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Article

Antitumor Activity of the ACC Inhibitor Firsocostat in Breast Cancer Cell Lines: A Proof-of-Concept In Vitro Study

1
Laboratory of Preclinical and Translational Research, Centro di Riferimento Oncologico della Basilicata (IRCCS-CROB), Rionero in Vulture, 85028 Potenza, Italy
2
Clinical Analysis Laboratory, Cerba HealthCare Basilicata S.r.l., Rionero in Vulture, 85028 Potenza, Italy
*
Author to whom correspondence should be addressed.
Pharmaceuticals 2026, 19(2), 201; https://doi.org/10.3390/ph19020201
Submission received: 15 December 2025 / Revised: 21 January 2026 / Accepted: 22 January 2026 / Published: 24 January 2026
(This article belongs to the Special Issue Adjuvant Therapies for Cancer Treatment: 2nd Edition)

Abstract

Background/Objectives: Breast cancer is the most frequently diagnosed malignancy among women and is characterized by marked heterogeneity in treatment response. Metabolic reprogramming, particularly enhanced de novo lipogenesis, represents a hallmark of cancer progression and a promising therapeutic target. Firsocostat, a selective allosteric inhibitor of acetyl-CoA carboxylase (ACC), has previously been investigated in metabolic diseases but has never been evaluated in breast cancer models. This study aimed to assess the antitumor effects of firsocostat on breast cancer cell lines. Methods: We investigated the cytotoxic and metabolic effects of firsocostat in four breast cancer cell lines—MCF7 (luminal A HR+), SK-BR-3 (HER2-positive), MDA-MB-231 (triple-negative), and HCC1937 (triple-negative, BRCA1-mutated)—together with the non-tumorigenic MCF-10A line. Dose- and time-dependent responses were evaluated using phase-contrast microscopy for morphological evaluation, Trypan Blue exclusion assays, and MTS-based viability assays. Results: Firsocostat significantly reduced cell viability across all breast cancer subtypes in a concentration- and time-dependent manner, with IC50 values ranging from 80 to 93 µM. In contrast, non-tumorigenic MCF-10A cells were less affected, indicating a selective cytotoxic effect toward malignant cells. Conclusions: Firsocostat exerts robust cytotoxic effects in breast cancer models, identifying it as a promising metabolism-targeting therapeutic candidate capable of selectively impairing breast cancer cell survival by disrupting fatty acid biosynthesis. These results indicate that firsocostat could represent a viable candidate as a metabolic-based therapeutic approach for breast cancer. Given its established clinical safety profile in metabolic diseases, firsocostat warrants further preclinical investigation and supports further mechanistic and preclinical evaluation.

Graphical Abstract

1. Introduction

Worldwide, breast cancer (BC) is the most frequently diagnosed malignancy in women, contributing to roughly one third of cases and approximately 15% of cancer-related mortality [1]. The global burden of BC has increased substantially over the past decades, with incidence cases rising from 875,657.23 in 1990 to over 2.1 million in 2021. The age-standardized incidence rate (ASIR) rose from 16.42 per 100,000 in 1990 to 26.88 per 100,000 in 2021 [2]. BC development is influenced by a complex interplay of genetic predisposition (mutations in genes such as BRCA1 and BRCA2), hormonal factors (late menopause, early menarche, absence of pregnancies), and lifestyle-related factors (smoking, obesity, radiation exposure, physical inactivity). From a molecular and histopathological standpoint, BC is commonly classified into three major subtypes: hormone receptor-positive tumor (characterized by the expression of estrogen—ER+—and/or progesterone receptors—PR+), human epidermal growth factor receptor 2-positive (HER2+) tumors, and triple-negative breast cancers (TNBC) (which lack expression of ER, PR, and HER2) [3,4]. This molecular heterogeneity strongly influences prognosis, therapeutic response, and clinical management.
Over the past two decades, expanding insight into breast cancer biology has enabled the development of targeted therapeutic strategies designed to interfere with molecular pathways that sustain tumor growth and survival [5]. Nevertheless, therapeutic resistance and disease recurrence remain major clinical challenges, highlighting the need for novel treatment approaches.
As a matter of fact, cancer cells undergo profound metabolic reprogramming to sustain uncontrolled proliferation and survival. These metabolic alterations contribute to redox balance, apoptosis regulation, and the utilization of alternative substrates such as lactate and acetate. Overall, cancer metabolism is characterized by coordinated changes in glucose, amino acid, and lipid metabolism that collectively sustain tumor progression, and reshape the tumor microenvironment in favor of malignancy [6,7,8]. One of the most well-known metabolic hallmarks of cancer is the Warburg effect, which describes a shift toward aerobic glycolysis with increased lactate production despite adequate oxygen availability and reduced reliance on oxidative phosphorylation [9,10,11,12].
In addition to altered glucose metabolism, another major alteration occurs in lipid metabolism. Unlike normal adult cells, which mainly rely on dietary or liver-derived fatty acids, tumor cells frequently reactivate de novo lipogenesis to ensure a continuous supply of lipids required for membrane biogenesis, energy storage through fatty acid oxidation (FAO), and signaling processes. Enhanced lipid biosynthesis supports rapid tumor cell proliferation, whereas its suppression compromises cancer cell viability and limits tumor progression. This metabolic reprogramming not only facilitates rapid cell division but also decreases reliance on exogenous lipid uptake [13,14,15]. Consistently, altered expression of key enzymes and regulatory factors involved in lipid biosynthesis and catabolic pathways has been shown to influence BC cell proliferation and metastatic potential [16,17,18].
Within this metabolic framework, acetyl-CoA carboxylase (ACC), which catalyzes the conversion of acetyl-CoA to malonyl-CoA, represents a key regulatory node coordinating the balance between de novo lipogenesis and fatty acid oxidation. In tumor cells, ACC inhibition is expected to decrease malonyl-CoA availability, thereby limiting the fatty acid synthesis required for membrane biogenesis and lipid-based signaling, and potentially impairing the generation of unsaturated lipids needed to maintain membrane fluidity [17,18,19]. In line with this concept, previous work showed that reducing free fatty acid availability and restricting the conversion of saturated fatty acids (SFA) into monounsaturated fatty acids (MUFA)—partly through limiting stearoyl-CoA desaturase (SCD) activity—can slow tumor growth, consistent with a critical dependency of proliferating cells on lipid desaturation for expansion and survival [17,18,19]. Because fatty acids are essential for tumor cell growth and survival, targeting ACC has emerged as an attractive therapeutic strategy.
In this context, modulating fatty acid metabolism in cancer cells has emerged as a promising adjunctive therapeutic strategy. By altering lipid availability, this approach may reduce cell proliferation, enhance oxidative stress, and ultimately induce cancer cell death.
Firsocostat, a potent allosteric inhibitor of ACC that was originally developed for the treatment of non-alcoholic steatohepatitis (NASH) [20,21,22,23], has demonstrated a robust capacity to modulate hepatic lipid metabolism. Although its clinical evaluation has thus far been limited to metabolic liver disorders, preclinical studies support a broader antitumor potential for ACC inhibition across different cancer models [20,21]. Nevertheless, no published evidence has specifically investigated the antineoplastic potential of firsocostat in breast cancer.
Previous work has implicated ACC as functionally relevant to breast cancer cell survival and linked lipid synthesis control to oncogenic phenotypes, supporting ACC as a plausible metabolic target in oncology. Breast cancer subtypes differ not only in receptor status and therapeutic vulnerabilities but also in metabolic features that may influence sensitivity to metabolic interventions. This heterogeneity provides distinct metabolic programs that can translate into differential dependencies on lipid acquisition and synthesis. Luminal tumors frequently show coordinated lipogenic signaling to sustain proliferation, HER2-driven cancers exhibit increased anabolic metabolism (including fatty acid synthesis) downstream of growth-factor pathways, and triple-negative breast cancers often rely on metabolic plasticity with heightened lipid turnover and sensitivity to perturbations in redox and energy balance [24].
Therefore, the present study aimed to evaluate, for the first time, the potential antitumor activity of firsocostat across luminal, HER2-positive, and triple-negative models rather than extrapolating from a single subtype. Among hereditary breast cancers, BRCA1 mutation carriers are predisposed to aggressive tumors that are frequently triple-negative and can display biological and metabolic features distinct from sporadic disease, with potential implications for treatment response and sensitivity [25,26,27]. BRCA1 loss has been associated with metabolic reprogramming, including increased reliance on fatty acid synthesis, altered mitochondrial function, and redox imbalance [28,29]. These features may increase dependence on ACC-regulated lipid metabolism, providing a plausible rationale for including a BRCA1-deficient model in this study [20].
This strategy may open new avenues to overcome resistance to conventional cancer therapies. To this end, the HCC1937, which carries a BRCA1 mutation, the MCF7, SK-BR-3, and MDA-MB-231 (ER+, HER2+, and TNBC, respectively) cell lines were employed as relevant in vitro models to explore the therapeutic potential of novel metabolism-targeting agents such as firsocostat.

2. Results

2.1. Firsocostat Selectively Induces Dose-Dependent Cytotoxicity in Breast Cancer Cell Lines

To investigate the potential antitumor effects of firsocostat, a selective allosteric inhibitor of acetyl-CoA carboxylase (ACC), we examined its impact on cell morphology and viability in a panel of BC cell lines representing distinct molecular subtypes—MCF7 (HR+, Luminal A), MDA-MB-231 (TNBC), and SK-BR-3 (HER2-amplified). HCC1937 (TNBC) cells were included as a BRCA1-mutant model to capture a clinically relevant genetic context within the breast cancer spectrum alongside the non-tumorigenic breast epithelial line MCF-10A.
Cells were exposed to increasing concentrations of firsocostat—0 µM (Figure 1a), 25 µM (Figure 1b), 100 µM (Figure 1c), and 200 µM (Figure 1d)—for 72 h, and morphological changes were assessed by phase-contrast microscopy (10X magnification).
Under control conditions (0 µM, Figure 1a), all cell lines exhibited confluent monolayers with preserved epithelial morphology and intact intercellular contacts. In contrast, firsocostat treatment induced a progressive reduction in cell density and loss of cell adhesion in all BC cell lines in a dose-dependent manner. Morphological features consistent with cytotoxic stress and apoptosis, including cell shrinkage, rounding, and detachment, were particularly evident at concentrations of 100 µM and 200 µM, where MDA-MB-231 and HCC1937 cells showed extensive cell loss and debris formation, indicating higher sensitivity of triple-negative subtypes. SK-BR-3 and MCF7 cells showed intermediate sensitivity, maintaining partial confluence at lower doses. Notably, the non-tumorigenic MCF-10A cells displayed only minor morphological alterations, even at the highest firsocostat concentration tested, maintaining overall structural integrity and partial confluence. This differential response suggests a selective cytotoxic activity of firsocostat toward malignant breast cells while sparing non-tumorigenic epithelial counterparts.

2.2. Evaluation of Cell Viability Using Trypan Blue Exclusion Assay

To confirm morphological observations, a Trypan Blue exclusion assay was subsequently performed exclusively on tumor cells, as the primary aim was to assess the effects of the treatment on malignant rather than healthy cells. The assay was not conducted on non-tumor cells, since, under the experimental conditions, these cells did not exhibit any detectable morphological alterations, and were therefore not expected to show significant changes in viability. Cell viability analysis revealed distinct dose-dependent responses to firsocostat across the four breast cancer cell lines. In MCF7 cells (Figure 2a), untreated control and the 25 µM firsocostat treatment exhibited exponential growth over 72 h. In contrast, treatment with 50 µM and 100 µM of firsocostat significantly reduced cell proliferation in a dose-dependent manner, culminating in near-complete inhibition at 100 µM after 72 h. In SK-BR-3 (Figure 2b) cells, firsocostat treatment displayed a comparatively lower sensitivity. While control cultures kept growing steadily, treatment with 25 µM only partially stopped growth, more clearly stopped at 50 µM, and almost completely stopped at 100 µM after 72 h. MDA-MB-231 cells (Figure 2c) exhibited robust growth under control conditions, while firsocostat treatment significantly slowed proliferation at both 25 µM and 50 µM, with cell viability stabilizing as early as 24 h at a higher concentration. Similarly, HCC1937 cells (Figure 2d) also exhibited continuous proliferation in control conditions, whereas firsocostat (25 µM and 50 µM) exposure slowly reduced viability in a dose-dependent trend, with 100 µM treatment having a detectable effect at 48 h that became more pronounced at 72 h.

2.3. Assessment of Cell Metabolic Activity by MTS Colorimetric Assay

To further investigate the effects of firsocostat on cellular viability and metabolic activity, an MTS assay was performed on HCC1937, MDA-MB-231, MCF7, SK-BR-3, as well as on the non-tumorigenic MCF-10A. Cells were treated for 72 h with increasing concentrations of firsocostat (25–200 µM). As shown in Figure 3, firsocostat exposure at concentrations ranging from 25 to 100 µM led to the progressive inhibition of cell proliferation, with statistically significant reductions observed at ≥50 µM in all tumor-derived lines, while exerting minimal effects on non-tumorigenic epithelial cells (One-Way ANOVA with Tukey’s post hoc test). Among malignant models, the luminal A HR+ MCF-7 cell line exhibited the greatest sensitivity, with viability decreasing to 24.8 ± 3.9% (p < 0.0001) at 100 µM compared to vehicle-treated controls (Figure 3a). HER2-amplified SK-BR-3 cells exhibited a similar sensitivity, with a viability of 28.7 ± 4.8% (p < 0.0001) at the same concentration (Figure 3b), indicating that the magnitude of inhibition varies with molecular subtype. Among malignant models, the TNBC MDA-MB-231 (Figure 3c) and the TNBC BRCA1-mutated HCC1937 cells (Figure 3d) exhibited a similar but slightly less pronounced response, with viability decreasing to 37.7 ± 3.6% and to 37.1 ± 4.1% at 100 µM compared to vehicle-treated controls, respectively (p < 0.0001). In contrast, the non-tumorigenic mammary epithelial cell line MCF-10A retained 54.1 ± 3.4% viability at the same concentration of 100 µM firsocostat (Figure 3e).
However, only by increasing the concentration of firsocostat to 200 µM, which is twice the highest concentration used for tumor cell lines, did MCF-10A cell viability decrease to 28.7 ± 4.2% (p < 0.0001), indicating its low selectivity for the healthy control and suggesting a potential therapeutic selectivity window (Figure 3e).
Data are reported as mean ± SD from three independent experiments, and statistical comparisons were assessed by one-way ANOVA with Tukey’s post hoc test correction.

2.4. Differential IC50 Responses Highlight Variable Sensitivity of Breast Cancer Cell Lines to Firsocostat

Based on MTS assay data, the next step was to determine the half-maximal inhibitory concentration (IC50) value for firsocostat in each cell line. Determining the IC50 values allowed us to compare the sensitivity of different BC cell lines to firsocostat and to evaluate the selectivity of its cytotoxic effects relative to the non-tumorigenic MCF-10A cells. As shown in Figure 4, MTS viability assays demonstrated that firsocostat induced a robust, concentration-dependent reduction in cell viability across all tested breast cancer cells, while sparing the non-tumorigenic MCF-10A epithelial control. Treatment with firsocostat at 25 µM, 50 µM, 75 µM, and 100 µM resulted in progressive declines in viability in the malignant cell lines, consistent with a strong inhibitory profile that yielded IC50 values in the low-to-mid range. Hence, quantitative analysis revealed IC50 values of 85.1 µM for MCF7, 80.1 µM for SK-BR-3, 92.4 µM for MDA-MB-231, and 92.7 µM for HCC1937 cells (Figure 4a–d). These findings demonstrate that firsocostat exerts comparable antiproliferative effects across distinct molecular subtypes of BC—including luminal A HR+ (MCF7), HER2-amplified (SK-BR-3), and triple-negative (MDA-MB-231 and HCC1937) models—suggesting a subtype-independent mechanism of action.
On the contrary, MCF-10A control cells exhibited minimal reduction in metabolic activity up to 100 µM and only modest effects at 200 µM (Figure 4e). Although MCF-10A cells exhibited higher IC50 values than the breast cancer cell lines under these experimental conditions, suggesting that firsocostat cytotoxicity is potentially selective for transformed breast cells, this difference represents an in vitro comparator based on a single non-tumorigenic mammary epithelial model and should not be interpreted as evidence of a therapeutic index or clinical safety margin.
To facilitate comparison, an in vitro selectivity index (SI) was calculated as IC50(MCF-10A)/IC50(tumor line) for each model. Using IC50(MCF-10A) = 128.2 µM, SI values ranged from 1.38 to 1.60 across the tested breast cancer cell lines, indicating higher IC50 values in MCF-10A than in the tumor models under identical assay conditions. The highest SI was observed for SK-BR-3 (1.60), MCF-7 (1.51), whereas MDA-MB-231 (1.39) and HCC1937 (1.38) showed similar SI values. Overall, SI values of 1.38–1.60 indicate a modest differential sensitivity, favoring the tumor cell lines, under the tested conditions; however, this magnitude of separation does not establish a therapeutic index and should be interpreted as an in vitro comparator requiring validation in additional normal-cell models and in vivo systems.

3. Discussion

This study provides the first evidence that firsocostat (GS-0976), a selective allosteric acetyl-CoA carboxylase (ACC) inhibitor, exerts a potent and selective cytotoxic effect in different breast cancer (BC) cell lines representing distinct molecular subtypes, while sparing non-tumorigenic mammary epithelial cells. These findings extend the pharmacological profile of firsocostat beyond metabolic diseases, such as non-alcoholic steatohepatitis (NASH) [20], and support its potential repurposing as an antineoplastic agent targeting tumor lipid metabolism [10,13].
Beyond metabolic indications, ACC-mediated de novo lipogenesis has been increasingly explored as an anticancer target across multiple tumor types. Pharmacologic ACC inhibition has been shown to suppress de novo fatty acid synthesis, induce stress responses and apoptosis, and reduce tumor growth in vivo, with rescue by exogenous palmitate supporting an on-target dependence on lipogenic flux [30,31,32]. Beyond single-agent activity, ACC has been implicated in therapy-driven metabolic rewiring and resistance, and ACC inhibition has shown promise in combination settings (e.g., with EGFR-targeted therapy). In preclinical models, ACC targeting also reduced tumor burden in hepatocellular carcinoma models and improved outcomes in combination with standard therapy [28,33].
Increasing evidence indicates that metabolic reprogramming represents a hallmark of breast cancer progression, with many subtypes showing a strong dependence on de novo lipogenesis to sustain proliferation and survival [24]. Luminal and HER2-positive breast cancers frequently display enhanced fatty acid synthesis, while triple-negative breast cancers, despite their pronounced metabolic plasticity, remain reliant on lipid biosynthesis pathways to support rapid cell growth [24].
Collectively, these studies provide a mechanistic and translational rationale for evaluating clinically advanced ACC inhibitors such as firsocostat as candidate metabolic therapeutics in breast cancer.
Our results demonstrated a clear dose- and time-dependent reduction in cell viability across all BC cell lines tested. Notably, MCF7, SK-BR-3, MDA-MB-231, and HCC1937 cells exhibited IC50 values within a narrow range of 80–93 μM, indicating a broadly conserved vulnerability to ACC inhibition across luminal A, HER2-positive, and triple-negative breast cancer subtypes. In contrast, the non-tumorigenic MCF-10A cells displayed markedly higher tolerance, supporting a degree of selectivity of firsocostat toward transformed cells and suggesting that metabolic targeting via ACC inhibition preferentially disrupts the metabolic homeostasis of cancer cells that rely heavily on lipid synthesis.
Nevertheless, the relatively high IC50 values observed in 2D in vitro conditions require cautious pharmacological interpretation, as effective in vitro concentrations may not directly reflect achievable exposures in vivo, where pharmacokinetics, tissue distribution, and microenvironmental factors can substantially influence drug activity and metabolic dependencies.
Clinically, firsocostat has the advantage of having human dosing and safety experience, mainly in metabolic liver disease, where it has been administered orally (commonly 20 mg once daily) and shown pharmacodynamic activity consistent with ACC inhibition (e.g., suppression of hepatic de novo lipogenesis/steatosis markers) [29]. However, systemic ACC inhibition carries on-target metabolic liabilities—most notably, increases in circulating triglycerides, with reports of marked hypertriglyceridemia in a subset of treated participants—highlighting that any oncology translation will require careful monitoring and potentially mitigation strategies (e.g., lipid-lowering co-therapy) to preserve a usable therapeutic window [20]. In addition, firsocostat exposure can be substantially altered by hepatic impairment, which is relevant when considering patients with liver involvement or comorbidities [34]. From a translational oncology standpoint, these considerations are particularly relevant because firsocostat was developed as a liver-directed ACC inhibitor and clinical experience to date mainly derives from non-oncology settings, such that the feasibility of achieving sustained tumor target engagement at exposures compatible with an acceptable safety margin remains to be established.
Therefore, these data should be considered proof-of-concept evidence for ACC pathway vulnerability, while translational relevance will need to be assessed in more physiologically relevant models (e.g., 3D/organoids) and ultimately in vivo, ideally supported by pharmacokinetic/pharmacodynamic evaluation of target engagement.
HCC1937 was included as a BRCA1-mutant, triple-negative breast cancer model to increase the molecular diversity of the panel and to explore whether BRCA1-associated biology may be linked to distinct metabolic dependencies, including sensitivity to ACC inhibition. Notably, HCC1937 cells showed enhanced sensitivity to firsocostat, consistent with evidence that BRCA1 loss has been associated with profound metabolic reprogramming characterized by increased fatty acid synthesis, impaired mitochondrial respiration, and altered redox balance [26]. BRCA1 directly interacts with ACC1 to regulate its phosphorylation and activity; loss of BRCA1 function leads to sustained ACC1 activation and lipid accumulation [35,36,37]. Therefore, pharmacologic ACC inhibition by firsocostat may partially compensate for BRCA1 loss, exposing a synthetic–lethal metabolic vulnerability in BRCA1-deficient tumors. This finding aligns with prior reports showing that BRCA1-deficient breast cancers display heightened dependency on lipid metabolism and oxidative stress-buffering pathways [26,38].
At the molecular level, firsocostat allosterically inhibits both ACC isoforms, thereby blocking the conversion of acetyl-CoA to malonyl-CoA, a rate-limiting step in fatty acid biosynthesis [18,37]. By suppressing de novo lipogenesis (DNL), this inhibition limits the availability and synthesis of long-chain fatty acids, and membrane phospholipids, and ultimately constrains the metabolic resources required for tumor proliferation and survival [15,17,21,22,23]. Additionally, ACC inhibition reduced malonyl-CoA, shifting lipid flux toward fatty acid oxidation (FAO) while reducing cytoplasmic NADPH availability impairing redox homeostasis. These changes may promote energetic and oxidative stress and favor susceptibility to apoptosis [21,22]. These converging effects provide a plausible mechanistic basis for the morphological features—cell shrinkage, rounding, and detachment—and decreased viability observed in our models and support prioritizing follow-up studies assessing ACC activity, lipid composition, and stress/apoptosis markers to directly link metabolic rewiring to cell fate.
Our findings are consistent with recent evidence highlighting the role of lipid metabolism and membrane biophysics in colorectal cancer progression. Jiang et al. [39] have demonstrated that the Colorectal Cancer Metastasis-Suppressed LncRNA (CRCMSL) suppresses tumor invasion and metastasis by restricting acetyl-CoA carboxylase 1 (ACC1) activity, leading to reduced phospholipid unsaturation, decreased membrane fluidity, and enhanced ferroptosis. Importantly, the study has shown that pharmacological inhibition of ACC using firsocostat synergizes with CRCMSL activity both in vitro and in vivo, resulting in reduced tumor growth and metastatic potential. Together, these data support the concept that targeting fatty acid metabolism and membrane fluidity represents a promising therapeutic strategy in cancer, particularly in the context of metastasis suppression and ferroptosis induction [39].
Recent evidence further supports the concept that breast cancer progression is tightly coupled to metabolic reprogramming and that this rewiring is heterogeneous across tumors. For instance, MAEL has been reported to promote metabolic reprogramming by inducing the chaperone-mediated autophagy-dependent degradation of citrate synthase and fumarate hydratase, thereby weakening TCA cycle capacity and favoring glycolytic traits linked to tumor aggressiveness [40]. These findings support the broader concept that breast cancer cells can reconfigure central carbon metabolism and stress-response features, which may increase reliance on biosynthetic lipid pathways for membrane remodeling and growth, and thus influence vulnerability to ACC/DNL blockade. Importantly, heterogeneity in metabolic wiring suggests that responses to ACC blockades may vary across patient subsets and underscores the value of biomarker-driven stratification. In this regard, computational frameworks such as FUNMarker highlight substantial inter-patient and subtype heterogeneity by identifying cluster-specific prognostic biomarkers using integrated network information, suggesting that metabolic liabilities are unlikely to be uniform across luminal, HER2-positive, and triple-negative contexts [41]. Within this framework, our results support further evaluation of ACC inhibition, together with subtype-aware biomarker and metabolic profiling (e.g., lipogenic signatures and stress-response readouts) to better define which breast cancer contexts—potentially including BRCA1-altered models—exhibit the most actionable susceptibility.
Interestingly, all molecular subtypes—luminal A HR+, HER2+, and triple-negative—exhibited comparable responses to firsocostat, suggesting that the dependence on de novo lipogenesis is a shared metabolic vulnerability across breast cancer phenotypes. Nevertheless, minor differences in sensitivity may reflect intrinsic metabolic flexibility, with triple-negative cells such as MDA-MB-231 exhibiting greater reliance on glycolysis and glutaminolytic pathways, whereas luminal A HR+ and HER2+ subtypes exhibit a stronger dependence on lipid biosynthetic fluxes.
Taken together, these data support the hypothesis that firsocostat selectively targets ACC-mediated lipid metabolism in BC, providing a mechanistic basis for its potential repositioning as an anticancer therapeutic. Firsocostat not only demonstrates antitumor potential in vitro but also provides a valuable proof-of-concept for repurposing metabolic inhibitors in oncology. From a translational perspective, firsocostat could be evaluated in synergistic studies as a metabolic sensitizer alongside subtype-specific therapeutic standards. In HR+/HER2 BC, a rational next step is pairing firsocostat with endocrine therapy (e.g., letrozole/anastrozole/exemestane or fulvestrant) plus a CDK4/6 inhibitor (palbociclib, ribociclib, or abemaciclib), which represents a frontline backbone in advanced settings. In HER2+ BC models, combinations with trastuzumab and pertuzumab (and/or a taxane such as docetaxel) are mechanistically appealing given the anabolic signaling downstream of HER2. In the TNBC subtype, firsocostat could be tested with chemotherapy and immunotherapy backbones (e.g., pembrolizumab + chemotherapy). Finally, in BRCA1-mutated contexts (e.g., HCC1937), combination with PARP inhibition (e.g., olaparib) is worth evaluating, given the established clinical activity of PARP inhibitors in germline BRCA, HER2-negative breast cancer, or TNBC.

4. Limitations

Despite the promising results, this study has limitations that warrant consideration.
First, the findings are based on in vitro assays without direct evidence of ACC target engagement, such as ACC phosphorylation/activity or downstream metabolites (e.g., malonyl-CoA). In addition, the observed IC50 values (80–93 µM in breast cancer cell lines) are relatively high and require cautious pharmacological interpretation. While micromolar concentrations are commonly used in vitro to interrogate metabolic vulnerabilities, their translational relevance depends on whether comparable exposures can be achieved in vivo at tolerable doses. Finally, 2D monoculture does not capture tumor–microenvironment interactions, immune-related effects, or systemic metabolic consequences that may influence responses to ACC inhibition in in vivo models.
Future studies should therefore include direct target-engagement assays and metabolic profiling (e.g., lipidomic and flux analyses), together with cell-death and cell-cycle markers, to clarify the biological basis of the observed effects. Evaluation in 3D culture systems and in vivo tumor models, coupled with longer-term studies (e.g., metabolic adaptation, acquired resistance, and compensatory lipid uptake) and pharmacokinetic/pharmacodynamic assessment, will be required to determine whether tumor-relevant exposures are achievable and to better define translational relevance.
Overall, this work provides in vitro proof-of-concept evidence that firsocostat reduces viability across multiple breast cancer cell line models, supporting further mechanistic and preclinical evaluation of ACC inhibition strategies.

5. Materials and Methods

5.1. Chemicals and Reagent

Firsocostat (HY-16901) was purchased from MedChemExpress (Monmouth Junction, NJ, USA) (Figure 5).
Human breast cancer cell lines MCF7 (#HTB-22), SK-BR-3 (#HTB-30), MDA-MB-231 (#HTB-26), HCC1937 (#CRL-2336), and the normal-like breast epithelial MCF-10A (#CRL-10317) cell lines were purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA) (Table 1). Dulbecco’s Modified Eagle Medium (DMEM) (Gibco, #31885-023), Advanced DMEM/F-12 (Gibco, Waltham, MA, USA, #12634-010), Roswell Park Memorial Institute (RPMI) 1640 Medium (Gibco, #11875093), Dimethyl sulfoxide (DMSO) (≥99.7% Sigma-Aldrich, #67-68-5), Trypsin–EDTA Solution (Gibco, #R001100), Trypan Blue Stain (Gibco, #15250-061), Dulbecco’s Phosphate-Buffered Saline (PBS) (Gibco, #14190144), L–Glutamine (Gibco, #25030081), Penicillin–Streptomycin Solution (Gibco, #15140130), Fetal Bovine Serum (Gibco, #A3160502), Horse Serum (Gibco, 16050122), Cholera Toxin (Sigma-Aldrich, St. Louis, MO, USA, #C8052), Hydrocortisone (Sigma-Aldrich, #H0888), Human EGF (PeproTech, Cranbury, NJ, USA, #AF-100-15), Human Insulin Recombinant Protein (#RP-10935), and LookOut® Mycoplasma qPCR Detection Kit (Sigma-Aldrich, #MP0035-1KT) were purchased from Thermo Fisher Scientific (Waltham, MA, USA). MTS AQueous CellTiter 96 (#G111A) was purchased from Promega (Madison, WI, USA).

5.2. Cell Cultures and Treatments

Human breast cancer cell lines MCF7, SK-BR-3, and MDA-MB-231 were maintained in complete DMEM, whereas HCC1937 cells were cultured in complete RPMI-1640 medium. All media were supplemented with 10% heat-inactivated fetal bovine serum (FBS), 100 U/mL penicillin, 100 mg/mL streptomycin, and 2 mM of glutamine [42,43]. The non-tumorigenic breast epithelial cell line MCF-10A was grown in advanced DMEM/F-12 medium containing 2.5 mM L-glutamine and 15 mM HEPES, supplemented with 5% horse serum, human epidermal growth factor (hEGF) (20 ng/mL), insulin (10 µg/mL), hydrocortisone (0.5 µg/mL), cholera toxin (0.1 μg/mL), and 1% penicillin–streptomycin [44]. All cell lines were cultured at 37 °C in a humidified incubator with 5% CO2 and routinely harvested with trypsin. Mycoplasma contamination was excluded prior to experimental use.
Firsocostat powder was dissolved in dimethyl sulfoxide (DMSO) to obtain 5 mM stock solutions, which were stored at −20 °C until use. Working solutions were freshly prepared and diluted in cell culture medium, ensuring a final DMSO concentration not exceeding 0.8% (v/v), a condition that did not affect cell growth.
Cells were treated with firsocostat or vehicle (DMSO) as a negative control at approximately 70% cell confluence. All experiments were performed in at least three independent replicates.

5.3. Observation of Morphological Changes

HCC1937, MDA-MB-231, MCF7, SK-BR-3, and MCF-10A cell lines were washed twice with calcium- and magnesium-free PBS, detached by trypsinization, and subsequently seeded into 96-well plates at a density of 7000 cells per well. The cells were then incubated overnight at 37 °C.
The following day, cell cultures were treated for 24 h, 48 h, and 72 h with increasing concentrations (25 µM, 100 µM, 150 µM, 200 µM) of firsocostat. Untreated cells and cells treated with DMSO were used as negative controls. Cellular morphology was monitored using an inverted light microscope (Axio Vert A1, Zeiss, Oberkochen, Germany).

5.4. Trypan Blue Exclusion Assay

At the end of the treatments, cells were collected from the 96-well plates by trypsinization and centrifuged at 1300 rpm for 5min. Cell pellets were gently resuspended in 1 mL of fresh complete medium. Cell viability was determined using the trypan blue exclusion method by mixing equal volumes (10 µL) of cell suspension and 0.4% trypan blue solution. An aliquot of the stained mixture (10 µL) was then loaded onto a Bürker counting chamber and examined under an inverted microscope (Nikon, Tokyo, Japan) at 10× magnification [45]. All measurements were performed in triplicate, and results are expressed as the mean ± standard deviation (SD) from three independent experiments.

5.5. MTS Colorimetric Assay

Cell viability and proliferation capacity were assessed using the colorimetric MTS assay [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium]. HCC1937, MDA-MB-231, MCF7, SK-BR-3, and MCF-10A cell lines were seeded into 96-well plates at a density of 7000 cells per well in 100 µL of medium and incubated at 37 °C and 5% CO2. After overnight attachment, cells were exposed for 24 h, 48 h, and 72 h to increasing concentrations (25 µM, 100 µM, 150 µM, 200 µM) of firsocostat, delivered in 50 µL of medium. Vehicle-treated cells receiving DMSO at the highest concentration used in the treatments were used as negative controls.
At each time point, 20 µL of MTS AQueous CellTiter 96 was added directly to the culture media. Following 2–4 h of incubation at 37 °C, absorbance at 490 nm was recorded using VICTOR Nivo Multimode Microplate Reader (PerkinElmer, Waltham, MA, USA, Life and Analytical Sciences).
Metabolically active cells reduce MTS to a soluble purple-brown formazan product via mitochondrial dehydrogenases, with absorbance values proportional to viable cell number [46]. Dose–response relationships were analyzed by non-linear regression using a sigmoidal dose–response (variable slope) model, and IC50 values were calculated from the fitted curves generated using GraphPad Prism version 10 (GraphPad, La Jolla, CA, USA). Cell viability was expressed as a percentage normalized according to the viability of DMSO-treated controls. All experiments were performed in triplicate, and data are reported as mean (%) ± standard deviation (SD) from three independent experiments.

5.6. Statistical Analysis

Statistical analyses were performed using GraphPad Prism version 10.6.0 (GraphPad Software, Inc., San Diego, CA, USA). Data were reported as mean ± standard deviation (SD) from at least three independent experiments performed in triplicate. Comparisons analyses were performed using an unpaired Student’s t-test, whereas multiple comparisons were analyzed by one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test. According to the p-value, differences were considered statistically significant when the value of * p < 0.05.

6. Conclusions

In this in vitro study, firsocostat reduced MTS signal and cell viability in breast cancer cell lines. Across the malignant breast cancer subtypes examined (luminal A, HER2-positive, and triple-negative models), firsocostat reduced cell viability in a dose- and time-dependent manner. Under the same experimental conditions, MCF-10A cells exhibited higher IC50 values than the tumor lines, indicating a modest differential sensitivity in this in vitro comparator model rather than a defined therapeutic window.
Taken together, these findings are consistent with the emerging concept that lipid metabolism can represent a critical vulnerability in breast cancer and provide in vitro support for further investigating ACC inhibition as a metabolism-targeting approach.
Although firsocostat has been clinically evaluated in metabolic disease settings, this experience does not establish dosing or safety margins in oncology. Future work should therefore validate these findings in more physiologically relevant systems and in vivo tumor models, incorporate direct measures of ACC inhibition and metabolic consequences (including lipidomic profiling), and assess tolerability alongside tumor exposure. Finally, from a translational perspective, combination strategies with established breast cancer therapies could be particularly relevant to determine whether metabolic targeting can enhance treatment response or modulate resistance.
Collectively, the present results provide an in vitro proof-of-concept rationale for further mechanistic and preclinical evaluation of firsocostat in breast cancer models before any translational conclusions are drawn.

Author Contributions

Conceptualization, S.P., M.M., M.S., M.R., E.G. and M.G.; methodology, S.P., M.S. and M.M.; software, S.P. and M.M.; validation, S.P., M.M. and M.S.; formal analysis, M.M. and M.S.; investigation, S.P., M.M., M.S., E.G. and M.G.; resources, S.P., M.M., M.S. and M.R.; data curation, S.P. and M.M.; writing—original draft preparation, S.P., M.M., M.S., E.G. and M.G.; writing—review and editing, S.P., M.M. and M.S.; visualization, S.P., M.M. and M.S.; supervision, M.M. and M.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by 2025 current research project funds (ID: RC-2023-2792851) Italian Ministry of Health, to IRCCS-CROB, Rionero in Vulture, Potenza, Italy.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed at the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
ACCAcetyl-CoA Carboxylase
BCBreast Cancer
BRCABReast CAncer Gene
DMEMDulbecco’s Modified Eagle Medium
DMSODimethyl Sulfoxide
DNLDe Novo Lipogenesis
DSDeviation Standard
EGFEpidermal Growth Factor
EREstrogen Receptor
FAOFatty Acid Oxidation
FBSFetal Bovine Serum
HEPES4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid
HER2Epidermal Growth Factor Receptor
HRHormone Receptor
IC50Half-Maximal Inhibitory Concentration
MTS[3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium]
MUFAMonounsaturated Fatty Acids
NADPHNicotinamide Adenine Dinucleotide Phosphate
NASHNon-alcoholic SteatoHepatitis
PBSPhosphate-Buffered Saline
PRProgesterone Receptor
RPMIRoswell Park Memorial Institute
SCDStearoyl-CoA Desaturase
SFASaturated Fatty Acid
TNBCTriple-Negative Breast Cancer

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Figure 1. Morphological analysis of BC and non-tumorigenic cell lines after exposure to firsocostat. Panels (ad) show representative phase-contrast micrographs (10X magnification) of MCF7 (1), SK-BR-3 (2), MDA-MB-231 (3), HCC1937 (4), and MCF-10A (5) cells after 72 h of treatment with firsocostat at (b) 25, (c) 100, and (d) 200 µM compared with (a) DMSO controls cells.
Figure 1. Morphological analysis of BC and non-tumorigenic cell lines after exposure to firsocostat. Panels (ad) show representative phase-contrast micrographs (10X magnification) of MCF7 (1), SK-BR-3 (2), MDA-MB-231 (3), HCC1937 (4), and MCF-10A (5) cells after 72 h of treatment with firsocostat at (b) 25, (c) 100, and (d) 200 µM compared with (a) DMSO controls cells.
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Figure 2. Effect of firsocostat on BC cell viability assessed by Trypan Blue exclusion assay. Panels (ad) show the dose- and time-dependent effects of firsocostat on BC cell viability: (a) MCF7, (b) SK-BR-3, (c) MDA-MB-231, and (d) HCC1937. Data represent mean values from three independent experiments, illustrating overall growth trends under control and treated conditions after 72 h with firsocostat at 25, 50, and 100 µM compared with DMSO control cells.
Figure 2. Effect of firsocostat on BC cell viability assessed by Trypan Blue exclusion assay. Panels (ad) show the dose- and time-dependent effects of firsocostat on BC cell viability: (a) MCF7, (b) SK-BR-3, (c) MDA-MB-231, and (d) HCC1937. Data represent mean values from three independent experiments, illustrating overall growth trends under control and treated conditions after 72 h with firsocostat at 25, 50, and 100 µM compared with DMSO control cells.
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Figure 3. Cell viability of BC and non-tumorigenic cell lines after firsocostat treatment assessed by MTS assay. Panels (ae) show viability of MCF7 (a), SK-BR-3 (b), MDA-MB-231 (c), HCC1937 (d), and MCF-10A (e) cells following 72 h of exposure to increasing concentrations of firsocostat (25–200 µM). Data are expressed as mean ± SD of three independent experiments, normalized to control (CTRL, 100%). Statistical analysis was performed using one-way ANOVA followed by Tukey’s post hoc test. Statistical significance vs. CTRL is indicated as ns, not significant; p < 0.05 (*); p < 0.01 (**); p < 0.001 (***); p < 0.0001 (****).
Figure 3. Cell viability of BC and non-tumorigenic cell lines after firsocostat treatment assessed by MTS assay. Panels (ae) show viability of MCF7 (a), SK-BR-3 (b), MDA-MB-231 (c), HCC1937 (d), and MCF-10A (e) cells following 72 h of exposure to increasing concentrations of firsocostat (25–200 µM). Data are expressed as mean ± SD of three independent experiments, normalized to control (CTRL, 100%). Statistical analysis was performed using one-way ANOVA followed by Tukey’s post hoc test. Statistical significance vs. CTRL is indicated as ns, not significant; p < 0.05 (*); p < 0.01 (**); p < 0.001 (***); p < 0.0001 (****).
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Figure 4. Dose–response curves of firsocostat in BC and non-tumorigenic cell lines. Panels (ae) depicts nonlinear regression curves based on cell viability assessed by MTS assay after 72 h of treatment with increasing concentrations of firsocostat: MCF7 (a), SK-BR-3 (b), MDA-MB-231 (c), HCC1937 (d), and MCF-10A (e). IC50 values (µM) were calculated using nonlinear regression (4-parameter logistic model) in GraphPad Prism. Data are presented as mean ± SD, normalized to untreated controls.
Figure 4. Dose–response curves of firsocostat in BC and non-tumorigenic cell lines. Panels (ae) depicts nonlinear regression curves based on cell viability assessed by MTS assay after 72 h of treatment with increasing concentrations of firsocostat: MCF7 (a), SK-BR-3 (b), MDA-MB-231 (c), HCC1937 (d), and MCF-10A (e). IC50 values (µM) were calculated using nonlinear regression (4-parameter logistic model) in GraphPad Prism. Data are presented as mean ± SD, normalized to untreated controls.
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Figure 5. Firsocostat chemical structure.
Figure 5. Firsocostat chemical structure.
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Table 1. Summary of non-tumorigenic and breast cancer cell lines and molecular classification.
Table 1. Summary of non-tumorigenic and breast cancer cell lines and molecular classification.
Cell LinesOrganismImmunoprofileCharacteristics
MCF7HumanER+, PR+, HER2Epithelial cell line from mammary gland adenocarcinoma
SK-BR-3HumanER, PR, HER2+ enrichedEpithelial cell line from mammary gland adenocarcinoma
MDA-MB-231HumanER, PR, HER2, EGFR+Epithelial cell line from mammary gland adenocarcinoma
HCC1937HumanER, PR, HER2, BRCA1HoEpithelial cell line from breast ductal carcinoma
MCF-10AHumanER, PR, HER2, EGFR+Non-tumorigenic epithelial cell line from mammary gland
ER (estrogen receptor), PR (progesterone receptor), HER2 (human epidermal growth factor receptor 2), and EGFR (epidermal growth factor receptor).
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MDPI and ACS Style

Picerno, S.; Giglio, E.; Giuseffi, M.; Radino, M.; Sichetti, M.; Mecca, M. Antitumor Activity of the ACC Inhibitor Firsocostat in Breast Cancer Cell Lines: A Proof-of-Concept In Vitro Study. Pharmaceuticals 2026, 19, 201. https://doi.org/10.3390/ph19020201

AMA Style

Picerno S, Giglio E, Giuseffi M, Radino M, Sichetti M, Mecca M. Antitumor Activity of the ACC Inhibitor Firsocostat in Breast Cancer Cell Lines: A Proof-of-Concept In Vitro Study. Pharmaceuticals. 2026; 19(2):201. https://doi.org/10.3390/ph19020201

Chicago/Turabian Style

Picerno, Simona, Eugenia Giglio, Martina Giuseffi, Marcello Radino, Marzia Sichetti, and Marisabel Mecca. 2026. "Antitumor Activity of the ACC Inhibitor Firsocostat in Breast Cancer Cell Lines: A Proof-of-Concept In Vitro Study" Pharmaceuticals 19, no. 2: 201. https://doi.org/10.3390/ph19020201

APA Style

Picerno, S., Giglio, E., Giuseffi, M., Radino, M., Sichetti, M., & Mecca, M. (2026). Antitumor Activity of the ACC Inhibitor Firsocostat in Breast Cancer Cell Lines: A Proof-of-Concept In Vitro Study. Pharmaceuticals, 19(2), 201. https://doi.org/10.3390/ph19020201

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