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<journal-id journal-id-type="publisher-id">Front. Pharmacol.</journal-id>
<journal-title>Frontiers in Pharmacology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Pharmacol.</abbrev-journal-title>
<issn pub-type="epub">1663-9812</issn>
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<publisher-name>Frontiers Media S.A.</publisher-name>
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<article-id pub-id-type="publisher-id">1514811</article-id>
<article-id pub-id-type="doi">10.3389/fphar.2024.1514811</article-id>
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<subj-group subj-group-type="heading">
<subject>Pharmacology</subject>
<subj-group>
<subject>Hypothesis and Theory</subject>
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<title-group>
<article-title>Clinical significance of lipid pathway-targeted therapy in breast cancer</article-title>
<alt-title alt-title-type="left-running-head">Li et al.</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fphar.2024.1514811">10.3389/fphar.2024.1514811</ext-link>
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<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Li</surname>
<given-names>Dan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
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<xref ref-type="aff" rid="aff2">
<sup>2</sup>
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<sup>&#x2020;</sup>
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<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Jin</surname>
<given-names>Pengcheng</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
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<sup>&#x2020;</sup>
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<name>
<surname>Cai</surname>
<given-names>Yiqi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
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<sup>&#x2020;</sup>
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<name>
<surname>Wu</surname>
<given-names>Shijie</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
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<xref ref-type="aff" rid="aff2">
<sup>2</sup>
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<name>
<surname>Guo</surname>
<given-names>Xianan</given-names>
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<sup>1</sup>
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<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Zhiyun</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
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<sup>2</sup>
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<surname>Liu</surname>
<given-names>Kexin</given-names>
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<surname>Li</surname>
<given-names>Panni</given-names>
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<contrib contrib-type="author" corresp="yes">
<name>
<surname>Hu</surname>
<given-names>Yue</given-names>
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<sup>1</sup>
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<contrib contrib-type="author" corresp="yes">
<name>
<surname>Zhou</surname>
<given-names>Yunxiang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
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<xref ref-type="aff" rid="aff2">
<sup>2</sup>
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<aff id="aff1">
<sup>1</sup>
<institution>Department of Breast Surgery and Oncology</institution>, <institution>The Second Affiliated Hospital</institution>, <institution>Zhejiang University School of Medicine</institution>, <addr-line>Hangzhou</addr-line>, <addr-line>Zhejiang</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Cancer Institute (Key Laboratory of Cancer Prevention and Intervention</institution>, <institution>China National Ministry of Education)</institution>, <institution>The Second Affiliated Hospital</institution>, <institution>Zhejiang University School of Medicine</institution>, <addr-line>Hangzhou</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Surgical Oncology, Linhai Branch, The Second Affiliated Hospital, Zhejiang University School of Medicine</institution>, <addr-line>Taizhou</addr-line>, <addr-line>Zhejiang</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2822061/overview">Zhendong Shi</ext-link>, Tianjin Medical University Cancer Institute and Hospital, China</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1700149/overview">Wei Yang</ext-link>, Stony Brook University, United States</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2419169/overview">Peiguo Shi</ext-link>, Columbia University, United States</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Yunxiang Zhou, <email>yxzhou@zju.edu.cn</email>; Yue Hu, <email>huyuezju@zju.edu.cn</email>
</corresp>
<fn fn-type="equal" id="fn001">
<label>
<sup>&#x2020;</sup>
</label>
<p>These authors have contributed equally to this work</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>06</day>
<month>01</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>15</volume>
<elocation-id>1514811</elocation-id>
<history>
<date date-type="received">
<day>21</day>
<month>10</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>17</day>
<month>12</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Li, Jin, Cai, Wu, Guo, Zhang, Liu, Li, Hu and Zhou.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Li, Jin, Cai, Wu, Guo, Zhang, Liu, Li, Hu and Zhou</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Globally, breast cancer represents the most common cancer and the primary cause of death by cancer in women. Lipids are crucial in human physiology, serving as vital energy reserves, structural elements of biological membranes, and essential signaling molecules. The metabolic reprogramming of lipid pathways has emerged as a critical factor in breast cancer progression, drug resistance, and patient prognosis. In this study, we delve into the clinical implications of lipid pathway-targeted therapy in breast cancer. We highlight key enzymes and potential therapeutic targets involved in lipid metabolism reprogramming, and their associations with cancer progression and treatment outcomes. Furthermore, we detail the clinical trials exploring the anticancer and cancer chemopreventive activity of therapies targeting these molecules. However, the clinical efficacy of these therapies remains controversial, highlighting the urgent need for predictive biomarkers to identify patient subpopulations likely to benefit from such treatment. We propose the Selective Lipid Metabolism Therapy Benefit Hypothesis, emphasizing the importance of personalized medicine in optimizing lipid pathway-targeted therapy for breast cancer patients.</p>
</abstract>
<kwd-group>
<kwd>breast cancer</kwd>
<kwd>lipid metabolism reprogramming</kwd>
<kwd>clinical trial</kwd>
<kwd>targeted therapy</kwd>
<kwd>predictive biomarkers</kwd>
<kwd>hypothesis</kwd>
</kwd-group>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Pharmacology of Anti-Cancer Drugs</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1">
<title>1 Introduction</title>
<p>Globally, breast cancer represents the most common cancer and the primary cause of death by cancer in women (<xref ref-type="bibr" rid="B15">Bray et al., 2024</xref>). China has 357,200 new cases of breast cancer each year, posing a serious threat to the lives and health of a large number of women (<xref ref-type="bibr" rid="B157">Zheng et al., 2024</xref>). In spite of the progress made in diagnostic techniques and therapeutic interventions, a considerable proportion of patients encounter relapse subsequent to their initial course of treatment, resulting in diminished overall survival (OS) rates and a compromised quality of life (<xref ref-type="bibr" rid="B37">DeSantis et al., 2019</xref>; <xref ref-type="bibr" rid="B158">Zhou et al., 2023</xref>; <xref ref-type="bibr" rid="B54">Garcia-Martinez et al., 2021</xref>). This notable public health challenge underscores the urgency to explore further into the intricacies of breast cancer development and actively seek out promising therapeutic avenues.</p>
<p>Lipids empower diverse cellular life activities, constituting one of the three key energy sources. Furthermore, lipids are crucial in the constitution of cell membranes and function as pivotal signaling molecules (<xref ref-type="bibr" rid="B148">Xiao et al., 2024</xref>). Recent studies have revealed alterations in lipid metabolism within tumor cells and microenvironment, which furnish a robust substrate for tumor cell proliferation during therapy and drive the development of therapy resistance (<xref ref-type="bibr" rid="B89">Ligorio et al., 2021</xref>; <xref ref-type="bibr" rid="B27">Cheng et al., 2018</xref>; <xref ref-type="bibr" rid="B10">Bian et al., 2021</xref>; <xref ref-type="bibr" rid="B93">Liu et al., 2024</xref>). Correspondingly, the significance of lipid metabolism reprogramming in breast cancer is gradually coming to light (<xref ref-type="bibr" rid="B160">Zipinotti Dos Santos et al., 2023</xref>; <xref ref-type="bibr" rid="B106">Nelson et al., 2014</xref>; <xref ref-type="bibr" rid="B62">Guo et al., 2020</xref>; <xref ref-type="bibr" rid="B4">Bacci et al., 2021</xref>; <xref ref-type="bibr" rid="B144">Wang et al., 2024</xref>). Increasing evidence suggests that lipid remodeling plays a vital role in conferring drug resistance to breast cancer cells via mechanisms involving ferroptosis, immune escape, endoplasmic reticulum stress, and stemness (<xref ref-type="bibr" rid="B153">Zhang et al., 2019</xref>; <xref ref-type="bibr" rid="B66">Havas et al., 2017</xref>; <xref ref-type="bibr" rid="B145">Wang et al., 2018</xref>; <xref ref-type="bibr" rid="B95">Luis et al., 2021</xref>). Consequently, targeting lipid metabolism emerges as a promising therapeutic avenue to tackle resistance to conventional treatments. Notably, lipids occupy pivotal roles in maintaining normal physiological functions (<xref ref-type="bibr" rid="B115">Petrenko et al., 2023</xref>). Therefore, prior to contemplating systemic therapies aimed at lipid metabolism as therapeutic modalities for breast cancer, it is imperative to achieve a thorough comprehension of lipid functions within both cancer cells and normal cells, as well as their interplay.</p>
<p>In this study, we present an overview of the physiological processes underlying lipid metabolism and its remodeling in breast cancer. We have also summarized potential therapeutic targets within the lipid metabolism remodeling. Furthermore, we offer a detailed assessment of the evidence derived from both completed and ongoing clinical trials, encompassing those targeting lipid metabolism directly for anticancer effects, those utilizing lipid metabolism modulation as adjunctive therapy to mitigate the toxicity of traditional treatments, and those employing it as a prophylactic measure to prevent breast cancer occurrence. Despite the variability observed in the findings, specific breast cancer patients may indeed benefit from therapies that regulate the lipid pathway (<xref ref-type="bibr" rid="B126">Serageldin et al., 2024</xref>; <xref ref-type="bibr" rid="B43">El-Khayat et al., 2021</xref>; <xref ref-type="bibr" rid="B77">Kamal et al., 2024</xref>; <xref ref-type="bibr" rid="B151">Yulian et al., 2021</xref>; <xref ref-type="bibr" rid="B38">Dewidar et al., 2022</xref>; <xref ref-type="bibr" rid="B152">Yulian et al., 2023</xref>; <xref ref-type="bibr" rid="B127">Serageldin et al., 2023</xref>). Consequently, we propose the Selective Lipid Metabolism Therapy Benefit Hypothesis, suggesting that lipid pathway-targeted therapy may confer benefits to a selected group of patients. This hypothesis can aid in better understanding the role of lipid metabolism reprogramming in breast cancer, facilitating the discovery of more stable biomarkers that can predict treatment response, and thereby enabling effective clinical translation.</p>
</sec>
<sec id="s2">
<title>2 Physiological processes and key molecules of lipid metabolism</title>
<p>Lipids constitute one of the three key energy sources for cells, vital components of cell membranes, and essential signaling molecules, holding a paramount position as fundamental constituents within the physiological machinery of the body (<xref ref-type="bibr" rid="B148">Xiao et al., 2024</xref>). Over a thousand distinct lipid types have been identified within living cells, such as fatty acids (FAs), cholesterol, phospholipids, and others (<xref ref-type="bibr" rid="B30">Corradi et al., 2019</xref>). Understanding the physiological processes and key molecules of lipid metabolism in normal cells is crucial to grasping how it impacts the behavior of malignant cells and their therapeutic potential as targets (<xref ref-type="fig" rid="F1">Figure 1</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Lipid metabolism pathways and promising targets for breast cancer treatment. This schematic diagram illustrates the key processes and molecular involved in lipid metabolism, including fatty acid (FA) uptake, <italic>De novo</italic> lipogenesis (DNL), FA oxidation (FAO) and cholesterol biosynthesis. Extracellular triglycerides are hydrolyzed by lipoprotein lipase (LPL), releasing free FAs for cellular uptake via membrane-associated proteins such as CD36, fatty acid transport protein (FATP), and plasma membrane fatty acid-binding protein (FABP). Intracellularly, acetyl-CoA generated from FAs or glucose enters the tricarboxylic acid (TCA) cycle to produce energy in mitochondria. Acetyl-CoA also serve as a substrate for DNL. This metabolic pathway leads to the synthesis of malonyl-CoA and, ultimately, palmitate, which can subsequently undergo elongation and desaturation processes to yield a diverse array of FAs. These FAs can be modified to form diverse lipids including diacylglycerols (DAGs) and triacylglycerols (TAGs). TAGs are stored in lipid droplets, which regulate lipid storage and release under metabolic demands. Additionally, the cholesterol biosynthesis pathway, which is initiated by acetyl-CoA, proceeds through the formation of intermediate compounds such as farnesyl pyrophosphate (FPP) and squalene, eventually leading to the production of cholesterol. Cholesterol contributes to membrane fluidity and steroid hormone synthesis, with excess cholesterol stored as cholesterol esters in lipid droplets. Importantly, these metabolic pathways altered in breast cancer cells, which is likely associated with cancer progression. Promising therapeutic targets are marked with orange lightning symbols. Created in <ext-link ext-link-type="uri" xlink:href="https://BioRender.com">https://BioRender.com</ext-link>.</p>
</caption>
<graphic xlink:href="fphar-15-1514811-g001.tif"/>
</fig>
<p>The essential details of the biochemical processes underlying lipid metabolism have been comprehensively discussed elsewhere (<xref ref-type="bibr" rid="B150">Yu et al., 2021</xref>). Briefly, FA uptake is facilitated by lipoprotein lipase (LPL)-mediated extracellular hydrolysis of triglycerides into free FAs and glycerol, with CD36, among other membrane-associated proteins, playing a pivotal role in cellular FA transport (<xref ref-type="bibr" rid="B89">Ligorio et al., 2021</xref>; <xref ref-type="bibr" rid="B1">Abumrad et al., 2021</xref>; <xref ref-type="bibr" rid="B123">Samovski et al., 2023</xref>). <italic>De novo</italic> lipogenesis (DNL, i.e., <italic>de novo</italic> FA synthesis) occurs in the cytoplasm, utilizing acetyl-coenzyme A (acetyl-CoA) as the base stock. Key enzymes in this process include adenosine triphosphate (ATP)-citrate lyase (ACLY), acetyl-CoA carboxylase (ACC), and FA synthase (FASN), which catalyze the formation of cytosolic acetyl-CoA, malonyl-CoA, and long-chain saturated FAs (primarily palmitate), respectively (<xref ref-type="bibr" rid="B139">Vasseur and Guillaumond, 2022</xref>; <xref ref-type="bibr" rid="B31">Currie et al., 2013</xref>; <xref ref-type="bibr" rid="B100">Martin-Perez et al., 2022</xref>). FAs are able to undergo conversion into diverse types of lipids (<xref ref-type="bibr" rid="B160">Zipinotti Dos Santos et al., 2023</xref>; <xref ref-type="bibr" rid="B42">Dyall et al., 2022</xref>). For instance, FAs can be further metabolized to produce various glycerophospholipids, e.g., phosphatidylserine (PS), which are essential for membrane structure and function (<xref ref-type="bibr" rid="B138">Vance, 2015</xref>; <xref ref-type="bibr" rid="B5">Baenke et al., 2013</xref>; <xref ref-type="bibr" rid="B8">Baxter et al., 2015</xref>; <xref ref-type="bibr" rid="B81">Kopecka et al., 2020</xref>). FA oxidation (FAO) is a critical energy-producing process that occurs in four stages: FA activation, mitochondrial transfer, &#x3b2;-oxidation yielding acetyl-CoA, and acetyl-CoA entering the tricarboxylic acid (TCA) cycle. Enzymes such as acyl-CoA synthetase (ACS) and carnitine palmitoyltransferase (CPT) 1 take an active part in this process (<xref ref-type="bibr" rid="B78">Kemp et al., 2024</xref>; <xref ref-type="bibr" rid="B87">Li et al., 2017</xref>; <xref ref-type="bibr" rid="B80">Knottnerus et al., 2018</xref>; <xref ref-type="bibr" rid="B19">Carracedo et al., 2013</xref>).</p>
<p>Cholesterol stands out as another vital lipid, crucial for cellular function, impacting membrane fluidity, signal transduction, and steroid hormone synthesis (<xref ref-type="bibr" rid="B96">Luo et al., 2020</xref>). Cholesterol can be produced via the endogenous mevalonate (MVA) pathway or obtained extracellularly through transmembrane receptor proteins, primarily low density lipoprotein receptor (LDLR). Cholesterol biosynthesis involves a series of essential enzymes, including 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase (HMGCR), which serves as the rate-limiting enzyme in the MVA pathway, as well as squalene synthase (SQS), squalene epoxidase (SQLE), and lanosterol synthase (LSS) (<xref ref-type="bibr" rid="B139">Vasseur and Guillaumond, 2022</xref>; <xref ref-type="bibr" rid="B96">Luo et al., 2020</xref>). Excessive cholesterol is metabolized either into its primary metabolite, 27-hydroxycholesterol (27HC), or into cholesterol ester, which is then stored in lipid droplets (<xref ref-type="bibr" rid="B160">Zipinotti Dos Santos et al., 2023</xref>). Lipid droplets, composed of FAs, sterol esters, and triacylglycerols, encapsulated by a cholesterol and phospholipid monolayer, function as crucial subcellular organelles managing cellular lipid metabolism. Enzymes such as adipose triglyceride lipase (ATGL) regulate lipid catabolism on their surface (<xref ref-type="bibr" rid="B150">Yu et al., 2021</xref>; <xref ref-type="bibr" rid="B47">Farese and Walther, 2009</xref>; <xref ref-type="bibr" rid="B109">Olzmann and Carvalho, 2019</xref>; <xref ref-type="bibr" rid="B133">Tauchi-Sato et al., 2002</xref>).</p>
</sec>
<sec id="s3">
<title>3 Potential and obstacles in targeting lipid remodeling in breast cancer</title>
<p>The rapid proliferation of cancer cells heightens the necessity for local oxygen and nutrients, yet inadequately structured blood vessels fail to meet this demand. Consequently, the tumor microenvironment becomes acidic, hypoxic, and glucose-deprived. This triggers the activation and utilization of lipids as a primary energy source and key regulators within tumor cells, disrupting various signaling pathways and immune activities, while fostering tumor cell growth, proliferation, and migration (<xref ref-type="bibr" rid="B160">Zipinotti Dos Santos et al., 2023</xref>; <xref ref-type="bibr" rid="B150">Yu et al., 2021</xref>). Given that the landscape of lipid metabolism in breast cancer has been extensively covered in recent reviews (<xref ref-type="bibr" rid="B148">Xiao et al., 2024</xref>; <xref ref-type="bibr" rid="B144">Wang et al., 2024</xref>), our focus herein is primarily on the potential therapeutic targets within the lipid remodeling (<xref ref-type="fig" rid="F2">Figure 2</xref>).</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Potential therapeutic targets within lipid remodeling pathways in breast cancer: mechanisms, roles, and strategies. This figure elucidates diverse therapeutic targets in lipid remodeling, underlying tumorigenesis and progression (top), and underscores their significance in breast cancer, presenting potential strategies to leverage these pathways for therapeutic advantage (bottom).</p>
</caption>
<graphic xlink:href="fphar-15-1514811-g002.tif"/>
</fig>
<sec id="s3-1">
<title>3.1 Fatty acid uptake</title>
<p>The overexpression of CD36 in cancer cells has reportedly been to enhance the transcription of genes associated with metastasis formation, facilitating the spread of cancer to lymph nodes in mice (<xref ref-type="bibr" rid="B112">Pascual et al., 2017</xref>). Feng and colleagues found that CD36 acted as a key player in resistance to lapatinib in human epidermal growth factor receptor 2 (HER2)-positive breast cancer cells, and inhibiting CD36 restored sensitivity to lapatinib and triggered apoptosis in those lapatinib-resistant cells (<xref ref-type="bibr" rid="B52">Feng et al., 2019</xref>). Moreover, elevated CD36 levels were found to be correlated with unfavorable prognoses (<xref ref-type="bibr" rid="B112">Pascual et al., 2017</xref>; <xref ref-type="bibr" rid="B82">Koundouros and Poulogiannis, 2020</xref>). Correspondingly, CD36 may provide a promising therapeutic target (<xref ref-type="bibr" rid="B155">Zhao J. et al., 2017</xref>). Besides, literature showed that LPL had the potential to accelerate the growth of tumor cells (<xref ref-type="bibr" rid="B83">Kuemmerle et al., 2011</xref>) However, no inhibitors targeting enzymes implicated in FA uptake have been introduced into clinical practice yet, restricting the translational potential of these findings.</p>
</sec>
<sec id="s3-2">
<title>3.2 Fatty acid synthesis</title>
<p>High expression of ACLY in breast cancer tissues is conversely proportional to disease stage and prognosis (<xref ref-type="bibr" rid="B148">Xiao et al., 2024</xref>; <xref ref-type="bibr" rid="B25">Chen et al., 2020</xref>). Furthermore, ACLY is implicated in the resistance to tamoxifen, palbociclib, and paclitaxel in breast cancer, whereas ACLY inhibition can re-establish sensitivity to these drugs and halts tumor progression (<xref ref-type="bibr" rid="B25">Chen et al., 2020</xref>; <xref ref-type="bibr" rid="B74">Ismail et al., 2022</xref>; <xref ref-type="bibr" rid="B73">Ismail et al., 2020</xref>; <xref ref-type="bibr" rid="B141">Velez et al., 2023</xref>). Besides cleavage of citrate by ACLY, the supply of cytosolic acetyl-CoA pool can be achieved via the conjugation of acetate with CoA under hypoxia and lipid-depleted conditions, catalyzed by acetyl-CoA synthetase 2 (ACSS2) (<xref ref-type="bibr" rid="B125">Schug et al., 2015</xref>). Hence, ACSS2 is essential for tumor growth under metabolic stress, and its expression can predict tumor staging and patient prognosis (<xref ref-type="bibr" rid="B125">Schug et al., 2015</xref>; <xref ref-type="bibr" rid="B90">Ling et al., 2022</xref>). As the rate-limiting enzyme of lipid biosynthesis, ACC definitely holds a pivotal position in breast cancer cell development (<xref ref-type="bibr" rid="B17">Brunet et al., 2008</xref>; <xref ref-type="bibr" rid="B23">Chaj&#xe8;s et al., 2006</xref>), while silencing ACC hinders cell proliferation and triggers apoptosis in breast cancer cell lines (<xref ref-type="bibr" rid="B23">Chaj&#xe8;s et al., 2006</xref>). Accordingly, ACC emerges as a potential target for suppressing FA biosynthesis in human cancers with pharmacological inhibitors exhibiting encouraging antitumor effects (<xref ref-type="bibr" rid="B136">Tong, 2005</xref>; <xref ref-type="bibr" rid="B86">Lally et al., 2019</xref>). As another crucial enzyme involved in DNL, FASN also contributes to breast cancer initiation, progression, and treatment resistance (<xref ref-type="bibr" rid="B102">Menendez and Lupu, 2017</xref>). Mechanistically, besides supplying energy to cancer cells, FASN exerts its pro-tumor effects through its positive feedback loop with HER2 (<xref ref-type="bibr" rid="B103">Menendez et al., 2021</xref>; <xref ref-type="bibr" rid="B84">Kumar-Sinha et al., 2003</xref>; <xref ref-type="bibr" rid="B140">Vazquez-Martin et al., 2008</xref>) as well as its interaction with nuclear factor-&#x3ba;B (NF-&#x3ba;B) (<xref ref-type="bibr" rid="B91">Liu et al., 2013</xref>; <xref ref-type="bibr" rid="B146">Wu et al., 2016</xref>), which affect downstream signaling pathways and cellular processes critical for cancer cell survival and resistance to treatment. Targeting FASN may therefore hold promise to inhibit tumor cell growth and enhance the vulnerability of breast cancer cells to traditional anticancer treatments (<xref ref-type="bibr" rid="B102">Menendez and Lupu, 2017</xref>).</p>
</sec>
<sec id="s3-3">
<title>3.3 Fatty acid oxidation</title>
<p>ACSs are categorized into five groups based on the length of the FA chain they act upon. Among them, long-chain ACSs (ACSLs) are accountable for the catalyzation of intracellular free long-chain FAs, which are then transported by transporter proteins such as CD36 (<xref ref-type="bibr" rid="B122">Rossi Sebastiano and Konstantinidou, 2019</xref>). Among the ACSL family, ACSL4 has been widely researched and linked to tumor progression. ACSL4 exhibits an abnormal upregulation in triple-negative breast cancer (TNBC) cells and is correlated with unfavorable prognosis and metastasis in TNBC patients (<xref ref-type="bibr" rid="B119">Qiu et al., 2024</xref>). Preclinical studies have revealed that ACSL4 can be activated in drug-resistant breast cancer cells (<xref ref-type="bibr" rid="B88">Li et al., 2022</xref>). In turn, this activation can impede the apoptotic pathway and enhance the mTOR pathway, thereby promoting cancer growth and conferring resistance to chemotherapy, endocrinotherapy, and radiotherapy (<xref ref-type="bibr" rid="B88">Li et al., 2022</xref>; <xref ref-type="bibr" rid="B147">Wu et al., 2013</xref>; <xref ref-type="bibr" rid="B110">Orlando et al., 2019</xref>). Consequently, targeting ACSL4 presents a novel therapeutic strategy for breast cancer, while transferring the basic scientific discoveries into clinical practice poses a significant hurdle. As the rate-limiting enzyme in FAO, CPT1 serves as a key factor in the initiation, progression, and migration of cancer cells (<xref ref-type="bibr" rid="B143">Wang et al., 2021</xref>). This enzyme not only fulfills the energy demands of cancer cells by facilitating FAO but also exerts its influence through various signaling pathways, cytokines, or microRNAs (<xref ref-type="bibr" rid="B143">Wang et al., 2021</xref>). Elevated levels of CPT1 expression have been detected in recurrent breast cancer cases, which are associated with unfavorable patient outcomes (<xref ref-type="bibr" rid="B65">Han et al., 2019</xref>). Moreover, serum CPT1 levels reliably signify the disease progression in breast cancer patients (<xref ref-type="bibr" rid="B131">Tan et al., 2021</xref>), underscoring its potential utility as a biomarker in breast cancer management. Accumulating evidence suggests that a key mechanism underlying CPT1&#x2019;s role in fostering treatment resistance is its ability to sustain stemness in stem cells (<xref ref-type="bibr" rid="B145">Wang et al., 2018</xref>; <xref ref-type="bibr" rid="B65">Han et al., 2019</xref>; <xref ref-type="bibr" rid="B68">He et al., 2019</xref>; <xref ref-type="bibr" rid="B128">Shim et al., 2022</xref>; <xref ref-type="bibr" rid="B26">Chen et al., 2023</xref>). Preclinical studies have demonstrated that etomoxir (a CPT1 inhibitor) can re-sensitize multiple cancers, including breast cancer, to conventional chemotherapy and radiotherapy (<xref ref-type="bibr" rid="B65">Han et al., 2019</xref>; <xref ref-type="bibr" rid="B128">Shim et al., 2022</xref>; <xref ref-type="bibr" rid="B26">Chen et al., 2023</xref>; <xref ref-type="bibr" rid="B130">Tan et al., 2018</xref>; <xref ref-type="bibr" rid="B118">Pucer et al., 2013</xref>). The mechanism by which CPT2 mediates radiotherapy resistance in breast cancer cells is analogous to that of CPT1 (<xref ref-type="bibr" rid="B65">Han et al., 2019</xref>). Unfortunately, despite their potential, none of the FAO-related therapeutic targets have been successfully translated into clinical practice for breast cancer treatment.</p>
</sec>
<sec id="s3-4">
<title>3.4 Cholesterol synthesis</title>
<p>In cancer patients, there is an increase in endogenous cholesterol synthesis, coupled with elevated circulating cholesterol levels (<xref ref-type="bibr" rid="B81">Kopecka et al., 2020</xref>). The heightened cholesterol levels can augment downstream oncogenic pathway signaling, including Hedgehog- and mammalian target of rapamycin complex 1 (mTORC1)-dependent pathways (<xref ref-type="bibr" rid="B40">Ding et al., 2019</xref>). Furthermore, by exerting its influence on membrane fluidity, lipid raft function, and transcriptional processes, cholesterol can also regulate the activity of drug efflux transporters, thereby contributing to drug resistance (<xref ref-type="bibr" rid="B81">Kopecka et al., 2020</xref>; <xref ref-type="bibr" rid="B40">Ding et al., 2019</xref>; <xref ref-type="bibr" rid="B22">Celestino et al., 2015</xref>). The overexpression of MVA pathway-related molecules was observed in breast cancer patients with a worse prognosis (<xref ref-type="bibr" rid="B85">Kuzu et al., 2016</xref>; <xref ref-type="bibr" rid="B16">Brown et al., 2016</xref>; <xref ref-type="bibr" rid="B28">Clendening et al., 2010</xref>; <xref ref-type="bibr" rid="B79">Kim et al., 2019</xref>; <xref ref-type="bibr" rid="B11">Bjarnadottir et al., 2020</xref>). Additionally, HMGCR may possess oncogenic properties, and perturbations within the MVA pathway could facilitate cellular transformation (<xref ref-type="bibr" rid="B28">Clendening et al., 2010</xref>). Research has indicated that HMGCR and SQLE represent compelling targets for cancer treatment, albeit clinical studies on the latter are still lacking (<xref ref-type="bibr" rid="B50">Feltrin et al., 2020</xref>).</p>
</sec>
<sec id="s3-5">
<title>3.5 Phospholipids</title>
<p>Glycerophospholipids hold a critical position in the initiation and progression of cancer, and they mediate the resistance of cancer cells to chemotherapy via various mechanisms, encompassing modulating the composition of cellular membranes, influencing FA metabolism, acting as second messengers to activate DNA repair mechanisms, and upregulating drug efflux transporters (<xref ref-type="bibr" rid="B81">Kopecka et al., 2020</xref>). PS is a phospholipid confined to the inner leaflet of the cell membrane. In solid tumors, hypoxia and other pathophysiological stressors induce the externalization of PS, where it migrates to the outer leaflet (<xref ref-type="bibr" rid="B56">Gerber et al., 2018</xref>). The interaction between PS and its receptors critically regulates immuno-inflammatory responses, fostering an immune-evasive tumor microenvironment. Additionally, PS-receptor interaction mediates chemoresistance in cancer cells by the upregulation of drug efflux transporters and the activation of signaling cascades, e.g., phosphatidylinositol 3-kinase (PI3K)/Akt pathways (<xref ref-type="bibr" rid="B159">Zhou et al., 2020</xref>). These findings indicate the promising potential of PS-targeted therapy in combating tumor invasion and chemoresistance.</p>
</sec>
<sec id="s3-6">
<title>3.6 Obstacles in targeting lipid remodeling</title>
<p>As mentioned above, despite the existence of numerous promising targets, their successful clinical translation remains elusive. Presently, the therapeutic strategies targeting lipid metabolism in breast cancer face several obstacles that require attention. Firstly, the inhibition of lipid metabolic pathways may raise safety concerns due to their potential to induce detrimental effects on normal cells, thereby limiting the development of safe and specific inhibitors (<xref ref-type="bibr" rid="B89">Ligorio et al., 2021</xref>). Secondly, the translation of preclinical findings into a clinical setting poses significant challenges, as experiment conditions utilized in preclinical studies may employ supra-physiological concentrations of lipid-modulating drugs (<xref ref-type="bibr" rid="B57">Goodwin et al., 2022</xref>). Thirdly, the metabolic adaptability of cancer cells may undermine the effectiveness of inhibiting a single enzyme or pathway alone in sustaining long-term tumor suppression (<xref ref-type="bibr" rid="B89">Ligorio et al., 2021</xref>; <xref ref-type="bibr" rid="B51">Fendt et al., 2020</xref>). Notwithstanding the challenges, some therapeutic strategies targeting lipid metabolism have still progressed into clinical trials, which will be exhaustively presented in the following section.</p>
</sec>
</sec>
<sec id="s4">
<title>4 Clinical trials concerning regulation of lipid metabolism in patients with breast cancer</title>
<sec id="s4-1">
<title>4.1 Anticancer activity</title>
<p>Despite strong evidence supporting FASN as a promising target for breast cancer therapy, only a few compounds inhibiting FASN have entered clinical studies to date. TVB-2640 is a small molecule that stands as the first highly selective human FASN inhibitor to progress into clinical trials (<xref ref-type="bibr" rid="B46">Falchook et al., 2021</xref>). A phase I clinical trial have confirmed the biological activities and safety of the TVB-2640 in solid tumors, including breast cancer (<xref ref-type="bibr" rid="B46">Falchook et al., 2021</xref>). Accordingly, an ongoing Phase II clinical study (NCT03179904) will further investigate the efficacy and safety profile of TVB-2640 administered in conjunction with trastuzumab plus paclitaxel or endocrine therapy in the management of advanced HER2-positive breast cancer (<xref ref-type="table" rid="T1">Table 1</xref>). Besides the FASN inhibitor TVB-2640, several other clinical medications or plant-derived polyphenols have been demonstrated to block FASN, among other targets, and enhance the effectiveness of numerous traditional therapies. Examples include omeprazole (<xref ref-type="bibr" rid="B124">Sardesai et al., 2021</xref>), conjugated linoleic acid (CLA) (<xref ref-type="bibr" rid="B101">McGowan et al., 2013</xref>), and epigallocatechin-3-gallate (EGCG) (<xref ref-type="bibr" rid="B18">Brusselmans et al., 2003</xref>), which have undergone corresponding clinical trials. Notably, research results for the former two have been published (<xref ref-type="table" rid="T2">Table 2</xref>). Consequently, the combination of omeprazole and neoadjuvant chemotherapy has yielded a promising pathological complete response (pCR) rate (<xref ref-type="bibr" rid="B124">Sardesai et al., 2021</xref>), and preoperative administration of CLA for ten to 28&#xa0;days resulted in significant reductions in Spot 14 and Ki67 levels (<xref ref-type="bibr" rid="B101">McGowan et al., 2013</xref>).</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Completed (unpublished) and ongoing trials of lipid pathway-targeted therapy in breast cancer (BC).</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Target</th>
<th align="left">Inhibitor</th>
<th align="left">Trial number</th>
<th align="left">Phase</th>
<th align="left">Enrollment (actual)</th>
<th align="left">Setting</th>
<th align="left">Regimen</th>
<th align="left">Primary endpoint</th>
<th align="left">Status</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="3" align="left">FASN</td>
<td align="left">TVB-2640</td>
<td align="left">NCT03179904</td>
<td align="left">II</td>
<td align="left">19</td>
<td align="left">Taxane and trastuzumab-resistant, HER2&#x2b; ABC</td>
<td align="left">TVB-2640 &#x2b; trastuzumab &#x2b; paclitaxel/endocrine therapy</td>
<td align="left">ORR</td>
<td align="left">Ongoing</td>
</tr>
<tr>
<td rowspan="2" align="left">EGCG</td>
<td rowspan="2" align="left">NCT05680662</td>
<td rowspan="2" align="left">I</td>
<td rowspan="2" align="left">200</td>
<td rowspan="2" align="left">Any type of BC</td>
<td align="left">Arm A: quercetin &#x2b; zinc &#x2b; EGCG &#x2b; metformin &#x2b; chemotherapy</td>
<td rowspan="2" align="left">iDFS</td>
<td rowspan="2" align="left">Ongoing</td>
</tr>
<tr>
<td align="left">Arm B: chemotherapy</td>
</tr>
<tr>
<td rowspan="23" align="left">HMGCR</td>
<td rowspan="17" align="left">Atorvastatin</td>
<td rowspan="4" align="left">NCT03872388</td>
<td rowspan="4" align="left">II</td>
<td rowspan="4" align="left">6</td>
<td rowspan="4" align="left">Stage IIb-III TNBC who did not achieve a pCR after receiving NACT</td>
<td align="left">Group A: atorvastatin</td>
<td rowspan="4" align="left">The proportion of CTC-negative</td>
<td rowspan="4" align="left">Terminated</td>
</tr>
<tr>
<td align="left">Group B</td>
</tr>
<tr>
<td align="left">Arm a: capecitabine</td>
</tr>
<tr>
<td align="left">Arm b: none</td>
</tr>
<tr>
<td align="left">NCT01980823</td>
<td align="left">I</td>
<td align="left" style="color:#171716">23</td>
<td align="left">EBC, WOO</td>
<td align="left">Atorvastatin &#x2b; metformin</td>
<td align="left">Ki67</td>
<td align="left">Completed</td>
</tr>
<tr>
<td rowspan="2" align="left">NCT04601116</td>
<td rowspan="2" align="left">III</td>
<td rowspan="2" align="left" style="color:#171716">3,360</td>
<td rowspan="2" align="left">ER &#x2b; EBC</td>
<td align="left">Arm A: (neo)adjuvant therapy &#x2b; atorvastatin</td>
<td rowspan="2" align="left">iDFS</td>
<td rowspan="2" align="left">Ongoing</td>
</tr>
<tr>
<td align="left">Arm B: (neo)adjuvant therapy &#x2b; placebo</td>
</tr>
<tr>
<td align="left">NCT02416427</td>
<td align="left">II</td>
<td align="left" style="color:#171716">78</td>
<td align="left">TAZ-expressing EBC, WOO</td>
<td align="left">Atorvastatin</td>
<td align="left">Ki67</td>
<td align="left">Unknown</td>
</tr>
<tr>
<td rowspan="2" align="left">NCT05103644</td>
<td rowspan="2" align="left">II/III</td>
<td rowspan="2" align="left" style="color:#171716">60</td>
<td rowspan="2" align="left">HER2- BC</td>
<td align="left">Arm A: atorvastatin</td>
<td rowspan="2" align="left">Ki67, TAZ expression, and cardiac markers</td>
<td rowspan="2" align="left">Ongoing</td>
</tr>
<tr>
<td align="left">Arm B: placebo</td>
</tr>
<tr>
<td rowspan="2" align="left">NCT02958852</td>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left" style="color:#171716">126</td>
<td rowspan="2" align="left">ER&#x2b;/HER2- ABC</td>
<td align="left">Arm A: letrozole &#x2b; atorvastatin</td>
<td rowspan="2" align="left">CBR</td>
<td rowspan="2" align="left">Unknown</td>
</tr>
<tr>
<td align="left">Arm B: letrozole<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</td>
</tr>
<tr>
<td rowspan="3" align="left">NCT05507398</td>
<td rowspan="3" align="left">&#x2163;</td>
<td rowspan="3" align="left" style="color:#171716">100</td>
<td rowspan="3" align="left">Non-metastatic BC</td>
<td align="left">Arm A: atorvastatin &#x2b; NACT</td>
<td rowspan="3" align="left">ORR and pCR</td>
<td rowspan="3" align="left">Unknown</td>
</tr>
<tr>
<td align="left">Arm B: metformin &#x2b; NACT</td>
</tr>
<tr>
<td align="left">Arm C: placebo &#x2b; NACT</td>
</tr>
<tr>
<td rowspan="2" align="left">NCT03358017</td>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left">54</td>
<td rowspan="2" align="left" style="color:#1B1B1B">TNBC</td>
<td align="left">Arm A: NACT &#x2b; zoledronate &#x2b; atorvastatin</td>
<td rowspan="2" align="left" style="color:#1B1B1B">&#xa0;pCR and YAP/TAZ expression</td>
<td rowspan="2" align="left">Completed</td>
</tr>
<tr>
<td align="left">Arm B: NACT</td>
</tr>
<tr>
<td rowspan="6" align="left">Simvastatin</td>
<td rowspan="2" align="left">NCT05550415</td>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left">26</td>
<td rowspan="2" align="left">Advanced TNBC</td>
<td align="left">Arm A: chemotherapy &#x2b; simvastatin</td>
<td rowspan="2" align="left">Vimentin epression</td>
<td rowspan="2" align="left">Ongoing</td>
</tr>
<tr>
<td align="left">Arm B: chemotherapy &#x2b; placebo</td>
</tr>
<tr>
<td rowspan="2" align="left">NCT05464810</td>
<td rowspan="2" align="left">I</td>
<td rowspan="2" align="left">40</td>
<td rowspan="2" align="left">Postmenopausal non-metastatic HR&#x2b;/HER2- BC, WOO</td>
<td align="left">Arm A: letrozole &#x2b; simvastatin</td>
<td rowspan="2" align="left">Ki67</td>
<td rowspan="2" align="left">Ongoing</td>
</tr>
<tr>
<td align="left">Arm B: letrozole</td>
</tr>
<tr>
<td align="left">NCT03324425</td>
<td align="left">II</td>
<td align="left">5</td>
<td align="left">HER2&#x2b; ABC</td>
<td align="left">Simvastatin &#x2b; dual anti-HER2 Therapy</td>
<td align="left">ORR</td>
<td align="left">Ongoing</td>
</tr>
<tr>
<td align="left">NCT03192293</td>
<td align="left">II</td>
<td align="left" style="color:#171716">28</td>
<td align="left">Postmenopausal ER &#x2b; ABC</td>
<td align="left">Simvastatin &#x2b; metformin &#x2b; fulvestrant</td>
<td align="left">CBR</td>
<td align="left">Unknown</td>
</tr>
<tr>
<td rowspan="22" align="left">ACC</td>
<td rowspan="22" align="left">Metformin<xref ref-type="table-fn" rid="Tfn2">
<sup>b</sup>
</xref>
</td>
<td rowspan="2" align="left">NCT01589367</td>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left">208</td>
<td rowspan="2" align="left" style="color:#1B1B1B">Non-diabetic, postmenopausal ER &#x2b; BC</td>
<td align="left">Arm A: neoadjuvant letrozole &#x2b; metformin</td>
<td rowspan="2" align="left" style="color:#1B1B1B">CRR</td>
<td rowspan="2" align="left">Completed</td>
</tr>
<tr>
<td align="left">Arm B: neoadjuvant letrozole &#x2b; placebo</td>
</tr>
<tr>
<td align="left">NCT01566799</td>
<td align="left">II</td>
<td align="left" style="color:#171716">60</td>
<td align="left">LABC</td>
<td align="left">Metformin &#x2b; NACT</td>
<td align="left">pCR</td>
<td align="left">Unknown</td>
</tr>
<tr>
<td rowspan="2" align="left">NCT04387630</td>
<td rowspan="2" align="left">II/III</td>
<td rowspan="2" align="left" style="color:#171716">120</td>
<td rowspan="2" align="left">Non-diabetic BC</td>
<td align="left">Arm A: metformin &#x2b; NACT</td>
<td rowspan="2" align="left">CRR</td>
<td rowspan="2" align="left">Unknown</td>
</tr>
<tr>
<td align="left">Arm B: placebo &#x2b; NACT</td>
</tr>
<tr>
<td rowspan="2" align="left">NCT03238495</td>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left" style="color:#171716">100</td>
<td rowspan="2" align="left">HER2&#x2b; EBC</td>
<td align="left">Arm A: metformin &#x2b; NACT &#x2b; FMD</td>
<td rowspan="2" align="left">pCR</td>
<td rowspan="2" align="left">Unknown</td>
</tr>
<tr>
<td align="left">Arm B: NACT &#x2b; FMD</td>
</tr>
<tr>
<td rowspan="2" align="left">NCT04248998</td>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left" style="color:#171716">30</td>
<td rowspan="2" align="left">TNBC</td>
<td align="left">Arm A: metformin &#x2b; NACT</td>
<td rowspan="2" align="left">pCR</td>
<td rowspan="2" align="left">Ongoing</td>
</tr>
<tr>
<td align="left">Arm B: NACT</td>
</tr>
<tr>
<td rowspan="2" align="left">NCT05023967</td>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left" style="color:#171716">120</td>
<td rowspan="2" align="left">HR &#x2b; EBC, WOO</td>
<td align="left">Arm A: metformin &#x2b; FMD</td>
<td rowspan="2" align="left">Safety and Ki67</td>
<td rowspan="2" align="left">Ongoing</td>
</tr>
<tr>
<td align="left">Arm B: usual dietary</td>
</tr>
<tr>
<td rowspan="3" align="left">NCT01477060</td>
<td rowspan="3" align="left">II</td>
<td rowspan="3" align="left" style="color:#171716">32</td>
<td rowspan="3" align="left">HR&#x2b;/HER2- ABC with progressive disease after first-line therapy</td>
<td align="left">Arm A: hormonal therapy &#x2b; metformin</td>
<td rowspan="3" align="left">PFS</td>
<td rowspan="3" align="left">Terminated</td>
</tr>
<tr>
<td align="left">Arm B: hormonal therapy &#x2b; lapatinib</td>
</tr>
<tr>
<td align="left">Arm C: hormonal therapy &#x2b; Metformin &#x2b; lapatinib</td>
</tr>
<tr>
<td rowspan="2" align="left">NCT04143282</td>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left" style="color:#171716">250</td>
<td rowspan="2" align="left">ABC</td>
<td align="left">Arm A: metformin &#x2b; chemotherapy</td>
<td rowspan="2" align="left">ORR, OS, and PFS</td>
<td rowspan="2" align="left">Completed</td>
</tr>
<tr>
<td align="left">Arm B: chemotherapy</td>
</tr>
<tr>
<td rowspan="3" align="left">NCT02506777</td>
<td rowspan="3" align="left">II</td>
<td rowspan="3" align="left" style="color:#171716">96</td>
<td rowspan="3" align="left">LABC</td>
<td align="left">Arm A: NACT &#x2b; metformin</td>
<td rowspan="3" align="left">ORR and pCR</td>
<td rowspan="3" align="left">Unknown</td>
</tr>
<tr>
<td align="left">Arm B: NACT &#x2b; melatonin</td>
</tr>
<tr>
<td align="left">Arm C: NACT</td>
</tr>
<tr>
<td rowspan="3" align="left">NCT02506790</td>
<td rowspan="3" align="left">II</td>
<td rowspan="3" align="left" style="color:#171716">96</td>
<td rowspan="3" align="left">LABC</td>
<td align="left">Arm A: neoadjuvant toremifene &#x2b; metformin</td>
<td rowspan="3" align="left">ORR and pCR</td>
<td rowspan="3" align="left">Unknown</td>
</tr>
<tr>
<td align="left">Arm B: neoadjuvant toremifene &#x2b; melatonin</td>
</tr>
<tr>
<td align="left">Arm C: neoadjuvant toremifene</td>
</tr>
<tr>
<td rowspan="2" align="left">PS</td>
<td rowspan="2" align="left">Bavituximab</td>
<td align="left">NCT00669565</td>
<td align="left">II</td>
<td align="left">46</td>
<td align="left">LABC or ABC</td>
<td align="left">Bavituximab &#x2b; paclitaxel &#x2b; carboplatin</td>
<td align="left" style="color:#1B1B1B">ORR</td>
<td align="left">Completed</td>
</tr>
<tr>
<td align="left">NCT00669591</td>
<td align="left">II</td>
<td align="left">46</td>
<td align="left" style="color:#1B1B1B">ABC</td>
<td align="left">Bavituximab &#x2b; docetaxel</td>
<td align="left" style="color:#1B1B1B">ORR</td>
<td align="left">Completed</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>FASN, fatty acid synthase; HER2, human epidermal growth factor receptor 2; ABC, advanced breast cancer; ORR, overall response rate; EGCG, epigallocatechin-3-gallate; BC, breast cancer; iDFS, invasive disease-free survival; HMGCR, 3-hydroxy-3-methylglutaryl-coenzyme A reductase; TNBC, triple-negative breast cancer; pCR, pathological complete response; NACT, neoadjuvant chemotherapy; CTC, circulating tumor cell; EBC, early breast cancer; WOO, window-of-opportunity; ER, estrogen receptor; TAZ, transcriptional co-activator with PDZ-binding motif; CBR, clinical benefit rate; YAP, Yes-associated protein; HR, hormone receptor; ACC, acetyl-CoA carboxylase; CRR, clinical response rate; LABC, locally advanced breast cancer; FMD, fasting-mimicking diet; OS, overall survival; PFS, progression-free survival; PS, phosphatidylserine.</p>
</fn>
<fn id="Tfn1">
<label>
<sup>a</sup>
</label>
<p>Fulvestrant will be used as second line endocrine treatment upon progression on first line with letrozole &#xb1; atorvastatin.</p>
</fn>
<fn id="Tfn2">
<label>
<sup>b</sup>
</label>
<p>Some studies related to metformin have already been mentioned in the section on statins.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Published trials concerning lipid pathway-targeted therapy in breast cancer (BC).</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Target</th>
<th align="left">Inhibitor</th>
<th align="left">Phase</th>
<th align="left">No.</th>
<th align="left">Setting</th>
<th align="left">Regimen</th>
<th align="left">Primary endpoint</th>
<th align="left">Findings</th>
<th align="left">References</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="2" align="left">FASN</td>
<td align="left">Omeprazole</td>
<td align="left">II</td>
<td align="left">42</td>
<td align="left">Early TNBC</td>
<td align="left">NACT &#x2b; omeprazole</td>
<td align="left">pCR</td>
<td align="left">Yielded a promising pCR rate</td>
<td align="left">
<xref ref-type="bibr" rid="B124">Sardesai et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">CLA</td>
<td align="left">I</td>
<td align="left">24</td>
<td align="left">EBC, WOO</td>
<td align="left">CLA</td>
<td align="left">Expression of biomarkers</td>
<td align="left">Significant decrements in Spot 14 and Ki67</td>
<td align="left">
<xref ref-type="bibr" rid="B101">McGowan et al. (2013)</xref>
</td>
</tr>
<tr>
<td rowspan="7" align="left">HMGCR</td>
<td align="left">Fluvastatin</td>
<td align="left">NA</td>
<td align="left">40</td>
<td align="left">Stage 0/I BC, WOO</td>
<td align="left">Fluvastatin</td>
<td align="left">Ki67</td>
<td align="left">Reduced tumor proliferation and increased apoptotic activity in high-grade tumors</td>
<td align="left">
<xref ref-type="bibr" rid="B55">Garwood et al. (2010)</xref>
</td>
</tr>
<tr>
<td align="left">Atorvastatin</td>
<td align="left">II</td>
<td align="left">50</td>
<td align="left">Postmenopausal BC, WOO</td>
<td align="left">Atorvastatin</td>
<td align="left">Ki67</td>
<td align="left">Indicated MAPK pathway inhibition, and pro-apoptotic and anti-proliferative effects</td>
<td align="left">
<xref ref-type="bibr" rid="B48">Feldt et al. (2015)</xref>, <xref ref-type="bibr" rid="B12">Bjarnadottir et al. (2015)</xref> <xref ref-type="bibr" rid="B49">Feldt et al. (2020)</xref>)</td>
</tr>
<tr>
<td rowspan="3" align="left">Simvastatin</td>
<td align="left">II</td>
<td align="left">24</td>
<td align="left">Stage I/II BC, WOO</td>
<td align="left">Simvastatin</td>
<td align="left">Ki67</td>
<td align="left">Ki-67 remained unchanged, whereas significant increases were detected in apoptotic markers</td>
<td align="left">
<xref ref-type="bibr" rid="B77">Kamal et al. (2024)</xref>
</td>
</tr>
<tr>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left">66</td>
<td rowspan="2" align="left" style="color:#1B1B1B">LABC</td>
<td align="left">Arm A: NACT &#x2b; placebo</td>
<td rowspan="2" align="left" style="color:#1B1B1B">Clinical response</td>
<td rowspan="2" align="left">Improved ORR and pathological response, especially in patients with HER2 overexpression</td>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B151">Yulian et al. (2021)</xref>, <xref ref-type="bibr" rid="B152">Yulian et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Arm B: NACT &#x2b; simvastatin</td>
</tr>
<tr>
<td rowspan="2" align="left">Pitavastatin</td>
<td rowspan="2" align="left">II/III</td>
<td rowspan="2" align="left">70</td>
<td rowspan="2" align="left" style="color:#1B1B1B">EBC</td>
<td align="left">Arm A: NACT &#x2b; placebo</td>
<td rowspan="2" align="left" style="color:#1B1B1B">CRR and Ki67</td>
<td rowspan="2" align="left">Higher reductions in tumor size</td>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B38">Dewidar et al. (2022)</xref>
</td>
</tr>
<tr>
<td align="left">Arm B: NACT &#x2b; pitavastatin</td>
</tr>
<tr>
<td rowspan="29" align="left">ACC</td>
<td rowspan="29" align="left">Metformin</td>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left">60</td>
<td rowspan="2" align="left">Pre-treated postmenopausal HR &#x2b; ABC</td>
<td align="left">Arm A: AI &#x2b; metformin</td>
<td rowspan="2" align="left">PFS</td>
<td rowspan="2" align="left">No improved efficacy</td>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B156">Zhao et al. (2017b)</xref>
</td>
</tr>
<tr>
<td align="left">Arm B: AI &#x2b; placebo</td>
</tr>
<tr>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left" style="color:#171716">122</td>
<td rowspan="2" align="left" style="color:#1B1B1B">Non-diabetic HER2- ABC</td>
<td align="left">Arm A: metformin &#x2b; chemotherapy</td>
<td rowspan="2" align="left">PFS</td>
<td rowspan="2" align="left">The addition of metformin did not improve PFS, whereas alleviated chemotherapy toxicity. Patients with insulin resistance exhibited significantly shortened PFS.</td>
<td rowspan="2" align="left">MYME (<xref ref-type="bibr" rid="B105">Nanni et al., 2019</xref>)</td>
</tr>
<tr>
<td align="left">Arm B: chemotherapy</td>
</tr>
<tr>
<td rowspan="2" align="left">NA</td>
<td rowspan="2" align="left" style="color:#171716">47</td>
<td rowspan="2" align="left">Non-diabetic EBC, WOO</td>
<td align="left">Arm A: metformin</td>
<td rowspan="2" align="left">Ki67</td>
<td rowspan="2" align="left">Ki67 fell significantly</td>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B63">Hadad et al. (2011)</xref>, <xref ref-type="bibr" rid="B64">Hadad et al. (2015)</xref>
</td>
</tr>
<tr>
<td align="left">Arm B: none</td>
</tr>
<tr>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left" style="color:#171716">80</td>
<td rowspan="2" align="left">Non-diabetic LABC</td>
<td align="left">Arm A: metformin &#x2b; NACT</td>
<td rowspan="2" align="left">CBR</td>
<td rowspan="2" align="left">Improveed non-significantly the clinical and pathological tumor response</td>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B7">Barakat et al. (2022)</xref>
</td>
</tr>
<tr>
<td align="left">Arm B: NACT</td>
</tr>
<tr>
<td align="left">II</td>
<td align="left" style="color:#171716">35</td>
<td align="left">Overweight EBC, WOO</td>
<td align="left">Metformin</td>
<td align="left">Ki67</td>
<td align="left">There was no reduction in Ki67</td>
<td align="left">
<xref ref-type="bibr" rid="B76">Kalinsky et al. (2014)</xref>
</td>
</tr>
<tr>
<td align="left">NA</td>
<td align="left" style="color:#171716">39</td>
<td align="left">Non-diabetic EBC, WOO</td>
<td align="left">Metformin</td>
<td align="left">Ki67</td>
<td align="left">Insulin-dependent effects of metformin as its antitumor mechanism</td>
<td align="left">
<xref ref-type="bibr" rid="B41">Dowling et al. (2015)</xref>
</td>
</tr>
<tr>
<td align="left">II</td>
<td align="left" style="color:#171716">22</td>
<td align="left">Postmenopausal, overweight HR&#x2b;/HER2- ABC</td>
<td align="left">Everolimus &#x2b; exemestane &#x2b; metformin</td>
<td align="left">PFS</td>
<td align="left">Safe and had moderate clinical benefit</td>
<td align="left">
<xref ref-type="bibr" rid="B149">Yam et al. (2019)</xref>
</td>
</tr>
<tr>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left" style="color:#171716">92</td>
<td rowspan="2" align="left">EBC with metabolic abnormality</td>
<td align="left">Arm A: Metformin &#x2b; NACT</td>
<td rowspan="2" align="left">pCR</td>
<td rowspan="2" align="left">Did not increase pCR rate</td>
<td rowspan="2" align="left">NeoMET (<xref ref-type="bibr" rid="B70">Huang et al., 2023</xref>)</td>
</tr>
<tr>
<td align="left">Arm B: NACT</td>
</tr>
<tr>
<td rowspan="2" align="left">NA</td>
<td rowspan="2" align="left" style="color:#171716">107</td>
<td rowspan="2" align="left">Non-diabetic ABC</td>
<td align="left">Arm A: Metformin &#x2b; chemotherapy</td>
<td rowspan="2" align="left">PFS and RR</td>
<td rowspan="2" align="left">No significant survival benefit</td>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B44">Essa et al. (2022)</xref>
</td>
</tr>
<tr>
<td align="left">Arm B: chemotherapy</td>
</tr>
<tr>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left" style="color:#171716">40</td>
<td rowspan="2" align="left">ABC</td>
<td align="left">Arm A: Metformin &#x2b; standard chemotherapy</td>
<td rowspan="2" align="left">PFS</td>
<td rowspan="2" align="left">No significant effect on RR, PFS, or OS</td>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B117">Pimentel et al. (2019)</xref>
</td>
</tr>
<tr>
<td align="left">Arm B: Placebo &#x2b; standard chemotherapy</td>
</tr>
<tr>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left" style="color:#171716">70</td>
<td rowspan="2" align="left">EBC</td>
<td align="left">Arm A: NACT &#x2b; Metformin</td>
<td rowspan="2" align="left">Apoptosis biomarker and safety</td>
<td rowspan="2" align="left">Improved clinical and pathological responses, alleviated chemotherapy toxicity</td>
<td rowspan="2" align="left">METNEO (<xref ref-type="bibr" rid="B127">Serageldin et al., 2023</xref>; <xref ref-type="bibr" rid="B126">Serageldin et al., 2024</xref>)</td>
</tr>
<tr>
<td align="left">Arm B: NACT</td>
</tr>
<tr>
<td rowspan="2" align="left">III</td>
<td rowspan="2" align="left" style="color:#171716">3,649</td>
<td rowspan="2" align="left">Non-diabetic T1c-3N0-3M0 BC</td>
<td align="left">Arm A: metformin</td>
<td rowspan="2" align="left">iDFS</td>
<td rowspan="2" align="left">Did not significantly improve iDFS; did not reduce the risk of new cancer development</td>
<td rowspan="2" align="left">MA.32 (<xref ref-type="bibr" rid="B116">Pimentel et al., 2021</xref>; <xref ref-type="bibr" rid="B61">Goodwin et al., 2015</xref>; <xref ref-type="bibr" rid="B59">Goodwin et al., 2021a</xref>; <xref ref-type="bibr" rid="B60">Goodwin et al., 2021b</xref>; <xref ref-type="bibr" rid="B57">Goodwin et al., 2022</xref>; <xref ref-type="bibr" rid="B58">Goodwin et al., 2023</xref>)</td>
</tr>
<tr>
<td align="left">Arm B: placebo</td>
</tr>
<tr>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left" style="color:#171716">84</td>
<td rowspan="2" align="left">Non-metastatic HER2&#x2b; BC</td>
<td align="left">Arm A: metformin &#x2b; NACT</td>
<td rowspan="2" align="left">pCR</td>
<td rowspan="2" align="left">Did not significantly improve pCR rate</td>
<td rowspan="2" align="left">METTEN (<xref ref-type="bibr" rid="B99">Martin-Castillo et al., 2018</xref>; <xref ref-type="bibr" rid="B32">Cuy&#xe0;s et al., 2019a</xref>; <xref ref-type="bibr" rid="B33">Cuy&#xe0;s et al., 2019b</xref>; <xref ref-type="bibr" rid="B94">Lopez-Bonet et al., 2019</xref>)</td>
</tr>
<tr>
<td align="left">Arm B: NACT</td>
</tr>
<tr>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left" style="color:#171716">59</td>
<td rowspan="2" align="left">Stage II/III non-diabetic BC</td>
<td align="left">Arm A: metformin &#x2b; NACT</td>
<td rowspan="2" align="left">Pathological response</td>
<td rowspan="2" align="left">Did not significantly improve pCR rate</td>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B43">El-Khayat et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Arm B: NACT</td>
</tr>
<tr>
<td rowspan="2" align="left">II</td>
<td rowspan="2" align="left" style="color:#171716">200</td>
<td rowspan="2" align="left">Non-diabetic EBC, WOO</td>
<td align="left">Arm A: metformin</td>
<td rowspan="2" align="left">Ki67</td>
<td rowspan="2" align="left">Did not significantly affect Ki67 overall, but showed significantly different effects according to insulin resistance, particularly in luminal B tumors</td>
<td rowspan="2" align="left">
<xref ref-type="bibr" rid="B14">Bonanni et al. (2012)</xref>, <xref ref-type="bibr" rid="B21">Cazzaniga et al. (2013)</xref>, <xref ref-type="bibr" rid="B36">DeCensi et al. (2015)</xref>
</td>
</tr>
<tr>
<td align="left">Arm B: placebo</td>
</tr>
<tr>
<td align="left">II</td>
<td align="left" style="color:#171716">39</td>
<td align="left">Non-diabetic BC, WOO</td>
<td align="left">Metformin</td>
<td align="left">Ki67</td>
<td align="left">Ki67 staining in invasive tumor tissue decreased and TUNEL staining increased</td>
<td align="left">
<xref ref-type="bibr" rid="B108">Niraula et al. (2012)</xref>
</td>
</tr>
<tr>
<td align="left">II</td>
<td align="left" style="color:#171716">47</td>
<td align="left">Non-diabetic HER2&#x2b; EBC/LABC</td>
<td align="left">Metformin &#x2b; NACT</td>
<td align="left">pCR</td>
<td align="left">Did not appear to improve activity over conventional sequential regimens</td>
<td align="left">
<xref ref-type="bibr" rid="B121">Rocca et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">PS</td>
<td align="left">Bavituximab</td>
<td align="left">I</td>
<td align="left">14</td>
<td align="left" style="color:#1B1B1B">HER2- ABC</td>
<td align="left">Bavituximab &#x2b; paclitaxel</td>
<td align="left" style="color:#1B1B1B">Safety</td>
<td align="left">Well tolerated</td>
<td align="left">
<xref ref-type="bibr" rid="B24">Chalasani et al. (2015)</xref>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>FASN, fatty acid synthase; TNBC, triple-negative breast cancer; NACT, neoadjuvant chemotherapy; pCR, pathological complete response; CLA, conjugated linoleic acid; EBC, early breast cancer; WOO, window-of-opportunity; HMGCR, 3-hydroxy-3-methylglutaryl-coenzyme A reductase; BC, breast cancer; LABC, locally advanced breast cancer; ORR, objective response rate; HER2, human epidermal growth factor receptor 2; CRR, clinical response rate; ACC, acetyl-CoA carboxylase; HR, hormone receptor; PFS, progression-free survival; ABC, advanced breast cancer; CBR, clinical benefit rate; RR, response rate; OS, overall survival; iDFS, invasive disease-free survival; TUNEL, terminal deoxynucleotidyl transferase-mediated dUTP, nick end labeling.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>Statins, functioning via the inhibition HMGCR, are commonly prescribed for patients with cardiovascular disease and high cholesterol levels to lower their cholesterol (<xref ref-type="bibr" rid="B29">Clendening and Penn, 2012</xref>). In recent years, growing trials have focused on their promising anticancer benefits (<xref ref-type="bibr" rid="B77">Kamal et al., 2024</xref>; <xref ref-type="bibr" rid="B151">Yulian et al., 2021</xref>; <xref ref-type="bibr" rid="B38">Dewidar et al., 2022</xref>; <xref ref-type="bibr" rid="B152">Yulian et al., 2023</xref>; <xref ref-type="bibr" rid="B55">Garwood et al., 2010</xref>; <xref ref-type="bibr" rid="B48">Feldt et al., 2015</xref>; <xref ref-type="bibr" rid="B12">Bjarnadottir et al., 2015</xref>; <xref ref-type="bibr" rid="B107">Nielsen et al., 2012</xref>). Currently, clinical trials for drugs such as fluvastatin, atorvastatin, simvastatin, and pitavastatin have been initiated worldwide, primarily for use before surgery in early breast cancer. The potential of these drugs, either as monotherapy or in addition to traditional standard therapy, is being evaluated through clinical or pathological responses (<xref ref-type="table" rid="T1">Tables 1</xref>, <xref ref-type="table" rid="T2">2</xref>). Among them, results from three window-of-opportunity studies have been published, generally finding that short-term monotherapy with statins could suppress tumor growth and enhance apoptotic processes (<xref ref-type="bibr" rid="B77">Kamal et al., 2024</xref>; <xref ref-type="bibr" rid="B55">Garwood et al., 2010</xref>; <xref ref-type="bibr" rid="B48">Feldt et al., 2015</xref>; <xref ref-type="bibr" rid="B12">Bjarnadottir et al., 2015</xref>). Additionally, two published studies in the neoadjuvant setting suggested that statins combined with standard neoadjuvant chemotherapy could, to some extent, enhance clinical and pathological responses compared to placebo, although the statistical differences were not always significant (<xref ref-type="bibr" rid="B151">Yulian et al., 2021</xref>; <xref ref-type="bibr" rid="B38">Dewidar et al., 2022</xref>; <xref ref-type="bibr" rid="B152">Yulian et al., 2023</xref>). Ongoing trials will delve deeper into the therapeutic potential of statins as monotherapy, alongside chemotherapy or with endocrine therapy for early- and advanced-stage breast cancer. For instance, the ongoing Phase III MASTER trial (NCT04601116) aims to determine whether long-term statin therapy can enhance the prognosis of women with early breast cancer.</p>
<p>Metformin, a frequently prescribed biguanide, stands as a cornerstone medication in managing hyperglycemia and type 2 diabetes (<xref ref-type="bibr" rid="B114">Pernicova and Korbonits, 2014</xref>). Increasing evidence suggests a potential effectiveness of this compound as an anticancer agent (<xref ref-type="bibr" rid="B114">Pernicova and Korbonits, 2014</xref>; <xref ref-type="bibr" rid="B135">Thompson, 2014</xref>). A fundamental way in which metformin exerts its influence encompasses the stimulation of AMP-activated protein kinase (AMPK), a vital metabolic modulator essential for maintaining energy balance and regulating cellular growth (<xref ref-type="bibr" rid="B9">Ben Sahra et al., 2010</xref>). Of note, AMPK has an impact on inhibiting ACC activity (<xref ref-type="bibr" rid="B53">Fullerton et al., 2013</xref>; <xref ref-type="bibr" rid="B129">Svensson et al., 2016</xref>). Accordingly, the antitumor activity of metformin could be at least partially facilitated by hindering FA biosynthesis (<xref ref-type="bibr" rid="B89">Ligorio et al., 2021</xref>). Herein, we also provide an overview of the clinical studies regarding the application of metformin in breast cancer (<xref ref-type="table" rid="T1">Table 1</xref> and <xref ref-type="table" rid="T2">2</xref>). Unfortunately, the research findings remain controversial. Some studies have found that preoperative monotherapy with metformin for 2-4 weeks could significantly reduce Ki67 levels and oncogenic signaling (<xref ref-type="bibr" rid="B63">Hadad et al., 2011</xref>; <xref ref-type="bibr" rid="B41">Dowling et al., 2015</xref>; <xref ref-type="bibr" rid="B108">Niraula et al., 2012</xref>; <xref ref-type="bibr" rid="B35">DeCensi et al., 2014</xref>). Furthermore, a study conducted by Serageldin et al. demonstrated that metformin could provide an additional benefit in terms of clinical and pathological responses compared to neoadjuvant chemotherapy alone (<xref ref-type="bibr" rid="B126">Serageldin et al., 2024</xref>). However, most research, including a phase III trial (MA.32) involving 3,649 patients (<xref ref-type="bibr" rid="B57">Goodwin et al., 2022</xref>), has indicated that metformin offered no advantage in antitumor effect, whether in early-stage (<xref ref-type="bibr" rid="B43">El-Khayat et al., 2021</xref>; <xref ref-type="bibr" rid="B57">Goodwin et al., 2022</xref>; <xref ref-type="bibr" rid="B58">Goodwin et al., 2023</xref>; <xref ref-type="bibr" rid="B7">Barakat et al., 2022</xref>; <xref ref-type="bibr" rid="B76">Kalinsky et al., 2014</xref>; <xref ref-type="bibr" rid="B70">Huang et al., 2023</xref>; <xref ref-type="bibr" rid="B99">Martin-Castillo et al., 2018</xref>; <xref ref-type="bibr" rid="B32">Cuy&#xe0;s et al., 2019a</xref>; <xref ref-type="bibr" rid="B33">Cuy&#xe0;s et al., 2019b</xref>; <xref ref-type="bibr" rid="B94">Lopez-Bonet et al., 2019</xref>; <xref ref-type="bibr" rid="B14">Bonanni et al., 2012</xref>; <xref ref-type="bibr" rid="B21">Cazzaniga et al., 2013</xref>; <xref ref-type="bibr" rid="B36">DeCensi et al., 2015</xref>; <xref ref-type="bibr" rid="B121">Rocca et al., 2021</xref>) or late-stage (<xref ref-type="bibr" rid="B156">Zhao Y. et al., 2017</xref>; <xref ref-type="bibr" rid="B44">Essa et al., 2022</xref>; <xref ref-type="bibr" rid="B105">Nanni et al., 2019</xref>; <xref ref-type="bibr" rid="B117">Pimentel et al., 2019</xref>; <xref ref-type="bibr" rid="B149">Yam et al., 2019</xref>) breast cancer, and regardless of whether the treatment was administered as monotherapy or in addition to conventional regimens. Notably, preclinical studies on ACC inhibition have exhibited contradictory outcomes regarding its anticancer effectiveness (<xref ref-type="bibr" rid="B89">Ligorio et al., 2021</xref>). Furthermore, Liu et al. discovered that the conjunction of metformin and simvastatin exhibits synergistic inhibition of various cancer cells, suggesting its potential in antitumor therapy when used in conjunction (<xref ref-type="bibr" rid="B92">Liu et al., 2023</xref>).</p>
<p>Bavituximab represents an unconjugated chimeric immunoglobulin G1 (IgG1) monoclonal antibody specifically binds to PS (<xref ref-type="bibr" rid="B56">Gerber et al., 2018</xref>). The unique external exposure of PS on tumor cells makes bavituximab an effective agent for targeting tumor specifically (<xref ref-type="bibr" rid="B75">Jennewein et al., 2008</xref>). Preclinical studies have shown that chemotherapy and radiation therapy could increase the exposure of PS, further enhancing bavituximab binding and immune activation (<xref ref-type="bibr" rid="B71">Huang et al., 2005</xref>; <xref ref-type="bibr" rid="B67">He et al., 2007</xref>). Therefore, bavituximab may serve as an ideal partner for chemotherapy and radiation therapy. A phase I clinical trial has thus far confirmed the safety of bavituximab administration in breast cancer (<xref ref-type="bibr" rid="B24">Chalasani et al., 2015</xref>). Additionally, two ongoing phase &#x2161; trials (NCT00669565 and NCT00669591) have completed their investigation into the potential value of combining bavituximab with chemotherapy in advanced breast cancer, although the research data have not yet been disclosed (<xref ref-type="table" rid="T1">Table 1</xref>). However, a randomized phase III trial comparing docetaxel plus bavituximab to docetaxel alone in patients with previously treated advanced non-squamous non-small-cell lung cancer failed to demonstrate survival benefit for the combination therapy (<xref ref-type="bibr" rid="B56">Gerber et al., 2018</xref>).</p>
</sec>
<sec id="s4-2">
<title>4.2 Complication reduction and cancer prevention potential</title>
<p>Despite contradictory research findings regarding its direct anticancer effects in breast cancer, lipid pathway-targeted therapy has been widely accepted for its crucial role in managing complications associated with treatments such as chemotherapy. For instance, metformin has been shown to alleviate chemotherapy-induced peripheral neuropathy neutropenia, cardiac toxicity, oral mucositis, and fatigue in non-diabetic breast cancer patients (<xref ref-type="bibr" rid="B127">Serageldin et al., 2023</xref>; <xref ref-type="bibr" rid="B105">Nanni et al., 2019</xref>; <xref ref-type="bibr" rid="B6">Bakry et al., 2023</xref>). Based on the preclinical evidence, statins appear to have the potential to mitigate chemotherapy-induced cardiotoxicity (<xref ref-type="bibr" rid="B111">Padegimas et al., 2020</xref>; <xref ref-type="bibr" rid="B113">Pecoraro et al., 2023</xref>; <xref ref-type="bibr" rid="B13">Bj&#xf8;rnstad et al., 2022</xref>). However, results from published clinical studies indicate that statins did not affect declines in left ventricular ejection fraction among certain breast cancer patients (<xref ref-type="bibr" rid="B72">Hundley et al., 2022</xref>; <xref ref-type="bibr" rid="B97">Makhlin et al., 2024</xref>; <xref ref-type="bibr" rid="B134">Thavendiranathan et al., 2023</xref>). An ongoing study is currently assessing the use of atorvastatin for prophylactic cardioprotection in patients undergoing anti-HER2 targeted therapy (NCT05559164). Lipid pathway-targeted therapy is also capable of protecting patients from the side effects of radiation therapy. In a phase &#x2161; double-blind, placebo-controlled randomized trial, the prophylactic application of EGCG solution significantly decreased both the occurrence and magnitude of radiation-induced dermatitis among breast cancer patients receiving adjuvant radiotherapy (<xref ref-type="bibr" rid="B154">Zhao et al., 2022</xref>). Statins are also believed to alleviate radiation-related complications (<xref ref-type="bibr" rid="B120">Ricco and Kron, 2023</xref>), however, clinical studies related to statin protection during radiotherapy in breast cancer patients have been terminated (NCT04385433, NCT00902668).</p>
<p>Furthermore, there are currently numerous completed as well as ongoing clinical trials exploring the potential of lipid pathway-targeted therapy in breast cancer prevention. The omega-3 preparation Lovaza was reported to reduce breast cancer risk in obese women (<xref ref-type="bibr" rid="B98">Manni et al., 2017</xref>). Although many observational analyses have found that metformin therapy did not practically influence cancer incidence (<xref ref-type="bibr" rid="B34">Dankner et al., 2019</xref>; <xref ref-type="bibr" rid="B39">Dickerman et al., 2023</xref>), there are also studies that supported a potential beneficial impact of metformin on reducing cancer risk (<xref ref-type="bibr" rid="B45">Evans et al., 2005</xref>; <xref ref-type="bibr" rid="B104">Muszy&#x144;ska-Og&#x142;aza et al., 2017</xref>; <xref ref-type="bibr" rid="B132">Tapia et al., 2021</xref>; <xref ref-type="bibr" rid="B137">Tseng, 2014</xref>). A clinical trial that is still ongoing will specifically explore the potential of metformin in preventing the development of invasive breast cancer among patients with a history of breast carcinoma <italic>in situ</italic> or atypical hyperplasia (NCT01905046). Similarly, there is no definitive conclusion pertaining to the association between statin administration and breast cancer risk (<xref ref-type="bibr" rid="B69">Higgins et al., 2012</xref>; <xref ref-type="bibr" rid="B142">Vinayak et al., 2013</xref>). Of note, several studies have indicated that lipophilic statins (i.e., simvastatin, fluvastatin, and lovastatin) may offer superior breast cancer prevention benefits compared to hydrophilic statins (i.e., atorvastatin and pravastatin) (<xref ref-type="bibr" rid="B3">Ahern et al., 2011</xref>; <xref ref-type="bibr" rid="B20">Cauley et al., 2006</xref>).</p>
</sec>
<sec id="s4-3">
<title>4.3 Selective lipid metabolism therapy benefit hypothesis</title>
<p>Based on the above, the clinical evidence projecting lipid pathway-targeted therapy as an anticancer or cancer chemopreventive strategy is variable. Nonetheless, it is recognized that certain breast cancer patients can indeed benefit from lipid pathway-targeted therapy (<xref ref-type="bibr" rid="B126">Serageldin et al., 2024</xref>; <xref ref-type="bibr" rid="B43">El-Khayat et al., 2021</xref>; <xref ref-type="bibr" rid="B77">Kamal et al., 2024</xref>; <xref ref-type="bibr" rid="B151">Yulian et al., 2021</xref>; <xref ref-type="bibr" rid="B38">Dewidar et al., 2022</xref>; <xref ref-type="bibr" rid="B152">Yulian et al., 2023</xref>; <xref ref-type="bibr" rid="B127">Serageldin et al., 2023</xref>). Consequently, we advance the Selective Lipid Metabolism Therapy Benefit Hypothesis, suggesting that therapeutic strategies targeting lipid metabolism may selectively benefit a subset of patients. This hypothesis neither unconditionally advocates for the absolute benefits of targeting lipid metabolism nor conclusively denies its significance based solely on negative trial results. Instead, it offers a more objective and dialectical understanding of the clinical value of lipid pathway-targeted therapies. This hypothesis highlights the need for a more precise identification of the patient subpopulation that may potentially benefit from such treatment, which is of paramount importance. Currently, some clinical trials have identified potential biomarkers capable of predicting the treatment response to lipid metabolism-targeting therapies, which will be comprehensively summarized in the next section.</p>
</sec>
<sec id="s4-4">
<title>4.4 Selective biomarkers</title>
<p>Currently, a number of clinical trials have identified a panel of promising biomarkers (<xref ref-type="bibr" rid="B48">Feldt et al., 2015</xref>; <xref ref-type="bibr" rid="B32">Cuy&#xe0;s et al., 2019a</xref>; <xref ref-type="bibr" rid="B64">Hadad et al., 2015</xref>; <xref ref-type="bibr" rid="B116">Pimentel et al., 2021</xref>; <xref ref-type="bibr" rid="B61">Goodwin et al., 2015</xref>; <xref ref-type="bibr" rid="B59">Goodwin et al., 2021a</xref>; <xref ref-type="bibr" rid="B49">Feldt et al., 2020</xref>; <xref ref-type="bibr" rid="B2">Ahern et al., 2020</xref>; <xref ref-type="bibr" rid="B60">Goodwin et al., 2021b</xref>). Based on an exploratory analysis of a window-of-opportunity breast cancer trial, Feldt and colleagues suggested that the expression levels of cyclin D1, p27, and low-density lipoprotein receptor in tumor tissues might influence the anti-proliferative efficacy of atorvastatin (<xref ref-type="bibr" rid="B48">Feldt et al., 2015</xref>; <xref ref-type="bibr" rid="B49">Feldt et al., 2020</xref>). Furthermore, evidence exists indicating that HER2 overexpression and genetic variations in ABCB1, CYP3A4, SLCO1B1, and CYP3A5 serve as biomarkers for predicting the response of breast tumors to simvastatin (<xref ref-type="bibr" rid="B151">Yulian et al., 2021</xref>; <xref ref-type="bibr" rid="B2">Ahern et al., 2020</xref>). Regarding Metformin, studies have found it to be more effective in patients with a BMI &#x2265;25 (<xref ref-type="bibr" rid="B43">El-Khayat et al., 2021</xref>), although this finding remains controversial (<xref ref-type="bibr" rid="B76">Kalinsky et al., 2014</xref>). The Phase &#x2161; METTEN trial suggested that the C allele of ataxia telangiectasia mutated (ATM) rs11212617 might function as a predictive biomarker to guide the personalized use of metformin in patients with breast cancer (<xref ref-type="bibr" rid="B32">Cuy&#xe0;s et al., 2019a</xref>); however, subsequent findings from the Phase &#x2162; MA.32 trial refuted this notion (<xref ref-type="bibr" rid="B60">Goodwin et al., 2021b</xref>). This controversy may stem from differences in the patient populations included in the two studies, as some research indicates that the anticancer effects of metformin in breast cancer exhibit subtype specificity (<xref ref-type="bibr" rid="B151">Yulian et al., 2021</xref>; <xref ref-type="bibr" rid="B14">Bonanni et al., 2012</xref>). Specifically, the METTEN trial exclusively enrolled HER2-positive breast cancer patients, whereas the MA.32 trial included patients regardless of their subtype. Additionally, the METTEN trial proposed that serum homocysteine levels might serve as an indicator connecting the antifolate-mimicking effects of metformin with tumor response (<xref ref-type="bibr" rid="B33">Cuy&#xe0;s et al., 2019b</xref>). An observable trend towards differing metformin efficacy, based on insulin resistance status, is also noted (<xref ref-type="bibr" rid="B14">Bonanni et al., 2012</xref>; <xref ref-type="bibr" rid="B21">Cazzaniga et al., 2013</xref>). Further exploration and validation of stable biomarkers for lipid pathway-targeted therapy in large-scale clinical trials are warranted.</p>
</sec>
</sec>
<sec id="s5">
<title>5 Conclusion and perspectives</title>
<p>The reprogramming of lipid metabolism has a vital role in breast cancer progression, drug resistance, and clinical outcome. We herein elaborate on the potential of regulating lipid metabolism in the clinical application for breast cancer, focusing on key enzymes and clinical trials. However, contrary to expectations, many trials regarding lipid pathway-targeted therapy have yielded negative results, possibly due to patient heterogeneity and the intricate crosstalk between lipid metabolism and cancer biology. Therefore, we propose the Selective Lipid Metabolism Therapy Benefit Hypothesis, advocating for the development of predictive biomarkers to guide personalized treatment decisions. Future research should focus on identifying and validating these biomarkers, as well as exploring novel therapeutic strategies to target lipid metabolism in breast cancer patients. By optimizing lipid pathway-targeted therapy, we can potentially improve patient outcomes, reduce complications, and prevent cancer recurrence.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s6">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec sec-type="author-contributions" id="s7">
<title>Author contributions</title>
<p>DL: Conceptualization, Investigation, Writing&#x2013;original draft. PJ: Conceptualization, Writing&#x2013;original draft. YC: Software, Writing&#x2013;original draft. SW: Writing&#x2013;original draft. XG: Writing&#x2013;original draft. ZZ: Writing&#x2013;review and editing. KL: Writing&#x2013;review and editing. PL: Writing&#x2013;review and editing. YH: Project administration, Supervision, Writing&#x2013;review and editing. YZ: Conceptualization, Project administration, Writing&#x2013;review and editing.</p>
</sec>
<sec sec-type="funding-information" id="s8">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was funded by the National Natural Science Foundation of China (Grant No. 82373437, 82072900), the Key Research and Development Program of Zhejiang Province (Grant No. 2024C03183), A Project Supported by Scientific Research Fund of Zhejiang Provincial Education Department (Grant No. Y202353498).</p>
</sec>
<sec sec-type="COI-statement" id="s9">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="s11">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
</sec>
<sec sec-type="disclaimer" id="s10">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
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