Original ArticleOriginal Article
Open Access

ACSL3 regulates breast cancer progression via lipid metabolism reprogramming and the YES1/YAP axis

Shirong Tan, Xiangyu Sun, Haoran Dong, Mozhi Wang, Litong Yao, Mengshen Wang, Ling Xu and Yingying Xu
Cancer Biology & Medicine July 2024, 21 (7) 606-635; DOI: https://doi.org/10.20892/j.issn.2095-3941.2023.0309

Abstract

Objective: Mitochondrial fatty acid oxidation is a metabolic pathway whose dysregulation is recognized as a critical factor in various cancers, because it sustains cancer cell survival, proliferation, and metastasis. The acyl-CoA synthetase long-chain (ACSL) family is known to activate long-chain fatty acids, yet the specific role of ACSL3 in breast cancer has not been determined.

Methods: We assessed the prognostic value of ACSL3 in breast cancer by using data from tumor samples. Gain-of-function and loss-of-function assays were also conducted to determine the roles and downstream regulatory mechanisms of ACSL3 in vitro and in vivo.

Results: ACSL3 expression was notably downregulated in breast cancer tissues compared with normal tissues, and this phenotype correlated with improved survival outcomes. Functional experiments revealed that ACSL3 knockdown in breast cancer cells promoted cell proliferation, migration, and epithelial–mesenchymal transition. Mechanistically, ACSL3 was found to inhibit β-oxidation and the formation of associated byproducts, thereby suppressing malignant behavior in breast cancer. Importantly, ACSL3 was found to interact with YES proto-oncogene 1, a member of the Src family of tyrosine kinases, and to suppress its activation through phosphorylation at Tyr419. The decrease in activated YES1 consequently inhibited YAP1 nuclear colocalization and transcriptional complex formation, and the expression of its downstream genes in breast cancer cell nuclei.

Conclusions: ACSL3 suppresses breast cancer progression by impeding lipid metabolism reprogramming, and inhibiting malignant behaviors through phospho-YES1 mediated inhibition of YAP1 and its downstream pathways. These findings suggest that ACSL3 may serve as a potential biomarker and target for comprehensive therapeutic strategies for breast cancer.

keywords

Introduction

Breast cancer (BC), the most common cancer worldwide, has the highest morbidity rate and the second highest mortality rate among cancers in women worldwide1, including in China2. The tumor microenvironment increases heterogeneity in cells’ composition and metabolic status. Consequently, many investigations have explored the mechanisms underlying oncogenesis3,4.

Major hallmarks of cancer cells include altered cellular metabolism and bioenergetics5. Recently, increased focus on cancer lipid metabolism has led to the identification of several mechanisms that promote tumor growth and survival, many of which are independent of classical cellular bioenergetics. The regulatory dynamics of diverse pathways, proteins, and energy homeostasis are altered to support aberrant cellular proliferation and facilitate metastatic dissemination, and immune resistance. De novo lipogenesis, fatty acid (FA) uptake, oxidation, and lipid accumulation all contribute to cancer malignancy6,7. FA consumption involves primarily 2 distinct pathways. In the first pathway, FAs undergo complex metabolism steps, permeate the mitochondria, participate in β-oxidation processes, and ultimately contribute to the tricarboxylic acid cycle, thereby facilitating adenosine triphosphate (ATP) generation. In the second pathway, FAs are converted into triacylglycerols (TAGs). Notably, the 2 pathways share the same initial step of activation of FA by acyl-CoA synthetases (ACSs)8,9. The specificity of ACSs depends on the fatty chain of the preferred substrate. Because long-chain FAs are the most abundant molecules in people’s daily diets, long-chain ASCs (ACSLs) are essential enzymes8,10.

The ACSL family comprises 5 isoenzymes: ACSL1, ACSL3, ACSL4, ACSL5, and ACSL69. Each subtype differs in its cellular and subcellular distribution, regulation, substrate specificity, and enzyme kinetics11,12. ACSL3 is abundant in the brain, in the periphery of lipid droplets (LDs) in lipogenic cells, and on the cytoplasmic face of the endoplasmic reticulum; it favors substrates such as activated myristate, palmitate, arachidonate, and eicosapentaenoate; and its primary function is increasing intracellular LDs13–16. FAs are activated by ACSs, thereby forming acyl-CoAs. Acyl-CoAs are an essential means of FA entry into the FA oxidation (FAO) process. Subsequently, acyl-CoAs participate in β-oxidation, thus producing acetyl-CoAs, which in turn serve as substrates for the tricarboxylic acid cycle, of which NADH is a major byproduct. Acetyl-CoA participates in the Krebs cycle and generates metabolites such as NADH, which in turn participate in oxidative phosphorylation and subsequent generation of ATP17.

Previous research has shown that breast tissue exhibits dynamic lipid metabolism18. LD abundance markedly changes across breast stages, including development19,20, menstruation, pregnancy, and lactation21. LDs, which provide FA and cholesteryl ester storage, are derived from the endoplasmic reticulum and interact with many organelles. FAs are activated by ACSs and subsequently participate in multiple physiological processes; they are an essential component of FAO22. Lipid metabolism dysregulation and FAO have been correlated with BC progression23. Both the overexpression of FAO enzymes [for example, carnitine palmitoyltransferase I (CPT1), and acyl-CoA oxidase 1 (ACOX1)]23 and a decrease in LDs induced by pharmacological activation of peroxisome-proliferator activated-receptor-γ24 support increased FAO and consequently cancer cell proliferation. A bidirectional promotion mechanism between Src-family kinases and FAO in BC has been identified25. Moreover, the overexpression of CUB-domain-containing protein 1, which is correlated with the activation of Src26, has been suggested to decrease ACSL3 expression and contribute to progression and metastasis in triple-negative BC (TNBC)27. However, on the basis of existing research, only a correlation can be inferred between ACSL3 and BC occurrence and progression; this correlation may be associated with SRC. The role of ACSL3 in cancer has not been thoroughly studied. In lung cancer, the KRAS pathway has been demonstrated to influence intracellular lipid metabolism and to promote lung cancer cell proliferation28. ACSL3 has also been confirmed to influence lipid storage and ferroptosis status in clear cell renal cell carcinoma29. No studies have demonstrated how ACSL3 suppresses the malignant biological behavior of BC cells. In addition, whether the modulation of lipid metabolism or other signaling pathways influences the proliferation and invasion of BC cells has not been determined.

Herein, we identified ACSL3 as an independent and valuable prognostic factor for BC. Its downregulation was found to be significantly associated with adverse clinicopathological characteristics in human BC specimens. ACSL3 promoted apoptosis and suppressed tumor progression-associated processes and epithelial-to-mesenchymal transition (EMT) in vitro. Mechanistically, ACSL3 was found to increase lipid-droplet storage capacity, suppresses the production of an enzyme critical for β-oxidation, and inhibit the generation of NADH and ATP. We demonstrated that ACSL3 interacts with YES proto-oncogene 1 (YES1), a nonreceptor tyrosine kinase belonging to the SRC family of kinases. ACSL3 inhibited the phosphorylation of YES1 and the YES1/Yes-associated protein 1 (YAP1) axis, thereby promoting apoptosis, and suppressing the progression and metastasis of BC cells. Our data suggested that BC cells downregulate ACSL3 to adapt to the heterogeneous tumor microenvironment, and exhibit heterogeneity in tumor lipid metabolism. Hence, ACSL3 might serve as a potential diagnostic marker and therapeutic target for BC, particularly for endocrine therapy-resistant luminal l and basal-like BC.

Materials and methods

Clinical tissue samples and ethics statement

The experimental protocol was approved by the research ethics committee of the First Affiliated Hospital of China Medical University (Approval No. 2019-72-2) and was conducted in strict accordance with the Declaration of Helsinki. Fresh BC tissues and adjacent normal tissues (ANTs) were collected from patients with BC who underwent modified radical mastectomy at the Department of Breast Surgery in the First Affiliated Hospital of China Medical University (Shenyang, China). Patient information is listed in Table 1. All participants or their guardians provided signed written consent before the study. The included patients did not receive pre-surgical chemotherapy or radiotherapy, and pathological subtypes were confirmed in all resected tissues. All tissues were preserved immediately after surgery, placed in liquid nitrogen overnight, and stored at −80 °C until further study.

View this table:
Table 1

Univariate analysis of relationships between basic patient characteristics and ACSL3 expression

Cell culture and transfection

Normal breast cell (MCF-10A) and human BC (MCF-7, MDA-MB-231, and SK-BR-3) cell lines were obtained from ATCC (Manassas, USA). T-47D, another human BC cell line, was purchased from the cell bank of the Shanghai Institutes for Biological Sciences of the Chinese Academy of Sciences (Shanghai, China). The culture medium for MCF-7 and T-47D cells was high-glucose Dulbecco’s modified Eagle’s medium (DMEM; HyClone) with 10% fetal bovine serum (FBS; Gibco), 1% penicillin, and 100 μg/mL streptomycin. Leibovitz’s L-15 Medium (Gibco) with 10% FBS, 1% penicillin, and 100 μg/mL streptomycin was used to culture MDA-MB-231 cells. SK-BR-3 was cultured in McCoy’s 5A medium (Gibco) and 10% FBS (Gibco). Most cells were cultured in a humidified incubator at 37 °C with 20% O2 and 5% CO2 (Thermo, Waltham, USA). MDA-MB-231 cells were cultured in a humidified incubator at 37 °C with 20% O2 (Thermo, Waltham, USA). All cells were observed microscopically (Leica, Germany).

MDA-MB-231 and MCF-7 cells were seeded in six-well plates (Corning, NY, USA) and transfected with transient small interfering RNAs (Si-RNA) targeting ACSL3 or a negative control (Si-NC). The above 2 cell lines were also transfected with plasmids for overexpression of ACSL3 or empty control plasmids (empty vector; GenePharma, Shanghai, China) with jetPrime reagents (Polyplus) according to the manufacturer’s protocol. The siRNA concentration was 20 μM, and the plasmid concentration was 2 μg/mol. After 6-h transfection, the culture medium was replaced. The duration of silencing was 2 days. Lentiviruses were constructed by co-transfection of the 293T cell line with the packaging plasmid Sh-ACSL3 (LV-Sh-ACSL3), ACSL3 (LV-ACSL3), or a negative control (LV-Sh-NC and LV-Vector) (GenePharma, Shanghai, China); all doses were 1 × 108 TU/mL. Lentiviruses were collected after 48 h and used to infect MCF-7 and MDA-MB-231 cells. Puromycin (2.5 μg/mL for MCF-7 cells, 2.0 μg/mL for MDA-MB-231 cells; Beyotime, China) was used to select stably transfected cells.

RNA isolation and quantitative real-time PCR

RNA was extracted from tissues and cells with TRIzol reagent (Ambion, Berlin, Germany). With a PrimeScriptTM RT reagent Kit with gDNA Eraser (Takara Bio, Beijing, China), total RNA was reverse transcribed into complementary DNA for mRNA detection. To determine gene expression levels with SYBR® Green (Takara Bio), we used A Light Cycler 480 II Real-Time PCR system (Roche Diagnostics, Basel, Switzerland). Relative mRNA levels were normalized to the level of GAPDH and calculated with the 2−ΔΔCt method30. All primers used were provided by Sangon Biotech (Shanghai, China); sequences are listed in Table S1.

Western blot

All protein content was extracted with a Total Protein Extraction Kit (KeyGen Biotech, Nanjing, China). Cells were lysed in protein lysis buffer and boiled, then subjected to 10% SDS-polyacrylamide gel electrophoresis and electrophoretically transferred to polyvinylidene fluoride membranes (Millipore, USA). The catalog numbers and concentration of the reagents are listed in Table S2.

Cell apoptosis assays

Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labelling (TUNEL) staining was used to detect cell apoptosis. A One Step TUNEL Apoptosis Assay Kit (Beyotime, China) was used, and the results were captured under a fluorescence microscope. The apoptosis percentage of whole cells (green + blue/blue) was calculated.

Immunofluorescence

MDA-MB-231 or MCF-7 cells with various treatments were plated on 6-well plates and seeded on coverslips. The samples were fixed in 4% paraformaldehyde and permeabilized with 0.1% Triton X-100. 2% BSA was used to block the slides. The slides were incubated with primary antibodies overnight at 4 °C and subsequently with CY3-conjugated secondary antibodies (CWBIO, Beijing, China) for 1 h at room temperature. Finally, DAPI was used for nuclear staining.

Quantification of metabolites

Measurement of free FAs (FFAs) inside cells was performed with a Free Fatty Acid Assay Kit (Solarbio, China). We use a spectrophotometer for analysis. This involves an extract solution and various reagents. Quantification of glycerol was performed with a Glycerol Assay Kit (Solarbio). Extracted glycerol underwent saponification, thus yielding glycerol and FAs. Glycerol oxidation formed formaldehyde, which reacted with acetylacetone and produced a yellow product. The absorption at 420 nm correlated with the TG content. Intracellular TAG was quantified with an Adipogenesis Colorimetric/Fluorometric Assay Kit (Bio-vision, Milpitas, CA, USA). The assay efficiently solubilized and hydrolyzed triglycerides, converting glycerol to a product whose color (ODmax = 570 nm) and fluorescence (Ex/Em = 535/587 nm) enabled detection of 0.2–10 nmol triglyceride. All experiments were performed strictly according to the manufacturers’ protocols.

The intracellular analytes NADH and ATP were measured with an NAD(H) assay kit (Solarbio, China) and an ATP assay kit (Solarbio, China).

Co-immunoprecipitation

MDA-MB-231 or MCF-7 cells with various treatments were lysed with lysis buffer containing phenylmethanesulfonyl fluoride. The lysate was centrifuged, and the supernatant was used for extract. The supernatant was divided into 3 groups with same sample for input and samples incubated with anti-IgG, anti-ACSL3, anti-YES1, anti-YAP, or anti-β-catenin overnight at 4°C. IP buffer was used to wash Dynabeads (Invitrogen), which were then added to samples. The mixtures were incubated for 2 h at room temperature. The immunoprecipitates were washed with IP buffer, resuspended in loading buffer and boiled. Finally, the Dynabeads were extracted in loading buffer, and the supernatant was subjected to Western blot.

Immunohistochemistry (IHC)

Tumor and adjacent normal tissue samples underwent fixation, embedding, sectioning, and deparaffinization. After being blocked with 3% H2O2 and 5% BSA, the sections were incubated with the indicated antibodies for 10 h at 4 °C. After incubation with secondary antibodies and staining with diaminobenzidine, the IHC score was calculated as the sum of the score of staining intensity multiplied by the score of the percentage of positively stained cells, as evaluated in a blinded manner by 2 researchers. Staining intensity was scored in 4 levels (absent = 0, weak = 1, moderate = 2, and strongly positive = 3). The percentage of positively stained cells was scored in 6 levels (< 1% = 0, 1%–25% = 1, 26%–50% = 3, 51%–75% = 4, and 76%–100% = 5). Scores below the median were considered to indicate low expression, and scores greater than or equal to the median were considered to indicate high expression.

Transwell assays

Transwell assays were conducted with 8 μm migration chambers (Corning). In cell migration assays, 3 × 104 cells and 200 μL FBS-free medium were added to the upper chambers, and 700 μL medium containing 10% FBS was added to the lower chambers. After 24 h of culture, the upper chambers were fixed with 4% PFA and stained with 0.5% crystal violet solution. After removal of non-migrating cells on the upper surface of the upper chamber, the migrated cells were photographed under an optical microscope. Six random microscope views (20 × 10 magnification) per treatment were observed, and 3 independent replicates were analyzed. For cell invasion assays, the upper surfaces of the chambers were coated with 25 μL Matrigel (Sigma); all other steps were the same as those of the cell migration assay described above. Three independent replicates were analyzed.

Cell viability and proliferation analysis

Cell viability was assessed with Cell Counting kit-8 assays (CCK-8; Dojindo, Japan) daily for 5 days. In 96-well plates, 2 × 103 MDA-MB-231 and MCF-7 cells were seeded. After cells in each well were incubated with 10 μL CCK-8 reagent for 1 h at 37 °C, the absorbance at 450 nm was measured with a microplate reader (Bio-Rad, Hercules, CA, USA). For cell proliferation assessment, EdU-positive cells were identified with an EdU Cell Proliferation Kit (Beyotime, China) according to the manufacturer’s specifications.

Colony formation assays

In colony formation assays, 1 × 103 MDA-MB-231 or MCF-7 cells were seeded in 6-well plates and subjected to transfection. After a 14-day incubation at 37 °C, the colonies were fixed with 4% paraformaldehyde and stained with crystal violet solution (Solarbio). The discernible colonies were then counted under a microscope.

Wound healing assays

MCF-7 and MDA-MB-231 cells were seeded into 6-well plates (100 μL/well) at a concentration of 4,000 cells per well. The cells were rinsed with PBS, fixed with 3.7% paraformaldehyde (Corning) for 15 min, and then stained with 1% crystal violet for 10 min. Wound healing was observed at 0 h, 8 h, and 72 h under a microscope for image capture. ImageJ software (National Institutes of Health) was used to measure and quantify the distances (μm) between scratches.

Xenograft model

BALB/c nude mice (4–6 weeks old, weighing 16–20 g) were obtained from a laboratory animal center (Vitong Lihua, Beijing). The experimental protocols involving mice were approved by the Ethics Committee of China Medical University (Approval No. CMU2022012) and the Animal Protection Association. MCF-7 and MDA-MB-231 cells, transfected with lentivirus control or ACSL3, were subcutaneously injected bilaterally into the armpits of the mice at a concentration of 1 × 106 cells/mouse. One-week post-injection, tumor volume was monitored 1 to 2 times per week and calculated with the following formula: volume (mm3) = π/6 × L × W × W (L: longest dimension; W: dimension perpendicular to length). After 21 days, mice were euthanized by cervical dislocation, and the tumors were subjected to detection of Ki67 expression with IHC staining.

Statistical analysis

All data were analyzed in GraphPad Prism software (version 9.4), and results are expressed as mean ± standard deviation. For analysis of patients’ clinical data, chi-square test, Pearson’s χ2 test, and Kaplan-Meier curves were used. Student’s t-test and one way analysis of variance were applied to analyze data from 2 or more groups, respectively. All experiments were repeated at least 3 times. P < 0.05 was considered to indicate a statistically significant result.

Results

ACSL3 downregulation correlates with poor prognosis in BC

To investigate the role of ACSL3 in BC, we first analyzed publicly available gene expression data on ACSL3 in BC tissues and normal breast tissues from TNMplot. ACSL3 was significantly downregulated in tumor tissues compared with normal tissues (Figure 1A). Subsequently, we explored the potential effect of ACSL3 on BC patient survival outcomes. Kaplan‒Meier analysis indicated that higher ACSL3 expression in BC tumor tissues correlated with better prognosis, as indicated by increases in distant metastasis-free survival (DMFS) [HR = 0.78 (0.66–0.91), P = 0.0013] and disease-free survival (DFS) [HR = 0.88 (0.79–0.97), P = 0.012] (Figure 1B). We also analyzed data from the GEO database. On the basis of the GSE22226 dataset, we confirmed that lower expression of ACSL3 correlated with poorer survival outcomes in terms of both DFS and OS (Figure 1C). The Kaplan-Meier analysis results for DFS and OS in patients with BC according to ACSL3 expression in the TCGA-BRCA cohort are presented in Figures S4 and S5. We also used TCGA database to determine the correlation of ACSL3 expression with clinical features (Table S3), estrogen receptor (ER) status, PR status, HER2 status, and BC subtypes (Figure 1D). Logistic regression analysis was performed to evaluate the correlation between ACSL3 expression and clinicopathological characteristics (Table S4).

Figure 1
Figure 1

ACSL3 is downregulated in human BC. (A) ACSL3 expression in patients with BC from the TNMplot public database. (B) Kaplan-Meier plot of DMFS and DFS, on the basis of ACSL3 expression in BC, downloaded from the Kaplan-Meier plotter database. (C) Kaplan-Meier analysis of DFS and OS in patients with BC according to ACSL3 mRNA expression, with follow-up data from the GEO GSE22226 dataset. (D) Chi-square test of correlations between ACSL3 expression and basic clinical features of patients with BC in TCGA database. (E) Western blot analysis of ACSL3 protein expression in representative ANTs and BC tissues. (F) Left, mRNA expression levels of ACSL3, measured by RT-PCR in 96 human BC tissues and paired ANTs. Right, ACSL3 expression in unpaired BC tissues and ANTs from clinical samples, is presented with Ct values. A higher Ct value indicates lower gene expression. Data are shown as mean ± S.D. (G) Chi-square test of correlations between ACSL3 expression level and clinicopathological characteristics of the 96 clinical patients with BC. (H) Representative IHC images of ACSL3 protein expression in 151 human BC tissues and ANTs. Scale bar, 20 μm. (I) Kaplan-Meier analysis of correlations between ACSL3 expression and DFS and OS outcomes in 151 human patients with BC. *P < 0.05; **P < 0.01; ***P < 0.001.

In agreement with previous results, ACSL3 expression was significantly downregulated in our clinical tissue samples. The 96 mRNA samples and 19 pairs of protein samples from BC patients, all supported the current conclusion (Figure 1E, F, Figure S8). We also analyzed the relationships between patients’ clinical features and ACSL3 expression (Table 1). The mRNA expression of ACSL3 correlated with the Ki67 percentage, primary tumor volume, and lymph node status (Figure 1G). To further explore the potential role of ACSL3 in BC survival outcomes, we performed IHC staining in 151 human BC samples in addition to samples from 96 patients with BC. The BC tissues were divided into 4 grades according to the expression level of ACSL3. Representative IHC staining images for ACSL3 are shown in Figure 1H. A comparison of the Kaplan‒Meier curves for the low and high expression groups indicated that low expression of ACSL3 was associated with poor DFS (P = 0.009) and OS (P = 0.0217) (Figure 1I). The relationships between patient clinicopathological features and ACSL3 expression are presented in Table 2.

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Table 2

Univariate and multivariate analysis of ACSL3 in clinical BC tissues

ACSL3 suppresses BC cell proliferation, invasion, migration, and EMT in vitro

To advance understanding of the basic mechanism through which ACSL3 influences BC, we performed gain-of-function and loss-of-function experiments in BC cells. We first confirmed ACSL3 expression in a normal breast cell line, and BC cell lines including MCF-10A, MCF-7, SK-BR-3, T-47D, and MDA-MB-231, at both the mRNA and protein levels. The results (Figure 2A) indicated that ACSL3 expression was highest in MCF-7 cells and lowest in MDA-MB-231 cells. Therefore, we used lentiviral vectors to transfect BC cells. We overexpressed ACSL3 in MDA-MB-231 cells and knocked down ACSL3 in MCF-7 cells. The efficiency of interference and overexpression was validated (Figure 2B, C). The gray value analysis of Figure 2B is presented in Figure 2D.

Figure 2
Figure 2

Low ACSL3 expression in BC cells promotes proliferation, invasion, and metastasis in vitro. (A) mRNA and protein expression of ACSL3 in normal breast cell and BC cell lines. (B, C) Efficacy of ACSL3 knockdown or overexpression in BC cells at the mRNA and protein levels. (D) Gray value analysis of the results in Figure 2B with ImageJ. Colony formation (E), CCK8 (F), and EdU assays (H) used to detect the proliferation of MCF-7 and MDA-MB-231 cells stably transfected with ACSL3 silencing and overexpression vectors. Transwell assays (G) and wound healing assays (G, I) indicating cell metastasis and invasion. Scale bar, 20 μm. Error bars represent the mean ± S.D. of 3 independent experiments. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

We used continuous monitoring methods, CCK-8 assays (Figure 2F), and colony formation assays (Figure 2E) to measure cell proliferation. These results validated the role of ACSL3 as a tumor suppressor in BC cells and revealed that elevated ACSL3 expression interferes with rapid proliferation of BC cells. We further used EdU assays to confirm these results (Figure 2H). The experimental results suggested that ACSL3 downregulation increased the malignant behavior of BC cells. Subsequently, we performed Transwell (Figure 2G) and wound-healing assays (Figure 2I) to evaluate invasion and metastasis ability. Knockdown of ACSL3 significantly promoted the invasion and metastasis of BC cells; in contrast, an increase in ACSL3 inhibited the malignant phenotypes of BC cells.

The EMT process is associated with the malignant behaviors of tumors31. Therefore, we confirmed the correlation between ACSL3 and typical EMT markers in TCGA database. Pearson correlation analysis revealed that ACSL3 expression positively correlated with the expression of epithelial markers (E-cadherin, ZO-1, and cytokeratin) and negatively correlated with a mesenchymal marker (vimentin) (Figure 3A). These results suggested that ACSL3 is associated with the EMT process in BC cells.

Figure 3
Figure 3

ACSL3 facilitates the EMT process in BC cells. (A) Pearson correlation analysis of ACSL3 and EMT markers [epithelial markers: E-cadherin (CDH1), ZO-1(TJP1) and cytokeratin (KRT19); mesenchymal marker vimentin (VIM)] in BC from TCGA database. (B) Western blot analysis of the correlation between ACSL3 and EMT typical markers in MCF-7 and MDA-MB-231 cells stably transfected with ACSL3 silencing and overexpression vectors. (C) Gray value analysis of the results in Figure 3B with ImageJ. (D) RT-PCR confirmation of the relationship between ACSL3 and EMT typical markers in MCF-7 and MDA-MB-231 cells stably transfected with ACSL3 silencing and overexpression vectors. (E) Immunofluorescence staining of E-cadherin and N-cadherin in MCF-7 and MDA-MB-231 cells stably transfected with ACSL3 silencing and overexpression vectors. Nuclei were stained with DAPI (blue). Scale bars, 10 μm. (F) Subcutaneous tumors mouse model constructed to test the effect of ACSL3 overexpression or knockdown on BC cells growth in vivo. (G) Bar graphs comparing final tumor weights. (H) Xenograft tumor volume growth curves. (I) Representative IHC staining images of Ki67 in tumor tissues isolated from the indicated groups of nude mice. **P < 0.01; ***P < 0.001; ****P < 0.0001.

We next studied the effects of ACSL3 on the EMT process at the mRNA and protein levels by detecting epithelial markers (E-cadherin and ZO-1) and mesenchymal markers (N-cadherin, vimentin, cytokeratin 19, and β-catenin). The mRNA (Figure 3D) and Western blot (Figure 3B) results confirmed that the overexpression of ACSL3 correlated with a decrease in mesenchymal marker expression and an increase in epithelial marker expression; in contrast, silencing of ACSL3 in MDA-MB-231 cells produced opposite results, with an increase in mesenchymal marker expression and a decrease in mesenchymal marker expression. The grey value analysis of Figure 3B is presented in Figure 3C. We also performed immunofluorescence analysis to confirm the changes in the expression of E-cadherin and N-cadherin induced by changes in ACSL3 expression (Figure 3E). Overexpression of ACSL3 increased E-cadherin expression and decreased N-cadherin expression.

An in vivo subcutaneous mouse model further demonstrated that ACSL3 overexpression inhibited the growth of subcutaneous tumors derived from MDA-MB-231 cells, whereas ACSL3 downregulation clearly promoted the growth of MCF-7 cell-derived tumors (Figure 3F). The subcutaneous tumor weight and tumor growth rate was also consistent with these findings (Figure 3G, H). We further used IHC staining to confirm the expression of Ki67 in the xenograft tumors (Figure 3I) and observed that the tumor growth rate was associated with ACSL3 expression.

ACSL3 regulates lipid metabolism through multiple pathways in BC cells

Previous research has indicated that the ACSL3 enzyme activates long-chain FAs in cells. We used Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to identify genes associated with ACSL3. Gene sets with a false discovery rate < 0.05 and statistical significance were screened and ranked according to the number of enriched genes. The results suggested that the genes associated with ACSL3 were enriched in FA biosynthesis function (Figure 4A).

Figure 4
Figure 4

Effects of ACSL3 on lipid metabolism in BC cells. (A) GO and KEGG enrichment pathways analysis of differentially expressed genes between ACSL3 high- and low-expression breast cancer tissues in TCGA database. The top 15 pathways are presented in a bubble diagram. (B) The main element of intracellular LDs (TAG), measured in MCF-7 and MDA-MB-231 cells stably transfected with ACSL3 silencing and overexpression vectors. FFA (C), NADPH (D), NADH (E), MDA (F) and ATP (G) measured in MCF-7 and MDA-MB-231 cells stably transfected with ACSL3 silencing and overexpression vectors. (H) LDs detected by Nile red staining assays in MCF-7 and MDA-MB-231 cells stably transfected with ACSL3 silencing and overexpression vectors. Scale bars, 10 μm. (I) ROS assays indicating ROS levels in MCF-7 and MDA-MB-231 cells stably transfected with ACSL3 silencing and overexpression vectors. Scale bars, 200 μm. (J, K) RT-PCR and Western blot indicating the expression of the 5 enzymes influenced by ACSL3 knockdown or overexpression in MCF-7 and MDA-MB-231 BC cells. Error bars represent the mean ± SD of 3 independent experiments. (L) Gray value analysis of the results in Figure 4K with ImageJ. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

To monitor the function of ACSL3 in FA metabolism in BC cells, we measured intracellular LDs. On the basis of their biological structure, LDs function as storage organelles for neutral lipids, primarily TAG. We tested the neutral lipids inside BC cells (Figure 4B). The results suggested that upregulation of ACSL3 increased the levels of neutral lipids, whereas ACSL3 silencing had an opposite effect. Nile red staining of MDA-MB-231 and MCF-7 cells (Figure 4H) indicated that ACSL3 expression correlated with LD accumulation. LDs decreased after ACSL3 was downregulated and increased after ACSL3 was overexpressed. Another biological function of ACSL3 is activation of FAs. Detection of the FFA content in BC cells (Figure 4C) confirmed that ACSL3 overexpression decreased FFA levels, whereas downregulation of ACSL3 induced an opposite effect.

Our bioinformatics analysis suggested that ACSL3 interferes with oxidative phosphorylation and NADH production. Moreover, knockdown of ACSL3 promoted the production of NADH and NADPH, whereas upregulation of ACSL3 induced opposite effects (Figure 4D, E). The levels of these products correlated with the levels of reactive oxygen species (ROS) and lipid peroxidation (MDA). We also measured the levels of MDA (Figure 4F) and ROS (Figure 4I), and observed that ACSL3 increased the levels of ROS and MDA in BC cells.

To study how ACSL3 regulates lipid metabolism in BC cells, we identified several key FA metabolism enzymes associated with ACSL3, according to the STRING database (Figure S1), which played important roles in β-oxidation, FAO, and de novo FA synthesis. The key enzymes were CPT1, carnitine palmitoyltransferase-2 (CPT2), ACOX1, acyl-CoA oxidase 2 (ACOX2), and FA synthase (FASN). We conducted real-time PCR and Western blot to validate the relationship between ACSL3 and the above enzymes in BC cells (Figure 4J, K) and confirmed that ACSL3 expression significantly decreased the expression of those key enzymes. After ACSL3 overexpression in MDA-MB-231 cells, the mRNA and protein expression of all the above enzymes except ACOX2 declined. The mRNA and protein expression of key enzymes, except ACOX2, clearly increased after ACSL3 knockdown in MCF-7 cells. On the basis of the experimental results, ACSL3 is strongly associated with the β-oxidation process inside BC cells. The gray value analysis of the expression of the above proteins is presented in Figure 4L. Next, we further assessed the production of ATP (Figure 4G), a critical product of intracellular β-oxidation. In general, our results suggested that ACSL3 promotes LD formation and accumulation, and impairs FA metabolism, including FAO and de novo FA synthesis, in BC cells.

ACSL3 suppresses BC cell proliferation, invasion, migration, and EMT in vitrovia the YES1/YAP1 axis

We subsequently focused on how ACSL3 suppresses the tumorigenesis of BC cells. Bioinformatics analysis via GeneMANIA32 and previous research33,34 suggested that ACSL3 might interact with the biological function of YES1 (Figure 5A). We further analyzed 3 public datasets of differentially expressed genes in different subtypes of BC. YES1 expression correlated with the major BC subtypes. Investigation of the relationships between YES1 and clinical features in the GSE123833 dataset indicated that the expression of YES1 was significantly associated with ER status (P = 0.001), histological grade (P = 0.031), and BC subtype (P = 0.012) (Figure S2).

Figure 5
Figure 5

ACSL3 interacts with YES1 and influences its phosphorylation status and the phosphorylation status of YAP1 through phosphorylated YES1. (A) The protein–protein interaction network of ACSL3 was constructed with the GENEMANIA database (https://genemania.org/). YES1 was notable among the interacting proteins. (B) Co-IP analysis of the interaction between ACSL3 and YES1 in MCF-7 and MDA-MB-231 BC cells. (C) Immunofluorescence colocalization assays of the interaction between ACSL3 and YES1 in MCF-7 and MDA-MB-231 BC cells. Scale bars, 10 μm. (D) Western blot detection of the expression of YES1 and phosphorylated-YES1 in MCF-7 and MDA-MB-231 cells stably transfected with ACSL3 silencing and overexpression vectors. The gray value analysis of the results is presented at right. (E) Immunofluorescence colocalization assay of the interaction between YES1 and YAP1 in MCF-7 and MDA-MB-231 BC cells. Scale bars, 10 μm. (F) Co-IP analysis of the interaction between YES1 and YAP1 in MCF-7 and MDA-MB-231 BC cells. (G) Western blot assay detecting expression levels of YAP1 and phosphorylated-YAP1 influenced by ACSL3 knockdown or overexpression in BC cells. The gray value analysis of the results is presented at right. (H, I) RT-PCR and western blot assays measuring the mRNA and protein expression of YAP1 and its downstream genes. The gray value analysis of the results is presented at right. (J) Western blot assay detection of p-YAP1 nuclear localization and expression of YAP1 downstream genes in the nuclei of MCF-7 and MDA-MB-231 BC cells with ACSL3 knockdown or overexpression. The gray value analysis of the results is presented at right. (K) Immunofluorescence assay detection of the expression levels and nuclear localization of BCL-xL in MCF-7 and MDA-MB-231 BC cells with ACSL3 knockdown or overexpression. Scale bars, 10 μm. (L) TUNEL assays confirming the apoptosis status of MCF-7 and MDA-MB-231 BC cells with ACSL3 knockdown or overexpression. Scale bars, 1,000 μm. Error bars represent the mean ± S.D. of 3 independent experiments. **P < 0.01; ***P < 0.001; ****P < 0.0001.

Next, we used coimmunoprecipitation (co-IP) analysis to confirm the specific interaction between intracellular ACSL3 and YES1 in both BC cell lines (Figure 5B). Immunofluorescence colocalization was additionally used to confirm the co-expression of ACSL3 and YES1 in MDA-MB-231 and MCF-7 cells (Figure 5C). We verified the expression of YES1 in MDA-MB-231 and MCF-7 cells via lentivirus transfection. Moreover, we observed that YES1 mRNA levels increased after ACSL3 knockdown and decreased after ACSL3 overexpression (Figure S3). However, at the protein level, the expression of the YES1 was only slightly affected by changes in ACSL3 expression. Moreover, we found that ACSL3 interfered with the phosphorylation of YES1 in BC cells (Figure 5D).

Our findings suggested that YES1 might interact with YAP1. Therefore, we evaluated the interaction between YES1 and YAP1 in 2 BC cell lines through co-IP and immunofluorescence colocalization analyses (Figure 5E, F). Several researchers have reported that YES1 phosphorylates YAP at Y357 and consequently increases its activity35. Knockdown of ACSL3 in MCF-7 cells increased the expression of p-YAP1Y357, whereas upregulation of ACSL3 in MDA-MB-231 cells had opposite results (Figure 5G). We also performed multiple experiments to confirm the expression of YAP1 downstream genes downregulated by ACSL3, including B-cell lymphoma-extra-large (BCL-xL) and β-catenin, at the mRNA and protein levels (Figure 5H, I). We further detected the nuclear localization of YAP1 and the downstream gene expression of YAP1 in BC cells suppressed by ACSL3 expression (Figure 5J, K). The expression of downstream genes of YAP1, including BCL-xL and β-catenin, was confirmed to correlate with BC survival outcomes and various clinical features in a public database (Table S5). We validated the apoptosis status of BC cells affected by changes in BCL-xL expression. Expression of ACSL3 led to apoptosis (Figure 5L).

On the basis of previous research, we used the SRC family kinase inhibitor dasatinib to inhibit YES1. The IC50 curves are presented in Figure 6A. With ACSL3 overexpression, the IC50 value increased for MDA-MB-231 cells but decreased for MCF-7 cells. Additionally, we analyzed cell viability in ACSL3-overexpressing and ACSL3-knockdown cells treated with various concentrations of dasatinib for 48 h. The cell viability data are presented as column charts in Figure 6B. ACSL3 overexpression decreased the sensitivity of MDA-MB-231 cells to dasatinib. In contrast, the dasatinib sensitivity of MCF-7 cells significantly increased after ACSL3 knockout. Hence, we confirmed that ACSL3 deficiency attenuates dasatinib resistance in BC. Because the viability of MCF-7 and MDA-MB-231 cells was not significantly affected by 0.01 μM dasatinib, we chose that concentration as the dasatinib dose in further experiments.

Figure 6
Figure 6

Dasatinib reverses the effects of ACSL3 knockdown in BC cells. (A) IC50 values of MCF-7 and MDA-MB-231 BC cells treated with dasatinib. (B) Effects of dasatinib on the proliferation of MCF-7 and MDA-MB-231 cells, determined with CCK8 assays. MCF-7 and MDA-MB-231 cells were treated with dasatinib at the indicated concentrations for 24 h. (C) RT-PCR measurement of mRNA expression levels of YAP1 downstream genes in the indicated cells treated with dasatinib (0.01 μM). (D) Western blot detection of protein levels of P-YES1, P-YAP1, BCL-xL, and β-catenin in ACSL3-knockdown MCF-7 cells with or without dasatinib treatment. The gray value analysis of the results is presented at right. (E) Western blot assays confirming the nuclear localization and expression levels of P-YAP, BCL-xL, and β-catenin in the nuclei of ACSL3-knockdown MCF-7 cells with or without dasatinib treatment. (F) Western blot assay indicating that the EMT process of ACSL3-knockdown MCF-7 cells is influenced by dasatinib. The gray value analysis of the results is presented at right. (G) Western blot assay measurement of the protein expression of key enzymes in FA metabolism in ACSL3-knockdown MCF-7 cells with or without dasatinib treatment. The gray value analysis of the results is presented at right. (I) Immunofluorescence detection of expression levels and nuclear localization of BCL-xL in ACSL3-knockdown MCF-7 cells with or without dasatinib treatment. Scale bars, 10 μm. (J) EdU assay confirming that dasatinib influences the proliferation of ACSL3-knockdown MCF-7 cells. Scale bars, 100 μm. (K) TUNEL assay detection of the apoptosis status of ACSL3-knockdown MCF-7 cells with or without dasatinib treatment. Scale bars, 1,000 μm. (L) Bar graphs comparing the percentages of proliferating cells. **P < 0.01; ***P < 0.001; ****P < 0.0001.

We used dasatinib to suppress phosphorylation of YES1 in ACSL3-knockdown MCF-7 cells. The expression of p-YAP1Y357 was lower than that in untreated ACSL3-knockdown MCF-7 cells; the downstream gene expression of YAP1 also decreased (Figure 6C, D), as did the nuclear localization rate and expression of downstream genes (Figure 6E, I). We also evaluated the EMT process in dasatinib-treated MCF-7 cells with ACSL3 downregulation. Western blot analysis revealed that dasatinib attenuated the induction of EMT by ACSL3 knockdown (Figure 6F). Because YAP1 can influence lipid metabolism, we also measured the expression of enzymes involved in β-oxidation and lipogenesis. Dasatinib decreased the expression of CPT1, CPT2, and FASN (Figure 6G). The concentrations of major lipid metabolites including FFAs, ATP and MDA were also affected by dasatinib (Figure 6H). BC cells treated with dasatinib had diminished levels of FFAs and ATP, but elevated MDA. To further explore the effect of p-YES1, we evaluated BC cell proliferation and apoptosis after dasatinib treatment. EdU proliferation and TUNEL apoptosis assays revealed that the reversal YES1 phosphorylation inhibited BC cell proliferation and promoted apoptosis (Figure 6J–L).

To explore whether YAP might be necessary for ACSL3 mediated BC progression, we overexpressed YAP in MDA-MB-231 cells overexpressing ACSL3 and knocked down YAP expression in MCF-7 cells with ACSL3 downregulation. The mRNA and protein expression levels of BCL-xL, E-Cadherin, and FASN were downregulated and recovered by the different expression of YAP in MCF-7shACSL3 cells and MDA-MB-231ACSL3 cells. We next applied qRT-PCR and Western blot to measure the mRNA and protein expression of the above genes (Figure 7A, B). Expression of YAP influenced the protein expression of BCL-xL in BC cell nuclei (Figure 7C). Moreover, the levels of lipid metabolites including FFAs, ATP, and MDA were affected by YAP (Figure 7D). Thus, the role of ACSL3 in interfering with BC progression occurs through YAP expression.

Figure 7
Figure 7

YAP is necessary for ACSL3’s interference with BC progression and lipid metabolic reprogramming. (A) qRT-PCR analysis of YES1, YAP1, FASN, E-cadherin, and BCL-xL expression in ACSL3-knockdown BC cells with further YAP overexpression or downregulation. (B) Western blot analysis of phospho-YES1, YAP1, phospho-YAPY357, FASN, E-cadherin, and BCL-xL in ACSL3-knockdown BC cells with further YAP overexpression or downregulation. The gray value analysis of the results is presented at right. (C) Western blot analysis of BCL-xL in the nuclei of ACSL3-knockdown BC cells with further YAP overexpression or downregulation. The gray value analysis of the results is presented at right. (D) Measurements of lipid metabolite concentrations, including FFAs, ATP, and MDA. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Discussion

Lipid metabolism provides an alternative but highly efficient route for cancer cells to generate sufficient energy to support their malignant biological behavior, compared with glucose metabolism. ACSL3, a crucial player in intracellular lipid metabolism, influences the activation of FAs and associated metabolic processes. Our study identified ACSL3 as a breast tumor suppressor, and its expression was found to be significantly downregulated in patients with BC—a phenotype correlated with poorer survival outcomes. The effects of ACSL3 downregulation extended to lipid metabolism, by inducing decreased LD formation and increased levels of β-oxidation enzymes. We propose a novel regulatory mechanism through which ACSL3 influences the phosphorylation of YES1, thereby inhibiting the nuclear localization and transcription of YAP1 and its downstream genes within the nucleus (Figure 8). This mechanism allows BC cells to proliferate, migrate, metastasize, and become insensitive to chemotherapeutic drugs, thus suggesting a novel avenue for combination therapy.

Figure 8
Figure 8

Influence of ACSL3 on the YES1/YAP1 axis in breast cancer. ACSL3 modulates intracellular lipid metabolism and interacts with YES1 in the cytoplasm, thereby influencing YAP1 activation in breast cancer cells. Elevated ACSL3 levels promote LD accumulation by initiating LD assembly in the endoplasmic reticulum. Additionally, ACSL3 downregulates the expression of CPTs, thus decreasing FAO and ATP production, and increasing peroxide accumulation. The formation of a complex between YAP1/TAZ and β-catenin is facilitated; phosphorylation of YAP1 by phosphorylated YES1 subsequently directs this complex to the promoters of anti-apoptotic genes such as BCL-xL. ACSL3 inhibits phosphorylated YES1 activation, thereby suppressing the YES1/YAP1 axis and hindering complex formation. Consequently, decreased expression of BCL-xL and its target gene, FASN, leads to inhibition of breast cancer cell survival and proliferation. In contrast, decreased ACSL3 levels lead to diminished LD accumulation; enhanced CPTs expression, FAO, ATP production; and diminished peroxide accumulation, thereby decreasing oxidative stress. Lower ACSL3 levels alleviate the inhibition of the YES1/YAP axis, thus promoting complex formation, increasing BCL-xL and FASN expression, enhancing anti-apoptotic effects, and ultimately fostering breast cancer cell survival and proliferation. These effects are reversed by use of dasatinib to block phosphorylation of YES1 at Tyr419.

Numerous studies have investigated the roles of ACSL3 in various cancers. Elevated ACSL3 in cancer tissues is recognized as a cancer promoter in fibrosarcoma, prostate cancer, melanoma, hepatocellular carcinoma, and lung cancer. In lung cancer, ACSL3, which is regulated by KRAS, increases FAO via extracellularly derived lipids28. However, in BC, it functions as a tumor suppressor, thereby restraining cell growth and metastasis, particularly BC cell growth and metastasis, which are regulated by CDCP1 or c-SRC in TNBC25,27. Our results align with previous findings indicating that lower ACSL3 expression in BC tissues is associated with poorer clinical outcomes, as observed in public datasets and our own tumor samples. Our research confirmed the role of ACSL3 in impeding the malignant behaviors of BC cells both in vitro and in vivo. We also confirmed that ACSL3 suppressed the EMT process associated with tumor metastasis. With silencing of ACSL3, the expression of mesenchymal markers significantly increased, and the expression of epithelial markers decreased in BC cells. These findings collectively underscore the critical role of ACSL3 in tumorigenesis, thereby suggesting its potential to serve as a biological marker for the diagnosis and prognosis of patients with BC.

Metabolic reprogramming is well known as a major hallmark of cancer. Cancer cells face challenges in synthesizing their own FAs, because this process is severely impaired by harsh environmental conditions. Cancer cells, particularly BC cells, which may directly contact adipocytes, can feed extracellular FAs into the FAO pathway for highly efficient energy provision36,37. Whereas high LD accumulation contributes to initial tumor progression, it hampers BC metastasis27,38,39. LDs, which serve as storage organelles for neutral lipids, play dual roles in cancers. As for FFAs, either acquired through direct exogenous uptake from the surroundings or synthesized de novo, is widely recognized as a metabolic hallmark of cancer cells, particularly in β-oxidation for ATP generation40. Furthermore, elevated FFAs and FA oxidation are associated with the inhibition of BC cell apoptosis and lymph node metastasis41,42. On the basis of current research findings, FFAs activates both the ERα and mTOR pathways, reprograms metabolism in BC cells, and augments BC cell migration43.

The byproducts of β-oxidation within mitochondria include ATP and NADH. Increased levels of ROS often arise from ATP synthase, and subsequently lead to DNA damage, protein oxidation, and MDA, and potentially the initiation of cell death44. In BC, decreased ATP and increased ROS levels have been demonstrated to impede cancer cell proliferation45. ROS interact with polyunsaturated FAs in lipid membranes, thereby inducing MDA44. Elevated MDA has been shown to enhance ferroptosis and hinder the metastasis and progression of BC cells46. Another product of β-oxidation, NADH, has been confirmed to regulate BC progression through the balance of NAD+/NADH and mitochondrial complex I activity. An increase in the NAD+/NADH ratio has been associated with a decrease in BC progression47.

In this study, we confirmed that knockdown of ACSL3 increased FFA levels in BC cells. Triglyceride and LD levels also markedly decreased after ACSL3 silencing. The FAO level increased, as indicated by the ATP content. NADH increased, thus alleviating ROS pressure on BC cells. Furthermore, we confirmed the promotion of several key enzymes involved in lipid metabolism, most of which are verified tumor promoters in BC48–52. Together, these findings support the use of a therapeutic strategy for patients with BC, particularly for those with lipid metabolism reprogramming.

Another notable finding of our study was that ACSL3 regulates BC through the YES1/YAP1 axis. YES1, a nonreceptor tyrosine kinase from the SRC family, is a proto-oncogene that is overexpressed in various cancers; higher YES1 expression is associated with poorer survival outcomes53–55. YES1 serves as the main regulator of YAP1; promotes the nuclear translocation of BCL-xL and β-catenin; accelerates the EMT process; and is essential for formation of the YAP1-β-catenin-TBX5 complex, thereby facilitating the tumorigenic effects of β-catenin56–58. More importantly, in BC, YES1 has been confirmed to be associated with EGFR expression and AKT phosphorylation, the latter of which influences the PI3K/AKT/mTOR pathway59,60. YES1 is also responsible for TNBC. Aberrant Src activation plays prominent roles in cancer formation and progression. The role of mitochondrial FAO in metastatic TNBC is energy dependent on the phosphorylation of Src61. Moreover, increased FAO in TNBC cells activates Src phosphorylation, and activated Src in turn phosphorylates mitochondrial ETC proteins, thus leading to maintenance of their activated status. CPT1, a key FAO enzyme, downregulated by ROS, is inhibited by the activation of Src25.

We initially observed an increase in YES1 after ACSL3 knockdown at the mRNA level. The level of phosphorylated YES1 notably increased, although the total protein expression of YES1 remained largely unchanged. Protein interaction between ACSL3 and YES1 was confirmed. Building on previous research, we established that YES1, regulated by ACSL3, enhances the expression, cellular localization, and transcription of YAP1 and its downstream genes in BC. To further validate this finding, we used an inhibitor of YES1 phosphorylation, dasatinib, to verify the downstream gene expression of YES1/YAP1. The genes downstream of the axis, including BCL-xL and β-catenin, were significantly upregulated after ACSL3 silencing. Together, our experimental findings support that ACSL3 impairs the malignant behaviors of BC cells, and hinders their ability to proliferate and metastasize.

Previous research has confirmed YAP’s involvement in metabolic alterations during tumorigenesis62. YAP/TAZ plays a role in promoting self-regulating FA oxidation. Increased FA oxidation induced by YAP has been shown to support lymph node metastasis in cancer63 and to be crucial for the survival of BC cells in nutrient-deprived environments64. Hence, we believe that the ACSL3/YES1/YAP1 axis, as demonstrated by our research, provides a positive feedback loop for the activation of FAO in BC. This study provides evidence of the correlation of ACSL3 with DFS or DMFS.

The Src pathway is one of the most highly activated pathways in TNBC65,66. In our research, analysis of several public datasets indicated that the expression levels of ACSL3, YES1, and genes downstream of YAP1 are associated with BC subtypes67–69. ACSL3 is enriched in luminal subtypes, and YES1 is highly expressed in TN subtypes. Multiple database analyses demonstrated that ACSL3 levels positively correlate with ER expression. In contrast, the expression of YES1 and YAP1 downstream genes negatively correlated with ER expression. Findings from the University of Alabama at Birmingham Cancer (CPTAC) support significant differences in ACSL3 and YES1 expression across distinct BC subtypes70. Compared with patients with other BC subtypes, patients with TNBC have poorer cancer treatment efficacy and survival outcomes71,72. Thus, for TNBC, the clinical benefit of current therapies is limited. Most conventional chemotherapeutic agents, the current clinical standard for TNBC treatment, generally kill cells by activating mitochondrial apoptosis. ACSL3 may be regulated by HIF-1alpha under hypoxic conditions73. Baseline gene expression profiling from other datasets has suggested that ACSL3 and YES1 influence BC cells’ sensitivity to dasatinib68,74. The amplification of YES1 leads to resistance to HER2 inhibitors and other chemotherapeutic agents, such as trastuzumab, neratinib, or trastuzumab in combination with lapatinib75,76. Several clinical trials have demonstrated that dasatinib has limited efficacy in patients with BC. However, many clinical trials have recently confirmed that the combination of dasatinib with paclitaxel is associated with better response and remission rates in patients with metastatic BC than dasatinib alone77. Moreover, recent studies have shown that the downstream genes of YAP1, including FASN and BCL-xL, are involved in endocrine therapy-resistant luminal BC, and both promote BC cells’ malignant biological behavior78–80. We also demonstrated that these 2 genes are regulated by ACSL3 expression. The above results together suggest that downregulation of ACSL3 may serve as a biomarker of malignant transition in BC. Targeting ACSL3 plus YES1/YAP may provide a novel therapeutic strategy for patients with BC with endocrine therapy-resistant luminal-type and basal-like BC types.

This study has several limitations, and future investigations should explore whether ACSL3 suppresses BC cells independently of the YES1/YAP axis. For example, ACSL3 may promote LD formation; however, further research is necessary to determine whether these droplets, in addition to increasing peroxidized lipids in BC cells, might affect other mechanisms, such as endoplasmic reticulum stress. These aspects will require thorough examination in future research. Moreover, how ACSL3 expression correlates with the expression of ER and HER2 should be investigated to determine the relationship between BC subtypes and ACSL3.

Conclusions

In summary, our findings confirmed that ACSL3 acts as a tumor suppressor in BC. Decreased ACSL3 levels in breast tumor tissues contribute to increased cell proliferation, invasion, and metastasis and poorer survival outcomes. ACSL3, an important component of lipid metabolism, suppresses β-oxidation and the expression of key lipid metabolism enzymes. Our study provided the first demonstration, to our knowledge, that ACSL3 suppresses BC cell biological behaviors by regulating the phosphorylation of YES1, the activation of YAP1, and the activity of the downstream YAP1 pathway. Importantly, these results suggest a potential biomarker and therapeutic target for improving BC treatment.

Supporting Information

Conflicts of interest statement

No potential conflicts of interest are disclosed.

Author contributions

Conceived and designed the analysis: Shirong Tan, Xiangyu Sun, Yingying Xu.

Collected the data: Shirong Tan, Xiangyu Sun, Haoran Dong.

Contributed data or analysis tools: Shirong Tan, Mozhi Wang, Litong Yao.

Performed the analysis: Shirong Tan, Mengshen Wang, Ling Xu.

Wrote the paper: Shirong Tan.

Data availability

The data generated in this study are available upon request from the corresponding author.

Acknowledgements

We extend our heartfelt appreciation to our fellow researchers, particularly Professor Yingying Xu, for their invaluable contributions and collaborative spirit, which greatly enriched the outcomes of this study.

Appendix A Abbreviations

FAO
fatty acid oxidation
ACSL
acyl-CoA synthetase long-chain family
BC
breast cancer
ANT
adjacent normal tissue
YES1
YES proto-oncogene 1
YAP1
Yes-associated protein 1
FA
fatty acid
TAG
triacylglycerols
ACS
acyl-CoA synthetase
LD
lipid droplet
OXPHOS
oxidative phosphorylation
ATP
adenosine triphosphate
CPT1
carnitine palmitoyltransferase I
ACOX1
acyl-CoA oxidase 1
CDCP1
CUB-domain-containing protein 1
TNBC
triple-negative breast cancer
EMT
epithelial-to-mesenchymal transition
FFA
free fatty acid
MDA
lipid peroxidation
ROS
reactive oxygen species
CPT2
carnitine palmitoyltransferase-2
ACOX2
acyl-CoA oxidase 2
FASN
fatty acid synthase
ER
estrogen-receptor
BCL-xL
B-cell lymphoma-extra large

Footnotes

  • ↵*These authors contributed equally to this work.

  • Received August 22, 2023.
  • Accepted April 15, 2024.

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