MCT protein inhibitor-related prognostic and therapeutic methods
10085987 ยท 2018-10-02
Assignee
Inventors
Cpc classification
G01N33/6872
PHYSICS
A61K31/519
HUMAN NECESSITIES
G01N33/57492
PHYSICS
G01N2800/52
PHYSICS
A61P35/00
HUMAN NECESSITIES
International classification
Abstract
This invention provides a method of identifying one or more subgroups of cancer patients that are likely to benefit from treatment with a monocarboxylate transporter (MCT) protein inhibitor comprising: (a) obtaining a sample of a cancer/tumor tissue from each of said cancer patients; (b) determining the expression level of stromal MCT4 protein in each of said samples of cancer/tumor tissue to obtain a first dataset; and (c) using the expression level of the stromal MCT4 protein from said first dataset to classify each of said sets of one or more cancer patients as stromal MCT4-positive or stromal MCT4-negative, wherein the cancer patients classified as stromal MCT4-positive are patients that are more likely to benefit from treatment with said MCT protein inhibitor. This invention also provides related methods for treating a cancer/tumor whose stromal component expresses the MCT4 protein in a patient.
Claims
1. A method for treating a triple negative breast cancer/tumor whose stromal component expresses the MCT4 protein in a patient, comprising: (a) obtaining a stromal breast tissue sample from said patient; (b) determining the expression level of stromal MCT4 protein in said stromal breast tissue sample by staining the stromal cells for MCT4 expression; (c) determining the expression level of stromal Cav-1 protein in said sample of cancer/tumor tissue by staining the stromal tissues for Cav-1 expression; and (d) diagnosing the patient with a high risk cancer by scoring the stained stromal cells, said diagnosis being confirmed wherein more than 30% of said stromal cells are stained in a sample for MCT4 expression and wherein no straining of the stromal cells is identified for Cav-1 expression; and (e) administering to said diagnosed patient with a high risk cancer, an MCT protein inhibitor wherein the MCT protein inhibitor is selected from the group consisting of AR-C15858, AR C117977, and AZD-3965, wherein AZD-3965, AR C155858 and AR C117977 are represented by the following formulas: ##STR00001##
2. The method of claim 1, wherein the mode of administration of said compound is inhalation, oral, intravenous, sublingual, ocular, transdermal, rectal, vaginal, topical, intramuscular, intraperitoneal, epidural, subcutaneous, buccal, or nasal.
Description
BRIEF DESCRIPTION OF THE FIGURES
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DETAILED DESCRIPTION OF THE INVENTION
(9) We have recently proposed a new model of cancer metabolism to explain the role of aerobic glycolysis and L-lactate production in fueling tumor growth and metastasis. In this model, cancer cells secrete hydrogen peroxide (H202), initiating oxidative stress and aerobic glycolysis in the tumor stroma. This, in turn, drives L-lactate secretion from cancer-associated fibroblasts. Secreted L-lactate then fuels oxidative mitochondrial metabolism (OXPHOS) in epithelial cancer cells, by acting as a paracrine oncometabolite. We have previously termed this type of two-compartment tumor metabolism the Reverse Warburg Effect, as aerobic glycolysis takes place in stromal fibroblasts, rather than epithelial cancer cells. In this invention, we used MCT4 immuno-staining of human breast cancer tissue microarrays (TMAs; >180 triple-negative patients) to directly assess the prognostic value of the Reverse Warburg Effect. MCT4 expression is a functional marker of hypoxia, oxidative stress, aerobic glycolysis, and L-lactate efflux. Remarkably, high stromal MCT4 levels (score=2) were specifically associated with decreased overall survival (<18/survival at 10-years post-diagnosis). In contrast, patients with absent stromal MCT4 expression (score=0), had 10-year survival rates of 97% (p-value <10.sup.32). High stromal levels of MCT4 were strictly correlated with a loss of stromal Cav-1 (p-value <10.sup.14), a known marker of early tumor recurrence and metastasis. In fact, the combined use of stromal Cav-1 and stromal MCT4 allowed us to more precisely identify high-risk triple-negative breast cancer patients, consistent with the goal of individualized risk-assessment and personalized cancer treatment. However, epithelial MCT4 staining had no prognostic value, indicating that the conventional Warburg effect does not predict clinical outcome. Thus, the Reverse Warburg Effect or parasitic energy-transfer is a key determinant of poor overall patient survival. As MCT4 is a druggable-target, MCT4 inhibitors should be developed for the treatment of aggressive breast cancers, and possibly other types of human cancers. Similarly, we discuss how stromal MCT4 could be used as a biomarker for identifying high-risk cancer patients that could likely benefit from treatment with FDA-approved drugs or existing MCT-inhibitors (such as, AR-C1558 8, AR-C117977, and AZD-3965).
EXPERIMENTAL DETAILS
Materials and Methods
(10) Materials.
(11) Anti-MCT4 isoform-specific rabbit polyclonal antibodies were previously generated and characterized by Dr. Nancy Philp.sup.30. Isoform-specific antibodies were produced against the 18-mer synthetic oligopeptide corresponding to the carboxyl terminal amino acids of MCT4.sup.30.
(12) The Study Population and Tumor Microarray Construction.
(13) Cases for the study where obtained from the Surgical Pathology files at the Thomas Jefferson University, with Institutional Review Board approval. The tissue-microarray (TMA) contained tumor samples derived from 181 largely consecutive patients with triple negative breast carcinoma (with follow-up information) treated at the Thomas Jefferson University. For inclusion in this study as TN breast cancer, expression of estrogen, progesterone receptors was not detected or present in <1% of tumor cells, with a satisfactory positive control. HER2 was scored 0-1+ or 2+, and an absence of HER2 amplification by fluorescent in situ hybridization was required for negativity. All cases were invasive ductal carcinomas (IDC). Clinical and pathological variables were determined following well-established criteria. All TN breast cancers were graded according to the method described by Elston and Ellis; lymphovascular invasion was classified as either present or absent. The tumor tissue-microarrays (TMAs) were constructed using a tissue arrayer (Veridiam, San Diego, Calif.). Two tissue cores (0.6 m diameter) were sampled from each block to account for tumor and tissue heterogeneity and transferred to the recipient block. Clinical and treatment information as extracted by chart review.
(14) Immunostaining.
(15) Cav-1 and MCT4 expression levels were assessed using a standard 3-step avidin-biotin immunoperoxide method, with a rabbit polyclonal anti-Cav-1 antibody (Santa Cruz Biotech, Inc. (N-20; sc-894, Santa Cruz Biotech, diluted 1:1,000) or a rabbit polyclonal anti-MCT4 antibody (diluted 1:250) a 3-step avidin biotin immunoperoxidase method. TMA sections were de-paraffinized and re-hydrated through graded alcohols. Antigen retrievals as performed in 10 mM citrate buffer, pH 6.0 for 10 min in a pressure cooker. Sections were cooled to room temperature, rinsed in PBS, blocked with 3% (v/v) H.sub.20.sub.2 for 15 min, followed by blocking for endogenous biotin using the DakoCytomation Biotin Blocking System cat#X0590. Slides were then incubated for 1 hour with 10% goat serum and incubated with primary antibody overnight at 4 C. Antibody binding was detected using a biotinylated secondary antibody (Vector Labs, cat#BA-1000) followed by streptavidin-HRP (Dako cat#K 1016). Immunoreactivity was detected using Dako Liquid DAB+Substrate-Chromogen Solution.
(16) Stromal Scoring.
(17) Stromal Cav-1 staining was scored semi-quantitatively as negative (0, no staining), weak (1, either diffuse weak staining or strong staining in less than 30% of stromal cells per core), or strong 2, defined as strong staining of 30% or more of the stromal cells).sup.1-3. MCT4 expression in the stroma was performed using same criteria as those we applied for scoring Cav-1 expression.
(18) Epithelial Scoring.
(19) For evaluating MCT4 expression in tumor epithelial cells, we used a previously developed scoring system.sup.31. Sections were scored semi-quantitatively as follows: 0, 0% immuno-reactive cells; 1, <5% immuno-reactive cells; 2, 5-50% immuno reactive cells; and 3, >50% reactive cells. Similarly, intensity of staining was evaluated semi-quantitatively on a scale 0-3 with 0, representing negative, 1, weak, 2, moderate and 3, strong staining. Then the final score was calculated, reflecting both the percent of immuno-reactive cells and staining intensity.
(20) Statistical Analysis.
(21) As noted, we scored stromal Cav-1 and MCT4 expression in the TMAs as 0 (none), 1 (low) and 2 (high). Epithelial MCT4 was scored as 0 (none), 1 (low), 2 (medium and 3 (high). The outcome of interest here is overall survival, i.e. death can occur for any cause. Survival curves were computed by expression strata using the Kaplan-Meier method, and differences between survival curves was assessed using the log-rank test. Hazard ratios for the biomarkers were computed using Cox proportional hazards regression, using the biomarker as predictor and adjusting for age and race. Agreement with the proportional hazards assumption was verified. Differences in 10-year survival were assessed based on two-sample z-tests, using estimates and standard errors from the Kaplan-Meier curves. All analyses were done using the statistical analysis package R version 2.13.sup.32, along with the R package survival version 2.36-9.sup.33. Associations were assessed using the -test for independence.
(22) Results
(23) Predicting Overall Survival in Triple-Negative (TN) Breast Cancer Patients: Assessing the Prognostic Value of Stromal MCT4
(24) Here, we investigated the predictive value of stromal MCT4 as a new candidate biomarker, for determining clinical outcome in TN breast cancer patients. More specifically, we used anti-MCT4 isoform-specific polyclonal antibodies to immuno-stain a tumor tissue microarray (TMA) containing paraffin-sections taken from TN breast cancer patients at surgical resection. This TMA cohort is well-annotated, and contains 181 patients seen at Thomas Jefferson University Hospital (TJUH), with up to 250 months (>20-years) of follow-up. In this TN breast cancer population, our main outcome of interest was overall survival. For comparison, the expression of MCT4 was scored in both the epithelial and stromal compartments. Also, the same TN-TMA was immune-stained for stromal Cav-1 expression. Table 1 shows the descriptive statistics (age, race, tumor size, histologic grade, stage, and lymph-node status) for the entire patient population.
(25) Stromal MCT4 and Stromal Cav-1 Levels are Inversely Related
(26) Representative images of MCT4 staining are shown in
(27) Interestingly, the expression levels of stromal MCT4 and stromal Cav-1 were inversely related. High levels of stromal MCT4 directly correlated with a loss of stromal Cav-1 immuno-staining, with a p-value of 510.sup.15. Table 2 shows the joint frequency distribution of stromal MCT4 and stromal Cav-1, and
(28) In this joint frequency distribution analysis, 55 patients showed high levels of MCT4 stromal staining, 72 showed moderate staining, and 32 showed an absence of MCT4 stromal staining.
(29) Similarly, 58 patients showed high levels of Cav-1 stromal staining, 50 showed and intermediate level of staining, and 51 showed an absence of Cav-1 stromal staining.
(30) Most notably, patients with stroma Cav-1=0 are most likely to be stromal MCT4=2. Conversely, patients with stromal Cav-1=2 are most likely to be stromal MCT4=0 or 1. Interestingly, we could not detect any patients with concomitant loss of both stromal Cav-1(Cav-1=0) and stromal MCT4 (MCT4=0), indicating that a loss of stromal Cav-1 is strictly correlated with increased MCT4 expression. Conversely, only very few cases (3 out of 159=2%) had high stromal expression of both MCT4 and Ca-11, indicating that high stromal MCT4 and high stromal Cav-1 are nearly mutually exclusive events.
(31) High Stromal MCT4 Predicts Poor Overall Survival
(32) Stromal Cav-1 and stromal MCT levels were also used to generate Kaplan-Meier survival curves, plotting percent survival (%) versus time since diagnosis (in months) (
(33) This univariate analysis identified the two high-risk groups as patients with i) absent stromal Cav-1 (score=0; N=51 patients) and ii) high stromal MCT4 (score=2; N=55 patients). Notably, the intersection of these two high-risk groups shows considerable overlap, with N=39 patients in co on Table 2).
(34) Hazard ratios are shown in Tables 3& 4, with stromal Cav-1 and stromal MCT4 showing 14-fold and 50-fold differences in relative risk stratification, respectively.
(35) In addition, 10-year survival rates are shown in Tables 5& 6. For example, if stromal MCT4=0, the 10-year survival rate was 97% versus <20% for stromal MCT4=2.
(36) Conversely, if stromal Cav-1=2, the 10-year survival rate was 91% versus 25% for stromal Cav-1=0.
(37) Combining Stromal Cav-1 with Stromal MCT4 Allows Further Stratification of the Intermediate Risk Group
(38) Notably, the two intermediate risk groups identified by stromal Cav-1 (score-1) and stromal MCT4 (score=1) could be further stratified by combining both stromal markers, allowing the unambiguous identification of high-risk and low-risk patients (
(39) For example, patients with stromal Cav-1 (score=1) could be further sub-divided into high- and low-risk groups using stromal MCT4 (
(40) MCT4 Expression in Tumor Epithelial Cells has No Prognostic Value
(41) Finally, in a parallel analysis carried out on the same exact patient TMAs, the levels of tumor epithelial MCT4 were scored (
(42) Similarly, we have previously shown that tumor epithelial Cav-1 levels have no prognostic value in two different breast cancer cohorts.sup.1,2.
(43) Discussion
(44) Tow-Compartment Tumor Metabolism: the Reverse Warburg Effect
(45) In 1889, Dr. Paget proposed the Seed and Soil Hypothesis, suggesting that cancer cells (the seeds) require a permissive microenvironment (the soil to facilitate tumor growth, progression and metastatic dissemination.sup.34-36.
(46) Recently, it has been proposed that oxidative stress in the tumor microenvironment may function as fertilizer, by driving DNA-damage, inflammation, and metabolic alterations.sup.24, 37-39. Tumor cells secrete hydrogen peroxide (H2O2) to induce oxidative stress (pseudo-hypoxia), fertilizing the tumor stroma.sup.28. As a consequence, oxidative stress initiated by tumor cells in transferred to cancer-associated fibroblasts.sup.28.
(47) Oxidative stress in cancer-associated fibroblasts then result in increased stromal ROS production, and the activiation of NFkB and HIF1-alpha transcription factors, inducing autophagy/mitophagy, inflammation, and aerobic glycolysis. Mitophagy (mitochondrial autophagy) then increases L-lactate and ketone production, due to a mitochondrial dysfunction or deficiency.sup.26,27,40.
(48) As a consequence, tumor-associated fibroblasts release high-energy metabolites (L-lactate and ketones) and chemical building blocks (nucleotides, fatty acids, and amino acids, such as glutamine). These catabolites stimulate mitochondrial biogenesis, OXPHOS, and autophagy-resistance in epithelial cancer cells, and protect cancer cells against chemotherapy-induced apoptosis.sup.17, 41, 42.
(49) We have termed this new model of cancer metabolism the Reverse Warburg Effect, as aerobic glycolysis takes place in stromal fibroblasts, and not in epithelial tumor cells.sup.11, 17, 18 (
(50) In this two-compartment system, oxidative cancer cells and glycolytic fibroblasts are metabolically-coupled, in a host parasite relationship.sup.17. Tumor cells directly feed off the glycolytic host microenvironment, behaving like an infectious parasite.sup.18. Thus, two-compartment tumor metabolism may be the basis of chemo-resistance or therapy-failure in cancer patients.sup.17. We have also demonstrated that ROS produced in cancer-associated fibroblasts, has a bystander effect on adjacent epithelial cancer cells, leading to DNA-damage, genomic-instability and aneuploidy.sup.26.
(51) In summary, we believe that a critical biological function of the tumor stroma is to produce L-lactate and other high-energy catabolites (such as ketones and glutamine) to fuel oxidative mitochondrial metabolism (OXPHOS) in adjacent epithelial cancer cells.sup.43-47.
(52) MCT4 and Normal Lactate Transport
(53) Specialized transporters, termed monocarboxylate transporters (MCTs), function as shuttles to transfer L-lactate from one cell-type to another.sup.48, 49. For example, MCT4 is primarily a transporter that extrudes L-lactate from cells that utilize aerobic glycolysis for energy metabolism and lack functional mitochondria.sup.50. Ketones are thought to be transported by the same MCT transporters that handle lactate transport. Physiologically, MCT4 expression is induced by hypoxia and/or oxidative stress, and MCT4 is a known HIF 1-alpha target gene.sup.48,51 Thus, MCT4 is a functional marker of oxidative stress and aerobic glycolysis, also known as the Warburg Effect.sup.29.
(54) Two physiological examples of cells that normally undergo the aerobic glycolysis are fast-twitch fibers in skeletal muscle and astrocytes in the brain.sup.52-56. In skeletal muscle, MCT4 is selectively expressed in fast-twitch fibers that are glycolytic, and extrude lactate, which is then taken up by slow-twitch fibers.sup.48, 49. In the brain, MCT4 is selectively expressed in astrocytes which are glycolytic, and export lactate, that is used as an energy source by adjacent neurons.sup.48, 49. In skeletal muscle, such metabolic-coupling is known as the Lactate Shuttle and in the brain, it is called Neuro-Glia Metabolic Coupling.sup.52-56. These normal physiologic forms of metabolic-coupling are analogous to the Reverse Warburg Effect, which is observe in tumor tissue.sup.29.
(55) MCT4 and the Reverse Warburg Effect
(56) Here, we investigated the compartment-specific expression of MCT4 in human breast cancer patients, and determined its potential association with overall clinical outcome. As MCT4 is a marker of oxidative stress and aerobic glycolysis, as well as L-lactate extrusion, it should allow us to determine if the Warburg Effect shows any prognostic value, in epithelial cancer cells, or the tumor stroma, or in both tumor compartments.
(57) In the conventional Warburg effect, epithelial cancer cells undergo aerobic glycolysis, likely due to mitochondrial dysfunction.sup.57, 60, and are predicted to express high levels of MCT4. Conversely, in the Reverse Warburg Effect, stromal fibroblasts undergo aerobic glycolysis, due to oxidative stress, and autophagy/mitophagy in the tumor stroma, resulting in a functional mitochondrial deficiency. As such, in the Reverse Warburg Effect, cancer-associated fibroblasts and the tumor stroma should over-express MCT4.sup.29. In both scenarios, glycolytic MCT4(+) cells would be metabolically-coupled with oxidative mitochondrial metabolism (OXPHOS) in adjacent MCT1(+) cells: MCT4 functions in L-lactate efflux, while MCT1 functions in L-lactate uptake (
(58) Thus, we directly compared the prognostic value of stromal and epithelial MCT4 expression in triple-negative breast cancer patients, within the same patient cohort. Our results directly show that high stromal MCT4 levels are specifically associated with poor overall survival. In contrast, expression of MCT4 in epithelial tumor cells had no prognostic value. As a result, it appears that high expression of MCT4 in the tumor stroma (the Reverse Warburg EWffect) is specifically associated with a lethal tumor microenvironment (
(59) Consistent with our current observations, increased serum and tumor L-lactate is a specific marker of poor clinical outcome in variety of cancer types 61-64, and lactic acidosis is a life-threatening complication in patients with metastatic breast cancer 65-70. Thus, these previous results may have been due to L-lactate over-production in the tumor microenvironment, rather than in epithelial tumor cells.
(60) Stromal MCT4: Implications for Treatment Stratification
(61) Here, we also show that stromal Cav-1 can be used in combination with stromal MCT4 to further stratify the intermediate risk group, into high-risk and low-risk subgroups, effectively increasing the prognosis power of stromal Cav-1 as a biomarker (
(62) Based on our mechanistic studies, this high-risk patient population should be more responsive to certain FDA-approved therapeutics, such as anti-oxidants (N-acetyl-cystein (NAC)), autophagy inhibitors (chloroquine and hydroxyl-chloroquine), mitochondrial poisons (metformin), as well as autophagy inducers (rapamycin and its derivatives).sup.20. All of these therapies would uncouple anabolic cancer cells from their catabolic hosts, by interrupting energy-transfer, effectively cutting off the fuel supply of preventing cancer cells from using the fuel supply (L-lactate, ketones, and/or glutamine) (Table 7). For Examiner, they could be used synergistically, in combination with conventional therapies, or during remission after conventional therapy to prevent recurrence, or even as single agents in patients with advanced metastatic disease.
(63) New targeted therapies would include MCT4 inhibitors to inhibit L-lactate/ketone efflux from glycolytic cancer-associated fibroblasts. MCT1/2 inhibitors may also be a rational approach, as they would likely prevent epithelial cancer from siphoning-off L-lactate/ketones from the MCT4(+) tumor microenvironment. MCT1 is highly expressed in epithelial tumor cells, and is involved in L-lactate/ketone uptake.sup.29.
(64) So, high-risk patients (defined as, stromal Cav-1-0 and stromal MCT4-2) could be selected for treatment with MCT1-inhibitors (such as, AR-C155858, AR-C117977, and AZD-3965.sup.71, 72) that have recently been developed by AstraZeneca, and are now undergoing Phase I/II clinical trials.
(65) See the following MCT1 inhibitor trial-related information:
(66) http://www.pharmaceutical-technology.com/news/news95840.html
(67) http://drugdiscoverynews.com/index.php?pg-77&articled-4235
(68) TABLE-US-00001 TABLE 1 Descriptive statistics for the TN Cohort. Variable N Values Age (years) 179 55.5 +/ 13.7 Race 178 White 76% (135) African American 24% (43) Tumor size (cm) 164 2.34 +/ 1.80 Histologic grade 168 1-2 26% (43) 3 74% (125) Stage 171 0 1% (1) 1 36% (62) 2 46% (78) 3 12% (21) 4 5% (9) Lymph node status 146 Negative 58% (85) Positive 42% (61) Numbers in brackets are frequencies. m s denotes mean standard deviation. N denotes number of non-missing observations. Total number of subjects in this study is 181.
(69) TABLE-US-00002 TABLE 2 Joint frequency distribution of stromal Cav-1 and stromal MCT4. There is evidence of a strong negative relationship between Cav-1 and MCT4 expression. The p-value is for the Fisher's exact test of independence between Cav-1 and MCT4 expression. The table includes only those records for which both Cav-1 and MCT4 are present (N = 159) MCT4 0 1 2 Total P value Cav-1 0 0 12 39 51 5 10.sup.15 1 8 29 13 50 2 24 31 3 58 Total 32 72 55 159
(70) TABLE-US-00003 TABLE 3 Hazard ratios for stromal Cav-1. 95% Confidence Hazard Ratio Interval Stromal Cav-1 0 14.17 (5.53, 36.35) 1 4.82 (1.78, 13.08) 2 (ref) 1
(71) TABLE-US-00004 TABLE 4 Hazard ratios for stromal MCT4. 95% Confidence Hazard Ratio Interval Stromal MCT4 0 0.02 (0.00, 0.16) 1 0.20 (0.11, 0.35) 2 (ref) 1
(72) TABLE-US-00005 TABLE 5 10 year survival by stromal MCT4 expression: Overall and conditional on stromal Cav-1 expression. Stromal MCT4 MCT4 = 0 MCT4 = 1 MCT4 = 2 Overall 10 yr survival 96.9% 75.5% 17.7% MCT4 = 0 3.9 10.sup.4 4.2 10.sup.33 MCT4 = 1 1.5 10.sup.13 Cav-1 = 1 10 yr survival 87.5% 77.9% 0% MCT4 = 0 0.50 7.3 10.sup.14 MCT4 = 1 2.14 10.sup.22 The shaded rows are the survival estimates, and the unshaded rows are the pairwise p-values testing equality of 10 year survival between strata.
(73) TABLE-US-00006 TABLE 6 10 year survival by stromal Cav-1 expression: Overall and conditional on stromal MCT4 expression. Stromal Cav-1 Cav-1 = 0 Cav-1 = 1 Cav-1 = 2 Overall 10 yr survival 25.2% 58.9% 90.8% Cav-1 = 0 0.001 5.9 10.sup.18 Cav-1 = 1 4.6 10.sup.4 MCT4 = 1 10 yr survival 43.8% 77.9% 86.7% Cav-1 = 0 0.05 0.01 Cav-1 = 1 0.39 The shaded rows are the survival estimates, and the unshaded rows are the pairwise p-values testing equality of 10 year survival between strata.
(74) TABLE-US-00007 TABLE 7 Candidate FDA-Approved Drugs for Targeting Two-Compartment Tumor Metabolism. Candidate Drugs Predicted Mechanism(s) of Action 1. N-Acetyl-Cysteine (NAC) Anti-Oxidant Will prevent oxidative stress in cancer-associated fibroblasts, halting autophagy in the tumor stroma, thereby cutting of the fuel supply (L-lactate, ketones, glutamine) to breast cancer cell mitochondria. 2. Hydroxy-Chloroquine* Autophagy Inhibitor Will inhibit autophagy and mitophagy in cancer-associated fibroblasts, thereby cutting off the fuel supply (L-lactate, ketones, glutamine) to breast cance cell mitochondria. 3. Metformin Inhibitor of Mitochondrial OXPHOS (Complex I) Will inhibit oxidative mitochondrial metabolism (OXPHOS) in breast cancer cells, preventing them from using L-lactate, ketones, and glutamine as mitochondrial fuels. 4. Rapamycin & Rapalogues Autophagy Inducer(s) Will induce autophagy and mitophagy in breast cancer cells, preventing them from using the available high-energy mitochondrial fuels, such as L-lactate, ketones, and glutamine. *Clinically, hydroxy-chloroquine is preferred as it has less side-effects than the parent compound, chloroquine. Importantly, we have shown that NAC, chloroquine, and metformin all prevent loss of stromal Cav-1 in fibroblasts, when co-cultured with breast cancer cells.
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