (n=10). (H) H&E of lungs, liver, and kidneys from mice exposed to vesicles, V-9302, or iMQT_020. No significant toxicity was observed. (I) Chronic toxicity was assessed by measuring AST, ALT, and BUN in plasma from mice exposed to vesicles, V-9302, or iMQT_020. No significant toxicity was observed. (J,K), (J) (K) Viability and activation of murine T cells isolated from thymus or spleen after treatment with 10 μM V-9302 and iMQT_020 for 48 hours (n=3). Viability was measured with 7-AAD, and activation was measured by flow cytometry via CD44 expression. All data are presented as mean ± standard deviation. P values ​​were determined by Student's two-tailed t-test. ** p < 0.01, * p < 0.05, ns not significant.

[0068] Figure 14 confirms that inhibition of mitochondrial SLC1A5_var inhibits cancer growth in vivo.

[0069] Specifically, Figure 14 (A) Schematic illustration of a 31-day treatment period in mice bearing MIA PaCa-2 cell line grafts. (B) Photographs of pancreatic graft tumor tissues treated with vesicles, iMQT_020, or V-9302 at 75 mpk. (C) Volumetric analysis of vesicles, iMQT_020, or V-9302 (75 mg / kg body weight daily) during the treatment period (n=5). Treatment was initiated 4 days after MIA PaCa-2 cell injection. (D) Final tumor tissue weights of pancreatic graft tumor tissues treated with vesicles, iMQT_020, or V-9302 (75 mpk) at day 31 (n=5). (E) Immunohistochemical analysis of c-cas3 expression in grafts treated with vesicles or 75 mpk iMQT_020 or V-9302. Representative micrographs (top) and quantification (bottom) are shown (n=5). (F) Schematic of treatment in naive mice with pancreatic MIA PaCa-2 tumor tissues treated with vesicles containing 75 mpk of iMQT_020 or V-9302. Analysis of radiative efficacy of vesicles or iMQT_020 or V-9302 (75 mg / kg body weight daily) in mice with MIA PaCa-2 cell line models over a 22-day treatment period (n=5). Treatment began 7 days after MIA PaCa-2 cell injection. (H) Luminescent photograph of treated MIA PaCa-2 tumor tissues in naive mice. (I) Schematic of 31-day treatment in mice with NCI-H1299 cell line grafts. (J) Photograph of lung explant tumor tissues treated with vesicles containing 75 mpk of iMQT_020 or V-9302. (K) Volumetric analysis of lung explant tumor tissues treated with vesicles, iMQT_020, or V-9302 (75 mg / kg body weight daily) during the treatment period (n=5). Treatment was initiated 4 days after NCI-H1299 cell injection. (L) Final tumor tissue weights of lung explant tumor tissues treated with vesicles iMQT_020 or V-9302 (75 mg / kg body weight) on day 31 (n=5).(M) Immunohistochemical analysis of c-cas3 labeling in grafts treated with vesicles or 75mpk iMQT_020 or V-9302. Representative photomicrographs (top) and quantification (bottom) are shown (n=5). (N) Schematic diagram of the experimental setup in mice bearing COLO 205 cell line grafts during 31 days of treatment. (O) Photographs of colon graft tumor tissues treated with vesicles, iMQT_020, or V-9302 treated with 75mpk. (P) Volumetric analysis of vesicles, iMQT_020, or V-9302 (75 mg / kg body weight daily) during the treatment period (n=5). Treatment was initiated 4 days after COLO 205 cell injection. (Q) Final tumor tissue weights of colon graft tumor tissues treated with vesicles, iMQT_020, or V-9302 (75mpk) on day 31 (n=5). (R) Immunohistochemical analysis of c-cas3 expression in grafts treated with vesicles or 75mpk iMQT_020 or V-9302. Representative photomicrographs (top) and quantification (bottom) are shown (n=5). All data are expressed as mean ± SD. P values ​​were determined by Student's unpaired two-tailed t test; *** p<0.001, * p<0.05.

[0070] Figure 15 confirms that inhibition of mitochondrial SLC1A5_var upregulates the expression of PD-L1.

[0071] Specifically, Fig. 15 (A) Normalized mRNA expression levels and protein expression levels of PD-L1 were determined in KPC, LLC, and MC-38 mouse cancer cell lines by treating vesicles or iMQT_020 with 2 mM αKG or 10 μM CPI-455 for 24 hours. (B) (Top) The fluorescence of PD-L1-PE-labeled cells was represented as a histogram. KPC cells were treated with vesicles or iMQT_020 with 2 mM αKG or 10 μM CPI-455 for 24 hours. (Bottom) The percentage of PD-L1-positive KPC cells was determined by treating vesicles or iMQT_020 with 2 mM αKG or 10 μM CPI-455 for 24 hours. (C) The degree of H3K4me3 enrichment in the PD-L1 promoter region was determined by chromatin immunoprecipitation in KPC cells treated with 2 mM αKG in vesicles or iMQT_020 for 24 hours. Treatment with iMQT_020 confirmed an increase in H3K4me3 enrichment. All data are expressed as mean ± SD. P values ​​were determined by Student's unpaired two-tailed t test; *** p < 0.001, * p < 0.05.

[0072] Figure 16 confirms that inhibition of mitochondrial SLC1A5_var has a synergistic effect with anti-PD-L1 immunotherapy.

[0073] Specifically, Figure 16 (A) Schematic diagram of a 21-day treatment in mice with KPC cell line grafts. (B) Volumetric analysis of vesicles, anti-PD-L1 antibody (200 μg, every 3 days), iMQT_020, or V-9302 (75 mg / kg body weight, daily) during the treatment period (n=5). Treatment was initiated on day 7 after KPC cell injection. (C) Final tumor tissue weight of pancreatic explant tumor tissues on day 28 (n=5). (D) Schematic diagram of a 21-day treatment in mice with LLC cell line grafts. (E) Volumetric analysis of vesicles, anti-PD-L1 antibody (200 μg, every 3 days), iMQT_020, or V-9302 (75 mg / kg body weight, daily) during the treatment period (n=5). Treatment was initiated on day 7 after LLC cell injection. (F) Final tumor tissue weight of lung explant tumor tissues on day 28 (n=5). (G) Schematic diagram of the experimental design for 21-day treatment in mice with MC-38 cell line grafts. (H) Volumetric analysis of vesicles, anti-PD-L1 antibody (200 μg, every 3 days), iMQT_020, or V-9302 (75 mg / kg body weight, daily) during the treatment period (n=5). Treatment was initiated 7 days after MC-38 cell injection. (I) Final tumor tissue weight of colon explant tumor tissues on day 28 (n=5). (J-L) Immunohistochemical analysis of the expression levels of Ki-67 and cCas3 in each treatment group (J), a quantification graph of Ki-67 (K), and a quantification graph of cCas3 (L) are shown. (M) The percentage of PD-L1-positive tumor cells in tumor tissues was determined in each treatment group. (N and O) Immune cell analysis was performed using flow cytometry in tissues containing tumors to determine the cell ratios of PD-L1-positive tumor cells, PD-1-positive T cells, CD8-positive T cells, IFN-gamma-positive CD8 T cells, Granzyme B-positive CD8 T cells (N), CD4-positive T cells, Treg cells, Ly6G-positive MDSC, Lys6C-positive MDSC, and TAM (O).

[0074]

[0075] Hereinafter, the present invention will be described in more detail. However, the present invention may be implemented in various different forms and is not limited to the embodiments described herein.

[0076] The terminology used in this specification is solely for the purpose of describing specific embodiments and is not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly dictates otherwise. In the present specification, the term "comprising" or "including" a component does not exclude other components, but rather implies the inclusion of other components, unless otherwise specifically stated.

[0077] It is known that SLC1A5 mutants are overexpressed in cancer cells, and that suppressing them can induce metabolic crisis in cancer cells and kill them by inhibiting glutamine transport into the mitochondria of cancer cells.

[0078] The present invention is a new discovery of a substance that can function as an allosteric inhibitor of the mitochondrial glutamine transporter, which is a mutant of SLC1A5. By modeling the mitochondrial transporter protein, the in silico binding of candidate substances targeting the trimer binding site was confirmed, and when mitochondria were isolated from cells and the candidate substances were treated, the extent to which glutamine was transported into the mitochondria was confirmed, and furthermore, whether only the mitochondrial glutamine transporter was selectively inhibited was confirmed.

[0079] The binding pocket was identified by focusing on the trimeric interaction site near the F97, I104, and L105 regions, and 103 top candidates were selected through a primary screening using grid-based ligand docking of 1.2 million compounds in the Cambridge database. These 103 compounds were then subjected to a secondary screening using direct mitochondrial glutamine transport assays, and their inhibition of SLC1A5_var function was measured using tritium-labeled glutamine. As a result, several effective compounds inhibiting SLC1A5_var function were identified, and among them, iMQT_020, which showed the highest inhibition rate at a concentration of 10 μM, was selected and demonstrated antitumor effects in pancreatic cancer cells and mice, confirming that it inhibited cancer growth.

[0080] In the present invention, "SLC1A5" refers to a neutral amino acid transporter protein whose official name is solute carrier family 1 member 5. In addition to SLC1A5, it is also called AAAT, ASCT2, M7V1, M7VS1, R16, RDRC, etc.

[0081] In the present invention, "SLC1A5 variant" may refer to a protein having glutamine transporter activity within mitochondria. "SLC1A5 variant" refers to a protein expressed by a SLC1A5 transcript variant consisting of 339 amino acids shorter than the wild type (WT) or normal type of SLC1A5 (NCBI genebank mRNA sequence NM_001145145.2; protein sequence NP_001138617.1), and is referred to herein as SLC1A5_var.

[0082] In the present invention, the term "prevention" may include, without limitation, any action that can block symptoms related to periodontal disease or inhibit or delay progression by using the composition of the present invention, and the term "treatment" refers to a series of activities performed to alleviate and improve the desired disease.

[0083] The “pharmaceutical composition” of the present invention may include a pharmaceutically acceptable carrier or diluent, and may be formulated in the form of oral dosage forms such as powders, granules, tablets, capsules, suspensions, emulsions, syrups, aerosols, etc., external preparations, suppositories, and sterile injection solutions, respectively, according to conventional methods. The pharmaceutically acceptable carriers include lactose, dextrose, sucrose, sorbitol, mannitol, xylitol, erythritol, maltitol, starch, acacia gum, alginate, gelatin, calcium phosphate, calcium silicate, cellulose, methylcellulose, microcrystalline cellulose, polyvinyl pyrrolidone, water, methylhydroxybenzoate, propylhydroxybenzoate, talc, magnesium stearate, mineral oil, etc. In addition, it includes diluents or excipients such as fillers, bulking agents, binders, wetting agents, disintegrating agents, and surfactants. Oral solid preparations include tablets, pills, powders, granules, capsules, etc., and these solid preparations may include at least one excipient such as starch, calcium carbonate, sucrose or lactose, gelatin, etc., and may include lubricants such as magnesium stearate, talc, etc. Oral liquid preparations include suspensions, oral solutions, emulsions, syrups, etc., and may include diluents such as water and liquid paraffin, wetting agents, sweeteners, fragrances, preservatives, etc. Parenteral preparations include sterile aqueous solutions, non-aqueous solvents, suspensions, emulsions, lyophilized preparations, and suppositories. Non-aqueous solvents and suspensions include propylene glycol, polyethylene glycol, vegetable oils such as olive oil, and injectable esters such as ethyl oleate. Suppository bases include witepsol, macrogol, Tween 61, cacao butter, laurin butter, and glycerogelatin.

[0084] The pharmaceutical composition of the present invention can be administered to mammals such as livestock and humans by various routes, for example, oral, transdermal, subcutaneous, intramuscular, intravenous, intraperitoneal, intrarectal, intrauterine, intradural or intracerebrovascular injection, and topical administration. Accordingly, the composition of the present invention can be formulated in various forms, such as tablets, capsules, aqueous solutions, or suspensions. In the case of tablets for oral administration, carriers such as lactose and corn starch and lubricants such as magnesium stearate can typically be added. In the case of capsules for oral administration, lactose and / or dried corn starch can be used as diluents. If an oral aqueous suspension is required, the active ingredient can be combined with an emulsifier and / or suspending agent. If desired, specific sweeteners and / or flavoring agents can be added. For intramuscular, intraperitoneal, subcutaneous, and intravenous administration, a sterile solution of the active ingredient is typically prepared, and the pH of the solution must be suitably adjusted and buffered. For intravenous administration, the total concentration of the solute should be adjusted to impart isotonicity to the formulation. The composition according to the present invention may be in the form of an aqueous solution containing a pharmaceutically acceptable carrier, such as saline with a pH of 7.4. The solution may be introduced into the patient's intramuscular bloodstream by local injection.

[0085] The dosage of the active ingredient contained in the pharmaceutical composition of the present invention varies depending on the patient's condition and weight, the severity of the disease, the form of the active ingredient, the route and period of administration, and can be appropriately adjusted depending on the patient. For example, the active ingredient may be administered at a dosage of 0.0001 to 300 mg / kg per day, preferably 50 to 300 mg / kg, and the administration may be administered once or twice a day. In addition, the pharmaceutical composition of the present invention may contain the active ingredient in a weight percentage of 0.001 to 90% based on the total weight of the composition.

[0086] The above “health functional food” refers to a food manufactured and processed using raw materials or ingredients with functionality useful to the human body according to the Health Functional Food Act, and “functionality” refers to consumption for the purpose of obtaining a useful effect for health purposes such as regulating nutrients for the structure and function of the human body or physiological action.

[0087] The health functional food of the present invention may contain conventional food additives, and its suitability as the "food additive" is determined by the specifications and standards for the relevant item in accordance with the general provisions and general test methods of the Food Additives Codex approved by the Ministry of Food and Drug Safety, unless otherwise specified. Items listed in the "Food Additives Codex" include, for example, chemical compounds such as ketones, glycine, potassium citrate, nicotinic acid, and cinnamic acid; natural additives such as persimmon pigment, licorice extract, crystalline cellulose, sorghum pigment, and guar gum; mixed preparations such as sodium L-glutamate preparations, alkaline agents added to noodles, preservative preparations, and tar color preparations.

[0088] The health functional food of the present invention, for the purpose of preventing or improving cancer, may contain the compound in a weight percentage of 0.01 to 95%, preferably 1 to 80%, based on the total weight of the composition. In addition, for the purpose of preventing or improving cancer, the health functional food may be manufactured and processed in the form of tablets, capsules, powders, granules, liquids, pills, etc.

[0089] Hereinafter, the present invention will be described in detail by way of examples. However, the following examples specifically illustrate the present invention, and the content of the present invention is not limited by the following examples.

[0090]

[0091] Preparation of cell lines

[0092] Lung cancer cell lines (NCI-H358, NCI-H596, NCI-H226, NCI-H441, NCI-H1299, A549, and NCI-H460), colon cancer cell lines (HT-29, HCT 116, DLD-1, NCI-H508, SW620, LS 174T, LS1034, COLO 205, and SW480), pancreatic cancer cell lines (SU.86..86., SW1990, BxPC-3, CFPAC-1, Panc10.05, AsPC-1, HPAF-II, Capan02, Panc-1, and MIA PaCa-2), brain tumor cell lines (U-251MG, A-172, D-54 MG, T98G, SNB-19, and U-343 MG), breast cancer cell lines Cell lines (MDA-MB-231, HCC1395, HCC1937, BT-20), ovarian cancer cell lines (TOV-112D, SK-OV-3, SNU-119, OVCAR3), FHC, and BJ were obtained from ATCC. Astroctye, MCF10A, HEK293T, HCC44, HCC15, and HCC2108 cells were obtained from the Korea Cell Line Bank, and 16HBE cells were obtained from Merck. The human pancreatic ductal epithelial cell line (HPDE) was provided by Dr. Chao Ming-Sound. All cells were cultured in the following media at 37°C and 5% CO2. MIA PaCa-2, Panc-1, HEK293T, and astrocytes were cultured in DMEM containing 10% FBS, and HPDE was cultured in serum-free medium supplemented with EGF and bovine pituitary extract. CFPAC-1 was cultured in Iscove's modified Dulbecco's medium (IMDM), HPAF-II and BJ were cultured in MEM supplemented with 10% FBS, Capan2 was cultured in McCoy's 5A medium supplemented with 10% FBS, and SW1990 was cultured in Leibovitz's L-15 medium supplemented with 10% FBS.FHC cells were cultured in complete growth medium (DMEM:F12 nutrient mixture = 1:1, 10% FBS, additional HEPES final 25 mM, cholera toxin, 10 ng / mL, transferrin, 5 mg / mL, hydrocortisone, 100 ng / mL, EGF, 20 ng / mL), MCF10A cells were cultured in DMEM with 5 mg / mL insulin, and 16HBE cells were cultured in DMEM / F12 with 10% FBS. NCI-H358, NCI-H596, NCI-H226, NCI-H441, NCI-H1299, A549, NCI-H460, HT-29, HCT 116, DLD-1, NCI-H508, SW620, LS 174T, LS1034, COLO 205, SW480, SU.86..86., BxPC-3, Panc 10.05, AsPC-1, U-251MG, A-172, D-54 MG, T98G, SNB-19, U-343 MG, MDA-MB-231, HCC1395, HCC1937, BT-20, TOV-112D, SK-OV-3, SNU-119, OVCAR3, HCC44, HCC15 and NCI-HCC2108 were cultured in RPMI with 10% FBS.

[0093]

[0094] Preparing the mouse

[0095] All animal experiments were performed in accordance with the Guide for the Care and Use of Laboratory Animals published by the National Institutes of Health (BEC-CAN-2016-001 and 002), and all studies were approved by the Institutional Animal Care and Use Committee of Yonsei University (IACUC-A-202204-1455-02). Five-week-old male athymic NCr-nu / nu (RRID:MGI:5652489, Coretech, Pyeongtaek, South Korea) mice were used for in vivo subcutaneous and orthotopic pancreatic tumor xenograft analyses. Mice were housed four per cage at 24°C on a 12-h light / dark cycle. Food (38057, Purina) and water were provided ad libitum in a pathogen-free facility, and their health was monitored by culture, serum, and microscopic examinations.

[0096]

[0097] Cell lysis and immunoblotting

[0098] Cells were washed once with DPBS and lysed in lysis buffer (40 mM HEPES, pH 7.4, 0.5% Triton X-100, 10 mM glycerol phosphate, 10 mM pyrophosphate, 2.5 mM MgCl2) supplemented with protease inhibitors (5 g / mL aprotinin, 10 g / mL leupeptin, 250 μM PMSF). The lysed solution was then sonicated on ice. Unless otherwise stated, samples containing SLC1A5_var were not heated above 4°C or frozen during each immunoblotting. Total protein concentration was determined by BCA Assay (Intron), and proteins were denatured in Remmili sample buffer immediately before SDS-PAGE. 30 g of protein was loaded onto SDS-PAGE and transferred to PVDF membranes (Merck) via a Trans-BlotR turbo blotting system (Bio-Rad). The membranes were then blocked in TBST buffer containing 2% skim milk and incubated with the respective primary antibodies for 18 hours. The membranes were then incubated with the respective secondary antibodies (anti-mouse or anti-rabbit IgG-HRP conjugated, Invitrogen) for 1 hour. Immunoblot signals were detected with chemiluminescence-enhanced MicroChemi (DNR Bioimaging System) or EzWestLumi (ATTO) and quantified by densitometry of protein bands using the DNR Bioimaging tool. Immunoblot images represent representative images of three independent experiments.

[0099]

[0100] Infection using cDNA constructs and siRNA

[0101] All vectors used in this study were constructed from SLC1A5, SLC38A1, and SLC38A2 cDNAs provided by the Korean Human Gene Bank (Korea Research Institute of Bioscience and Biotechnology, Medical Genome Research Center). For expression studies, the coding sequence of human SLC1A5_var was cloned into the pIRESpuro3 vector containing Myc, His, and 3XFlag tags. SLC1A5_var tandem deletions were also cloned into pIRESpuro3. TM5 Del, HP2 Del, TM4 Del, HP1 Del, and TM3 Del contain 1-252aa, 1-208aa, 1-169aa, 1-130aa, and 1-90aa, respectively. The EGFP-fused SLC1A5_var protein was cloned as previously described. FIL / AAA, GK / AA, D / A, and LRKY / AAAA were generated using primers containing point mutations, and then PCR was performed. For infection of these cDNAs, cells were seeded at 1x10 in 6-well plates. 6 Cells were cultured per well and incubated overnight, then infected with each cDNA cloning vector using TurboFect infection reagent (Thermo Fisher Scientific, #R0531). Cells were used for experiments 24 h prior to infection. For siRNA experiments, siRNA was infected using Lipofectamine RNAiMAX reagent (Invitrogen) as described by the manufacturer.

[0102]

[0103] Mitochondrial isolation

[0104] Mitochondria were isolated as described previously. All experiments were performed on ice using pre-chilled buffers and equipment. Cells cultured in 15 cm dishes (>90% confluency) were washed twice with KPBS (136 mM KCl, 10 mM KH2 PO4, pH 7.2) and then gently scraped into 1 mL of KPBS. Cells were centrifuged at 900 g for 3 min, the supernatant was discarded, and the cell pellet was resuspended in 1 mL of KPBS with protease inhibitors (5 mg / mL aprotinin, 10 mg / mL leupeptin, 250 mM PMSF). Cells were then lysed by homogenizing 50 times in a 2 mL Dounce homogenizer, ensuring no air bubbles were introduced into the sample (cell integrity was carefully inspected under a microscope after 50 strokes to ensure that at least 80% of the total cells were damaged). The homogenate was centrifuged at 600 g for 5 minutes, and the pellet was retained for further experiments. The supernatant was centrifuged at 7,000 g for 10 minutes, and the supernatant was removed. Next, the pellet was resuspended using a Dounce homogenizer. Finally, the mitochondrial suspension was centrifuged at 10,000 g for 10 minutes. Total mitochondrial protein content was measured using a BCA assay kit (Intron). The method described previously was applied for the mitochondrial fraction. Briefly, the purified mitochondria were suspended in 500 μL swelling buffer (10 μM KH2 PO4, pH 7.4) with digitonin (2 mg / mL) using a Dounce homogenizer (Sigma). The solution was kept on ice for 1 h, with stirring every 10 min to ensure swelling, and then 1 volume of isosmotic solution (32% sucrose, 30% glycerol, 10 mM MgCl2) was added. The mixture of the two solutions was spun at 10,000 g for 10 min. The supernatant fraction S1 contained the outer mitochondrial membrane, while the pellet P1 contained the matrix and intact inner membrane.P1 was resuspended in 500 iL homogenization buffer (Sigma) and kept on ice for 1 hour to swell. Then, 1 volume of iso-osmotic solution was added, and S1 and the resuspended P1 were spun at 17,000 g for 1 hour. The supernatant of S1 contained the outer membrane. The supernatant of P1 contained the matrix, and the pellet contained the inner membrane. Each fraction was analyzed by immunoblotting using the indicated antibodies.

[0105]

[0106] Crosslinking

[0107] 1 x 10 6 Mitochondria isolated from cells were incubated on ice for 30 min with a 0–1% formaldehyde gradient and quenched with 50 mM Tris-Cl, pH 8.0. The cross-linked lysates were then sampled with Laemmelli buffer, separated on a 10% SDS-PAGE gel, and subjected to immunoblotting. Purified eGFP-SLC1A5_var was incubated on ice for 30 min with a 0–1% formaldehyde gradient and the reaction was stopped by adding an equal volume of 50 mM Tris-Cl, pH 8.0. The cross-linked lysates were then sampled with Laemmelli buffer, separated on a 10% SDS-PAGE gel, and subjected to immunoblotting.

[0108]

[0109] Purification of SLC1A5_var

[0110] eGFP-tagged SLC1A5_var was expressed in SF9 insect cells, and cells transiently infected with eGFP-tagged SLC1A5_var were collected by centrifugation. The membrane was disrupted using a homogenizer in a buffer containing 20 mM HEPES pH 7.5, 150 mM NaCl, and then the purified membrane was solubilized in a buffer containing 20 mM HEPES (pH 7.5), 150 mM NaCl, 0.5% (w / v) n-dodecyl-beta-D-maltopyranoside (DDM, Anatrace), and 0.2% (w / v) cholesterol hemisuccinate (CHS, Sigma) at 4°C for 2 h. The solubilized protein was separated by ultracentrifugation at 60,000 rpm for 40 min at 4°C and then incubated with TALON resin overnight at 4°C. The resin was then washed with washing buffer (20 mM HEPES pH7.5, 100 mM NaCl, 0.05% DDM, 20 mM imidazole) and the protein sample was eluted using elution buffer (20 mM HEPES pH7.5, 100 mM NaCl, 0.05% DDM, 250 mM imidazole).

[0111]

[0112] Co-immunoprecipitation

[0113] Depending on the experimental conditions, the coding sequences of different cDNAs were cotranscribed at a ratio of 1:1 or 1:1:1. After 24 h, cells were harvested by cell lysis as described in the cell lysis section. The cell lysates were incubated with 1 g of each antibody in the presence of protein A / G agarose beads (Invivogen) at 4°C for 4 h, and the resulting complexes were washed four times with a washing buffer containing 40 mM HEPES, pH 7. The complexes were washed four times with a washing buffer containing 0.5% Triton X-100, 10 mM glycerol phosphate, 10 mM pyrophosphate, and 2.5 mM MgCl2 and eluted with 2x Laemmell's solution by vigorous vortexing. The eluates were separated by centrifugation and subjected to SDS-PAGE for immunoblotting. For the two-step Co-IP, cell lysates were incubated with 1 μg anti-3XFlag (Bethyl) antibody for 4 hours at 4°C in the presence of protein A / G agarose beads (Invivogen), and the resulting complexes were washed four times with wash buffer. 340 μM 3XFlag peptide (Sigma-Aldrich, #F4799) was then added to the tube containing the agarose-protein-3XFlag antibody complex. The solution was incubated for 4 hours at 4°C, the agarose beads were separated by centrifugation, and the supernatant was added to the tube containing 1 μg anti-His (Bethyl) antibody in the presence of protein A / G agarose beads (Invivogen) and incubated for 4 hours at 4°C. The complexes were then washed four times with wash buffer and eluted with 2x Laemmelli buffer with vigorous vortexing. The lysate was separated by centrifugation and subjected to SDS-PAGE for immunoblotting.

[0114]

[0115] size exclusion chromatography

[0116] Membrane fractions of HEK293T cell lysates containing eGFP_SLC1A5_var_WT with vesicles and iMQT_020 and eGFP_SLC1A5_var_FIL / AAA with vesicles and iMQT_020 were applied to a Superdex 200 Increase 10 / 300 GL column in 20 mM Tris pH 8.0, 300 mM NaCl, and 0.2% DDM. The Superdex 200 Increase 10 / 300 GL column was calibrated with apoferritin (440 kDa), alcohol dehydrogenase (150 kDa), conalbumin (75 kDa), ovalbumin (44 kDa), carbonic anhydrase (29 kDa), and ribonuclease (13.7 kDa) purchased from GE Healthcare. In the collected fractions, eGFP-tagged proteins were detected with a fluorescence detector at Ex / Em = 488 / 510 nm.

[0117]

[0118] SLC1A5_var modeling

[0119] A new monomer prediction model for SLC1A5_var was generated using RoseTTFold2.0. The input included the query sequence of SLC1A5_var without using the templates in MMseqs or MSA. RoseTTFold2.0 prediction was run on a local GPU cluster using the ColabFold code. The output monomer model was then input to the MZ-Dock server to generate a homotrimer structure. The homotrimer structure was modeled by covering the TM3 domain, which serves as a site for monomer interactions. The output homotrimer contained binding clashes, so further refinement was performed using molecular dynamics. Molecular dynamics (MD) simulations were performed using the Desmond default settings. The Desmond application was opened and the predicted homotrimer structure of SLC1A5_var was uploaded. Energy minimization was performed using Desmond simulations. Structural relaxation was performed using Desmond's Relax panel. Finally, an NVIDIA GeForce GTX 1660 Super was used for the final MD simulations.

[0120]

[0121] In silico docking and virtual screening

[0122] Molecular docking-based virtual screening was used to screen the Cambridge database (1.2 million compounds). The Glide software program (Schrödinger, LLC, USA) was used for virtual docking of compounds, using grid-based ligand docking and energetics algorithms. The trimeric homology model structure of SLC1A5_var was used as the starting model for virtual screening. The grid box (20 Å × 20 Å × 20 Å) was generated using the receptor grid generation panel built into the Schrödinger suite, with the centers of residues Phe97, Iso104, and Leu105 selected as the grid box centers. The protein structure was corrected by adding hydrogen atoms, bond order, and formal charges using the Protein Preparation Wizard tool in the Maestro software package (version 9.6; Schrödinger, LLC, USA). For ligand preparation, 1.2 million compounds were initially downloaded from the ChemBridge database in SDF format. The LigPrep module of the Schrödinger software suite was used for ligand preparation. The following criteria were applied during ligand preparation: (i) OPLS3 force field, (ii) generation of all possible ionization states at pH 7.0, (iii) desalting option, (iv) generation of tautomers for all conformers, and (v) generation of one low-energy conformer per ligand. The prepared ligands were then subjected to a structure-based virtual screening process using the Glide module of the Schrödinger software suite. The HTVS mode was used to filter chemical entities proposed from the molecular library, the SP mode was applied for further screening, and the XP mode was utilized to obtain more accurate docking calculations.

[0123]

[0124] Cellular amino acid transport analysis

[0125] HEK293T and MIA PaCa-2 cells were seeded at 75% confluency in 12-well culture plates. Radiolabeled proline (L-[3 H]Pro), serine (L-[3 H]Ser), glutamine (L-[3 H]Gln), asparagine (L-[3 H]Asn), and leucine (L-[3 H]Leu) (Perkin Elmer) (3 uCi / mL) was added to DMEM without each amino acid. The cells were then incubated at 37°C for 1 h and terminated by removing the medium. The cells were washed with DPBS solution, extracted with lysis buffer (0.2% SDS), and mixed with AquaLight+ (HIDEX). All measurements were analyzed using a liquid scintillation counter (HIDEX). The lysates were later used to measure the mitochondrial protein concentration of each sample using a BCA assay kit (Intron). Amino acid uptake was calculated from the number of amino acids per minute per sample and the specific activity of each labeled amino acid, and this amino acid uptake was normalized to mitochondrial protein content.

[0126]

[0127] Purification of mitochondria from cells and analysis of mitochondrial amino acid transport

[0128] Mitochondria were prepared according to Wieckowski et al. with minor modifications. For each experiment, HEK293T and MIA PaCa-2 cells stably transfected with 3XMyc-EGFP-OMP25 were immunoprecipitated with anti-Myc antibodies. 100 anti-Myc magnetic beads (Pierce) were pre-washed three times with KPBS, and all washes were performed by gently pipetting using a pipette tip and collecting the beads using a DynaMag spin magnet (Invitrogen), a magnetic stand. 1 x 10 7Cells cultured in 15 cm dishes were washed twice with DPBS and gently scraped with 1 mL of KPBS. The cells were centrifuged at 900 g for 3 minutes, and the pellet was resuspended in 1 mL of KPBS. The cell solution was carefully homogenized with 50 strokes in a 2 mL Dounce homogenizer to avoid bubbles. The homogenized solution was centrifuged at 1,000 g for 2 minutes, and the supernatant was immunoprecipitated with anti-c-Myc antibody bound to magnetic beads for 20 minutes. c-Myc-tagged mitochondria were eluted with 250 mL of 0.25 mg / mL c-Myc peptide (Pierce). To measure mitochondrial amino acid uptake, purified mitochondria were first diluted in 50 μL of KPBS, and mitochondrial amino acid transport was measured. This solution was placed in a 1.5 mL tube with vehicles or chemicals for 24 h. Radiolabeled amino acids (L-[3H]Pro), serine (L-[3H]Ser), glutamine (L-[3H]Gln), asparagine (L-[3H]Asn), and leucine (L-[3H]Leu) (Perkin Elmer) (3 uCi / mL) were added to each tube and incubated at 37°C for 1 h to assess mitochondrial amino acid transport. The tubes were incubated at 4°C to stop the uptake reaction, centrifuged at 12,000 g for 15 min, the supernatant was removed, and washed twice with KPBS. The cells were extracted with lysis buffer (0.2% SDS) and mixed with 3 mL of AquaLight+ (HIDEX). All measurements were analyzed with a liquid scintillation counter (HIDEX). The lysates were later used to measure the mitochondrial protein concentration of each sample using the BCA assay kit (Intron). Amino acid uptake was calculated from the number of amino acids per minute per sample and the specific activity of each labeled amino acid, and this amino acid uptake was normalized to mitochondrial protein content.

[0129]

[0130] Indirect screening of SLC1A5, SLC38A1, and SLC38A2 glutamine uptake functions

[0131] HEK293T cells expressing control vector and human wild-type SLC1A5, SLC38A1, SLC38A2, and YFP-F46L / H148Q / I152L, respectively, were seeded at 2 x 10 in 96-well culture plates. 4 Cells were plated at a concentration of 100 cells / ml and incubated for 24 h. Each well of a 96-well culture plate was washed twice with 100 μL of DPBS and filled with 50 μL of HEPES buffer. Each compound, vesicle, iMQT_020, and V-9302 were added at 10 μM. After 24 h of incubation, the 96-well culture plate was placed in a FLUOstar Omega microplate reader (BMG Labtech, Ortenberg, Germany) for fluorescence analysis. Fluorescence from each well was recorded continuously for 5 s (1 s per point) to individually analyze control, SCL1A5, SLC38A1, and SLC38A2-mediated iodide ion influx. Then, 50 μL of NaI-substituted HEPES buffer (NaI replacing NaCl in the original HEPES buffer) was added using a liquid injector over 5 s, and YFP fluorescence was recorded for 10 s. The activity of each glutamine transporter was calculated by comparing the YFP fluorescence quenching with that of the control vector group.

[0132]

[0133] Mitochondrial morphology analysis

[0134] Mitochondrial morphology was analyzed as described previously. Mitochondrial morphology was classified into three categories: "elongated / tubular," with more than 90% of mitochondria forming an elongated, interconnected network; "intermediate," with a mixture of tubular and short mitochondria; and "fragmented," with more than 90% of mitochondria comprising short, pore-like structures. The percentage of cells with elongated / tubular, intermediate, or fragmented mitochondria was measured, and at least 100 cells from each vesicle and iMQT_020-treated cell sample were quantified from three biologically independent experiments.

[0135]

[0136] Measurement of mitochondrial membrane potential

[0137] Changes in mitochondrial membrane potential were analyzed by incubating cells treated with vehicle or iMQT_020 with tetramethylrhodamine ethyl ester (TMRE 20 nM, Invitrogen) for 15 min and analyzing them by flow cytometry (BD FACS ARIA III).

[0138]

[0139] OCR / ECAR analysis

[0140] OCR and ECAR were measured using an XFe24 extracellular flux analyzer (Agilent Technologies) as described in the manufacturer's protocol. A total of 4.0 x 10 4Cells were seeded per well in 24-well microcell culture plates (for Seahorse) in DMEM containing 10% FBS and cultured overnight at 37°C in a 5% CO2 incubator. The DMEM was then removed and replaced with phenol red- and bicarbonate-free DMEM (pH 7.4), and the cells were cultured for 1 hour at 37°C in a non-CO2 incubator to equilibrate with the atmospheric CO2 level. Using an XFe24 analyzer, OCR and ECAR were measured under baseline conditions and under drug treatments such as glucose (Glc, 4 mM), 2-deoxy-glucose (2-DG, 50 mM), glutamine (Gln, 2 mM), oligomycin (2 mM), carbonylcyanide-p-trifluoromethyl-phenylhydrazone (FCCP, 0.5 mM), and rotenone / antimycin A (0.5 mM / 0.5 mM) (these drugs were included in the Cell Mito Stress Test Kit, Agilent Technologies). For metabolic phenotype analysis, cells were used to measure basal OCR and basal ECAR. To measure maximal OCR and ECAR, cells were exposed to oligomycin (2 mM) and FCCP (0.5 mM). Each measurement cycle consisted of 3 min of mixing, 3 min of waiting, and 4 min of measurement. OCR and ECAR values ​​were normalized to cell number and analyzed using WAVE software (Agilent Technologies).

[0141]

[0142] Measurement of GSH, ROS, and mitochondrial ROS

[0143] Reduced glutathione (GSH) contains a thiol group derivatized with the fluorescent tag monobromobimane (Ex / Em: 394 / 490 nm). Cells were incubated with monobromobimane (40 mM, 10 min) and analyzed using a flow cytometer (BD FACS ARIA III). The GSH to oxidized glutathione (GSSG) ratio was measured using a GSH / GSSH assay kit (Abcam) according to the manufacturer's instructions. Fluorescence was recorded at Ex / Em = 490 / 520 nm, and the GSH / GSSG ratio was calculated according to the formula described in the manufacturer's instructions. Intracellular ROS was measured by staining cells with 1 mM 5-(and-6)-carboxy-2',7'-dichlorodihydrofluorescein diacetate (H2DCFDA, Invitrogen) for 10 min according to the manufacturer's protocol (Ex / Em: 492 / 517 nm). The stained cells were analyzed using a flow cytometer (BD FACS ARIA III). Mitochondrial ROS was measured by staining cells with 5 mM MitoSOX Red, a mitochondrial superoxide indicator (Ex / Em = 510 / 580 nm), for 10 min, and the stained cells were analyzed using a flow cytometer (BD FACS ARIA III).

[0144]

[0145] Measurement of cell viability and growth

[0146] To exclude the influence of serum-derived nutrients, dialyzed FBS (GIBCO) was used. For cell viability analysis, cells were seeded at a density of 10,000 cells per well in 96-well culture plates in each medium containing 10% dialyzed FBS. After successful cell attachment, the medium was replaced with conditioned medium, and cell viability was measured 48 h later using the WST-1 assay. The WST-1 assay utilizes a highly sensitive water-soluble tetrazolium salt that, upon reduction in the presence of mitochondrial dehydrogenase, produces a water-soluble formazan dye. For each sample, absorbance was measured at 450 nm (reference wavelength 625 nm) using a microplate reader (Infinite 200 PRO, TECAN) and normalized to the control. Cell number was counted using an automated cell counter (ADAM-MC, NanoEntek).

[0147]

[0148] RNAseq and gene enrichment analysis

[0149] RNA-seq data for each sample, and the quality of raw data, were controlled using FastQC (RRID: SCR_014583). Reads from the RNA-seq experiment were mapped to the reference genome (Homo sapiens GRCh38.94) using TopHat (RRID: SCR_013035). The mapped reads were then counted using HTSeq (RRID: SCR_005514) with the following parameters: htseq-count -s no -m intersection-nonempty-f bam. Differential gene expression analysis was performed with the DESeq2 package (v. 1.24.0, RRID: SCR_000154), and data were manipulated in R (v3.6.1). Genes with low counts (<10) were filtered out, and a normalized log transformation was applied to minimize differences between samples with low counts. Gene set enrichment analysis (GSEA; RRID:SCR_003199) compared differences between vehicle-treated and iMQT_020-treated MIA PaCa-2 cells. Subsets were divided according to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway gene sets, and rlog FPKM FC values ​​were calculated. Then, for each gene set, the average rlog FPKM FC value for each sample was calculated. This allowed for an overall comparison between vehicle-treated cells and iMQT_020-treated MIA PaCa-2 cells. Normalized enrichment scores were calculated for each KEGG pathway gene set and plotted graphically.

[0150]

[0151] LC / MS-based metabolomics and metabolite abundance quantification

[0152] Whole cell metabolome profiling was performed for glutamine metabolome profiling analysis using glutamine (L-[ 13 1 x 10 of MIA PaCa-2 cells and iMQT_020 cells treated with [C]Gln 7Cells were washed twice with DPBS, briefly washed with Optima LC / MS water, and then scraped in 1 mL of 80% methanol for Optima LC / MS. The samples were vortexed vigorously for 1 min, spun at 17,500 g for 15 min, and the supernatant was analyzed by LC / MS. The metabolite extracts were diluted with 20% (v / v) acetonitrile for ultra-performance liquid chromatography-triple quadrupole mass spectrometry (UPLC-TQ-MS). The analysis was performed on an Ultimate 3000 RSLC equipped with an Acquity UPLC BEH C18, 1.7 m, 2.1 × 100 mm, and a Q-Exactive Orbitrap Plus MS (Thermo Fisher). Compound Discoverer (version 3.0, Thermo Fisher) software was used for data acquisition and analysis. MS was operated at the following parameters: gas temperature 37°C, isolation window 2.0 m / z, collision energy 30, dynamic exclusion 5 s, sheath gas flow rate 50, auxiliary gas flow rate 13, and spray voltage 2.5 kV. Metabolomics analysis was performed using the Metabolika pathway analysis software for Compound Discoverer (version 3.0, Thermo Fisher). Detected metabolites were compared to the Metabolika Pathway library. All molecules present in the library were identified in the acquired data. Peaks were quantified using the area under the curve. Fold change and statistical significance analysis were performed using GraphPad Prism 7 software.

[0153]

[0154] Gene expression analysis

[0155] RNA was isolated from cells using the MiniBEST Universal RNA Extraction Kit (TAKARA) according to the manufacturer's instructions. Reverse transcription of 1,000 ng of RNA was performed using the PrimeScript Single-Strand cDNA Synthesis Kit (TAKARA). The entire reaction mixture was incubated at 42°C for 45 minutes, and reverse transcriptase was inactivated at 90°C for 5 minutes. For RT-PCR, the resulting cDNA was diluted with nuclease-free water (1:1) and PCR was performed using EmeraldAmp GT PCR Master Mix (TAKARA). The PCR products were then analyzed by 1% agarose gel electrophoresis. Gene expression levels were measured using ImageJ and normalized to the expression level of the housekeeping gene GAPDH. For quantitative real-time PCR analysis, cDNA was diluted in nuclease-free water (1:4) and gene expression levels were analyzed using Step One Plus (Applied Biosystems). Expression levels were normalized to the expression level of the housekeeping gene GAPDH.

[0156]

[0157] Glucose and glutamine measurements

[0158] Glucose concentrations were measured using the Glucose Colorimetric Assay Kit II (BioVision), and glutamine concentrations were measured using the Glutamine Detection Assay Kit (BioVision) according to the manufacturer's instructions. Compounds of interest generated stable colorimetric signals measured by absorbance at a specific wavelength (450 nm for Glucose Colorimetric Assay Kit II and Glutamine Detection Assay Kit) using a microplate reader (Infinite 200 PRO, Tecan). Control wells were also measured to subtract background signals.

[0159]

[0160] Ames test and hERG toxicity test

[0161] Ames test strains (TA98 and TA100) and media were purchased from Xenometrix (Basel, Switzerland), and the test procedure was performed according to the manufacturer's instructions. iMQT_020 and positive control were prepared at 10.2, 30.8, 92.5, 277.7, 833.3, and 2500 g / mL, respectively, and 2-NF was prepared at 2 g / mL for TA98 without S9, 2-AA at 0.5 g / mL for TA98 with S9, 4-NQO at 0.1 g / mL for TA100 without S9, and 2-AA at 1.25 g / mL for TA100 with S9. Each chemical was dissolved in the exposure medium at 37°C for 90 min. Indicator medium was added, and the plates were dispensed into 284-well plates and incubated for 24–48 h. Mutagenicity was assessed according to the baseline presented in the control group. Cells expressing hERG were plated on 8 mm coverslips and cultured overnight. The coverslips were placed on a microscope stage and placed in a chamber perfused with saline containing 160 mM NaCl, 4 mM KCl, 2 mM CaCl2, 1 mM MgCl2, 10 mM HEPES, and 10 mM glucose at 1 mL / min. All recordings were performed at room temperature. Currents were recorded using whole-cell recording mode. The cell membrane was held at -90 mV, and the currents were filtered at 67 Hz and sampled at 2.0 kHz using an EPC10 / 2 amplifier. Voltage-dependent activation curves were obtained by increasing the potential at -70 mV for 50 s, eliciting the command potential from -70 mV to -40 mV for 2 s, repolarizing the voltage to -70 mV for 2 s, and finally holding the potential at -90 mV every 5 s.

[0162]

[0163] iMQT_020 Plasma Stability Test

[0164] Whole blood samples (n = 5 mice) were collected at 0, 0.08, 0.25, 0.5, 1, 2, 4, 6, 8, and 10 h after intravenous and intraperitoneal injections of 5 mg / kg and 75 mg / kg, respectively, of iMQT_020. Liquid chromatography-tandem mass spectrometry (LC-MS / MS) analysis was performed by reversed-phase chromatography using a Q-Exactive Orbitrap Plus MS (ThermoFisher). Standard curves and quality control samples were generated by spiking iMQT_020 into fresh whole blood and applying it to a 10 L Mitra microsampler. All data were collected by Compound Discoverer and analyzed with the corresponding software.

[0165]

[0166] In vivo subcutaneous xenograft and orthopedic xenograft tumor studies

[0167] All animal experiments were performed in accordance with the Guide for the Care and Use of Laboratory Animals published by the National Institutes of Health (BEC-CAN-2016-001 and 002), and all studies were approved by the Institutional Animal Care and Use Committee of Yonsei University (IACUC-A-202204-1455-02). Xenografts were performed on 5-week-old male athymic NCr-nu / nu mice. 5.0 x 10 in 200 uL of DPBS 5 After subcutaneous injection of MIA PaCa-2 cells, the tumor size was approximately 30 mm 3Upon reaching , mice were treated with vesicles (10% DMSO, 10% Tween20, 0.9% NaCl, 79.1% water, IP, daily) or iMQT_020 (50 mg / kg and 75 mg / kg, IP, daily). Tumor volumes were measured daily with electronic calipers and calculated using the formula (length x width x height) / 2. Five-week-old male athymic nu / nu mice were used for injection of MIA PaCa-2 cells stably expressing luciferase. Mice were anesthetized with isoflurane, and a small incision was made on the left abdomen. 5.0 x 10 5 Cells were diluted in 100 μL of DMEM and injected into the tip of the mouse pancreas using isoflurane (Pfizer). A cotton swab was applied to the injection site for 1 minute to prevent leakage of pancreatic tumor cells. The peritoneum and skin incisions were sequentially sutured with absorbable sutures. The tumor size was approximately 30 mm. 3 Upon reaching , mice were treated with vesicles (10% DMSO, 10% Tween20, 0.9% NaCl, 79.1% water, daily) or iMQT_020 (50 mg / kg and 75 mg / kg, IP, daily). Every 3 days, mice were injected with D-luciferin (3 mg / mouse, IP) for 10 min, and luminescence was measured via IVIS (Caliper Life Sciences). At the end of the study, mice were sacrificed via CO2 asphyxiation, and tumor volumes (n = 6) were measured.

[0168]

[0169] Immunohistochemistry

[0170] Tumor tissues were dissected after sacrifice of the NCr-nu / nu mouse tumor model. Tumor tissues were fixed in formalin and sectioned for immunohistochemistry (IHC). IHC was performed on a fully automated Ventana Discovery Ultra instrument (Roche Diagnostics International AG). Formalin-fixed tumor tissue sections were deparaffinized and processed for antigen retrieval using CC1 buffer (Roche Diagnostics). The sections were then treated with anti-pS6K antibody (1:500 dilution) and anti-cleaved Cas3 antibody (1,500 dilution) and incubated at 37°C for 30 minutes. Tissue slides were developed using the Ultramap DAB staining kit (Roche Diagnostics) according to the manufacturer's instructions. Positive cells per field were counted at 10x magnification in at least four fields, and the average values ​​were calculated using ImageJ.

[0171]

[0172] CD8+ cell studies

[0173] CD8+ cells were isolated from the spleen and thymocytes of 8-week-old C57BL6 / N mice according to the Guide for the Care and Use of Laboratory Animals. Spleen and thymocytes were stimulated with activated recombinant IL-2 (10 ng / mL) together with 5 μg / mL anti-CD3 and 5 μg / mL anti-CD28 antibodies for up to 7 days. After activation, cells were stained with FITC-Annexin V, incubated in the dark at room temperature for 30 min, and then analyzed using a flow cytometer (BD FACS Aria III). To analyze the activation status of CD8+ cells, cells were stained with CD44-PE / Cy5 in the dark at room temperature for 30 min, and then analyzed using a flow cytometer (BD FACS Aria III).

[0174]

[0175] Microscale thermophoresis

[0176] Microscale thermophoresis experiments were performed using a Monolith NT.115 (NanoTemper Technologies). The eGFP-tagged SLC1A5_var protein was purified as described above. Protein samples were diluted with 20 mM HEPES (pH 7.5), 100 mM NaCl, and 0.05% DDM and analyzed using the Monolith to confirm the thermophoresis results. A series of steps, including statistical analysis, protein dilution, and fluorescence normalization, were performed as instructed by the instrument. iMQT_020 was mixed with protein at the specified concentration and placed inside a Premium Capillary (Nanotemper, MO-K025). The experiment was performed with red fluorescence selected as the LED source and 50% infrared laser power. Data analysis was performed using MO Affinity Analysis 2.3.

[0177]

[0178] Circular dichroism analysis

[0179] Circular dichroism analysis was performed using a Jasco J-1500 spectropolarimeter (Japan Spectroscopic Company). The SLC1A5_var protein was purified as described above. Protein samples were diluted to 0.5 mg / mL and scanned, and the instrument's spectral wavelength was set to measure between 190 and 340 nm. The data for spectral background scattering were corrected by the difference in the values ​​using a solvent containing buffer or vesicle. CD and absorbance were measured in the same cuvette to minimize errors. For samples with different molar ratios, the total protein concentration was maintained at 0.5 mg / mL even though the protein molar ratios of WT and FIL / AAA mutants were changed. CD spectra were measured in a solvent of 20 mM HEPES (pH 7.5) and 100 mM NaCl.

[0180]

[0181] Measurement of serum profiles of liver and kidney damage

[0182] After isolating the blood of the mice in the prepared experimental group, the blood was centrifuged at 5,000 rpm for 20 minutes to obtain a serum fraction. Aspartate aminotransferase (AST), alanine aminotransferase (ALT), and blood urea nitrogen (BUN) levels were measured using AST (BioAssay System, EASTR-100), ALT (BioAssay System, EALT-100), and BUN (BioAssay System, DIUR-100) tests, respectively, according to the kit manufacturer's protocol.

[0183]

[0184] Chromatin immunoprecipitation assay

[0185] KPC cells were prepared by treating them with vesicles, iMQT_020, or iMQT_020 plus 2 mM αKG for 24 h, and ChIP analysis was performed using a ChIP kit (Abcam) according to the manufacturer's protocol. Briefly, 4 × 10 6 After fixing the cells with 1.5% formaldehyde for 10 minutes, nuclei were isolated, and the nuclear samples were sonicated to fragment chromatin into 200–1,000 bp fragments. The resulting fragmented chromatin was incubated with anti-H3K4me3 and anti-H3K27me3 antibodies and an IgG complex conjugated to Protein A / G agarose beads for 24 hours. The immunoprecipitated DNA was heated at 95°C for 10 minutes to dissociate cross-links, and the proteins were removed by proteinase K treatment. As a control, an unconcentrated DNA sample was prepared in the same manner. The resulting ChIP and DNA were subjected to qRT-PCR using specific primers for the promoter region of PD-L1.

[0186]

[0187] PD-L1 expression and flow cytometric analysis of tumor-infiltrating immune cells

[0188] Tumor tissue was excised and washed with pre-chilled PBS. The tumor was minced and digested with 50 mg / mL DNase (10104159001, Roche) and 150 mg / mL Liberase (05401020001, Roche) at 37°C for 15 min, followed by addition of 10% RPMI medium to stop the digestion. The fragmented tissue was filtered through a 40 μm cell filter (431750, Corning), and the precipitate was lysed with RBC lysis buffer (00-4333-57, Invitrogen). The prepared cells were incubated with CD16 / CD32 antibody (156604, Biolegend). FITC CD45 (S18009F, Biolegend), APC-Cy7 PD-1 (135223, Biolegend), PE PD-L1 (1242307, Biolegend), PE-Cy7 CD3 (100219, Biolegend), PE-Cy5 CD8 (100709, Biolegend), PerCP-Cy5 CD4 (100433, Biolegend), PE CD45 (147711, Biolegend), PerCP-Cy5 CD8 (140417, Biolegend), PE-Cy7 TCR-b (109221, Biolegend), FITC CD25 (102005, Biolegend), PerCP-Cy5 CD11b (101229, Biolegend), V450 Ly6G (127603, Biolegend), APC Cell membrane proteins were labeled by treating with Ly6C (128005, Biolegend), PE CD206 (141705, Biolegend), and PE-Cy7 F4 / 80 (157305, Biolegend) antibodies. To label intracellular marker proteins, cells were fixed with fixation buffer (420801, Biolegend), washed with washing buffer (421002, Biolegend), and then labeled with APC FoxP-3 (320011, Biolegend), FITC Granzyme B (515403, Biolegend), and APC IFNγ (505809, Biolegend).Live and dead cells were excluded by staining with PI (421301, Biolegend) or viability stain reagent (AB_2869405, BD Biosciences). Finally, samples were analyzed and data were acquired using a flow cytometer (BD FACSAria III) and Flow Jo (BD Biosciences).

[0189]

[0190] Statistical analysis

[0191] All statistical analyses were performed using GraphPad Prism 7 software. Data from RT-PCR, immunofluorescence, and OCR / ECAR were statistically analyzed using the Student's t test, and graphs represent the mean ± SD. Metabolomics data were statistically analyzed using Welch's two-sample t-test. For animal studies, experiments were replicated across multiple batches. Mice were randomly assigned to groups and treated according to the experimental design. Animal experimental data were statistically analyzed using the Student's t test, and graphs represent the mean ± SD. Although no statistical method was used to predetermine sample sizes, the group sizes used were similar to those commonly used in mouse studies. Detailed methods for statistical significance and p-values ​​are described in the figure legends and Methods Details.

[0192]

[0193] Example 1. Screening of iMQT_020, an allosteric inhibitor of the mitochondrial glutamine transporter SLC1A5_var.

[0194] 1-1. Confirmation of the trimeric structure of the mitochondrial glutamine transporter

[0195] The mitochondrial glutamine transporter SLC1A5_var drives metabolic reprogramming in cancer cells, and genetic inhibition of SLC1A5_var inhibits cancer growth. Therefore, pharmacological inhibition of SLC1A5_var is expected to have a potent anticancer effect. Therefore, we began with the structural elucidation of SLC1A5_var through biochemical studies and pursued structure-based drug discovery. Given that SLC1A5, the major transcript variant of SLC1A5_var, was previously identified as a trimer, we hypothesized that SLC1A5_var also exists as a trimer. Crosslinking experiments with mitochondrial extracts or purified eGFP-tagged SLC1A5_var protein confirmed the trimer existence of SLC1A5_var (Fig. 1 a-c). To confirm the trimer structure, a two-step immunoprecipitation method was performed. Myc-, His-, and Flag-SLC1A5_var consistently interacted, confirming the presence of SLC1A5_var monomers in the second step, demonstrating that SLC1A5_var is a trimer (Fig. 1d). Notably, the C-terminus of SLC1A5_var, particularly the TM3 domain, led to a marked reduction in inter-monomer interactions (Fig. 1e). This suggests that the TM3 domain plays a crucial role in maintaining the trimeric structure of SLC1A5_var.

[0196] We used state-of-the-art AI-based prediction tools, such as AlphaFold and RoseTTAFold, to predict the structure of SLC1A5_var, but these models were very similar to those of SLC1A5 (Fig. 2a). This model showed interactions between monomers in the TM1, TM2, and TM4 regions, which contradicted previous biochemical results (Fig. 1e). Therefore, after predicting a reliable monomer structure using AlphaFold and RoseTTAFold, we predicted the trimer structure using the MZ-Dock server, a protein-protein interaction prediction program. Evaluation of the top 20 models confirmed that the trimer structure derived from the monomer model structure predicted by RoseTTAFold showed interactions in the HP1 and TM3 domains (Fig. 2a). Confirmation of the model revealed strong interactions involving F97, I104, and L105 (FIL) (Fig. 2b). To maintain trimeric interactions, one monomer must interact with the other two monomers, and this interaction pattern was consistently observed within the SLC1A5_var trimer. Specifically, F97 from one monomer interacted with A98, G101, and K102 from the other monomer, and vice versa (Fig. 2b). Similar interactions were also observed with I104 and L105 (Fig. 2b). F97, A98, G101, K102, I104, and L105 were identified as conserved residues across species (Fig. 1f), suggesting that they play a crucial role in homotrimeric interactions.

[0197] Next, we evaluated the biochemical properties to verify the accuracy of the MZ-dock trimer model generated by RoseTTAFold. First, we investigated the interaction sites between monomers and confirmed the importance of the FIL residue through immunoprecipitation experiments. The protein-protein interaction between SLC1A5_var WT and the F97A / I104A / L105A mutant (FIL / AAA) was somewhat conserved, but the interaction between the two FIL / AAA mutants was significantly reduced (Fig. 1g). In addition, we mutated G101A and K102A (GK / AA) to analyze the importance of nearby conserved residues. In addition, we compared the results with the inactive D186A mutant (D / A) and another control (LRKY / AAAA) consisting of residues L116A, R128A, K129A, and Y132A. Based on the model structure, the LRKY / AAAA mutants predicted to interact with other monomers were residues in the HP1 and TM4 domains. The FIL / AAA mutant and the GK / AA mutant showed significantly reduced protein-protein interactions compared to the D / A mutant and the LRKY / AAAA mutant, further confirming that the FIL residues, rather than the TM4 domain residues, are important for trimer formation (Fig. 1h).

[0198]

[0199] To assess the importance of trimeric interactions for mitochondrial glutamine transport function, we performed direct mitochondrial glutamine transport assays using various SLC1A5_var mutants. The FIL / AAA mutant exhibited significantly reduced transport function compared to SLC1A5_var_WT (Fig. 1i). Silencing endogenous SLC1A5_var expression restored glutamine transport levels when overexpressing SLC1A5_var_WT, but not when overexpressing SLC1A5_var_FIL / AAA (Fig. 1i). Furthermore, in MIA PaCa-2 cells in which SLC1A5_var expression was suppressed, overexpression of SLC1A5_var_WT increased cell viability, whereas overexpression of SLC1A5_var_FIL / AAA did not (Fig. 1j). To confirm the importance of trimer maintenance for the metabolic function of SLC1A5_var, we examined changes in OCR. SLC1A5_var_FIL / AAA overexpression did not change the basal OCR compared to the control (Con), whereas SLC1A5_var_WT overexpression restored the basal OCR (Fig. 1k). We also quantified the amount of alpha-ketoglutarate (aKG) in whole cells to assess the consequences of SLC1A5_var dysfunction. Since SLC1A5_var mediates glutamine-derived aKG production, we expected that inhibition of SLC1A5_var function by FIL / AAA mutation would decrease aKG production. This was confirmed by the fact that aKG levels increased compared to SLC1A5_var_WT overexpression, but SLC1A5_var FIL / AAA overexpression did not show a significant difference compared to Con (Fig. 1l). Therefore, we conclude that maintaining the trimeric structure is essential for mitochondrial glutamine transport activity.

[0200]

[0201] 1-2. Discovery of allosteric inhibitors of SLC1A5-var

[0202] Previous inhibitors targeting glutaminolysis were typically developed using substrate-like or ligand-based drug discovery methods. Consequently, these inhibitors could bind to the substrate-binding site, potentially causing off-target effects due to the important role of glutamine in normal cells. To address this issue, we aimed to develop compounds that inhibit glutaminolysis without affecting the substrate-binding site. The model structure of SLC1A5_var revealed the presence of an allosteric site, an inhibitor-binding site, within the trimeric interaction region (Figure 2a). To identify precise inhibitors, we conducted an initial virtual screening. Grid-based ligand docking of 1.2 million compounds from the Cambridge database was performed. The binding pocket was identified by focusing on the trimeric interaction region near the F97, I104, and L105 regions. The protein structure was prepared using Maestro (Schrödinger, USA), and the OPLS3 force profiling application was utilized for compound docking using the LigPrep module of Schrödinger software. As a result, hit compounds were identified through screening, and the top 103 compounds were selected for further evaluation by examining their pharmacological activity and binding conformational states. The 103 selected compounds underwent a secondary screening through direct mitochondrial glutamine transport assay, and their inhibition activity against SLC1A5_var was measured using tritium-labeled glutamine. Among them, iMQT_020 showed the highest inhibition rate at a concentration of 10 μM, which is characterized by a benzyl-quinazoline-dione structure with various nucleophilic and electrophilic functional groups (Fig. 2c). The results of the virtual screening were analyzed to evaluate the binding energy of iMQT_020. The in silico binding of iMQT_020 to the SLC1A5_var model was determined to be 19.77 μM with a K value of -6.A Gibbs free energy of 42 kJ / mol (Fig. 2e and Fig. 3a, b) was calculated, indicating that iMQT_020 exhibits a stable energy state when bound to the protein. The quinazoline-dione structure of iMQT_020 interacted hydrophobicly with F97, one of three residues important for the trimeric interaction. In addition, it maintained hydrogen bonds with R263 and I87, forming bonds with the hydroxyl and chloride groups of the chloro-fluorophenol side chain of iMQT_020, respectively (Fig. 2f). Other residues such as V83, M90, V93, and L260 were confirmed to form hydrophobic bonds with the carbon molecules of the chloro-fluorophenol side chain (Fig. 2f).

[0203]

[0204] [Screening of allosteric inhibitory compounds against SLC1A5_var]

[0205] 1. Compound 1 and its analogs

[0206]

[0207]

[0208]

[0209] 2. Compound 2 and its analogs

[0210]

[0211]

[0212]

[0213]

[0214]

[0215]

[0216] 3. Compound 3 and its analogs

[0217]

[0218]

[0219]

[0220] 4. Compound 4 and its analogs

[0221]

[0222]

[0223]

[0224]

[0225]

[0226] 5. Compound 5 and its analogs

[0227]

[0228]

[0229] 1-3. Confirming the mechanism of action of iMQT_020

[0230] To determine the mechanism of action of iMQT_020, we investigated whether it inhibited trimer formation of SLC1A5_var. Immunoprecipitations were performed between Myc-tagged SLC1A5_var_WT and His-tagged SLC1A5_var_WT using various concentrations of iMQT_020. The protein-protein interaction between the two tags was attenuated in a concentration-dependent manner, with an IC50 of 1.594 μM (Fig. 2g). In contrast, iMQT_020 did not inhibit the protein-protein interaction with ASCT2 (Fig. 2g). To further confirm the inhibition of SLC1A5_var trimer formation by iMQT_020, size-exclusion chromatography-based FPLC was performed. We used eGFP SLC1A5_var_WT and FIL / AAA to assess whether iMQT_020 dissociates the trimer of SLC1A5_var (Fig. 2h). eGFP SLC1A5_var_WT or FIL / AAA were passed through a Superdex 200 Increase 10 / 300 column in the presence or absence of iMQT_020. In the absence of iMQT_020, eGFP SLC1A5_var_WT showed a peak at 11.2 mL (blue), and eGFP SLC1A5_var_FIL / AAA showed a peak at 13.4 mL (green). Upon introduction of iMQT_020, eGFP-tagged SLC1A5_var_WT showed two peaks (red) at 11.4 mL and 13.3 mL. In contrast, iMQT_020 did not induce a change in the fluorescence peak of eGFP SLC1A5_var_FIL / AAA (purple). Fractions collected from 8 mL to 14 mL were analyzed to detect SLC1A5_var. Interestingly, for eGFP-tagged SLC1A5_var_WT, the SLC1A5_var band was detected in the initial fraction, whereas in the other fractions, the protein band of SLC1A5_var appeared in the 11th and 12th fractions (Fig. 2h).This suggests that iMQT_020 acts as a selective allosteric inhibitor of SLC1A5_var, effectively inhibiting the formation of the trimeric structure.

[0231]

[0232] After elucidating the mechanism of action of iMQT_020, we validated the proof-of-concept. IC for mitochondrial glutamine transport by iMQT_020 50The value was confirmed to be 6.156 μM (Fig. 2i). To confirm that iMQT_020 acts as a non-competitive allosteric inhibitor of SLC1A5_var, a Weaver-Burk plot of iMQT_020 was performed at concentrations of 0, 5, and 10 μM (Fig. 2j). As a result, iMQT_020 was found to exert its inhibitory effect in a non-competitive manner with the substrate, meaning that the compound does not bind to the substrate binding site but rather binds to the allosteric site of SLC1A5_var. Further investigation was conducted to evaluate whether iMQT_020 could inhibit other substrates of SLC1A5_var. Mitochondrial transport assays for asparagine, serine, leucine, and proline were performed. Asparagine and serine, known substrates of SLC1A5_var, showed inhibition rates of 84.01% and 62.14%, respectively. However, leucine and proline, which are not known substrates of SLC1A5_var, did not show a significant inhibitory effect or even increased uptake (Fig. 2k, top). Next, the selectivity of iMQT_020 was investigated by measuring the degree of amino acid transport through the cell membrane. Glutamine, asparagine, serine, leucine, and arginine did not change their transport through the cell membrane when treated with 10 μM iMQT_020 (Fig. 2k, bottom). To confirm that iMQT_020 directly binds to SLC1A5_var, microscale thermophoresis (MST) was performed using purified eGFP-tagged SLC1A5_var WT and FIL / AAA proteins. The change in fluorescence intensity in response to various concentrations of iMQT_020 indicates direct binding to SLC1A5_var WT (Fig. 2l, left). In contrast, no binding of iMQT_020 was observed in the FIL / AAA mutant (Fig. 2l, right). MST data confirmed that iMQT_020 and SLC1A5_var protein exhibited a dissociation constant (Kd) of 4.473 μM (Fig. 2m).To investigate the structural changes in SLC1A5_var induced by binding of iMQT_020, circular dichroism (CD) spectroscopy was performed. CD spectra were first collected at various molar concentrations of SLC1A5_var WT and FIL / AAA proteins. As the FIL / AAA ratio increased, the amount of protein present as a monomer increased, resulting in a distinct pattern of decreased CD between 190 and 270 nm (Fig. 2n). Treatment of SLC1A5_var WT with iMQT_020 resulted in a significant decrease in this wavelength range compared to vesicle treatment. In contrast, no spectral changes in FIL / AAA were observed upon addition of iMQT_020 (Fig. 2o). These results confirm that iMQT_020 directly binds to SLC1A5_var WT and induces structural changes. We directly assessed the off-target effects of iMQT_020 using a transporter activity assay system that utilizes YFP protein, a widely used halogen transporter assay system for amino acid transport. YFP quenching systems for SLC1A5, SLC38A1, SLC6A14, SLC6A19, SLC26A3, SLC26A4, SLC26A6, SLC26A7, SLC26A9, and ANO1 were prepared (Fig. 3c). While V-9302, a known SLC1A5 inhibitor, inhibited YFP quenching of SLC1A5, SLC38A2, and SLC6A19, iMQT_020 did not inhibit quenching of any transporters, confirming its selectivity for the mitochondrial SLC1A5_var. The selectivity of iMQT_020 was further validated using a thermostability assay (Figs. 3d, 3e). Based on previous studies, this assay to assess the stability of membrane proteins upon ligand binding revealed that iMQT_020 selectively destabilizes SLC1A5_var, resulting in a melting temperature (Tm) of 26.1°C to 21.A significant change was observed at 0℃ (Fig. 3e). Conversely, the Tm of SLC1A5, SLC38A1, and SLC38A2 due to iMQT_020 did not change significantly (Fig. 3e). These results collectively indicate that iMQT_020 functions as a selective allosteric inhibitor of mitochondrial SLC1A5_var.

[0233] To investigate the role of mitochondrial glutamine transport in cancer metabolic reprogramming, cancer cells were treated with iMQT_020, and the effect on glutamine metabolism was examined using C13-labeled glutamine (Fig. 4a). MIA PaCa-2 cells treated with control or iMQT_020 were analyzed by LC-MS / MS. iMQT_020 treatment reduced the levels of glutamine-derived TCA cycle metabolites and glutaminolysis products (Fig. 4b-k). In particular, the levels of glutamine-derived glutamate and aKG, a major mitochondrial glutamine breakdown product, were significantly reduced compared to non-glutamine-derived metabolites (Fig. 4b,c). Next, the effect of iMQT_020 on glutamine-derived TCA cycle metabolites was investigated. Surprisingly, the levels of glutamine-derived succinate (Fig. 4d), fumarate (Fig. 4e), malate (Fig. 4f), oxaloacetate (Fig. 4g), and citrate (Fig. 4h) were significantly reduced by iMQT_020 treatment. Furthermore, downstream metabolites, such as reduced glutathione, proline, lactate, and palmitate, resulting from the reductive carboxylation of glutamine, were also evaluated (Fig. 4a). Glutamine-derived glutathione (Fig. 4i) and proline (Fig. 4j) were significantly reduced in iMQT_020-treated cells. Although most palmitate is not derived from glutamine, glutamine-derived palmitate was significantly reduced by iMQT_020 (Fig. 4k). These results demonstrate that iMQT_020 significantly inhibits glutamine catabolism, a key pathway required for cancer metabolism, by inhibiting mitochondrial glutamine transport. To further elucidate the effects of iMQT_020, we investigated the effects of inhibition of mitochondrial glutamine transport. First, we confirmed that iMQT_020 decreased C13-labeled glutathione (GSH) levels (Fig. 4l). Addition of aKG, a glutamine-degrading GSH metabolite, restored glutathione levels in iMQT_020-treated cells.Furthermore, iMQT_020 treatment increased cellular reactive oxygen species (ROS) levels in MIA PaCa-2 cells, but aKG supplementation again reduced ROS levels (Fig. 4m). iMQT_020 increased mitochondrial ROS (MitoROS) levels by interfering with mitochondrial metabolism, but levels could be restored by aKG supplementation (Fig. 4n). Because glutaminolysis promotes oxidative phosphorylation for ATP production, we expected iMQT_020 to decrease ATP levels. Indeed, iMQT_020 inhibited ATP production, a phenomenon that could be reversed by aKG supplementation (Fig. 4o). These results demonstrate how inhibition of mitochondrial glutamine transport impairs ATP production and redox balance in cancer cells.

[0234]

[0235] Example 2. Confirmation of metabolic changes in pancreatic cancer cells due to mitochondrial SLC1A5_var inhibition.

[0236] Next, to assess the effect of iMQT_020 on cellular metabolic flux, we investigated the specific metabolic effects of iMQT_020 in cells overexpressing SLC1A5_var WT and the FIL / AAA mutant. After 24 h of treatment with 10 μM iMQT_020, a Seahorse assay was performed. The results showed that the oxygen consumption rate (OCR) was significantly increased in cells overexpressing SLC1A5_var WT (Fig. 6a, b). In contrast, the OCR of cells overexpressing the FIL / AAA mutant was similar to that of control (Con) cells. After iMQT_020 treatment, the OCR of cells overexpressing SLC1A5_var WT decreased to the level of control cells. These results suggest that iMQT_020 targets SLC1A5_var and that its metabolic effects are not off-target. To further confirm this, we investigated the effect of glutamine on OCR. While the glutamine-induced OCR in cells overexpressing SLC1A5_var WT was suppressed by iMQT_020, cells overexpressing the FIL / AAA mutant maintained a low and stable OCR regardless of glutamine supplementation (Fig. 6c, d). In the presence of 2 mM αKG, mitochondrial respiration was maintained regardless of iMQT_020 treatment (Fig. 6e, f). However, iMQT_020 treatment alone induced mitochondrial stress, significantly reducing OCR in cells overexpressing SLC1A5_var WT (Fig. 6e, f). These results demonstrate that iMQT_020 directly targets SLC1A5_var to inhibit mitochondrial respiration, highlighting the specific action of iMQT_020 on SLC1A5_var.

[0237] To explore the effect of iMQT_020 on glutamine-dependent glycolysis, we analyzed metabolic pathways. The extracellular acidification rate (ECAR) was measured in response to glutamine and iMQT_020. Glutamine supplementation slightly increased ECAR, whereas iMQT_020 treatment did not (Fig. 6g, h). This suggests that inhibition of mitochondrial glutaminolysis by iMQT_020 leads to decreased glycolytic activity. Furthermore, iMQT_020 decreased the basal ECAR in cells overexpressing SLC1A5_var WT. To further verify the effect of iMQT_020 on the glucose-dependent metabolic phenotype, we performed a comprehensive metabolic analysis. Upon iMQT_020 treatment for 24 h, both glucose-induced OCR (Fig. 6i, j) and ECAR (Fig. 6k, l) were suppressed. In cells overexpressing SLC1A5_var WT, iMQT_020 significantly reduced both basal and maximal OCR (Fig. 6i), whereas in cells overexpressing the FIL / AAA mutant, OCR showed no difference between the control and iMQT_020-treated groups. Furthermore, iMQT_020 partially suppressed the glucose-stimulated ECAR increase in cells overexpressing SLC1A5_var WT (Fig. 6k). However, in cells overexpressing SLC1A5_var FIL / AAA, the glucose-stimulated ECAR increase was not affected by iMQT_020. To verify the mitochondrial-specific effects of iMQT_020, experiments were conducted using mitochondria isolated from MIA PaCa-2 cells. In mitochondria where SLC1A5_var was knocked down, glutamine-induced OCR was attenuated (Fig. 6m, n). Control (Con) and expression of SLC1A5_var FIL / AAA failed to restore OCR, and iMQT_020 also failed to induce significant changes in OCR.However, when SLC1A5_var WT expression was restored, the OCR inhibition induced by iMQT_020 treatment was reversed, demonstrating that the effect of iMQT_020 is mediated through the inhibition of SLC1A5_var function in the mitochondria. Additionally, analysis of OCR in cancer cell lines revealed that iMQT_020 treatment decreased OCR, and this phenomenon was restored by αKG supplementation (Fig. 6o). Furthermore, metabolic profiling of cancer cells under iMQT_020 treatment confirmed that mitochondrial SLC1A5_var suppression caused cells to transition from an energy-consuming to a quiescent state. This metabolic transition could be reversibly restored by αKG supplementation (Fig. 6p). These results demonstrate that iMQT_020 reprograms cancer cell metabolism by allosterically inhibiting mitochondrial SLC1A5_var, inhibiting both glycolysis and oxidative phosphorylation.

[0238] Since iMQT_020 interferes with oxidative phosphorylation in cancer cells (Fig. 6a), we investigated its effects on mitochondria. First, we examined whether iMQT_020 affects the localization of the target SLC1A5_var. Immunofluorescence analysis revealed that SLC1A5_var and MitoTracker remained localized identically even after iMQT_020 treatment (Fig. 5a, b). Mitochondrial fractionation analysis confirmed that SLC1A5_var co-fractionated with the inner mitochondrial membrane marker Tim23, indicating that iMQT_020 did not affect target localization (Fig. 5c). Next, we investigated the effect of iMQT_020 on mitochondrial biogenesis. In cells treated with iMQT_020, the number of fragmented mitochondria was reduced (Fig. 5a, d), indicating that mitochondrial conditions were worsened and oxidative stress and fragmentation were induced. This was supported by a decrease in mitochondrial membrane potential observed using TMRE dye in iMQT_020-treated cells (Fig. 5e). These data demonstrate that iMQT_020 significantly alters mitochondrial dynamics in cancer cells by inhibiting mitochondrial glutamine transport activity.

[0239]

[0240]

[0241] Example 3. Confirmation of the effect of mitochondrial SLC1A5_var inhibition on cytosolic glucose and glutamine metabolism in pancreatic cancer cells.

[0242] We investigated the effects of blocking glutamine uptake into mitochondria by iMQT_020 treatment on overall cellular metabolism. The effect of iMQT_020 on the metabolic flux of glucose was analyzed using 13-C6-labeled glucose (Fig. 7a). In particular, iMQT_020 treatment significantly increased the production of C6-labeled glucose such as fructose-1,6-bisphosphate (Fig. 7) and lactate (Fig. 7). 13-These actions were significantly inhibited by a decrease in labeled glucose metabolites. Furthermore, the production of glucose-derived TCA cycle metabolites, including citrate, αKG, and succinate, was reduced (Fig. 7d-f). Furthermore, the pentose phosphate pathway of glucose metabolism was confirmed to be inhibited by 6-phosphogluconate, which was reduced by iMQT_020 (Fig. 7g). However, the hexosamine biosynthesis pathway of glucose metabolism was increased. Increases in 13C-labeled GlcNAc-1-P (Fig. 7h) and C13-labeled UDP-GlcNAc (Fig. 7i) indicated a shift in the metabolic fate of cytosolic glucose. These results suggest that inhibition of SLC1A5_var not only disrupts a key glutaminolytic pathway but also glucose metabolism.

[0243]

[0244] We then explored the metabolic fate of cytoplasmic glutamine following inhibition of SLC1A5_var (Fig. 7j). To comprehensively elucidate the metabolic pathway of accumulated cytoplasmic glutamine, which serves as an important nitrogen source in the cytoplasm, LC-MS / MS analysis of N15-labeled glutamine was performed. The nitrogen of glutamine can be assimilated into the purine or pyrimidine pool during de novo nucleotide synthesis. Inhibition of SLC1A5_var via iMQT_020 resulted in N 15 - The levels of AMP and UMP derived from labeled glutamine decreased (Fig. 7k, l). In addition, the nitrogen of glutamine can be catabolized to produce UDP-GlcNAc and asparagine. N 15 -15N-labeled asparagine and N-labeled glutamine derived from 15- The amount of labeled UDP-GlcNAc increased (Fig. 7m, n). Interestingly, the levels of asparagine and UDP-GlcNAc in unlabeled metabolites were also significantly increased compared to iMQT_020-untreated cells (Fig. 7o, p). These results suggest that under metabolic perturbation, metabolites are diverted toward asparagine and hexosamine biosynthesis. Notably, cytosolic glutamine is preferentially utilized along specific metabolic pathways (Fig. 7k-n). Overall, these results indicate that metabolic stress alters glucose and glutamine metabolic pathways to overcome energy resource limitations, and furthermore, inhibition of mitochondrial glutamine transport reorients cancer cell metabolism, affecting glucose metabolism and allowing the utilization of excess cytosolic glutamine for asparagine and UDP-GlcNAc biosynthesis.

[0245]

[0246] Example 4. Confirmation of metabolic crisis induction in pancreatic cancer cells by mitochondrial SLC1A5_var inhibition.

[0247] To investigate the overall effects of iMQT_020 on cancer cell metabolism, we examined mRNA expression changes in MIA PaCa-2 cells treated with iMQT_020. mRNA-seq analysis revealed significant changes in over 279 genes. Subsequent KEGG pathway analysis revealed that genes related to metabolism were significantly downregulated in iMQT_020-treated cells. Given that iMQT_020 significantly altered cancer cell metabolism, we conducted a detailed investigation of metabolism-related genes. In particular, genes controlling amino acid, carbohydrate, energy metabolism, lipid, and nucleotide metabolism were significantly downregulated (Fig. 8a). Glutathione metabolism, amino sugar and nucleotide metabolism, fatty acid metabolism, and purine metabolism showed decreased gene expression associated with each metabolic pathway, with significant p-values. We further confirmed the downregulation of oxidative phosphorylation, glycolysis, and gluconeogenesis upon iMQT_020 treatment (Fig. 9a). When iMQT_020 inhibits SLC1A5_var function, it induces suppression of comprehensive metabolic pathways, suggesting that targeting the mitochondrial glutamine transporter induces metabolic crisis in cancer cells, leading to selective metabolic collapse.

[0248]

[0249] Next, we performed gene set enrichment analysis (GSEA) using the GO-Biological Process gene set (Fig. 9b). Within this gene set, we analyzed metabolic processes and identified the top 15 metabolic processes that showed changes. Notably, both glutathione and glutamine metabolism showed statistically significant decreases in gene expression upon iMQT_020 treatment. Furthermore, metabolic pathways such as pyruvate metabolism, pyrimidine metabolism, and unsaturated fatty acid metabolism were significantly downregulated (Fig. 9b). Among the top 10 significantly differentially expressed gene sets within the GO-Biological Process gene set, both glycolysis and oxidative phosphorylation gene sets were significantly downregulated in iMQT_020-treated MIA PaCa-2 cells (Fig. 9c). This observation, further supported by GO term analysis, indicates that iMQT_020 induced a metabolic crisis in pancreatic cancer cells. Finally, we performed HALLMARK analysis using GSEA (Fig. 9d). Surprisingly, HALLMARKs associated with oxidative phosphorylation, ROS pathway, and glycolysis showed significantly negative normalized enrichment scores (Fig. 9d).

[0250]

[0251] To validate the transcriptome results, we compared them with proteomic data. First, protein expression analysis after iMQT_020 treatment revealed no significant changes in SLC1A5_var expression (Fig. 8b). We observed decreased p-S6K levels, likely due to the inhibition of mTORC1 by SLC1A5_var. Consistent with the transcriptome data, protein expression of GPX4, IDH2, HK1, PKM1, ACADVL, ACADM, APRT, NME2, PPAT, and PFAS, enzymes involved in amino acid, carbohydrate, lipid, and nucleotide metabolism, was decreased (Fig. 8b). Consistent with the transcriptome and metabolic flux analyses, expression of UDP-GlcNAc and ASNS increased.

[0252]

[0253] To understand the overall effects of iMQT_020 on cancer, unbiased metabolomics analysis was used to compare iMQT_020-treated and control MIA PaCa-2 cells. Using Q-Exactive Orbitrap LC-MS / MS, we identified 615 metabolites, and found significant differences in 188 metabolites across six Metabolika Superpathways (p<0.05, Welch's two-sample t-test) (Figs. 8c and 9e). In particular, metabolites related to glutamine metabolism, purine metabolism, glutathione metabolism, and ammonia recycling were significantly altered (Fig. 9e). Glutamine-derived metabolites, such as glutathione, glutamate, aKG, and N-acetyl-glutamate, were reduced (Fig. 8c), and metabolites related to ATP and NAD were also reduced upon iMQT_020 treatment (Fig. 8c). Furthermore, due to glutamine's pivotal role in the nucleotide salvage pathway, numerous purine- and pyrimidine-related metabolites were found to be downregulated (Fig. 8c). Among lipid metabolites, a significant decrease in fatty acid-related metabolites, such as stearic acid, lauric acid, and oleic acid, was observed (Fig. 8c). Increased levels of asparagine and UDP-GlcNAc indicate cytosolic glutamine conversion to asparagine or hexosamine. DL-histidine, hydroxyethyl methacrylate (HEMA), and vitamin C act as major antioxidants in place of glutathione. The increase in D-pantothenic acid (Fig. 8c) suggests a compensatory response to metabolic deficiency through coenzyme A (CoA) production and antioxidant synthesis via the Krebs cycle.

[0254]

[0255] Example 5. Confirmation of pancreatic cancer cell death by inhibition of mitochondrial SLC1A5_var.

[0256] The crucial role of SLC1A5_var in cancer cell survival has been reported, and we genetically verified its importance. SLC1A5_var mRNA expression was low in normal epithelial cells and normal stellate cells from the pancreas, colon, lung, breast, and ovary, but high in most cancer cells (Figures 10A and 11A). In contrast, other membrane glutamine transporters, such as SLC1A5, SLC38A1, and SLC38A2, did not consistently differ between normal and cancer cells (Figures 10A and 11A). Because glutamine promotes mitochondrial activity, particularly in cancer cells, through the Warburg Effect, SLC1A5_var is essential for survival. We tested this by using siRNA to suppress SLC1A5_var expression in normal and cancer cells from the pancreas, colon, and lung. Normal cells were not affected, but the viability of cancer cells was significantly reduced (Fig. 11b), indicating that SLC1A5_var is important for supplying TCA cycle metabolites and ATP energy for cancer cell survival.

[0257]

[0258] Based on these results, we expected that iMQT_020 would selectively inhibit SLC1A5_var, thereby reducing cancer cell viability and inducing metabolic crisis only in cancer cells while sparing normal cells. To test this, we performed a cancer cell viability screening using 10 μM iMQT_020 in 11 pancreatic cell lines, including normal epithelial cells and 10 pancreatic cancer cell lines (Fig. 10b). Eight pancreatic cancer cell lines showed significant changes in viability regardless of mutation status. We compared the IC50 values ​​of iMQT_020 in normal pancreatic epithelial cells and pancreatic cancer cells (Fig. 10c). The HPDE cell line did not reach 50% viability even at 300 μM of iMQT_020. The IC50 values ​​for MIA PaCa-2 and Panc-1 cells were 13.15 and 13.86 μM, respectively. We sought to investigate the correlation between iMQT_020 efficacy and SLC1A5_var expression (Fig. 10d). The Pearson correlation coefficient was -0.7351, indicating a strong negative correlation. To closely examine the effects of iMQT_020 on other cancers, we additionally screened 39 other cell lines, including 6 normal and 33 cancer cell lines from 5 tissues (Fig. 11c). Normal cells, such as BJ, 16HBE, FHC, MCF10A, Astrocyte, and CHO-K1, showed minimal changes, whereas most cancer cells showed significantly reduced viability. As observed in pancreatic cancer cells, mutation status did not significantly affect the efficacy of iMQT_020. Comparing the efficacy of iMQT_020 with the expression of SLC1A5_var across all 50 cell lines, the Pearson correlation coefficient was -0.6881 (Fig. 11d), indicating a strong negative correlation with SLC1A5_var expression. Notably, other membrane glutamine transporters, such as SLC1A5, SLC38A1, and SLC38A2, did not correlate with iMQT_020 efficacy. This demonstrates the potential of iMQT_020 as an anticancer agent that centrally targets glutamine metabolism.We compared the efficacy of iMQT_020 against cancer and normal cells. Interestingly, no IC50 value was observed in normal cells (Fig. 12a-e). In the case of cancer cells, the IC. 50 The values ​​ranged from 5 to 40 uM, and the specific values ​​for NCI-H460 (Fig. 12a), COLO205 (Fig. 12b), SNB-19 (Fig. 12c), BT-20 (Fig. 12d), and SK-OV-3 (Fig. 12e) were 7.612, 19.18, 28.21, 9.993, and 21.83 uM, respectively. Supplementation of aKG restored the viability of pancreatic cancer cells, confirming the mechanism of iMQT_020 (Fig. 10e). Then, the effect of iMQT_020 on organoids derived from human pancreatic ductal adenocarcinoma (PDAC) patients was evaluated, and SLC1A5_var expression was differentially observed (Fig. 10f). Treatment with iMQT_020 reduced organoid growth (Fig. 10g), and the IC50 value for growth inhibition was determined (Fig. 10h). A correlation plot of the effect of iMQT_020 on SLC1A5_var expression in PDAC patient-derived organoids yielded a significant correlation constant of -0.6740 (Fig. 10i). These results demonstrate the efficacy of iMQT_020 in selectively targeting cancer cells while sparing normal cells, inducing a metabolic crisis in cancer cells that rely on glutamine metabolism for survival.

[0259]

[0260] Example 6. Confirmation of pancreatic cancer growth inhibition by suppression of mitochondrial SLC1A5_var.

[0261] Next, we evaluated the in vivo efficacy of iMQT_020. First, we examined pharmacokinetic data. The mean drug residence time was 6.9 hours, peak steady-state concentration was reached within 0.6 hours after intraperitoneal injection, and the half-life was 3.8 hours (Fig. 13a). To assess safety, hERG toxicity and the Ames assay were performed. iMQT_020 did not inhibit the hERG channel, and no mutagenic effects were observed in the Ames assay (Fig. 13b-d). Furthermore, to assess the toxicity of iMQT_020 following chronic exposure, we monitored body weight changes in mice treated with the vesicle, 75 mg / kg V-9302, or 75 mg / kg iMQT_020. No significant body weight changes were observed in any of the treatment groups (Fig. 13e). To more closely evaluate systemic toxicity, plasma glucose and glutamine concentrations were measured in healthy mice administered vesicle, V-9302, or iMQT_020. As a result, iMQT_020 did not alter plasma glucose and glutamine concentrations compared to vehicle, whereas V-9302 decreased glutamine concentrations. Hematoxylin & Eosin (H&E) staining of lung, liver, and kidney tissues to evaluate tissue toxicity revealed no significant tissue damage caused by iMQT_020 or V-9302 treatment. These results were further supported by the absence of significant changes in plasma AST (aspartate aminotransferase), ALT (alanine aminotransferase), and BUN (blood urea nitrogen) levels (Fig. 13 h, i).To investigate potential effects on immune cells, we analyzed the viability and activation of splenocytes and thymocytes from mice treated with iMQT_020 or V-9302. While neither compound affected cell viability, it activated immune cells, as evidenced by increased CD44 expression (Fig. 13j, k). These results are consistent with previous studies showing that inhibition of glutamine metabolism promotes anti-tumor activity of T cells.

[0262] After confirming the safety of iMQT_020, we evaluated its antitumor efficacy in vivo. In athymic nude mice bearing MIA PaCa-2 xenograft tumors, administration of 75 mg / kg of iMQT_020 or V-9302 for 35 days significantly reduced tumor size, volume, and weight (Figs. 14a-d). Immunohistochemical (IHC) analysis of tumor tissues revealed that the iMQT_020-treated group had an increased number of cleaved caspase-3-positive cells, indicating increased apoptosis and decreased cell proliferation (Fig. 14e). In an orthotopic pancreatic adenocarcinoma (PDAC) xenograft model, iMQT_020 administration for 35 days significantly inhibited tumor growth, as evidenced by a decrease in radiant efficiency (Figs. 14f-h). To evaluate the antitumor activity of iMQT_020, experiments were conducted in colon and lung cancer xenograft models. iMQT_020 treatment significantly reduced the volume and weight of lung cancer (NCI-H1299) and colon cancer (COLO 205) xenograft tumors (Figs. 14i-l, nq). Furthermore, IHC staining of cleaved caspase-3 in these tumor tissues revealed similar apoptosis-promoting effects for both iMQT_020 and V-9302 (Figs. 14m, r).

[0263]

[0264] Example 7. Synergistic effect of inhibition of mitochondrial SLC1A5_var and anti-PD-L1 treatment.

[0265] Next, we analyzed the effect of iMQT_020 on PD-L1 gene expression. Treatment with iMQT_020 for 24 hours in mouse cancer cell lines (KPC, LC, and MC-38) resulted in an increase in both mRNA and protein levels of PD-L1 (Fig. 15a). This effect was reversed by treatment with αKG or CPI-455, suggesting that PD-L1 induction is mediated by glutamine metabolism-dependent epigenetic regulation, namely H3K4me3 modification. Furthermore, flow cytometry analysis of KPC cells revealed that iMQT_020 treatment increased membrane expression of PD-L1, which was reduced by treatment with the KDM5 inhibitor αKG (Fig. 15b). To further elucidate the PD-L1 induction mechanism, chromatin immunoprecipitation (ChIP) analysis was performed, and it was confirmed that iMQT_020 treatment significantly increased the H3K4me3 level in the PD-L1 promoter region of KPC cells (Fig. 15c). To evaluate the in vivo synergistic effect of iMQT_020 and immune checkpoint inhibitor combination therapy, experiments were performed in a subcutaneous xenograft model using KPC, LLC, and MC-38 mouse cancer cells. Mice were treated under the following conditions: 200 μg of αPD-L1 antibody (administered every 3 days), 25 mg / kg iMQT_020 (administered daily), 25 mg / kg V-9302 (administered daily), co-administration of αPD-L1 + V-9302, co-administration of αPD-L1 + iMQT_020.As a result, combination therapy significantly reduced tumor volume and weight compared to monotherapy, and a stronger effect was observed in the KPC and LLC tumor models than in the MC-38 tumor model (Fig. 16a-i). These results demonstrate the enhanced therapeutic effect of iMQT_020 and αPD-L1 combination therapy. Immunohistochemical staining results showed that cleaved caspase-3-positive cells increased and Ki-67-positive cells decreased in the combination treatment group, confirming the effects of promoting apoptosis and inhibiting cell proliferation (Fig. 16j-l). In addition, flow cytometry and IHC analyses confirmed increased PD-L1 expression, decreased PD-1+ T cells, and increased infiltration of cytotoxic CD8+ T cells in tumor tissues in the combination treatment group (Fig. 16m and 16n). Additionally, tumor digestion analysis revealed that iMQT_020 treatment increased the proportion of cytotoxic CD8+ T cells expressing Granzyme B and IFNγ (Fig. 16n). Tumor microenvironment analysis confirmed an increase in CD4+ T cells, a decrease in regulatory T cells (Treg), and a significant decrease in Ly6G+ and Ly6C+ myeloid-derived suppressor cells (MDSCs) (Fig. 16o). These results suggest that iMQT_020 modulates the tumor microenvironment to promote immune-mediated antitumor activity and exhibits potent antitumor effects when combined with αPD-L1.

[0266]

[0267] The foregoing description of the present invention is for illustrative purposes only, and those skilled in the art will readily appreciate that the present invention can be readily modified into other specific forms without altering the technical spirit or essential characteristics of the present invention. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. For example, each component described as a single entity may be implemented in a distributed manner, and similarly, components described as distributed may be implemented in a combined manner.

[0268] The scope of the present invention is indicated by the claims set forth below, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be interpreted as being included in the scope of the present invention.

Claims

1. A composition for preventing or treating cancer, comprising one compound selected from compounds represented by the following chemical formulas 1 to 5: [Chemical Formula 1] (Here, R1 is , , , , , , , and ) is selected from [Chemical Formula 2] (Here, R1 is , , , , , , , , , , , , , , , , and , and R2 is methyl or hydrogen) [Chemical Formula 3] (So ​​R1 is and ) is selected from [Chemical Formula 4] (Here R1 is , , , , , , , , , , , and , and R2 is methyl or hydrogen) [Chemical Formula 5] (Here R1 is lim) 2. In paragraph 1, The composition is a composition for preventing or treating cancer, which inhibits a mutant of SLC1A5, a mitochondrial glutamine transporter.

3. In paragraph 1, A composition for preventing or treating cancer, wherein the composition does not inhibit plasma membrane glutamine transporters.

4. In paragraph 1, The composition is a composition for preventing or treating cancer, which inhibits the transport of glutamine into mitochondria.

5. In paragraph 1, A composition for preventing or treating cancer, wherein the composition induces a metabolic crisis in cancer cells.

6. In paragraph 1, A composition for preventing or treating cancer, wherein the composition is formulated in the form of a tablet, capsule, pill, granule, powder, injection or liquid.

7. In paragraph 1, The composition is a composition for preventing or treating cancer, comprising a compound represented by the following chemical formula: [chemical formula] 8. In paragraph 1, The above compound is 6-(5-chloro-2-fluoro-4-hydroxyphenyl)quinazoline-2,4(1H,3H)-dione, 6-(2-fluoro-4-hydroxy-5-methylphenyl)quinazoline-2,4(1H,3H)-dione, 6-(2-fluoro-6-methoxyphenyl)quinazoline-2,4(1H,3H)-dione, 6-(4-hydroxy-2,6-dimethylphenyl)quinazoline-2,4(1H,3H)-dione, 6-(3,4-dimethoxyphenyl)quinazoline-2,4(1H,3H)-dione, 6-{4-[1-(morpholin-4-yl)ethyl]phenyl}quinazoline-2,4(1H,3H)-dione, 6-[2-(aminomethyl)-2,3-dihydro-1-benzofuran-7-yl]quinazoline-2,4(1H,3H)-dione, 4-(2,4-dioxo-1,2,3,4-tetrahydroquinazolin-6-yl)-N-methyl-N-(2-methylpropyl)benzamide, 6-{4-[2-(methoxymethyl)pyrrolidine-1-carbonyl]phenyl}quinazoline-2,4(1H,3H)-dione, 7-{4-[(2-ethylpiperidin-1-yl)carbonyl]phenyl}isoquinolin-1(2H)-one, 7-[4-(1-morpholin-4-ylethyl)phenyl]isoquinolin-1(2H)-one, 3-(1-oxo-1,2-dihydroisoquinolin-7-yl)-N-(tetrahydro-2H-pyran-4-ylmethyl)benzamide, 7-[3-hydroxy-5-(2-piperidin-2-ylethyl)phenyl]isoquinolin-1(2H)-one, 7-(2-methoxy-5-methylphenyl)isoquinolin-1(2H)-one, 7-(2-fluoro-6-methoxyphenyl)isoquinolin-1(2H)-one, 7-[2-hydroxy-5-(trifluoromethyl)phenyl]isoquinolin-1(2H)-one, 7-(8-methylquinolin-5-yl)isoquinolin-1(2H)-one, 7-(2-chloro-6-methoxyphenyl)isoquinolin-1(2H)-one, 7-{5-[(4-butyl-1-piperazinyl)methyl]-2-methoxyphenyl}-1(2H)-isoquinolinone, 7-(8-methoxyquinolin-5-yl)isoquinolin-1(2H)-one, 7-[3-(azepan-1-ylcarbonyl)phenyl]isoquinolin-1(2H)-one, 6-(3-{[3-(hydroxymethyl)morpholin-4-yl]carbonyl}phenyl)isoquinolin-1(2H)-one, N-[3-(dimethylamino)propyl]-N-methyl-3-(1-oxo-1,2-dihydroisoquinolin-7-yl)benzamide, [3-(1-oxo-1,2-dihydro-7-isoquinolinyl)phenyl]acetic acid, 4-methyl-6-(3,4,5-trimethoxyphenyl)quinolin-2(1H)-one, N-ethyl-N-(4-hydroxybutyl)-4-(4-methyl-2-oxo-1,2-dihydroquinolin-6-yl)benzamide, 4-methyl-6-{4-[(4-methylpiperazin-1-yl)carbonyl]phenyl}quinolin-2(1H)-one, 6-(2,5-dimethoxyphenyl)-4-methoxyquinazoline trifluoroacetate, [4-(4-methoxy-6-quinazolinyl)phenyl]methanol, 6-[4-(2-aminoethyl)phenyl]quinazolin-4(3H)-one, 6-{3-[(4-methylpiperazin-1-yl)carbonyl]phenyl}quinazolin-4(3H)-one, 6-(5-chloro-2-fluoro-4-hydroxyphenyl)-4(3H)-quinazolinone, 6-{4-[(dimethylamino)methyl]phenyl}-4(3H)-quinazolinone, 6-[4-(2-methoxyethoxy)phenyl]quinazolin-4(3H)-one, 6-[4-(5-oxo-3-pyrrolidinyl)phenyl]-4(3H)-quinazolinone, 6-(2,3-dihydro-1,4-benzodioxin-6-yl)-4(3H)-quinazolinone, 6-[3-(methylthio)phenyl]quinazolin-4(3H)-one, 6-[4-(4-isopropylpiperazin-1-yl)phenyl]quinazolin-4(3H)-one, 6-[4-(azocan-1-ylcarbonyl)phenyl]quinazolin-4(3H)-one, 6-(4-methoxy-3,5-dimethylphenyl)quinazolin-4(3H)-one, 2-methyl-6-[3-(1H-pyrazol-3-yl)phenyl]quinazolin-4(3H)-one, 6-(4-hydroxyphenyl)-2-methylquinazolin-4(3H)-one and A composition for preventing or treating cancer, wherein the composition is any one selected from the group consisting of 3-[2-(4-amino-6-hydroxypyrimidin-2-yl)ethyl]-6-(4-fluorophenyl)quinazolin-4(3H)-one.

9. In paragraph 1, A composition for preventing or treating cancer, wherein the cancer is at least one selected from the group consisting of leukemia, lymphoma, hematopoietic malignancy, cervical cancer, sarcoma, testicular cancer, malignant melanoma, endocrine tumor, bone cancer, prostate cancer, uterus cancer, breast cancer, bladder cancer, brain cancer, liver cancer, stomach cancer, pancreatic cancer, skin cancer, lung cancer, larynx cancer, head and neck cancer, esophageal cancer, colorectal cancer, and ovarian cancer.

10. A health functional food for preventing or improving cancer, comprising a composition according to any one of claims 1 to 9. 11.a) Step of confirming the degree of binding of the candidate substance to the F97, I104 and L105 positions of the mitochondrial glutamine transporter protein; b) a step of treating the candidate substance with excellent binding degree to the mitochondrial glutamine transporter protein to confirm changes in the amount or biological activity of the protein; and c) a step of determining that the candidate substance that reduces the amount or activity of the mitochondrial glutamine transporter protein does not affect the plasma membrane glutamine transporter, and determining that the candidate substance is a substance for preventing or treating cancer; A method for screening a pharmaceutical composition for preventing or treating cancer comprising:

12. In paragraph 11, A method for screening a pharmaceutical composition for preventing or treating cancer, wherein the mitochondrial glutamine transporter protein is a SLC1A5 mutant.

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