NDUFS1 promotes malignant breast cancer behaviors through activation of mitochondrial metabolism and PROX1/c-Myc signaling

NDUFS1 promotes malignant breast cancer behaviors through activation of mitochondrial metabolism and PROX1/c-Myc signaling | 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 NDUFS1 promotes malignant breast cancer behaviors through activation of mitochondrial metabolism and PROX1/c-Myc signaling Yen-Yun Wang, Pang-Yu Chen, Hieu D.H. Nguyen, Chih-Huang Tseng, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5968936/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Breast cancer is the most prevalent cancer among women. Previous studies demonstrated that adipose-derived stem cells (ADSCs) co-cultured with resistin promote malignant behaviors in breast cancer cells. This study explores the roles of ADSCs and the adipocytokine resistin within the breast tumor microenvironment, emphasizing their contributions to metabolic reprogramming and cancer progression. RNA sequencing analysis of metabolic reprogramming pathways revealed that breast cancer cells in co-culture with resistin-treated ADSCs exhibited elevated expression of NDUFS1, the largest subunit of mitochondrial complex I. Knockdown of NDUFS1 inhibited breast cancer cell proliferation and tumorsphere formation, whereas its overexpression enhanced these effects through mitochondrial metabolism-mediated PROX1/c-Myc signaling pathway. Furthermore, treatment with metformin, an inhibitor of NDUFS1-activated mitochondrial metabolism, reduced Myc and PROX1 expression and diminished breast cancer cell proliferation. Syngeneic orthotopic mouse model showed that NDUFS1 downregulation significantly inhibited mammary tumor growth alongside decreased expression of PROX1 and c-Myc. Also, mitochondrial metabolism inhibitors metformin and rotenone demonstrated a therapeutic effect on NDUFS1-expressing breast tumor. Collectively, this research establishes a novel mechanistic framework linking metabolic adaptations and breast cancer, paving the way for innovative therapeutic strategies aimed at targeting NDUFS1 signaling. breast cancer ADSCs resistin NDUFS1 mitochondrial metabolism Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Breast cancer is the most prevalent cancer type in women in developed countries, with obesity emerging as a crucial factor in breast cancer development, particularly in postmenopausal women. Epidemiological studies demonstrate higher incidence and poorer prognosis (Chan et al., 2014 ), with research recently focusing on the role of adipocytokines and adipose-derived stem cells (ADSCs) in the breast tumor microenvironment (DeRose et al., 2011 ). As obesity progresses, adipose tissue expands and triggers excessive production of adipocytokines, leading to the proliferation of ADSCs (An et al., 2023 ; Calle and Thun, 2004 ). These ADSCs are subsequently recruited to the tumor site and release various chemokines, growth factors and adipocytokines such as resistin and visfatin - that have been shown to correlate with more aggressive breast cancer behavior and decreased patient survival (Freese et al., 2015 ; Hung et al., 2016 ; Lee et al., 2012 ; Lee et al., 2011 ; Wang et al., 2018a ; Zhang et al., 2009 ). Adipose tissue surrounding the mammary glands consists of heterogenous mix of adipocytes and stromal cells including ADSCs (Bourin et al., 2013 ). ADSCs, a form of multipotent mesenchymal stem cells (MSCs), possess the capability to differentiate into adipocytes, osteocytes, chondrocytes, or myocytes when exposed to specific lineage-inducing factors, with secretory factors from the breast cancer microenvironment responsible for inducing differentiation capability (Maysaa El Sayed et al., 2011 ). The secretome of ADSCs contains a diverse array of substances including cytokines, growth factors, angiogenic factors, adipokines, and neurotrophic factors, some of which are implicated in tumor progression and epithelial-mesenchymal transition (EMT) (Dubey et al., 2018 ), such as insulin-like growth factor (IGF), hepatocyte growth factor (HGF), VEGF, and IL8. Obesity-associated adipocytokines promote malignant breast cancer cell behaviors, including proliferation, migration and invasion, through autocrine, paracrine, and endocrine pathways (Divella et al., 2016 ; Hoy et al., 2017 ; Tahergorabi et al., 2016 ). Among these adipocytokines, elevated levels of leptin, resistin, and visfatin in the tumor microenvironment are associated with breast cancer progression (Al-Suhaimi and Shehzad, 2013 ; Chen et al., 2006 ; Gnerlich et al., 2013 ; Wang et al., 2021b ). Resistin, a 12.5 kDa cysteine-rich adipocytokine, was initially identified for its role in insulin resistance and other non-oncologic pathways including inflammatory processes such as atherosclerosis (Steppan et al., 2001 ). More recently, its importance as a key oncogenic driver has been clarified in multiple cancer subtypes such as colon, prostate, endometrium, and breast (Hlavna et al., 2011 ; Housa et al., 2008 ; Koerner et al., 2005 lăgeanu et al., 2010 ). Our previous research has demonstrated that resistin promotes breast cancer cell proliferation, migration, and stemness by activating the TLR4/NF-κB/STAT3 signaling pathway, and may additionally act via CXCL5 to enhance migration and invasion (Jiang et al., 2016 ; Tarkowski et al., 2010 ; Wang et al., 2018a ; Wang et al., 2022 ). Other groups have noted that resistin triggers the ezrin and moesin proteins, influencing metastasis (Lee et al., 2016 ). Recently, the role of adipocytokines as a critical driver of obesity associated cancer progression has emerged in relation to metabolic reprogramming, including mitochondrial and lipid metabolism (Pham and Park, 2021 ). However, the influence of resistin on metabolic reprogramming in breast cancer is as yet undefined. Metabolic reprogramming - particularly in oxygen sensing and energy metabolism (Bai and Cui, 2023 ; Sajnani et al., 2017 ) - is a hallmark of cancer cells, ensuring sustained cell growth and proliferation in the face of a harsh tumor microenvironment (Kroemer and Pouyssegur, 2008 ; Puchades-Carrasco and Pineda-Lucena, 2017 ). Mitochondria are responsible for processes such as the tricarboxylic acid (TCA) cycle, oxidative phosphorylation (OXPHOS), fatty acid oxidation (FAO) and signal exchange with other cell compartments to adjust to fluctuating metabolic demands (Castelli et al., 2023 ). One of the key metabolic phenotypes responsible for cancer cell energy generation is the preferential dependence on glycolysis rather than oxidative phosphorylation, even with normal oxygen concentrations – commonly known as the Warburg effect - and was initially thought to be related to impairment of mitochondrial OXPHOS. However, recent studies challenge these assumptions and indicate that mitochondrial OXPHOS, regulated by the electron transport chain (ETC) complexes I to IV, is largely intact and in some instances upregulated in cancers (Moreno-Sanchez et al., 2007 ; Weinberg and Chandel, 2015 ). A meta-analysis examining normal and cancer cell lines indicated that OXPHOS contributes to 80% of relative ATP production in normal cells and 83% in cancer cells (Zu and Guppy, 2004 ). Inhibition of OXPHOS has shown therapeutic efficacy in several cancer subtypes (Ashton et al., 2018 ). Breast cancer of basal-like subtype with frequent RB1 loss and p53 disruption exhibits an elevated mitochondrial metabolism (Jones et al., 2016 ). Breast cancer cells display higher complex IV activity compared to adjacent stromal and normal ductal epithelial cells (Whitaker-Menezes et al., 2011 ). In this study, metabolic reprogramming related to resistin’s effects on ADSC-breast tumor cell interactions was investigated. In this regard, the potential of NADH:ubiquinone oxidoreductase core subunit S1 (NDUFS1) - the largest subunit of mitochondrial complex I and which catalyzes the first step of nicotinamide adenine dinucleotide (NADH) oxidation – was evaluated as a clinical indicator of breast cancer progression and patient outcome. Additionally, the cellular mechanism of NDUFS1 in regulating breast cancer cell proliferation and stemness in vitro and in vivo was explored. Herein, this study delineates a novel NDUFS1-associated mitochondrial metabolic pathway that may aid in the development of innovative metabolic approaches in breast cancer therapy. Results Clinical association of NDUFS1 with breast cancer progression and patient outcomes The gene expression profiles of MDA-MB-231 cells co-cultured with resistin-treated ADSCs or untreated ADSCs were analyzed by RNAseq. To identify metabolic enzymes associated with resistin-treated ADSCs that promote breast cancer progression, we analyzed genes that were differentially expressed (1.5 folds, p < 0.05) between the two MDA-MB-231-ADSCs co-culture groups. Among the four mitochondrial complexes, we found that NDUFS1, the largest subunit of mitochondrial complex I, had the greatest increase in expression in MDA-MB-231 cells co-cultured with resistin-treated ADSCs compared to that co-cultured with untreated ADSCs (Fig. 1 B). Mitochondrial complex I has 45 subunits that are encoded by mitochondrial DNA (mtDNA) and nuclear DNA (nDNA). Among the core subunits, seven subunits including NDUFS1, NDUFS2, NDUFS3, NDUFS7, NDUFS8, NDUFV1, and NDUFV2 are encoded by nDNA. NDUFS1, NDUFV1, and NDUFV2 are components of the NADH dehydrogenase module and NDUFS2, NDUFS3, NDUFS7, and NDUFS8 are components of the NADH hydrogenase module (Sharma et al., 2009 ). Notably, NDUFS1 is the largest subunit of mitochondrial complex I. The data were then confirmed using western blot analysis, which showed higher NDUFS1 expression in MDA-MB-231 cells co-cultured with resistin-treated ADSCs (Fig. 1 C). From the Oncomine database, the expression level of NDUFS1 transcripts was found to be significantly higher in invasive ductal breast carcinoma tissues than that in normal breast tissues (Fig. 1 D). To evaluate the protein expression of NDUFS1 in breast cancer, immunohistochemical analysis was performed on breast cancer tissues and normal tissues. Our data showed an elevated level of NDUFS1 expression in breast cancer tissues compared to that in normal tissues (Fig. 1 E). Moreover, Kaplan-Meier survival analyses using publicly available breast cancer microarray datasets showed that a high expression level of NDUFS1 was significantly associated with worse overall survival in breast cancer patients (Fig. 1 F). In addition, we further analyzed the correlation of NDUFS1 protein expression and clinical behaviors. As shown in Table 1 , NDUFS1 is positively associated with stage and tumor size. Table 1 The association of NDUFS1 expression and clinicopathological characteristics of breast cancer patients using logistic regression. Variable NDUFS1 Low High N (%) N (%) p -value crud OR (95% CI) p -value adj OR (95% CI) Total 90 (57.7) 66 (42.3) Stage I 21 (31.8) 12 (13.3) 0.0052 1 - II-IV 45 (68.2) 78 (86.7) 3.03 (1.35–6.74) - Grade I 9 (13.6) 8 (8.9) 0.35 1 0.84 1 II + III 57(86.4) 82 (91.1) 1.62 (0.59–4.55) 1.12 (0.37–3.41) Age(years) < 65 56 (84.9) 79 (87.8) 0.60 1 0.44 1 ⩾65 10 (15.2) 11 (12.2) 0.78 (0.31–1.99) 0.68 (0.25–1.82) BMI(kg/m2) < 24 39 (59.1) 50 (55.6) 0.66 1 0.71 1 ⩾24 27 (40.9) 40 (44.4) 1.16 (0.61–2.21) 1.14 (0.57–2.28) T status T1 34 (51.5) 24 (26.7) 0.0015 1 0.0038 1 T2-T4 32 (48.5) 66 (73.3) 2.92 (1.50–5.78) 2.84 (1.40–5.75) LN metastasis N0 29 (43.9) 28 (31.1) 0.1008 1 0.41 1 N1-3 37 (56.1) 62 (68.9) 1.74 (0.90–3.37) 1.35 (0.66–5.75) ER status Positive 43 (65.1) 57 (63.3) 0.82 1 0.47 1 Negative 23 (34.9) 33 (36.7) 1.08 (0.56–2.11) 1.47 (0.52–4.16) PR status Positive 36 (54.6) 51 (56.7) 0.79 1 0.56 1 Negative 30 (45.5) 39 (43.3) 0.92 (0.48–1.74) 0.73 (0.26–2.06) HER2 status Negative 19 (28.8) 26 (28.9) 0.99 1 0.99 1 Positive 47 (71.2) 64 (71.1) 1.00 (0.50–2.04) 1.05 (0.49–2.26) NDUFS1 promoted breast cancer cell proliferation and stemness Endogenous protein expression of NDUFS1 was examined in six human breast cancer cell lines, including ZR-75-1, T-47D, MCF-7, BT-549, Hs 578T, and MDA-MB-231 cells (Sup. Fig. S1 A). NDUFS1 protein expression in MDA-MB-231 and MCF-7 cells was downregulated using shRNA clones #1 and #2 which showed better knockdown efficiency compared to the other four clones (Sup. Fig. S1 B). The effects of NDUFS1 knockdown (KD) and overexpression (OE) on breast cancer cell proliferation was analyzed using the XTT assay. Knockdown of NDUFS1 (Fig. 2 A) significantly decreased MDA-MB-231 and MCF-7 cell proliferation (Fig. 2 B), whereas overexpression of NDUFS1 (Fig. 2 C) significantly increased MDA-MB-231 and MCF-7 cell proliferation (Fig. 2 D). Tumorsphere formation assay has been widely used for the determination of cancer cell stemness (Dianat-Moghadam et al., 2023 ; Yakisich et al., 2017 ). Using the tumorsphere formation assay, we observed that knockdown of NDUFS1 in MCF-7 cells reduced tumorsphere formation (Fig. 2 E). Western blotting was further applied to evaluate stemness markers in MCF-7 and 4T1 cell lines, and we found that knockdown of NDUFS1 significantly suppressed c-Myc expression in MDA-MB-231 and MCF-7 cell lines (Sup. Fig. S1 C), while overexpression of NDUFS1 enhanced c-Myc expression (Fig. 2 F). Additionally, we found a positive correlation between NDUFS1 and MYC expression (p = 0.046) using the TCGA-BRCA online database (Fig. 2 G). We further employed immunohistochemical staining to explore the correlation between NDUFS1 and MYC, and a positive correlation between NDUFS1 expression and c-MYC expression (Fig. 2 H) was observed in breast tumor tissues from breast cancer patients. Taken together, these data suggested that alteration of NDUFS1 expression affects cancer cell growth in breast cancer cells, and shows the properties of cancer stemness-associated growth (Ponomarev et al., 2022 ). NDUFS1 promoted malignant breast cancer cell behaviors via activation of mitochondrial metabolism In this study, we noted an association between NDUFS1 and cancer cell stemness (Fig. 2 ), which suggests the involvement of mitochondrial metabolism in oncogenesis. Therefore, we further examined the role of mitochondrial metabolism in NDUFS1-associated cancer cell progression. Using CLARIOstar, we found that knockdown of NDUFS1 decreased the oxygen consumption rate (OCR), an indicator of impaired mitochondrial metabolism, while overexpression of NDUFS1 increased the OCR (Fig. 3 A-B). Further Seahorse assays showed downregulated basal OCR, ATP production, maximal respiration and spare respiratory capacity when NDUFS1 was knocked down (Fig. 3 C-D). Furthermore, NDUFS1-induced MDA-MB-231 and MCF-7 cell proliferation (Fig. 3 E) was reduced by the mitochondrial complex inhibitor metformin, when treated at a concentration that did not affect cancer cell viability (Yuan et al., 2023b ). Notably, NDUFS1 knockdown in MDA-MB-231 and MCF-7 cells also decreased the extracellular acidification rate (ECAR) (Sup. Fig. S2). NDUFS1 promoted breast cancer cell proliferation and stemness via mitochondrial metabolism-activated PROX1/c-Myc pathway Using RNAseq, a total of 6 genes were identified across the two domains (proliferation and stemness) when MDA-MB-231 cells with or without NDUFS1 knockdown were compared. Three genes were shared by the three domains, namely PROX1, MEF2C and WNT5A (Fig. 4 A). Although both real time PCR and TCGA database confirmed the association of NDUFS1 with MEF2C and WNT5A (Sup. Fig. S3 A and B), further Kaplan-Meier survival analysis using publicly available breast cancer microarray datasets showed that MEF2C and WNT5A were not correlated with breast cancer survival (Sup. Fig. S3C), and Western blot analysis did not show significant increase of WNT5A expression when NDUFS1 was overexpressed in MDA-MB-231 cells (Sup. Fig. S3D). Conversely, knockdown of NDUFS1 decreased PROX1 expression while overexpression of NDUFS1 increased PROX1 expression (Fig. 4 B). In addition, there was a positive correlation between NDUFS1 and PROX1 expression (p = 2.6e-7), determined using the TCGA-BRCA online database (Fig. 4 C). We also used immunohistochemical staining to study the correlation between NDUFS1 and PROX1 proteins, and a positive correlation between NDUFS1 expression and PROX1 expression was observed in breast tumor tissues from breast cancer patients (Fig. 4 D). Kaplan-Meier survival analyses using publicly available breast cancer microarray datasets showed that high levels of PROX1 expression were significantly associated with worse overall survival in breast cancer patients (p = 0.019) (Fig. 4 E). We also found that inhibition of PROX1 by siPROX1 reduced the expression of c-Myc while inhibition of c-Myc by shMYC did not affect the expression of PROX1 (Fig. 4 F). NDUFS1 knockdown inhibited orthotopic breast tumor growth and tumoral expression of PROX1 and c-Myc in vivo The in vivo effect of NDUFS1 on breast tumor growth was evaluated using syngeneic BALB/c mouse model using luciferase-expressing 4T1 mouse breast cancer cells. The efficiency of NDUFS1 knockdown in 4T1 cells was first confirmed by Western blot analysis ( Fig. 5 A). Further studies showed decreased 4T1 cell proliferation and stemness property when NDUFS1 was knocked down in 4T1 cells (Fig. 5 B-D). 4T1 cells with NDUFS1 knockdown were injected into the left fourth mammary fat pad of mice, and tumor volume and bioluminescent signal from in vivo imaging system (IVIS) were measured weekly. At the end of the experiment, the NDUFS1 knockdown group demonstrated decreased bioluminescent signal (Fig. 5 E), tumor volume (Fig. 5 F) and tumor weight (Fig. 5 G). Further immunohistochemical analysis of the tumor tissues showed that the expression of NDUFS1, PROX1 and c-Myc was decreased in the NDUFS1 knockdown group (Fig. 6 A-C). In addition, NDUFS1 expression in the tumor tissues was positively correlated with PROX1 (p = 0.0018) and c-Myc (p = 0.0008) (Fig. 6 D-E). Therapeutic effects of mitochondrial metabolism inhibitors metformin and rotenone on NDUFS1-expressing breast tumor To study the therapeutic effects of mitochondrial metabolism inhibitors metformin and rotenone on NDUFS1-expressing breast cancer in vivo, female BALB/c mice, after generation of orthotopic breast tumors were injected with metformin and rotenone into the peritoneal cavity five times per week and were sacrificed after four weeks of treatment. As shown in Fig. 7 , bioluminescent signal in tumor (Fig. 7 A), tumor volume (Fig. 7 B) and tumor weight (Fig. 7 C) were significantly higher in Luc group mice than NDUFS1 knockdown mice and treatment of metformin and rotenone reversed the tumor growth in Luc group mice. Furthermore, analysis of the orthotopic tumors by immunohistochemical analysis showed that the expression of NDUFS1 (Fig. 7 D), PROX1 (Fig. 7 E) and c-Myc (Fig. 7 F) was higher in the Luc group mice, which was decreased after treatment with metformin and rotenone. Discussion The data presented here provide evidence for a novel metabolic reprogramming role for resistin in the breast tumor microenvironment, acting via ADSC intermediaries to upregulate expression of NDUFS1. This, in turn, promotes mitochondrial metabolism and breast cancer stemness via the PROX1/c-Myc pathway, resulting in breast cancer progression both in vitro and in vivo (Fig. 7 G). Resistin-treated ADSCs promote breast cancer development via NDUFS1/PROX-1/c-Myc pathway A significant increase of NDUFS1 expression in breast cancer cells co-cultured with resistin-treated ADSCs was observed in this study. Although low NDUFS1 expression has been associated with poorer clinical outcomes and cancer progression in renal cell, non-small cell lung and gastric carcinomas (Chen et al., 2023 ; Ellinger et al., 2017 ; Su et al., 2016 ), we found that increased NDUFS1 expression led to breast cancer progression, via activation of mitochondrial metabolism and PROX-1/c-Myc pathway. c-Myc has previously been reported to be highly expressed during breast cancer development (Deng et al., 2023 ; Liao and Dickson, 2000 ), and bioinformatics analyses have shown an interaction between c-Myc and NDUFS1, which leads to tumorigenicity in non-small cell lung cancer (Su and Hsiao, 2013 ) Additionally, in the present study NDUFS1 was found to activate PROX-1, with clinicopathological analysis revealing a positive correlation between the expression of NDUFS1 and the expression of PROX-1 and c-Myc in breast cancer tissues. Likewise, elevated expression of PROX-1 mRNA has been found in other cancers including neuroblastoma, glioma, lung carcinoid tumor, small cell lung carcinoma, colon cancer, liver carcinoma, and rhabdomyosarcoma (Elsir et al., 2012 ). PROX-1 drives the transition from benign to malignant phenotypes through alterations in cell polarity, extracellular matrix interactions and cell adhesion (Petrova et al., 2008 ), and promotes breast cancer cell invasion and metastasis via WNT/β-catenin signaling pathways (Zhu et al., 2022 ). However, a recent study has also demonstrated that PROX1, via inhibition of c-Myc expression, suppresses breast cancer cell proliferation (Michail et al., 2023 ). Further studies are required to explain these contradictory findings. Resistin exerts direct and indirect oncologic effects in breast cancer These findings add to the accumulating evidence that resistin plays a truly diverse oncogenic role in breast cancer, extending to metabolic reprogramming in the tumor microenvironment. Previously, we and others have demonstrated that resistin exerts effects both directly on breast cancer cells, and indirectly via the secretome of resistin treated ADSCs. These direct effects include increased breast cancer cell growth and stemness through STAT3 activation downstream of IL-6 (Deshmukh et al., 2015 ; Wang et al., 2018b ); and toll-like receptor 4 (TLR4)-mediated NF-κB signaling (Wang et al., 2018a ). Indirect effects mediated by the secretome of resistin treated ADSCs include enhanced migration and invasion via CXCL5 (Wang et al., 2022 ). Interestingly, EMT and mitochondrial metabolism may act co-operatively, with EMT both inducing and being the consequence of metabolic reprogramming. EMT may induce metabolic rewiring, due to the motility and invasiveness of mesenchymal cells exerting increased metabolic demands after the epithelial transition. Yet, similar to the present study, metabolic reprogramming may itself lead to increased invasiveness and EMT induction (Lunetti et al., 2019 ). Although not the focus of this study, a mutual interplay of this nature may therefore exist between the resistin mediated NDUFS1 mitochondrial reprogramming highlighted herein, and resistin mediated CXCL5 invasion and migration noted in our previous research. Breast cancer stemness is promoted by NDUFS1 Cancer stemness, characterized by an increased capacity for self-renewal and enhanced motility of cancer cells, is strongly linked to tumor recurrence and metastasis in breast cancer (Lee et al., 2019 ; Velasco-Velazquez et al., 2011 ). In the present study, we observed that NDUFS1 promoted cancer stemness-related properties in breast cancer cells, including self-proliferation and increased tumorsphere formation. Additionally, knockdown of NDUFS1 suppressed the expression of c-Myc while overexpression of NDUFS1 enhanced c-Myc expression in breast cancer cells (Fig. 2 F and Sup. Fig. S 2C-D). Since c-Myc is a transcription factor linking stemness and malignancy (Liu et al., 2021 ), our results suggest that NDUFS1 may play a key role in regulating breast cancer cell proliferation and stemness. NDUFS1 upregulates the PROX1/c-Myc pathway through activation of mitochondrial metabolism Modification of cellular energy and redox status through mitochondrial metabolic reprogramming is strongly linked with cancer progression (Bian et al., 2022 ; Zheng, 2012 ). Targeting the inhibition of mitochondrial complexes has emerged as a novel and promising strategy for cancer treatment (Bian et al., 2022 ; Yan et al., 2021 ). Our in vitro data demonstrated that NDUFS1 overexpression increased the rate of mitochondrial oxidative metabolism to promote breast cancer cell proliferation and stemness, which were reversed by the anti-diabetic drugs metformin and phenformin, both of which inhibit mitochondrial metabolism (Vasan et al., 2020 ). Limitations and future work A limitation of this study is that the detailed mechanism regarding how resistin activates NDUFS1 to promote malignant breast cancer cell behaviors remains undefined. The cytokine in the resistin-treated ADSC secretome responsible for the elevation of NDUFS1 levels has yet to be identified. The cross-talk between PROX1 and c-Myc deserves further exploration, such as the binding sites for PROX1 on the promoter region of c-Myc for transcriptional activation. Furthermore, apart from the effect of metformin and phenformin in vitro, the potential of these drugs should be investigated in vivo to explore the therapeutic effect of metformin/phenformin on breast cancer in pre-clinical study. Although a recent randomized controlled trial in 3649 patients failed to find a positive benefit from metformin for invasive disease-free survival in breast cancer, our study provides evidence that may point toward the need for stratification of patients with higher resistin levels (and therefore by association NDUFS1) when designing future clinical trials, considering factors such as BMI and post-menopausal status (Goodwin et al., 2022 ). Conclusion Together these data support the increasingly diverse role of resistin in breast cancer, with this study demonstrating its scope includes metabolic reprogramming via ADSCs in the tumor microenvironment. A novel NDUFS1/PROX1/c-Myc pathway may play a critical role in breast cancer development and may additionally provide an avenue for repurposing of metabolic drugs such as metformin. Materials and Methods Patient samples Breast tumor tissues were obtained from patients at Kaohsiung Medical University Hospital (KMUH), Taiwan, and confirmed using clinical and histological data from the Cancer Registry. This study was approved by the Institutional Review Board of Kaohsiung Medical University Hospital (approval numbers KMUHIRB-E(I)-20180136 and KMUHIRB-E(I)-20190424), and patient informed consent was waived for the de-identified patient samples. Cell culture Human breast carcinoma cell lines MDA-MB-231, MCF-7, T-47D, ZR-75-1, BT-549, Hs-578T and the mouse breast carcinoma cell line 4T1 were purchased from the Bioresource Collection and Research Center (BCRC, Hsinchu, Taiwan). MDA-MB-231, MCF-7, T-47D, and BT-549 cells were maintained in Dulbecco's Modified Eagle Medium (Gibco), while Hs-578T, ZR-75-1, and 4T1 cells were cultured in Roswell Park Memorial Institute 1640 (Gibco) with 5% CO 2 at 37°C in a humidified incubator. All culture media were supplemented with 10% fetal bovine serum (Biological Industries) and 1% penicillin /streptomycin/amphotericin B (Sartorius). Gene knockdown and overexpression of NDUFS1 To knock down NDUFS1 expression in MDA-MB-231 and MCF-7 cell lines, lentivirus carrying a pLKO.1_puro lentiviral vector (ordered from National RNAi Core Facility, Academia Sinica, Taipei, Taiwan) that expressed double-stranded short hairpin (sh)RNA oligonucleotides targeting the sequences of human NDUFS1 was used (Clone 1, ID: TRCN000006463; Clone 2, ID: TRCN0000064632), while a pLKO.1_puro lentiviral vector (ordered from National RNAi Core Facility, Academia Sinica, Taipei, Taiwan) expressing shRNA targeting firefly luciferase, unrelated to the human genome sequence, was used as a negative control (ID: TRCN000072249). Lentiviral infection was achieved by adding the viral solution to cells in culture media containing 8 g/ml polybrene. For selection, 2 µg/ml puromycin was added 48 hours after infection. Selected cells were cultured in 2 µg/ml puromycin for the duration of the experiment. To overexpress NDUFS1 in MDA-MB-231 and MCF-7 cell lines, ready-to-use lentiviral particles containing the pReceiver lentiviral vector which expressed human NDUFS1 gene were purchased from Topgen. For negative control, lentiviral particles which carried an empty lentiviral vector were used (Topgen). Lentiviral infection was performed by adding the viral solution to cells, with culture media containing 8 g/ml polybrene. After infection for 48 hours, 2 µg/ml puromycin was added for selection. Selected cells were cultured in 2 µg/ml puromycin for the duration of the experiment. Co-culture for RNA sequencing ADSCs were incubated in the presence or absence of 50 ng/ml resistin for 48 hours (Wang et al., 2022 ). MDA-MB-231 cells were seeded in the lower chamber of a 6-well plate while ADSCs were seeded in the upper insert (0.4 µm pores, CoStar) for 72 hours. At the indicated time point, total RNA from MDA-MB-231 cells was extracted using Trizol® Reagent (Invitrogen, USA) according to the manufacturer's instructions. Purified RNA was quantified at OD260nm using a ND-1000 spectrophotometer (Nanodrop Technology, USA) and RNA quality was assessed using a Bioanalyzer 2100 (Agilent Technology, USA) with RNA 6000 LabChip kit (Agilent Technology, USA). All RNA sample preparation and RNA sequencing procedures were carried out according to Illumina's official protocol and a previous report (Wang et al., 2021a). XTT cell viability assay The cells were seeded onto 96-well plates at a density of 4×10 3 cells per well for MDA-MB-231 and MCF-7 cells, and 6×10 3 cells per well for 4T1 cells. For XTT assay, the procedure followed the methods described in a previous report (Yuan et al., 2024 ). Tumorsphere formation assay MCF-7 and 4T1 cells were seeded in ultra-low attachment 96-well plates (Corning) at a density of 500 cells per well with serum-free cell culture medium supplemented with 20 ng/ml recombinant human fibroblast growth factor basic, 20 ng/ml recombinant human epidermal growth factor, 10 µg/ml insulin and 1 × B27. After 14 days of cell incubation, images of tumorspheres larger than 50 µm in diameter were captured using a light microscope (Nikon) and analyzed using ImageJ software ( https://imagej.nih.gov/ij/ ). Real-time PCR Total RNA was extracted using Trizol reagent (Ambion). Real-time PCR reactions were performed on the AriaMx Real-Time PCR System (Agilent Technologies, USA) using Brilliant III Ultra-Fast SYBR Green Low ROX qPCR Master Mix (Agilent Technologies, USA). The fold expression or repression of the target gene relative to the internal control gene TBP in each sample was then calculated by the formula: 2 -△△Cq where △Cq = Cq target gene – Cq internal control and △△Cq = △Cq test sample - △Cq control sample Western blot The detailed procedure followed a previous report (Yuan et al., 2024 ). The primary antibodies used for Western blot analysis included NDUFS1 (1:1000, GeneTex, GTX113787), c-Myc (1:1000, Abcam, ab32072), PROX1 (1:1000, GeneTex, GTX129143), CD44 (1:1000, GeneTex, GTX102111), Oct4 (1:1000, GeneTex, GTX627419), CD133 (1:1000, GeneTex, GTX100567), ALDH1A1 (1:5000, GeneTex, GTX123973), Nanog (1:1000, GeneTex, GTX100863), KLF4 (1:1000, Abcam, ab151733), ALDH2 (1:1000, GeneTex, GTX101429), Notch1 (1:1000, Cell Signaling, #3608), SOX2 (1:3000, GeneTex, GTX101507), MEF2C (1:2500, GeneTex, GTX105433), Wnt-5a (1:250, Abcam, ab229200), GAPDH (1:60000, GeneTex, GTX100118), and α-Tubulin (1:10000, Genetex, GTX112141). Immunohistochemistry For immunohistochemistry (IHC), slides were baked, de-waxed, and stained with avidin-biotin complexes following our previous procedure (Wang et al., 2021a). Immunohistochemical staining for NDUFS1 (1:100, GeneTex, GTX113787) and c-Myc (1:200, Abcam, ab32072) was carried out using the automated Bond-Max system, following the manufacturer’s instructions (Leica Microsystems). For quantification, the histochemical score (H-score) was used to detect the intensity of signals, which was calculated as the products ofpercentage of stained cells and intensity of staining. The score was evaluated independently by two experts under the same imaging conditions. Extracellular O 2 consumption assay by CLARIOstar MDA-MB-231 and MCF-7 cells were seeded onto 96-well plates (black wall with clear flat bottom) at a density of 8×10 4 cells per well and incubated overnight. The medium was replaced with fresh culture medium. After addition of the extracellular O 2 consumption reagent (ab197243, Abcam, Cambridge, UK), the wells were promptly sealed with pre-warmed mineral oil. The extracellular O 2 consumption signal was measured using the CLARIOstar Plus plate reader at 1.5 minute intervals for 120 minutes at Ex/Em = 360/650 nm. Glycolysis assay MDA-MB-231 and MCF-7 cells were seeded onto 96-well plates at a density of 8×10 4 cells per well and cultured overnight. The medium was replaced with fresh culture medium. After purging CO 2 in a CO 2 -free incubator at 37°C with 95% humidity for 3 hours, the medium was replaced with the respiration buffer containing the glycolysis assay reagent (Abcam, ab197244). The glycolysis signal (lifetime signal) was measured using the CLARIOstar Plus plate reader at 1.5 minute intervals for > 120 minutes at Ex/Em = 380/615 nm. Seahorse bioscience extracellular flux analyzer for OCR Seahorse XF Analyzer (Agilent) was applied for OCR analyses. MDA-MB-231 and MCF-7 cells were seeded in 8-well Seahorse XF Cell Culture Microplates at density of 8×10 3 cells per well and cultured with 5% CO 2 at 37°C in a humidified incubator. The detailed procedure followed a previous report (Yuan et al., 2023a ). Animal study Experiments involving animals were approved by the Institutional Animal Care and Utilization Committee of Kaohsiung Medical University, Kaohsiung, Taiwan (Approval no. 108126). According to principles of 3Rs, we minimized the number of animals used in our experiments. Six-week-old female BALB/c mice were purchased from the National Laboratory Animal Center (NLAC, Taipei, Taiwan). Mice were randomized into two groups of ten. 4T1 cells expressing luciferase (1 × 10 5 cells in 50 µl normal saline and 50 µl Matrigel per mouse) were subcutaneously injected into the left fourth mammary fat pads of mice. The tumor size was measured weekly and calculated by the formula of (width² × length)/2. All mice were monitored weekly using an IVIS50 Spectrum in vivo imaging system (Xenogen) with the injection of firefly D-luciferin substrate (Biosynth). After 6 weeks, all mice were sacrificed, and the orthotopic tumors were collected for tumor weight and tumor volume measurements, followed by immunohistochemical analysis. For the study of therapeutic effects of metformin and rotenone, female BALB/c mice were randomly assigned to six groups, each consisting of eight mice. After the orthotopic tumor became measurable, injections of 1% DMSO, 200 mg/kg metformin, and 2.5 mg/kg rotenone were administered into the peritoneal cavity of the mice at a frequency of five times per week. After four weeks of treatment, all mice were sacrificed, and orthotopic tumors were collected for the assessment of tumor weight and volume, followed by immunohistochemical analysis. Statistical analysis Statistical analyses were performed using the SPSS 14.0 statistical package (SPSS). The cut off point for high and low NDUFS1 level was determined by the receiver operating characteristic (ROC) curve. The associations between NDUFS1 level and clinicopathologic characteristics were analyzed by the Chi-square test. Data from three independent experiments were analyzed by the Student t test for comparison between two groups using Prism 9.5.0 software (GraphPad). One-way analysis of variance (ANOVA) with post-hoc Tukey’s test was used for multiple group comparisons. The data were presented as mean ± SD and the P values less than 0.05 were considered statistically significant. Abbreviations ADSCs AMPK ATP HGF ECAR EMT EV ETC FAO hKD1 hKD2 IGF IHC IVIS Luc MSCs mtDNA NADH nDNA NDUFS1 NGF OCR OE OXPHOS ROS TCA TLR4 VEGF Adipose-derived stem cells AMP-activated protein kinase Adenosine triphosphate Hepatocyte growth factor Extracellular acidification rate Epithelial-to-mesenchymal transition Empty vector Electron transport chain Fatty acid oxidation Knockdown of human NDUFS1 clone 1 Knockdown of human NDUFS1 clone 2 Insulin-like growth factor Immunohistochemistry In vivo imaging system Knockdown of firefly luciferase Mesenchymal stem cells Mitochondria DNA Nicotinamide adenine dinucleotide Nuclear DNA NADH:Ubiquinone Oxidoreductase Core Subunit S1 Nerve growth factor Oxygen consumption rate Overexpression of NDUFS1 Oxidative phosphorylation Reactive oxygen species Tricarboxylic acid Toll-like receptor 4 Vascular endothelial growth factor Declarations Acknowledgments This work was supported by grants from the National Science and Technology Council (NSTC 112-2314-B-037-112-MY3, NSTC 112-2314-B-037-120) and the Center for Intelligent Drug Systems and Smart Biodevices (IDS 2 B) from the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education, Taiwan. This work was also supported by grants from Kaohsiung Medical University Hospital (KMUH109-9R44, KMUH110-0R43, KMUH111-1R37, KMUH-DK(A)110001, KMUH-DK(A)112001) and Kaohsiung Medical University (KMU-DK(A)111005, KMU-DK(A)112006, NYCUKMU-111-I002, NYCU-KMU-112-I005, KMU-TC112A03-5, NYCUKMU-113-I002), Taiwan. Declaration of Interest Statement We declare no conflict of interest References Al-Suhaimi, E.A., and A. Shehzad. 2013. Leptin, resistin and visfatin: the missing link between endocrine metabolic disorders and immunity. European journal of medical research 18:1-13. An, C., I. Pipia, A.S. Ruiz, I. Argüelles, M. An, S. Wase, and G. Peng. 2023. The molecular link between obesity and genomic instability in cancer development. Cancer Lett 555:216035. Ashton, T.M., W.G. McKenna, L.A. Kunz-Schughart, and G.S. Higgins. 2018. Oxidative Phosphorylation as an Emerging Target in Cancer Therapy. Clin Cancer Res 24:2482-2490. Bai, R., and J. Cui. 2023. Mitochondrial immune regulation and anti-tumor immunotherapy strategies targeting mitochondria. Cancer Lett 564:216223. Bian, C., Z. Zheng, J. Su, H. Wang, S. Chang, Y. Xin, and X. Jiang. 2022. Targeting Mitochondrial Metabolism to Reverse Radioresistance: An Alternative to Glucose Metabolism. Antioxidants (Basel) 11: Bourin, P., B.A. Bunnell, L. Casteilla, M. Dominici, A.J. Katz, K.L. March, H. Redl, J.P. Rubin, K. Yoshimura, and J.M. Gimble. 2013. Stromal cells from the adipose tissue-derived stromal vascular fraction and culture expanded adipose tissue-derived stromal/stem cells: a joint statement of the International Federation for Adipose Therapeutics and Science (IFATS) and the International Society for Cellular Therapy (ISCT). Cytotherapy 15:641-648. Calle, E.E., and M.J. Thun. 2004. Obesity and cancer. Oncogene 23:6365-6378. Castelli, S., F. Ciccarone, P. De Falco, and M.R. Ciriolo. 2023. Adaptive antioxidant response to mitochondrial fatty acid oxidation determines the proliferative outcome of cancer cells. Cancer Lett 554:216010. Chan, D.S., A. Vieira, D. Aune, E.V. Bandera, D. Greenwood, A. McTiernan, D.N. Rosenblatt, I. Thune, R. Vieira, and T. Norat. 2014. Body mass index and survival in women with breast cancer—systematic literature review and meta-analysis of 82 follow-up studies. Annals of Oncology 25:1901-1914. Chen, D.-C., Y.-F. Chung, Y.-T. Yeh, H.-C. Chaung, F.-C. Kuo, O.-Y. Fu, H.-Y. Chen, M.-F. Hou, and S.-S.F. Yuan. 2006. Serum adiponectin and leptin levels in Taiwanese breast cancer patients. Cancer letters 237:109-114. Chen, T., D. Li, Y. Wang, X. Shen, A. Dong, C. Dong, K. Duan, J. Ren, W. Li, G. Shu, J. Yang, Y. Xie, F. Qian, and J. Zhou. 2023. Loss of NDUFS1 promotes gastric cancer progression by activating the mitochondrial ROS-HIF1α-FBLN5 signaling pathway. Br J Cancer 129:1261-1273. Deng, L., L. Liao, Y.L. Zhang, S.Y. Hu, S.Y. Yang, X.Y. Ma, M.Y. Huang, F.L. Zhang, and D.Q. Li. 2023. MYC-driven U2SURP regulates alternative splicing of SAT1 to promote triple-negative breast cancer progression. Cancer Lett 560:216124. DeRose, Y.S., G. Wang, Y.-C. Lin, P.S. Bernard, S.S. Buys, M.T. Ebbert, R. Factor, C. Matsen, B.A. Milash, and E. Nelson. 2011. Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes. Nature medicine 17:1514-1520. Deshmukh, S.K., S.K. Srivastava, A. Bhardwaj, A.P. Singh, N. Tyagi, S. Marimuthu, D.L. Dyess, V. Dal Zotto, J.E. Carter, and S. Singh. 2015. Resistin and interleukin-6 exhibit racially-disparate expression in breast cancer patients, display molecular association and promote growth and aggressiveness of tumor cells through STAT3 activation. Oncotarget 6:11231-11241. Dianat-Moghadam, H., M. Sharifi, R. Salehi, M. Keshavarz, M. Shahgolzari, and Z. Amoozgar. 2023. Engaging stemness improves cancer immunotherapy. Cancer Lett 554:216007. Divella, R., R. De Luca, I. Abbate, E. Naglieri, and A. Daniele. 2016. Obesity and cancer: the role of adipose tissue and adipo-cytokines-induced chronic inflammation. Journal of Cancer 7:2346. Dubey, N.K., V.K. Mishra, R. Dubey, Y.-H. Deng, F.-C. Tsai, and W.-P. Deng. 2018. Revisiting the advances in isolation, characterization and secretome of adipose-derived stromal/stem cells. International journal of molecular sciences 19:2200. Ellinger, J., M. Poss, M. Bruggemann, A. Gromes, D. Schmidt, N. Ellinger, Y. Tolkach, D. Dietrich, G. Kristiansen, and S.C. Muller. 2017. Systematic Expression Analysis of Mitochondrial Complex I Identifies NDUFS1 as a Biomarker in Clear-Cell Renal-Cell Carcinoma. Clin Genitourin Cancer 15:e551-e562. Elsir, T., A. Smits, M.S. Lindstrom, and M. Nister. 2012. Transcription factor PROX1: its role in development and cancer. Cancer Metastasis Rev 31:793-805. Freese, K.E., L. Kokai, R.P. Edwards, B.J. Philips, M.A. Sheikh, J. Kelley, J. Comerci, K.G. Marra, J.P. Rubin, and F. Linkov. 2015. Adipose-derived stems cells and their role in human cancer development, growth, progression, and metastasis: a systematic review. Cancer research 75:1161-1168. Gnerlich, J.L., K.A. Yao, P.S. Fitchev, R.A. Goldschmidt, M.C. Bond, M. Cornwell, and S.E. Crawford. 2013. Peritumoral expression of adipokines and fatty acids in breast cancer. Annals of surgical oncology 20:731-738. Goodwin, P.J., B.E. Chen, K.A. Gelmon, T.J. Whelan, M. Ennis, J. Lemieux, J.A. Ligibel, D.L. Hershman, I.A. Mayer, T.J. Hobday, J.M. Bliss, P. Rastogi, M. Rabaglio-Poretti, S.D. Mukherjee, J.R. Mackey, V.G. Abramson, C. Oja, R. Wesolowski, A.M. Thompson, D.W. Rea, P.M. Stos, L.E. Shepherd, V. Stambolic, and W.R. Parulekar. 2022. Effect of Metformin vs Placebo on Invasive Disease-Free Survival in Patients With Breast Cancer: The MA.32 Randomized Clinical Trial. Jama 327:1963-1973. Hlavna, M., L. Kohút, J. Lipková, J. Bienertova-Vasku, Z. Dostalova, J. Chovanec, and A. Vasku. 2011. Relationship of resistin levels with endometrial cancer risk. Neoplasma 58:124-128. Housa, D., Z. Vernerova, J. Heracek, P. Cechak, B. Rosova, J. Kuncova, and M. Haluzik. 2008. Serum resistin levels in benign prostate hyperplasia and non-metastatic prostate cancer: possible role in cancer progression. Neoplasma 55:442. Hoy, A.J., S. Balaban, and D.N. Saunders. 2017. Adipocyte–tumor cell metabolic crosstalk in breast cancer. Trends in molecular medicine 23:381-392. Hung, A.C., S. Lo, M.-F. Hou, Y.-C. Lee, C.-H. Tsai, Y.-Y. Chen, W. Liu, Y.-H. Su, Y.-H. Lo, and C.-H. Wang. 2016. Extracellular visfatin-promoted malignant behavior in breast cancer is mediated through c-Abl and STAT3 activation. Clinical Cancer Research 22:4478-4490. Jiang, Y., L. Lu, Y. Hu, Q. Li, C. An, X. Yu, L. Shu, A. Chen, C. Niu, and L. Zhou. 2016. Resistin induces hypertension and insulin resistance in mice via a TLR4-dependent pathway. Scientific reports 6:22193. Jones, R.A., T.J. Robinson, J.C. Liu, M. Shrestha, V. Voisin, Y. Ju, P.E. Chung, G. Pellecchia, V.L. Fell, S. Bae, L. Muthuswamy, A. Datti, S.E. Egan, Z. Jiang, G. Leone, G.D. Bader, A. Schimmer, and E. Zacksenhaus. 2016. RB1 deficiency in triple-negative breast cancer induces mitochondrial protein translation. J Clin Invest 126:3739-3757. Koerner, A., J. Kratzsch, and W. Kiess. 2005. Adipocytokines: leptin—the classical, resistin—the controversical, adiponectin—the promising, and more to come. Best practice & research Clinical endocrinology & metabolism 19:525-546. Kroemer, G., and J. Pouyssegur. 2008. Tumor cell metabolism: cancer's Achilles' heel. Cancer cell 13:472-482. Lee, J.O., N. Kim, H.J. Lee, Y.W. Lee, S.J. Kim, S.H. Park, and H.S. Kim. 2016. Resistin, a fat-derived secretory factor, promotes metastasis of MDA-MB-231 human breast cancer cells through ERM activation. Scientific reports 6:18923. Lee, K.L., Y.C. Kuo, Y.S. Ho, and Y.H. Huang. 2019. Triple-Negative Breast Cancer: Current Understanding and Future Therapeutic Breakthrough Targeting Cancer Stemness. Cancers (Basel) 11: Lee, Y.-C., Y.-J. Chen, C.-C. Wu, S. Lo, M.-F. Hou, and S.-S.F. Yuan. 2012. Resistin expression in breast cancer tissue as a marker of prognosis and hormone therapy stratification. Gynecologic oncology 125:742-750. Lee, Y.-C., Y.-H. Yang, J.-H. Su, H.-L. Chang, M.-F. Hou, and S.-S.F. Yuan. 2011. High visfatin expression in breast cancer tissue is associated with poor survival. Cancer epidemiology, biomarkers & prevention 20:1892-1901. Liao, D.J., and R.B. Dickson. 2000. c-Myc in breast cancer. Endocr Relat Cancer 7:143-164. Liu, Y., C. Zhu, L. Tang, Q. Chen, N. Guan, K. Xu, and X. Guan. 2021. MYC dysfunction modulates stemness and tumorigenesis in breast cancer. Int J Biol Sci 17:178-187. Lunetti, P., M. Di Giacomo, D. Vergara, S. De Domenico, M. Maffia, V. Zara, L. Capobianco, and A. Ferramosca. 2019. Metabolic reprogramming in breast cancer results in distinct mitochondrial bioenergetics between luminal and basal subtypes. Febs j 286:688-709. Maysaa El Sayed, Z., F. Mansour, M. Ghal, and S. Abou-Zahra. 2011. Evaluation of interleukin-8 in hepatitis C virus infection: relation to combined peg-interferon ribavirin response and genotype 4. Immunological Investigations 40:29-38. Michail, A., D. Gkikas, D. Stellas, V. Kaltezioti, and P.K. Politis. 2023. Prox1 Suppresses the Proliferation of Breast Cancer Cells via Direct Inhibition of c-Myc Gene Expression. Cells 12: Moreno-Sanchez, R., S. Rodriguez-Enriquez, A. Marin-Hernandez, and E. Saavedra. 2007. Energy metabolism in tumor cells. FEBS J 274:1393-1418. Petrova, T.V., A. Nykanen, C. Norrmen, K.I. Ivanov, L.C. Andersson, C. Haglund, P. Puolakkainen, F. Wempe, H. von Melchner, G. Gradwohl, S. Vanharanta, L.A. Aaltonen, J. Saharinen, M. Gentile, A. Clarke, J. Taipale, G. Oliver, and K. Alitalo. 2008. Transcription factor PROX1 induces colon cancer progression by promoting the transition from benign to highly dysplastic phenotype. Cancer Cell 13:407-419. Pham, D.V., and P.H. Park. 2021. Tumor Metabolic Reprogramming by Adipokines as a Critical Driver of Obesity-Associated Cancer Progression. Int J Mol Sci 22: Ponomarev, A., Z. Gilazieva, V. Solovyeva, C. Allegrucci, and A. Rizvanov. 2022. Intrinsic and Extrinsic Factors Impacting Cancer Stemness and Tumor Progression. Cancers (Basel) 14: Puchades-Carrasco, L., and A. Pineda-Lucena. 2017. Metabolomics applications in precision medicine: an oncological perspective. Current topics in medicinal chemistry 17:2740-2751. Sajnani, K., F. Islam, R.A. Smith, V. Gopalan, and A.K.-Y. Lam. 2017. Genetic alterations in Krebs cycle and its impact on cancer pathogenesis. Biochimie 135:164-172. Sălăgeanu, A., L. Lerescu, I. Caraş, R. Pitica, G. Gangura, R. Costea, and S. Neagu. 2010. Serum levels of adipokines resistin and leptin in patients with colon cancer. Journal of medicine and life 3:416. Sharma, L.K., J. Lu, and Y. Bai. 2009. Mitochondrial respiratory complex I: structure, function and implication in human diseases. Curr Med Chem 16:1266-1277. Steppan, C.M., S.T. Bailey, S. Bhat, E.J. Brown, R.R. Banerjee, C.M. Wright, H.R. Patel, R.S. Ahima, and M.A. Lazar. 2001. The hormone resistin links obesity to diabetes. Nature 409:307-312. Su, C.Y., Y.C. Chang, C.J. Yang, M.S. Huang, and M. Hsiao. 2016. The opposite prognostic effect of NDUFS1 and NDUFS8 in lung cancer reflects the oncojanus role of mitochondrial complex I. Sci Rep 6:31357. Su, C.Y., and M. Hsiao. 2013. NDUFS1 as a prognostic marker in lung cancer: a clinicopathological analysis of 106 cases of non‐small cell lung cancer. In Wiley Online Library. Tahergorabi, Z., M. Khazaei, M. Moodi, and E. Chamani. 2016. From obesity to cancer: a review on proposed mechanisms. Cell biochemistry and function 34:533-545. Tarkowski, A., J. Bjersing, A. Shestakov, and M.I. Bokarewa. 2010. Resistin competes with lipopolysaccharide for binding to toll‐like receptor 4. Journal of cellular and molecular medicine 14:1419-1431. Vasan, K., M. Werner, and N.S. Chandel. 2020. Mitochondrial Metabolism as a Target for Cancer Therapy. Cell Metab 32:341-352. Velasco-Velazquez, M.A., V.M. Popov, M.P. Lisanti, and R.G. Pestell. 2011. The role of breast cancer stem cells in metastasis and therapeutic implications. Am J Pathol 179:2-11. Wang, C., P. Wang, Y. Hsieh, S. Lo, Y. Lee, Y. Chen, C. Tsai, W. Chiu, S. Chu-Sung Hu, and C. Lu. 2018a. Resistin facilitates breast cancer progression via TLR4-mediated induction of mesenchymal phenotypes and stemness properties. Oncogene 37:589-600. Wang, L., X. Zhan, X. Shen, M. Li, J. Yang, W. Yu, H. Chen, B. Jin, and Z. Mao. 2018b. P16 promotes the growth and mobility potential of breast cancer both in vitro and in vivo: the key role of the activation of IL-6/JAK2/STAT3 signaling. Mol Cell Biochem 446:137-148. Wang, Y.Y., Y.K. Chen, S. Lo, T.C. Chi, Y.H. Chen, S.C. Hu, Y.W. Chen, S.S. Jiang, F.Y. Tsai, W. Liu, R.N. Li, Y.C. Hsieh, C.J. Huang, and S.F. Yuan. 2021a. MRE11 promotes oral cancer progression through RUNX2/CXCR4/AKT/FOXA2 signaling in a nuclease-independent manner. Oncogene 40:3510-3532. Wang, Y.Y., A.C. Hung, S. Lo, and S.F. Yuan. 2021b. Adipocytokines visfatin and resistin in breast cancer: Clinical relevance, biological mechanisms, and therapeutic potential. Cancer Lett 498:229-239. Wang, Y.Y., A.C. Hung, Y.C. Wu, S. Lo, H.D. Chen, Y.K. Chen, Y.C. Hsieh, S.C. Hu, M.F. Hou, and S.F. Yuan. 2022. ADSCs stimulated by resistin promote breast cancer cell malignancy via CXCL5 in a breast cancer coculture model. Sci Rep 12:15437. Weinberg, S.E., and N.S. Chandel. 2015. Targeting mitochondria metabolism for cancer therapy. Nature chemical biology 11:9-15. Whitaker-Menezes, D., U.E. Martinez-Outschoorn, N. Flomenberg, R.C. Birbe, A.K. Witkiewicz, A. Howell, S. Pavlides, A. Tsirigos, A. Ertel, R.G. Pestell, P. Broda, C. Minetti, M.P. Lisanti, and F. Sotgia. 2011. Hyperactivation of oxidative mitochondrial metabolism in epithelial cancer cells in situ: visualizing the therapeutic effects of metformin in tumor tissue. Cell Cycle 10:4047-4064. Yakisich, J.S., N. Azad, V. Kaushik, and A.K.V. Iyer. 2017. Cancer Cell Plasticity: Rapid Reversal of Chemosensitivity and Expression of Stemness Markers in Lung and Breast Cancer Tumorspheres. J Cell Physiol 232:2280-2286. Yan, L., Y. Tan, G. Chen, J. Fan, and J. Zhang. 2021. Harnessing Metabolic Reprogramming to Improve Cancer Immunotherapy. Int J Mol Sci 22: Yuan, S.-S.F., Y.-M. Wang, L.-P. Chan, A.C. Hung, H.D.H. Nguyen, Y.-K. Chen, S.C.S. Hu, S. Lo, and Y.-Y. Wang. 2023a. IL-1RA promotes oral squamous cell carcinoma malignancy through mitochondrial metabolism-mediated EGFR/JNK/SOX2 pathway. Journal of Translational Medicine 21:473. Yuan, S.F., L.P. Chan, H.D.H. Nguyen, C.W. Su, Y.K. Chen, J.Y. Chen, S. Shimodaira, S.C. Hu, S. Lo, and Y.Y. Wang. 2024. Areca nut-induced metabolic reprogramming and M2 differentiation promote OPMD malignant transformation. J Exp Clin Cancer Res 43:233. Yuan, S.F., Y.M. Wang, L.P. Chan, A.C. Hung, H.D.H. Nguyen, Y.K. Chen, S.C. Hu, S. Lo, and Y.Y. Wang. 2023b. IL-1RA promotes oral squamous cell carcinoma malignancy through mitochondrial metabolism-mediated EGFR/JNK/SOX2 pathway. J Transl Med 21:473. Zhang, Y., A. Daquinag, D.O. Traktuev, F. Amaya-Manzanares, P.J. Simmons, K.L. March, R. Pasqualini, W. Arap, and M.G. Kolonin. 2009. White adipose tissue cells are recruited by experimental tumors and promote cancer progression in mouse models. Cancer research 69:5259-5266. Zheng, J. 2012. Energy metabolism of cancer: Glycolysis versus oxidative phosphorylation (Review). Oncol Lett 4:1151-1157. Zhu, L., Q. Tian, H. Gao, K. Wu, B. Wang, G. Ge, S. Jiang, K. Wang, C. Zhou, J. He, P. Liu, Y. Ren, and B. Wang. 2022. PROX1 promotes breast cancer invasion and metastasis through WNT/beta-catenin pathway via interacting with hnRNPK. Int J Biol Sci 18:2032-2046. Zu, X.L., and M. Guppy. 2004. Cancer metabolism: facts, fantasy, and fiction. Biochem Biophys Res Commun 313:459-465. Supplementary Files SupplementaryFigurelegends.docx SupplementaryFigures.pptx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5968936","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":417943435,"identity":"b5ba909e-06b3-492b-9b93-5dfbd74993db","order_by":0,"name":"Yen-Yun Wang","email":"","orcid":"","institution":"Kaohsiung Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yen-Yun","middleName":"","lastName":"Wang","suffix":""},{"id":417943436,"identity":"99f5d0ca-0008-4521-a1b3-ce2288f7e10b","order_by":1,"name":"Pang-Yu Chen","email":"","orcid":"","institution":"Kaohsiung Medical University","correspondingAuthor":false,"prefix":"","firstName":"Pang-Yu","middleName":"","lastName":"Chen","suffix":""},{"id":417943437,"identity":"ffead59c-d9c6-4d0e-a2fe-8932919faa32","order_by":2,"name":"Hieu D.H. Nguyen","email":"","orcid":"","institution":"Kaohsiung Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hieu","middleName":"D.H.","lastName":"Nguyen","suffix":""},{"id":417943438,"identity":"a090f629-3911-4155-b3cc-7c8ac8e3efd3","order_by":3,"name":"Chih-Huang Tseng","email":"","orcid":"","institution":"Kaohsiung Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chih-Huang","middleName":"","lastName":"Tseng","suffix":""},{"id":417943439,"identity":"8004d0ef-d631-4016-b708-e5971f60e685","order_by":4,"name":"Yuk-Kwan Chen","email":"","orcid":"","institution":"Kaohsiung Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuk-Kwan","middleName":"","lastName":"Chen","suffix":""},{"id":417943440,"identity":"f1caa7f1-f04a-4380-a021-9fadf101defe","order_by":5,"name":"Stephen Chu‐Sung Hu","email":"","orcid":"","institution":"Kaohsiung Medical University","correspondingAuthor":false,"prefix":"","firstName":"Stephen","middleName":"Chu‐Sung","lastName":"Hu","suffix":""},{"id":417943441,"identity":"f52b1b05-796f-4007-a566-b42bbe9ba72d","order_by":6,"name":"Steven Lo","email":"","orcid":"","institution":"University of Glasgow","correspondingAuthor":false,"prefix":"","firstName":"Steven","middleName":"","lastName":"Lo","suffix":""},{"id":417943442,"identity":"86728b8d-c710-433c-8a5d-ed66bcbdc34b","order_by":7,"name":"Ming-Feng Hou","email":"","orcid":"","institution":"Kaohsiung Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ming-Feng","middleName":"","lastName":"Hou","suffix":""},{"id":417943443,"identity":"612cb3f7-6ff8-47a3-9100-7189f2695b23","order_by":8,"name":"Shyng-Shiou F. Yuan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvUlEQVRIiWNgGAWjYPACOTkJMM1GvBZjY7gWHmK1JM4gWovBjeRnD3/8MUifOe2MAcOHssMM9hIJhLSkmRvzthnkzpbOMWCcce4wAw9hLQlm0owNf3LnAbUw87YBtUgT1JL+TRLkMDmQlr/Eackxk+BhM0iQBmlhJEaL5Jk3ZdJAvxjOnJ1WcLDnXDoPz/0H+LXwHU/fBnKYvMTt5I0PfpRZy7H3HMCvRQFZHsQmHJPyDQSVjIJRMApGwYgHACerPtwNifWYAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-4753-788X","institution":"Kaohsiung Medical University","correspondingAuthor":true,"prefix":"","firstName":"Shyng-Shiou","middleName":"F.","lastName":"Yuan","suffix":""}],"badges":[],"createdAt":"2025-02-06 00:15:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5968936/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5968936/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":76872199,"identity":"dcbefc8e-54d9-4f31-a857-8db6cb4ef576","added_by":"auto","created_at":"2025-02-21 15:34:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":6061054,"visible":true,"origin":"","legend":"\u003cp\u003eClinical association of NDUFS1 expression with breast cancer patient outcome. (A) Schematic diagram of MDA-MB-231 cells co-cultured with resistin-treated ADSCs (R-ADSC) or untreated ADSCs (ADSC). (B) Differential gene expression in subunits of mitochondria complexes I, II, III, and IV in MDA-MB-231 cells co-cultured with resistin-treated ADSCs (R50) compared to MDA-MB-231 cells co-cultured with untreated ADSCs (R0) according to RNAseq analysis. (C) Protein expression of NDUFS1 in MDA-MB-231 cells co-cultured with resistin-treated ADSCs (R50) and untreated ADSCs (R0) was determined using Western blot. (D) Analysis of the expression level of NDUFS1 transcript in normal breast tissues and breast cancer tissues from the Oncomine database (https://www.oncomine.org/resource/login.html). (E) Protein expression of NDUFS1 in breast cancer tissues and normal breast tissues was determined using the method of histochemical score (H-score). (F) Kaplan-Meier graph of progression-free survival from publicly available breast cancer microarray datasets stratified according to the expression of NDUFS1 transcript from the Kaplan-Meier Plotter (https://kmplot.com/analysis/). The data are presented as mean ± SD; *, P \u0026lt; 0.05; **, P \u0026lt; 0.01; ***, P \u0026lt; 0.001; ****, P \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5968936/v1/7fdd2c10f3c2e045eb4e6bb8.png"},{"id":76871677,"identity":"7827072b-7196-421b-b299-62f289479538","added_by":"auto","created_at":"2025-02-21 15:26:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5815550,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe effects of NDUFS1 on breast cancer cell properties and c-Myc expression. \u003c/strong\u003e(A) Western blot showing NDUFS1 protein expression in MDA-MB-231 and MCF7 cellsafter NDUFS1 knockdown. (B) The effect of NDUFS1 knockdown on MDA-MB-231 and MCF-7 breast cancer cell proliferation, determined by the XTT assay. (C) Protein expression of NDUFS1 in MDA-MB-231 and MCF7 cells after NDUFS1 overexpression. (D) The effect of NDUFS1 overexpression on breast cancer cell viability. (E) The effect of NDUFS1 knockdown on MCF-7 tumorsphere formation. (\u003cdel\u003eH\u003c/del\u003eF) The effects of NDUFS1 knockdown and overexpression on c-Myc protein expression in MDA-MB-231 and MCF-7 cells. (G) Correlation between NDUFS1 and MYC expression, analyzed using the TCGA-BRCA online database. (H) Correlation between NDUFS1 and MYC protein expression in breast tumor tissues, as determined by immunohistochemical staining. Data are presented as mean ± SD from three independent experiments. *, P \u0026lt; 0.05; **, P \u0026lt; 0.01; ***, P \u0026lt; 0.001; ****, P \u0026lt; 0.0001. Luc, knockdown of firefly luciferase; hKD1, knockdown of human NDUFS1 clone 1; hKD2, knockdown of human NDUFS1 clone 2; EV, empty vector; OE, overexpression of NDUFS1.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5968936/v1/7084573135e4d433cdaaa4f0.png"},{"id":76870391,"identity":"dfe2e137-08b8-45a6-ae64-070ee7507875","added_by":"auto","created_at":"2025-02-21 15:18:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1733558,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe effects of NDUFS1 on mitochondrial metabolism in breast cancer cells. \u003c/strong\u003e(A-B) The effects of knockdown and overexpression of NDUFS1 on oxygen consumption rate (OCR) in MDA-MB-231 and MCF-7 cells, as indicated by the slope (∆RFU/∆min), measured with CLARIOstar Plus multi-mode plate reader using a commercial oxygen consumption-labeling kit. (C-D) The effect of NDUFS1 knockdown on the status of mitochondrial metabolism in (C) MDA-MB-231 cells and (D) MCF-7 cells, measured by OCR rate using Agilent Seahorse XFe24 Analyzer via sequential delivery of the indicated mitochondrial modulators (oligomycin, FCCP, and a mixture of rotenone and antimycin A). (E) XTT assay for MDA-MB-231 cells and MCF-7 cells with NDUFS1 overexpression after treatment with metformin (30 mM).­The data are presented as mean ± SD from three independent experiments. *, P \u0026lt; 0.05; **, P \u0026lt; 0.01; ***, P \u0026lt; 0.001; ****, P \u0026lt; 0.0001. Luc, knockdown of firefly luciferase; hKD2, knockdown of human NDUFS1 clone 2; EV, empty vector; OE, overexpression of NDUFS1.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5968936/v1/1b1de7b05ddf1ef737bf0b0d.png"},{"id":76871680,"identity":"34bba1f0-9b08-4dc3-818b-5ae429c036de","added_by":"auto","created_at":"2025-02-21 15:26:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5908675,"visible":true,"origin":"","legend":"\u003cp\u003eInvolvement of NDUFS1/PROX1/c-Myc pathway in breast cancer cells. (A) The Venn diagram presents the number of upregulated genes involved in cell proliferation and stemness from RNAseq analysis in MDA-MB-231 cells with NDUFS1 knockdown. (B) Protein expression of NDUFS1 and PROX1 in MDA-MB-231 and MCF-7 cells with NDUFS1 knockdown or overexpression was determined by Western blot. (C) Correlation between NDUFS1 and PROX1 transcripts in breast cancer tissues from the GEPIA database (http://gepia.cancer-pku.cn/index.html). (D) Correlation between NDUFS1 and PROX1 protein expression, determined by IHC. (E) Kaplan-Meier graph of distant metastasis-free survival from publicly available breast cancer microarray datasets stratified according to the expression of PROX1 transcript from the Kaplan-Meier Plotter (https://kmplot.com/analysis/). (F) NDUFS1-overexpressing MDA-MB-231 cells were treated with PROX1 siRNA or infected with lentivirus carrying MYC shRNA, and then protein expression of NDUFS1, PROX1 and c-Myc was determined by Western blot. (G) Expression of PROX1 and c-Myc after metformin (30 mM) treatment was determined by Western blot. ¬The data were presented as mean ± SD from three independent experiments. ¬The data are presented as mean ± SD from three independent experiments. *, P \u0026lt; 0.05; **, P \u0026lt; 0.01; ***, P \u0026lt; 0.001; ****, P \u0026lt; 0.0001. Luc, knockdown of firefly luciferase; hKD2, knockdown of NDUFS1 clone 2; EV, empty vector; OE, overexpression of NDUFS1; siCTRL, control siRNA; siPROX1, PROX1-specific siRNA; shLuc, knockdown of firefly luciferase; shMYC, knockdown of MYC.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5968936/v1/27ea094a523f9b7128d7f559.png"},{"id":76870397,"identity":"f0e9a3cb-108a-4149-a918-eca41d222f4d","added_by":"auto","created_at":"2025-02-21 15:18:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1560212,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIn vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e effect of NDUFS1 on breast tumor growth in syngeneic orthotopic mouse model. \u003c/strong\u003e(A) Protein expression of NDUFS1 in 4T1 cells was determined by Western blot. (B-C) After knockdown of mouse NDUFS1, cell viability was performed using XTT assay (B) and tumorsphere formation was assessed by tumorsphere assay (C). (D) Protein expression of NDUFS1, PROX1 and c-Myc in 4T1 cells after mouse NDUFS1 knockdown was determined by Western blot. ­The data were presented as mean ± SD from three independent experiments. (E) \u003cem\u003eIn vivo\u003c/em\u003e photon emission of luciferase-expressing 4T1 cells in orthotopic tumors was detected and photographed by IVIS50 imaging system at the endpoint of the experiment. Luciferase-expressing 4T1 cells (1 × 10\u003csup\u003e5\u003c/sup\u003e cells per mice) were injected into the left 4th mammary fat pad of 6-week-old female BALB/c mice to generate orthotopic tumors. (F-G) Orthotopic tumors collected at the endpoint of the experiment were measured for tumor volume (F) using the formula of (width\u003csup\u003e2\u003c/sup\u003e × length)/2, and tumor weight (G). The data are presented as mean ± SD; *, P \u0026lt; 0.05; **, P \u0026lt; 0.01; ***, P \u0026lt; 0.001; ****, P \u0026lt; 0.0001. Luc, knockdown of firefly luciferase; mKD1, knockdown of mouse NDUFS1 clone 1.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5968936/v1/39d1fd367742a6b2928a6e70.png"},{"id":76871681,"identity":"1df9d0ea-76ac-4155-9b2a-e060b9633258","added_by":"auto","created_at":"2025-02-21 15:26:13","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":7225960,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression and association of NDUFS1, PROX1 and c-Myc proteins in mouse orthotopic tumors.\u003c/strong\u003e(A-D) After sacrifice at the endpoint of the experiment, the orthotopic tumors were collected and analyzed for protein expression of (A) NDUFS1, (B) PROX1 and (C) c-Myc. (D-E) The association of NDUFS1 expression with (D) PROX1 expression and (E) c-Myc expression. The data are presented as mean ± SD; *, P \u0026lt; 0.05; ***, P \u0026lt; 0.001. Luc, knockdown of firefly luciferase; mKD1, knockdown of mouse NDUFS1 clone 1.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5968936/v1/b3ccad221372dc1d90d38067.png"},{"id":76870406,"identity":"9bee595c-f28a-4993-bbe4-c7a971bfc31b","added_by":"auto","created_at":"2025-02-21 15:18:14","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":11634415,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMetformin and rotenone treatment reduces tumor growth by inhibiting the NDUFS1 pathway in syngeneic orthotopic mouse model.\u003c/strong\u003e (A) In vivo photon emission from luciferase-expressing 4T1 cells in orthotopic tumors was detected and captured using IVIS50 imaging system at the experiment's endpoint. (B-C) At the experiment's endpoint, orthotopic tumors were collected, and tumor volume (B) was calculated using the formula (width² × length) / 2, and tumor weight (C) was measured. (D-F) Following sacrifice, orthotopic tumors were analyzed for protein expression of (D) NDUFS1, (E) PROX1, and (F) c-Myc. (G) A schematic summary illustrates the current study. Data are presented as mean ± SD; *P \u0026lt; 0.05; ***P \u0026lt; 0.001. Luc, firefly luciferase knockdown; mKD1, knockdown of mouse NDUFS1 clone 1.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5968936/v1/a7a97545933894ff4d4ccc95.png"},{"id":80177845,"identity":"dadde558-0e28-4af1-9764-98b021712f45","added_by":"auto","created_at":"2025-04-08 21:28:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":47555232,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5968936/v1/3275377f-6176-4d6e-ad0b-078ed02ea412.pdf"},{"id":76870390,"identity":"0344eb50-7ce7-4b5a-913a-5bde45d5aac7","added_by":"auto","created_at":"2025-02-21 15:18:13","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23695,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigurelegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-5968936/v1/b71aa2af9e1173b7fe9cc92f.docx"},{"id":76870404,"identity":"75e6830a-989c-4512-86f6-09f393f68813","added_by":"auto","created_at":"2025-02-21 15:18:14","extension":"pptx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":19032562,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigures.pptx","url":"https://assets-eu.researchsquare.com/files/rs-5968936/v1/bf3739725735c7990b0b7c5d.pptx"}],"financialInterests":"","formattedTitle":"NDUFS1 promotes malignant breast cancer behaviors through activation of mitochondrial metabolism and PROX1/c-Myc signaling","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer is the most prevalent cancer type in women in developed countries, with obesity emerging as a crucial factor in breast cancer development, particularly in postmenopausal women. Epidemiological studies demonstrate higher incidence and poorer prognosis (Chan et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), with research recently focusing on the role of adipocytokines and adipose-derived stem cells (ADSCs) in the breast tumor microenvironment (DeRose et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). As obesity progresses, adipose tissue expands and triggers excessive production of adipocytokines, leading to the proliferation of ADSCs (An et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Calle and Thun, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). These ADSCs are subsequently recruited to the tumor site and release various chemokines, growth factors and adipocytokines such as resistin and visfatin - that have been shown to correlate with more aggressive breast cancer behavior and decreased patient survival (Freese et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Hung et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Lee et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Lee et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdipose tissue surrounding the mammary glands consists of heterogenous mix of adipocytes and stromal cells including ADSCs (Bourin et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). ADSCs, a form of multipotent mesenchymal stem cells (MSCs), possess the capability to differentiate into adipocytes, osteocytes, chondrocytes, or myocytes when exposed to specific lineage-inducing factors, with secretory factors from the breast cancer microenvironment responsible for inducing differentiation capability (Maysaa El Sayed et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The secretome of ADSCs contains a diverse array of substances including cytokines, growth factors, angiogenic factors, adipokines, and neurotrophic factors, some of which are implicated in tumor progression and epithelial-mesenchymal transition (EMT) (Dubey et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), such as insulin-like growth factor (IGF), hepatocyte growth factor (HGF), VEGF, and IL8.\u003c/p\u003e \u003cp\u003eObesity-associated adipocytokines promote malignant breast cancer cell behaviors, including proliferation, migration and invasion, through autocrine, paracrine, and endocrine pathways (Divella et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Hoy et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Tahergorabi et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Among these adipocytokines, elevated levels of leptin, resistin, and visfatin in the tumor microenvironment are associated with breast cancer progression (Al-Suhaimi and Shehzad, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Gnerlich et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e). Resistin, a 12.5 kDa cysteine-rich adipocytokine, was initially identified for its role in insulin resistance and other non-oncologic pathways including inflammatory processes such as atherosclerosis (Steppan et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). More recently, its importance as a key oncogenic driver has been clarified in multiple cancer subtypes such as colon, prostate, endometrium, and breast (Hlavna et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Housa et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Koerner et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2005\u003c/span\u003elăgeanu et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Our previous research has demonstrated that resistin promotes breast cancer cell proliferation, migration, and stemness by activating the TLR4/NF-κB/STAT3 signaling pathway, and may additionally act via CXCL5 to enhance migration and invasion (Jiang et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Tarkowski et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Other groups have noted that resistin triggers the ezrin and moesin proteins, influencing metastasis (Lee et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Recently, the role of adipocytokines as a critical driver of obesity associated cancer progression has emerged in relation to metabolic reprogramming, including mitochondrial and lipid metabolism (Pham and Park, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, the influence of resistin on metabolic reprogramming in breast cancer is as yet undefined.\u003c/p\u003e \u003cp\u003eMetabolic reprogramming - particularly in oxygen sensing and energy metabolism (Bai and Cui, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sajnani et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) - is a hallmark of cancer cells, ensuring sustained cell growth and proliferation in the face of a harsh tumor microenvironment (Kroemer and Pouyssegur, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Puchades-Carrasco and Pineda-Lucena, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Mitochondria are responsible for processes such as the tricarboxylic acid (TCA) cycle, oxidative phosphorylation (OXPHOS), fatty acid oxidation (FAO) and signal exchange with other cell compartments to adjust to fluctuating metabolic demands (Castelli et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). One of the key metabolic phenotypes responsible for cancer cell energy generation is the preferential dependence on glycolysis rather than oxidative phosphorylation, even with normal oxygen concentrations \u0026ndash; commonly known as the Warburg effect - and was initially thought to be related to impairment of mitochondrial OXPHOS. However, recent studies challenge these assumptions and indicate that mitochondrial OXPHOS, regulated by the electron transport chain (ETC) complexes I to IV, is largely intact and in some instances upregulated in cancers (Moreno-Sanchez et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Weinberg and Chandel, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). A meta-analysis examining normal and cancer cell lines indicated that OXPHOS contributes to 80% of relative ATP production in normal cells and 83% in cancer cells (Zu and Guppy, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Inhibition of OXPHOS has shown therapeutic efficacy in several cancer subtypes (Ashton et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Breast cancer of basal-like subtype with frequent RB1 loss and p53 disruption exhibits an elevated mitochondrial metabolism (Jones et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Breast cancer cells display higher complex IV activity compared to adjacent stromal and normal ductal epithelial cells (Whitaker-Menezes et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, metabolic reprogramming related to resistin\u0026rsquo;s effects on ADSC-breast tumor cell interactions was investigated. In this regard, the potential of NADH:ubiquinone oxidoreductase core subunit S1 (NDUFS1) - the largest subunit of mitochondrial complex I and which catalyzes the first step of nicotinamide adenine dinucleotide (NADH) oxidation \u0026ndash; was evaluated as a clinical indicator of breast cancer progression and patient outcome. Additionally, the cellular mechanism of NDUFS1 in regulating breast cancer cell proliferation and stemness in vitro and in vivo was explored. Herein, this study delineates a novel NDUFS1-associated mitochondrial metabolic pathway that may aid in the development of innovative metabolic approaches in breast cancer therapy.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eClinical association of NDUFS1 with breast cancer progression and patient outcomes\u003c/h2\u003e \u003cp\u003eThe gene expression profiles of MDA-MB-231 cells co-cultured with resistin-treated ADSCs or untreated ADSCs were analyzed by RNAseq.\u0026nbsp;To identify metabolic enzymes associated with resistin-treated ADSCs that promote breast cancer progression, we analyzed genes that were differentially expressed (1.5 folds, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between the two MDA-MB-231-ADSCs co-culture groups. Among the four mitochondrial complexes, we found that NDUFS1, the largest subunit of mitochondrial complex I, had the greatest increase in expression in MDA-MB-231 cells co-cultured with resistin-treated ADSCs compared to that co-cultured with untreated ADSCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Mitochondrial complex I has 45 subunits that are encoded by mitochondrial DNA (mtDNA) and nuclear DNA (nDNA). Among the core subunits, seven subunits including NDUFS1, NDUFS2, NDUFS3, NDUFS7, NDUFS8, NDUFV1, and NDUFV2 are encoded by nDNA. NDUFS1, NDUFV1, and NDUFV2 are components of the NADH dehydrogenase module and NDUFS2, NDUFS3, NDUFS7, and NDUFS8 are components of the NADH hydrogenase module (Sharma et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Notably, NDUFS1 is the largest subunit of mitochondrial complex I. The data were then confirmed using western blot analysis, which showed higher NDUFS1 expression in MDA-MB-231 cells co-cultured with resistin-treated ADSCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). From the Oncomine database, the expression level of NDUFS1 transcripts was found to be significantly higher in invasive ductal breast carcinoma tissues than that in normal breast tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). To evaluate the protein expression of NDUFS1 in breast cancer, immunohistochemical analysis was performed on breast cancer tissues and normal tissues. Our data showed an elevated level of NDUFS1 expression in breast cancer tissues compared to that in normal tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). Moreover, Kaplan-Meier survival analyses using publicly available breast cancer microarray datasets showed that a high expression level of NDUFS1 was significantly associated with worse overall survival in breast cancer patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). In addition, we further analyzed the correlation of NDUFS1 protein expression and clinical behaviors. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, NDUFS1 is positively associated with stage and tumor size.\u003c/p\u003e \u003cp\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\u003eThe association of NDUFS1 expression and clinicopathological characteristics of breast cancer patients using logistic regression.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNDUFS1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ecrud OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eadj OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e90 (57.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66 (42.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21 (31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII-IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45 (68.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78 (86.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.03 (1.35\u0026ndash;6.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGrade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII\u0026thinsp;+\u0026thinsp;III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57(86.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82 (91.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.62 (0.59\u0026ndash;4.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.12 (0.37\u0026ndash;3.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge(years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56 (84.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79 (87.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e⩾65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78 (0.31\u0026ndash;1.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.68 (0.25\u0026ndash;1.82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI(kg/m2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39 (59.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e⩾24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27 (40.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.16 (0.61\u0026ndash;2.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.14 (0.57\u0026ndash;2.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eT status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34 (51.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (26.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2-T4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32 (48.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66 (73.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.92 (1.50\u0026ndash;5.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.84 (1.40\u0026ndash;5.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLN metastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28 (31.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN1-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37 (56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62 (68.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.74 (0.90\u0026ndash;3.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.35 (0.66\u0026ndash;5.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eER status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43 (65.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57 (63.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23 (34.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33 (36.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.08 (0.56\u0026ndash;2.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.47 (0.52\u0026ndash;4.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePR status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36 (54.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51 (56.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30 (45.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39 (43.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92 (0.48\u0026ndash;1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.73 (0.26\u0026ndash;2.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHER2 status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26 (28.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47 (71.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64 (71.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00 (0.50\u0026ndash;2.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.05 (0.49\u0026ndash;2.26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eNDUFS1 promoted breast cancer cell proliferation and stemness\u003c/h3\u003e\n\u003cp\u003eEndogenous protein expression of NDUFS1 was examined in six human breast cancer cell lines, including ZR-75-1, T-47D, MCF-7, BT-549, Hs 578T, and MDA-MB-231 cells (Sup. Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA). NDUFS1 protein expression in MDA-MB-231 and MCF-7 cells was downregulated using shRNA clones #1 and #2 which showed better knockdown efficiency compared to the other four clones (Sup. Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB). The effects of NDUFS1 knockdown (KD) and overexpression (OE) on breast cancer cell proliferation was analyzed using the XTT assay. Knockdown of NDUFS1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) significantly decreased MDA-MB-231 and MCF-7 cell proliferation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), whereas overexpression of NDUFS1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC) significantly increased MDA-MB-231 and MCF-7 cell proliferation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). Tumorsphere formation assay has been widely used for the determination of cancer cell stemness (Dianat-Moghadam et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yakisich et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Using the tumorsphere formation assay, we observed that knockdown of NDUFS1 in MCF-7 cells reduced tumorsphere formation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). Western blotting was further applied to evaluate stemness markers in MCF-7 and 4T1 cell lines, and we found that knockdown of NDUFS1 significantly suppressed c-Myc expression in MDA-MB-231 and MCF-7 cell lines (Sup. Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC), while overexpression of NDUFS1 enhanced c-Myc expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAdditionally, we found a positive correlation between NDUFS1 and MYC expression (p\u0026thinsp;=\u0026thinsp;0.046) using the TCGA-BRCA online database (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG). We further employed immunohistochemical staining to explore the correlation between NDUFS1 and MYC, and a positive correlation between NDUFS1 expression and c-MYC expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH) was observed in breast tumor tissues from breast cancer patients. Taken together, these data suggested that alteration of NDUFS1 expression affects cancer cell growth in breast cancer cells, and shows the properties of cancer stemness-associated growth (Ponomarev et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eNDUFS1 promoted malignant breast cancer cell behaviors via activation of mitochondrial metabolism\u003c/h3\u003e\n\u003cp\u003eIn this study, we noted an association between NDUFS1 and cancer cell stemness (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), which suggests the involvement of mitochondrial metabolism in oncogenesis. Therefore, we further examined the role of mitochondrial metabolism in NDUFS1-associated cancer cell progression. Using CLARIOstar, we found that knockdown of NDUFS1 decreased the oxygen consumption rate (OCR), an indicator of impaired mitochondrial metabolism, while overexpression of NDUFS1 increased the OCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-B). Further Seahorse assays showed downregulated basal OCR, ATP production, maximal respiration and spare respiratory capacity when NDUFS1 was knocked down (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D). Furthermore, NDUFS1-induced MDA-MB-231 and MCF-7 cell proliferation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE) was reduced by the mitochondrial complex inhibitor metformin, when treated at a concentration that did not affect cancer cell viability (Yuan et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e). Notably, NDUFS1 knockdown in MDA-MB-231 and MCF-7 cells also decreased the extracellular acidification rate (ECAR) (Sup. Fig. S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eNDUFS1 promoted breast cancer cell proliferation and stemness via mitochondrial metabolism-activated PROX1/c-Myc pathway\u003c/h3\u003e\n\u003cp\u003eUsing RNAseq, a total of 6 genes were identified across the two domains (proliferation and stemness) when MDA-MB-231 cells with or without NDUFS1 knockdown were compared. Three genes were shared by the three domains, namely PROX1, MEF2C and WNT5A (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Although both real time PCR and TCGA database confirmed the association of NDUFS1 with MEF2C and WNT5A (Sup. Fig. S3 A and B), further Kaplan-Meier survival analysis using publicly available breast cancer microarray datasets showed that MEF2C and WNT5A were not correlated with breast cancer survival (Sup. Fig. S3C), and Western blot analysis did not show significant increase of WNT5A expression when NDUFS1 was overexpressed in MDA-MB-231 cells (Sup. Fig. S3D). Conversely, knockdown of NDUFS1 decreased PROX1 expression while overexpression of NDUFS1 increased PROX1 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). In addition, there was a positive correlation between NDUFS1 and PROX1 expression (p\u0026thinsp;=\u0026thinsp;2.6e-7), determined using the TCGA-BRCA online database (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). We also used immunohistochemical staining to study the correlation between NDUFS1 and PROX1 proteins, and a positive correlation between NDUFS1 expression and PROX1 expression was observed in breast tumor tissues from breast cancer patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). Kaplan-Meier survival analyses using publicly available breast cancer microarray datasets showed that high levels of PROX1 expression were significantly associated with worse overall survival in breast cancer patients (p\u0026thinsp;=\u0026thinsp;0.019) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). We also found that inhibition of PROX1 by siPROX1 reduced the expression of c-Myc while inhibition of c-Myc by shMYC did not affect the expression of PROX1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eNDUFS1 knockdown inhibited orthotopic breast tumor growth and tumoral expression of PROX1 and c-Myc in vivo\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe in vivo effect of NDUFS1 on breast tumor growth was evaluated using syngeneic BALB/c mouse model using luciferase-expressing 4T1 mouse breast cancer cells. The efficiency of NDUFS1 knockdown in 4T1 cells was first confirmed by Western blot analysis \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Further studies showed decreased 4T1 cell proliferation and stemness property when NDUFS1 was knocked down in 4T1 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB-D). 4T1 cells with NDUFS1 knockdown were injected into the left fourth mammary fat pad of mice, and tumor volume and bioluminescent signal from in vivo imaging system (IVIS) were measured weekly. At the end of the experiment, the NDUFS1 knockdown group demonstrated decreased bioluminescent signal (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE), tumor volume (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF) and tumor weight (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurther immunohistochemical analysis of the tumor tissues showed that the expression of NDUFS1, PROX1 and c-Myc was decreased in the NDUFS1 knockdown group (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA-C). In addition, NDUFS1 expression in the tumor tissues was positively correlated with PROX1 (p\u0026thinsp;=\u0026thinsp;0.0018) and c-Myc (p\u0026thinsp;=\u0026thinsp;0.0008) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD-E).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTherapeutic effects of mitochondrial metabolism inhibitors metformin and rotenone on NDUFS1-expressing breast tumor\u003c/h3\u003e\n\u003cp\u003eTo study the therapeutic effects of mitochondrial metabolism inhibitors metformin and rotenone on NDUFS1-expressing breast cancer in vivo, female BALB/c mice, after generation of orthotopic breast tumors were injected with metformin and rotenone into the peritoneal cavity five times per week and were sacrificed after four weeks of treatment. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, bioluminescent signal in tumor (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA), tumor volume (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB) and tumor weight (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC) were significantly higher in Luc group mice than NDUFS1 knockdown mice and treatment of metformin and rotenone reversed the tumor growth in Luc group mice. Furthermore, analysis of the orthotopic tumors by immunohistochemical analysis showed that the expression of NDUFS1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD), PROX1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE) and c-Myc (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF) was higher in the Luc group mice, which was decreased after treatment with metformin and rotenone.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe data presented here provide evidence for a novel metabolic reprogramming role for resistin in the breast tumor microenvironment, acting via ADSC intermediaries to upregulate expression of NDUFS1. This, in turn, promotes mitochondrial metabolism and breast cancer stemness via the PROX1/c-Myc pathway, resulting in breast cancer progression both in vitro and in vivo (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eG).\u003c/p\u003e\n\u003ch3\u003eResistin-treated ADSCs promote breast cancer development via NDUFS1/PROX-1/c-Myc pathway\u003c/h3\u003e\n\u003cp\u003eA significant increase of NDUFS1 expression in breast cancer cells co-cultured with resistin-treated ADSCs was observed in this study. Although low NDUFS1 expression has been associated with poorer clinical outcomes and cancer progression in renal cell, non-small cell lung and gastric carcinomas (Chen et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ellinger et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Su et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), we found that increased NDUFS1 expression led to breast cancer progression, via activation of mitochondrial metabolism and PROX-1/c-Myc pathway. c-Myc has previously been reported to be highly expressed during breast cancer development (Deng et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Liao and Dickson, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), and bioinformatics analyses have shown an interaction between c-Myc and NDUFS1, which leads to tumorigenicity in non-small cell lung cancer (Su and Hsiao, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) Additionally, in the present study NDUFS1 was found to activate PROX-1, with clinicopathological analysis revealing a positive correlation between the expression of NDUFS1 and the expression of PROX-1 and c-Myc in breast cancer tissues. Likewise, elevated expression of PROX-1 mRNA has been found in other cancers including neuroblastoma, glioma, lung carcinoid tumor, small cell lung carcinoma, colon cancer, liver carcinoma, and rhabdomyosarcoma (Elsir et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). PROX-1 drives the transition from benign to malignant phenotypes through alterations in cell polarity, extracellular matrix interactions and cell adhesion (Petrova et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), and promotes breast cancer cell invasion and metastasis via WNT/β-catenin signaling pathways (Zhu et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, a recent study has also demonstrated that PROX1, via inhibition of c-Myc expression, suppresses breast cancer cell proliferation (Michail et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Further studies are required to explain these contradictory findings.\u003c/p\u003e\n\u003ch3\u003eResistin exerts direct and indirect oncologic effects in breast cancer\u003c/h3\u003e\n\u003cp\u003eThese findings add to the accumulating evidence that resistin plays a truly diverse oncogenic role in breast cancer, extending to metabolic reprogramming in the tumor microenvironment. Previously, we and others have demonstrated that resistin exerts effects both directly on breast cancer cells, and indirectly via the secretome of resistin treated ADSCs. These direct effects include increased breast cancer cell growth and stemness through STAT3 activation downstream of IL-6 (Deshmukh et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e); and toll-like receptor 4 (TLR4)-mediated NF-κB signaling (Wang et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e). Indirect effects mediated by the secretome of resistin treated ADSCs include enhanced migration and invasion via CXCL5 (Wang et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Interestingly, EMT and mitochondrial metabolism may act co-operatively, with EMT both inducing and being the consequence of metabolic reprogramming. EMT may induce metabolic rewiring, due to the motility and invasiveness of mesenchymal cells exerting increased metabolic demands after the epithelial transition. Yet, similar to the present study, metabolic reprogramming may itself lead to increased invasiveness and EMT induction (Lunetti et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Although not the focus of this study, a mutual interplay of this nature may therefore exist between the resistin mediated NDUFS1 mitochondrial reprogramming highlighted herein, and resistin mediated CXCL5 invasion and migration noted in our previous research.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBreast cancer stemness is promoted by NDUFS1\u003c/h2\u003e \u003cp\u003eCancer stemness, characterized by an increased capacity for self-renewal and enhanced motility of cancer cells, is strongly linked to tumor recurrence and metastasis in breast cancer (Lee et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Velasco-Velazquez et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In the present study, we observed that NDUFS1 promoted cancer stemness-related properties in breast cancer cells, including self-proliferation and increased tumorsphere formation. Additionally, knockdown of NDUFS1 suppressed the expression of c-Myc while overexpression of NDUFS1 enhanced c-Myc expression in breast cancer cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF and Sup. Fig. S 2C-D). Since c-Myc is a transcription factor linking stemness and malignancy (Liu et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), our results suggest that NDUFS1 may play a key role in regulating breast cancer cell proliferation and stemness.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eNDUFS1 upregulates the PROX1/c-Myc pathway through activation of mitochondrial metabolism\u003c/h2\u003e \u003cp\u003eModification of cellular energy and redox status through mitochondrial metabolic reprogramming is strongly linked with cancer progression (Bian et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zheng, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Targeting the inhibition of mitochondrial complexes has emerged as a novel and promising strategy for cancer treatment (Bian et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Yan et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Our in vitro data demonstrated that NDUFS1 overexpression increased the rate of mitochondrial oxidative metabolism to promote breast cancer cell proliferation and stemness, which were reversed by the anti-diabetic drugs metformin and phenformin, both of which inhibit mitochondrial metabolism (Vasan et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and future work\u003c/h2\u003e \u003cp\u003eA limitation of this study is that the detailed mechanism regarding how resistin activates NDUFS1 to promote malignant breast cancer cell behaviors remains undefined. The cytokine in the resistin-treated ADSC secretome responsible for the elevation of NDUFS1 levels has yet to be identified. The cross-talk between PROX1 and c-Myc deserves further exploration, such as the binding sites for PROX1 on the promoter region of c-Myc for transcriptional activation. Furthermore, apart from the effect of metformin and phenformin in vitro, the potential of these drugs should be investigated in vivo to explore the therapeutic effect of metformin/phenformin on breast cancer in pre-clinical study. Although a recent randomized controlled trial in 3649 patients failed to find a positive benefit from metformin for invasive disease-free survival in breast cancer, our study provides evidence that may point toward the need for stratification of patients with higher resistin levels (and therefore by association NDUFS1) when designing future clinical trials, considering factors such as BMI and post-menopausal status (Goodwin et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eTogether these data support the increasingly diverse role of resistin in breast cancer, with this study demonstrating its scope includes metabolic reprogramming via ADSCs in the tumor microenvironment. A novel NDUFS1/PROX1/c-Myc pathway may play a critical role in breast cancer development and may additionally provide an avenue for repurposing of metabolic drugs such as metformin.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePatient samples\u003c/h2\u003e \u003cp\u003eBreast tumor tissues were obtained from patients at Kaohsiung Medical University Hospital (KMUH), Taiwan, and confirmed using clinical and histological data from the Cancer Registry. This study was approved by the Institutional Review Board of Kaohsiung Medical University Hospital (approval numbers KMUHIRB-E(I)-20180136 and KMUHIRB-E(I)-20190424), and patient informed consent was waived for the de-identified patient samples.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eCell culture\u003c/h2\u003e \u003cp\u003eHuman breast carcinoma cell lines MDA-MB-231, MCF-7, T-47D, ZR-75-1, BT-549, Hs-578T and the mouse breast carcinoma cell line 4T1 were purchased from the Bioresource Collection and Research Center (BCRC, Hsinchu, Taiwan). MDA-MB-231, MCF-7, T-47D, and BT-549 cells were maintained in Dulbecco's Modified Eagle Medium (Gibco), while Hs-578T, ZR-75-1, and 4T1 cells were cultured in Roswell Park Memorial Institute 1640 (Gibco) with 5% CO\u003csub\u003e2\u003c/sub\u003e at 37\u0026deg;C in a humidified incubator. All culture media were supplemented with 10% fetal bovine serum (Biological Industries) and 1% penicillin /streptomycin/amphotericin B (Sartorius).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eGene knockdown and overexpression of NDUFS1\u003c/h2\u003e \u003cp\u003eTo knock down NDUFS1 expression in MDA-MB-231 and MCF-7 cell lines, lentivirus carrying a pLKO.1_puro lentiviral vector (ordered from National RNAi Core Facility, Academia Sinica, Taipei, Taiwan) that expressed double-stranded short hairpin (sh)RNA oligonucleotides targeting the sequences of human NDUFS1 was used (Clone 1, ID: TRCN000006463; Clone 2, ID: TRCN0000064632), while a pLKO.1_puro lentiviral vector (ordered from National RNAi Core Facility, Academia Sinica, Taipei, Taiwan) expressing shRNA targeting firefly luciferase, unrelated to the human genome sequence, was used as a negative control (ID: TRCN000072249). Lentiviral infection was achieved by adding the viral solution to cells in culture media containing 8 g/ml polybrene. For selection, 2 \u0026micro;g/ml puromycin was added 48 hours after infection. Selected cells were cultured in 2 \u0026micro;g/ml puromycin for the duration of the experiment.\u003c/p\u003e \u003cp\u003eTo overexpress NDUFS1 in MDA-MB-231 and MCF-7 cell lines, ready-to-use lentiviral particles containing the pReceiver lentiviral vector which expressed human NDUFS1 gene were purchased from Topgen. For negative control, lentiviral particles which carried an empty lentiviral vector were used (Topgen). Lentiviral infection was performed by adding the viral solution to cells, with culture media containing 8 g/ml polybrene. After infection for 48 hours, 2 \u0026micro;g/ml puromycin was added for selection. Selected cells were cultured in 2 \u0026micro;g/ml puromycin for the duration of the experiment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eCo-culture for RNA sequencing\u003c/h2\u003e \u003cp\u003eADSCs were incubated in the presence or absence of 50 ng/ml resistin for 48 hours (Wang et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). MDA-MB-231 cells were seeded in the lower chamber of a 6-well plate while ADSCs were seeded in the upper insert (0.4 \u0026micro;m pores, CoStar) for 72 hours. At the indicated time point, total RNA from MDA-MB-231 cells was extracted using Trizol\u0026reg; Reagent (Invitrogen, USA) according to the manufacturer's instructions. Purified RNA was quantified at OD260nm using a ND-1000 spectrophotometer (Nanodrop Technology, USA) and RNA quality was assessed using a Bioanalyzer 2100 (Agilent Technology, USA) with RNA 6000 LabChip kit (Agilent Technology, USA). All RNA sample preparation and RNA sequencing procedures were carried out according to Illumina's official protocol and a previous report (Wang et al., 2021a).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eXTT cell viability assay\u003c/h2\u003e \u003cp\u003eThe cells were seeded onto 96-well plates at a density of 4\u0026times;10\u003csup\u003e3\u003c/sup\u003e cells per well for MDA-MB-231 and MCF-7 cells, and 6\u0026times;10\u003csup\u003e3\u003c/sup\u003e cells per well for 4T1 cells. For XTT assay, the procedure followed the methods described in a previous report (Yuan et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eTumorsphere formation assay\u003c/h2\u003e \u003cp\u003eMCF-7 and 4T1 cells were seeded in ultra-low attachment 96-well plates (Corning) at a density of 500 cells per well with serum-free cell culture medium supplemented with 20 ng/ml recombinant human fibroblast growth factor basic, 20 ng/ml recombinant human epidermal growth factor, 10 \u0026micro;g/ml insulin and 1 \u0026times; B27. After 14 days of cell incubation, images of tumorspheres larger than 50 \u0026micro;m in diameter were captured using a light microscope (Nikon) and analyzed using ImageJ software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://imagej.nih.gov/ij/\u003c/span\u003e\u003cspan address=\"https://imagej.nih.gov/ij/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eReal-time PCR\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted using Trizol reagent (Ambion). Real-time PCR reactions were performed on the AriaMx Real-Time PCR System (Agilent Technologies, USA) using Brilliant III Ultra-Fast SYBR Green Low ROX qPCR Master Mix (Agilent Technologies, USA). The fold expression or repression of the target gene relative to the internal control gene TBP in each sample was then calculated by the formula:\u003c/p\u003e \u003cp\u003e2\u003csup\u003e-△△Cq\u003c/sup\u003e where △Cq\u0026thinsp;=\u0026thinsp;Cq \u003csub\u003etarget gene\u003c/sub\u003e \u0026ndash; Cq \u003csub\u003einternal control\u003c/sub\u003e and △△Cq = △Cq \u003csub\u003etest sample\u003c/sub\u003e - △Cq \u003csub\u003econtrol sample\u003c/sub\u003e\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eWestern blot\u003c/h2\u003e \u003cp\u003eThe detailed procedure followed a previous report (Yuan et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The primary antibodies used for Western blot analysis included NDUFS1 (1:1000, GeneTex, GTX113787), c-Myc (1:1000, Abcam, ab32072), PROX1 (1:1000, GeneTex, GTX129143), CD44 (1:1000, GeneTex, GTX102111), Oct4 (1:1000, GeneTex, GTX627419), CD133 (1:1000, GeneTex, GTX100567), ALDH1A1 (1:5000, GeneTex, GTX123973), Nanog (1:1000, GeneTex, GTX100863), KLF4 (1:1000, Abcam, ab151733), ALDH2 (1:1000, GeneTex, GTX101429), Notch1 (1:1000, Cell Signaling, #3608), SOX2 (1:3000, GeneTex, GTX101507), MEF2C (1:2500, GeneTex, GTX105433), Wnt-5a (1:250, Abcam, ab229200), GAPDH (1:60000, GeneTex, GTX100118), and α-Tubulin (1:10000, Genetex, GTX112141).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemistry\u003c/h2\u003e \u003cp\u003eFor immunohistochemistry (IHC), slides were baked, de-waxed, and stained with avidin-biotin complexes following our previous procedure (Wang et al., 2021a). Immunohistochemical staining for NDUFS1 (1:100, GeneTex, GTX113787) and c-Myc (1:200, Abcam, ab32072) was carried out using the automated Bond-Max system, following the manufacturer\u0026rsquo;s instructions (Leica Microsystems). For quantification, the histochemical score (H-score) was used to detect the intensity of signals, which was calculated as the products ofpercentage of stained cells and intensity of staining. The score was evaluated independently by two experts under the same imaging conditions.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eExtracellular O\u003csub\u003e2\u003c/sub\u003e consumption assay by CLARIOstar\u003c/h2\u003e \u003cp\u003eMDA-MB-231 and MCF-7 cells were seeded onto 96-well plates (black wall with clear flat bottom) at a density of 8\u0026times;10\u003csup\u003e4\u003c/sup\u003e cells per well and incubated overnight. The medium was replaced with fresh culture medium. After addition of the extracellular O\u003csub\u003e2\u003c/sub\u003e consumption reagent (ab197243, Abcam, Cambridge, UK), the wells were promptly sealed with pre-warmed mineral oil. The extracellular O\u003csub\u003e2\u003c/sub\u003e consumption signal was measured using the CLARIOstar Plus plate reader at 1.5 minute intervals for 120 minutes at Ex/Em\u0026thinsp;=\u0026thinsp;360/650 nm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eGlycolysis assay\u003c/h2\u003e \u003cp\u003eMDA-MB-231 and MCF-7 cells were seeded onto 96-well plates at a density of 8\u0026times;10\u003csup\u003e4\u003c/sup\u003e cells per well and cultured overnight. The medium was replaced with fresh culture medium. After purging CO\u003csub\u003e2\u003c/sub\u003e in a CO\u003csub\u003e2\u003c/sub\u003e-free incubator at 37\u0026deg;C with 95% humidity for 3 hours, the medium was replaced with the respiration buffer containing the glycolysis assay reagent (Abcam, ab197244). The glycolysis signal (lifetime signal) was measured using the CLARIOstar Plus plate reader at 1.5 minute intervals for \u0026gt;\u0026thinsp;120 minutes at Ex/Em\u0026thinsp;=\u0026thinsp;380/615 nm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eSeahorse bioscience extracellular flux analyzer for OCR\u003c/h2\u003e \u003cp\u003eSeahorse XF Analyzer (Agilent) was applied for OCR analyses. MDA-MB-231 and MCF-7 cells were seeded in 8-well Seahorse XF Cell Culture Microplates at density of 8\u0026times;10\u003csup\u003e3\u003c/sup\u003e cells per well and cultured with 5% CO\u003csub\u003e2\u003c/sub\u003e at 37\u0026deg;C in a humidified incubator. The detailed procedure followed a previous report (Yuan et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eAnimal study\u003c/h2\u003e \u003cp\u003e Experiments involving animals were approved by the Institutional Animal Care and Utilization Committee of Kaohsiung Medical University, Kaohsiung, Taiwan (Approval no. 108126). According to principles of 3Rs, we minimized the number of animals used in our experiments. Six-week-old female BALB/c mice were purchased from the National Laboratory Animal Center (NLAC, Taipei, Taiwan). Mice were randomized into two groups of ten. 4T1 cells expressing luciferase (1 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells in 50 \u0026micro;l normal saline and 50 \u0026micro;l Matrigel per mouse) were subcutaneously injected into the left fourth mammary fat pads of mice. The tumor size was measured weekly and calculated by the formula of (width\u0026sup2; \u0026times; length)/2. All mice were monitored weekly using an IVIS50 Spectrum in vivo imaging system (Xenogen) with the injection of firefly D-luciferin substrate (Biosynth). After 6 weeks, all mice were sacrificed, and the orthotopic tumors were collected for tumor weight and tumor volume measurements, followed by immunohistochemical analysis.\u003c/p\u003e \u003cp\u003eFor the study of therapeutic effects of metformin and rotenone, female BALB/c mice were randomly assigned to six groups, each consisting of eight mice. After the orthotopic tumor became measurable, injections of 1% DMSO, 200 mg/kg metformin, and 2.5 mg/kg rotenone were administered into the peritoneal cavity of the mice at a frequency of five times per week. After four weeks of treatment, all mice were sacrificed, and orthotopic tumors were collected for the assessment of tumor weight and volume, followed by immunohistochemical analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using the SPSS 14.0 statistical package (SPSS). The cut off point for high and low NDUFS1 level was determined by the receiver operating characteristic (ROC) curve. The associations between NDUFS1 level and clinicopathologic characteristics were analyzed by the Chi-square test. Data from three independent experiments were analyzed by the Student t test for comparison between two groups using Prism 9.5.0 software (GraphPad). One-way analysis of variance (ANOVA) with post-hoc Tukey\u0026rsquo;s test was used for multiple group comparisons. The data were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD and the P values less than 0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"588\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4558%;\"\u003e\n \u003cp\u003eADSCs\u003c/p\u003e\n \u003cp\u003eAMPK\u003c/p\u003e\n \u003cp\u003eATP\u003c/p\u003e\n \u003cp\u003eHGF\u003c/p\u003e\n \u003cp\u003eECAR\u003c/p\u003e\n \u003cp\u003eEMT\u003c/p\u003e\n \u003cp\u003eEV\u003c/p\u003e\n \u003cp\u003eETC\u003c/p\u003e\n \u003cp\u003eFAO\u003c/p\u003e\n \u003cp\u003ehKD1\u003c/p\u003e\n \u003cp\u003ehKD2\u003c/p\u003e\n \u003cp\u003eIGF\u003c/p\u003e\n \u003cp\u003eIHC\u003c/p\u003e\n \u003cp\u003eIVIS\u003c/p\u003e\n \u003cp\u003eLuc\u003c/p\u003e\n \u003cp\u003eMSCs\u003c/p\u003e\n \u003cp\u003emtDNA\u003c/p\u003e\n \u003cp\u003eNADH\u003c/p\u003e\n \u003cp\u003enDNA\u003c/p\u003e\n \u003cp\u003eNDUFS1\u003c/p\u003e\n \u003cp\u003eNGF\u003c/p\u003e\n \u003cp\u003eOCR\u003c/p\u003e\n \u003cp\u003eOE\u003c/p\u003e\n \u003cp\u003eOXPHOS\u003c/p\u003e\n \u003cp\u003eROS\u003c/p\u003e\n \u003cp\u003eTCA\u003c/p\u003e\n \u003cp\u003eTLR4\u003c/p\u003e\n \u003cp\u003eVEGF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85.5442%;\"\u003e\n \u003cp\u003eAdipose-derived stem cells\u003c/p\u003e\n \u003cp\u003eAMP-activated protein kinase\u003c/p\u003e\n \u003cp\u003eAdenosine triphosphate\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eHepatocyte growth factor\u003c/p\u003e\n \u003cp\u003eExtracellular acidification rate\u003c/p\u003e\n \u003cp\u003eEpithelial-to-mesenchymal transition\u003c/p\u003e\n \u003cp\u003eEmpty vector\u003c/p\u003e\n \u003cp\u003eElectron transport chain\u003c/p\u003e\n \u003cp\u003eFatty acid oxidation\u003c/p\u003e\n \u003cp\u003eKnockdown of human NDUFS1 clone 1\u003c/p\u003e\n \u003cp\u003eKnockdown of human NDUFS1 clone 2\u003c/p\u003e\n \u003cp\u003eInsulin-like growth factor\u003c/p\u003e\n \u003cp\u003eImmunohistochemistry\u003c/p\u003e\n \u003cp\u003eIn vivo imaging system\u003c/p\u003e\n \u003cp\u003eKnockdown of firefly luciferase\u003c/p\u003e\n \u003cp\u003eMesenchymal stem cells\u003c/p\u003e\n \u003cp\u003eMitochondria DNA\u003c/p\u003e\n \u003cp\u003eNicotinamide adenine dinucleotide\u003c/p\u003e\n \u003cp\u003eNuclear DNA\u003c/p\u003e\n \u003cp\u003eNADH:Ubiquinone Oxidoreductase Core Subunit S1\u003c/p\u003e\n \u003cp\u003eNerve growth factor\u003c/p\u003e\n \u003cp\u003eOxygen consumption rate\u003c/p\u003e\n \u003cp\u003eOverexpression of NDUFS1\u003c/p\u003e\n \u003cp\u003eOxidative phosphorylation\u003c/p\u003e\n \u003cp\u003eReactive oxygen species\u003c/p\u003e\n \u003cp\u003eTricarboxylic acid\u003c/p\u003e\n \u003cp\u003eToll-like receptor 4\u003c/p\u003e\n \u003cp\u003eVascular endothelial growth factor\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the National Science and Technology Council (NSTC 112-2314-B-037-112-MY3, NSTC 112-2314-B-037-120) and the Center for Intelligent Drug Systems and Smart Biodevices (IDS\u003csup\u003e2\u003c/sup\u003eB) from the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education, Taiwan. This work was also supported by grants from Kaohsiung Medical University Hospital (KMUH109-9R44, KMUH110-0R43, KMUH111-1R37, KMUH-DK(A)110001, KMUH-DK(A)112001) and Kaohsiung Medical University (KMU-DK(A)111005, KMU-DK(A)112006, NYCUKMU-111-I002, NYCU-KMU-112-I005, KMU-TC112A03-5, NYCUKMU-113-I002), Taiwan.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eDeclaration of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe declare no conflict of interest\u003c/p\u003e\n\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAl-Suhaimi, E.A., and A. Shehzad. 2013. Leptin, resistin and visfatin: the missing link between endocrine metabolic disorders and immunity. \u003cem\u003eEuropean journal of medical research\u003c/em\u003e 18:1-13.\u003c/li\u003e\n\u003cli\u003eAn, C., I. Pipia, A.S. Ruiz, I. Arg\u0026uuml;elles, M. An, S. Wase, and G. Peng. 2023. The molecular link between obesity and genomic instability in cancer development. \u003cem\u003eCancer Lett\u003c/em\u003e 555:216035.\u003c/li\u003e\n\u003cli\u003eAshton, T.M., W.G. McKenna, L.A. Kunz-Schughart, and G.S. Higgins. 2018. Oxidative Phosphorylation as an Emerging Target in Cancer Therapy. \u003cem\u003eClin Cancer Res\u003c/em\u003e 24:2482-2490.\u003c/li\u003e\n\u003cli\u003eBai, R., and J. Cui. 2023. Mitochondrial immune regulation and anti-tumor immunotherapy strategies targeting mitochondria. \u003cem\u003eCancer Lett\u003c/em\u003e 564:216223.\u003c/li\u003e\n\u003cli\u003eBian, C., Z. Zheng, J. Su, H. Wang, S. Chang, Y. Xin, and X. Jiang. 2022. Targeting Mitochondrial Metabolism to Reverse Radioresistance: An Alternative to Glucose Metabolism. \u003cem\u003eAntioxidants (Basel)\u003c/em\u003e 11:\u003c/li\u003e\n\u003cli\u003eBourin, P., B.A. Bunnell, L. Casteilla, M. Dominici, A.J. Katz, K.L. March, H. Redl, J.P. Rubin, K. Yoshimura, and J.M. Gimble. 2013. Stromal cells from the adipose tissue-derived stromal vascular fraction and culture expanded adipose tissue-derived stromal/stem cells: a joint statement of the International Federation for Adipose Therapeutics and Science (IFATS) and the International Society for Cellular Therapy (ISCT). \u003cem\u003eCytotherapy\u003c/em\u003e 15:641-648.\u003c/li\u003e\n\u003cli\u003eCalle, E.E., and M.J. Thun. 2004. Obesity and cancer. \u003cem\u003eOncogene\u003c/em\u003e 23:6365-6378.\u003c/li\u003e\n\u003cli\u003eCastelli, S., F. Ciccarone, P. De Falco, and M.R. Ciriolo. 2023. Adaptive antioxidant response to mitochondrial fatty acid oxidation determines the proliferative outcome of cancer cells. \u003cem\u003eCancer Lett\u003c/em\u003e 554:216010.\u003c/li\u003e\n\u003cli\u003eChan, D.S., A. Vieira, D. Aune, E.V. Bandera, D. Greenwood, A. McTiernan, D.N. Rosenblatt, I. Thune, R. Vieira, and T. Norat. 2014. Body mass index and survival in women with breast cancer\u0026mdash;systematic literature review and meta-analysis of 82 follow-up studies. \u003cem\u003eAnnals of Oncology\u003c/em\u003e 25:1901-1914.\u003c/li\u003e\n\u003cli\u003eChen, D.-C., Y.-F. Chung, Y.-T. Yeh, H.-C. Chaung, F.-C. Kuo, O.-Y. Fu, H.-Y. Chen, M.-F. Hou, and S.-S.F. Yuan. 2006. Serum adiponectin and leptin levels in Taiwanese breast cancer patients. \u003cem\u003eCancer letters\u003c/em\u003e 237:109-114.\u003c/li\u003e\n\u003cli\u003eChen, T., D. Li, Y. Wang, X. Shen, A. Dong, C. Dong, K. Duan, J. Ren, W. Li, G. Shu, J. Yang, Y. Xie, F. Qian, and J. Zhou. 2023. Loss of NDUFS1 promotes gastric cancer progression by activating the mitochondrial ROS-HIF1\u0026alpha;-FBLN5 signaling pathway. \u003cem\u003eBr J Cancer\u003c/em\u003e 129:1261-1273.\u003c/li\u003e\n\u003cli\u003eDeng, L., L. Liao, Y.L. Zhang, S.Y. Hu, S.Y. Yang, X.Y. Ma, M.Y. Huang, F.L. Zhang, and D.Q. Li. 2023. MYC-driven U2SURP regulates alternative splicing of SAT1 to promote triple-negative breast cancer progression. \u003cem\u003eCancer Lett\u003c/em\u003e 560:216124.\u003c/li\u003e\n\u003cli\u003eDeRose, Y.S., G. Wang, Y.-C. Lin, P.S. Bernard, S.S. Buys, M.T. Ebbert, R. Factor, C. Matsen, B.A. Milash, and E. Nelson. 2011. Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes. \u003cem\u003eNature medicine\u003c/em\u003e 17:1514-1520.\u003c/li\u003e\n\u003cli\u003eDeshmukh, S.K., S.K. Srivastava, A. Bhardwaj, A.P. Singh, N. Tyagi, S. Marimuthu, D.L. Dyess, V. Dal Zotto, J.E. Carter, and S. Singh. 2015. Resistin and interleukin-6 exhibit racially-disparate expression in breast cancer patients, display molecular association and promote growth and aggressiveness of tumor cells through STAT3 activation. \u003cem\u003eOncotarget\u003c/em\u003e 6:11231-11241.\u003c/li\u003e\n\u003cli\u003eDianat-Moghadam, H., M. Sharifi, R. Salehi, M. Keshavarz, M. Shahgolzari, and Z. Amoozgar. 2023. Engaging stemness improves cancer immunotherapy. \u003cem\u003eCancer Lett\u003c/em\u003e 554:216007.\u003c/li\u003e\n\u003cli\u003eDivella, R., R. De Luca, I. Abbate, E. Naglieri, and A. Daniele. 2016. Obesity and cancer: the role of adipose tissue and adipo-cytokines-induced chronic inflammation. \u003cem\u003eJournal of Cancer\u003c/em\u003e 7:2346.\u003c/li\u003e\n\u003cli\u003eDubey, N.K., V.K. Mishra, R. Dubey, Y.-H. Deng, F.-C. Tsai, and W.-P. Deng. 2018. Revisiting the advances in isolation, characterization and secretome of adipose-derived stromal/stem cells. \u003cem\u003eInternational journal of molecular sciences\u003c/em\u003e 19:2200.\u003c/li\u003e\n\u003cli\u003eEllinger, J., M. Poss, M. Bruggemann, A. Gromes, D. Schmidt, N. Ellinger, Y. Tolkach, D. Dietrich, G. Kristiansen, and S.C. Muller. 2017. Systematic Expression Analysis of Mitochondrial Complex I Identifies NDUFS1 as a Biomarker in Clear-Cell Renal-Cell Carcinoma. \u003cem\u003eClin Genitourin Cancer\u003c/em\u003e 15:e551-e562.\u003c/li\u003e\n\u003cli\u003eElsir, T., A. Smits, M.S. Lindstrom, and M. Nister. 2012. Transcription factor PROX1: its role in development and cancer. \u003cem\u003eCancer Metastasis Rev\u003c/em\u003e 31:793-805.\u003c/li\u003e\n\u003cli\u003eFreese, K.E., L. Kokai, R.P. Edwards, B.J. Philips, M.A. Sheikh, J. Kelley, J. Comerci, K.G. Marra, J.P. Rubin, and F. Linkov. 2015. Adipose-derived stems cells and their role in human cancer development, growth, progression, and metastasis: a systematic review. \u003cem\u003eCancer research\u003c/em\u003e 75:1161-1168.\u003c/li\u003e\n\u003cli\u003eGnerlich, J.L., K.A. Yao, P.S. Fitchev, R.A. Goldschmidt, M.C. Bond, M. Cornwell, and S.E. Crawford. 2013. Peritumoral expression of adipokines and fatty acids in breast cancer. \u003cem\u003eAnnals of surgical oncology\u003c/em\u003e 20:731-738.\u003c/li\u003e\n\u003cli\u003eGoodwin, P.J., B.E. Chen, K.A. Gelmon, T.J. Whelan, M. Ennis, J. Lemieux, J.A. Ligibel, D.L. Hershman, I.A. Mayer, T.J. Hobday, J.M. Bliss, P. Rastogi, M. Rabaglio-Poretti, S.D. Mukherjee, J.R. Mackey, V.G. Abramson, C. Oja, R. Wesolowski, A.M. Thompson, D.W. Rea, P.M. Stos, L.E. Shepherd, V. Stambolic, and W.R. Parulekar. 2022. Effect of Metformin vs Placebo on Invasive Disease-Free Survival in Patients With Breast Cancer: The MA.32 Randomized Clinical Trial. \u003cem\u003eJama\u003c/em\u003e 327:1963-1973.\u003c/li\u003e\n\u003cli\u003eHlavna, M., L. Koh\u0026uacute;t, J. Lipkov\u0026aacute;, J. Bienertova-Vasku, Z. Dostalova, J. Chovanec, and A. Vasku. 2011. Relationship of resistin levels with endometrial cancer risk. \u003cem\u003eNeoplasma\u003c/em\u003e 58:124-128.\u003c/li\u003e\n\u003cli\u003eHousa, D., Z. Vernerova, J. Heracek, P. Cechak, B. Rosova, J. Kuncova, and M. Haluzik. 2008. Serum resistin levels in benign prostate hyperplasia and non-metastatic prostate cancer: possible role in cancer progression. \u003cem\u003eNeoplasma\u003c/em\u003e 55:442.\u003c/li\u003e\n\u003cli\u003eHoy, A.J., S. Balaban, and D.N. Saunders. 2017. Adipocyte\u0026ndash;tumor cell metabolic crosstalk in breast cancer. \u003cem\u003eTrends in molecular medicine\u003c/em\u003e 23:381-392.\u003c/li\u003e\n\u003cli\u003eHung, A.C., S. Lo, M.-F. Hou, Y.-C. Lee, C.-H. Tsai, Y.-Y. Chen, W. Liu, Y.-H. Su, Y.-H. Lo, and C.-H. Wang. 2016. Extracellular visfatin-promoted malignant behavior in breast cancer is mediated through c-Abl and STAT3 activation. \u003cem\u003eClinical Cancer Research\u003c/em\u003e 22:4478-4490.\u003c/li\u003e\n\u003cli\u003eJiang, Y., L. Lu, Y. Hu, Q. Li, C. An, X. Yu, L. Shu, A. Chen, C. Niu, and L. Zhou. 2016. Resistin induces hypertension and insulin resistance in mice via a TLR4-dependent pathway. \u003cem\u003eScientific reports\u003c/em\u003e 6:22193.\u003c/li\u003e\n\u003cli\u003eJones, R.A., T.J. Robinson, J.C. Liu, M. Shrestha, V. Voisin, Y. Ju, P.E. Chung, G. Pellecchia, V.L. Fell, S. Bae, L. Muthuswamy, A. Datti, S.E. Egan, Z. Jiang, G. Leone, G.D. Bader, A. Schimmer, and E. Zacksenhaus. 2016. RB1 deficiency in triple-negative breast cancer induces mitochondrial protein translation. \u003cem\u003eJ Clin Invest\u003c/em\u003e 126:3739-3757.\u003c/li\u003e\n\u003cli\u003eKoerner, A., J. Kratzsch, and W. Kiess. 2005. Adipocytokines: leptin\u0026mdash;the classical, resistin\u0026mdash;the controversical, adiponectin\u0026mdash;the promising, and more to come. \u003cem\u003eBest practice \u0026amp; research Clinical endocrinology \u0026amp; metabolism\u003c/em\u003e 19:525-546.\u003c/li\u003e\n\u003cli\u003eKroemer, G., and J. Pouyssegur. 2008. Tumor cell metabolism: cancer\u0026apos;s Achilles\u0026apos; heel. \u003cem\u003eCancer cell\u003c/em\u003e 13:472-482.\u003c/li\u003e\n\u003cli\u003eLee, J.O., N. Kim, H.J. Lee, Y.W. Lee, S.J. Kim, S.H. Park, and H.S. Kim. 2016. Resistin, a fat-derived secretory factor, promotes metastasis of MDA-MB-231 human breast cancer cells through ERM activation. \u003cem\u003eScientific reports\u003c/em\u003e 6:18923.\u003c/li\u003e\n\u003cli\u003eLee, K.L., Y.C. Kuo, Y.S. Ho, and Y.H. Huang. 2019. Triple-Negative Breast Cancer: Current Understanding and Future Therapeutic Breakthrough Targeting Cancer Stemness. \u003cem\u003eCancers (Basel)\u003c/em\u003e 11:\u003c/li\u003e\n\u003cli\u003eLee, Y.-C., Y.-J. Chen, C.-C. Wu, S. Lo, M.-F. Hou, and S.-S.F. Yuan. 2012. Resistin expression in breast cancer tissue as a marker of prognosis and hormone therapy stratification. \u003cem\u003eGynecologic oncology\u003c/em\u003e 125:742-750.\u003c/li\u003e\n\u003cli\u003eLee, Y.-C., Y.-H. Yang, J.-H. Su, H.-L. Chang, M.-F. Hou, and S.-S.F. Yuan. 2011. High visfatin expression in breast cancer tissue is associated with poor survival. \u003cem\u003eCancer epidemiology, biomarkers \u0026amp; prevention\u003c/em\u003e 20:1892-1901.\u003c/li\u003e\n\u003cli\u003eLiao, D.J., and R.B. Dickson. 2000. c-Myc in breast cancer. \u003cem\u003eEndocr Relat Cancer\u003c/em\u003e 7:143-164.\u003c/li\u003e\n\u003cli\u003eLiu, Y., C. Zhu, L. Tang, Q. Chen, N. Guan, K. Xu, and X. Guan. 2021. MYC dysfunction modulates stemness and tumorigenesis in breast cancer. \u003cem\u003eInt J Biol Sci\u003c/em\u003e 17:178-187.\u003c/li\u003e\n\u003cli\u003eLunetti, P., M. Di Giacomo, D. Vergara, S. De Domenico, M. Maffia, V. Zara, L. Capobianco, and A. Ferramosca. 2019. Metabolic reprogramming in breast cancer results in distinct mitochondrial bioenergetics between luminal and basal subtypes. \u003cem\u003eFebs j\u003c/em\u003e 286:688-709.\u003c/li\u003e\n\u003cli\u003eMaysaa El Sayed, Z., F. Mansour, M. Ghal, and S. Abou-Zahra. 2011. Evaluation of interleukin-8 in hepatitis C virus infection: relation to combined peg-interferon ribavirin response and genotype 4. \u003cem\u003eImmunological Investigations\u003c/em\u003e 40:29-38.\u003c/li\u003e\n\u003cli\u003eMichail, A., D. Gkikas, D. Stellas, V. Kaltezioti, and P.K. Politis. 2023. Prox1 Suppresses the Proliferation of Breast Cancer Cells via Direct Inhibition of c-Myc Gene Expression. \u003cem\u003eCells\u003c/em\u003e 12:\u003c/li\u003e\n\u003cli\u003eMoreno-Sanchez, R., S. Rodriguez-Enriquez, A. Marin-Hernandez, and E. Saavedra. 2007. Energy metabolism in tumor cells. \u003cem\u003eFEBS J\u003c/em\u003e 274:1393-1418.\u003c/li\u003e\n\u003cli\u003ePetrova, T.V., A. Nykanen, C. Norrmen, K.I. Ivanov, L.C. Andersson, C. Haglund, P. Puolakkainen, F. Wempe, H. von Melchner, G. Gradwohl, S. Vanharanta, L.A. Aaltonen, J. Saharinen, M. Gentile, A. Clarke, J. Taipale, G. Oliver, and K. Alitalo. 2008. Transcription factor PROX1 induces colon cancer progression by promoting the transition from benign to highly dysplastic phenotype. \u003cem\u003eCancer Cell\u003c/em\u003e 13:407-419.\u003c/li\u003e\n\u003cli\u003ePham, D.V., and P.H. Park. 2021. Tumor Metabolic Reprogramming by Adipokines as a Critical Driver of Obesity-Associated Cancer Progression. \u003cem\u003eInt J Mol Sci\u003c/em\u003e 22:\u003c/li\u003e\n\u003cli\u003ePonomarev, A., Z. Gilazieva, V. Solovyeva, C. Allegrucci, and A. Rizvanov. 2022. Intrinsic and Extrinsic Factors Impacting Cancer Stemness and Tumor Progression. \u003cem\u003eCancers (Basel)\u003c/em\u003e 14:\u003c/li\u003e\n\u003cli\u003ePuchades-Carrasco, L., and A. Pineda-Lucena. 2017. Metabolomics applications in precision medicine: an oncological perspective. \u003cem\u003eCurrent topics in medicinal chemistry\u003c/em\u003e 17:2740-2751.\u003c/li\u003e\n\u003cli\u003eSajnani, K., F. Islam, R.A. Smith, V. Gopalan, and A.K.-Y. Lam. 2017. Genetic alterations in Krebs cycle and its impact on cancer pathogenesis. \u003cem\u003eBiochimie\u003c/em\u003e 135:164-172.\u003c/li\u003e\n\u003cli\u003eSălăgeanu, A., L. Lerescu, I. Caraş, R. Pitica, G. Gangura, R. Costea, and S. Neagu. 2010. Serum levels of adipokines resistin and leptin in patients with colon cancer. \u003cem\u003eJournal of medicine and life\u003c/em\u003e 3:416.\u003c/li\u003e\n\u003cli\u003eSharma, L.K., J. Lu, and Y. Bai. 2009. Mitochondrial respiratory complex I: structure, function and implication in human diseases. \u003cem\u003eCurr Med Chem\u003c/em\u003e 16:1266-1277.\u003c/li\u003e\n\u003cli\u003eSteppan, C.M., S.T. Bailey, S. Bhat, E.J. Brown, R.R. Banerjee, C.M. Wright, H.R. Patel, R.S. Ahima, and M.A. Lazar. 2001. The hormone resistin links obesity to diabetes. \u003cem\u003eNature\u003c/em\u003e 409:307-312.\u003c/li\u003e\n\u003cli\u003eSu, C.Y., Y.C. Chang, C.J. Yang, M.S. Huang, and M. Hsiao. 2016. The opposite prognostic effect of NDUFS1 and NDUFS8 in lung cancer reflects the oncojanus role of mitochondrial complex I. \u003cem\u003eSci Rep\u003c/em\u003e 6:31357.\u003c/li\u003e\n\u003cli\u003eSu, C.Y., and M. Hsiao. 2013. NDUFS1 as a prognostic marker in lung cancer: a clinicopathological analysis of 106 cases of non‐small cell lung cancer. In Wiley Online Library.\u003c/li\u003e\n\u003cli\u003eTahergorabi, Z., M. Khazaei, M. Moodi, and E. Chamani. 2016. From obesity to cancer: a review on proposed mechanisms. \u003cem\u003eCell biochemistry and function\u003c/em\u003e 34:533-545.\u003c/li\u003e\n\u003cli\u003eTarkowski, A., J. Bjersing, A. Shestakov, and M.I. Bokarewa. 2010. Resistin competes with lipopolysaccharide for binding to toll‐like receptor 4. \u003cem\u003eJournal of cellular and molecular medicine\u003c/em\u003e 14:1419-1431.\u003c/li\u003e\n\u003cli\u003eVasan, K., M. Werner, and N.S. Chandel. 2020. Mitochondrial Metabolism as a Target for Cancer Therapy. \u003cem\u003eCell Metab\u003c/em\u003e 32:341-352.\u003c/li\u003e\n\u003cli\u003eVelasco-Velazquez, M.A., V.M. Popov, M.P. Lisanti, and R.G. Pestell. 2011. The role of breast cancer stem cells in metastasis and therapeutic implications. \u003cem\u003eAm J Pathol\u003c/em\u003e 179:2-11.\u003c/li\u003e\n\u003cli\u003eWang, C., P. Wang, Y. Hsieh, S. Lo, Y. Lee, Y. Chen, C. Tsai, W. Chiu, S. Chu-Sung Hu, and C. Lu. 2018a. Resistin facilitates breast cancer progression via TLR4-mediated induction of mesenchymal phenotypes and stemness properties. \u003cem\u003eOncogene\u003c/em\u003e 37:589-600.\u003c/li\u003e\n\u003cli\u003eWang, L., X. Zhan, X. Shen, M. Li, J. Yang, W. Yu, H. Chen, B. Jin, and Z. Mao. 2018b. P16 promotes the growth and mobility potential of breast cancer both in vitro and in vivo: the key role of the activation of IL-6/JAK2/STAT3 signaling. \u003cem\u003eMol Cell Biochem\u003c/em\u003e 446:137-148.\u003c/li\u003e\n\u003cli\u003eWang, Y.Y., Y.K. Chen, S. Lo, T.C. Chi, Y.H. Chen, S.C. Hu, Y.W. Chen, S.S. Jiang, F.Y. Tsai, W. Liu, R.N. Li, Y.C. Hsieh, C.J. Huang, and S.F. Yuan. 2021a. MRE11 promotes oral cancer progression through RUNX2/CXCR4/AKT/FOXA2 signaling in a nuclease-independent manner. \u003cem\u003eOncogene\u003c/em\u003e 40:3510-3532.\u003c/li\u003e\n\u003cli\u003eWang, Y.Y., A.C. Hung, S. Lo, and S.F. Yuan. 2021b. Adipocytokines visfatin and resistin in breast cancer: Clinical relevance, biological mechanisms, and therapeutic potential. \u003cem\u003eCancer Lett\u003c/em\u003e 498:229-239.\u003c/li\u003e\n\u003cli\u003eWang, Y.Y., A.C. Hung, Y.C. Wu, S. Lo, H.D. Chen, Y.K. Chen, Y.C. Hsieh, S.C. Hu, M.F. Hou, and S.F. Yuan. 2022. ADSCs stimulated by resistin promote breast cancer cell malignancy via CXCL5 in a breast cancer coculture model. \u003cem\u003eSci Rep\u003c/em\u003e 12:15437.\u003c/li\u003e\n\u003cli\u003eWeinberg, S.E., and N.S. Chandel. 2015. Targeting mitochondria metabolism for cancer therapy. \u003cem\u003eNature chemical biology\u003c/em\u003e 11:9-15.\u003c/li\u003e\n\u003cli\u003eWhitaker-Menezes, D., U.E. Martinez-Outschoorn, N. Flomenberg, R.C. Birbe, A.K. Witkiewicz, A. Howell, S. Pavlides, A. Tsirigos, A. Ertel, R.G. Pestell, P. Broda, C. Minetti, M.P. Lisanti, and F. Sotgia. 2011. Hyperactivation of oxidative mitochondrial metabolism in epithelial cancer cells in situ: visualizing the therapeutic effects of metformin in tumor tissue. \u003cem\u003eCell Cycle\u003c/em\u003e 10:4047-4064.\u003c/li\u003e\n\u003cli\u003eYakisich, J.S., N. Azad, V. Kaushik, and A.K.V. Iyer. 2017. Cancer Cell Plasticity: Rapid Reversal of Chemosensitivity and Expression of Stemness Markers in Lung and Breast Cancer Tumorspheres. \u003cem\u003eJ Cell Physiol\u003c/em\u003e 232:2280-2286.\u003c/li\u003e\n\u003cli\u003eYan, L., Y. Tan, G. Chen, J. Fan, and J. Zhang. 2021. Harnessing Metabolic Reprogramming to Improve Cancer Immunotherapy. \u003cem\u003eInt J Mol Sci\u003c/em\u003e 22:\u003c/li\u003e\n\u003cli\u003eYuan, S.-S.F., Y.-M. Wang, L.-P. Chan, A.C. Hung, H.D.H. Nguyen, Y.-K. Chen, S.C.S. Hu, S. Lo, and Y.-Y. Wang. 2023a. IL-1RA promotes oral squamous cell carcinoma malignancy through mitochondrial metabolism-mediated EGFR/JNK/SOX2 pathway. \u003cem\u003eJournal of Translational Medicine\u003c/em\u003e 21:473.\u003c/li\u003e\n\u003cli\u003eYuan, S.F., L.P. Chan, H.D.H. Nguyen, C.W. Su, Y.K. Chen, J.Y. Chen, S. Shimodaira, S.C. Hu, S. Lo, and Y.Y. Wang. 2024. Areca nut-induced metabolic reprogramming and M2 differentiation promote OPMD malignant transformation. \u003cem\u003eJ Exp Clin Cancer Res\u003c/em\u003e 43:233.\u003c/li\u003e\n\u003cli\u003eYuan, S.F., Y.M. Wang, L.P. Chan, A.C. Hung, H.D.H. Nguyen, Y.K. Chen, S.C. Hu, S. Lo, and Y.Y. Wang. 2023b. IL-1RA promotes oral squamous cell carcinoma malignancy through mitochondrial metabolism-mediated EGFR/JNK/SOX2 pathway. \u003cem\u003eJ Transl Med\u003c/em\u003e 21:473.\u003c/li\u003e\n\u003cli\u003eZhang, Y., A. Daquinag, D.O. Traktuev, F. Amaya-Manzanares, P.J. Simmons, K.L. March, R. Pasqualini, W. Arap, and M.G. Kolonin. 2009. White adipose tissue cells are recruited by experimental tumors and promote cancer progression in mouse models. \u003cem\u003eCancer research\u003c/em\u003e 69:5259-5266.\u003c/li\u003e\n\u003cli\u003eZheng, J. 2012. Energy metabolism of cancer: Glycolysis versus oxidative phosphorylation (Review). \u003cem\u003eOncol Lett\u003c/em\u003e 4:1151-1157.\u003c/li\u003e\n\u003cli\u003eZhu, L., Q. Tian, H. Gao, K. Wu, B. Wang, G. Ge, S. Jiang, K. Wang, C. Zhou, J. He, P. Liu, Y. Ren, and B. Wang. 2022. PROX1 promotes breast cancer invasion and metastasis through WNT/beta-catenin pathway via interacting with hnRNPK. \u003cem\u003eInt J Biol Sci\u003c/em\u003e 18:2032-2046.\u003c/li\u003e\n\u003cli\u003eZu, X.L., and M. Guppy. 2004. Cancer metabolism: facts, fantasy, and fiction. \u003cem\u003eBiochem Biophys Res Commun\u003c/em\u003e 313:459-465.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"breast cancer, ADSCs, resistin, NDUFS1, mitochondrial metabolism","lastPublishedDoi":"10.21203/rs.3.rs-5968936/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5968936/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBreast cancer is the most prevalent cancer among women. Previous studies demonstrated that adipose-derived stem cells (ADSCs) co-cultured with resistin promote malignant behaviors in breast cancer cells. This study explores the roles of ADSCs and the adipocytokine resistin within the breast tumor microenvironment, emphasizing their contributions to metabolic reprogramming and cancer progression. RNA sequencing analysis of metabolic reprogramming pathways revealed that breast cancer cells in co-culture with resistin-treated ADSCs exhibited elevated expression of NDUFS1, the largest subunit of mitochondrial complex I. Knockdown of NDUFS1 inhibited breast cancer cell proliferation and tumorsphere formation, whereas its overexpression enhanced these effects through mitochondrial metabolism-mediated PROX1/c-Myc signaling pathway. Furthermore, treatment with metformin, an inhibitor of NDUFS1-activated mitochondrial metabolism, reduced Myc and PROX1 expression and diminished breast cancer cell proliferation. Syngeneic orthotopic mouse model showed that NDUFS1 downregulation significantly inhibited mammary tumor growth alongside decreased expression of PROX1 and c-Myc. Also, mitochondrial metabolism inhibitors metformin and rotenone demonstrated a therapeutic effect on NDUFS1-expressing breast tumor. Collectively, this research establishes a novel mechanistic framework linking metabolic adaptations and breast cancer, paving the way for innovative therapeutic strategies aimed at targeting NDUFS1 signaling.\u003c/p\u003e","manuscriptTitle":"NDUFS1 promotes malignant breast cancer behaviors through activation of mitochondrial metabolism and PROX1/c-Myc signaling","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-21 15:18:08","doi":"10.21203/rs.3.rs-5968936/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b9bae6e3-f0fe-4184-91f0-91c90bf29b8a","owner":[],"postedDate":"February 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-08T21:20:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-21 15:18:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5968936","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5968936","identity":"rs-5968936","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}