FN1 Mediated Activation of Aspartate Metabolism Promotes the Progression of Triple-negative and Luminal A Breast Cancer

FN1 Mediated Activation of Aspartate Metabolism Promotes the Progression of Triple-negative and Luminal A Breast Cancer | 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 FN1 Mediated Activation of Aspartate Metabolism Promotes the Progression of Triple-negative and Luminal A Breast Cancer Chen Chen, Leiguang Ye, Jinfeng Yi, Tong Liu, Zhigao Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2629354/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 Background Breast cancer (BC) is regarded as one of the most common cancers diagnosed among the female population and has an extremely high mortality rate. It is known that Fibronectin 1 (FN1) drives the occurrence and development of a variety of cancers through metabolic reprogramming. Aspartic acid is considered to be an important substrate for nucleotide synthesis. However, the regulatory mechanism between FN1 and aspartate metabolism is currently unclear. Methods We used RNA sequencing (RNA seq) and liquid chromatography-mass spectrometry (LC-MS) to analyze the tumor tissues and paracancerous tissues of patients. MCF7 and MDA-MB-231 cells were used to explore the effects of FN1-regulated aspartic acid metabolism on cell survival, invasion, migration and tumor growth. We used PCR, Western blot, immunocytochemistry and immunofluorescence techniques to study it. Results We found that FN1 was highly expressed in tumor tissues, especially in Lumina A and TNBC subtypes, and was associated with poor prognosis. In vivo and in vitro experiments showed that silencing FN1 inhibits the activation of the YAP1/Hippo pathway by enhancing YAP1 phosphorylation, down-regulates SLC1A3-mediated aspartate uptake and utilization by tumor cells, inhibits BC cell proliferation, invasion and migration, and promotes apoptosis. In addition, inhibition of FN1 combined with the YAP1 inhibitor or SLC1A3 inhibitor can effectively inhibit tumor growth, of which inhibition of FN1 combined with the YAP1 inhibitor is more effective. Conclusion Targeting the "FN1/YAP1/SLC1A3/Aspartate metabolism" regulatory axis provides a new target for BC diagnosis and treatment. This study also revealed that intratumoral metabolic heterogeneity plays an important role in the progression of different subtypes of breast cancer. Fibronectin 1 Metabolic reprogramming Aspartate metabolism Metabolic heterogeneity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. INTRODUCTION Breast cancer (BC) is the primary cause of cancer deaths among the female population worldwide. At present, BC has surpassed the incidence rate of lung cancer, reflecting its status as the most common malignant tumor worldwide [ 1 ]. According to the statistical data obtained from the National Central Cancer Registry (NCCR) of China, both the incidence and mortality rate of BC is predicted to continuously increase until 2030 [ 2 ]. Current treatment approaches for BC patients are based on surgical methods and assisted by chemotherapy, radiotherapy, endocrine therapy, immunotherapy, and other therapeutic methods[ 3 ]. Although these interventions have exhibited substantial progress in the clinical diagnosis and treatment of BC, the overall survival rate (OSR) of patients remains poor as a direct result of treatment resistance, particularly in the case of distant metastasis and recurrence [ 4 , 5 ]. Therefore, it is of great clinical significance and importance to identify and discover novel therapeutic targets of BC while considering the application value. BC is defined as a malignant tumor of solid consistency with strong heterogeneity. In addition to the molecular and phenotypic variations observed in cancer cells, intratumoral heterogeneity also extends to the tumor microenvironment [ 6 ]. In the 2000s, due to the wide application of high-throughput analysis, the heterogeneity between the four subtypes of breast cancer, such as Luminal A, Luminal B, HER 2 + and basal like, was well described[ 7 ]. In this regard, metabolic reprogramming is considered a hallmark of malignancy [ 8 ]. Accordingly, the metabolic reprogramming of cancer cells is driven by the combination of carcinogenic changes within the internal cellular environment in conjunction with host cytokines affecting the external tumor microenvironment [ 9 ]. In recent years, a number of studies have shown that extracellular matrix (ECM) remodeling is directly involved in regulating the metabolic reprogramming of BC cells [ 10 , 11 ] and metabolic heterogeneity is closely related to the metastatic ability of cancer cells [ 12 ]. Fibronectin (FN) is an important component of the ECM. Structurally, FN is defined as a large molecular weight glycoprotein, which exhibits different expressions and functions in various cancers [ 13 , 14 ]. FN1 directly participates in ECM formation and plays an important role in tumor cell adhesion, proliferation, migration, and invasion [ 15 , 16 ]. An increasing body of evidence has validated the importance of FN1 as a prominent tumor related gene [ 17 ], whereby its abnormal expression is closely related to the staging, prognosis, and treatment response of bladder cancer, esophageal cancer, colorectal cancer (CRC), ovarian cancer, and other tumors [ 18 – 21 ]. The solute carrier (SLC) family mediates nutrient and metabolite cell homeostasis [ 22 ]. Solute carrier family 1 member 3 (SLC1A3), also known as the glutamate/aspartate transporter (GLAST) or excitatory amino acid transporter 1 (EAAT1), is a member of the high-affinity glutamate transporter family [ 23 , 24 ]. Studies by Javier Garcia Bermudez on BC, colon cancer, and lung cancer have shown that SLC1A3 mediated aspartate uptake, was associated with resistance to inhibiting electron transport chains in vitro, and further facilitated increased growth both in vivo and under hypoxia [ 25 ]. Aspartate is regarded as an essential component of cell proliferation and is an important substrate for nucleotide synthesis. Aspartic acid could be a potential limiting metabolite of tumor growth and represents a novel target for tumor therapy [ 26 ]. SLC1A3, which forms an essential regulator in the aspartic acid metabolic pathway, is involved in the occurrence and progression of colorectal cancer [ 27 ], however, its mechanism of action in the pathogenesis of BC remains unclear. The hippo signaling pathway is characterized as a reprogrammable cellular metabolic pathway. Its activation is closely related to the energy state of cells, the availability of nutrients, the composition of tissue microenvironments and structures, as well as external biochemical signal transduction [ 28 ]. Based on its functions, this pathway enables tumor cell adaptation in response to the changing microenvironment, thus effectively promoting tumor progression [ 29 – 31 ]. As an important component of the hippo pathway, the activity of yes-associated protein 1 (YAP1) is directly affected by ECM stiffness, cell density, and shear force [ 10 , 32 ]. BC exhibits high levels of nuclear transcriptional coactivator with PDZ-binding motif (TAZ)/YAP expression, and effectively relies on nuclear TAZ/YAP transcriptional activity to reprogram the energy metabolism of tumor cells, subsequently driving the growth and invasion of BC cells [ 33 , 34 ]. It has been reported that FN can promote tumor cell growth and chemotherapy resistance through the CDC42-YAP dependent signal pathway in colorectal cancer [ 35 ]. In this study, we investigated the expression of FN1 in Luminal A and triple negative subtypes of breast cancer, and studied its regulatory role in SLC1A3 mediated aspartate uptake. FN1 is highly expressed in BC tissues, and its high expression is directly related to a poor prognosis. The findings showed that FN1 activates SLC1A3 through the YAP1/Hippo signaling pathway, regulates aspartate metabolism, promotes BC cell growth, and inhibits apoptosis. The "FN1-YAP1-SLC1A3 regulation axis" has been identified for the first time in this study. Moreover, we proved that applying inhibition of the combination FN1 and YAP1 or SLC1A3 inhibitors can play a synergistic role, whereby the therapeutic effect is significantly better than that of single drug therapy, subsequently providing a novel strategy for the treatment of Luminal A breast cancer and TNBC. This finding also showed that different subtypes of breast cancer cells have different preferences for aspartate metabolism, and different biological behaviors in tumor cells of the same subtype also have different dependence on aspartate metabolism, further clarifying the heterogeneity of tumors from the perspective of energy metabolism. 2. MATERIALS AND METHODS 2.1 Patients and breast tissue samples A total of 20 matched pairs of BC and surrounding non-cancerous tissue specimens were harvested while patients were undergoing surgical BC resection at the XX Hospital. Informed consent was obtained from all subjects prior to collection and all samples were subjected to histological confirmation. The Ethics Committee of the XX Hospital approved the present study. All experiments and protocols adhered to the ethical standards as outlined in the Declaration of Helsinki. 2.2 Metabolic profiling analysis The metabolic profiling analysis was conducted by Biotree Co., Ltd. (Shanghai, China) on the ultra-high performance liquid chromatography (UPLC) system (Waters, Milford, MA, USA) that was coupled to a 6520 series accurate quadrupole time-of-flight mass spectrometer (Q-TOF MS) system (Agilent, Santa Clara, CA, USA). The samples were randomized before analysis to avoid differences caused by the injection sequence. Autoscaling was used on the metabolomics data before multivariate analysis, in which the centered metabolite intensity was divided by the standard deviation. To decrease the false discovery rate (FDR) for biomarker selection, local FDR (lFDR) based on the P-value was calculated to adjust the multiple comparisons. The potential biomarkers were selected as univariate lFDR 1[ 36 ]. Furthermore, hierarchical cluster analysis (HCA) was conducted to detect the classification ability and concentration levels of the selected metabolites. Pathway information was extracted from the Kyoto Encyclopedia of Genes and Genomes (KEGG). All the other statistical analyses and visualizations were performed using the R platform. 2.3 RNA sequencing (RNA seq) and analysis Sequencing was carried out by Biotree Ltd. (Shanghai, China) on the Illumina (Miseq/Hiseq) platform. Paired-end reads were generated and then quality controlled in-house Perl scripts were used. The pathway enrichment analysis of the differentially expressed genes (DEGs) was performed by using the KEGG and Gene Ontology (GO) databases. The DESeq2 software based on the negative binomial distribution was used to perform statistical analysis on all data to compare genes with differences in expression between groups (with a cutoff threshold of an absolute log2 (fold change)). The method used for multiple test correction was BH (FDR correction with Benjamini/Hochberg) and P-values < 0.05 were considered as the threshold for statistical significance difference at a 95% confidence level[ 37 ]. The clusterProfiler package of R software was used in this study and utilized for GO function analysis. Based on the co-expression screening data, KEGG pathway analysis was also performed to retrieve further information. 2.4 Protein-protein interaction (PPI) The STRING website ( https://string-db.org/ ) integrated and constructed the PPI using computational predictions, which visualized the intrinsic links among of FN1, YAP1, and SCLA3 genes[ 38 ]. Cytoscape's plugin CytoHubba was used to discover key nodes in the PPI network[ 39 ]. 2.5 Cells and cell culture The BC cells used were purchased from ATCC (ATCC; Manassas, VA, USA). All the cell lines used in this study were of human origin and were cultured at 37℃ in a humidified atmosphere of 5% CO2. MCF7 and MDA-MB-231 cells were cultured in DMEM (0020916, Biological Industries, Israel) supplemented with 10% fetal bovine serum (FBS, 1618326, Biological Industries, Israel) and 1% penicillin-streptomycin. Aspartate was purchased from Sigma Aldrich (Sigma Aldrich, St. Louis, MO, USA) and used at a concentration of 5 mM [ 40 , 41 ] in the rescue experiment, consistent with prior in vitro studies linking cancer cell proliferation to aspartate metabolism. For the verteporfin (ab143294, Abcam, Cambridge, United Kingdom) / UCPH-101 (ab120309, Abcam) response experiments, MCF7 and MDA-MB-231 cells were given either vehicle or 10 µm verteporfin / UCPH-101. 2.6 Cell transfection For cell transfection, short hairpin RNA against FN1 (sh-FN1), short hairpin RNA against SLC1A3 (sh-SLC1A3), sh-FN1 + sh-SLC1A3, or their negative controls (sh-NCs) (E2691, Promega, WI USA) were constructed into lentiviral vectors and transfected into 293 T cells for 72 h to establish lentivirus particles. Then the lentivirus particles were transfected into the MCF7 and MDA-MB-231 cells. Subsequently, the cells were cultured in an incubator at 37°C with 5% CO2 for 48 h. The shRNA sequences for the target genes were as follows: FN1 shRNA1, FN1-Homo-1423, 5′-GCAGCACAACTTCGAATTATG-3′; FN1 shRNA2, FN1-Homo-3917, 5′-GGGAAATTCTTTGGAAGAAGT-3′; FN1 shRNA3 FN1-Homo-5046, 5′-GCTACCATCAGCGGCCTTAAA-3′; SLC1A3 shRNA1, SLC1A3-homo-487, 5′-GCAATGGAGAAGAGCCCAAGA-3′; SLC1A3 shRNA2, SLC1A3-homo-876, 5′-GCTGTGGTGATTGGCATAATC-3′; SLC1A3 shRNA3, SLC1A3-homo-1528, 5′-GGTTGCTGCAAGCACTCATCA-3′. 2.7 Immunohistochemistry (IHC) The slices were incubated in 3% H2O2 in methanol and 5% normal horse serum to minimize nonspecific staining. Sections were incubated at 37°C for 1 h and at 4°C overnight with the primary antibodies anti-FN1 (66042-1-Ig, Proteintech, China) and anti-SLC1A3 (20785-1-AP, Proteintech, China). Next, the slices were incubated with a secondary IgG antibody (Proteintech, China) at 37°C for 1 h. Signals were visualized using DAB kits. The immunostaining was visualized under a microscope (Nikon, Melville, NY, Japan). We use the IHC Profiler plug-in of ImageJ to automatically score the staining of samples, and take the average gray value (staining intensity) of positive cells and the percentage of positive areas (staining area) together as the IHC measurement index[ 42 , 43 ]. Finally, we give four scores: High Positive (3+), Positive (2+), Low positive (1+) and Negative (0). 2.8 Cell viability assessment Cell viability analysis was conducted using the Cell Counting Kit-8 (CCK-8, C0037, Beyotime, China) with three replications. Different groups of cells in the logarithmic growth phase were seeded into 96-well plates with 5 × 104 cells/well. After seeding, cells were grown for 0, 24, 48, and 72 h, 10 µL CCK-8 solution was added, and the cells were incubated at 37°C in 5% CO2 for 2 h. Finally, the absorbance at 450nm was measured with a microplate reader (SpectraMax i3, Molecular Devices, CA, USA). 2.9 Transwell invasiveness assays The 24-well Transwell chambers (Corning Costar, Thermo Fisher Scientific, MA USA) with or without Matrigel coating were used to evaluate invasiveness or migration ability, respectively. Briefly, 750 µl of medium supplied with 20% FBS was added into the lower chamber as a chemoattractant, cells (4× 105 cells) were added into the upper chambers with 200 µl of serum-free medium and cultured for 48 h (for invasiveness assay). Cells on the lower surface of the upper chamber were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet. 2.10 Wound healing assay Cell migration was investigated by the scratch wound assay. MCF7 and MDA-MB-231 cells (density of 1 × 106 cells) were plated into 6-well plates for 24h. When the cells reach 80% confluence, used sterile plastic tip (100 µ L) to scrape the cells and create interstitial spaces, and used the reduced serum DMEM medium to continue to culture for 24 hours. Photos of the wound area were captured using an inverted microscope (Nikon, Melville, NY, Japan) at 0 and 24 h. 2.11 Total RNA extraction and Reverse Transcriptase qPCR (qRT-PCR) assay The TRIzol reagent was applied for total RNA extraction. NanoDrop (ND-1000 model, Thermo Fisher Scientific, MA, USA) was used to verify the RNA concentration and purity. The cDNA was reverse transcribed using the PrimeScript™ RT Master Mix (Perfect Real Time) (RR036A, Takara, Japan). The relative RNA level was calculated using the conventional 2 −ΔΔCt method. Real-time PCR primers for the target genes were as follows: FN1: Forward primer 5′-CCGCCGAATGTAGGACAAGA-3′, Reverse primer 5′-CCGCCGAATGTAGGACAAGA-3′; SLC1A3: Forward primer 5′-ACATGAAGGAACAGGGGCAG-3′, Reverse primer 5′-CACGGGGGCATACCACATTA-3′; YAP1: Forward primer 5′-GAACTCGGCTTCAGGTCCTC-3′, Reverse primer 5′-GGTTCATGGCAAAACGAGGG-3′; BIRC5: Forward primer 5′-GATGACGACCCCATGCAAAG-3′, Reverse primer 5′-CAGTAGAGGAGCCAGGGACT-3′; TOP2A: Forward primer 5′-TGTCACCATTGCAGCCTGT-3′, Reverse primer 5′-CAGTAGAGGAGCCAGGGACT-3′; GADPH: Forward primer 5′-CTCCTCCACCTTTGACGC-3′, Reverse primer 5′-CCACCACCCTGTTGCTGT-3′. 2.12 Western Blot NP40 lysis buffer with protease inhibitor cocktail was applied to lyse the cells. The same amounts of protein (20 µg) were isolated on SDS-PAGE gel, then transferred onto a PVDF membrane, blocked with 5% non-fat milk, and incubated with primary and secondary antibodies. The following antibodies were used: anti-FN1 (66042-1-Ig, Proteintech), anti-SLC1A3 (20785-1-AP, Proteintech), anti-YAP1 (13584-1-AP, Proteintech), anti-pYAP1 (AP0489, ABclonal, MA, USA), anti-Bcl2 (26593-1-AP, Proteintech), anti-Caspase3 (66470-2-Ig, Proteintech), anti-MMP9 (10375-2-AP, Proteintech), anti-N-cadherin (22018-1-AP, Proteintech), anti-BIRC5 (10508-1-AP, Proteintech) and anti-TOP2A (24641-1-AP, Proteintech). 2.13 Annexin V-FITC apoptosis assay Cell apoptosis was analyzed using the Annexin V-FITC Apoptosis Detection Kit (C1062M, Beyotime, China). Briefly, treated tumor cells were collected and washed in phosphate-buffered saline (PBS). Then, the cells were stained with FITC‐Annexin V for 15 min at room temperature. Subsequently, apoptosis was detected by flow cytometry on a C6 flow cytometer (FACS Calibur, Becton Dickinson, NJ, USA). Each experiment was performed three independent times. 2.14 Immunofluorescence staining (IF) IF for YAP1 and p-YAP1 was performed on BC cells and/or cultured spheroids using fluorescence-conjugated primary antibodies. In brief, cells were harvested after treatment and fixed in 1.6% paraformaldehyde for 10 min, blocked with 1% normal goat serum, and incubated with the above antibodies for 30 min at room temperature in the dark. Immunofluorescent (IF) images were captured with a confocal microscope system (Carl Zeiss, Jena, German). 2.15 Co-immunoprecipitation (Co-IP) Cell lysates were first reacted with anti-FN1 (66042-1-Ig, Proteintech), anti-SLC1A3 (20785-1-AP, Proteintech), anti-YAP1 (13584-1-AP, Proteintech), or control IgG (Proteintech) for 1 h at 4°C, and then with protein A-agarose (150 µg protein A) for 3 h at 4°C. Precipitates were washed three times in lysis buffer and detected by western blot (WB) analysis. 2.16 Animal experiments Sixty BALB/c nude mice (20 ~ 22 g, five weeks) were SiPeiFu Biotechnology Co., Ltd. (Beijing, China). Animal experiment was conducted in accordance with China Animal Welfare Legislation and was approved by the Ethics Committee of our hospital. MCF7 and MDA-MB-231cells transduced with the lentiviruses were subcutaneously injected (1 × 10 6 cells) into the right flanks of six-week-old female BALB/C nude mice (n = 5 per group). Tumor length and width were measured every 3 days after injection. Tumor volume was calculated as length × (width 2 /2). Mice were euthanized by intraperitoneal injection of sodium pentobarbital were sacrificed 28 daysand the tumors were collected and weighed. For the verteporfin (ab143294, Abcam) / UCPH-101 (ab120309, Abcam) response experiments after implantation, the mice were intraperitoneally injected either vehicle or 2 mg verteporfin (100 mg/kg, 400 ul) [ 44 ] / UCPH-101(100 mg/kg, 400 ul) [ 45 ] on the 7th, 9th, and 11th day respectively. Tumor volumes were monitored every 3 days. 2.17 Data analysis and statistics All statistical analyses were carried out using GraphPad Prism 8.0 (Graph Pad Software Inc., CA, USA). Data from at least three independent experiments performed in triplicate are presented as means ± SD. Overall survival in relation to FN1 expression was evaluated by the Kaplan-Meier survival curve and the log-rank nonparametric test. Chi square analysis is used to analyze the relationship between categorical data. The unpaired two-tailed Student’s t-test, one-way ANOVA, and two-way ANOVA followed by Tukey’s or Dunnett’s multiple comparisons test were used for comparison between groups. The P-values were indicated as follows in the figures: *, P < 0.05; **, P < 0.01; ***, P < 0.001; and ****, P < 0.0001, and designated as statistically significant. 3. RESULTS 3.1 High expression of FN1 in tumor tissues of BC patients is positively correlated with poor prognosis Detection of second-generation RNA sequencing on both the tumor tissues and adjacent tissues of 20 BC patients was performed first. The results showed significant differences in the transcriptional profiles between tumor tissues and adjacent tissues (Fig. 1 A). Through strict screening of differential genes, 170 highly significant up-regulated genes, and 14 significantly down-regulated genes were identified (log2 FC > = 3, P adj < 0.001). KEGG and GO enrichment analyses were conducted respectively. KEGG enrichment analysis of up-regulated genes showed that the ECM receiver interaction was representative of a significant enrichment pathway (Fig. 1 B). Furthermore, GO analysis revealed that the ECM related genes occurring in the top 10 pathways of up-regulated gene enrichment were extractable matrix organization and extractable structure organization within the Biological Process (BP) and extractable matrix structural construct in the Molecular Function (MF) (Fig. 1 C). Since FN1 is regarded as a primary ECM member, we analyzed the relationship between FN1 expression in the TCGA data set as well as the clinical follow-up information of BC patients on the Gene Expression Profiling Interactive Analysis (GEPIA) website. Based on these investigations, it was found that the expression of FN1 in BC tissues was significantly higher than in adjacent normal tissues (Fig. 1 D). Moreover, the results indicate that an increased expression of FN1 in BC patients was directly correlated with a poor OSR, (|log2fc| = 1, P < 0.05, Fig. 1 E). RT qPCR was used to evaluate the expression level of FN1 in formalin-fixed paraffin-embedded (FFPE) tumors and adjacent tissues of 20 BC patients. The results revealed that the mRNA expression level of FN1 in cancer tissues (CA) was significantly higher than in paracancerous tissues (PY) (Fig. 1 G). These findings were consistent with the RNA sequencing results (Fig. 1 F) (P < 0.05). In addition, IHC was performed on the tumor and adjacent tissue samples. Similarly, when compared with PY, FN1 was significantly overexpressed in CA (Fig. 1 H). The results above indicate that the core ECM gene, FN1, is significantly overexpressed in BC and is directly associated with a poor prognosis. Moreover, we hypothesize that FN1 may promote the evolution of BC by inducing ECM remodeling. 3.2 Aspartic acid metabolism up-regulated in tumor tissues of BC patients, and SLC1A3 was highly expressed and positively correlated with FN1 Metabolic reprogramming has been acknowledged as a hallmark of malignant tumors. In order to meet their own characteristic of unlimited proliferation, cancer cells usually exhibit an up-regulation of glycolysis and enhanced amino acid metabolism [ 46 ]. In light of this, liquid chromatography-mass spectroscopy (LC-MS) analysis was performed on the tumors and adjacent tissues of 20 BC patients, and 240 differential metabolites were obtained (VIP > 1 and P < 0.05). The cluster heat map showed the following: 154 were significantly enriched in CA, and 86 in PY (Fig. 2 A). Further path enrichment analysis and topological analysis of differential metabolites showed that alanine, aspartate, and glutamate metabolism demonstrated the most significant difference in metabolic pathways between CA and PY (Fig. 2 B). It was also found that the six key metabolites observed in this pathway were significantly enriched in tumor tissues (marked by the red border in Fig. 2 A). Hence, we further investigated whether the up-regulation of FN1 promoted the progression of BC through the activation of alanine aspartate and glutamate metabolic pathways. To test this hypothesis, the correlation between FN1 and the six key products occurring in alanine, aspartate, and glutamate metabolism was analyzed. It was found that both FN1 and the key metabolites had a positive correlation (P < 0.05, Fig. 2 C). With regard to the expression of SLC1A3 in BC, qRT-PCR and IHC were utilized to detect the mRNA and protein expression levels of SLC1A3 in tumors and adjacent tissues of 20 BC patients. The outcomes showed that SLC1A3 was significantly overexpressed in the tumor tissues of patients (Fig. 2 D-E). By applying Pearson’s correlation analysis, it was found that FN1 and SLC1A3 in BC were significantly positively correlated (Fig. 2 F-G) and consistent with the results of the GEPIA database (Fig. 2 H). 3.3 The complex regulatory relationship between FN1, SLC1A3, and aspartic acid metabolism in BC tumor cells, inhibition of FN1 or SLC1A3 can inhibit cell proliferation and promote apoptosis To explore whether FN1 can promote cell proliferation and induce apoptosis by regulating the uptake of aspartic acid by BC tumor cells, we detected the expression of FN1 in six breast cancer cell lines, and used MCF7 and MDA-MB-231 breast cancer cell lines with high FN1 expression in the following experiments (Fig. 3 A). It was established that MCF7 and MDA-MB-231 cell lines knockdown FN1 (sh-FN1) or negative control (sh-NC) via the lentivirus plasmid. The results indicated that compared with sh-NC, the downregulation of FN1 in MCF7 and MDA-MB-231 cells significantly reduced the protein expression of FN1 and SLC1A3, while the addition of aspartic acid could ameliorate the downregulation of SLC1A3 induced by FN1 knockdown in MCF7 (Fig. 3 A). In addition, downregulation of FN1 significantly inhibited the cell viability of MCF7 and MDA-MB-231 at 24, 48, and 72 h (Fig. 3 B). Then, the related apoptotic activity was detected by flow cytometry. In MCF7 and MDA-MB-231, the apoptotic cells in the sh-FN1 group increased around 3 times (mean of 5.247 vs 1.677) and 2 times (mean of 3.407 vs 1.593), respectively (Fig. 3 C). The results above suggests that FN1 may regulate the uptake of aspartic acid in BC tumor cells by directly affecting the expression of SLC1A3. Furthermore, inhibition of FN1 may reduce cell viability and promote apoptosis. Hence, we investigated the impact of SLC1A3 on the expression of FN1. MCF7 and MDA-MB-231 cell lines were treated with sh-RNA and UCPH-101 (a specific pharmacological inhibitor of the glutamate aspartate transporter ), respectively, and it was found that both of these components could significantly down-regulate the protein expression of FN1 and SLC1A3. With the remedial addition of aspartic acid, the down-regulation of FN1 and SLC1A3 induced by sh-RNA and UCPH-101 in MCF7 was restored, while only the down-regulation of both FN1 and SLC1A3 induced by UCPH-101 in MDA-MB-231 was restored (Fig. 3 D). Subsequently, the related cell viability and apoptosis were evaluated. The expression of SLC1A3 was knocked down, and cell viability was significantly decreased, which could be up-regulated after the addition of aspartic acid (Fig. 3 E). We observed that apoptosis was significantly increased after sh-RNA and UCPH-101 treatment, while the addition of aspartic acid inhibited apoptosis in MCF7 (Fig. 3 F). It was observed that SLC1A3 inhibition directly down-regulated the expression of FN1 in BC. Different BC cells react differently after adding aspartic acid, which may present another embodiment of tumor heterogeneity. The results above indicate to the existence of a complex regulatory relationship between FN1, SLC1A3, and aspartic acid metabolism. Furthermore, inhibition of FN1 and SLC1A3 can reduce BC cell viability and induce apoptosis. 3.4 Inhibition of FN1 and SLC1A3 can inhibit the evolution of BC related to aspartic acid metabolism In addition to cell proliferation and apoptosis, the ability of invasion and migration is also crucial to the evolution of malignant tumors. To study the effects of FN1 and SLC1A3 on the movement of BC cells, migration and invasion experiments were carried out, and the expression of adhesion and apoptosis related proteins were detected. Compared with sh-NC, the migration ability (Fig. 4 A-B) and invasion ability (Fig. 4 C-D) of tumor cells in sh-FN1 and sh-SLC1A3 groups within MCF7 and MDA-MB-231 cells were significantly reduced. Aspartic acid supplementation could only reverse the decreased migration ability induced by FN1 knockdown, however, it could also reverse the decreased invasion ability induced by both sh-FN1 and sh-SLC1A3 knockdown (Fig. 4 A-D). It has been identified that FN1 can not only activate specific matrix metalloproteinases (MMP) but can also regulate the expression of N-cadherin to promote tumor invasion and metastasis [ 47 – 49 ]. To further explore the mechanism of FN1 and SLC1A3 affecting BC cell invasion, metastasis, and apoptosis, we investigated the expression of related proteins after FN1 and SLC1A3 knockdown through WB analysis. Compared with NC, the downregulation of FN1 and SLC1A3 significantly decreased the expression of MMP-9 and N-cadherin in MCF7 and MDA-MB-231 cells, whilst simultaneously increasing the expression of Bcl-2 and caspase-3 (Fig. 4 E-F). Aspartic acid supplementation could reverse the knockdown effect of FN1 in BC cells. However, after knockdown of SLC1A3 and the addition of aspartate, the expression of N-cadherin in MCF7 was up-regulated, Bcl-2 and caspase-3 were down-regulated, the expression of MMP-9 and N-cadherin in MDA-MB-231 was up-regulated, and Bcl-2 was down-regulated (Fig. 4 E-F). The results above revealed that the inhibition of FN1 and SLC1A3 could regulate the progression of BC by reducing MMP-9 and N-cadherin and increasing Bcl-2 and Caspase-3, which were affected by aspartate metabolism. 3.5 The "FN1-YAP1-SLC1A3 axis" activates the aspartic acid metabolic pathway and promotes BC evolution To explore the regulatory mechanism between FN1 and SLC1A3, we investigated the hippo pathway and affiliated components. The results indicated that the hippo pathway can be regulated by FN1. Further, YAP is known to be a key effector of the hippo pathway. Upon review of the transcriptome sequencing results, it was found that the mRNA level of YAP1 was lower in BC tumor tissues, but the mRNA expression levels of its downstream target genes, BIRC5 and TOP2A, were significantly higher in tumor tissues (Fig. 5 A). To this end, qRT-PCR showed that YAP1, BIRC5, and TOP2A were highly expressed in tumors (Fig. 5 B). Since both the method of RNA sequencing database building and the algorithm of gene expression will affect the resultant calculation of gene expression, the calculated expression can vary from the actual one, hence a difference between the calculated expression and the quantitative results of qPCR exists. Further WB detection showed that the expression of YAP1 was basically unchanged and slightly up-regulated after knockdown of FN1. However, the expression level of p-YAP1 was significantly up-regulated, while the expression of TOP2A and BIRC5 was significantly reduced (Fig. 5 C). Moreover, STRING and Cytoscape were used to illustrate the protein interaction network of FN1, YAP1, and SCLA3, suggesting that FN1 may regulate SLC1A3 by affecting the binding of YAP1 and LATS2 (Fig. 5 D). To investigate whether the inhibition of FN1 affects its migration from the cytoplasm to the nucleus via inhibition of the dephosphorylation of p-YAP1, which results in further inhibited activation of the hippo pathway, immunofluorescence experiments were performed. The results revealed that the nuclear localization of YAP1 in the sh-FN1 group decreased, while the expression of p-YAP1 in the cytoplasm increased significantly (Fig. 5 E). To further investigate the interaction between FN1, YAP1, and SLC1A3, co-IP experiments were conducted. The results showed that FN1 succeeded in binding to SLC1A3, although all of these components interacted with YAP1 (Fig. 5 F). YAP1 was knocked down by sh-RNA and verteporfin to verify the regulatory effect of YAP1 on SLC1A3. It was found that YAP1 inhibition was also sufficient to induce the reduction of SLC1A3 protein expression (Fig. 5 G). The results above show that the "FN1-YAP1-SLC1A3 axis" directly affects the occurrence and development of BC by regulating aspartic acid metabolism. 3.6 The value of blocking "FN1-YAP1-SLC1A3 axis" in the treatment of BC To determine whether FN1-YAP1-SLC1A3 in BC cells can inhibit tumor growth in vivo, and whether it plays the same role in different subtypes of breast cancer. First, we detected the expression of FN1 in tissue microarray of 132 patients, and removed cases without clinical staging and those with missing follow-up information, leaving 125 cases. We divide the expression of FN1 in different molecular subtypes of breast cancer into four grades according to the staining scores (Fig. 6 A), and define FN1 ≤ 1 as the high expression group and FN1 > 1 as the low expression group according to the scoring criteria. The high and low expression groups of FN1 in each molecular subtype are shown in Fig. 6 B. Then, we carried out survival analysis for each subtype of patients, and the results showed that Luminal A and TNBC patients with high FN1 expression had poor survival prognosis (P = 0.042 and P = 0.018, Fig. 6 C). In order to further explore the therapeutic value of "FN1-YAP1-SLC1A3 axis " in vivo, we used MCF7 and MDA-MB-231 cells, which were stably transfected by sh-NC and sh-FN1, were subcutaneously injected into nude mice. Verteporfin and UCPH-101 (ab120309) were respectively used for treatment. The tumor volume and weight of mice in the sh-FN1 group were significantly reduced (Fig. 6 D-E). Further, the addition of verteporfin and UCPH-101 could also inhibit the growth of tumors. The treatment effect of sh-FN1 in combination with verteporfin presented the most superior effects (Fig. 6 D-E). WB analysis revealed that inhibition of FN1 combined with verteporfin or UCPH-101 significantly reduced the expression of MMP-9 and N-cadherin, and increased the expression of Bcl-2 and caspase-3 (Fig. 6 F-G). The above results indicate that blocking FN1-YAP1-SLC1A3 pathway can significantly inhibit the growth of tumor of Luminal A and TNBC subtypes, and the therapeutic effect of FN1 combined with verteporfin or UCPH-101 is significantly better than that of single inhibition, whereby the effect of sh-FN1 + UCPH-101 is the most superior. 4. DISCUSSION The evolution of tumors is highly regulated by changes in the microenvironment. It has been found that FN1 expression, loss of cell adhesion, and degradation of the ECM during BC invasion can allow malignant cells to escape from their site of origin[ 50 , 51 ]. In addition, the BC microenvironment is also a reflection of a highly heterogeneous nature, in which, in addition to tumor cells, fibroblasts, mesenchymal cells, and many different types of immune cells, etc. can be found. These cells can build a complex regulatory network by secreting collagen, FN1, growth factors, and competing nutrients [ 52 ]. In this study, a close correlation between BC evolution and the core ECM gene FN1 as well as aspartate metabolism was discovered by performing RNA seq and LC-MS analysis on tumor and paracancerous tissues clinically obtained from BC patients. In addition, aspartate is known as a fundamental factor in cell proliferation, and is an important substrate for nucleotide synthesis [ 26 ]. Research by Thomas Bertero et al. has described the existence of metabolic crosstalk between carcinoma associated fibroblasts and human head and neck squamous cell carcinoma (HNSCC). In this regard, these metabolic interactions allow the exchange of glutamic acid aspartate through SLC1A3, thereby increasing the uptake of aspartate by tumor cells and subsequently promoting cancer progression and metastasis [ 41 ]. The findings were consistent with recently reported results indicating that increased tumor stromal rigidity promotes BC ECM deposition and remodeling [ 53 , 54 ], overcoming the metabolic limitations of aspartate, which is beneficial for tumor growth [ 25 , 55 ]. In this study, we found through rescue experiments that the effects of supplementation of aspartic acid on MCF7 and MDA-MB-231 cells were different. For example, after shRNA and drugs were applied to inhibit the expression of SLC1A3, the expression recovery of FN1 and SLC1A3 was different after aspartic acid supplementation, and MDA-MB-231 had no effect on shRNA inhibition group (Fig. 3 D). However, the apoptosis experiment showed that after the expression of slc1a3 was knocked down, aspartic acid supplementation did not change the apoptosis rate of MDA-MB-231 tumor cells (Fig. 3 F). This may indicate that the inhibition of apoptosis of MCF7 cells is more dependent on aspartate metabolism than MDA-MB-231. This study also found that in the migration experiment, supplementation of aspartic acid could rescue the inhibitory effect of FN1 knockdown on MDA-MB-231 and MCF7, but could not rescue the SLC1A3 knockdown group (Fig. 4 A-B). The results of transwell experiment showed that aspartate supplementation had a rescue effect on both FN1 knockdown and SLC1A3 knockdown mediated invasion inhibition (Fig. 4 C-D). The above results suggest that the energy metabolism preference required for invasion and migration may be different, and the invasion ability is more dependent on the aspartate metabolic pathway. It is further demonstrated that intratumoral metabolic heterogeneity and derived metabolic interactions can be stored in the progression of cancer[ 56 , 57 ]. To sum up, our results elucidate the importance of FN1 and aspartate metabolism in tumor progression, demonstrating that BC can upregulate the expression level of p-YAP1, YAP1 dephosphorylates in the cytoplasm and enters the nucleus, activates the YAP/TAZ pathway, plays an important role in nuclear transcription, and up-regulates the expression of downstream target genes, which leads to the proliferation, survival, and movement of tumor cells, thus effectively playing an essential role in tumorigenesis and development [ 58 – 60 ]. It can be seen that high levels of p-YAP1 can inhibit the activation of the YAP1/Hippo pathway, and regulate the expression of SLC1A3 through overexpression of FN1, resulting in the regulation of the aspartate requirement of tumor cells. This is the first study in which the important role of the "FN1/YAP1/SLC1A3/aspartate metabolism" regulatory axis in the evolution of BC has been determined and described. The present study has some limitations that should be addressed. We did not further explore in depth the specific sites of action of silencing FN1-induced YAP1 phosphorylation modification and the binding sites between YAP1 and SLC1A3. In addition, the tumor microenvironment is highly complex, and the crosstalk between different cell types in the tumor microenvironment was not considered in this study. This may also be one of the main reasons for obtaining different results of aspartic acid supplementation in MCF7 and MDA-MB-231 cells. Finally, the efficacy of the triple inhibition regimen of FN1, YAP1, and SLC1A3 was not investigated in the combination therapy experiments. Tumor cells can sense the biophysical properties of tumor microenvironment (TME) - tissue mechanics and adapt to the changes of these signals in its evolution. In recent years, an increased amount of attention has been paid to the role of ECM remodeling and tissue mechanics in tumorigenesis, metastasis, treatment, and anti-tumor immunity [ 61 , 62 ]. The increase in rigidity not only affects the growth and invasive metastasis of tumor cells but also inhibits immune cells and some anti-tumor drugs from acting directly on the surface of tumor cells to kill them, which in turn affects the level of patient's response to treatment [ 10 ]. In addition, FN1 expression is strongly correlated with the level of immune cell infiltration, which may serve as an immune-related biomarker and therapeutic target in thyroid cancer [ 63 ]. In HNSCC, FN1 positively correlated with CD4 + T cells, endothelial cells, macrophages, and NK cells, while negatively correlating with CD8 + T cells [ 64 ]. Therefore, in the future, it is necessary to combine single-cell sequencing technology, atomic force microscopy, CRISPR-Cas9 gene editing technology, tumor cell and immune cell co-culture models, and human organoid models to systematically study the mechanism of tissue mechanics regulating metabolic reprogramming in BC during ECM remodeling mediated by FN1 and the role of immune cells in it. We will continue our research by comprehensively confirming our new theory and developing a new strategy of combined immunotherapy. 5. CONCLUSIONS We propose a new mechanism for the first time - FN1 activates the YAP1/Hippo pathway by regulating the expression of SLC1A3, a key transporter of aspartate uptake, to drive Luminal A and TNBC subtypes evolution. This finding also showed that different subtypes of breast cancer cells have different preferences for aspartate metabolism, and different biological behaviors in tumor cells of the same subtype also have different dependence on aspartate metabolism, further clarifying the heterogeneity of tumors from the perspective of energy metabolism. In addition, we believe that FN1 is a multifunctional regulator in Luminal A and TNBC. Silencing FN1 inhibits the expression of ECM degradation related MMP2 and cell adhesion related N-cadherin, and promotes the expression of apoptosis related proteins Bcl-2 and Caspase-3, which may be affected differently by the supplementation of aspartic acid. Downregulation of FN1 inhibits the activity of the YAP1/Hippo pathway by increasing phosphorylation of YAP1, which in turn regulates SLC1A3 expression and promotes aspartate uptake and utilization. This is the first time that the key position of FN1 in metabolism has been elucidated, which demonstrates that energy metabolism is the basis of any life activity. Preclinical translational experiments confirmed that FN1 could be a new target for BC diagnosis and treatment, and targeting FN1 could simultaneously inhibit the unlimited proliferation and invasive metastatic potential of tumor cells in terms of both ECM remodeling and tumor metabolism. In addition, the combination of FN1 and YAP1 inhibitor or SLC1A3 inhibitor is more effective than single inhibition, among which, "silent FN1 combined with the YAP1 inhibitor" is more effective and has good prospects in clinical application. Abbreviations Asp aspartate BC breast cancer CCK-8 Cell Counting Kit-8 Co-IP co-immunoprecipitation CRC colorectal cancer EAAT1 excitatory amino acid transporter 1 ECM extracellular matrix FBS fetal bovine serum FDR false discovery rate FN fibronectin GLAST glutamate/aspartate transporter GO Gene Ontology HCA hierarchical cluster analysis IF immunofluorescence staining IHC immunohistochemistry KEGG Kyoto Encyclopedia of Genes and Genomes LC-MS liquid chromatography-mass spectrometry NCCR National Central Cancer Registry OSR overall survival rate qRT-PCR Reverse Transcriptase qPCR Q-TOF MS quadrupole time-of-flight mass spectrometer RNA seq RNA sequencing SLC solute carrier family SLC1A3 solute carrier family 1 member 3 Declarations Ethics approval and consent to participate: Informed consent was obtained from all subjects prior to collection and all samples were subjected to histological confirmation. The study was conducted in accordance with the Declaration of Helsinki. All experimental protocols were approved by the Animal Ethics Committee of Harbin Medical University Cancer Hospital. All methods were carried out in accordance with the Guide for the Care and Use of Laboratory Animals. All methods are reported in accordance with ARRIVE guidelines for the reporting of animal experiments. The study was carried out in accordance with the relevant guidelines and regulation. Consent for publication: The authors declare that they have no conflicts for publication. Availability of data and materials: The RNA-seq data have been deposited in the NCBI GEO under accession number PRJNA962803, and the metabolomics data in this study can be obtained from the corresponding author on request. Competing interests: The authors declare that they have no conflicts of interest. Funding: This study was supported by National Natural Science Foundation of China (82073146 and 82072903). Authors' contributions: Chen Chen and Leiguang Ye conceived the study, did the experiment, analyzed the data and writing the manuscript; Jinfeng Yi analyzed and proofread the data; Zhigao Li and Tong Liu supervised the study. All authors read and approved the final manuscript. Corresponding authors: Zhigao Li or Tong Liu. Acknowledgements: None. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin (2021) 71:209-49. doi: 10.3322/caac.21660 Lei S, Zheng R, Zhang S, Chen R, Wang S, Sun K, et al. Breast cancer incidence and mortality in women in China: temporal trends and projections to 2030. Cancer Biol Med (2021) . doi: 10.20892/j.issn.2095-3941.2020.0523 Ren, X. (2021). Cancer Biol Med 18 , 931-933 Waks AG, Winer EP. Breast Cancer Treatment: A Review. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2629354","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":197443208,"identity":"ad3cc42e-b551-40c6-b6c8-0fa696aaa3f2","order_by":0,"name":"Chen Chen","email":"","orcid":"","institution":"Harbin Medical University Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Chen","suffix":""},{"id":197443209,"identity":"cc408395-9753-4e5d-90fa-3e3dfa8eb2ac","order_by":1,"name":"Leiguang Ye","email":"","orcid":"","institution":"Harbin Medical University Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Leiguang","middleName":"","lastName":"Ye","suffix":""},{"id":197443211,"identity":"59862787-ba2a-467f-812e-44e76eb76f3b","order_by":2,"name":"Jinfeng Yi","email":"","orcid":"","institution":"Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jinfeng","middleName":"","lastName":"Yi","suffix":""},{"id":197443212,"identity":"d2d998ab-fd0f-4e73-8c35-555cea579a9f","order_by":3,"name":"Tong Liu","email":"","orcid":"","institution":"Harbin Medical University Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tong","middleName":"","lastName":"Liu","suffix":""},{"id":197443213,"identity":"08c85f35-ebb8-499c-8452-371f635c9a32","order_by":4,"name":"Zhigao Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYDCCAwxsDAlAmo+Z+RgDYwNYzIA4LWzMbGkkaAEBNgYeM+K08N0+/uzBg192cmzsPN8eV+7YltjA3rxNgqHmDk4tkucS0g0S+5KN2Zh5txuePXM7sYHnWJkEw7FnOLUYnGE4JpHYw5zYxsy7TbKxDahFIsdMgrHhMB4tjG1ALfVALTzPIFrk3xDSwswmkfDjMEgLG9QWHvxaJM+wsUkkNhwH+oXNTLLxzG3jNp60YouEY7i18J1hfyb540+1HD//YaDDdtyW7Wc/vPHGhxrcWsCAsQ2JA46mBPwagOAPQRWjYBSMglEwkgEARJ9TwbS5WfMAAAAASUVORK5CYII=","orcid":"","institution":"Harbin Medical University Cancer Hospital","correspondingAuthor":true,"prefix":"","firstName":"Zhigao","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2023-02-26 04:14:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2629354/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2629354/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":36720479,"identity":"66456fbf-349f-404a-9a77-30b43559b925","added_by":"auto","created_at":"2023-05-08 22:01:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2352433,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFN1 was overexpressed in BC tissues.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Differential gene volcano map of patient tissue by RNA seq.\u003c/p\u003e\n\u003cp\u003eB. KEGG enrichment analysis of differential genes.\u003c/p\u003e\n\u003cp\u003eC. GO enrichment analysis of differential genes.\u003c/p\u003e\n\u003cp\u003eD. Expression of FN1 in BC patients in GEPIA database.\u003c/p\u003e\n\u003cp\u003eE. FN1 and survival of BC patients in GEPIA database.\u003c/p\u003e\n\u003cp\u003eF. Expression of FN1 was determined by RNA seq.\u003c/p\u003e\n\u003cp\u003eG. Expression of FN1 was determined by qRT-PCR.\u003c/p\u003e\n\u003cp\u003eH. Expression of FN1 was determined by IHC.\u003c/p\u003e\n\u003cp\u003e*, P \u0026lt; 0.05; and ****, P \u0026lt; 0.0001\u003c/p\u003e","description":"","filename":"F1.png","url":"https://assets-eu.researchsquare.com/files/rs-2629354/v1/88045ad45ad5818503765a02.png"},{"id":36720480,"identity":"b79158dd-362f-4b4a-98a3-0611e5730e48","added_by":"auto","created_at":"2023-05-08 22:01:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1968140,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAspartic acid metabolism was up-regulated in BC tissues,\u003c/strong\u003e \u003cstrong\u003eand SLC1A3 was highly expressed and positively correlated with FN1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Thermographic analysis of differential metabolites by LC-MS.\u003c/p\u003e\n\u003cp\u003eB. KEGG enrichment analysis of differential metabolites.\u003c/p\u003e\n\u003cp\u003eC. Correlation between FN1 and key metabolites.\u003c/p\u003e\n\u003cp\u003eD. Expression of SLC1A3 was determined by qRT-PCR.\u003c/p\u003e\n\u003cp\u003eE. Expression of SLC1A3 was determined by IHC.\u003c/p\u003e\n\u003cp\u003eF. Correlation between FN1 and SLC1A3 were determined by qRT-PCR.\u003c/p\u003e\n\u003cp\u003eG. Correlation between FN1 and SLC1A3 were determined by IHC.\u003c/p\u003e\n\u003cp\u003eH. Correlation between FN1 and SLC1A3 in GEPIA database.\u003c/p\u003e\n\u003cp\u003e*, P \u0026lt; 0.05; **, P \u0026lt; 0.01; and ****, P \u0026lt; 0.0001\u003c/p\u003e","description":"","filename":"F2.png","url":"https://assets-eu.researchsquare.com/files/rs-2629354/v1/d4622d57e8f1a7d55bbf375d.png"},{"id":36721527,"identity":"b9f1c5bd-14a9-4ffc-b962-014fcb34a45d","added_by":"auto","created_at":"2023-05-08 22:09:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1002409,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDown-regulation of FN1 inhibited cell viability and induced apoptosis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Expression of FN1 in BC cell lines (MCF7 and MDA-MB-231) with FN1-siRNA transfection was measured by western blotting.\u003c/p\u003e\n\u003cp\u003eB. Cell viability of MCF7 and MDA-MB-231 cells was measured by CCK-8 assay.\u003c/p\u003e\n\u003cp\u003eC. Cell apoptosis of MCF7 and MDA-MB-231 cells with FN1-siRNA transfection was measured by flow cytometry assay.\u003c/p\u003e\n\u003cp\u003eD. Expression of SLC1A3 and FN1 in BC cell lines (MCF7 and MDA-MB-231) with SLC1A3-siRNA transfection, UCPH-101 and Asp was measured by western blotting.\u003c/p\u003e\n\u003cp\u003eE. Cell viability of MCF7 and MDA-MB-231 cells with SLC1A3-siRNA transfection, UCPH-101 and Asp was measured by CCK-8 assay.\u003c/p\u003e\n\u003cp\u003eF. Cell apoptosis of MCF7 and MDA-MB-231 cells with SLC1A3-siRNA transfection, UCPH-101 and Asp was measured by flow cytometry assay.\u003c/p\u003e\n\u003cp\u003e*, P \u0026lt; 0.05; **, P \u0026lt; 0.01; ***, P \u0026lt; 0.001; and ****, P \u0026lt; 0.0001\u003c/p\u003e","description":"","filename":"F3.png","url":"https://assets-eu.researchsquare.com/files/rs-2629354/v1/12172d56654dd377e7e81773.png"},{"id":36720482,"identity":"ed239a8a-4d63-4e8f-b599-a898c786afde","added_by":"auto","created_at":"2023-05-08 22:01:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5943677,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDown-regulation of FN1 inhibited cell migration, invasion and effects on protein expression.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA-B. Cell migration in MCF7 and MDA-MB-231cells was measured by Wound healing test.\u003c/p\u003e\n\u003cp\u003eC-D. Cell invasion in MCF7 and MDA-MB-231 cells was measured by Transwell assay.\u003c/p\u003e\n\u003cp\u003eE-F. Expression of MMP9, N-cadherin, Bcl-2 and Caspase3 in BC cell lines (MCF7 and MDA-MB-231) with FN1-siRNA transfection, SLC1A3-siRNA transfection and Asp was measured by western blotting.\u003c/p\u003e\n\u003cp\u003e*, P \u0026lt; 0.05; **, P \u0026lt; 0.01; ***, P \u0026lt; 0.001; and ****, P \u0026lt; 0.0001\u003c/p\u003e","description":"","filename":"F4.png","url":"https://assets-eu.researchsquare.com/files/rs-2629354/v1/a684e342e02a97bda6f0e477.png"},{"id":36721528,"identity":"39d8a8b0-2dc6-46d4-8745-13629bddcd63","added_by":"auto","created_at":"2023-05-08 22:09:47","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1876477,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFN1 regulated BC cell proliferation, apoptosis, migration and invasion through interacting with YAP1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Expression of YAP1, TOPA2 and BIRC5 was determined by RNA seq.\u003c/p\u003e\n\u003cp\u003eB. Expression of YAP1, TOPA2 and BIRC5 was determined by qRT-PCR.\u003c/p\u003e\n\u003cp\u003eC. Expression of YAP1, p-YAP1, TOPA2 and BIRC5 in BC cell lines (MCF7 and MDA-MB-231) with FN1-siRNA transfection and SLC1A3-siRNA transfection was measured by western blotting.\u003c/p\u003e\n\u003cp\u003eD. Protein-protein interaction prediction network through String website.\u003c/p\u003e\n\u003cp\u003eE. The distribution of Yap1 and p-yap1 after FN1 knockdown was detected by IF.\u003c/p\u003e\n\u003cp\u003eF. Co-IP showed that FN1 interacts with SLC1A3, YAP1 interacts with FN1 and SLC1A3 in BC tissues.\u003c/p\u003e\n\u003cp\u003eG. Expression of SLC1A3 in BC cell lines (MCF7 and MDA-MB-231) with FN1-siRNA transfection and Verteporfin was measured by western blotting.\u003c/p\u003e\n\u003cp\u003e*, P \u0026lt; 0.05; **, P \u0026lt; 0.01; ***, P \u0026lt; 0.001; and ****, P \u0026lt; 0.0001\u003c/p\u003e","description":"","filename":"F5.png","url":"https://assets-eu.researchsquare.com/files/rs-2629354/v1/c9dc5ebe1289fbb345bccc03.png"},{"id":36720484,"identity":"5073dfff-6705-4662-8976-0dd164f970a9","added_by":"auto","created_at":"2023-05-08 22:01:47","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":4474369,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDown-regulation of FN1 inhibited tumor growth of BC in vivo.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Expression of FN1 in different subtypes of breast cancer patients by IHC.\u003c/p\u003e\n\u003cp\u003eB. Score of FN1 in different subtypes of breast cancer patients by IHC.\u003c/p\u003e\n\u003cp\u003eC. Survival analysis of high and low expression groups of FN1 in different subtypes of breast cancer.\u003c/p\u003e\n\u003cp\u003eD-E. At 28 days after MCF7 and MDA-MB-231 cells transfected with shNC, pLKO.1-FN1-shRNA injection with UCPH-101 or Verteporfin treatment, the mice were euthanized and the tumor volume and weight were measured.\u003c/p\u003e\n\u003cp\u003eF-G. At 28 days after MCF7 and MDA-MB-231 cells transfected with shNC, pLKO.1-FN1-shRNA injection with UCPH-101 or Verteporfin treatment, expression of MMP9, N-cadherin, Bcl-2 and Caspase3 in BC cell lines (MCF7 and MDA-MB-231).\u003c/p\u003e\n\u003cp\u003e***, P \u0026lt; 0.001; and ****, P \u0026lt; 0.0001\u003c/p\u003e","description":"","filename":"F6.png","url":"https://assets-eu.researchsquare.com/files/rs-2629354/v1/9f83b797827c2d9d5b1ed026.png"},{"id":49359299,"identity":"787d749d-e755-4337-b5cf-d213324114dc","added_by":"auto","created_at":"2024-01-09 09:07:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4643204,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2629354/v1/8df1d3a6-a36d-4e33-8fae-e6601a1ead3e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"FN1 Mediated Activation of Aspartate Metabolism Promotes the Progression of Triple-negative and Luminal A Breast Cancer","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eBreast cancer (BC) is the primary cause of cancer deaths among the female population worldwide. At present, BC has surpassed the incidence rate of lung cancer, reflecting its status as the most common malignant tumor worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to the statistical data obtained from the National Central Cancer Registry (NCCR) of China, both the incidence and mortality rate of BC is predicted to continuously increase until 2030 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Current treatment approaches for BC patients are based on surgical methods and assisted by chemotherapy, radiotherapy, endocrine therapy, immunotherapy, and other therapeutic methods[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Although these interventions have exhibited substantial progress in the clinical diagnosis and treatment of BC, the overall survival rate (OSR) of patients remains poor as a direct result of treatment resistance, particularly in the case of distant metastasis and recurrence [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, it is of great clinical significance and importance to identify and discover novel therapeutic targets of BC while considering the application value.\u003c/p\u003e \u003cp\u003eBC is defined as a malignant tumor of solid consistency with strong heterogeneity. In addition to the molecular and phenotypic variations observed in cancer cells, intratumoral heterogeneity also extends to the tumor microenvironment [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In the 2000s, due to the wide application of high-throughput analysis, the heterogeneity between the four subtypes of breast cancer, such as Luminal A, Luminal B, HER 2\u0026thinsp;+\u0026thinsp;and basal like, was well described[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In this regard, metabolic reprogramming is considered a hallmark of malignancy [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Accordingly, the metabolic reprogramming of cancer cells is driven by the combination of carcinogenic changes within the internal cellular environment in conjunction with host cytokines affecting the external tumor microenvironment [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In recent years, a number of studies have shown that extracellular matrix (ECM) remodeling is directly involved in regulating the metabolic reprogramming of BC cells [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and metabolic heterogeneity is closely related to the metastatic ability of cancer cells [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFibronectin (FN) is an important component of the ECM. Structurally, FN is defined as a large molecular weight glycoprotein, which exhibits different expressions and functions in various cancers [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. FN1 directly participates in ECM formation and plays an important role in tumor cell adhesion, proliferation, migration, and invasion [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. An increasing body of evidence has validated the importance of FN1 as a prominent tumor related gene [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], whereby its abnormal expression is closely related to the staging, prognosis, and treatment response of bladder cancer, esophageal cancer, colorectal cancer (CRC), ovarian cancer, and other tumors [\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe solute carrier (SLC) family mediates nutrient and metabolite cell homeostasis [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Solute carrier family 1 member 3 (SLC1A3), also known as the glutamate/aspartate transporter (GLAST) or excitatory amino acid transporter 1 (EAAT1), is a member of the high-affinity glutamate transporter family [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Studies by Javier Garcia Bermudez on BC, colon cancer, and lung cancer have shown that SLC1A3 mediated aspartate uptake, was associated with resistance to inhibiting electron transport chains in vitro, and further facilitated increased growth both in vivo and under hypoxia [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Aspartate is regarded as an essential component of cell proliferation and is an important substrate for nucleotide synthesis. Aspartic acid could be a potential limiting metabolite of tumor growth and represents a novel target for tumor therapy [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. SLC1A3, which forms an essential regulator in the aspartic acid metabolic pathway, is involved in the occurrence and progression of colorectal cancer [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], however, its mechanism of action in the pathogenesis of BC remains unclear.\u003c/p\u003e \u003cp\u003eThe hippo signaling pathway is characterized as a reprogrammable cellular metabolic pathway. Its activation is closely related to the energy state of cells, the availability of nutrients, the composition of tissue microenvironments and structures, as well as external biochemical signal transduction [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Based on its functions, this pathway enables tumor cell adaptation in response to the changing microenvironment, thus effectively promoting tumor progression [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. As an important component of the hippo pathway, the activity of yes-associated protein 1 (YAP1) is directly affected by ECM stiffness, cell density, and shear force [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. BC exhibits high levels of nuclear transcriptional coactivator with PDZ-binding motif (TAZ)/YAP expression, and effectively relies on nuclear TAZ/YAP transcriptional activity to reprogram the energy metabolism of tumor cells, subsequently driving the growth and invasion of BC cells [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. It has been reported that FN can promote tumor cell growth and chemotherapy resistance through the CDC42-YAP dependent signal pathway in colorectal cancer [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we investigated the expression of FN1 in Luminal A and triple negative subtypes of breast cancer, and studied its regulatory role in SLC1A3 mediated aspartate uptake. FN1 is highly expressed in BC tissues, and its high expression is directly related to a poor prognosis. The findings showed that FN1 activates SLC1A3 through the YAP1/Hippo signaling pathway, regulates aspartate metabolism, promotes BC cell growth, and inhibits apoptosis. The \"FN1-YAP1-SLC1A3 regulation axis\" has been identified for the first time in this study. Moreover, we proved that applying inhibition of the combination FN1 and YAP1 or SLC1A3 inhibitors can play a synergistic role, whereby the therapeutic effect is significantly better than that of single drug therapy, subsequently providing a novel strategy for the treatment of Luminal A breast cancer and TNBC. This finding also showed that different subtypes of breast cancer cells have different preferences for aspartate metabolism, and different biological behaviors in tumor cells of the same subtype also have different dependence on aspartate metabolism, further clarifying the heterogeneity of tumors from the perspective of energy metabolism.\u003c/p\u003e"},{"header":"2. MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Patients and breast tissue samples\u003c/h2\u003e \u003cp\u003eA total of 20 matched pairs of BC and surrounding non-cancerous tissue specimens were harvested while patients were undergoing surgical BC resection at the XX Hospital. Informed consent was obtained from all subjects prior to collection and all samples were subjected to histological confirmation. The Ethics Committee of the XX Hospital approved the present study. All experiments and protocols adhered to the ethical standards as outlined in the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Metabolic profiling analysis\u003c/h2\u003e \u003cp\u003eThe metabolic profiling analysis was conducted by Biotree Co., Ltd. (Shanghai, China) on the ultra-high performance liquid chromatography (UPLC) system (Waters, Milford, MA, USA) that was coupled to a 6520 series accurate quadrupole time-of-flight mass spectrometer (Q-TOF MS) system (Agilent, Santa Clara, CA, USA). The samples were randomized before analysis to avoid differences caused by the injection sequence. Autoscaling was used on the metabolomics data before multivariate analysis, in which the centered metabolite intensity was divided by the standard deviation.\u003c/p\u003e \u003cp\u003eTo decrease the false discovery rate (FDR) for biomarker selection, local FDR (lFDR) based on the P-value was calculated to adjust the multiple comparisons. The potential biomarkers were selected as univariate lFDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and multivariate variable influence on projection (VIP)\u0026thinsp;\u0026gt;\u0026thinsp;1[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Furthermore, hierarchical cluster analysis (HCA) was conducted to detect the classification ability and concentration levels of the selected metabolites. Pathway information was extracted from the Kyoto Encyclopedia of Genes and Genomes (KEGG). All the other statistical analyses and visualizations were performed using the R platform.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 RNA sequencing (RNA seq) and analysis\u003c/h2\u003e \u003cp\u003eSequencing was carried out by Biotree Ltd. (Shanghai, China) on the Illumina (Miseq/Hiseq) platform. Paired-end reads were generated and then quality controlled in-house Perl scripts were used. The pathway enrichment analysis of the differentially expressed genes (DEGs) was performed by using the KEGG and Gene Ontology (GO) databases. The DESeq2 software based on the negative binomial distribution was used to perform statistical analysis on all data to compare genes with differences in expression between groups (with a cutoff threshold of an absolute log2 (fold change)). The method used for multiple test correction was BH (FDR correction with Benjamini/Hochberg) and P-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered as the threshold for statistical significance difference at a 95% confidence level[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe clusterProfiler package of R software was used in this study and utilized for GO function analysis. Based on the co-expression screening data, KEGG pathway analysis was also performed to retrieve further information.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Protein-protein interaction (PPI)\u003c/h2\u003e \u003cp\u003eThe STRING website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://string-db.org/\u003c/span\u003e\u003cspan address=\"https://string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) integrated and constructed the PPI using computational predictions, which visualized the intrinsic links among of FN1, YAP1, and SCLA3 genes[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Cytoscape's plugin CytoHubba was used to discover key nodes in the PPI network[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Cells and cell culture\u003c/h2\u003e \u003cp\u003eThe BC cells used were purchased from ATCC (ATCC; Manassas, VA, USA). All the cell lines used in this study were of human origin and were cultured at 37℃ in a humidified atmosphere of 5% CO2. MCF7 and MDA-MB-231 cells were cultured in DMEM (0020916, Biological Industries, Israel) supplemented with 10% fetal bovine serum (FBS, 1618326, Biological Industries, Israel) and 1% penicillin-streptomycin.\u003c/p\u003e \u003cp\u003eAspartate was purchased from Sigma Aldrich (Sigma Aldrich, St. Louis, MO, USA) and used at a concentration of 5 mM [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] in the rescue experiment, consistent with prior in vitro studies linking cancer cell proliferation to aspartate metabolism.\u003c/p\u003e \u003cp\u003eFor the verteporfin (ab143294, Abcam, Cambridge, United Kingdom) / UCPH-101 (ab120309, Abcam) response experiments, MCF7 and MDA-MB-231 cells were given either vehicle or 10 \u0026micro;m verteporfin / UCPH-101.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Cell transfection\u003c/h2\u003e \u003cp\u003eFor cell transfection, short hairpin RNA against FN1 (sh-FN1), short hairpin RNA against SLC1A3 (sh-SLC1A3), sh-FN1\u0026thinsp;+\u0026thinsp;sh-SLC1A3, or their negative controls (sh-NCs) (E2691, Promega, WI USA) were constructed into lentiviral vectors and transfected into 293 T cells for 72 h to establish lentivirus particles. Then the lentivirus particles were transfected into the MCF7 and MDA-MB-231 cells. Subsequently, the cells were cultured in an incubator at 37\u0026deg;C with 5% CO2 for 48 h. The shRNA sequences for the target genes were as follows:\u003c/p\u003e \u003cp\u003eFN1 shRNA1, FN1-Homo-1423, 5\u0026prime;-GCAGCACAACTTCGAATTATG-3\u0026prime;;\u003c/p\u003e \u003cp\u003eFN1 shRNA2, FN1-Homo-3917, 5\u0026prime;-GGGAAATTCTTTGGAAGAAGT-3\u0026prime;;\u003c/p\u003e \u003cp\u003eFN1 shRNA3 FN1-Homo-5046, 5\u0026prime;-GCTACCATCAGCGGCCTTAAA-3\u0026prime;;\u003c/p\u003e \u003cp\u003eSLC1A3 shRNA1, SLC1A3-homo-487, 5\u0026prime;-GCAATGGAGAAGAGCCCAAGA-3\u0026prime;;\u003c/p\u003e \u003cp\u003eSLC1A3 shRNA2, SLC1A3-homo-876, 5\u0026prime;-GCTGTGGTGATTGGCATAATC-3\u0026prime;;\u003c/p\u003e \u003cp\u003eSLC1A3 shRNA3, SLC1A3-homo-1528, 5\u0026prime;-GGTTGCTGCAAGCACTCATCA-3\u0026prime;.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Immunohistochemistry (IHC)\u003c/h2\u003e \u003cp\u003eThe slices were incubated in 3% H2O2 in methanol and 5% normal horse serum to minimize nonspecific staining. Sections were incubated at 37\u0026deg;C for 1 h and at 4\u0026deg;C overnight with the primary antibodies anti-FN1 (66042-1-Ig, Proteintech, China) and anti-SLC1A3 (20785-1-AP, Proteintech, China). Next, the slices were incubated with a secondary IgG antibody (Proteintech, China) at 37\u0026deg;C for 1 h. Signals were visualized using DAB kits. The immunostaining was visualized under a microscope (Nikon, Melville, NY, Japan). We use the IHC Profiler plug-in of ImageJ to automatically score the staining of samples, and take the average gray value (staining intensity) of positive cells and the percentage of positive areas (staining area) together as the IHC measurement index[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Finally, we give four scores: High Positive (3+), Positive (2+), Low positive (1+) and Negative (0).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Cell viability assessment\u003c/h2\u003e \u003cp\u003eCell viability analysis was conducted using the Cell Counting Kit-8 (CCK-8, C0037, Beyotime, China) with three replications. Different groups of cells in the logarithmic growth phase were seeded into 96-well plates with 5 \u0026times; 104 cells/well. After seeding, cells were grown for 0, 24, 48, and 72 h, 10 \u0026micro;L CCK-8 solution was added, and the cells were incubated at 37\u0026deg;C in 5% CO2 for 2 h. Finally, the absorbance at 450nm was measured with a microplate reader (SpectraMax i3, Molecular Devices, CA, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Transwell invasiveness assays\u003c/h2\u003e \u003cp\u003eThe 24-well Transwell chambers (Corning Costar, Thermo Fisher Scientific, MA USA) with or without Matrigel coating were used to evaluate invasiveness or migration ability, respectively. Briefly, 750 \u0026micro;l of medium supplied with 20% FBS was added into the lower chamber as a chemoattractant, cells (4\u0026times; 105 cells) were added into the upper chambers with 200 \u0026micro;l of serum-free medium and cultured for 48 h (for invasiveness assay). Cells on the lower surface of the upper chamber were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.10 Wound healing assay\u003c/h2\u003e \u003cp\u003eCell migration was investigated by the scratch wound assay. MCF7 and MDA-MB-231 cells (density of 1 \u0026times; 106 cells) were plated into 6-well plates for 24h. When the cells reach 80% confluence, used sterile plastic tip (100 \u0026micro; L) to scrape the cells and create interstitial spaces, and used the reduced serum DMEM medium to continue to culture for 24 hours. Photos of the wound area were captured using an inverted microscope (Nikon, Melville, NY, Japan) at 0 and 24 h.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.11 Total RNA extraction and Reverse Transcriptase qPCR (qRT-PCR) assay\u003c/h2\u003e \u003cp\u003eThe TRIzol reagent was applied for total RNA extraction. NanoDrop (ND-1000 model, Thermo Fisher Scientific, MA, USA) was used to verify the RNA concentration and purity. The cDNA was reverse transcribed using the PrimeScript\u0026trade; RT Master Mix (Perfect Real Time) (RR036A, Takara, Japan). The relative RNA level was calculated using the conventional 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method. Real-time PCR primers for the target genes were as follows:\u003c/p\u003e \u003cp\u003eFN1: Forward primer 5\u0026prime;-CCGCCGAATGTAGGACAAGA-3\u0026prime;, Reverse primer 5\u0026prime;-CCGCCGAATGTAGGACAAGA-3\u0026prime;;\u003c/p\u003e \u003cp\u003eSLC1A3: Forward primer 5\u0026prime;-ACATGAAGGAACAGGGGCAG-3\u0026prime;, Reverse primer 5\u0026prime;-CACGGGGGCATACCACATTA-3\u0026prime;;\u003c/p\u003e \u003cp\u003eYAP1: Forward primer 5\u0026prime;-GAACTCGGCTTCAGGTCCTC-3\u0026prime;, Reverse primer 5\u0026prime;-GGTTCATGGCAAAACGAGGG-3\u0026prime;;\u003c/p\u003e \u003cp\u003eBIRC5: Forward primer 5\u0026prime;-GATGACGACCCCATGCAAAG-3\u0026prime;, Reverse primer 5\u0026prime;-CAGTAGAGGAGCCAGGGACT-3\u0026prime;;\u003c/p\u003e \u003cp\u003eTOP2A: Forward primer 5\u0026prime;-TGTCACCATTGCAGCCTGT-3\u0026prime;, Reverse primer 5\u0026prime;-CAGTAGAGGAGCCAGGGACT-3\u0026prime;;\u003c/p\u003e \u003cp\u003eGADPH: Forward primer 5\u0026prime;-CTCCTCCACCTTTGACGC-3\u0026prime;, Reverse primer 5\u0026prime;-CCACCACCCTGTTGCTGT-3\u0026prime;.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.12 Western Blot\u003c/h2\u003e \u003cp\u003eNP40 lysis buffer with protease inhibitor cocktail was applied to lyse the cells. The same amounts of protein (20 \u0026micro;g) were isolated on SDS-PAGE gel, then transferred onto a PVDF membrane, blocked with 5% non-fat milk, and incubated with primary and secondary antibodies. The following antibodies were used: anti-FN1 (66042-1-Ig, Proteintech), anti-SLC1A3 (20785-1-AP, Proteintech), anti-YAP1 (13584-1-AP, Proteintech), anti-pYAP1 (AP0489, ABclonal, MA, USA), anti-Bcl2 (26593-1-AP, Proteintech), anti-Caspase3 (66470-2-Ig, Proteintech), anti-MMP9 (10375-2-AP, Proteintech), anti-N-cadherin (22018-1-AP, Proteintech), anti-BIRC5 (10508-1-AP, Proteintech) and anti-TOP2A (24641-1-AP, Proteintech).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.13 Annexin V-FITC apoptosis assay\u003c/h2\u003e \u003cp\u003eCell apoptosis was analyzed using the Annexin V-FITC Apoptosis Detection Kit (C1062M, Beyotime, China). Briefly, treated tumor cells were collected and washed in phosphate-buffered saline (PBS). Then, the cells were stained with FITC‐Annexin V for 15 min at room temperature. Subsequently, apoptosis was detected by flow cytometry on a C6 flow cytometer (FACS Calibur, Becton Dickinson, NJ, USA). Each experiment was performed three independent times.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e2.14 Immunofluorescence staining (IF)\u003c/h2\u003e \u003cp\u003eIF for YAP1 and p-YAP1 was performed on BC cells and/or cultured spheroids using fluorescence-conjugated primary antibodies. In brief, cells were harvested after treatment and fixed in 1.6% paraformaldehyde for 10 min, blocked with 1% normal goat serum, and incubated with the above antibodies for 30 min at room temperature in the dark. Immunofluorescent (IF) images were captured with a confocal microscope system (Carl Zeiss, Jena, German).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e2.15 Co-immunoprecipitation (Co-IP)\u003c/h2\u003e \u003cp\u003eCell lysates were first reacted with anti-FN1 (66042-1-Ig, Proteintech), anti-SLC1A3 (20785-1-AP, Proteintech), anti-YAP1 (13584-1-AP, Proteintech), or control IgG (Proteintech) for 1 h at 4\u0026deg;C, and then with protein A-agarose (150 \u0026micro;g protein A) for 3 h at 4\u0026deg;C. Precipitates were washed three times in lysis buffer and detected by western blot (WB) analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e2.16 Animal experiments\u003c/h2\u003e \u003cp\u003eSixty BALB/c nude mice (20\u0026thinsp;~\u0026thinsp;22 g, five weeks) were SiPeiFu Biotechnology Co., Ltd. (Beijing, China). Animal experiment was conducted in accordance with China Animal Welfare Legislation and was approved by the Ethics Committee of our hospital. MCF7 and MDA-MB-231cells transduced with the lentiviruses were subcutaneously injected (1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells) into the right flanks of six-week-old female BALB/C nude mice (n\u0026thinsp;=\u0026thinsp;5 per group). Tumor length and width were measured every 3 days after injection. Tumor volume was calculated as length \u0026times; (width\u003csup\u003e2\u003c/sup\u003e /2). Mice were euthanized by intraperitoneal injection of sodium pentobarbital were sacrificed 28 daysand the tumors were collected and weighed.\u003c/p\u003e \u003cp\u003eFor the verteporfin (ab143294, Abcam) / UCPH-101 (ab120309, Abcam) response experiments after implantation, the mice were intraperitoneally injected either vehicle or 2 mg verteporfin (100 mg/kg, 400 ul) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] / UCPH-101(100 mg/kg, 400 ul) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] on the 7th, 9th, and 11th day respectively. Tumor volumes were monitored every 3 days.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e2.17 Data analysis and statistics\u003c/h2\u003e \u003cp\u003eAll statistical analyses were carried out using GraphPad Prism 8.0 (Graph Pad Software Inc., CA, USA). Data from at least three independent experiments performed in triplicate are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Overall survival in relation to FN1 expression was evaluated by the Kaplan-Meier survival curve and the log-rank nonparametric test. Chi square analysis is used to analyze the relationship between categorical data. The unpaired two-tailed Student\u0026rsquo;s t-test, one-way ANOVA, and two-way ANOVA followed by Tukey\u0026rsquo;s or Dunnett\u0026rsquo;s multiple comparisons test were used for comparison between groups. The P-values were indicated as follows in the figures: *, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; and ****, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, and designated as statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003e \u003cb\u003e3.1 High expression of FN1 in tumor tissues of BC patients is positively correlated with poor prognosis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eDetection of second-generation RNA sequencing on both the tumor tissues and adjacent tissues of 20 BC patients was performed first. The results showed significant differences in the transcriptional profiles between tumor tissues and adjacent tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Through strict screening of differential genes, 170 highly significant up-regulated genes, and 14 significantly down-regulated genes were identified (log2 FC\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;3, P adj\u0026thinsp;\u0026lt;\u0026thinsp;0.001). KEGG and GO enrichment analyses were conducted respectively. KEGG enrichment analysis of up-regulated genes showed that the ECM receiver interaction was representative of a significant enrichment pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Furthermore, GO analysis revealed that the ECM related genes occurring in the top 10 pathways of up-regulated gene enrichment were extractable matrix organization and extractable structure organization within the Biological Process (BP) and extractable matrix structural construct in the Molecular Function (MF) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Since FN1 is regarded as a primary ECM member, we analyzed the relationship between FN1 expression in the TCGA data set as well as the clinical follow-up information of BC patients on the Gene Expression Profiling Interactive Analysis (GEPIA) website. Based on these investigations, it was found that the expression of FN1 in BC tissues was significantly higher than in adjacent normal tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Moreover, the results indicate that an increased expression of FN1 in BC patients was directly correlated with a poor OSR, (|log2fc| = 1, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). RT qPCR was used to evaluate the expression level of FN1 in formalin-fixed paraffin-embedded (FFPE) tumors and adjacent tissues of 20 BC patients. The results revealed that the mRNA expression level of FN1 in cancer tissues (CA) was significantly higher than in paracancerous tissues (PY) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG). These findings were consistent with the RNA sequencing results (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In addition, IHC was performed on the tumor and adjacent tissue samples. Similarly, when compared with PY, FN1 was significantly overexpressed in CA (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results above indicate that the core ECM gene, FN1, is significantly overexpressed in BC and is directly associated with a poor prognosis. Moreover, we hypothesize that FN1 may promote the evolution of BC by inducing ECM remodeling.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.2 Aspartic acid metabolism up-regulated in tumor tissues of BC patients, and SLC1A3 was highly expressed and positively correlated with FN1\u003c/b\u003e \u003c/p\u003e \u003cp\u003eMetabolic reprogramming has been acknowledged as a hallmark of malignant tumors. In order to meet their own characteristic of unlimited proliferation, cancer cells usually exhibit an up-regulation of glycolysis and enhanced amino acid metabolism [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. In light of this, liquid chromatography-mass spectroscopy (LC-MS) analysis was performed on the tumors and adjacent tissues of 20 BC patients, and 240 differential metabolites were obtained (VIP\u0026thinsp;\u0026gt;\u0026thinsp;1 and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The cluster heat map showed the following: 154 were significantly enriched in CA, and 86 in PY (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Further path enrichment analysis and topological analysis of differential metabolites showed that alanine, aspartate, and glutamate metabolism demonstrated the most significant difference in metabolic pathways between CA and PY (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). It was also found that the six key metabolites observed in this pathway were significantly enriched in tumor tissues (marked by the red border in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Hence, we further investigated whether the up-regulation of FN1 promoted the progression of BC through the activation of alanine aspartate and glutamate metabolic pathways. To test this hypothesis, the correlation between FN1 and the six key products occurring in alanine, aspartate, and glutamate metabolism was analyzed. It was found that both FN1 and the key metabolites had a positive correlation (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). With regard to the expression of SLC1A3 in BC, qRT-PCR and IHC were utilized to detect the mRNA and protein expression levels of SLC1A3 in tumors and adjacent tissues of 20 BC patients. The outcomes showed that SLC1A3 was significantly overexpressed in the tumor tissues of patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD-E). By applying Pearson\u0026rsquo;s correlation analysis, it was found that FN1 and SLC1A3 in BC were significantly positively correlated (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF-G) and consistent with the results of the GEPIA database (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e3.3 The complex regulatory relationship between FN1, SLC1A3, and aspartic acid metabolism in BC tumor cells, inhibition of FN1 or SLC1A3 can inhibit cell proliferation and promote apoptosis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo explore whether FN1 can promote cell proliferation and induce apoptosis by regulating the uptake of aspartic acid by BC tumor cells, we detected the expression of FN1 in six breast cancer cell lines, and used MCF7 and MDA-MB-231 breast cancer cell lines with high FN1 expression in the following experiments (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). It was established that MCF7 and MDA-MB-231 cell lines knockdown FN1 (sh-FN1) or negative control (sh-NC) via the lentivirus plasmid. The results indicated that compared with sh-NC, the downregulation of FN1 in MCF7 and MDA-MB-231 cells significantly reduced the protein expression of FN1 and SLC1A3, while the addition of aspartic acid could ameliorate the downregulation of SLC1A3 induced by FN1 knockdown in MCF7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In addition, downregulation of FN1 significantly inhibited the cell viability of MCF7 and MDA-MB-231 at 24, 48, and 72 h (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Then, the related apoptotic activity was detected by flow cytometry. In MCF7 and MDA-MB-231, the apoptotic cells in the sh-FN1 group increased around 3 times (mean of 5.247 vs 1.677) and 2 times (mean of 3.407 vs 1.593), respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The results above suggests that FN1 may regulate the uptake of aspartic acid in BC tumor cells by directly affecting the expression of SLC1A3. Furthermore, inhibition of FN1 may reduce cell viability and promote apoptosis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHence, we investigated the impact of SLC1A3 on the expression of FN1. MCF7 and MDA-MB-231 cell lines were treated with sh-RNA and UCPH-101 (a specific pharmacological inhibitor of the glutamate aspartate transporter ), respectively, and it was found that both of these components could significantly down-regulate the protein expression of FN1 and SLC1A3. With the remedial addition of aspartic acid, the down-regulation of FN1 and SLC1A3 induced by sh-RNA and UCPH-101 in MCF7 was restored, while only the down-regulation of both FN1 and SLC1A3 induced by UCPH-101 in MDA-MB-231 was restored (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Subsequently, the related cell viability and apoptosis were evaluated. The expression of SLC1A3 was knocked down, and cell viability was significantly decreased, which could be up-regulated after the addition of aspartic acid (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). We observed that apoptosis was significantly increased after sh-RNA and UCPH-101 treatment, while the addition of aspartic acid inhibited apoptosis in MCF7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). It was observed that SLC1A3 inhibition directly down-regulated the expression of FN1 in BC. Different BC cells react differently after adding aspartic acid, which may present another embodiment of tumor heterogeneity.\u003c/p\u003e \u003cp\u003eThe results above indicate to the existence of a complex regulatory relationship between FN1, SLC1A3, and aspartic acid metabolism. Furthermore, inhibition of FN1 and SLC1A3 can reduce BC cell viability and induce apoptosis.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.4 Inhibition of FN1 and SLC1A3 can inhibit the evolution of BC related to aspartic acid metabolism\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn addition to cell proliferation and apoptosis, the ability of invasion and migration is also crucial to the evolution of malignant tumors. To study the effects of FN1 and SLC1A3 on the movement of BC cells, migration and invasion experiments were carried out, and the expression of adhesion and apoptosis related proteins were detected. Compared with sh-NC, the migration ability (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-B) and invasion ability (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-D) of tumor cells in sh-FN1 and sh-SLC1A3 groups within MCF7 and MDA-MB-231 cells were significantly reduced. Aspartic acid supplementation could only reverse the decreased migration ability induced by FN1 knockdown, however, it could also reverse the decreased invasion ability induced by both sh-FN1 and sh-SLC1A3 knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-D). It has been identified that FN1 can not only activate specific matrix metalloproteinases (MMP) but can also regulate the expression of N-cadherin to promote tumor invasion and metastasis [\u003cspan additionalcitationids=\"CR48\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. To further explore the mechanism of FN1 and SLC1A3 affecting BC cell invasion, metastasis, and apoptosis, we investigated the expression of related proteins after FN1 and SLC1A3 knockdown through WB analysis. Compared with NC, the downregulation of FN1 and SLC1A3 significantly decreased the expression of MMP-9 and N-cadherin in MCF7 and MDA-MB-231 cells, whilst simultaneously increasing the expression of Bcl-2 and caspase-3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE-F). Aspartic acid supplementation could reverse the knockdown effect of FN1 in BC cells. However, after knockdown of SLC1A3 and the addition of aspartate, the expression of N-cadherin in MCF7 was up-regulated, Bcl-2 and caspase-3 were down-regulated, the expression of MMP-9 and N-cadherin in MDA-MB-231 was up-regulated, and Bcl-2 was down-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE-F).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results above revealed that the inhibition of FN1 and SLC1A3 could regulate the progression of BC by reducing MMP-9 and N-cadherin and increasing Bcl-2 and Caspase-3, which were affected by aspartate metabolism.\u003c/p\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.5 The \"FN1-YAP1-SLC1A3 axis\" activates the aspartic acid metabolic pathway and promotes BC evolution\u003c/h2\u003e \u003cp\u003eTo explore the regulatory mechanism between FN1 and SLC1A3, we investigated the hippo pathway and affiliated components. The results indicated that the hippo pathway can be regulated by FN1. Further, YAP is known to be a key effector of the hippo pathway. Upon review of the transcriptome sequencing results, it was found that the mRNA level of YAP1 was lower in BC tumor tissues, but the mRNA expression levels of its downstream target genes, BIRC5 and TOP2A, were significantly higher in tumor tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). To this end, qRT-PCR showed that YAP1, BIRC5, and TOP2A were highly expressed in tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Since both the method of RNA sequencing database building and the algorithm of gene expression will affect the resultant calculation of gene expression, the calculated expression can vary from the actual one, hence a difference between the calculated expression and the quantitative results of qPCR exists. Further WB detection showed that the expression of YAP1 was basically unchanged and slightly up-regulated after knockdown of FN1. However, the expression level of p-YAP1 was significantly up-regulated, while the expression of TOP2A and BIRC5 was significantly reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Moreover, STRING and Cytoscape were used to illustrate the protein interaction network of FN1, YAP1, and SCLA3, suggesting that FN1 may regulate SLC1A3 by affecting the binding of YAP1 and LATS2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo investigate whether the inhibition of FN1 affects its migration from the cytoplasm to the nucleus via inhibition of the dephosphorylation of p-YAP1, which results in further inhibited activation of the hippo pathway, immunofluorescence experiments were performed. The results revealed that the nuclear localization of YAP1 in the sh-FN1 group decreased, while the expression of p-YAP1 in the cytoplasm increased significantly (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). To further investigate the interaction between FN1, YAP1, and SLC1A3, co-IP experiments were conducted. The results showed that FN1 succeeded in binding to SLC1A3, although all of these components interacted with YAP1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). YAP1 was knocked down by sh-RNA and verteporfin to verify the regulatory effect of YAP1 on SLC1A3. It was found that YAP1 inhibition was also sufficient to induce the reduction of SLC1A3 protein expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG). The results above show that the \"FN1-YAP1-SLC1A3 axis\" directly affects the occurrence and development of BC by regulating aspartic acid metabolism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.6 The value of blocking \"FN1-YAP1-SLC1A3 axis\" in the treatment of BC\u003c/h2\u003e \u003cp\u003eTo determine whether FN1-YAP1-SLC1A3 in BC cells can inhibit tumor growth in vivo, and whether it plays the same role in different subtypes of breast cancer. First, we detected the expression of FN1 in tissue microarray of 132 patients, and removed cases without clinical staging and those with missing follow-up information, leaving 125 cases. We divide the expression of FN1 in different molecular subtypes of breast cancer into four grades according to the staining scores (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA), and define FN1\u0026thinsp;\u0026le;\u0026thinsp;1 as the high expression group and FN1\u0026thinsp;\u0026gt;\u0026thinsp;1 as the low expression group according to the scoring criteria. The high and low expression groups of FN1 in each molecular subtype are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB. Then, we carried out survival analysis for each subtype of patients, and the results showed that Luminal A and TNBC patients with high FN1 expression had poor survival prognosis (P\u0026thinsp;=\u0026thinsp;0.042 and P\u0026thinsp;=\u0026thinsp;0.018, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). In order to further explore the therapeutic value of \"FN1-YAP1-SLC1A3 axis \" in vivo, we used MCF7 and MDA-MB-231 cells, which were stably transfected by sh-NC and sh-FN1, were subcutaneously injected into nude mice. Verteporfin and UCPH-101 (ab120309) were respectively used for treatment. The tumor volume and weight of mice in the sh-FN1 group were significantly reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD-E). Further, the addition of verteporfin and UCPH-101 could also inhibit the growth of tumors. The treatment effect of sh-FN1 in combination with verteporfin presented the most superior effects (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD-E). WB analysis revealed that inhibition of FN1 combined with verteporfin or UCPH-101 significantly reduced the expression of MMP-9 and N-cadherin, and increased the expression of Bcl-2 and caspase-3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF-G). The above results indicate that blocking FN1-YAP1-SLC1A3 pathway can significantly inhibit the growth of tumor of Luminal A and TNBC subtypes, and the therapeutic effect of FN1 combined with verteporfin or UCPH-101 is significantly better than that of single inhibition, whereby the effect of sh-FN1\u0026thinsp;+\u0026thinsp;UCPH-101 is the most superior.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThe evolution of tumors is highly regulated by changes in the microenvironment. It has been found that FN1 expression, loss of cell adhesion, and degradation of the ECM during BC invasion can allow malignant cells to escape from their site of origin[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. In addition, the BC microenvironment is also a reflection of a highly heterogeneous nature, in which, in addition to tumor cells, fibroblasts, mesenchymal cells, and many different types of immune cells, etc. can be found. These cells can build a complex regulatory network by secreting collagen, FN1, growth factors, and competing nutrients [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. In this study, a close correlation between BC evolution and the core ECM gene FN1 as well as aspartate metabolism was discovered by performing RNA seq and LC-MS analysis on tumor and paracancerous tissues clinically obtained from BC patients. In addition, aspartate is known as a fundamental factor in cell proliferation, and is an important substrate for nucleotide synthesis [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Research by Thomas Bertero et al. has described the existence of metabolic crosstalk between carcinoma associated fibroblasts and human head and neck squamous cell carcinoma (HNSCC). In this regard, these metabolic interactions allow the exchange of glutamic acid aspartate through SLC1A3, thereby increasing the uptake of aspartate by tumor cells and subsequently promoting cancer progression and metastasis [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The findings were consistent with recently reported results indicating that increased tumor stromal rigidity promotes BC ECM deposition and remodeling [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], overcoming the metabolic limitations of aspartate, which is beneficial for tumor growth [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we found through rescue experiments that the effects of supplementation of aspartic acid on MCF7 and MDA-MB-231 cells were different. For example, after shRNA and drugs were applied to inhibit the expression of SLC1A3, the expression recovery of FN1 and SLC1A3 was different after aspartic acid supplementation, and MDA-MB-231 had no effect on shRNA inhibition group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). However, the apoptosis experiment showed that after the expression of slc1a3 was knocked down, aspartic acid supplementation did not change the apoptosis rate of MDA-MB-231 tumor cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). This may indicate that the inhibition of apoptosis of MCF7 cells is more dependent on aspartate metabolism than MDA-MB-231. This study also found that in the migration experiment, supplementation of aspartic acid could rescue the inhibitory effect of FN1 knockdown on MDA-MB-231 and MCF7, but could not rescue the SLC1A3 knockdown group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-B). The results of transwell experiment showed that aspartate supplementation had a rescue effect on both FN1 knockdown and SLC1A3 knockdown mediated invasion inhibition (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-D). The above results suggest that the energy metabolism preference required for invasion and migration may be different, and the invasion ability is more dependent on the aspartate metabolic pathway. It is further demonstrated that intratumoral metabolic heterogeneity and derived metabolic interactions can be stored in the progression of cancer[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo sum up, our results elucidate the importance of FN1 and aspartate metabolism in tumor progression, demonstrating that BC can upregulate the expression level of p-YAP1, YAP1 dephosphorylates in the cytoplasm and enters the nucleus, activates the YAP/TAZ pathway, plays an important role in nuclear transcription, and up-regulates the expression of downstream target genes, which leads to the proliferation, survival, and movement of tumor cells, thus effectively playing an essential role in tumorigenesis and development [\u003cspan additionalcitationids=\"CR59\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. It can be seen that high levels of p-YAP1 can inhibit the activation of the YAP1/Hippo pathway, and regulate the expression of SLC1A3 through overexpression of FN1, resulting in the regulation of the aspartate requirement of tumor cells. This is the first study in which the important role of the \"FN1/YAP1/SLC1A3/aspartate metabolism\" regulatory axis in the evolution of BC has been determined and described.\u003c/p\u003e \u003cp\u003eThe present study has some limitations that should be addressed. We did not further explore in depth the specific sites of action of silencing FN1-induced YAP1 phosphorylation modification and the binding sites between YAP1 and SLC1A3. In addition, the tumor microenvironment is highly complex, and the crosstalk between different cell types in the tumor microenvironment was not considered in this study. This may also be one of the main reasons for obtaining different results of aspartic acid supplementation in MCF7 and MDA-MB-231 cells. Finally, the efficacy of the triple inhibition regimen of FN1, YAP1, and SLC1A3 was not investigated in the combination therapy experiments.\u003c/p\u003e \u003cp\u003eTumor cells can sense the biophysical properties of tumor microenvironment (TME) - tissue mechanics and adapt to the changes of these signals in its evolution. In recent years, an increased amount of attention has been paid to the role of ECM remodeling and tissue mechanics in tumorigenesis, metastasis, treatment, and anti-tumor immunity [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. The increase in rigidity not only affects the growth and invasive metastasis of tumor cells but also inhibits immune cells and some anti-tumor drugs from acting directly on the surface of tumor cells to kill them, which in turn affects the level of patient's response to treatment [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In addition, FN1 expression is strongly correlated with the level of immune cell infiltration, which may serve as an immune-related biomarker and therapeutic target in thyroid cancer [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. In HNSCC, FN1 positively correlated with CD4\u0026thinsp;+\u0026thinsp;T cells, endothelial cells, macrophages, and NK cells, while negatively correlating with CD8\u0026thinsp;+\u0026thinsp;T cells [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Therefore, in the future, it is necessary to combine single-cell sequencing technology, atomic force microscopy, CRISPR-Cas9 gene editing technology, tumor cell and immune cell co-culture models, and human organoid models to systematically study the mechanism of tissue mechanics regulating metabolic reprogramming in BC during ECM remodeling mediated by FN1 and the role of immune cells in it. We will continue our research by comprehensively confirming our new theory and developing a new strategy of combined immunotherapy.\u003c/p\u003e"},{"header":"5. CONCLUSIONS","content":"\u003cp\u003eWe propose a new mechanism for the first time - FN1 activates the YAP1/Hippo pathway by regulating the expression of SLC1A3, a key transporter of aspartate uptake, to drive Luminal A and TNBC subtypes evolution. This finding also showed that different subtypes of breast cancer cells have different preferences for aspartate metabolism, and different biological behaviors in tumor cells of the same subtype also have different dependence on aspartate metabolism, further clarifying the heterogeneity of tumors from the perspective of energy metabolism.\u003c/p\u003e \u003cp\u003eIn addition, we believe that FN1 is a multifunctional regulator in Luminal A and TNBC. Silencing FN1 inhibits the expression of ECM degradation related MMP2 and cell adhesion related N-cadherin, and promotes the expression of apoptosis related proteins Bcl-2 and Caspase-3, which may be affected differently by the supplementation of aspartic acid. Downregulation of FN1 inhibits the activity of the YAP1/Hippo pathway by increasing phosphorylation of YAP1, which in turn regulates SLC1A3 expression and promotes aspartate uptake and utilization. This is the first time that the key position of FN1 in metabolism has been elucidated, which demonstrates that energy metabolism is the basis of any life activity. Preclinical translational experiments confirmed that FN1 could be a new target for BC diagnosis and treatment, and targeting FN1 could simultaneously inhibit the unlimited proliferation and invasive metastatic potential of tumor cells in terms of both ECM remodeling and tumor metabolism. In addition, the combination of FN1 and YAP1 inhibitor or SLC1A3 inhibitor is more effective than single inhibition, among which, \"silent FN1 combined with the YAP1 inhibitor\" is more effective and has good prospects in clinical application.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAsp\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003easpartate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebreast cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCK-8\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCell Counting Kit-8\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCo-IP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eco-immunoprecipitation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecolorectal cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEAAT1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eexcitatory amino acid transporter 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eECM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eextracellular matrix\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efetal bovine serum\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFDR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efalse discovery rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efibronectin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGLAST\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eglutamate/aspartate transporter\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGene Ontology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHCA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehierarchical cluster analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eimmunofluorescence staining\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eimmunohistochemistry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKEGG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKyoto Encyclopedia of Genes and Genomes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLC-MS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eliquid chromatography-mass spectrometry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNCCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Central Cancer Registry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOSR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eoverall survival rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eqRT-PCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReverse Transcriptase qPCR\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eQ-TOF MS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003equadrupole time-of-flight mass spectrometer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRNA seq\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRNA sequencing\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSLC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esolute carrier family\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSLC1A3\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esolute carrier family 1 member 3\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all subjects prior to collection and all samples were subjected to histological confirmation. The study was conducted in accordance with the Declaration of Helsinki.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll experimental protocols were approved by the Animal Ethics Committee of Harbin Medical University Cancer Hospital.\u003c/p\u003e\n\u003cp\u003eAll methods were carried out in accordance with the Guide for the Care and Use of Laboratory Animals.\u003c/p\u003e\n\u003cp\u003eAll methods are reported in accordance with ARRIVE guidelines for the reporting of animal experiments. The study was carried out in accordance with the relevant guidelines and regulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe RNA-seq data have been deposited in the NCBI GEO under accession number PRJNA962803, and the metabolomics data in this study can be obtained from the corresponding author on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by National Natural Science Foundation of China (82073146 and 82072903).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChen Chen and Leiguang Ye conceived the study, did the experiment, analyzed the data and writing the manuscript; Jinfeng Yi analyzed and proofread the data; Zhigao Li and Tong Liu supervised the study.\u0026nbsp;All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eCorresponding authors: Zhigao Li or Tong Liu.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNone.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. 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Biochim Biophys Acta Rev Cancer. 2021;1876:188593.\u003c/li\u003e\n\u003cli\u003eGeng QS, Huang T, Li LF, Shen ZB, Xue WH, Zhao J. Over-Expression and Prognostic Significance of FN1, Correlating With Immune Infiltrates in Thyroid Cancer. Front Med (Lausanne). 2021;8:812278.\u003c/li\u003e\n\u003cli\u003eSheng S, Guo B, Wang Z, Zhang Z, Zhou J, Huo Z. Aberrant Methylation and Immune Microenvironment Are Associated With Overexpressed Fibronectin 1: A Diagnostic and Prognostic Target in Head and Neck Squamous Cell Carcinoma. Front Mol Biosci. 2021;8:753563.\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":"Fibronectin 1, Metabolic reprogramming, Aspartate metabolism, Metabolic heterogeneity","lastPublishedDoi":"10.21203/rs.3.rs-2629354/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2629354/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eBreast cancer (BC) is regarded as one of the most common cancers diagnosed among the female population and has an extremely high mortality rate. It is known that Fibronectin 1 (FN1) drives the occurrence and development of a variety of cancers through metabolic reprogramming. Aspartic acid is considered to be an important substrate for nucleotide synthesis. However, the regulatory mechanism between FN1 and aspartate metabolism is currently unclear.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe used RNA sequencing (RNA seq) and liquid chromatography-mass spectrometry (LC-MS) to analyze the tumor tissues and paracancerous tissues of patients. MCF7 and MDA-MB-231 cells were used to explore the effects of FN1-regulated aspartic acid metabolism on cell survival, invasion, migration and tumor growth. We used PCR, Western blot, immunocytochemistry and immunofluorescence techniques to study it.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe found that FN1 was highly expressed in tumor tissues, especially in Lumina A and TNBC subtypes, and was associated with poor prognosis. In vivo and in vitro experiments showed that silencing FN1 inhibits the activation of the YAP1/Hippo pathway by enhancing YAP1 phosphorylation, down-regulates SLC1A3-mediated aspartate uptake and utilization by tumor cells, inhibits BC cell proliferation, invasion and migration, and promotes apoptosis. In addition, inhibition of FN1 combined with the YAP1 inhibitor or SLC1A3 inhibitor can effectively inhibit tumor growth, of which inhibition of FN1 combined with the YAP1 inhibitor is more effective.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTargeting the \"FN1/YAP1/SLC1A3/Aspartate metabolism\" regulatory axis provides a new target for BC diagnosis and treatment. This study also revealed that intratumoral metabolic heterogeneity plays an important role in the progression of different subtypes of breast cancer.\u003c/p\u003e","manuscriptTitle":"FN1 Mediated Activation of Aspartate Metabolism Promotes the Progression of Triple-negative and Luminal A Breast Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-05-08 22:01:42","doi":"10.21203/rs.3.rs-2629354/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":"82934958-9f91-43a1-a192-108058571349","owner":[],"postedDate":"May 8th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-09T08:59:13+00:00","versionOfRecord":[],"versionCreatedAt":"2023-05-08 22:01:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2629354","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2629354","identity":"rs-2629354","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}