Investigating the effect of stearoyl-coenzyme desaturase 1 inhibition on inflammatory and anti-inflammatory patterns in luminal A breast cancer patients peripheral blood mononuclear cells

Investigating the effect of stearoyl-coenzyme desaturase 1 inhibition on inflammatory and anti-inflammatory patterns in luminal A breast cancer patients peripheral blood mononuclear cells | 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 Investigating the effect of stearoyl-coenzyme desaturase 1 inhibition on inflammatory and anti-inflammatory patterns in luminal A breast cancer patients peripheral blood mononuclear cells Neda Naghashi, Esmaeil Babaei, Zohreh Sanaat, Amir Mehdizadeh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6911415/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Purpose: Breast cancer (BC) is the most prevalent female cancer globally. A key feature of cancer cells is a remarkable alteration in lipid composition, notably an enrichment in monounsaturated fatty acids. This change results from upregulated expression of enzymes involved in fatty acid metabolism, such as stearoyl CoA desaturase 1 (SCD1) which may affect the immune-related responses. Patients and Methods In the present study, 20 patients with luminal A BC and 20 healthy controls were included based on diagnostic criteria. Then, 10 ml of peripheral blood was retrieved from each participant, and peripheral blood mononuclear cells (PBMCs) were isolated, and cultured in RPMI 1640 medium. The treatment and control groups were then treated with 3 µM of SCD1 chemical inhibitor and DMSO for 48 hours, respectively. The alteration in inflammatory markers IL-17 and TNF-α, anti-inflammatory markers IL-10 and TGF-β, inflammatory differentiation markers RORγt and anti-inflammatory differentiation markers FOXP3 were assessed through Real-time PCR. Furthermore, the amount of the respective protein was measured through the enzyme-linked immunosorbent assay method. Results : Chemical inhibition of SCD1 resulted in a significant downregulation of IL-17/TNF-α and upregulation of of IL-10/TGF-β expression in the patient group. Additionally, a significant upregulation of FOXP3 was observed in BC patients after SCD1 inhibition. RORγt expression was also decreased in healthy individuals after SCD1 inhibition with no effect on patient group. Conclusion: The results of this study suggest that SCD1 may act as a potential biomarker in the context of immune response. Luminal A breast cancer Stearoyl CoA desaturase 1 Inflammation Immune response Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Breast cancer (BC) is the most common malignancy and the second leading cause of cancer-related death in women worldwide. With an annual incidence of more than 13,000 and an age-standardized incidence rate of 35.8 per 100,000 per year, it is the most common cancer in Iranian women. With an age-standardized mortality rate of 10.8 per 100,000 women, this cancer is in a lower range than neighboring middle-income countries. This incidence rate has increased compared to the previous report published in the Iranian National Cancer Registry Program, which reported 34.5 per 100,000 women ( 1 , 2 ). According to the latest GLOBOCAN2020 report, breast cancer is the most common malignancy worldwide, and with a high mortality rate of 685,000 deaths in 2020, it has become one of the most common causes of cancer deaths. Cancer mortality accounts for 11% of deaths among the 2.3 million newly diagnosed patients. Since 2008, the incidence and mortality rates of breast cancer have increased by about 20% and 14%, respectively ( 3 ). However, according to several studies conducted worldwide, it is expected that by 2040, the number of new cases and related deaths from breast cancer will increase by 40% (more than 3 million) and 50% (one million), respectively. Accordingly, the 5-year survival rate of patients in Iran is more than 70%, which can be increased to 90% by improving early diagnostic and treatment strategies ( 4 , 5 ). The exact cause of BC is unknown; however, several risk factor have been identified including advancing age (the most important), family history, early menarche, late menopause, older age at first live birth, long-term hormone replacement therapy, previous chest wall radiotherapy, benign proliferative breast disease, increased breast density on mammography, postmenopausal obesity, smoking, diabetes, alcohol consumption, night shifts, and genetic mutations. Genetic makeup, environmental factors, variability in immune response, and host vulnerability are other factors that influence the development of breast malignancy. This malignancy is more common in women with a family history of the disease, and researchers have demonstrated that sporadic mutations are responsible for only 5% of affected people ( 4 , 5 ). The luminal A and luminal B molecular subtypes of hormone receptor-positive clinical breast cancer respond to selective estrogen receptor modulators, aromatase inhibitors. However, long-term anti-estrogen therapy and human epidermal growth factor receptor-2 (HER-2)-targeted therapy are associated with intrinsic and/or acquired drug resistance, which compromises therapeutic efficacy and increases the progression of refractory disease ( 6 ). A key feature of cancer cells is a marked change in lipid composition, which is associated with an enrichment in monounsaturated fatty acids (MUFAs). Lipid synthesis in cancer cells is mediated by increased expression of fatty acid-metabolizing enzymes such as stearoyl-CoA-desaturase1. In addition to the structural functions of fatty acids in the membranes of proliferating cancer cells, fatty acids are also involved in tumorigenic signaling. Increased expression and activity of stearoyl CoA desaturase (SCD1), an enzyme that converts saturated fatty acids to monounsaturated fatty acids, have been observed in various cancer cells. This increased expression and activity has been associated with cancer aggressiveness and poor prognosis. Among the enzymes involved in lipid biosynthesis, SCD1, as the most abundant isoform of SCD in humans, catalyzes the conversion of saturated fatty acids (SFAs) to monounsaturated fatty acids. Various studies have reported an increase in the ratio of MUFAs to SFAs in various malignancies, including pancreas, liver, colon, breast, and prostate, which has been associated with cancer invasion ( 7 ). Evidence suggests that replacing saturated fats with MUFA or PUFA can reduce inflammation and endoplasmic reticulum stress and stimulate adiponectin gene expression, which in turn can reduce IL-6 and TNF-α production. Studies have shown a significant anti-inflammatory relationship between dietary PUFAs and CRP. Using objective and subjective measures of fat intake and diet quality, a positive association between saturated fat and inflammation has been identified. While, an inverse association has been observed between MUFAs, PUFAs, the Mediterranean diet, and inflammation. Furthermore, manipulation of diet quality especially fatty acid intake, may be beneficial for reducing chronic systemic inflammation ( 8 ). Recent advances have also shown that lipids play a key role in regulating macrophage and T-lymphocyte function. Pathways that promote lipid synthesis and accumulation lead to the development of an inflammatory phenotype. While, pathways of increased oxidation and lipid leakage direct immune cells towards an anti-inflammatory phenotype. Studies have shown that omega-3 and omega-6 polyunsaturated fatty acids differentially affect the expression of genes related to inflammation (IL-18, IL-6, IL-1β, TNF-α), angiogenesis (VEGF, PDGF, IGF-1) and proliferation (Cyclin, PTEN, p53 wnt) and therefore can control tumorigenesis. Omega-3 fatty acids such as alpha-linolenic acid (ALA), vitamin D, calcium, fish and phytoestrogens reduce the risk of breast cancer. In contrast, omega-6 fatty acids such as linoleic acid, arachidonic acid, meat consumption and chicken increase breat malignancy risk. Consumption of fish rich in omega-3 fats also reduces the risk of prostate cancer ( 8 ). Given the importance of nutrient metabolism in cancer biology, the regulation of metabolic pathways has profound effects on cancer development. Nutritional interventions can be used as a therapeutic approach to treat cancer. These interventions target different mechanisms and are actually more effective than conventional treatments ( 8 ). According to studies, SCD1 plays a role in increasing the proliferation, growth, migration, and metastasis of cancer cells. Therefore, it seems that SCD1 is a major factor in the development of malignancy. The aim of this study was to investigate the inhibitory effect of the SCD1 enzyme on the expression pattern of inflammatory/anti-inflammatory markers and differentiation of peripheral blood mononuclear cells (PBMCs), which could serve as a new therapeutic target in breast cancer. 2. Materials and methods 2.1. Patient selection and sampling The present study was an analytical-descriptive study on 40 PBMC samples isolated from 20 healthy individuals without any underlying disease and 20 newly diagnosed patients with luminal A breast cancer. The exclusion criteria included patients who were undergoing or had been treated with chemotherapy or radiotherapy. The present study was approved by the Ethics Committee of Tabriz University of Medical Sciences (ethical code: IR.TBZMED.REC.1402.604). Before performing any action, all study steps were explained to the individuals, and informed consent was obtained from all the participants. Then, 5 ml of peripheral blood was obtained from each individual and transferred to heparinized (10 µl) sterile falcons for PBMCs isolation. 2.2. PBMCs isolation To isolate PBMCs, a total of 5 ml of RPMI culture medium was put into falcons (containing 5 ml of peripheral blood). Then, the contents of the falcon were slowly placed into 5 ml of Ficoll, and the falcon was centrifuged at 450 RCF for 20 minutes at 24°C. Following centrifugation, the PBMCs ring were found between the plasma and the ficoll solution. The washing step was done with RPMI, and the amount of ficoll was doubled and centrifuged at 350 RCF for 10 minutes at 24°C, and finally the obtained precipitate containing PBMCs, were taken for cell culture ( 9 ). Isolated PBMCs were then pooled together and cultured in RPMI 1640 medium supplemented with 10% fetal bovine serum (FBS) (AnaCell, Iran), 5% CO 2 , 95% humidity at 37 °C in a 6-well plate. The treatment group was treated with 3µM concentration of the specific SCD1 inhibitor (Cay10566, US) for 48 hours. The control group was also treated with the same amount of DMSO. The cells were then collected and subjected for gene expression assay. 2.3. Total RNA extraction and cDNA synthesis Total RNA extraction was performed using YTzol Pure RNA solution (YTA, Iran) according to the manufacturer’s instructions. The quality and quantity of total RNA were evaluated using 1.5% agarose gel electrophoresis and NanoDrop1000 spectrophotometer (Wilmington, NC), respectively. Next, about 0.5-3 µg of extracted total RNA was converted to cDNA using the cDNA synthesis kit (YTA, Iran). Quantitative polymerase chain reaction (qPCR) was then performed using SYBR green master mix (YTA, Iran) using Applied Biosystem instrument (Thermo Fisher Scientific, US). The specific primers for tumor necrosis factor-α (TNF-α), interleukin (IL)-17, IL10, transforming growth factor-β (TGF-β), forkhead box P3 (FoxP3), and RAR-related orphan receptor C (RORc) were designed using NCBI primer designing tool and Oligo 7 software. To obtain the optimal temperature of the primers, a gradient temperature program was considered based on the Tm recommended by the manufacturer. β-actin was also used as housekeeping gene. The obtained Ct values were analyzed using W.P faffle equation for relative expression analysis ( 10 ). The sequence of the primers and the optimal Tm of each primer are presented in supplementary Table 1. 2.4. Enzyme-linked immunosorbent assay (ELISA) The ELISA assay was employed to study the expression of proteins including TNF-α (Sino Biological, KIT10602), IL-17 (Mybiosource, MBS266143), IL10 (Sino Biological, KIT12047), TGF-β (Mybiosource, MBS266143), FoxP3 (Mybiosource, MBS162054), and RORγt ( Mybiosource , MBS2884310). Accordingly, TNF-α, IL-17, IL10, and TGF-β levels were evaluated in cell culture medium, while FoxP3 and RORγt were measured in cell lysate. All assays were performed according to manufacturer protocols. 2.5. Statistical analysis The results were presented as mean ± standard deviation (SD). One-Way ANOVA and Tukey Post-hoc tests were used to show significant differences between groups, and p < 0.05 was considered as the significance level. Graphpad Prism 8.0.2 software was used to analyze the data and draw graphs. Data were obtained from 2 or 3 independent experiments. 3. Results 3.1. General characteristics of the individuals The Present study was performed on 20 newly diagnosed luminal A BC patients and 20 healthy counterparts as control group. The mean age of the patient group (53.2 ± 8.0 years) is a little less than that of the control group (56.2 ± 8.0 years), although this difference was not statistically significant (p = 0.24). Moreover, the BMI of the patients (29.67 ± 2.98 kg/m²) and controls (29.94 ± 2.45 kg/m²) was comparable, and no visible difference is observed (p = 0.76). These statistics reveal that age and BMI are not characteristic factors for distinguishing the groups in question. However, vitamin D level was significantly lower in the patient group in comparison to the control (24.2 ± 13.01 µg/mL versus 35.95 ± 18.21 µg/mL, p = 0.02). Additional demographic and clinical data of the individuals are presented in Table 1 . Table 1 General characteristics of the individuals under study. Parameters Patients (n = 20) Controls (n = 20) p-Value Age (year) 53.2 ± 8.0 56.2 ± 8.0 0.24 BMI (Kg/m 2 ) 29.67 ± 2.98 29.94 ± 2.45 0.76 Vitamin D (µg/mL) 24.2 ± 13.01 35.95 ± 18.21 0.02 Menopausal Status Pre 6 3 - Post 14 17 - Contraceptive use Yes 16 13 - No 4 3 - Labor Yes 15 16 - No 5 4 - Pathological T stage I 11 - - II 6 - - III 3 - - Pathological N N0 6 - - N1 10 - - N2 4 - - Pathological stage I 10 - - II 4 - - III 4 - - IV 2 - - Lymphovascular invasion Yes 6 - - No 14 - - Data are presented as mean ± standard division or number. P < 0.05 was considered as statistically significant. 3.2. Anti-inflammatory cytokines (IL-10 and TGF-β) expression were increased following SCD1 inhibition in BC patients. As presented in Fig. 1 , a significant up-regulation of IL-10 was observed in BC-SCDi group compared to control-DMSO, control-SCDi, and BC-DMSO at the mRNA level (120.96 ± 21.78 fold expression change versus 1 ± 0, 0.56 ± 0.11, and 22.91 ± 4.12, p = 0.0014, p = 0.0014, and p = 0.0031, respectively). Similar results were also observed regarding this cytokine at the protein level in mentioned groups (422.66 ± 31.64 pg/ml versus 7.33 ± 1.52 pg/ml, 8.66 ± 3.51 pg/ml, and 11.0 ± 2.64 pg/ml, p < 0.0001, p < 0.0001, and p < 0.0001, respectively). Regarding the TGF-β, a significant increased expression was also observed in BC-SCDi group compared to control-DMSO, control-SCDi, and BC-DMSO in mRNA levels (12.06 ± 4.41 fold expression change versus 1 ± 0, 0.01 ± 0.01, and 0.81 ± 0.8, p = 0.007, p = 0.007, and p = 0.006, respectively. These records at the protein level in the mentioned groups were as 151.66 ± 6.02 pg/ml versus 11.33 ± 2.08 pg/ml, 9.0 ± 2.64 pg/ml, and 15.0 ± 2.64 p < 0.0001, p < 0.0001, and p < 0.0001, respectively. 3.3. SCD1 inhibition led to decreased expression of inflammatory cytokines in BC patients. As presented in Fig. 2 , a significant downregulation of TNF-α was observed in BC-SCDi group compared to BC-DMSO at the mRNA level (0.59 ± 0.36 fold expression change versus 12.66 ± 2.3, p = 0.0018, respectively). Accordingly, similar results were also observed at the protein level in mentioned groups (25.0 ± 2.64 pg/ml versus 7.33 ± 1.52 pg/ml, 311.0 ± 16.09 pg/ml, p < 0.0001, respectively). Regarding the IL-17, a significant decreased expression was also observed in BC-SCDi group compared to BC-DMSO at the mRNA levels (21.51 ± 2.3 fold expression change versus 61.53 ± 28.75, p = 0.0001, respectively. Similar results were also detected in protein level in the mentioned groups (216 ± 7.3 pg/ml versus 343.6 ± 10.9 pg/ml, p < 0.0001, respectively). 3.4. SCD1 inhibition led to increased expression of anti-inflammatory differentiative marker FoxP3 in healthy individuals. Figure 3 shows the expression level of FoxP3 as anti-inflammatory differentiative marker at the mRNA and protein levels in the study groups. As indicated, an increased expression of FoxP3 was detected in BC-SCDi group compared to control-DMSO, BC-SCDi, and BC-DMSO in mRNA level (87.16 ± 9.62 versus 1.0 ± 0, 0.12 ± 0.07 and 3.5 ± 1.73, p = 0.0001, p = 0.0001, and p = 0.0001, respectively). These results at the protein level were 35.0 ± 4.0 versus 3.33 ± 0.57, 4.33 ± 2.08, and 4.6 ± 2.1, p < 0.0001, p < 0.0001, and p < 0.0001, respectively. 3.5. SCD1 inhibition led to decreased expression of inflammatory differentiative marker RORc in healthy individuals. Figure 4 shows the expression level of RORc as inflammatory differentiative marker at the mRNA and protein levels in the study groups. As illustrated, decreased expression of RORc was observed in Control-SCDi group compared to control-DMSO in mRNA level (0.15 ± 0.05 versus 1.0 ± 0, 0.0001 ± 0.00008, p = 0.0001, respectively). Similar results were also detected in mentioned groups regarding the RORc expression in protein level (10.33 ± 3.21 versus 48.66 ± 8.96, p < 0.0001, respectively). Supplementary Table 2 also demonstrates the mean ± standard division for the measured parameters in the study groups. 4. Discussion The findings of the present study suggest that the enzyme SCD1 inhibits inflammation, while simultaneously promoting anti-inflammatory effects, as its chemical inhibition decreased the inflammatory cytokines TNF-a and IL-17, while simultaneously increasing the expression of the anti-inflammatory cytokines IL-10 and TGF-b in patients with luminal A breast cancer (BC) PBMCs. Accordingly, the authors were pleased to find that the present study’s current findings matched previous studies demonstrating how modifications in immune system signaling and decreases in inflammation can affect BC. Interleukins play a known role in breast cancer, and current research has demonstrated that higher levels of inflammatory cytokines are present in the serum samples and tumor tissues of BC patients. It was well-established that the presence of excessive cytokine levels in the blood of cancer patients is associated with both disease progression and migration of cancer cells into surrounding tissues ( 11 ). Numerous studies have now suggested that the progression of BC along with its development is associated with inflammatory mechanisms and a dysregulated production of chemokines, including interleukin-8, which is a key mechanism for the process of cancer metastasis ( 12 ). After referring to and analyzing previous studies alongside our own, it can be deduced that inhibiting the scd1 enzyme might be valuable in the mitigation of inflammatory factors associated with the rate of growth and metastasis in breast cancer patients. Notwithstanding, further investigations in the form of human and animal trials, with more diverse sample populations, are necessary to substantiate this theory. It has been shown that the inhibition of SCD1 reduces Wnt/β-catenin signaling in cancer cells as well as the endoplasmic reticulum stress in CD8 + T cells. These effects subsequently increases chemokine CCL4 production, recruits dendritic cells, and enhances the antitumor T cell responses. It was reported that the administration of systemic SCD1 inhibitor in mouse tumor models lead to an increasing CCL level through Wnt/β-catenin as well as the inhibition CD8 + T cells. This in turn, leads to DCs recruitment to the tumors and ultimately to the induction of antitumor CD8 + T cells and trapping of these cells into the tumors. The SCD1 inhibitor was also shown to activate CD8 + T cells and DCs, directly. Moreover, overexpression of SCD1 in the non-inflammatory T-cell subset in human colon cancer and serum fatty acids have also correlated with the response rate and prognosis in patients with non-small cell lung cancer receiving an anti-PD-1 antibody ( 13 ). These findings are consistent with the results of the current study. In a preceding investigation that examined a direct effect of SCD1 inhibition on T cells, it was shown that SCD1 inhibition directly enhanced cytotoxicity and IFN-γ production of CD8 + T cells, and this activity was associated with reduced oleic acid and esterified cholesterol in these cells. Simply adding oleic acid or oleate cholesterol would abolish this activity ( 14 , 15 ). Thus, the current report are consistent with their findings. According to previous findings , inhibition of SCD1 enhanced the immunogenicity of poorly immunogenic tumors, due to induction of endoplasmic reticulum stress and programmed cell death, and has been suggested as a novel approach to enhance T-cell based immunotherapy of tumors ( 14 ). In addition, a related study that looked at SCD1 enzyme inhibition on immunogenicity of tumors, it was reported that inhibition of SCD1 enhanced the immunogenic response in poorly immunogenic tumors when tumor cells underwent endoplasmic reticulum stress and subsequent apoptosis. Subsequently, this method has been suggested as a new strategy to improve T-cell based immunotherapy. A clinical investigation linking the expression levels of the SCD1 enzyme with cancer prognosis found that in some cancers, such as lung and colon adenocarcinoma, high SCD1 expression was associated with advanced disease stage and poorer prognosis. Additionally, the inhibition of this enzyme was suggested as a novel potential therapeutic target ( 15 ). However, it is clear that additional clinical research in this area is warranted. In a study investigating the effects of oxidative stress and inflammatory response inflicted with disruption of signaling and fat accumulation minimally induced by diet in mice, it was reported that plasma levels of IL-10 as an anti-inflammatory cytokine were decreased in mice treated with a SFA-rich diet compared to other groups. In this study, they reported increased levels of inflammatory mediators TNF-α and interleukin-6 in Phospholipids ( 16 ). In line with the results of this study, another work demonstrated that palmitate induced an inflammatory response in primary human skeletal muscle and HEK cells. Here, the exposure of HEK cells to palmitate was completely inhibited by the overexpression of the SCD1 gene. Additionally, the inflammatory response to palmitate exposure was directly related to the content of SCD1 enzyme. The data also showed that higher content of SCD1 enzyme leads to less inflammatory response to palmitate exposure contained less expression of the inflammatory cytokines IL-6, IL-8, and CXCL3 in human myotubes ( 17 ). Moreover, the overexpression of the enzyme related to inflammation was shown to increase liver inflammation and acute colitis ( 18 ). The absence of SCD1 in familial hypercholesterolemia mice exhibited inflammation in causing atherogenesis ( 19 , 20 ). A recent study also showed that the absence of SCD1 provided a favorable metabolic state with increased insulin sensitivity, decreased hepatic steatosis and obesity. Furthermore, SCD1 inhibition corresponds with inhibition of cancer cell proliferation. SCD1 inhibition alters cellular function by controlling inflammatory responses and stress pathways in adipocytes, liver, macrophages, aorta, skin, myocytes, beta cells, and endothelial cells ( 21 ), further confirming the findings of the current study. Additionally, in another study using metalloproteinase 3 knockout models, it was found that increased SCD1 is one of the markers associated with increased inflammation in both white adipose tissue and the liver ( 22 , 23 ). SCD1 plays an important role in a variety of inflammatory and cellular stress responses by maintaining overall homeostasis between single unsaturated fatty acids (MUFA) and saturated fatty acids (SFA), where SFAs act as ligands for cell surface immune receptors such as members of the Toll-like receptor (TLR) family, and thereby promote pro-inflammatory responses ( 21 ). In contrast, MUFAs can reverse the negative impacts of SFAs on adipose tissue and liver tissue through anti-inflammatory mechanisms including increasing M2 macrophage polarization and adipose IL-10 secretion ( 24 ). Most notably, increased activity of SCD1 is reflected as an increase of MUFA within macrophages that will lower the inflammatory response induced by myeloid differentiation factor 88 (MyD88) ( 25 , 26 ). Furthermore, a different study showed when SCD1 was inhibited in adipocytes with chemical inhibitors, the upregulation of fatty acids like stearate significantly modulated the secretion of numerous inflammatory markers, including IL-6, MCP-1, CCL5 and induced cellular stress ( 27 ). A number of studies have also shown that lowering inflammatory mediators such as IL-17 in breast cancer (BC) patients can translate into better clinical outcomes, symptoms, and tumor growth. For example, studies in patients with BC examining the effects of resistance or endurance training reported a reduction in IL-17 and other inflammatory cytokines ( 28 , 29 ). A decrease in chronic inflammatory markers like IL-17 can counteract tumor growth, and will likely enhance antitumor immune responses through changes of cellular metabolism and better cytokine homeostasis ( 30 ). Comparing the findings of this investigation to our study, which proposes chemical inhibition of the SCD1 enzyme as a viable means of suppressing inflammation, supports the claim that lipid metabolism pathways can affect the modulation of inflammatory and immune responses in tumor systems, directly or indirectly. SCD1 inhibition has been shown to interfere with inflammatory signaling pathways by decreasing the levels of monounsaturated fatty acids, thus resulting in a decrease in the levels of inflammatory mediators such as IL-17 and TNF-α, which is consistent with the overall reduction of systemic inflammation and localized tumor inflammation in the microenvironment. In contrast, research has shown that reduction in IL-17 and increase in anti-inflammatory cytokines, such as IL-10, can help to transform the immune balance towards normal control of tumor growth ( 28 ). This is backed up by our study illustration of decrease in inflammatory cytokines with SCD-1 inhibition, and can underlie a combination treatment with SCD-1 inhibition and immunomodulation. Our study also found that SCD-1 inhibition reduced levels of anti-inflammatory mediators TGF-β and IL-10 in luminal A BC patients, of importance aligning with these mediator's roles in immunosuppressive and tumor forming capacities. There has not been specific citations in the scientific literature to date that has cited this correlation in detail, and is seen as an emerging finding needing confirmation and further study in the future. In the current study, we also examined the effect of chemical inhibition of SCD1 on expression levels of the anti-inflammatory differentiation factors. We determined that the expression levels of the anti-inflammatory differentiation factor FOXP3 - at the mRNA and protein levels - in the patient was higher, while in healthy controls, inhibition of SCD1 did not significantly modified the expression level of FOXP3. Previous studies have established that FOXP3 as a major marker of Tregs in BC, plays an important role in the suppression of a tumors anti-immune response. The higher levels of Tregs and FOXP3 in tumor tissues are associated with disease progression, higher invasion or metastasis, and the capability to inhibit CD4 + and CD8 + T cells activity, which will lead to increased tumor growth and spread. Normal levels of FOXP3 are important to control the oncogenic factors in the epithelial cells of BC by regulating the expression levels of other genes (including c-Myc, LATS2, SKP2, ErbB2/HER2) which will ultimately lead to a decrease of Tregs ( 31 ). This discrepancy between our results and the previous studies maybe due to biological condition. The obtained data regarding FOXP3 maybe different in 2D culture and in vivo condition. Hence, more studies are still required to fully clarify this controversial results. Reflecting on the results we observed with FOXP3 regulation in the luminal A BC patients after SCD1 inhibition in this study, it is reasonable to predict that inhibiting FOXP1 in BC, would keep FOXP3 in the normal range of expression values, down regulate BC regulatory genes, and reduce the number of regulatory T cells. Similarly, our work can provide SCD1 inhibition for BC, while reproducing the above work. Further, the increase in FOXP3 within the control group after SCD1 inhibition may demonstrate a complex response, with many components that need to be investigated to see if this is an enhanced immune suppression by Tregs or the broad regulatory response found in the tumor microenvironment. Prior studies have demonstrated that the tumor microenvironment can release TGF-β and IL-6; these cytokines can induce normal Th17 cells to differentiate into CD25high Th17 cells expressing CD39 and CD73. Th17 cells are used to induce inflammation and are known to play a role in the pathogenesis of autoimmune and allergic diseases. There is still some controversy about the role of Th17 cells in cancer progression. Foxp3 + Th17 cells are clustered in advanced BC. In human memory, CD25-high Th17 cells can suppress T-cell immune responses in BC. Th17 cells also can express ectonucleotidase (i.e., CD39) and can also infiltrate BC tumors and suppress activation of CD4 + and CD8 + cells. These cells co-express Rorγt and Foxp3 genes and produce Th17-related cytokines. Tumor infiltrating Th17 cells express the ectonucleotidase CD39 upon TGF-β and IL-6 stimulation. Finally, immunohistochemical approaches of localized BC showed that high infiltration of Th17 + in the tumor correlates with poor clinical outcomes and nullifies the protective role of high CD8 + infiltration. Overall, these results indicate that Th17 cells in the tumor microenvironment can suppress anticancer immune response in patients diagnosed with BC. An important study has shown that when either genetic or pharmacological approaches inhibited SCD1 in MS autoimmunity models (e.g., EAE-an animal model), there was a reduction in inflammation, and T cell and macrophage infiltration into target organs. The authors suggest that inhibition of SCD1 can change the balance of T cell subsets, as inhibition of SCD1 can block the differentiation of Th17 cells (RORγt dependent), which reduced RORγt gene expression as well as IL-17 production ( 32 ). The results that chemical inhibition of SCD1 was also able to decrease the level of the inflammatory differentiation factor RORγt in a healthy controls with no comorbidity at both mRNA and protein levels were consistent with findings of the previously described study and this function of SCD1 inhibition in healthy women with no comorbidities and who are at a high risk of developing BC can be used to slow the development of BC through targeting Th17 function (RORγt-dependent). Lastly, differences among the results in the different studies could be attributed to differences in models, cancer type, patient statuses, and/or measurements. Therefore, results produced from this study can be seen as a remarkable advance in understanding how lipid metabolism regulates inflammation relative to BC. Future investigations should evaluate the impacts of SCD1 inhibition on other immune markers and pathways that will be involved. 5. Conclusions A quantitative analysis found that the key role of inhibition of SCD1 enzyme in the context of patients with luminal A BC that probably inhibits inflammation and enhances anti-inflammatory effect and so this means that inhibition of SCD1 can be a useful biomarker to improve the treatment process of patients with luminal A BC. Abbreviations BC: breast cancer; DMSO: Dimethyl sulfoxide; FoxP3: Forkhead box protein P3; RORγt: Retinoic acid-related orphan receptor gamma t; SCD1: Stearoyl CoA-desaturase 1; TGF-β: Transforming growth factor beta; TNF-α: Tumor necrosis factor alpha; PBMCs: Peripheral blood mononuclear cells. Declarations Acknowledgment This work has been done as part of the Ph.D. dissertation for Neda Naghashi. The authors are grateful to acknowledge Department of Biology, School of Natural Sciences, University of Tabriz, Tabriz, Iran for their great help. Funding Our study was funded by Hematology and Oncology Research Center at Tabriz University of Medical Sciences, Iran [Grant No. 72345]. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author contribution statement NN wrote the initial draft of the manuscript and conducted the experiments. EB, and AM designed and supervised the project. ZS selected the patients under study. All authors read and approved the manuscript. The authors confirm that no paper mill and artificial intelligence was used. Data availability statement All data supporting the findings of this study are available within the paper and its Supplementary Information. Ethics approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Tabriz University of Medical Sciences (No.: IR.TBZMED.REC.1402.604). Consent to Participate Informed consent was obtained from all individual participants included in the study. Consent to Publish The authors affirm that human research participants provided informed consent for publication of all Figures and Tables. Clinical trial number not applicable References Sabzichi M, Ramezani M, Mohammadian J, Ghorbani M, Mardomi A, Najafipour F, et al. The synergistic impact of quinacrine on cell cycle and anti-invasiveness behaviors of doxorubicin in MDA-MB-231 breast cancer cells. Process Biochemistry. 2019;81:175-81. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians. 2021;71(3):209-49. Giaquinto AN, Miller KD, Tossas KY, Winn RA, Jemal A, Siegel RL. Cancer statistics for African American/black people 2022. CA: a cancer journal for clinicians. 2022;72(3):202-29. Miller KD, Ortiz AP, Pinheiro PS, Bandi P, Minihan A, Fuchs HE, et al. Cancer statistics for the US Hispanic/Latino population, 2021. CA: a cancer journal for clinicians. 2021;71(6):466-87. Sharma R. Breast cancer incidence, mortality and mortality-to-incidence ratio (MIR) are associated with human development, 1990–2016: evidence from Global Burden of Disease Study 2016. Breast Cancer. 2019;26:428-45. Łukasiewicz S, Czeczelewski M, Forma A, Baj J, Sitarz R, Stanisławek A. Breast cancer—epidemiology, risk factors, classification, prognostic markers, and current treatment strategies—an updated review. Cancers. 2021;13(17):4287. Noori M, Mousavi SE, Asghari K, Nejadghaderi SA, Sullman M, Kolahi A-A. The Burden of Cancers and Their Attributable Risk Factors Among Iranian Adults Aged 70 and Above, 1990-2019. International Journal of Aging. 2023;1:e5, DOI: 10.34172/ija.2023.e5. Nardin S, Mora E, Varughese FM, D'Avanzo F, Vachanaram AR, Rossi V, et al. Breast Cancer Survivorship, Quality of Life, and Late Toxicities. Front Oncol. 2020;10:864, DOI: 10.3389/fonc.2020.00864. Motavalli R, Etemadi J, Soltani-Zangbar MS, Ardalan M-R, Kahroba H, Roshangar L, et al. Altered Th17/Treg ratio as a possible mechanism in pathogenesis of idiopathic membranous nephropathy. Cytokine. 2021;141:155452, DOI: https://doi.org/10.1016/j.cyto.2021.155452. Pfaffl MW. A new mathematical model for relative quantification in real-time RT–PCR. Nucleic acids research. 2001;29(9):e45-e. de Andrés PJ, Illera JC, Cáceres S, Díez L, Pérez-Alenza MD, Peña L. Increased levels of interleukins 8 and 10 as findings of canine inflammatory mammary cancer. Veterinary Immunology and Immunopathology. 2013;152(3-4):245-51. Vogel CFA, Li W, Wu D, Miller JK, Sweeney C, Lazennec G, et al. Interaction of aryl hydrocarbon receptor and NF-κB subunit RelB in breast cancer is associated with interleukin-8 overexpression. Archives of biochemistry and biophysics. 2011;512(1):78-86. Katoh Y, Yaguchi T, Kubo A, Iwata T, Morii K, Kato D, et al. Inhibition of stearoyl-CoA desaturase 1 (SCD1) enhances the antitumor T cell response through regulating β-catenin signaling in cancer cells and ER stress in T cells and synergizes with anti-PD-1 antibody. Journal for Immunotherapy of Cancer. 2022;10. Sugi T, Katoh Y, Ikeda T, Seta D, Iwata T, Nishio H, et al. SCD1 inhibition enhances the effector functions of CD8+ T cells via ACAT1‐dependent reduction of esterified cholesterol. Cancer science. 2024;115(1):48-58. von Roemeling CA, Caulfield TR, Marlow L, Bok I, Wen J, Miller JL, et al. Accelerated bottom-up drug design platform enables the discovery of novel stearoyl-CoA desaturase 1 inhibitors for cancer therapy. Oncotarget. 2017;9(1):3. Tamer F, Ulug E, Akyol A, Nergiz-Unal R. The potential efficacy of dietary fatty acids and fructose induced inflammation and oxidative stress on the insulin signaling and fat accumulation in mice. Food and chemical toxicology. 2020;135:110914. Flowers MT, Keller MP, Choi Y, Lan H, Kendziorski C, Ntambi JM, et al. Liver gene expression analysis reveals endoplasmic reticulum stress and metabolic dysfunction in SCD1-deficient mice fed a very low-fat diet. Physiological genomics. 2008. Chen C, Shah YM, Morimura K, Krausz KW, Miyazaki M, Richardson TA, et al. Metabolomics reveals that hepatic stearoyl-CoA desaturase 1 downregulation exacerbates inflammation and acute colitis. Cell metabolism. 2008;7(2):135-47. MacDonald ML, Van Eck M, Hildebrand RB, Wong BW, Bissada N, Ruddle P, et al. Despite antiatherogenic metabolic characteristics, SCD1-deficient mice have increased inflammation and atherosclerosis. Arteriosclerosis, thrombosis, and vascular biology. 2009;29(3):341-7. Peter A, Weigert C, Staiger H, Machicao F, Schick F, Machann J, et al. Individual stearoyl-coa desaturase 1 expression modulates endoplasmic reticulum stress and inflammation in human myotubes and is associated with skeletal muscle lipid storage and insulin sensitivity in vivo. Diabetes. 2009;58(8):1757-65. Nguyen MA, Favelyukis S, Nguyen A-K, Reichart D, Scott PA, Jenn A, et al. A subpopulation of macrophages infiltrates hypertrophic adipose tissue and is activated by free fatty acids via Toll-like receptors 2 and 4 and JNK-dependent pathways. Journal of biological chemistry. 2007;282(48):35279-92. Liu X, Strable MS, Ntambi JM. Stearoyl CoA desaturase 1: role in cellular inflammation and stress. Advances in nutrition. 2011;2(1):15-22. Menghini R, Menini S, Amoruso R, Fiorentino L, Casagrande V, Marzano V, et al. Tissue inhibitor of metalloproteinase 3 deficiency causes hepatic steatosis and adipose tissue inflammation in mice. Gastroenterology. 2009;136(2):663-72. e4. Ravaut G, Légiot A, Bergeron K-F, Mounier C. Monounsaturated fatty acids in obesity-related inflammation. International journal of molecular sciences. 2020;22(1):330. Hsieh W-Y, Zhou QD, York AG, Williams KJ, Scumpia PO, Kronenberger EB, et al. Toll-like receptors induce signal-specific reprogramming of the macrophage lipidome. Cell metabolism. 2020;32(1):128-43. e5. Sun Q, Xing X, Wang H, Wan K, Fan R, Liu C, et al. SCD1 is the critical signaling hub to mediate metabolic diseases: mechanism and the development of its inhibitors. Biomedicine & Pharmacotherapy. 2024;170:115586. Ralston JC, Metherel AH, Stark KD, Mutch DM. SCD1 mediates the influence of exogenous saturated and monounsaturated fatty acids in adipocytes: effects on cellular stress, inflammatory markers and fatty acid elongation. The Journal of nutritional biochemistry. 2016;27:241-8. Pournemati P, Hooshmand Moghadam B. The effect of 12 Weeks of interval and continuous training on serum levels of interleukin-17 and interleukin-10 in postmenopausal breast cancer survivors: a clinical trial. Iranian Journal of Breast Diseases. 2021;14(2):4-15. Radmehr L, KALANTARI KB, KAZEMI A. The effect of 8 weeks of endurance training on serum levels of IL-10 and IL-17 in elderly women with breast cancer. 2016. Kazemi A, Agha Alinejad H, Eslami R, Ehsan P, Baghaei R, Dabaghzadeh R, et al. Investigating the Effect of Endurance Training on Tumor Level of IL-8 and Serum Level of IL-17 in Female Mice with Breast Cancer. Journal of Advanced Biomedical Sciences. 2015;5(3):347-55. Shou J, Zhang Z, Lai Y, Chen Z, Huang J. Worse outcome in breast cancer with higher tumor-infiltrating FOXP3+ Tregs: a systematic review and meta-analysis. BMC cancer. 2016;16:1-8. Grajchen E, Loix M, Baeten P, Côrte-Real BF, Hamad I, Vanherle S, et al. Fatty acid desaturation by stearoyl-CoA desaturase-1 controls regulatory T cell differentiation and autoimmunity. Cellular & molecular immunology. 2023;20(6):666-79. Additional Declarations No competing interests reported. Supplementary Files Supplementarydata.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 15 Sep, 2025 Reviews received at journal 10 Sep, 2025 Reviews received at journal 07 Sep, 2025 Reviewers agreed at journal 01 Sep, 2025 Reviewers agreed at journal 31 Aug, 2025 Reviewers agreed at journal 23 Jul, 2025 Reviewers invited by journal 23 Jul, 2025 Editor assigned by journal 17 Jun, 2025 Submission checks completed at journal 17 Jun, 2025 First submitted to journal 17 Jun, 2025 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. 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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-6911415","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":489822300,"identity":"f929dce4-d467-472b-841e-6ba7971e04ae","order_by":0,"name":"Neda Naghashi","email":"","orcid":"","institution":"University of Tabriz","correspondingAuthor":false,"prefix":"","firstName":"Neda","middleName":"","lastName":"Naghashi","suffix":""},{"id":489822301,"identity":"f7eaf8dc-eb79-409f-b80e-6cca35764df5","order_by":1,"name":"Esmaeil Babaei","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYBACAwYeEGnDwCDBwHAAIsbYQIyWNAlStTAcBmshDpiznz344UPB+Tr+2b0PD/5sY5Dnb2Bu+4BPi2VPXrLkDIPbEhJ3jhsckGxjMJxxgLF5Bl6HHcgxkOYBamG4kcZwwLCNgXEDA2Mzfr+cf2P8+4/BOQl5kJbENgZ7wlpu5JhJA+2SMABpOdjGkEhQi+WMd2mWPQbJkhvvHGM42HBOInnGYQJazPlzD9/48ceOX+52G/PHH2U2tv3t7Y/xakEHwNhhJknDKBgFo2AUjAJsAAAwr0jEqKpClQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Tabriz","correspondingAuthor":true,"prefix":"","firstName":"Esmaeil","middleName":"","lastName":"Babaei","suffix":""},{"id":489822302,"identity":"68b15a77-d000-41bc-b30d-ae38fb92d278","order_by":2,"name":"Zohreh Sanaat","email":"","orcid":"","institution":"Tabriz University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Zohreh","middleName":"","lastName":"Sanaat","suffix":""},{"id":489822303,"identity":"18e605a7-85a5-453b-a7d5-9cef1cf2beaa","order_by":3,"name":"Amir Mehdizadeh","email":"","orcid":"","institution":"Tabriz University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Amir","middleName":"","lastName":"Mehdizadeh","suffix":""}],"badges":[],"createdAt":"2025-06-17 07:23:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6911415/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6911415/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87693726,"identity":"8d5c54ad-4dcd-4dff-a9b6-7d0ef767fb9e","added_by":"auto","created_at":"2025-07-28 05:34:17","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":327077,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression analysis of anti-inflammatory (IL-10 and TGF-β) cytokines. \u003c/strong\u003eData are presented as mean±standard division. P\u0026lt;0.05 was considered as statistically significant. Non-similar letters represent for significant statistical difference.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6911415/v1/ba0c1b6815b2cb37b0879dbc.jpg"},{"id":87693729,"identity":"e6682981-f5f3-41b0-92bd-3a95b6a4e088","added_by":"auto","created_at":"2025-07-28 05:34:17","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":335304,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression analysis of inflammatory (IL-17 and TNF-α) cytokines. \u003c/strong\u003eData are presented as mean±standard division. P\u0026lt;0.05 was considered as statistically significant. Non-similar letters represent for significant statistical difference.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6911415/v1/18a415bf4cfffd3b1def2a9b.jpg"},{"id":87694349,"identity":"7e2b76db-31fd-4815-a0c8-199f22aef4c3","added_by":"auto","created_at":"2025-07-28 05:42:18","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":161996,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression analysis of anti-inflammatory differentiative (FoxP3) marker. \u003c/strong\u003eData are presented as mean±standard division. P\u0026lt;0.05 was considered as statistically significant. Non-similar letters represent for significant statistical difference.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6911415/v1/e2301446a46137d33cd72ddb.jpg"},{"id":87693736,"identity":"fd854a60-c7ce-415d-97ab-0779242fd53c","added_by":"auto","created_at":"2025-07-28 05:34:18","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":156400,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression analysis of inflammatory differentiative (RORc) marker. \u003c/strong\u003eData are presented as mean±standard division. P\u0026lt;0.05 was considered as statistically significant. Non-similar letters represent for significant statistical difference.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6911415/v1/1769191e5eabd91933268363.jpg"},{"id":87695763,"identity":"73157a76-8806-4f1f-810b-7cb055ea461a","added_by":"auto","created_at":"2025-07-28 05:58:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1978156,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6911415/v1/75fe6024-fe3c-4275-ba43-4e999217e930.pdf"},{"id":87694347,"identity":"ea5e9653-d679-4578-bff8-a4ac1cf894c8","added_by":"auto","created_at":"2025-07-28 05:42:17","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":16002,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarydata.docx","url":"https://assets-eu.researchsquare.com/files/rs-6911415/v1/2a3b638461b52c4516132432.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Investigating the effect of stearoyl-coenzyme desaturase 1 inhibition on inflammatory and anti-inflammatory patterns in luminal A breast cancer patients peripheral blood mononuclear cells","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eBreast cancer (BC) is the most common malignancy and the second leading cause of cancer-related death in women worldwide. With an annual incidence of more than 13,000 and an age-standardized incidence rate of 35.8 per 100,000 per year, it is the most common cancer in Iranian women. With an age-standardized mortality rate of 10.8 per 100,000 women, this cancer is in a lower range than neighboring middle-income countries. This incidence rate has increased compared to the previous report published in the Iranian National Cancer Registry Program, which reported 34.5 per 100,000 women (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). According to the latest GLOBOCAN2020 report, breast cancer is the most common malignancy worldwide, and with a high mortality rate of 685,000 deaths in 2020, it has become one of the most common causes of cancer deaths. Cancer mortality accounts for 11% of deaths among the 2.3\u0026nbsp;million newly diagnosed patients. Since 2008, the incidence and mortality rates of breast cancer have increased by about 20% and 14%, respectively (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). However, according to several studies conducted worldwide, it is expected that by 2040, the number of new cases and related deaths from breast cancer will increase by 40% (more than 3\u0026nbsp;million) and 50% (one million), respectively. Accordingly, the 5-year survival rate of patients in Iran is more than 70%, which can be increased to 90% by improving early diagnostic and treatment strategies (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe exact cause of BC is unknown; however, several risk factor have been identified including advancing age (the most important), family history, early menarche, late menopause, older age at first live birth, long-term hormone replacement therapy, previous chest wall radiotherapy, benign proliferative breast disease, increased breast density on mammography, postmenopausal obesity, smoking, diabetes, alcohol consumption, night shifts, and genetic mutations. Genetic makeup, environmental factors, variability in immune response, and host vulnerability are other factors that influence the development of breast malignancy. This malignancy is more common in women with a family history of the disease, and researchers have demonstrated that sporadic mutations are responsible for only 5% of affected people (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe luminal A and luminal B molecular subtypes of hormone receptor-positive clinical breast cancer respond to selective estrogen receptor modulators, aromatase inhibitors. However, long-term anti-estrogen therapy and human epidermal growth factor receptor-2 (HER-2)-targeted therapy are associated with intrinsic and/or acquired drug resistance, which compromises therapeutic efficacy and increases the progression of refractory disease (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA key feature of cancer cells is a marked change in lipid composition, which is associated with an enrichment in monounsaturated fatty acids (MUFAs). Lipid synthesis in cancer cells is mediated by increased expression of fatty acid-metabolizing enzymes such as stearoyl-CoA-desaturase1. In addition to the structural functions of fatty acids in the membranes of proliferating cancer cells, fatty acids are also involved in tumorigenic signaling. Increased expression and activity of stearoyl CoA desaturase (SCD1), an enzyme that converts saturated fatty acids to monounsaturated fatty acids, have been observed in various cancer cells. This increased expression and activity has been associated with cancer aggressiveness and poor prognosis. Among the enzymes involved in lipid biosynthesis, SCD1, as the most abundant isoform of SCD in humans, catalyzes the conversion of saturated fatty acids (SFAs) to monounsaturated fatty acids. Various studies have reported an increase in the ratio of MUFAs to SFAs in various malignancies, including pancreas, liver, colon, breast, and prostate, which has been associated with cancer invasion (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEvidence suggests that replacing saturated fats with MUFA or PUFA can reduce inflammation and endoplasmic reticulum stress and stimulate adiponectin gene expression, which in turn can reduce IL-6 and TNF-α production. Studies have shown a significant anti-inflammatory relationship between dietary PUFAs and CRP. Using objective and subjective measures of fat intake and diet quality, a positive association between saturated fat and inflammation has been identified. While, an inverse association has been observed between MUFAs, PUFAs, the Mediterranean diet, and inflammation. Furthermore, manipulation of diet quality especially fatty acid intake, may be beneficial for reducing chronic systemic inflammation (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRecent advances have also shown that lipids play a key role in regulating macrophage and T-lymphocyte function. Pathways that promote lipid synthesis and accumulation lead to the development of an inflammatory phenotype. While, pathways of increased oxidation and lipid leakage direct immune cells towards an anti-inflammatory phenotype. Studies have shown that omega-3 and omega-6 polyunsaturated fatty acids differentially affect the expression of genes related to inflammation (IL-18, IL-6, IL-1β, TNF-α), angiogenesis (VEGF, PDGF, IGF-1) and proliferation (Cyclin, PTEN, p53 wnt) and therefore can control tumorigenesis. Omega-3 fatty acids such as alpha-linolenic acid (ALA), vitamin D, calcium, fish and phytoestrogens reduce the risk of breast cancer. In contrast, omega-6 fatty acids such as linoleic acid, arachidonic acid, meat consumption and chicken increase breat malignancy risk. Consumption of fish rich in omega-3 fats also reduces the risk of prostate cancer (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGiven the importance of nutrient metabolism in cancer biology, the regulation of metabolic pathways has profound effects on cancer development. Nutritional interventions can be used as a therapeutic approach to treat cancer. These interventions target different mechanisms and are actually more effective than conventional treatments (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to studies, SCD1 plays a role in increasing the proliferation, growth, migration, and metastasis of cancer cells. Therefore, it seems that SCD1 is a major factor in the development of malignancy. The aim of this study was to investigate the inhibitory effect of the SCD1 enzyme on the expression pattern of inflammatory/anti-inflammatory markers and differentiation of peripheral blood mononuclear cells (PBMCs), which could serve as a new therapeutic target in breast cancer.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Patient selection and sampling\u003c/h2\u003e\u003cp\u003eThe present study was an analytical-descriptive study on 40 PBMC samples isolated from 20 healthy individuals without any underlying disease and 20 newly diagnosed patients with luminal A breast cancer. The exclusion criteria included patients who were undergoing or had been treated with chemotherapy or radiotherapy. The present study was approved by the Ethics Committee of Tabriz University of Medical Sciences (ethical code: IR.TBZMED.REC.1402.604). Before performing any action, all study steps were explained to the individuals, and informed consent was obtained from all the participants. Then, 5 ml of peripheral blood was obtained from each individual and transferred to heparinized (10 \u0026micro;l) sterile falcons for PBMCs isolation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. PBMCs isolation\u003c/h2\u003e\u003cp\u003eTo isolate PBMCs, a total of 5 ml of RPMI culture medium was put into falcons (containing 5 ml of peripheral blood). Then, the contents of the falcon were slowly placed into 5 ml of Ficoll, and the falcon was centrifuged at 450 RCF for 20 minutes at 24\u0026deg;C. Following centrifugation, the PBMCs ring were found between the plasma and the ficoll solution. The washing step was done with RPMI, and the amount of ficoll was doubled and centrifuged at 350 RCF for 10 minutes at 24\u0026deg;C, and finally the obtained precipitate containing PBMCs, were taken for cell culture (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIsolated PBMCs were then pooled together and cultured in RPMI 1640 medium supplemented with 10% fetal bovine serum (FBS) (AnaCell, Iran), 5% CO\u003csub\u003e2\u003c/sub\u003e, 95% humidity at 37\u003csup\u003e\u0026deg;C\u003c/sup\u003e in a 6-well plate. The treatment group was treated with 3\u0026micro;M concentration of the specific SCD1 inhibitor (Cay10566, US) for 48 hours. The control group was also treated with the same amount of DMSO. The cells were then collected and subjected for gene expression assay.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Total RNA extraction and cDNA synthesis\u003c/h2\u003e\u003cp\u003eTotal RNA extraction was performed using YTzol Pure RNA solution (YTA, Iran) according to the manufacturer\u0026rsquo;s instructions. The quality and quantity of total RNA were evaluated using 1.5% agarose gel electrophoresis and NanoDrop1000 spectrophotometer (Wilmington, NC), respectively. Next, about 0.5-3 \u0026micro;g of extracted total RNA was converted to cDNA using the cDNA synthesis kit (YTA, Iran). Quantitative polymerase chain reaction (qPCR) was then performed using SYBR green master mix (YTA, Iran) using Applied Biosystem instrument (Thermo Fisher Scientific, US). The specific primers for tumor necrosis factor-α (TNF-α), interleukin (IL)-17, IL10, transforming growth factor-β (TGF-β), forkhead box P3 (FoxP3), and RAR-related orphan receptor C (RORc) were designed using NCBI primer designing tool and Oligo 7 software. To obtain the optimal temperature of the primers, a gradient temperature program was considered based on the Tm recommended by the manufacturer. β-actin was also used as housekeeping gene. The obtained Ct values were analyzed using W.P faffle equation for relative expression analysis (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The sequence of the primers and the optimal Tm of each primer are presented in supplementary Table\u0026nbsp;1.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Enzyme-linked immunosorbent assay (ELISA)\u003c/h2\u003e\u003cp\u003eThe ELISA assay was employed to study the expression of proteins including TNF-α (Sino Biological, KIT10602), IL-17 (Mybiosource, MBS266143), IL10 (Sino Biological, KIT12047), TGF-β (Mybiosource, MBS266143), FoxP3 (Mybiosource, MBS162054), and RORγt (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMybiosource\u003c/span\u003e, MBS2884310). Accordingly, TNF-α, IL-17, IL10, and TGF-β levels were evaluated in cell culture medium, while FoxP3 and RORγt were measured in cell lysate. All assays were performed according to manufacturer protocols.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Statistical analysis\u003c/h2\u003e\u003cp\u003eThe results were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). One-Way ANOVA and Tukey Post-hoc tests were used to show significant differences between groups, and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered as the significance level. Graphpad Prism 8.0.2 software was used to analyze the data and draw graphs. Data were obtained from 2 or 3 independent experiments.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1. General characteristics of the individuals\u003c/h2\u003e\u003cp\u003eThe Present study was performed on 20 newly diagnosed luminal A BC patients and 20 healthy counterparts as control group. The mean age of the patient group (53.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0 years) is a little less than that of the control group (56.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0 years), although this difference was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.24). Moreover, the BMI of the patients (29.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.98 kg/m\u0026sup2;) and controls (29.94\u0026thinsp;\u0026plusmn;\u0026thinsp;2.45 kg/m\u0026sup2;) was comparable, and no visible difference is observed (p\u0026thinsp;=\u0026thinsp;0.76). These statistics reveal that age and BMI are not characteristic factors for distinguishing the groups in question. However, vitamin D level was significantly lower in the patient group in comparison to the control (24.2\u0026thinsp;\u0026plusmn;\u0026thinsp;13.01 \u0026micro;g/mL versus 35.95\u0026thinsp;\u0026plusmn;\u0026thinsp;18.21 \u0026micro;g/mL, p\u0026thinsp;=\u0026thinsp;0.02). Additional demographic and clinical data of the individuals are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGeneral characteristics of the individuals under study.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePatients (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eControls (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAge (year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eBMI (Kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29.94\u0026thinsp;\u0026plusmn;\u0026thinsp;2.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eVitamin D (\u0026micro;g/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.2\u0026thinsp;\u0026plusmn;\u0026thinsp;13.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.95\u0026thinsp;\u0026plusmn;\u0026thinsp;18.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMenopausal Status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePost\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eContraceptive use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eLabor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ePathological T stage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eII\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIII\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ePathological N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003ePathological stage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eII\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIII\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eLymphovascular invasion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard division or number. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered as statistically significant.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Anti-inflammatory cytokines (IL-10 and TGF-β) expression were increased following SCD1 inhibition in BC patients.\u003c/h2\u003e\u003cp\u003eAs presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, a significant up-regulation of IL-10 was observed in BC-SCDi group compared to control-DMSO, control-SCDi, and BC-DMSO at the mRNA level (120.96\u0026thinsp;\u0026plusmn;\u0026thinsp;21.78 fold expression change versus 1\u0026thinsp;\u0026plusmn;\u0026thinsp;0, 0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11, and 22.91\u0026thinsp;\u0026plusmn;\u0026thinsp;4.12, p\u0026thinsp;=\u0026thinsp;0.0014, p\u0026thinsp;=\u0026thinsp;0.0014, and p\u0026thinsp;=\u0026thinsp;0.0031, respectively). Similar results were also observed regarding this cytokine at the protein level in mentioned groups (422.66\u0026thinsp;\u0026plusmn;\u0026thinsp;31.64 pg/ml versus 7.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52 pg/ml, 8.66\u0026thinsp;\u0026plusmn;\u0026thinsp;3.51 pg/ml, and 11.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.64 pg/ml, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, and p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, respectively).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eRegarding the TGF-β, a significant increased expression was also observed in BC-SCDi group compared to control-DMSO, control-SCDi, and BC-DMSO in mRNA levels (12.06\u0026thinsp;\u0026plusmn;\u0026thinsp;4.41 fold expression change versus 1\u0026thinsp;\u0026plusmn;\u0026thinsp;0, 0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01, and 0.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8, p\u0026thinsp;=\u0026thinsp;0.007, p\u0026thinsp;=\u0026thinsp;0.007, and p\u0026thinsp;=\u0026thinsp;0.006, respectively. These records at the protein level in the mentioned groups were as 151.66\u0026thinsp;\u0026plusmn;\u0026thinsp;6.02 pg/ml versus 11.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08 pg/ml, 9.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.64 pg/ml, and 15.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.64 p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, and p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, respectively.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3. SCD1 inhibition led to decreased expression of inflammatory cytokines in BC patients.\u003c/h2\u003e\u003cp\u003eAs presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, a significant downregulation of TNF-α was observed in BC-SCDi group compared to BC-DMSO at the mRNA level (0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36 fold expression change versus 12.66\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3, p\u0026thinsp;=\u0026thinsp;0.0018, respectively). Accordingly, similar results were also observed at the protein level in mentioned groups (25.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.64 pg/ml versus 7.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52 pg/ml, 311.0\u0026thinsp;\u0026plusmn;\u0026thinsp;16.09 pg/ml, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, respectively).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eRegarding the IL-17, a significant decreased expression was also observed in BC-SCDi group compared to BC-DMSO at the mRNA levels (21.51\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 fold expression change versus 61.53\u0026thinsp;\u0026plusmn;\u0026thinsp;28.75, p\u0026thinsp;=\u0026thinsp;0.0001, respectively. Similar results were also detected in protein level in the mentioned groups (216\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3 pg/ml versus 343.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9 pg/ml, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, respectively).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.4. \u003cem\u003eSCD1 inhibition led to increased expression of anti-inflammatory differentiative marker FoxP3 in healthy individuals.\u003c/em\u003e\u003c/h2\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the expression level of FoxP3 as anti-inflammatory differentiative marker at the mRNA and protein levels in the study groups. As indicated, an increased expression of FoxP3 was detected in BC-SCDi group compared to control-DMSO, BC-SCDi, and BC-DMSO in mRNA level (87.16\u0026thinsp;\u0026plusmn;\u0026thinsp;9.62 versus 1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0, 0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07 and 3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73, p\u0026thinsp;=\u0026thinsp;0.0001, p\u0026thinsp;=\u0026thinsp;0.0001, and p\u0026thinsp;=\u0026thinsp;0.0001, respectively). These results at the protein level were 35.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0 versus 3.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57, 4.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08, and 4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, and p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, respectively.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.5. \u003cem\u003eSCD1 inhibition led to decreased expression of inflammatory differentiative marker RORc in healthy individuals.\u003c/em\u003e\u003c/h2\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the expression level of RORc as inflammatory differentiative marker at the mRNA and protein levels in the study groups. As illustrated, decreased expression of RORc was observed in Control-SCDi group compared to control-DMSO in mRNA level (0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 versus 1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0, 0.0001\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00008, p\u0026thinsp;=\u0026thinsp;0.0001, respectively).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSimilar results were also detected in mentioned groups regarding the RORc expression in protein level (10.33\u0026thinsp;\u0026plusmn;\u0026thinsp;3.21 versus 48.66\u0026thinsp;\u0026plusmn;\u0026thinsp;8.96, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, respectively). Supplementary Table\u0026nbsp;2 also demonstrates the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard division for the measured parameters in the study groups.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe findings of the present study suggest that the enzyme SCD1 inhibits inflammation, while simultaneously promoting anti-inflammatory effects, as its chemical inhibition decreased the inflammatory cytokines TNF-a and IL-17, while simultaneously increasing the expression of the anti-inflammatory cytokines IL-10 and TGF-b in patients with luminal A breast cancer (BC) PBMCs. Accordingly, the authors were pleased to find that the present study\u0026rsquo;s current findings matched previous studies demonstrating how modifications in immune system signaling and decreases in inflammation can affect BC. Interleukins play a known role in breast cancer, and current research has demonstrated that higher levels of inflammatory cytokines are present in the serum samples and tumor tissues of BC patients. It was well-established that the presence of excessive cytokine levels in the blood of cancer patients is associated with both disease progression and migration of cancer cells into surrounding tissues (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Numerous studies have now suggested that the progression of BC along with its development is associated with inflammatory mechanisms and a dysregulated production of chemokines, including interleukin-8, which is a key mechanism for the process of cancer metastasis (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). After referring to and analyzing previous studies alongside our own, it can be deduced that inhibiting the scd1 enzyme might be valuable in the mitigation of inflammatory factors associated with the rate of growth and metastasis in breast cancer patients. Notwithstanding, further investigations in the form of human and animal trials, with more diverse sample populations, are necessary to substantiate this theory. It has been shown that the inhibition of SCD1 reduces Wnt/β-catenin signaling in cancer cells as well as the endoplasmic reticulum stress in CD8\u0026thinsp;+\u0026thinsp;T cells. These effects subsequently increases chemokine CCL4 production, recruits dendritic cells, and enhances the antitumor T cell responses. It was reported that the administration of systemic SCD1 inhibitor in mouse tumor models lead to an increasing CCL level through Wnt/β-catenin as well as the inhibition CD8\u0026thinsp;+\u0026thinsp;T cells. This in turn, leads to DCs recruitment to the tumors and ultimately to the induction of antitumor CD8\u0026thinsp;+\u0026thinsp;T cells and trapping of these cells into the tumors. The SCD1 inhibitor was also shown to activate CD8\u0026thinsp;+\u0026thinsp;T cells and DCs, directly. Moreover, overexpression of SCD1 in the non-inflammatory T-cell subset in human colon cancer and serum fatty acids have also correlated with the response rate and prognosis in patients with non-small cell lung cancer receiving an anti-PD-1 antibody (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). These findings are consistent with the results of the current study.\u003cb\u003eIn a preceding investigation\u003c/b\u003e that examined a direct effect of SCD1 inhibition on T cells, it was shown that SCD1 inhibition directly enhanced cytotoxicity and IFN-γ production of CD8\u0026thinsp;+\u0026thinsp;T cells, and this activity was associated with reduced oleic acid and esterified cholesterol in these cells. Simply adding oleic acid or oleate cholesterol would abolish this activity (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Thus, the current report are consistent with their findings. \u003cb\u003eAccording to previous findings\u003c/b\u003e, inhibition of SCD1 enhanced the immunogenicity of poorly immunogenic tumors, due to induction of endoplasmic reticulum stress and programmed cell death, and has been suggested as a novel approach to enhance T-cell based immunotherapy of tumors (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In addition, \u003cb\u003ea related study\u003c/b\u003e that looked at SCD1 enzyme inhibition on immunogenicity of tumors, it was reported that inhibition of SCD1 enhanced the immunogenic response in poorly immunogenic tumors when tumor cells underwent endoplasmic reticulum stress and subsequent apoptosis. Subsequently, this method has been suggested as a new strategy to improve T-cell based immunotherapy.\u003c/p\u003e\u003cp\u003eA clinical investigation linking the expression levels of the SCD1 enzyme with cancer prognosis found that in some cancers, such as lung and colon adenocarcinoma, high SCD1 expression was associated with advanced disease stage and poorer prognosis. Additionally, the inhibition of this enzyme was suggested as a novel potential therapeutic target (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). However, it is clear that additional clinical research in this area is warranted. In a study investigating the effects of oxidative stress and inflammatory response inflicted with disruption of signaling and fat accumulation minimally induced by diet in mice, it was reported that plasma levels of IL-10 as an anti-inflammatory cytokine were decreased in mice treated with a SFA-rich diet compared to other groups. In this study, they reported increased levels of inflammatory mediators TNF-α and interleukin-6 in Phospholipids (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn line with the results of this study, another work demonstrated that palmitate induced an inflammatory response in primary human skeletal muscle and HEK cells. Here, the exposure of HEK cells to palmitate was completely inhibited by the overexpression of the SCD1 gene. Additionally, the inflammatory response to palmitate exposure was directly related to the content of SCD1 enzyme. The data also showed that higher content of SCD1 enzyme leads to less inflammatory response to palmitate exposure contained less expression of the inflammatory cytokines IL-6, IL-8, and CXCL3 in human myotubes (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Moreover, the overexpression of the enzyme related to inflammation was shown to increase liver inflammation and acute colitis (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The absence of SCD1 in familial hypercholesterolemia mice exhibited inflammation in causing atherogenesis (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). A recent study also showed that the absence of SCD1 provided a favorable metabolic state with increased insulin sensitivity, decreased hepatic steatosis and obesity. Furthermore, SCD1 inhibition corresponds with inhibition of cancer cell proliferation. SCD1 inhibition alters cellular function by controlling inflammatory responses and stress pathways in adipocytes, liver, macrophages, aorta, skin, myocytes, beta cells, and endothelial cells (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), further confirming the findings of the current study. Additionally, in another study using metalloproteinase 3 knockout models, it was found that increased SCD1 is one of the markers associated with increased inflammation in both white adipose tissue and the liver (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSCD1 plays an important role in a variety of inflammatory and cellular stress responses by maintaining overall homeostasis between single unsaturated fatty acids (MUFA) and saturated fatty acids (SFA), where SFAs act as ligands for cell surface immune receptors such as members of the Toll-like receptor (TLR) family, and thereby promote pro-inflammatory responses (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). In contrast, MUFAs can reverse the negative impacts of SFAs on adipose tissue and liver tissue through anti-inflammatory mechanisms including increasing M2 macrophage polarization and adipose IL-10 secretion (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Most notably, increased activity of SCD1 is reflected as an increase of MUFA within macrophages that will lower the inflammatory response induced by myeloid differentiation factor 88 (MyD88) (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Furthermore, a different study showed when SCD1 was inhibited in adipocytes with chemical inhibitors, the upregulation of fatty acids like stearate significantly modulated the secretion of numerous inflammatory markers, including IL-6, MCP-1, CCL5 and induced cellular stress (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). A number of studies have also shown that lowering inflammatory mediators such as IL-17 in breast cancer (BC) patients can translate into better clinical outcomes, symptoms, and tumor growth. For example, studies in patients with BC examining the effects of resistance or endurance training reported a reduction in IL-17 and other inflammatory cytokines (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). A decrease in chronic inflammatory markers like IL-17 can counteract tumor growth, and will likely enhance antitumor immune responses through changes of cellular metabolism and better cytokine homeostasis (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Comparing the findings of this investigation to our study, which proposes chemical inhibition of the SCD1 enzyme as a viable means of suppressing inflammation, supports the claim that lipid metabolism pathways can affect the modulation of inflammatory and immune responses in tumor systems, directly or indirectly. SCD1 inhibition has been shown to interfere with inflammatory signaling pathways by decreasing the levels of monounsaturated fatty acids, thus resulting in a decrease in the levels of inflammatory mediators such as IL-17 and TNF-α, which is consistent with the overall reduction of systemic inflammation and localized tumor inflammation in the microenvironment.\u003c/p\u003e\u003cp\u003eIn contrast, research has shown that reduction in IL-17 and increase in anti-inflammatory cytokines, such as IL-10, can help to transform the immune balance towards normal control of tumor growth (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). This is backed up by our study illustration of decrease in inflammatory cytokines with SCD-1 inhibition, and can underlie a combination treatment with SCD-1 inhibition and immunomodulation. Our study also found that SCD-1 inhibition reduced levels of anti-inflammatory mediators TGF-β and IL-10 in luminal A BC patients, of importance aligning with these mediator's roles in immunosuppressive and tumor forming capacities. There has not been specific citations in the scientific literature to date that has cited this correlation in detail, and is seen as an emerging finding needing confirmation and further study in the future.\u003c/p\u003e\u003cp\u003eIn the current study, we also examined the effect of chemical inhibition of SCD1 on expression levels of the anti-inflammatory differentiation factors. We determined that the expression levels of the anti-inflammatory differentiation factor FOXP3 - at the mRNA and protein levels - in the patient was higher, while in healthy controls, inhibition of SCD1 did not significantly modified the expression level of FOXP3. Previous studies have established that FOXP3 as a major marker of Tregs in BC, plays an important role in the suppression of a tumors anti-immune response. The higher levels of Tregs and FOXP3 in tumor tissues are associated with disease progression, higher invasion or metastasis, and the capability to inhibit CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;T cells activity, which will lead to increased tumor growth and spread. Normal levels of FOXP3 are important to control the oncogenic factors in the epithelial cells of BC by regulating the expression levels of other genes (including c-Myc, LATS2, SKP2, ErbB2/HER2) which will ultimately lead to a decrease of Tregs (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). This discrepancy between our results and the previous studies maybe due to biological condition. The obtained data regarding FOXP3 maybe different in 2D culture and in vivo condition. Hence, more studies are still required to fully clarify this controversial results.\u003c/p\u003e\u003cp\u003eReflecting on the results we observed with FOXP3 regulation in the luminal A BC patients after SCD1 inhibition in this study, it is reasonable to predict that inhibiting FOXP1 in BC, would keep FOXP3 in the normal range of expression values, down regulate BC regulatory genes, and reduce the number of regulatory T cells. Similarly, our work can provide SCD1 inhibition for BC, while reproducing the above work. Further, the increase in FOXP3 within the control group after SCD1 inhibition may demonstrate a complex response, with many components that need to be investigated to see if this is an enhanced immune suppression by Tregs or the broad regulatory response found in the tumor microenvironment. Prior studies have demonstrated that the tumor microenvironment can release TGF-β and IL-6; these cytokines can induce normal Th17 cells to differentiate into CD25high Th17 cells expressing CD39 and CD73. Th17 cells are used to induce inflammation and are known to play a role in the pathogenesis of autoimmune and allergic diseases. There is still some controversy about the role of Th17 cells in cancer progression. Foxp3\u0026thinsp;+\u0026thinsp;Th17 cells are clustered in advanced BC. In human memory, CD25-high Th17 cells can suppress T-cell immune responses in BC. Th17 cells also can express ectonucleotidase (i.e., CD39) and can also infiltrate BC tumors and suppress activation of CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;cells. These cells co-express Rorγt and Foxp3 genes and produce Th17-related cytokines. Tumor infiltrating Th17 cells express the ectonucleotidase CD39 upon TGF-β and IL-6 stimulation. Finally, immunohistochemical approaches of localized BC showed that high infiltration of Th17\u0026thinsp;+\u0026thinsp;in the tumor correlates with poor clinical outcomes and nullifies the protective role of high CD8\u0026thinsp;+\u0026thinsp;infiltration. Overall, these results indicate that Th17 cells in the tumor microenvironment can suppress anticancer immune response in patients diagnosed with BC. An important study has shown that when either genetic or pharmacological approaches inhibited SCD1 in MS autoimmunity models (e.g., EAE-an animal model), there was a reduction in inflammation, and T cell and macrophage infiltration into target organs. The authors suggest that inhibition of SCD1 can change the balance of T cell subsets, as inhibition of SCD1 can block the differentiation of Th17 cells (RORγt dependent), which reduced RORγt gene expression as well as IL-17 production (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe results that chemical inhibition of SCD1 was also able to decrease the level of the inflammatory differentiation factor RORγt in a healthy controls with no comorbidity at both mRNA and protein levels were consistent with findings of the previously described study and this function of SCD1 inhibition in healthy women with no comorbidities and who are at a high risk of developing BC can be used to slow the development of BC through targeting Th17 function (RORγt-dependent). Lastly, differences among the results in the different studies could be attributed to differences in models, cancer type, patient statuses, and/or measurements. Therefore, results produced from this study can be seen as a remarkable advance in understanding how lipid metabolism regulates inflammation relative to BC. Future investigations should evaluate the impacts of SCD1 inhibition on other immune markers and pathways that will be involved.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eA quantitative analysis found that the key role of inhibition of SCD1 enzyme in the context of patients with luminal A BC that probably inhibits inflammation and enhances anti-inflammatory effect and so this means that inhibition of SCD1 can be a useful biomarker to improve the treatment process of patients with luminal A BC.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBC: breast cancer; DMSO: Dimethyl sulfoxide; FoxP3: Forkhead box protein P3; ROR\u0026gamma;t: Retinoic acid-related orphan receptor gamma t; SCD1: Stearoyl CoA-desaturase 1; TGF-\u0026beta;: Transforming growth factor beta; TNF-\u0026alpha;: Tumor necrosis factor alpha; PBMCs: Peripheral blood mononuclear cells.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work has been done as part of the Ph.D. dissertation for Neda Naghashi. The authors are grateful to acknowledge Department of Biology, School of Natural Sciences, University of Tabriz, Tabriz, Iran for their great help.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOur study was funded by Hematology and Oncology Research Center at Tabriz University of Medical Sciences, Iran [Grant No. 72345].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting Interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthor contribution statement\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNN wrote the initial draft of the manuscript and conducted the experiments. EB, and AM designed and supervised the project. ZS selected the patients under study. All authors read and approved the manuscript. The authors confirm that no paper mill and artificial intelligence was used.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData availability statement\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll data supporting the findings of this study are available within the paper and its Supplementary Information.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEthics approval\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Tabriz University of Medical Sciences (No.: IR.TBZMED.REC.1402.604).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent to Participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent to Publish\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors affirm that human research participants provided informed consent for publication of all Figures and Tables.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eClinical trial number\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;not applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSabzichi M, Ramezani M, Mohammadian J, Ghorbani M, Mardomi A, Najafipour F, et al. 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Interaction of aryl hydrocarbon receptor and NF-\u0026kappa;B subunit RelB in breast cancer is associated with interleukin-8 overexpression. Archives of biochemistry and biophysics. 2011;512(1):78-86.\u003c/li\u003e\n\u003cli\u003eKatoh Y, Yaguchi T, Kubo A, Iwata T, Morii K, Kato D, et al. Inhibition of stearoyl-CoA desaturase 1 (SCD1) enhances the antitumor T cell response through regulating \u0026beta;-catenin signaling in cancer cells and ER stress in T cells and synergizes with anti-PD-1 antibody. Journal for Immunotherapy of Cancer. 2022;10.\u003c/li\u003e\n\u003cli\u003eSugi T, Katoh Y, Ikeda T, Seta D, Iwata T, Nishio H, et al. SCD1 inhibition enhances the effector functions of CD8+ T cells via ACAT1‐dependent reduction of esterified cholesterol. Cancer science. 2024;115(1):48-58.\u003c/li\u003e\n\u003cli\u003evon Roemeling CA, Caulfield TR, Marlow L, Bok I, Wen J, Miller JL, et al. Accelerated bottom-up drug design platform enables the discovery of novel stearoyl-CoA desaturase 1 inhibitors for cancer therapy. Oncotarget. 2017;9(1):3.\u003c/li\u003e\n\u003cli\u003eTamer F, Ulug E, Akyol A, Nergiz-Unal R. The potential efficacy of dietary fatty acids and fructose induced inflammation and oxidative stress on the insulin signaling and fat accumulation in mice. Food and chemical toxicology. 2020;135:110914.\u003c/li\u003e\n\u003cli\u003eFlowers MT, Keller MP, Choi Y, Lan H, Kendziorski C, Ntambi JM, et al. Liver gene expression analysis reveals endoplasmic reticulum stress and metabolic dysfunction in SCD1-deficient mice fed a very low-fat diet. Physiological genomics. 2008.\u003c/li\u003e\n\u003cli\u003eChen C, Shah YM, Morimura K, Krausz KW, Miyazaki M, Richardson TA, et al. Metabolomics reveals that hepatic stearoyl-CoA desaturase 1 downregulation exacerbates inflammation and acute colitis. 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Cell metabolism. 2020;32(1):128-43. e5.\u003c/li\u003e\n\u003cli\u003eSun Q, Xing X, Wang H, Wan K, Fan R, Liu C, et al. SCD1 is the critical signaling hub to mediate metabolic diseases: mechanism and the development of its inhibitors. Biomedicine \u0026amp; Pharmacotherapy. 2024;170:115586.\u003c/li\u003e\n\u003cli\u003eRalston JC, Metherel AH, Stark KD, Mutch DM. SCD1 mediates the influence of exogenous saturated and monounsaturated fatty acids in adipocytes: effects on cellular stress, inflammatory markers and fatty acid elongation. The Journal of nutritional biochemistry. 2016;27:241-8.\u003c/li\u003e\n\u003cli\u003ePournemati P, Hooshmand Moghadam B. The effect of 12 Weeks of interval and continuous training on serum levels of interleukin-17 and interleukin-10 in postmenopausal breast cancer survivors: a clinical trial. Iranian Journal of Breast Diseases. 2021;14(2):4-15.\u003c/li\u003e\n\u003cli\u003eRadmehr L, KALANTARI KB, KAZEMI A. The effect of 8 weeks of endurance training on serum levels of IL-10 and IL-17 in elderly women with breast cancer. 2016.\u003c/li\u003e\n\u003cli\u003eKazemi A, Agha Alinejad H, Eslami R, Ehsan P, Baghaei R, Dabaghzadeh R, et al. Investigating the Effect of Endurance Training on Tumor Level of IL-8 and Serum Level of IL-17 in Female Mice with Breast Cancer. Journal of Advanced Biomedical Sciences. 2015;5(3):347-55.\u003c/li\u003e\n\u003cli\u003eShou J, Zhang Z, Lai Y, Chen Z, Huang J. Worse outcome in breast cancer with higher tumor-infiltrating FOXP3+ Tregs: a systematic review and meta-analysis. BMC cancer. 2016;16:1-8.\u003c/li\u003e\n\u003cli\u003eGrajchen E, Loix M, Baeten P, C\u0026ocirc;rte-Real BF, Hamad I, Vanherle S, et al. Fatty acid desaturation by stearoyl-CoA desaturase-1 controls regulatory T cell differentiation and autoimmunity. Cellular \u0026amp; molecular immunology. 2023;20(6):666-79.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Luminal A breast cancer, Stearoyl CoA desaturase 1, Inflammation, Immune response","lastPublishedDoi":"10.21203/rs.3.rs-6911415/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6911415/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose:\u003c/strong\u003e Breast cancer (BC) is the most prevalent female cancer globally. A key feature of cancer cells is a remarkable alteration in lipid composition, notably an enrichment in monounsaturated fatty acids. This change results from upregulated expression of enzymes involved in fatty acid metabolism, such as stearoyl CoA desaturase 1 (SCD1) which may affect the immune-related responses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatients and Methods\u003c/strong\u003e In the present study, 20 patients with luminal A BC and 20 healthy controls were included based on diagnostic criteria. Then, 10 ml of peripheral blood was retrieved from each participant, and peripheral blood mononuclear cells (PBMCs) were isolated, and cultured in RPMI 1640 medium. The treatment and control groups were then treated with 3 µM of SCD1 chemical inhibitor and DMSO for 48 hours, respectively. The alteration in inflammatory markers IL-17 and TNF-α, anti-inflammatory markers IL-10 and TGF-β, inflammatory differentiation markers RORγt and anti-inflammatory differentiation markers FOXP3 were assessed through Real-time PCR. Furthermore, the amount of the respective protein was measured through the enzyme-linked immunosorbent assay method.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Chemical inhibition of SCD1 resulted in a significant downregulation of\u003cbr\u003e\nIL-17/TNF-α and upregulation of of IL-10/TGF-β expression in the patient group. Additionally, a significant upregulation of FOXP3 was observed in BC patients after SCD1 inhibition. RORγt expression was also decreased in healthy individuals after SCD1 inhibition with no effect on patient group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The results of this study suggest that SCD1 may act as a potential biomarker in the context of immune response.\u003c/p\u003e","manuscriptTitle":"Investigating the effect of stearoyl-coenzyme desaturase 1 inhibition on inflammatory and anti-inflammatory patterns in luminal A breast cancer patients peripheral blood mononuclear cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-28 05:34:13","doi":"10.21203/rs.3.rs-6911415/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-15T06:46:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-10T04:14:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-08T02:11:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"26033637129888905458089698999975681413","date":"2025-09-01T15:21:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308805495915656734475084572980775303246","date":"2025-09-01T03:05:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"163692312752144073039555415389900694956","date":"2025-07-23T14:13:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-23T04:05:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-17T14:00:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-17T13:59:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Oncology","date":"2025-06-17T07:19:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3044af36-fb5a-43c3-bf50-df299ef5514f","owner":[],"postedDate":"July 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-17T08:53:59+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-28 05:34:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6911415","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6911415","identity":"rs-6911415","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}