miR-526b dysregulates glucose metabolism via the COX2/EP4 pathway

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Abstract Introduction: Breast cancer (BRCA) remains a primary global health concern, with ongoing research focused on early detection and improving treatment methods. Moving forward, it is crucial to understand cancer cell metabolism and its impact on tumor growth and metastasis. This study aims to identify potential BRCA markers related to glucose metabolism for targeted therapy, focusing on the role of miR-526b. miR-526b promotes BRCA phenotypes, including migration, invasion, hypoxia, angiogenesis, and metastasis. Further, cell-free secretion of miR-526b-high BRCA tumor cells can alter the tumor microenvironment. This study will investigate the role of miR-526b in the dysregulation of glucose metabolism. Methods: We used two immortalized BRCA cell lines, MCF7 and SKBR3, and stable miR-526b overexpressed cells MCF7-miR526b and SKBR3-miR526b and a naturally miR-526b high cell line MCF7-COX2 for in vitro assays. We measured ATP production, oxygen consumption rate, and extracellular acidification rate. We used glycolysis and OXPHOS inhibitors to measure metabolic plasticity induced by miR-526b. A COX-2 inhibitor and EP4 antagonist were used to alter miR-526b-induced functions. For RNA and protein measurement, we used qRT-PCR and western blots. In silico analysis with online datasets validated our findings in human BRCA. Results: In silico analysis showed that genes related to glycolysis and oxidative phosphorylation (OXPHOS) are enriched in human breast cancer tissues. Overexpression of miR-526b promotes cell proliferation and ATP production. It also contributes to the upregulation of LDHA and PDHA1, which determine the fate of the glycolytic product pyruvate, either producing lactate or entering the TCA cycle to promote OXPHOS. miR-526b overexpressing cells demonstrated increased metabolic plasticity and decreased adverse effects following treatment with glycolysis and OXPHOS inhibitors, showing increased survival and proliferation. The metabolic dysregulation induced by miR-526b, including increased proliferation, ATP production, and marker expression, can be reversed using a COX2 inhibitor and EP4 antagonist. Conclusion: miR-526b promotes increased glucose metabolism and ATP production, supporting increased growth and division of BRCA cells. It also increases metabolic plasticity, improving cells' ability to thrive in a complex and heterogeneous tumor microenvironment. The dysregulation observed with miR-526b can be reversed by targeting the COX2/EP4 pathway.
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miR-526b dysregulates glucose metabolism via the COX2/EP4 pathway | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article miR-526b dysregulates glucose metabolism via the COX2/EP4 pathway Braydon D Nault, Mousumi Majumder This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4510975/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction: Breast cancer (BRCA) remains a primary global health concern, with ongoing research focused on early detection and improving treatment methods. Moving forward, it is crucial to understand cancer cell metabolism and its impact on tumor growth and metastasis. This study aims to identify potential BRCA markers related to glucose metabolism for targeted therapy, focusing on the role of miR-526b. miR-526b promotes BRCA phenotypes, including migration, invasion, hypoxia, angiogenesis, and metastasis. Further, cell-free secretion of miR-526b-high BRCA tumor cells can alter the tumor microenvironment. This study will investigate the role of miR-526b in the dysregulation of glucose metabolism. Methods: We used two immortalized BRCA cell lines, MCF7 and SKBR3, and stable miR-526b overexpressed cells MCF7-miR526b and SKBR3-miR526b and a naturally miR-526b high cell line MCF7-COX2 for in vitro assays. We measured ATP production, oxygen consumption rate, and extracellular acidification rate. We used glycolysis and OXPHOS inhibitors to measure metabolic plasticity induced by miR-526b. A COX-2 inhibitor and EP4 antagonist were used to alter miR-526b-induced functions. For RNA and protein measurement, we used qRT-PCR and western blots. In silico analysis with online datasets validated our findings in human BRCA. Results: In silico analysis showed that genes related to glycolysis and oxidative phosphorylation (OXPHOS) are enriched in human breast cancer tissues. Overexpression of miR-526b promotes cell proliferation and ATP production. It also contributes to the upregulation of LDHA and PDHA1, which determine the fate of the glycolytic product pyruvate, either producing lactate or entering the TCA cycle to promote OXPHOS. miR-526b overexpressing cells demonstrated increased metabolic plasticity and decreased adverse effects following treatment with glycolysis and OXPHOS inhibitors, showing increased survival and proliferation. The metabolic dysregulation induced by miR-526b, including increased proliferation, ATP production, and marker expression, can be reversed using a COX2 inhibitor and EP4 antagonist. Conclusion: miR-526b promotes increased glucose metabolism and ATP production, supporting increased growth and division of BRCA cells. It also increases metabolic plasticity, improving cells' ability to thrive in a complex and heterogeneous tumor microenvironment. The dysregulation observed with miR-526b can be reversed by targeting the COX2/EP4 pathway. Breast Cancer metabolism miRNA glycolysis oxidative phosphorylation metabolic dysregulation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 I. Introduction Breast cancer continues to have a devastating impact on the global population. In 2022, the most recent international data available, breast cancer was the second most-diagnosed cancer in the world, the most diagnosed among females (24.7% of female cancer diagnoses), and the deadliest cancer among females (16.1% of female cancer deaths) accounting for 666 103 deaths.( 1 ) Currently, routine screening is recommended to begin at age 50 in Canada. However, 21% of breast cancer deaths are reported in the younger population.( 1 , 2 ) Current research focuses on developing liquid biopsy screening techniques to improve overall survival with early detection. Another focus is targeted therapy options that improve patient outcomes, using personalized medicine to predict the best result based on an individual’s cancer characteristics. One of the hallmark phenotypes observed in cancer cells is alterations in metabolism.( 3 ) Understanding these metabolic abnormalities in various subtypes of breast cancer can lead to the development of new therapeutic targets and treatment options. The commitment to developing liquid biopsy screening for breast cancer will improve early detection as well as quality of life through a personalized medicine approach. Otto Warburg was the first to identify the increased consumption of glucose seen in cancer cells. A selective shift to the glycolytic production of ATP in the presence of oxygen, counter to oxidative phosphorylation (OXPHOS), is reported in cancer cells. ( 4 ) The observed ‘aerobic glycolysis’ is often called the Warburg effect in various cancer types. This phenomenon was initially thought to result from dysfunctional mitochondria; however, it was later found that the Warburg effect occurs while the mitochondria remain fully functional. ( 5 ) Cells may choose this mechanism due to the faster ATP production by glycolysis compared to OXPHOS. ( 6 ) Also, many byproducts of glycolysis are necessary for the biosynthesis of other molecules required for cell division; thus, increased glycolysis supports faster growth rates observed in tumor cells. ( 7 ) Increased ‘aerobic glycolysis’ can be observed by increased glucose consumption and lactate production, contributing to extracellular acidification. This phenotype is often paired with expression changes in markers related to glycolysis and glucose catabolism, including, but not limited to, upregulation of glucose transporters (e.g., GLUT1), glycolysis initiator hexokinase II (HK2), and Lactate Dehydrogenase (LDHA). This is often accompanied by the downregulation of genes involved in OXPHOS. In this study, we measured Pyruvate Dehydrogenase (PDHA1) and mitochondrial ATP synthase F1 subunit alpha (ATP5A1), and ATP production was considered a measure of glucose metabolism. Breast cancer can be classified as one of four subtypes: Luminal A, Luminal B, HER2 enriched, and triple-negative (TNBC). This depends on the presence or absence of hormone receptors, including estrogen receptor (ER), progesterone receptor (PR), and the human epidermal growth factor receptor 2 (HER2). Breast cancer cell lines representing these subtypes have quite different growth rates. This manuscript will investigate how miR-526b alters glucose metabolism in two breast cancer cell lines: MCF7, a luminal A, ER+, PR + HER2- cell line, and SKBR3, a HER2 enriched cell line that is hormone receptor (ER/PR) negative. MCF7 has a balanced metabolism in normoxic conditions, but SKBR3 displays increased glycolytic activity with increased glucose consumption and extracellular acidification rates (ECAR). ( 8 ) miR-526b is shown to have an oncogenic effect in MCF7 and SKBR3 breast cancer cells. Overexpression of miR-526b promotes a metastatic phenotype, and COX-2 inhibitors and EP4 antagonists significantly reduced miRNA expression in aggressive breast cancer and abolished miRNA functions. ( 9 , 10 ) miR-526b overexpression also induced changes in the profile of secretory proteins, enhanced tumor-associated angiogenesis and lymphangiogenesis, and stimulated the secretion of growth factors and metabolites. When normal endothelial cells were treated with miRNA-high cell secretions, they showed pre-metastatic phenotypes. ( 9 , 11 ) The primary transcript of miR-526b (pri-miR-526b) can be detected in human blood plasma. It is a proven biomarker that can distinguish malignant tumor plasma from benign tumor plasma as early as stage I. ( 12 ) Overexpression of miR-526b in luminal A breast cancer cell lines showed an increased EMT, oxidative stress, and hypoxic response. We observed an increased upregulation of HIF1A in both hypoxic and normoxic conditions in miRNA-overexpressed cells. In human breast cancer tissues, HIF1A expression was positively correlated with miR-526b expression. ( 13 , 14 ). The significant upregulation of HIF1A by miR-526b stimulated our interest in the regulatory roles of miR-526b on cell metabolism. HIF1A is often associated with glycolysis, as it is typically seen upregulated in hypoxic environments, and glycolysis is active as an oxygen-independent form of ATP production. We hypothesize that the upregulation of HIF1A by miR-526b induces a similar promotion of glycolysis in normoxic conditions. The primary purpose of this study is to establish the role of miR-526b in glucose metabolism. II. Methods Cell culture Human breast cancer cell lines MCF7 and SKBR3 were purchased from the American Type Culture Collection (ATCC, Rockville, MD, USA). As previously described, miR-526b, COX2 overexpressing, and empty vector cell lines were established by transfection of plasmids. ( 10 ) Cells were cultured in RPMI 1640 (Gibco, ON, Canada), supplemented with 10% fetal bovine serum (VWR, ON, Canada) and 1% Pen-Strep. Cells were incubated at 37 degrees Celsius with 5% CO 2 . Transfected cells were maintained with 200ng/mL Geneticin (G418) (Biobasic, ON, Canada). Drugs and Reagents Glycolysis inhibitor 2 Deoxy-D-Glucose (2DG) (Millipore-Sigma, ON, Canada) was dissolved in 10% DMSO, and 10mM, 20mM, and 40mM were used during assays. OXPHOS inhibitor Oligomycin (Millipore-Sigma, ON, Canada) was dissolved in 100% DMSO, and 1µM, 2.5µM, and 5µM were used during assays. COX-2 inhibitor NS-398 (Cayman Chemical, Ann Arbor, MI, USA) was used at 20µM. EP4 antagonist CJ-042794 (RQ-15986) was a gift from RaQualia Pharma, Nagoya, Japan, and used at 5µM during assays. DMSO (Biobasic, ON, Canada) was used as the vehicle for drug treatment. RNA Extraction and Real-time qPCR RNA was extracted using Qiazol and mini-RNeasy kits (Qiagen, MD, USA). cDNA was synthesized using mRNA cDNA Reverse Transcription Kit (Applied Biosystems, MA, USA). For ΔCT calculations, ACTB (Hs01060665_g1) was used as a housekeeping gene. Other target genes include hsa-miR-526b (Hs03296227_pri), HK2 (Hs08606086_m1), LDHA (Hs01378790_g1), PDHA1 (Hs01049345_g1), GLUT1 (or SLC2A1) (Hs00892681_m1), ATP5A1 (Hs00900735_m1) and TIGAR (Hs00608644_m1). ΔCT, ΔΔCT, and Fold Changes were calculated using the Livak method. ( 15 ) SDS-PAGE/Western Blotting Cells were lysed with Cell Lysis Buffer (10X) (New England Biolabs, ON, Canada) with Halt Protease and Phosphatase Inhibitors (100X) (Thermo Scientific, MA, USA). 20µg protein was electrophoresed on 10% SDS-polyacrylamide gel and transferred onto a nitrocellulose membrane. Blots were incubated with anti-ACTB primary antibody (SantaCruz, TX, USA, Cat no. SC-47778) at 1:5000 dilution, and anti-TIGAR (Cell Signaling, MA, USA, Cat no. 14751s) or anti-ATP5A1 (SantaCruz. TX, USA, Cat no. SC-136178) primary antibody at 1:1000 dilution at 4 o C overnight. Blots were washed and incubated with Azurespectra 700 (Azure Biosystems, CA, USA, Cat no. AC2129) and Azurespectra 800 (Azure Biosystems, CA, USA, Cat no. AC2134) NIR-fluorescent secondary antibodies at 1:20000 dilution for 1 hour at room temperature. Dry membranes were imaged using Azure Sapphire Biomolecular Imager (Azure Biosystems, CA, USA) and analyzed using AzureSpot Pro software with Rolling ball background noise elimination and housekeeping gene normalization. Graphs illustrate fold change between cell lines according to Normalized volume. Glucose Consumption Roche AccuChek Guide glucose monitor (Roche, ON, Canada) was used to measure the glucose concentration of culture media at given time points. Corning CytoSmart cell counter (Corning, AZ, USA) was used to seed initial and count final cell numbers. The decrease in glucose concentration was recorded. The following equation was used to normalize glucose consumption per million cells: Gf is the final glucose concentration, Gi is the initial glucose concentration, V is the Volume of cell culture media, Ci is the initial cell number, and Cf is the final cell number. $$Glucose Consumption per million cells=\frac{\left[\left({G}_{f}-{G}_{i}\right)*V\right]}{\left[\right({C}_{i}+{C}_{f})/2]}*1 000 000$$ Extracellular Acidification Rate (ECAR) Assay ECAR assay kit was purchased from Abcam (Abcam, United Kingdom, Cat no. Ab197244). Seed 50k cells in a 96-well plate, allowing cells to grow overnight. Before the experiment, purge CO 2 for 3 hours at 37°C in a non-CO 2 incubator. Remove media, wash once with respiration buffer, and replace with 150µl respiration buffer. Add glycolysis assay reagent. In the plate reader set to 37°C, measure time-resolved (TR)-fluorescence every 90 seconds for a minimum of 2 hours. TR-F settings were 100us delay and 100us integration, Ex = 380 +/- 20nm, Em = 615 +/- 20nm. Oxygen Consumption Assay The oxygen consumption rate (OCR) assay kit was purchased from Abcam (Abcam, United Kingdom, Cat no. Ab197243). Seed 50k cells in a 96-well plate, allowing cells to grow overnight. Remove media and replace with 150µl fresh cell culture media. Add oxygen consumption reagent and promptly seal wells with mineral oil. Incubate at 37°C and measure TR-Fluorescence every 90 seconds for a minimum of 2 hours using a TECAN Spark Cyto plate reader (TECAN, Switzerland). TR-F settings were 30us delay and 100us integration, Ex = 380 +/- 20nm, Em = 650 +/- 20nm. LUCID RESIPHER Oxygen Consumption OCR was measured using Lucid Resipher (Lucid Sci, Atlanta, GA, USA). 10k cells were seeded into a 96-well plate with 100µl media and allowed to settle for approximately one hour. The adaptor lid and measurement device were attached. Continuous measurement occurred inside the incubator at 37°C and 5% CO 2 for over 48 hours. After the experiment, real-time OCR at 48 hours was calculated and normalized by average cell number to account for proliferation rates. ATP Determination 25k cells were seeded into a 96-well plate and allowed to attach for 6–8 hours in 100µl complete media (non-treated) or metabolic inhibitors diluted in basal media (treated). A Luminescent ATP Detection kit (Abcam, United Kingdom) was used. Reagents were added directly to wells without washing or removing media. ATP production was measured with the TECAN Spark Cyto plate reader. Cell Viability and Proliferation 50k cells were seeded into a 24-well plate and allowed to attach overnight. Complete media was replaced with basal media containing metabolic inhibitors (2-DG or Oligomycin) or vehicle (DMSO). After 24 hours, ReadyProbes live/dead Cell dye (Invitrogen, MA, USA) was added directly to the media, and fluorescent whole-well images were taken at 4x magnification and quantified using a TECAN Spark Cyto plate reader. Fluorescent images were also taken on Nikon Eclipse Ti-2 at 10x. Bioinformatics Microarray datasets (GSE45827) include 130 breast cancer tissue samples across all subtypes and 11 non-cancerous breast tissue samples. GSE45827 was obtained from NCBI Gene Expression Omnibus. Gene set enrichment analysis (GSEA) software version 4.3.2 was used to investigate gene set enrichment in the microarray dataset. ( 16 , 17 ) Fifty gene sets were analyzed from the MSigDB Hallmark collection (h.all.v2023.1.Hs.symbols.gmt). ( 18 , 19 ) Heatmaps for two gene sets were included in the manuscript: glycolysis and OXPHOS. Statistics Statistical analysis was performed using GraphPad Prism Software version 10.0.2 for Windows (GraphPad Software, MA, USA). Differences between the two datasets were examined using a student’s t-test, except for Fig. 6 F-H, where a paired t-test was used to determine the effect of inhibitors. Graphical representations were developed using GraphPad Prism Software version 10.0.2. III. Results Multiple metabolic pathways are enriched in Breast Cancer tissue. Gene expression analysis from breast cancer and non-cancerous breast tissue microarray data was curated from NCBI dataset GSE45827.( 20 ) GSEA, using this microarray data and the MSigDB Hallmark gene set collection, uncovered multiple gene sets that are significantly enriched (FDR < 25%) in breast cancer samples. Of these, metabolic gene sets for glycolysis, and OXPHOS (Supplementary Tables 1 and 2) are significantly enriched (FDR < 25%) in breast cancer samples (Fig. 1 A). The same gene sets also showed minor enrichment when comparing aggressive breast cancer subtypes (Luminal B, HER2+, TNBC) to Luminal A tumors (Fig. 1 B). This enrichment analysis illustrates that gene sets for glycolysis (Fig. 1 C) and OXPHOS (Fig. 1 D) have significantly different expression in breast cancer and normal tissues. This preliminary analysis shows that glucose metabolism is altered in the cancerous state by varying degrees based on the cancer subtype. miR-526b overexpression increases cell proliferation. MCF7 and SKBR3 breast cancer cell lines were transfected to overexpress miR-526b. ( 12 ) Relative to MCF7-Parental, MCF7-miR526b maintains overexpression of pri-miR-526b by, on average, 20.7-fold. SKBR3-miR526b shows a 1306-fold increase in pri-miR-526b expression relative to SKBR3-Mock (Fig. 2 A). These miRNA-high cells divide faster, and cell secretion turns media very acidic. Over 48 hours, MCF7-miR526b increased live cell number by 2.32-fold, while MCF7-Parental increased live cell number by only 1.40-fold over the same period. The same trend is seen in SKBR3, a cell line with a higher proliferation rate than MCF7. While SKBR3-MOCK increased cell number by 2.68-fold, SKBR3-miR526b increased live cell number by 3.99-fold over 48 hours (Fig. 2 B). miR-526b increases glucose metabolism. Overexpression of miRNA in the transfected cell lines upregulates glucose metabolism as observed in MCF7 and SKBR3 breast cancer cell lines. One metric used to determine overall metabolic activity is ATP production, as ATP is the fuel for many reactions in the cell. MCF7-miR526b cells were observed to have a 1.81-fold increase in ATP concentration compared to MCF7-Parental cells. SKBR3-miR526b cells had a 2.07-fold increase in ATP concentration compared to SKBR3-MOCK (Fig. 2 C). Thus, miR-526b overexpression moderately increases the ATP in cells. Next, glucose consumption was examined as glucose is one primary fuel for ATP synthesis. Glucose consumption was investigated by measuring the changes in glucose concentration in the cell culture media over time. For both MCF7 and SKBR3 cell lines, the miR-526b overexpressing line consumed significantly more glucose over 72 hours (Supplementary Fig. 1). Although we started with the same number of cells at t = 0hr, these cell lines have different proliferation rates; therefore, cell numbers must be considered over time. Glucose consumption per million cells was calculated to account for different proliferation rates. In general, the SKBR3 glucose consumption rate is higher than MCF7 cells. However, after considering differences in cell number, the overexpression of miR-526b did not increase glucose consumption significantly in either cell line (Fig. 2 D). miR-526b expression resulted in more glucose consumed by cells overall, but this was shown to be a result of the increased proliferation rates of miRNA-high cells. A decrease in extracellular pH often accompanies increased glycolytic metabolism. This is attributed to the increase in acidic byproducts of glucose metabolism, specifically lactate. We measured the culture media pH over 72 hours to see this effect. MCF7 showed the least changes in media pH (Δ = -0.2), but a significant reduction in pH was observed in MCF7-miR526b (Δ = -0.64). SKBR3-Mock cell media pH decreased by -0.56 over 48 hours, while SKBR3-miR526b showed a slightly more significant decrease (Δ = -0.76) (Supplementary Fig. 2). Because of the difference in cell proliferation rate, the increased acidification of the media could be due to cell division. To overcome this, a more sensitive method is used to monitor acidification in a reduced time frame. A fluorescent-based pH indicator is used, and over 2 hours, the extracellular acidification rate is calculated. In this case, the ECAR of MCF7-miR526b media is 0.42-fold less than MCF7-Parental. No significant differences were observed in the ECAR between SKBR3-MOCK and SKBR3-miR526b cells (Fig. 2 E). miR-526b increases extracellular acidification; however, this is due to increased cell proliferation, not on an individual cell basis. When proliferation is normalized, miR-526b decreases ECAR in the MCF7 cell line and does not affect the SKBR3 cell line. OXPHOS is an oxygen-dependent process; therefore, we can detect differences in OXPHOS between cell lines by measuring oxygen consumption. Increased oxygen consumption implies the cells utilize OXPHOS to synthesize ATP as O 2 is consumed in the electron transport chain. For MCF7 and SKBR3, miR-526b overexpressing cells consumed less oxygen (Fig. 2 F). The OCR was determined after interval measurements over 2 hours, limiting the effect of varying proliferation rates. A second OCR assay was performed over 48 hours. In this case, the real-time OCR at 48 hours was normalized to cell number by multiplying the initial cell number by the 48-hour proliferation rate identified in Fig. 2 B. This long-term assay also shows that miR-526b overexpression leads to decreased oxygen consumption in both MCF7 and SKBR3 cells (Supplementary Fig. 3). miR-526b dysregulates markers of aerobic glycolysis and glycolytic metabolism. A panel of mRNA markers for glucose metabolism, Glucose transporter 1 (GLUT1), Hexokinase 2 (HK2), and Lactate dehydrogenase (LDHA) were screened to evaluate glycolytic and aerobic glycolytic pathways. Pyruvate dehydrogenase (PDHA1) and F1-F0 ATP Synthase subunit F1 (ATP5A1) were used as a marker for aerobic respiration. TP53-induced glycolysis and apoptosis regulator (TIGAR) were screened as potential targets of miR-526b that are involved in glycolytic regulation, as predicted by TargetScan V8.0 (Supplementary Table 3).( 21 , 22 ) An increase in expression of LDHA (2.31-fold) and PDHA1 (4.21-fold) was observed in MCF7-miR526b compared to MCF7-Parental, which naturally has a balanced metabolism (Fig. 3 A). Other minor changes were observed in MCF7-miR526b, for example, HK2 (0.84-fold), ATP5A1 (1.31-fold), and TIGAR (1.45-fold). In contrast, SKBR3, which natively is more glycolytic than MCF7, shows notable differences. SKBR3-miR526b showed a decrease in glycolysis markers HK2 (0.38-fold) and GLUT1 (0.31-fold) compared to SKBR3-Mock. Also, marginal reductions in LDHA (0.79-fold) and ATP5A1(0.45) (Fig. 3 B) were recorded. The differences observed in the two cell lines show how miR-526b can increase metabolic efficiency in diverse ways based on the cell's native metabolism. Protein expression was measured for the predicted miR-526b target TIGAR and ATP synthase subunit ATP5A1 (full western blots in Supplementary Figs. 4–6). TIGAR protein was upregulated in MCF7-miR526b and SKBR3-miR526b (Fig. 3 C-D). ATP5A1 protein expression was unchanged in MCF7-miR526b and significantly downregulated in SKBR3-miR526b. This indicates that miR-526b might be involved in aerobic glucose metabolism and energy production in breast cancer. The effect of glycolysis inhibition on MCF7, SKBR3, and miR-526b overexpressed cell lines. The sensitivity to specific metabolic inhibitors is examined to better understand the changes in metabolic profile. By targeting or inhibiting glycolysis using 2-deoxy-d-glucose (2-DG), we can evaluate metabolic plasticity or the cell’s ability to adapt to continue to meet high energy demands and survive. To examine the impact of this inhibition, relative ATP concentration, cell viability, and proliferation are measured. When exposed to 2-DG treatment, SKBR3-MOCK cells showed a more significant decrease in ATP than MCF7-Parental. This is expected as SKBR3 is more glycolytic; therefore, the inhibition of glycolysis would impact ATP yield. Both MCF7-miR526b and SKBR3-miR526b were less affected by 2-DG treatment than their miR-low counterparts (Fig. 4 A), indicating miR-526b might help cells switch between glucose metabolism pathways. Cell viability is the proportion of live cells following treatment. After glycolysis inhibition by 2-DG, all cell lines had high viability, although overexpression of miR-526b increased viability marginally in both MCF7 and SKBR3 cell lines (Fig. 4 B). Viability illustrates cell death, yet the differences in total live cells after treatment stood out. To quantify how the drugs are affecting cell proliferation, the number of live cells following treatment is compared to the number of live cells following a vehicle control treatment over the same time. This better illustrates the inhibitors' effect on cell growth and division rate when the treatment is not causing cell death. For both cell lines, the 2-DG treatment has less impact on live cell count in the miR-526b overexpressed lines. Therefore, with miR562b overexpression, the cells were less affected by 2-DG treatment and better-maintained proliferation (Fig. 4 C). The fluorescent images (Fig. 4 D-G) show both viability and proliferation. In the miRNA-overexpressed cell lines, there are more live cells (blue) and fewer dead cells (red). This indicates that miRNA-overexpressed cells can more effectively overcome glycolysis inhibition. The effect of OXPHOS inhibition on MCF7, SKBR3, and miR-526b overexpressing cell lines. OXPHOS is inhibited using Oligomycin, which blocks mitochondrial ATP synthesis. To examine the impact of this inhibition, relative ATP concentration and cell viability/proliferation is measured. When exposed to Oligomycin treatment, all cell lines showed a slight increase in ATP production, with no significant differences identified between cell lines or miR-526b status. An increase in ATP is expected as the cancer cells can adapt and produce ATP, often in higher yields under hypoxic conditions. The inhibition of OXPHOS mirrors hypoxic conditions in that both prevent cell respiration and the electron transport chain. ATP was decreased with the combination treatment, where cells were exposed to glycolysis and OXPHOS inhibitors. Cell lines with high miR-526b maintained ATP production better in this case. (Fig. 5 A). After OXPHOS inhibition by oligomycin, overall cell viability remained high. MCF7-miR526b showed slightly better viability (97.3%, 91.4%) than MCF7-Parental (88.6%, 85.6%). The opposite was true for SKBR3. SKBR3-miR526b showed decreased viability (96.5%, 89.7%) compared to SK-MOCK (98.6%, 93.5%) (Fig. 5 B). Also, MCF7 showed the same result regarding cell proliferation. MCF7-miR526b cells showed higher proliferation (0.83, 0.72) than MCF7-Parental (0.72, 0.59). SKBR3 cells showed the same result; SKBR3-miR526 b cells (0.92, 0.81) showed higher proliferation in response to oligomycin than SKBR3-MOCK cells (0.77, 0.73) (Fig. 5 C). This indicates the miR-high cells better maintain their growth after OXPHOS inhibition, but this is less sustainable in SKBR3-miR526b cells as there is a higher proportion of cell death. The fluorescent images (Fig. 5 D-G) show both viability and proliferation. In the MCF7 miRNA-overexpressed cell lines, there are more live cells (blue) and fewer red cells (dead). For SKBR3, there are more live (blue) cells and dead (red) cells in the miR-high treated conditions. So, miR-526b overexpression in MCF7 and SKBR3 cell lines enhances the metabolic plasticity of breast cancer cells by maintaining cell proliferation. COX2, EP4, and miR-526b contribute to metabolic dysregulation We discovered that miR-526b was upregulated in Cyclooxygenase-2 (COX2) overexpressing breast cancer cells, and many oncogenic functions of miR-526b could be abolished with a COX-2 inhibitor. COX2 is part of an inflammatory pathway that results in the production of Prostaglandin E2 (PGE2), which binds to G-protein-coupled receptors (GPCR) EP1, EP2, EP3, and EP4, each having different cellular localizations and downstream signal transductions.( 23 , 24 ) COX-2 upregulates miR-526b via the EP4 signaling pathway, and miR526 b-induced functions can be disrupted with the use of NS398, a COX-2-specific inhibitor, and CJ047, an EP4-specific antagonist (Supplementary Fig. 7).( 10 ) COX-2 is the master regulator of miR-526b. MCF7-COX2 cell line shows upregulation of miR-526b with an average increase in pri-miR-526b of 32.0-fold compared to MCF7-Parental (Fig. 6 A). MCF7-COX2 shows an increased proliferation rate like that observed with miR-526b overexpression. ( 25 ) MCF7-COX2 cell number increased by 2.87-fold over 48 hours, while MCF7-Parental only increased cell number by 1.4-fold (Fig. 6 B). MCF7-COX2 showed transcriptomic changes similar to MCF7-miR526b regarding RNA expression of metabolic markers. Compared to MCF7-Parental, MCF7-COX2 showed marginal downregulations in glycolytic markers HK2 (0.75-fold), GLUT1 (0.84-fold) and LDHA (0.76-fold). Genes associated with OXPHOS were upregulated: PDHA1 (2.93-fold) and ATP5A1 (14.0-fold). TIGAR gene expression was also marginally upregulated in MCF7-COX2 cells (1.59-fold) (Fig. 6 C). TIGAR and ATP5A1 protein expression was significantly upregulated in MCF7-COX2 cells compared to MCF7 (Supplementary Fig. 6). TIGAR showed 2.45-fold upregulation, and ATP5A1 showed 3.37-fold upregulation compared to MCF7-Parental cell line expression (Fig. 6 D, E). miR-526b expression and function can be inhibited with COX2 inhibitor and EP4 antagonist treatment. Following the norm of miR-526b function, 48-hour treatment with COX2 inhibitors and EP4 antagonist reduces the expression of pri-miR-526b by 0.64-fold and 0.36-fold, respectively, in MCF7-COX2 cells (Fig. 6 F). Similarly, this treatment also decreases cell proliferation. The relative proliferation rate in COX2-i treated cells is 0.74 relative to vehicle control treatment. MCF7-COX2 cells treated with EP4A show a proliferation rate of 0.93 relative to vehicle treatment (Fig. 6 G). Interestingly, the observed miR-526b regulation of metabolic markers can be reversed with COX2 inhibitor and EP4 antagonist treatment. LDHA, PDHA1, and ATP5A1 gene expression are reduced in MCF7-COX2 cells following treatment with COX2-i and EP4A (Fig. 6 H). Therefore, treatment with a COX2 inhibitor and EP4 antagonist inhibits miR-526b expression and reverses miRNA-induced glucose metabolism. IV. Discussion It is well known fact that cell metabolism is altered and plays a critical role in cancer biology; our preliminary findings support this, showing more aggressive cancer cells require more energy to sustain their growth. Genes associated with glycolysis and OXPHOS are enriched in breast cancer tissues compared to normal tissues. It was also observed that these gene sets are further enriched in more aggressive breast cancer subtypes, compared to the most common subtype, Luminal A breast cancer. The strongest gene set enrichment was observed when comparing normal tissue and unstratified tumors. Luminal A is the most common subtype of breast cancer diagnosed (40%), and HER2-enriched tumors account for approximately 20% of all breast cancer diagnoses. Here, we investigated the roles of miRNA in glucose metabolism for these two subtypes of tumors. Deciphering the mechanisms in which miRNA promotes dysregulation of glucose metabolism may uncover potential therapeutic targets for breast cancer and identify biomarkers to monitor the reprogramming of cancer cell metabolism. Previously, we reported that miR-526b overexpressed in MCF7 (luminal A) and SKBR3 (HER2 enriched) cells promotes aggressive phenotypes and increases cell proliferation and survival under stressful conditions. MiR-526b overexpression enhanced hypoxia responses, including HIF1a expression in tumor cells and increased expression of VEGFA and COX-2 to enhance tumor-associated angiogenesis and lymphangiogenesis. ( 9 , 14 ) Under severe oxidative stress conditions, miR-526b and secretory pri-miR-526b helped BRCA cells to survive and proliferate. ( 13 , 26 ) Finally, we discovered markers linked with cell metabolism, such as ATP5A1 , TXNDC12 , and SFN , in the miRNA-high tumor cell secretion. ( 11 ) Therefore, miR-526b could be linked with increased cellular metabolism and might be a key regulator of metabolic plasticity in breast cancer to sustain growth and survival. We conducted this research to understand how miR-526b promotes glucose metabolism and metabolic flexibility and how these processes fit within the complex and heterogeneous tumor microenvironment. Dysregulation of metabolic pathways often seen in cancer becomes increasingly challenging to investigate due to the involvement of various extracellular factors. For example, cancer cell metabolism is altered when co-cultured with cancer-associated fibroblasts (CAFs), which increases metabolic efficiency. ( 27 ) This study presents a novel approach to understanding the tumor microenvironment. By showing the impact of miR-526b on cell metabolism, we observed a significant increase in miR-526b expression. This led to a cascade of effects, including increased cell proliferation rate, glucose breakdown, acidification, and ATP production. We also measured the gene and protein expression of key markers of glucose metabolism in miRNA overexpressed cells, identifying significant changes in HK2, ATP5A1, TIGAR, LDHA, and PDHA expression, which indicates an alteration in glucose metabolism. We found high TIGAR gene and protein expression in miR-526b overexpressed cells. We previously reported that miR-526b targets and downregulates CPEB2 , a tumor suppressor gene that transiently alters TP53 expression in breast cancer. ( 28 ) Further investigation of the miR-526b gene target revealed that TP53-induced glycolysis and apoptotic regulator (TIGAR) is a predicted target of this miRNA. The primary enzymatic function of TIGAR leads to a negative regulation of glycolysis, promoting the pentose phosphate pathway (PPP). ( 29 ) However, further investigation into TIGAR's secondary functions revealed its potential roles in metabolic dysregulation in miRNA-overexpressed cells. Enzymatically, TIGAR regulates the conversion of fructose − 2,6-bisphosphate to fructose-6-phosphate, inhibiting PFK-1 activity and promoting the PPP pathway. ( 29 ) This would benefit the growing cancer cells as PPP promotes antioxidant and DNA damage repair pathways. ( 29 , 30 ) Additionally, in the presence of excess HIF1a, as seen in miR-526b high cells, TIGAR is translocated to the mitochondria, stimulating HK2 activity, a rate-limiting step in glycolysis. ( 31 ) This explains our observed downregulation of HK2 expression but upregulation of ATP production in miRNA overexpressed cells. Our findings shed light on the intricate role miR-526b plays in the metabolic reprogramming observed in breast cancer progression, working as a metabolic switch to alter glucose metabolism in response to stress and cellular needs. Therefore, overexpression of miR-526b will impact cells differently based on their native metabolic tendencies. In general, miR-526b will make cells more resilient or plastic in situations of stress. In response to inhibitors of glycolysis or OXPHOS, miR-526b overexpressing cells were less affected compared to parental and miRNA-low cells. In the context of a growing tumor, high miR-526b cells showed higher proliferation rates and gain in metabolic plasticity, making tumors more suitable to survive in a heterogeneous environment. In areas of low oxygen or glucose, cells would better adapt their mechanisms of ATP production, aiding growth, and aggressive tumor progression. Previously, we reported that miR-526b helps tumor cells survive and grow in hypoxic conditions, promoting angiogenesis and lymphangiogenesis, which rely heavily on metabolic plasticity to meet the energy needs in a stressful environment. ( 9 , 14 ) We first identified miR-526b with a high-throughput analysis of MCF7-COX2 and MCF7 cell lines. We have also shown that miR-526b overexpression in a positive feedback loop enhances COX-2 expression by MCF7 and SKBR3 cells.( 10 ) Also, miRNA-induced functions are regulated by COX-2/EP4/pI3K/Akt signaling pathways and can be rescinded after inhibition of COX-2 and antagonizing EP4.( 9 , 10 , 14 , 25 ) It was reported that COX-2 expression is regulated by glycosylation, and high glucose level enhances COX-2 expression. ( 32 , 33 ) Here, we observed COX-2-overexpressing cells showing high pri-miR-526b expression, increased cell proliferation rate, and stimulated ATP production, supporting cell growth. We observed an upregulation of PDHA1, ATP5A1, and TIGAR in miR-526b overexpressed cells. With a selective COX-2 inhibitor and EP4 antagonist, we found a significant downregulation of pri-miR-526b, PDHA1, ATP5A1, and TIGAR expression. This confirms the involvement of COX-2/EP4/miR-526b in the glucose metabolism and maintenance of metabolic plasticity in breast cancer. V. Conclusion Here, we show novel functions of miR-526b in regulating glucose metabolism and promoting metabolic plasticity. This allows cells to switch between OXPHOS and glycolysis in response to stress, maintaining ATP production as required by aggressive tumor cells. This research also demonstrates the therapeutic potential of exploring the miR-526b/COX2/EP4 pathway for controlling tumor growth. Abbreviations BRCA: Breast cancer OXPHOS: Oxidative phosphorylation TNBC: Triple-negative breast cancer ECAR: Extracellular acidification rate OCR: Oxygen consumption rate 2-DG: 2-deoxy-d-glucose GSEA: Gene set enrichment analysis GLUT1: Glucose transporter I HK2: Hexokinase II LDHA: Lactate dehydrogenase A PDHA1: Pyruvate dehydrogenase E1 subunit alpha 1 ATP5A1: ATP synthase F1 subunit alpha TIGAR: TP53 induces glycolysis and apoptosis regulator ACTB: Actin beta COX2: Cyclooxygenase 2 Declarations Acknowledgments We appreciate Prof. Peeyush K Lala's generosity in sharing the COX-2 inhibitor NS-398 and Takayuki Maruyama from Ono Pharmaceutical, Osaka, Japan, in sharing the ONO-AE3-208. Authors’ contributions BN conducted all experiments, generated data, performed data analysis, made figures, and wrote the first draft; MM contributed to funding acquisition, supervision, and manuscript writing and editing. Funding This work is supported by Breast Cancer Canada, the Lotte, and John Hecht Memorial Foundation Grants to M.M. This study is also supported by the Canada Research Chair Program (CRCP), the Canada Foundation for Innovation (CFI), and Research Manitoba Matching fundings to M.M. B.N. received Research Manitoba MSc scholarships and the CIHR MSc scholarships. Availability of data and materials All data generated in this study are available within the article, its supplemental information, or from the corresponding author upon reasonable request. The Brandon University Ethical Approval Committee (approval # 23056) and the Brandon University Biosafety Committee (approval # 2020-BIO-02) approve this study. Consent for publication Not applicable Competing interests The authors declare no conflict of interest. References Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. 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Glycosylation regulates turnover of cyclooxygenase-2. FEBS Lett [Internet]. 2006 Dec 11 [cited 2024 May 16];580(28–29):6533–6. Available from: https://onlinelibrary.wiley.com/doi/full/10.1016/j.febslet.2006.10.073 Shanmugam N, Gonzalo ITG, Natarajan R. Molecular mechanisms of high glucose-induced cyclooxygenase-2 expression in monocytes. Diabetes [Internet]. 2004 Mar [cited 2024 May 16];53(3):795–802. Available from: https://pubmed.ncbi.nlm.nih.gov/14988266/ Additional Declarations No competing interests reported. Supplementary Files SupplementaryFig1jpeg.jpg Supplementary Figure 1: Glucose concentration of cell culture media measured over 72 hours. The initial cell number for all cell lines was 100 thousand cells. SupplementaryFig2jpeg.jpg Supplementary Figure 2: Extracellular acidification, pH of cell culture media measured over 48 hours. The initial cell number for all cell lines was 1 million cells. SupplementaryFig3jpeg.jpg Supplementary Figure 3: Oxygen consumption rate (OCR) measured using Lucid Resipher, long-term/open system. SupplementaryFig4MCF7ATP5A1ACTB.tif Supplementary Figure 4. NIR-Fluorescence western blot image. Red channel: ACTB (43 K) Green channel: ATP5A1 (55 K). Lane 1: Molecular weight marker. Lanes 2-4: MCF7-Parental. Lanes 5-7: MCF7-526b. Lane 8: Molecular weight marker. SupplementaryFig5SKBRATP5A1ACTB.tif Supplementary Figure 5: NIR-Fluorescence western blot image. Red channel: ACTB (43 K) Green channel: ATP5A1 (55 K). Lane 1: Molecular weight marker. Lanes 2-4: SKBR3-Mock. Lane 5: Molecular weight marker. Lanes 6-8: SKBR3-526b. SupplementaryFig6BRCAATP5A1ACTBTIGAR.tif Supplementary Figure 6: NIR-Fluorescence western blot image. Red channel: ACTB (43 K), Green channel: ATP5A1 (55 K), TIGAR (28 K). Lane 1: Molecular weight marker. Lanes 2-3: MCF7-Parental. Lane 4: MCF7-526b. Lane 5: MCF7-COX2. Lanes 6-7: SKBR3-Mock. Lane 8: SKBR3-526b. Lane 9: MDA-MB-231. Lane 10: Molecular weight marker. SupplementaryFig7jpeg.jpg Supplementary Figure 7: Arachidonic acid pathway involving COX2 and EP4 can be inhibited using COX2 inhibitor (NS-398) or EP4 antagonist (CJ047). SupplementaryTable1.docx Supplementary Table 1: Metabolic gene set analysis for glycolysis SupplementaryTable2.docx Supplementary Table 2: Metabolic gene set analysis for OxPhos SupplementaryTable3.docx Supplementary Table 3: TargetScan v8.0 identified C12orf5 (TIGAR) as a potential target of has-mir-526b-5p. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4510975","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":311804942,"identity":"678bb1c3-53ae-43a9-a440-1b979e781ea2","order_by":0,"name":"Braydon D Nault","email":"","orcid":"","institution":"Brandon University","correspondingAuthor":false,"prefix":"","firstName":"Braydon","middleName":"D","lastName":"Nault","suffix":""},{"id":311804943,"identity":"9a5b088d-580f-4b4f-8c62-5f481d365de8","order_by":1,"name":"Mousumi Majumder","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYHCCBAYGNiDF3gPiMJOihecM8VoYIFokcojUott+4JnUjTKbfN2Zb499+LnDWs5cIoHxww88WszOJKRJ55xLs9x2Oy95Zu+ZdGPLGQnMkj34tBwAasltO2xgdjvHmIG37XDihhsJbAw8+LScfwDS8t/A7OYZY8a/UC2Mf/BpuQG25YCB2Q0eY2aYLcx4bbnxINk651yygdmZvGRm2bZ0Y4MzD5ulZfA6LCfxdk6ZnYHZ8bOHGd+2WcsZHE8++PENHi3AKExAF2FswKsBmFAOEFAwCkbBKBgFIx4AAEOdT+n970bFAAAAAElFTkSuQmCC","orcid":"","institution":"Brandon University","correspondingAuthor":true,"prefix":"","firstName":"Mousumi","middleName":"","lastName":"Majumder","suffix":""}],"badges":[],"createdAt":"2024-05-31 20:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4510975/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4510975/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58037588,"identity":"7b9d5e9e-6bb9-44b6-a528-d4bd732cd149","added_by":"auto","created_at":"2024-06-10 09:33:43","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1161829,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGlucose metabolism is enriched in breast cancer\u003c/strong\u003e. GSEA analysis identifies enriched gene sets in (A) breast cancer tissues vs. normal tissues and (B) Luminal B, HER2 enriched, and TNBC vs. Luminal A breast cancer tissues. Gene expression heatmaps for (C) glycolysis and (D) OXPHOS gene sets.\u003c/p\u003e","description":"","filename":"Figure1jpeg.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/5e0b3b5078cfcf3fa5ec9ad0.jpg"},{"id":58037586,"identity":"98485acb-1a17-4fd5-91f8-3d042b337466","added_by":"auto","created_at":"2024-06-10 09:33:43","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":453434,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverexpression of miR-526b increases glycolytic metabolism\u003c/strong\u003e. pri-miR-526b expression is measured by RT-qPCR to validate overexpression in transfected cell lines MCF7-miR526b and SKBR3-miR526b (A). Relative ATP concentration is measured by luminescence (C). Change in media glucose concentration is normalized to cell number to achieve glucose consumption per million cells (D). The extracellular media's pH change is measured over 2 hours using a fluorescent indicator (E). The oxygen consumption rate per million cells is measured, and %change is measured between the miR-high transfected and parental cell lines (F). *p\u0026lt;0.05, **p\u0026lt;0.01, ****p\u0026lt;0.0001.\u003c/p\u003e","description":"","filename":"Figure2jpeg.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/bd108de3eec2f7f4e81d601b.jpg"},{"id":58039231,"identity":"93bd480e-be0c-4c47-be56-4cecbd54d09f","added_by":"auto","created_at":"2024-06-10 09:49:43","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":470785,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMetabolic marker expression in MCF7 and SKBR3 cell lines\u003c/strong\u003e. Marker gene expression in MCF7 and MCF7-miR526b transfected cell Line (A), and SKBR3 and SKBR3-miR526b transfected cell line (B). Western blot images for TIGAR (i) and ATP5A1 (ii) protein expression (C) and corresponding densitometry analysis for n=4 (MCF7) and n=3 (SKBR3) (D). *p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"Figure3jpeg.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/89104e298d51d7b3833cf73c.jpg"},{"id":58037592,"identity":"106f05b5-91ca-44ef-ad9f-5dbbf2b1ad65","added_by":"auto","created_at":"2024-06-10 09:33:43","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":979369,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of glycolysis inhibitor 2-DG on MCF7 and SKBR3 cell lines\u003c/strong\u003e. Relative ATP concentration following treatment with 2-DG (A). Cell viability (B) and proliferation (C) following treatment. Fluorescent images of all cell lines post-treatment, visualized with live (blue) and dead (red) cell stain (D-G). Images compare vehicle treatment (i) with 2-DG treatment (ii). The scale bar indicates 100uM.\u003c/p\u003e","description":"","filename":"Figure4jpeg.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/17e0bf22e4b47a406644eeb8.jpg"},{"id":58037591,"identity":"9d7da5fa-87f7-49ed-b2b1-068913e401d1","added_by":"auto","created_at":"2024-06-10 09:33:43","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":946399,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of OXPHOS inhibitor Oligomycin on MCF7 and SKBR3 cell lines\u003c/strong\u003e. Relative ATP concentration following treatment with oligomycin (A). Cell viability (B) and proliferation (C) following treatment. Fluorescent images of all cell lines post-treatment, visualized with live (blue) and dead (red) cell stain (D-G). Images compare vehicle treatment (i) with 2-DG treatment (ii). The scale bar indicates 100uM.\u003c/p\u003e","description":"","filename":"Figure5jpeg.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/971e929d01ac89dcaa21a29c.jpg"},{"id":58037599,"identity":"02533f31-7517-4cc9-b647-73ac0b8aeffb","added_by":"auto","created_at":"2024-06-10 09:33:44","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":687260,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCOX2 induces similar metabolic effects as miR-526b and can be reversed using COX2 and EP4 inhibitors\u003c/strong\u003e. Pri-miR-526b expression following COX2 overexpression (A). Proliferation rates over 48hrs (B). RNA expression of metabolic markers in COX2 overexpressed cells (C). Protein expression of chosen metabolic markers shown in western blot (D) and densitometry analysis of blots (E). Pri-miR-526b expression following treatment with OCX2 and EP4 inhibitors (F). 48hr proliferation rates following treatment with COX2 and EP4 inhibitors (G). RNA expression of chosen markers following treatment with OCX2 and EP4 inhibitors (H). *p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"Figure6jpeg.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/ddf2106dd105e61fb0347c91.jpg"},{"id":58039695,"identity":"a4a55b42-2d64-4015-ae41-f5a664168f6a","added_by":"auto","created_at":"2024-06-10 09:57:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5182302,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/4a1592fb-de22-4a28-bb88-f2774bfedfa1.pdf"},{"id":58037589,"identity":"25a48b06-ce13-44e2-96f9-9683c9dd3c25","added_by":"auto","created_at":"2024-06-10 09:33:43","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":72694,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure 1: Glucose concentration of cell culture media measured over 72 hours. The initial cell number for all cell lines was 100 thousand cells.\u003c/p\u003e","description":"","filename":"SupplementaryFig1jpeg.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/8d8d2e5206fb08386fe9f87e.jpg"},{"id":58037590,"identity":"b1e47a34-06f5-4351-a970-670e86cfe867","added_by":"auto","created_at":"2024-06-10 09:33:43","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":110687,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure 2: Extracellular acidification, pH of cell culture media measured over 48 hours. The initial cell number for all cell lines was 1 million cells.\u003c/p\u003e","description":"","filename":"SupplementaryFig2jpeg.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/f748b772d9efa7b0ad2d0b19.jpg"},{"id":58037595,"identity":"2272d8d4-7c7b-4ad8-ab40-faf45befc024","added_by":"auto","created_at":"2024-06-10 09:33:44","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":69107,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure 3: Oxygen consumption rate (OCR) measured using Lucid Resipher, long-term/open system.\u003c/p\u003e","description":"","filename":"SupplementaryFig3jpeg.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/70ab522a01ba98cec8a84f19.jpg"},{"id":58039232,"identity":"9f35fbf5-552f-4f94-b9f5-7f3572a13031","added_by":"auto","created_at":"2024-06-10 09:49:44","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":1952796,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure 4. NIR-Fluorescence western blot image. Red channel: ACTB (43 K) Green channel: ATP5A1 (55 K). Lane 1: Molecular weight marker. Lanes 2-4: MCF7-Parental. Lanes 5-7: MCF7-526b. Lane 8: Molecular weight marker.\u003c/p\u003e","description":"","filename":"SupplementaryFig4MCF7ATP5A1ACTB.tif","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/59170179869288cb5913ba89.tif"},{"id":58039233,"identity":"9e1c0f14-53e0-43df-b8d7-b32061e5bfc5","added_by":"auto","created_at":"2024-06-10 09:49:44","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":2115360,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure 5: NIR-Fluorescence western blot image. Red channel: ACTB (43 K) Green channel: ATP5A1 (55 K). Lane 1: Molecular weight marker. Lanes 2-4: SKBR3-Mock. Lane 5: Molecular weight marker. Lanes 6-8: SKBR3-526b.\u003c/p\u003e","description":"","filename":"SupplementaryFig5SKBRATP5A1ACTB.tif","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/96c89811043e0b8fa9878b82.tif"},{"id":58037602,"identity":"95d9d0e5-e40f-4130-bc5d-cc12d1d3c428","added_by":"auto","created_at":"2024-06-10 09:33:44","extension":"tif","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":3723020,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure 6: NIR-Fluorescence western blot image. Red channel: ACTB (43 K), Green channel: ATP5A1 (55 K), TIGAR (28 K). Lane 1: Molecular weight marker. Lanes 2-3: MCF7-Parental. Lane 4: MCF7-526b. Lane 5: MCF7-COX2. Lanes 6-7: SKBR3-Mock. Lane 8: SKBR3-526b. Lane 9: MDA-MB-231. Lane 10: Molecular weight marker.\u003c/p\u003e","description":"","filename":"SupplementaryFig6BRCAATP5A1ACTBTIGAR.tif","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/f92ff499f47f79aeb5d9142e.tif"},{"id":58037593,"identity":"6e278e37-edae-4c23-b1b6-9ea099a25691","added_by":"auto","created_at":"2024-06-10 09:33:43","extension":"jpg","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":247001,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure 7: Arachidonic acid pathway involving COX2 and EP4 can be inhibited using COX2 inhibitor (NS-398) or EP4 antagonist (CJ047).\u003c/p\u003e","description":"","filename":"SupplementaryFig7jpeg.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/f1bafde9edf3cc6ac461ba0a.jpg"},{"id":58038155,"identity":"91fde536-0b61-4516-ab21-e55e7a1882af","added_by":"auto","created_at":"2024-06-10 09:41:46","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":16682,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 1: Metabolic gene set analysis for glycolysis\u003c/p\u003e","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/94147519cfd34d0f1ba6e630.docx"},{"id":58037597,"identity":"0d133b0a-3a0f-4699-8f51-1dbf18485f57","added_by":"auto","created_at":"2024-06-10 09:33:44","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":16609,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 2: Metabolic gene set analysis for OxPhos\u003c/p\u003e","description":"","filename":"SupplementaryTable2.docx","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/8d60b55e6df247c0e2741b9d.docx"},{"id":58038149,"identity":"701ff7df-f51f-41a0-ae40-ace48d3ce5e5","added_by":"auto","created_at":"2024-06-10 09:41:44","extension":"docx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":19390,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 3: TargetScan v8.0 identified C12orf5 (TIGAR) as a potential target of has-mir-526b-5p.\u003c/p\u003e","description":"","filename":"SupplementaryTable3.docx","url":"https://assets-eu.researchsquare.com/files/rs-4510975/v1/349d98920883b5d70587f983.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"miR-526b dysregulates glucose metabolism via the COX2/EP4 pathway","fulltext":[{"header":"I. Introduction","content":"\u003cp\u003eBreast cancer continues to have a devastating impact on the global population. In 2022, the most recent international data available, breast cancer was the second most-diagnosed cancer in the world, the most diagnosed among females (24.7% of female cancer diagnoses), and the deadliest cancer among females (16.1% of female cancer deaths) accounting for 666 103 deaths.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Currently, routine screening is recommended to begin at age 50 in Canada. However, 21% of breast cancer deaths are reported in the younger population.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Current research focuses on developing liquid biopsy screening techniques to improve overall survival with early detection. Another focus is targeted therapy options that improve patient outcomes, using personalized medicine to predict the best result based on an individual\u0026rsquo;s cancer characteristics. One of the hallmark phenotypes observed in cancer cells is alterations in metabolism.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Understanding these metabolic abnormalities in various subtypes of breast cancer can lead to the development of new therapeutic targets and treatment options. The commitment to developing liquid biopsy screening for breast cancer will improve early detection as well as quality of life through a personalized medicine approach.\u003c/p\u003e \u003cp\u003eOtto Warburg was the first to identify the increased consumption of glucose seen in cancer cells. A selective shift to the glycolytic production of ATP in the presence of oxygen, counter to oxidative phosphorylation (OXPHOS), is reported in cancer cells. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) The observed \u0026lsquo;aerobic glycolysis\u0026rsquo; is often called the Warburg effect in various cancer types. This phenomenon was initially thought to result from dysfunctional mitochondria; however, it was later found that the Warburg effect occurs while the mitochondria remain fully functional. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Cells may choose this mechanism due to the faster ATP production by glycolysis compared to OXPHOS. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) Also, many byproducts of glycolysis are necessary for the biosynthesis of other molecules required for cell division; thus, increased glycolysis supports faster growth rates observed in tumor cells. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) Increased \u0026lsquo;aerobic glycolysis\u0026rsquo; can be observed by increased glucose consumption and lactate production, contributing to extracellular acidification. This phenotype is often paired with expression changes in markers related to glycolysis and glucose catabolism, including, but not limited to, upregulation of glucose transporters (e.g., GLUT1), glycolysis initiator hexokinase II (HK2), and Lactate Dehydrogenase (LDHA). This is often accompanied by the downregulation of genes involved in OXPHOS. In this study, we measured Pyruvate Dehydrogenase (PDHA1) and mitochondrial ATP synthase F1 subunit alpha (ATP5A1), and ATP production was considered a measure of glucose metabolism.\u003c/p\u003e \u003cp\u003eBreast cancer can be classified as one of four subtypes: Luminal A, Luminal B, HER2 enriched, and triple-negative (TNBC). This depends on the presence or absence of hormone receptors, including estrogen receptor (ER), progesterone receptor (PR), and the human epidermal growth factor receptor 2 (HER2). Breast cancer cell lines representing these subtypes have quite different growth rates. This manuscript will investigate how miR-526b alters glucose metabolism in two breast cancer cell lines: MCF7, a luminal A, ER+, PR\u0026thinsp;+\u0026thinsp;HER2- cell line, and SKBR3, a HER2 enriched cell line that is hormone receptor (ER/PR) negative. MCF7 has a balanced metabolism in normoxic conditions, but SKBR3 displays increased glycolytic activity with increased glucose consumption and extracellular acidification rates (ECAR). (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u003c/p\u003e \u003cp\u003emiR-526b is shown to have an oncogenic effect in MCF7 and SKBR3 breast cancer cells. Overexpression of miR-526b promotes a metastatic phenotype, and COX-2 inhibitors and EP4 antagonists significantly reduced miRNA expression in aggressive breast cancer and abolished miRNA functions. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) miR-526b overexpression also induced changes in the profile of secretory proteins, enhanced tumor-associated angiogenesis and lymphangiogenesis, and stimulated the secretion of growth factors and metabolites. When normal endothelial cells were treated with miRNA-high cell secretions, they showed pre-metastatic phenotypes. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) The primary transcript of miR-526b (pri-miR-526b) can be detected in human blood plasma. It is a proven biomarker that can distinguish malignant tumor plasma from benign tumor plasma as early as stage I. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) Overexpression of miR-526b in luminal A breast cancer cell lines showed an increased EMT, oxidative stress, and hypoxic response. We observed an increased upregulation of HIF1A in both hypoxic and normoxic conditions in miRNA-overexpressed cells. In human breast cancer tissues, HIF1A expression was positively correlated with miR-526b expression. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The significant upregulation of HIF1A by miR-526b stimulated our interest in the regulatory roles of miR-526b on cell metabolism. HIF1A is often associated with glycolysis, as it is typically seen upregulated in hypoxic environments, and glycolysis is active as an oxygen-independent form of ATP production. We hypothesize that the upregulation of HIF1A by miR-526b induces a similar promotion of glycolysis in normoxic conditions. The primary purpose of this study is to establish the role of miR-526b in glucose metabolism.\u003c/p\u003e"},{"header":"II. Methods","content":"\u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eCell culture\u003c/span\u003e \u003c/p\u003e \u003cp\u003eHuman breast cancer cell lines MCF7 and SKBR3 were purchased from the American Type Culture Collection (ATCC, Rockville, MD, USA). As previously described, miR-526b, COX2 overexpressing, and empty vector cell lines were established by transfection of plasmids. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) Cells were cultured in RPMI 1640 (Gibco, ON, Canada), supplemented with 10% fetal bovine serum (VWR, ON, Canada) and 1% Pen-Strep. Cells were incubated at 37 degrees Celsius with 5% CO\u003csub\u003e2\u003c/sub\u003e. Transfected cells were maintained with 200ng/mL Geneticin (G418) (Biobasic, ON, Canada).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eDrugs and Reagents\u003c/span\u003e \u003c/p\u003e \u003cp\u003eGlycolysis inhibitor 2 Deoxy-D-Glucose (2DG) (Millipore-Sigma, ON, Canada) was dissolved in 10% DMSO, and 10mM, 20mM, and 40mM were used during assays. OXPHOS inhibitor Oligomycin (Millipore-Sigma, ON, Canada) was dissolved in 100% DMSO, and 1\u0026micro;M, 2.5\u0026micro;M, and 5\u0026micro;M were used during assays. COX-2 inhibitor NS-398 (Cayman Chemical, Ann Arbor, MI, USA) was used at 20\u0026micro;M. EP4 antagonist CJ-042794 (RQ-15986) was a gift from RaQualia Pharma, Nagoya, Japan, and used at 5\u0026micro;M during assays. DMSO (Biobasic, ON, Canada) was used as the vehicle for drug treatment.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eRNA Extraction and Real-time qPCR\u003c/span\u003e \u003c/p\u003e \u003cp\u003eRNA was extracted using Qiazol and mini-RNeasy kits (Qiagen, MD, USA). cDNA was synthesized using mRNA cDNA Reverse Transcription Kit (Applied Biosystems, MA, USA). For ΔCT calculations, ACTB (Hs01060665_g1) was used as a housekeeping gene. Other target genes include hsa-miR-526b (Hs03296227_pri), HK2 (Hs08606086_m1), LDHA (Hs01378790_g1), PDHA1 (Hs01049345_g1), GLUT1 (or SLC2A1) (Hs00892681_m1), ATP5A1 (Hs00900735_m1) and TIGAR (Hs00608644_m1). ΔCT, ΔΔCT, and Fold Changes were calculated using the Livak method. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSDS-PAGE/Western Blotting\u003c/span\u003e \u003c/p\u003e \u003cp\u003eCells were lysed with Cell Lysis Buffer (10X) (New England Biolabs, ON, Canada) with Halt Protease and Phosphatase Inhibitors (100X) (Thermo Scientific, MA, USA). 20\u0026micro;g protein was electrophoresed on 10% SDS-polyacrylamide gel and transferred onto a nitrocellulose membrane. Blots were incubated with anti-ACTB primary antibody (SantaCruz, TX, USA, Cat no. SC-47778) at 1:5000 dilution, and anti-TIGAR (Cell Signaling, MA, USA, Cat no. 14751s) or anti-ATP5A1 (SantaCruz. TX, USA, Cat no. SC-136178) primary antibody at 1:1000 dilution at 4\u003csup\u003eo\u003c/sup\u003eC overnight. Blots were washed and incubated with Azurespectra 700 (Azure Biosystems, CA, USA, Cat no. AC2129) and Azurespectra 800 (Azure Biosystems, CA, USA, Cat no. AC2134) NIR-fluorescent secondary antibodies at 1:20000 dilution for 1 hour at room temperature. Dry membranes were imaged using Azure Sapphire Biomolecular Imager (Azure Biosystems, CA, USA) and analyzed using AzureSpot Pro software with \u003cem\u003eRolling ball\u003c/em\u003e background noise elimination and housekeeping gene normalization. Graphs illustrate fold change between cell lines according to Normalized volume.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eGlucose Consumption\u003c/span\u003e \u003c/p\u003e \u003cp\u003eRoche AccuChek Guide glucose monitor (Roche, ON, Canada) was used to measure the glucose concentration of culture media at given time points. Corning CytoSmart cell counter (Corning, AZ, USA) was used to seed initial and count final cell numbers. The decrease in glucose concentration was recorded. The following equation was used to normalize glucose consumption per million cells: \u003cem\u003eGf\u003c/em\u003e is the final glucose concentration, \u003cem\u003eGi\u003c/em\u003e is the initial glucose concentration, \u003cem\u003eV\u003c/em\u003e is the Volume of cell culture media, \u003cem\u003eCi\u003c/em\u003e is the initial cell number, and \u003cem\u003eCf\u003c/em\u003e is the final cell number.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$Glucose Consumption per million cells=\\frac{\\left[\\left({G}_{f}-{G}_{i}\\right)*V\\right]}{\\left[\\right({C}_{i}+{C}_{f})/2]}*1 000 000$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eExtracellular Acidification Rate (ECAR) Assay\u003c/span\u003e \u003c/p\u003e \u003cp\u003eECAR assay kit was purchased from Abcam (Abcam, United Kingdom, Cat no. Ab197244). Seed 50k cells in a 96-well plate, allowing cells to grow overnight. Before the experiment, purge CO\u003csub\u003e2\u003c/sub\u003e for 3 hours at 37\u0026deg;C in a non-CO\u003csub\u003e2\u003c/sub\u003e incubator. Remove media, wash once with respiration buffer, and replace with 150\u0026micro;l respiration buffer. Add glycolysis assay reagent. In the plate reader set to 37\u0026deg;C, measure time-resolved (TR)-fluorescence every 90 seconds for a minimum of 2 hours. TR-F settings were 100us delay and 100us integration, Ex\u0026thinsp;=\u0026thinsp;380 +/- 20nm, Em\u0026thinsp;=\u0026thinsp;615 +/- 20nm.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eOxygen Consumption Assay\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe oxygen consumption rate (OCR) assay kit was purchased from Abcam (Abcam, United Kingdom, Cat no. Ab197243). Seed 50k cells in a 96-well plate, allowing cells to grow overnight. Remove media and replace with 150\u0026micro;l fresh cell culture media. Add oxygen consumption reagent and promptly seal wells with mineral oil. Incubate at 37\u0026deg;C and measure TR-Fluorescence every 90 seconds for a minimum of 2 hours using a TECAN Spark Cyto plate reader (TECAN, Switzerland). TR-F settings were 30us delay and 100us integration, Ex\u0026thinsp;=\u0026thinsp;380 +/- 20nm, Em\u0026thinsp;=\u0026thinsp;650 +/- 20nm.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eLUCID RESIPHER Oxygen Consumption\u003c/span\u003e \u003c/p\u003e \u003cp\u003eOCR was measured using Lucid Resipher (Lucid Sci, Atlanta, GA, USA). 10k cells were seeded into a 96-well plate with 100\u0026micro;l media and allowed to settle for approximately one hour. The adaptor lid and measurement device were attached. Continuous measurement occurred inside the incubator at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e for over 48 hours. After the experiment, real-time OCR at 48 hours was calculated and normalized by average cell number to account for proliferation rates.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATP Determination\u003c/span\u003e \u003c/p\u003e \u003cp\u003e25k cells were seeded into a 96-well plate and allowed to attach for 6\u0026ndash;8 hours in 100\u0026micro;l complete media (non-treated) or metabolic inhibitors diluted in basal media (treated). A Luminescent ATP Detection kit (Abcam, United Kingdom) was used. Reagents were added directly to wells without washing or removing media. ATP production was measured with the TECAN Spark Cyto plate reader.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eCell Viability and Proliferation\u003c/span\u003e \u003c/p\u003e \u003cp\u003e50k cells were seeded into a 24-well plate and allowed to attach overnight. Complete media was replaced with basal media containing metabolic inhibitors (2-DG or Oligomycin) or vehicle (DMSO). After 24 hours, ReadyProbes live/dead Cell dye (Invitrogen, MA, USA) was added directly to the media, and fluorescent whole-well images were taken at 4x magnification and quantified using a TECAN Spark Cyto plate reader. Fluorescent images were also taken on Nikon Eclipse Ti-2 at 10x.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eBioinformatics\u003c/span\u003e \u003c/p\u003e \u003cp\u003eMicroarray datasets (GSE45827) include 130 breast cancer tissue samples across all subtypes and 11 non-cancerous breast tissue samples. GSE45827 was obtained from NCBI Gene Expression Omnibus. Gene set enrichment analysis (GSEA) software version 4.3.2 was used to investigate gene set enrichment in the microarray dataset. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) Fifty gene sets were analyzed from the MSigDB Hallmark collection (h.all.v2023.1.Hs.symbols.gmt). (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) Heatmaps for two gene sets were included in the manuscript: glycolysis and OXPHOS.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eStatistics\u003c/span\u003e \u003c/p\u003e \u003cp\u003eStatistical analysis was performed using GraphPad Prism Software version 10.0.2 for Windows (GraphPad Software, MA, USA). Differences between the two datasets were examined using a student\u0026rsquo;s t-test, except for Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e6\u003c/span\u003eF-H, where a paired t-test was used to determine the effect of inhibitors. Graphical representations were developed using GraphPad Prism Software version 10.0.2.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"III. Results","content":"\u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMultiple metabolic pathways are enriched in Breast Cancer tissue.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eGene expression analysis from breast cancer and non-cancerous breast tissue microarray data was curated from NCBI dataset GSE45827.(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) GSEA, using this microarray data and the MSigDB Hallmark gene set collection, uncovered multiple gene sets that are significantly enriched (FDR\u0026thinsp;\u0026lt;\u0026thinsp;25%) in breast cancer samples. Of these, metabolic gene sets for glycolysis, and OXPHOS (Supplementary Tables\u0026nbsp;1 and 2) are significantly enriched (FDR\u0026thinsp;\u0026lt;\u0026thinsp;25%) in breast cancer samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The same gene sets also showed minor enrichment when comparing aggressive breast cancer subtypes (Luminal B, HER2+, TNBC) to Luminal A tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). This enrichment analysis illustrates that gene sets for glycolysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eC) and OXPHOS (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) have significantly different expression in breast cancer and normal tissues. This preliminary analysis shows that glucose metabolism is altered in the cancerous state by varying degrees based on the cancer subtype.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003emiR-526b overexpression increases cell proliferation.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eMCF7 and SKBR3 breast cancer cell lines were transfected to overexpress miR-526b. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) Relative to MCF7-Parental, MCF7-miR526b maintains overexpression of pri-miR-526b by, on average, 20.7-fold. SKBR3-miR526b shows a 1306-fold increase in pri-miR-526b expression relative to SKBR3-Mock (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). These miRNA-high cells divide faster, and cell secretion turns media very acidic. Over 48 hours, MCF7-miR526b increased live cell number by 2.32-fold, while MCF7-Parental increased live cell number by only 1.40-fold over the same period. The same trend is seen in SKBR3, a cell line with a higher proliferation rate than MCF7. While SKBR3-MOCK increased cell number by 2.68-fold, SKBR3-miR526b increased live cell number by 3.99-fold over 48 hours (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003emiR-526b increases glucose metabolism.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eOverexpression of miRNA in the transfected cell lines upregulates glucose metabolism as observed in MCF7 and SKBR3 breast cancer cell lines. One metric used to determine overall metabolic activity is ATP production, as ATP is the fuel for many reactions in the cell. MCF7-miR526b cells were observed to have a 1.81-fold increase in ATP concentration compared to MCF7-Parental cells. SKBR3-miR526b cells had a 2.07-fold increase in ATP concentration compared to SKBR3-MOCK (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Thus, miR-526b overexpression moderately increases the ATP in cells.\u003c/p\u003e \u003cp\u003eNext, glucose consumption was examined as glucose is one primary fuel for ATP synthesis. Glucose consumption was investigated by measuring the changes in glucose concentration in the cell culture media over time. For both MCF7 and SKBR3 cell lines, the miR-526b overexpressing line consumed significantly more glucose over 72 hours (Supplementary Fig.\u0026nbsp;1). Although we started with the same number of cells at t\u0026thinsp;=\u0026thinsp;0hr, these cell lines have different proliferation rates; therefore, cell numbers must be considered over time. Glucose consumption per million cells was calculated to account for different proliferation rates. In general, the SKBR3 glucose consumption rate is higher than MCF7 cells. However, after considering differences in cell number, the overexpression of miR-526b did not increase glucose consumption significantly in either cell line (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). miR-526b expression resulted in more glucose consumed by cells overall, but this was shown to be a result of the increased proliferation rates of miRNA-high cells.\u003c/p\u003e \u003cp\u003eA decrease in extracellular pH often accompanies increased glycolytic metabolism. This is attributed to the increase in acidic byproducts of glucose metabolism, specifically lactate. We measured the culture media pH over 72 hours to see this effect. MCF7 showed the least changes in media pH (Δ = -0.2), but a significant reduction in pH was observed in MCF7-miR526b (Δ = -0.64). SKBR3-Mock cell media pH decreased by -0.56 over 48 hours, while SKBR3-miR526b showed a slightly more significant decrease (Δ = -0.76) (Supplementary Fig.\u0026nbsp;2). Because of the difference in cell proliferation rate, the increased acidification of the media could be due to cell division. To overcome this, a more sensitive method is used to monitor acidification in a reduced time frame. A fluorescent-based pH indicator is used, and over 2 hours, the extracellular acidification rate is calculated. In this case, the ECAR of MCF7-miR526b media is 0.42-fold less than MCF7-Parental. No significant differences were observed in the ECAR between SKBR3-MOCK and SKBR3-miR526b cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). miR-526b increases extracellular acidification; however, this is due to increased cell proliferation, not on an individual cell basis. When proliferation is normalized, miR-526b decreases ECAR in the MCF7 cell line and does not affect the SKBR3 cell line.\u003c/p\u003e \u003cp\u003eOXPHOS is an oxygen-dependent process; therefore, we can detect differences in OXPHOS between cell lines by measuring oxygen consumption. Increased oxygen consumption implies the cells utilize OXPHOS to synthesize ATP as O\u003csub\u003e2\u003c/sub\u003e is consumed in the electron transport chain. For MCF7 and SKBR3, miR-526b overexpressing cells consumed less oxygen (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). The OCR was determined after interval measurements over 2 hours, limiting the effect of varying proliferation rates. A second OCR assay was performed over 48 hours. In this case, the real-time OCR at 48 hours was normalized to cell number by multiplying the initial cell number by the 48-hour proliferation rate identified in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eB. This long-term assay also shows that miR-526b overexpression leads to decreased oxygen consumption in both MCF7 and SKBR3 cells (Supplementary Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003emiR-526b dysregulates markers of aerobic glycolysis and glycolytic metabolism.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eA panel of mRNA markers for glucose metabolism, Glucose transporter 1 (GLUT1), Hexokinase 2 (HK2), and Lactate dehydrogenase (LDHA) were screened to evaluate glycolytic and aerobic glycolytic pathways. Pyruvate dehydrogenase (PDHA1) and F1-F0 ATP Synthase subunit F1 (ATP5A1) were used as a marker for aerobic respiration. TP53-induced glycolysis and apoptosis regulator (TIGAR) were screened as potential targets of miR-526b that are involved in glycolytic regulation, as predicted by TargetScan V8.0 (Supplementary Table\u0026nbsp;3).(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) An increase in expression of LDHA (2.31-fold) and PDHA1 (4.21-fold) was observed in MCF7-miR526b compared to MCF7-Parental, which naturally has a balanced metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Other minor changes were observed in MCF7-miR526b, for example, HK2 (0.84-fold), ATP5A1 (1.31-fold), and TIGAR (1.45-fold). In contrast, SKBR3, which natively is more glycolytic than MCF7, shows notable differences. SKBR3-miR526b showed a decrease in glycolysis markers HK2 (0.38-fold) and GLUT1 (0.31-fold) compared to SKBR3-Mock. Also, marginal reductions in LDHA (0.79-fold) and ATP5A1(0.45) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) were recorded. The differences observed in the two cell lines show how miR-526b can increase metabolic efficiency in diverse ways based on the cell's native metabolism.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eProtein expression was measured for the predicted miR-526b target TIGAR and ATP synthase subunit ATP5A1 (full western blots in Supplementary Figs.\u0026nbsp;4\u0026ndash;6). TIGAR protein was upregulated in MCF7-miR526b and SKBR3-miR526b (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D). ATP5A1 protein expression was unchanged in MCF7-miR526b and significantly downregulated in SKBR3-miR526b. This indicates that miR-526b might be involved in aerobic glucose metabolism and energy production in breast cancer.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eThe effect of glycolysis inhibition on MCF7, SKBR3, and miR-526b overexpressed cell lines.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe sensitivity to specific metabolic inhibitors is examined to better understand the changes in metabolic profile. By targeting or inhibiting glycolysis using 2-deoxy-d-glucose (2-DG), we can evaluate metabolic plasticity or the cell\u0026rsquo;s ability to adapt to continue to meet high energy demands and survive. To examine the impact of this inhibition, relative ATP concentration, cell viability, and proliferation are measured. When exposed to 2-DG treatment, SKBR3-MOCK cells showed a more significant decrease in ATP than MCF7-Parental. This is expected as SKBR3 is more glycolytic; therefore, the inhibition of glycolysis would impact ATP yield. Both MCF7-miR526b and SKBR3-miR526b were less affected by 2-DG treatment than their miR-low counterparts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), indicating miR-526b might help cells switch between glucose metabolism pathways.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCell viability is the proportion of live cells following treatment. After glycolysis inhibition by 2-DG, all cell lines had high viability, although overexpression of miR-526b increased viability marginally in both MCF7 and SKBR3 cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Viability illustrates cell death, yet the differences in total live cells after treatment stood out. To quantify how the drugs are affecting cell proliferation, the number of live cells following treatment is compared to the number of live cells following a vehicle control treatment over the same time. This better illustrates the inhibitors' effect on cell growth and division rate when the treatment is not causing cell death. For both cell lines, the 2-DG treatment has less impact on live cell count in the miR-526b overexpressed lines. Therefore, with miR562b overexpression, the cells were less affected by 2-DG treatment and better-maintained proliferation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). The fluorescent images (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eD-G) show both viability and proliferation. In the miRNA-overexpressed cell lines, there are more live cells (blue) and fewer dead cells (red). This indicates that miRNA-overexpressed cells can more effectively overcome glycolysis inhibition.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eThe effect of OXPHOS inhibition on MCF7, SKBR3, and miR-526b overexpressing cell lines.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eOXPHOS is inhibited using Oligomycin, which blocks mitochondrial ATP synthesis. To examine the impact of this inhibition, relative ATP concentration and cell viability/proliferation is measured. When exposed to Oligomycin treatment, all cell lines showed a slight increase in ATP production, with no significant differences identified between cell lines or miR-526b status. An increase in ATP is expected as the cancer cells can adapt and produce ATP, often in higher yields under hypoxic conditions. The inhibition of OXPHOS mirrors hypoxic conditions in that both prevent cell respiration and the electron transport chain. ATP was decreased with the combination treatment, where cells were exposed to glycolysis and OXPHOS inhibitors. Cell lines with high miR-526b maintained ATP production better in this case. (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAfter OXPHOS inhibition by oligomycin, overall cell viability remained high. MCF7-miR526b showed slightly better viability (97.3%, 91.4%) than MCF7-Parental (88.6%, 85.6%). The opposite was true for SKBR3. SKBR3-miR526b showed decreased viability (96.5%, 89.7%) compared to SK-MOCK (98.6%, 93.5%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Also, MCF7 showed the same result regarding cell proliferation. MCF7-miR526b cells showed higher proliferation (0.83, 0.72) than MCF7-Parental (0.72, 0.59). SKBR3 cells showed the same result; SKBR3-miR526 b cells (0.92, 0.81) showed higher proliferation in response to oligomycin than SKBR3-MOCK cells (0.77, 0.73) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). This indicates the miR-high cells better maintain their growth after OXPHOS inhibition, but this is less sustainable in SKBR3-miR526b cells as there is a higher proportion of cell death.\u003c/p\u003e \u003cp\u003eThe fluorescent images (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eD-G) show both viability and proliferation. In the MCF7 miRNA-overexpressed cell lines, there are more live cells (blue) and fewer red cells (dead). For SKBR3, there are more live (blue) cells and dead (red) cells in the miR-high treated conditions. So, miR-526b overexpression in MCF7 and SKBR3 cell lines enhances the metabolic plasticity of breast cancer cells by maintaining cell proliferation.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eCOX2, EP4, and miR-526b contribute to metabolic dysregulation\u003c/span\u003e \u003c/p\u003e \u003cp\u003eWe discovered that miR-526b was upregulated in Cyclooxygenase-2 (COX2) overexpressing breast cancer cells, and many oncogenic functions of miR-526b could be abolished with a COX-2 inhibitor. COX2 is part of an inflammatory pathway that results in the production of Prostaglandin E2 (PGE2), which binds to G-protein-coupled receptors (GPCR) EP1, EP2, EP3, and EP4, each having different cellular localizations and downstream signal transductions.(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) COX-2 upregulates miR-526b via the EP4 signaling pathway, and miR526 b-induced functions can be disrupted with the use of NS398, a COX-2-specific inhibitor, and CJ047, an EP4-specific antagonist (Supplementary Fig.\u0026nbsp;7).(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) COX-2 is the master regulator of miR-526b.\u003c/p\u003e \u003cp\u003eMCF7-COX2 cell line shows upregulation of miR-526b with an average increase in pri-miR-526b of 32.0-fold compared to MCF7-Parental (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). MCF7-COX2 shows an increased proliferation rate like that observed with miR-526b overexpression. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) MCF7-COX2 cell number increased by 2.87-fold over 48 hours, while MCF7-Parental only increased cell number by 1.4-fold (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). MCF7-COX2 showed transcriptomic changes similar to MCF7-miR526b regarding RNA expression of metabolic markers. Compared to MCF7-Parental, MCF7-COX2 showed marginal downregulations in glycolytic markers HK2 (0.75-fold), \u003cem\u003eGLUT1\u003c/em\u003e (0.84-fold) and \u003cem\u003eLDHA\u003c/em\u003e (0.76-fold). Genes associated with OXPHOS were upregulated: \u003cem\u003ePDHA1\u003c/em\u003e (2.93-fold) and \u003cem\u003eATP5A1\u003c/em\u003e (14.0-fold). \u003cem\u003eTIGAR\u003c/em\u003e gene expression was also marginally upregulated in MCF7-COX2 cells (1.59-fold) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). TIGAR and ATP5A1 protein expression was significantly upregulated in MCF7-COX2 cells compared to MCF7 (Supplementary Fig.\u0026nbsp;6). TIGAR showed 2.45-fold upregulation, and ATP5A1 showed 3.37-fold upregulation compared to MCF7-Parental cell line expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e6\u003c/span\u003eD, E).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003emiR-526b expression and function can be inhibited with COX2 inhibitor and EP4 antagonist treatment.\u003c/span\u003e \u003c/p\u003e \u003cp\u003eFollowing the norm of miR-526b function, 48-hour treatment with COX2 inhibitors and EP4 antagonist reduces the expression of pri-miR-526b by 0.64-fold and 0.36-fold, respectively, in MCF7-COX2 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). Similarly, this treatment also decreases cell proliferation. The relative proliferation rate in COX2-i treated cells is 0.74 relative to vehicle control treatment. MCF7-COX2 cells treated with EP4A show a proliferation rate of 0.93 relative to vehicle treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e6\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003eInterestingly, the observed miR-526b regulation of metabolic markers can be reversed with COX2 inhibitor and EP4 antagonist treatment. LDHA, PDHA1, and ATP5A1 gene expression are reduced in MCF7-COX2 cells following treatment with COX2-i and EP4A (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e6\u003c/span\u003eH). Therefore, treatment with a COX2 inhibitor and EP4 antagonist inhibits miR-526b expression and reverses miRNA-induced glucose metabolism.\u003c/p\u003e"},{"header":"IV. Discussion","content":"\u003cp\u003eIt is well known fact that cell metabolism is altered and plays a critical role in cancer biology; our preliminary findings support this, showing more aggressive cancer cells require more energy to sustain their growth. Genes associated with glycolysis and OXPHOS are enriched in breast cancer tissues compared to normal tissues. It was also observed that these gene sets are further enriched in more aggressive breast cancer subtypes, compared to the most common subtype, Luminal A breast cancer. The strongest gene set enrichment was observed when comparing normal tissue and unstratified tumors. Luminal A is the most common subtype of breast cancer diagnosed (40%), and HER2-enriched tumors account for approximately 20% of all breast cancer diagnoses. Here, we investigated the roles of miRNA in glucose metabolism for these two subtypes of tumors. Deciphering the mechanisms in which miRNA promotes dysregulation of glucose metabolism may uncover potential therapeutic targets for breast cancer and identify biomarkers to monitor the reprogramming of cancer cell metabolism. Previously, we reported that miR-526b overexpressed in MCF7 (luminal A) and SKBR3 (HER2 enriched) cells promotes aggressive phenotypes and increases cell proliferation and survival under stressful conditions. MiR-526b overexpression enhanced hypoxia responses, including HIF1a expression in tumor cells and increased expression of VEGFA and COX-2 to enhance tumor-associated angiogenesis and lymphangiogenesis. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) Under severe oxidative stress conditions, miR-526b and secretory pri-miR-526b helped BRCA cells to survive and proliferate. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) Finally, we discovered markers linked with cell metabolism, such as \u003cem\u003eATP5A1\u003c/em\u003e, \u003cem\u003eTXNDC12\u003c/em\u003e, and \u003cem\u003eSFN\u003c/em\u003e, in the miRNA-high tumor cell secretion. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) Therefore, miR-526b could be linked with increased cellular metabolism and might be a key regulator of metabolic plasticity in breast cancer to sustain growth and survival. We conducted this research to understand how miR-526b promotes glucose metabolism and metabolic flexibility and how these processes fit within the complex and heterogeneous tumor microenvironment.\u003c/p\u003e \u003cp\u003eDysregulation of metabolic pathways often seen in cancer becomes increasingly challenging to investigate due to the involvement of various extracellular factors. For example, cancer cell metabolism is altered when co-cultured with cancer-associated fibroblasts (CAFs), which increases metabolic efficiency. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) This study presents a novel approach to understanding the tumor microenvironment. By showing the impact of miR-526b on cell metabolism, we observed a significant increase in miR-526b expression. This led to a cascade of effects, including increased cell proliferation rate, glucose breakdown, acidification, and ATP production. We also measured the gene and protein expression of key markers of glucose metabolism in miRNA overexpressed cells, identifying significant changes in HK2, ATP5A1, TIGAR, LDHA, and PDHA expression, which indicates an alteration in glucose metabolism.\u003c/p\u003e \u003cp\u003eWe found high TIGAR gene and protein expression in miR-526b overexpressed cells. We previously reported that miR-526b targets and downregulates \u003cem\u003eCPEB2\u003c/em\u003e, a tumor suppressor gene that transiently alters TP53 expression in breast cancer. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) Further investigation of the miR-526b gene target revealed that TP53-induced glycolysis and apoptotic regulator (TIGAR) is a predicted target of this miRNA. The primary enzymatic function of TIGAR leads to a negative regulation of glycolysis, promoting the pentose phosphate pathway (PPP). (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) However, further investigation into TIGAR's secondary functions revealed its potential roles in metabolic dysregulation in miRNA-overexpressed cells. Enzymatically, TIGAR regulates the conversion of fructose \u0026minus;\u0026thinsp;2,6-bisphosphate to fructose-6-phosphate, inhibiting PFK-1 activity and promoting the PPP pathway. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) This would benefit the growing cancer cells as PPP promotes antioxidant and DNA damage repair pathways. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) Additionally, in the presence of excess HIF1a, as seen in miR-526b high cells, TIGAR is translocated to the mitochondria, stimulating HK2 activity, a rate-limiting step in glycolysis. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) This explains our observed downregulation of HK2 expression but upregulation of ATP production in miRNA overexpressed cells.\u003c/p\u003e \u003cp\u003eOur findings shed light on the intricate role miR-526b plays in the metabolic reprogramming observed in breast cancer progression, working as a metabolic switch to alter glucose metabolism in response to stress and cellular needs. Therefore, overexpression of miR-526b will impact cells differently based on their native metabolic tendencies. In general, miR-526b will make cells more resilient or plastic in situations of stress. In response to inhibitors of glycolysis or OXPHOS, miR-526b overexpressing cells were less affected compared to parental and miRNA-low cells. In the context of a growing tumor, high miR-526b cells showed higher proliferation rates and gain in metabolic plasticity, making tumors more suitable to survive in a heterogeneous environment. In areas of low oxygen or glucose, cells would better adapt their mechanisms of ATP production, aiding growth, and aggressive tumor progression. Previously, we reported that miR-526b helps tumor cells survive and grow in hypoxic conditions, promoting angiogenesis and lymphangiogenesis, which rely heavily on metabolic plasticity to meet the energy needs in a stressful environment. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eWe first identified miR-526b with a high-throughput analysis of MCF7-COX2 and MCF7 cell lines. We have also shown that miR-526b overexpression in a positive feedback loop enhances COX-2 expression by MCF7 and SKBR3 cells.(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) Also, miRNA-induced functions are regulated by COX-2/EP4/pI3K/Akt signaling pathways and can be rescinded after inhibition of COX-2 and antagonizing EP4.(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) It was reported that COX-2 expression is regulated by glycosylation, and high glucose level enhances COX-2 expression. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) Here, we observed COX-2-overexpressing cells showing high pri-miR-526b expression, increased cell proliferation rate, and stimulated ATP production, supporting cell growth. We observed an upregulation of PDHA1, ATP5A1, and TIGAR in miR-526b overexpressed cells. With a selective COX-2 inhibitor and EP4 antagonist, we found a significant downregulation of pri-miR-526b, PDHA1, ATP5A1, and TIGAR expression. This confirms the involvement of COX-2/EP4/miR-526b in the glucose metabolism and maintenance of metabolic plasticity in breast cancer.\u003c/p\u003e"},{"header":"V. Conclusion","content":"\u003cp\u003eHere, we show novel functions of miR-526b in regulating glucose metabolism and promoting metabolic plasticity. This allows cells to switch between OXPHOS and glycolysis in response to stress, maintaining ATP production as required by aggressive tumor cells. This research also demonstrates the therapeutic potential of exploring the miR-526b/COX2/EP4 pathway for controlling tumor growth.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBRCA: Breast cancer\u003c/p\u003e\n\u003cp\u003eOXPHOS: Oxidative phosphorylation\u003c/p\u003e\n\u003cp\u003eTNBC: Triple-negative breast cancer\u003c/p\u003e\n\u003cp\u003eECAR: Extracellular acidification rate\u003c/p\u003e\n\u003cp\u003eOCR: Oxygen consumption rate\u003c/p\u003e\n\u003cp\u003e2-DG: 2-deoxy-d-glucose\u003c/p\u003e\n\u003cp\u003eGSEA: Gene set enrichment analysis\u003c/p\u003e\n\u003cp\u003eGLUT1: Glucose transporter I\u003c/p\u003e\n\u003cp\u003eHK2: Hexokinase II\u003c/p\u003e\n\u003cp\u003eLDHA: Lactate dehydrogenase A\u003c/p\u003e\n\u003cp\u003ePDHA1: Pyruvate dehydrogenase E1 subunit alpha 1\u003c/p\u003e\n\u003cp\u003eATP5A1: ATP synthase F1 subunit alpha\u003c/p\u003e\n\u003cp\u003eTIGAR: TP53 induces glycolysis and apoptosis regulator\u003c/p\u003e\n\u003cp\u003eACTB: Actin beta\u003c/p\u003e\n\u003cp\u003eCOX2: Cyclooxygenase 2\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe appreciate Prof. Peeyush K Lala\u0026apos;s generosity in sharing the COX-2 inhibitor NS-398 and Takayuki Maruyama from Ono Pharmaceutical, Osaka, Japan, in sharing the ONO-AE3-208.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBN conducted all experiments, generated data, performed data analysis, made figures, and wrote the first draft; MM contributed to funding acquisition, supervision, and manuscript writing and editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is supported by Breast Cancer Canada, the Lotte, and John Hecht Memorial Foundation Grants to M.M. This study is also supported by the Canada Research Chair Program (CRCP), the Canada Foundation for Innovation (CFI), and Research Manitoba Matching fundings to M.M. B.N. received Research Manitoba MSc scholarships and the CIHR MSc scholarships.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Availability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated in this study are available within the article, its supplemental information, or from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003eThe Brandon University Ethical Approval Committee (approval # 23056) and the Brandon University Biosafety Committee (approval # 2020-BIO-02) approve this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. 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Available from: https://pubmed.ncbi.nlm.nih.gov/37128318/\u003c/li\u003e\n \u003cli\u003eMajumder M, Ugwuagbo KC, Maiti S, Lala PK, Brackstone M. Pri-miR526b and Pri-miR655 Are Potential Blood Biomarkers for Breast Cancer. Cancers (Basel) [Internet]. 2021 Aug 1 [cited 2022 Jun 6];13(15). Available from: https://pubmed.ncbi.nlm.nih.gov/34359739/\u003c/li\u003e\n \u003cli\u003eShin B, Feser R, Nault B, Hunter S, Maiti S, Ugwuagbo KC, et al. miR526b and miR655 Induce Oxidative Stress in Breast Cancer. Int J Mol Sci [Internet]. 2019 Aug 2 [cited 2022 Jun 6];20(16). Available from: https://pubmed.ncbi.nlm.nih.gov/31430859/\u003c/li\u003e\n \u003cli\u003eGervin E, Shin B, Opperman R, Cullen M, Feser R, Maiti S, et al. Chemically Induced Hypoxia Enhances miRNA Functions in Breast Cancer. Cancers (Basel) [Internet]. 2020 Aug 1 [cited 2023 May 11];12(8):1\u0026ndash;36. Available from: https://pubmed.ncbi.nlm.nih.gov/32707933/\u003c/li\u003e\n \u003cli\u003eLivak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods [Internet]. 2001 [cited 2023 Aug 1];25(4):402\u0026ndash;8. Available from: https://pubmed.ncbi.nlm.nih.gov/11846609/\u003c/li\u003e\n \u003cli\u003eMootha VK, Lindgren CM, Eriksson KF, Subramanian A, Sihag S, Lehar J, et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet [Internet]. 2003 Jul 1 [cited 2023 Aug 2];34(3):267\u0026ndash;73. Available from: https://pubmed.ncbi.nlm.nih.gov/12808457/\u003c/li\u003e\n \u003cli\u003eSubramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A [Internet]. 2005 Oct 25 [cited 2023 Aug 2];102(43):15545\u0026ndash;50. Available from: https://pubmed.ncbi.nlm.nih.gov/16199517/\u003c/li\u003e\n \u003cli\u003eLiberzon A, Subramanian A, Pinchback R, Thorvaldsd\u0026oacute;ttir H, Tamayo P, Mesirov JP. Molecular signatures database (MSigDB) 3.0. Bioinformatics. 2011 Jun;27(12):1739\u0026ndash;40.\u003c/li\u003e\n \u003cli\u003eLiberzon A, Birger C, Thorvaldsd\u0026oacute;ttir H, Ghandi M, Mesirov JP, Tamayo P. The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst [Internet]. 2015 Dec 23 [cited 2023 Aug 2];1(6):417\u0026ndash;25. Available from: https://pubmed.ncbi.nlm.nih.gov/26771021/\u003c/li\u003e\n \u003cli\u003eGruosso T, Mieulet V, Cardon M, Bourachot B, Kieffer Y, Devun F, et al. Chronic oxidative stress promotes H2AX protein degradation and enhances chemosensitivity in breast cancer patients. EMBO Mol Med [Internet]. 2016 May [cited 2024 May 15];8(5):527\u0026ndash;49. Available from: https://pubmed.ncbi.nlm.nih.gov/27006338/\u003c/li\u003e\n \u003cli\u003eMcGeary SE, Lin KS, Shi CY, Pham TM, Bisaria N, Kelley GM, et al. The biochemical basis of microRNA targeting efficacy. Science [Internet]. 2019 Dec 20 [cited 2024 May 16];366(6472). Available from: https://pubmed.ncbi.nlm.nih.gov/31806698/\u003c/li\u003e\n \u003cli\u003eAgarwal V, Bell GW, Nam JW, Bartel DP. Predicting effective microRNA target sites in mammalian mRNAs. Elife. 2015 Aug 12;4(AUGUST2015).\u003c/li\u003e\n \u003cli\u003eDe Paz Linares GA, Opperman RM, Majumder M, Lala PK. Prostaglandin E2 Receptor 4 (EP4) as a Therapeutic Target to Impede Breast Cancer-Associated Angiogenesis and Lymphangiogenesis. Cancers (Basel) [Internet]. 2021 Mar 1 [cited 2024 May 16];13(5):1\u0026ndash;27. Available from: https://pubmed.ncbi.nlm.nih.gov/33668160/\u003c/li\u003e\n \u003cli\u003eKulesza A, Paczek L, Burdzinska A. The Role of COX-2 and PGE2 in the Regulation of Immunomodulation and Other Functions of Mesenchymal Stromal Cells. Biomedicines [Internet]. 2023 Feb 1 [cited 2024 May 16];11(2). Available from: https://pubmed.ncbi.nlm.nih.gov/36830980/\u003c/li\u003e\n \u003cli\u003eXin X, Majumder M, Girish G V, Mohindra V, Maruyama T, Lala PK. Targeting COX-2 and EP4 to control tumor growth, angiogenesis, lymphangiogenesis and metastasis to the lungs and lymph nodes in a breast cancer model. Laboratory Investigation [Internet]. 2012;92:1115\u0026ndash;28. Available from: www.laboratoryinvestigation.org\u003c/li\u003e\n \u003cli\u003eFeser R, Opperman RM, Maiti S, Majumder M. MicroRNAs: The Master Regulators of the Breast Cancer Tumor Microenvironment. Handbook of Oxidative Stress in Cancer: Therapeutic Aspects [Internet]. 2022 [cited 2024 May 30];1\u0026ndash;23. 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Available from: https://pubmed.ncbi.nlm.nih.gov/33510458/\u003c/li\u003e\n \u003cli\u003ePatra KC, Hay N. The pentose phosphate pathway and cancer. Trends Biochem Sci [Internet]. 2014 [cited 2024 May 16];39(8):347. Available from: /pmc/articles/PMC4329227/\u003c/li\u003e\n \u003cli\u003eCheung EC, Ludwig RL, Vousden KH. Mitochondrial localization of TIGAR under hypoxia stimulates HK2 and lowers ROS and cell death. Proc Natl Acad Sci U S A [Internet]. 2012 Dec 11 [cited 2024 May 16];109(50):20491\u0026ndash;6. Available from: https://pubmed.ncbi.nlm.nih.gov/23185017/\u003c/li\u003e\n \u003cli\u003eSevigny MB, Li CF, Alas M, Hughes-Fulford M. Glycosylation regulates turnover of cyclooxygenase-2. FEBS Lett [Internet]. 2006 Dec 11 [cited 2024 May 16];580(28\u0026ndash;29):6533\u0026ndash;6. Available from: https://onlinelibrary.wiley.com/doi/full/10.1016/j.febslet.2006.10.073\u003c/li\u003e\n \u003cli\u003eShanmugam N, Gonzalo ITG, Natarajan R. 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Available from: https://pubmed.ncbi.nlm.nih.gov/14988266/\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Breast Cancer, metabolism, miRNA, glycolysis, oxidative phosphorylation, metabolic dysregulation","lastPublishedDoi":"10.21203/rs.3.rs-4510975/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4510975/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eIntroduction:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBreast cancer (BRCA) remains a primary global health concern, with ongoing research focused on early detection and improving treatment methods. Moving forward, it is crucial to understand cancer cell metabolism and its impact on tumor growth and metastasis. This study aims to identify potential BRCA markers related to glucose metabolism for targeted therapy, focusing on the role of miR-526b. miR-526b promotes BRCA phenotypes, including migration, invasion, hypoxia, angiogenesis, and metastasis. Further, cell-free secretion of miR-526b-high BRCA tumor cells can alter the tumor microenvironment. This study will investigate the role of miR-526b in the dysregulation of glucose metabolism.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMethods:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe used two immortalized BRCA cell lines, MCF7 and SKBR3, and stable miR-526b overexpressed cells MCF7-miR526b and SKBR3-miR526b and a naturally miR-526b high cell line MCF7-COX2 for in vitro assays. We measured ATP production, oxygen consumption rate, and extracellular acidification rate. We used glycolysis and OXPHOS inhibitors to measure metabolic plasticity induced by miR-526b. A COX-2 inhibitor and EP4 antagonist were used to alter miR-526b-induced functions. For RNA and protein measurement, we used qRT-PCR and western blots. In silico analysis with online datasets validated our findings in human BRCA.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eResults:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn silico\u003c/em\u003e analysis showed that genes related to glycolysis and oxidative phosphorylation (OXPHOS) are enriched in human breast cancer tissues. Overexpression of miR-526b promotes cell proliferation and ATP production. It also contributes to the upregulation of \u003cem\u003eLDHA \u003c/em\u003eand \u003cem\u003ePDHA1, \u003c/em\u003ewhich determine the fate of the glycolytic product pyruvate, either producing lactate or entering the TCA cycle to promote OXPHOS. miR-526b overexpressing cells demonstrated increased metabolic plasticity and decreased adverse effects following treatment with glycolysis and OXPHOS inhibitors, showing increased survival and proliferation. The metabolic dysregulation induced by miR-526b, including increased proliferation, ATP production, and marker expression, can be reversed using a COX2 inhibitor and EP4 antagonist.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConclusion:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003emiR-526b promotes increased glucose metabolism and ATP production, supporting increased growth and division of BRCA cells. It also increases metabolic plasticity, improving cells' ability to thrive in a complex and heterogeneous tumor microenvironment. The dysregulation observed with miR-526b can be reversed by targeting the COX2/EP4 pathway.\u003c/p\u003e","manuscriptTitle":"miR-526b dysregulates glucose metabolism via the COX2/EP4 pathway","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-10 09:33:38","doi":"10.21203/rs.3.rs-4510975/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fab35492-a7ec-4fc4-b555-7c6bc18c6d61","owner":[],"postedDate":"June 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-10T13:17:45+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-10 09:33:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4510975","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4510975","identity":"rs-4510975","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

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