Exploring metabolic approaches for epithelial ovarian cancer therapy

1. Introduction

Ovarian cancer is one of the most lethal types of gynecological cancer, accounting for an estimated 19,680 new cases and 12,740 reported deaths in the year 2024 (Siegel, Giaquinto, & Jemal, 2024). It is heterogeneous disease consisting of different subtypes, with the most common type being high-grade serous ovarian cancer(HGSOC) a subtype of epithelial ovarian cancer (EOC)(Jayson, Kohn, Kitchener, & Ledermann, 2014; Tothill et al., 2008; Vaughan et al., 2011). HGSOC is one of the most lethal subtypes of ovarian cancer with limited therapeutic options available (S. Zhang et al., 2019). Recent studies have demonstrated that a significant number of HGSOC cases originate in the epithelium of the fallopian tubes (Labidi-Galy et al., 2017).

Due to the lack of early screening and vague abdominal symptoms HGSOC is often diagnosed at a late stage. The disease often results in peritoneal deposits and the formation of ascites. Current treatment typically involves debulking surgery followed by platinum-based chemotherapy, although chemoresistance often develops after a certain period (Patch et al., 2015). The five-year survival rate of advanced-stage HGSOC is less than 35% (Hu et al., 2022). New treatment options, such as PARP inhibitors, are only effective for a limited subset of patients (Dias, Moser, Ganesan, & Jonkers, 2021). However, despite advancements in these approaches, the prognosis for ovarian cancer remains challenging, particularly in the advanced stages of the disease. Hence, there is an unmet need for new therapeutic targeting options to treat this devastating disease effectively.

Cancer cells undergo metabolic reprogramming to adapt to nutrient deficiencies and develop resistance to chemotherapies. This reprogramming, involving alterations in glucose, lipids, and amino acid metabolism, is a well-known characteristics of tumor metabolism. In HGSOC cells, mutations in TP53 are frequently observed, leading to disruptions in metabolic pathways (Y. Zhang, Cao, Nguyen, & Lu, 2016). Oncogenes like MYC, RAS, and PI3K drive increased glucose uptake, glycolysis, and glutamine metabolism to fulfill the increased energy requirements of cancer cells (M. Wang, Zhang, & Wu, 2023). Of note, tumor suppressor genes such as p53 and PTEN regulate metabolism by inhibiting glycolysis and promoting oxidative phosphorylation. Moreover, changes in genes like BRCA1/2 can impact DNA repair mechanisms and mitochondrial function, further influencing metabolic reprogramming in cancer cells (Kanakkanthara et al., 2019). However, a significant number of patients do not respond to targeted therapies due to the absence of relevant gene mutations. Targeting cancer cell metabolism is an attractive therapeutic approach for various types of cancer. Cancer cell metabolism plays a crucial role in cancer progression and survival. Uncontrolled cell proliferation is a key feature of cancer, and metabolic processes significantly promote cancer cell proliferation and motility (Hanahan & Weinberg, 2011). These metabolic processes provide the necessary nutrients for uncontrolled growth by modulating the expression of specific genes and proteins involved in tumorigenesis. The constraints of existing metabolic treatments for ovarian cancer patients indicate the importance of investigating novel targets and refining treatment approaches.

In this review, we will address the role of carbohydrate, amino acid, and lipid metabolism in HGSOC tumorigenesis as well as the clinical potential of targeting these cellular processes in therapy. Cancer cells frequently display altered metabolism; therefore, targeting these metabolic changes can be a potential therapeutic approach. The rapid proliferation of HGSOC cells is the first hallmark, requiring a large amount of energy supplies and carbon are needed to rebuild biomasses, such as bio-membranes, nucleic acids and proteins. The reprogramming of carbohydrate, lipid, and amino acid metabolism is a well-known hallmark of cancer and provides the basis of its proliferation.

In this context, targeting of ovarian cancer metabolism should be grounded in comprehensive understanding of how inhibiting specific metabolic pathways affects the tumor immune microenvironment (TME) cells, which can either hinder or promote tumor progression (Dang & Semenza, 1999; DeBerardinis & Chandel, 2016; Vander Heiden, Cantley, & Thompson, 2009). The limitations observed in current metabolic therapies for cancer patients underscore the importance of investigating novel targets and refining treatment strategies for optimal outcomes.

2. Carbohydrate metabolism

2.1. Glycolysis

Glycolysis is a crucial metabolic pathway that breaks down glucose into two three-carbon compounds, generating ATP and NADH (Chandel, 2021). Cancer cells often depend on aerobic glycolysis, known as the “Warburg effect,” leading to increased cell proliferation, glucose uptake, and lactate production even in the presence of oxygen (Hitosugi et al., 2011). HGSOC exhibits elevated glycolytic activity under standard cell culture conditions (Nojima & Wada, 2023).

In certain malignancies, cancer cells may compete with immune cells, particularly CD8+ cytotoxic T lymphocytes (CTLs), for glucose uptake within the TME. This phenomenon has been demonstrated in immunocompetent mouse model of sarcoma(Y. Ma et al., 2018). Several pharmacological and genetic strategies aimed at inhibiting glycolysis have demonstrated the ability to mediate immunostimulatory effects and partially restore immunosurveillance in preclinical tumor models. Specifically, genetic inhibition of glycolysis in mouse models has shown promising results. This dependency on glycolysis has been proposed as a therapeutic target for ovarian cancer growth (Fig. 1).

Figure 1.

Inhibitors of glucose metabolism in high-grade serous ovarian cancer

2.1.1. Dysregulated glycolysis

Several enzymes and transporters involved in glycolysis have been used as potential targets, including glucose transporters such as Na+-independent sugar transporters (GLUT1) and Na+-dependent sugar cotransporters (SGLT), as well as the glycolytic pathway enzyme hexokinase 2 (HK2)(E. Shin & Koo, 2021). To facilitate increased aerobic glycolysis, cancer cells often overexpress glucose transporters such as GLUT1(Calvo, Figueroa, Pulido, Campelo, & Aparicio, 2010). GLUT1 is a glucose transporter that is encoded by SLC2A1 gene. GLUT that initiates glucose entry into the cell as the initial step in the glycolytic pathway(Tsukioka et al., 2007). Ovarian cancer patients exhibiting GLUT1 overexpression experience shorter disease-free survival. GLUT1 serves as a critical regulator of both basal and stress-induced glycolysis in ovarian cancer. Moreover, in EOC, overexpression of GLUT1 positively correlates with tumor proliferation and micro vessel density (Semaan et al., 2011; Tsukioka et al., 2007). Additionally, SGLT is a protein that transports glucose utilizing sodium/potassium ATPase. It can transport glucose across membranes regardless of the glucose concentration in the microenvironment. Despite limited data on SGLT in ovarian cancer, studies have revealed that SGLT1 serves as an independent biomarker indicating a poor prognosis in ovarian cancer (Lai et al., 2012). HK2 has also been recognized as a pivotal factor in cancer biology (Mathupala, Ko, & Pedersen, 2006). This enzyme catalyzes the phosphorylation of glucose to glucose-6-phosphate, serving as the rate-limiting step in the glycolytic pathway. Notably, HK2 levels are high in HGSOC cell lines compared to non-HGSOC cell lines (Xintaropoulou et al., 2018) with its overexpression being associated with both chemoresistance and disease recurrence (Suh et al., 2014). Furthermore, in vivo mouse models have demonstrated that genetic deletion of HK2 significantly reduces tumor burden, underscoring the critical role of HK2 in tumor progression (Patra et al., 2013)

2.1.2. Targeting glycolysis in EOC

GLUT1 inhibitors:

The overexpression of SLC2A1 induced by hypoxia is believed to be an adaptive response to oxygen deprivation commonly observed in EOC (Kalir et al., 2002). However, another study also indicates that GLUT1 is highly upregulated in malignant HGSOC (Cho, Lee, Kim, Chung, & Kim, 2013). Interestingly, the pharmacological application of the GLUT1 inhibitor BAY-876 in HGSOC led to a notable reduction in tumor growth by 50–71%, accompanied by decreased glucose influx and consumption in both in vitro and in vivo murine models (Y. Ma et al., 2018). Furthermore, BAY 876 has been shown to reduce CD4+ T cell proliferation and IFN-γ secretion through the inhibition of GLUT1(L. Chen et al., 2023). Importantly, the inhibition of GLUT1 using BAY-876 enhanced the sensitivity of patient-derived spheroid cells from uterine endometrial cancer to Paclitaxel (Mori et al., 2019). Additionally, Ciglitazone, an antidiabetic medication, exhibited an anti- proliferative effect on EOC cells in vitro by modulating GLUT1 abundance in the plasma membrane, thereby regulating glucose utilization and attenuating EOC’s rapid growth (S. J. Shin et al., 2014). Further, research demonstrated that the GLUT1 inhibitor STF31, in combination with metformin and chemotherapy, enhanced therapy efficacy in both sensitive and resistant EOC cases (Xintaropoulou et al., 2018). The combination of GLUT1 inhibitors with chemotherapeutic agents have demonstrated a synergistic effect in various types of cancers (Tilekar et al., 2020). Therefore, the inhibition of glucose uptake mediated by GLUT1 plays a significant role in the suppression of EOC cells and can be a potential target in the treatment of EOC.

HK2 inhibitors:

HK2, serving as the initial rate-limiting enzyme in glycolysis, is intricately linked to cancer progression. Nevertheless, its specific role in EOC remains ambiguous(Y. Li, Tian, Luo, Fu, & Jiao, 2020). Several studies demonstrated the increased levels of HK2 in many cancers including EOC. HK2 may be a potential biomarker for the poor prognosis of EOC patients and a potential therapeutic target (M. Zhang et al., 2020). Pharmacological inhibition of HK2 leads to a significant reduction in glycolysis, impacting various pathways of central metabolism and inducing destabilization of the mitochondrial outer membrane, promoting cell death (Garcia, Guedes, & Marques, 2019). Preclinical studies showed that the glucose analog 2-DG inhibited glycolysis in human ovarian cancer cells by competitively inhibiting HK2 (L. Wang, Yang, Peng, & Liu, 2019) (Table 1). 2-DG therapy may provide beneficial effects for patients with tumors or allergic airway inflammation by negatively regulating the polarization of M2 macrophages(Q. Zhao et al., 2017). Small molecule inhibitors of HK2 such as 3- bromopyruvate and ABT-737(J. H. Ha et al., 2018) show potential targeting options to inhibit the growth of ovarian cancer cells.

Table 1.

Targeting metabolic pathways in epithelial ovarian cancer

Pathway	Target	Drug	ID Number	Tumor types	Effect on Immune cells	Trial Phase	Summary	Results	Reference
Glycolysis	GLUT1	BAY-876		Ovarian cancer, lung cancer, head and neck cancer and pancreatic cancer	BAY 876 application results in CD4+ T cell proliferation and IFN-γ secretion.	Preclinical	Targeting of GLUT1 suppresses glycolytic metabolism and in vitro and in vivo ovarian cancer growth.		(Ma et al. 2018), (Tilekar et al. 2020)
	ETS1	Metformin	NCT01579812	Ovarian cancer	Metformin modulates the differentiation and activation of various immune-mediated cells such as CD4+ and CD+8 T cells.	Phase II	The objective of this study is to evaluate whether the combination of Carboplatin, Paclitaxel, and metformin in patients with advanced ovarian, primary peritoneal, or fallopian tube cancer will improve recurrence-free survival at 18 months compared to control groups.	Completed	(Brown et al. 2020), (Nojima and Wada 2023)
	HK2	2-DG		Ovarian cancer	2-DG negatively regulate on M2 macrophage polarization.	Preclinical	It shows cytotoxicity, reducing lactate production, and blocking the expression of drug resistance-associated proteins in ovarian cancer cells.		(Park et al. 2022), (Nojima and Wada 2023)
Fatty acid	FASN	Compound 34		Ovarian, prostate, lymphoma, lung, and breast	Activation and proliferation of various immune cells, such as T cells, B cells, and macrophages.	Preclinical	Compound 34 inhibits cell proliferation in multiple cancer cell lines including ovarian, prostate, lymphoma, lung, and breast.		(Lu et al. 2018)
		Cerulenin		Ovarian cancer	Cerulenin may enhance T cell activation and proliferation by promoting a shift in metabolic reliance from fatty acid oxidation to glycolysis. .	Preclinical	The FASN inhibitor cerulenin significantly inhibited FASN protein expression, stimulated apoptosis, and re-induced Platinum sensitivity in ovarian cancer cells.		(Bauerschlag et al. 2015),
	FAO (CPT1)	Etomoxir		Glioblastoma, Ovarian cancer	Etomoxir plays a significant role in T cell activation and differentiation, as well as in macrophage polarization.	Preclinical	Etomoxir combined with a CD47 blocker impairs tumor growth in glioblastoma patients.		(Jiang et al. 2022)
	HMGCR	Atorvastatin	NCT02201381	Ovarian cancer	It promotes cytotoxic T-cell activity and enhances the antitumor immune response, thereby leading to antitumor effects.	Phase 3	The purpose of this study is to evaluate the effectiveness of selected metabolic treatments for cancer patients in a real-world setting and to perform relationship study between the degree of response and changes in biochemical markers.	Recruiting	(Jones et al. 2017)
		Simvastatin	NCT04457089	Ovarian cancer	Simvastatin induces activation and proliferation of CD4+ T cells.	Phase 1	The study was conducted to assess the feasibility of a simvastatin intervention and to evaluate its effects on cancer progression in patients with Platinum-sensitive ovarian cancer treated with carboplatin and liposomal doxorubicin.	Recruiting	(Kato et al. 2010)
		Lovastatin	NCT00585052	Ovarian cancer	Lovastatin enhanced T-cell killing of tumor cells.	Phase 2	The purpose of this study is to determine whether the combination of Paclitaxel and lovastatin is more effective than the currently available chemotherapy for patients with refractory or relapsed ovarian cancer.	Terminated	(Liu et al. 2009)
	SOAT1	Avasimibe		Ovarian cancer	Avasimibe effectively regulate immune cell activity, in conjunction with other drugs, can enhance the antitumor effect.	Preclinical	SOAT1 inhibitor Avasimibe have ani-proliferative effect on different ovarian cancer cell lines.		(Ayyagari et al. 2020)
Amino acid	GLS1	BPTES		Ovarian cancer	BPTES treatment promoted pro-inflammatory M1-like activation of macrophages	Preclinical	BPTES combined with chemotherapy on drug resistant ovarian cancer cell lines.		(Masamha and LaFontaine 2018), (Yuan et al. 2016), (Shen et al. 2020), (Ma et al. 2022)
		IACS-6274	NCT05039801	Advanced Solid Tumors	IACS-6274 promote the cytotoxic activity of T cells and natural killer (NK) cells,	Phase 1	IACS-6274 With or Without Bevacizumab and Paclitaxel for the treatment of advanced solid tumors of patients.	Recruiting	(Glassman et al. 2023)
		CB-839	NCT03944902	Ovarian Cancer	Activates antigen–specific T cells, and improved tumor killing activity in an immune-competent mouse model of adoptive T cell therapy.	Phase 1	The purpose of this study is to investigate the efficacy of the combination treatment with Niraparib in patients with Platinum-resistant, BRCA-wild-type ovarian cancer patients.	Terminated	(Vander Heiden, Cantley and Thompson 2009)
		Compound 968		Endometrial Cancer	Compound 968 can increase CD3+ T cell infiltration into the tumor site.	Preclinical	Synergistic effects of Compound 968 and Paclitaxel were analyzed in ovarian cancer cell lines.		(Guo et al. 2023), (Wang et al. 2021)
		IPN60090	NCT03894540	Advanced Solid Tumors	IPN60090-mediated GLS1 inhibition increases the glycolytic activity of CD4+ and CD8+ T-cells.	Phase I	The purpose of study investigates the efficacy of IPN60090 as a single agent and in combination with Pembrolizumab or Paclitaxel in patients with advanced solid tumors and to evaluate food effect.	Completed	(Yap et al. 2021)
	xCT	Erastin		Ovarian cancer	Erastin regulate neutrophil activation.	Preclinical	Induce ferroptosis and overcome cisplatin resistance in ovarian cancer cell lines.		(Verschoor and Singh 2013)
		Sulfasalazine		Endometrial cancer	Sulfasalazine prevents T-helper 1 immune response by suppressing interleukin-12 production in macrophages.	Preclinical	Sulfasalazine treatment may be an effective strategy for circumventing glutathione-related chemotherapeutic drug resistance in endometrial carcer patients.		(Sendo et al. 2022),(Lee et al. 2020, Kang et al. 1999)
		Sorafenib		Ovarian, kidney, liver, and thyroid cancer	Sorafenib influence the activity of various immune cells, including T cells, dendritic cells, and natural killer (NK) cells.	Preclinical	Combination treatment of Bevacizumab and sorafenib in ovarian cancer patients with Platinum-resistant disease has promising clinical activity.		(Lee et al. 2020)
	Arginine deprivation	HuArgI (Co)- PEG5000		Ovarian cancer	It enhances the efficacy of immunotherapies by modulating the immune response.	Preclinical	Inhibits ovarian cancer cell adhesion and migration through autophagy-mediated inhibition of RhoA in ovarian cancer cell lines.		(El-Mais et al. 2021)
		ADI-PEG 20	NCT 00056992 NCT00450372 NCT03254732	HCC Melanoma Advanced Solid Cancers	Modulates T-cell activity and enhances the therapeutic efficacy of programmed death-1 (PD-1) inhibition.	Phase II Phase II Phase I	These drugs are tried as a monotherapy or in combination with other existing therapies in patients with different cancers.	Completed Completed Terminated	(Chu, Lai and Yeh 2023), (Chang et al. 2021)
	ASCT2	V-9302		CRC, lung cancer, TNBC, ovarian cancer	V-9302 strengthened CD8+ T-cells infiltration and activation and sensitize cancer to PD-1 blockade therapy.	Preclinical	Optionally combined with a PD1 blocker to inhibit different cancer cell line proliferation.		(Edwards et al. 2021), (Byun et al. 2020, Li et al. 2022)

The table shows details of different metabolic targets for ovarian cancer, ASCT2, amino acid transporter; HK2, Hexokinase 2; BPTES, bis-2-(5-phenylacetamido-1,2,4-thiadiazol-2-yl)ethyl sulfide 3; CRC, Colorectal cancer; CPT1, carnitine palmitoyltransferase 1; HCC, Hepatocellular carcinoma; ETS1, ETS proto-oncogene 1; HMGCR, HMG-CoA reductase (3-hydroxy-3-methyl-glutaryl-coenzyme A reductase ; SOAT1, Sterol O-Acyltransferase 1; FAO, fatty acid oxidation; 2-DG, 2-deoxy-D-glucose; FASN, fatty acid synthase; xCT;Cystine/Glutamate Antiporter, GLS, glutaminase; GLUT1, glucose transporter 1: PEG-ADA, PEGylated adenosine deaminase;, prostaglandin E receptor 2; TNBC, triple-negative breast cancer, USP14, ubiquitin specific peptidase according to ClinicalTrials.gov.

Metformin:

Glucose deprivation emerges as a potent antitumor treatment strategy as evidenced by the potential of antihyperglycemic drugs like metformin and rosiglitazone to diminish glucose availability to tumors, effectively starving them of nutrients (Hua et al., 2023). Metformin functions as an anticancer agent through both AMPK-dependent and independent pathways (Saini & Yang, 2018). Its primary target is mitochondria, where it impacts mitochondrial-related energy status, nucleotide metabolism, and oxidation state. Furthermore, these drugs exhibit direct effects on metabolic and signaling pathways that operate independently of glucose levels. Moreover, they have been shown to enhance the effectiveness of conventional chemotherapeutic agents such as cisplatin (Karimi et al., 2024)

Numerous clinical trials have been conducted to provide more definitive evidence of the anticancer effects of metformin, both as a single agent or in combination with chemotherapy. Preliminary result on metformin efficiency has been found to inhibit cell cycle arrest at the G2/M stage in ovarian cancer cells in Phase 2 clinical trial (Table 1) (NCT01579812) (Fu, Zhang, Wang, & He, 2017). Several completed early-stage clinical trials have been investigated the use of metformin in ovarian cancer patients (Broekman et al., 2020; J. R. Brown et al., 2020). Also, metformin influences the differentiation and activation of various immune-mediated cells, including CD4+ and CD8+ T cells (Nojima & Wada, 2023).

2.2. Pentose phosphate pathway

The pentose phosphate pathway (PPP) is the initial pathway in a series of pathways branching from glycolysis. This major glucose metabolic shunt is upregulated in several cancer cells including HGSOC, comprising both oxidative and nonoxidative phases essential for nucleotide synthesis in rapidly dividing cells (Giacomini, Ragazzi, Pasut, & Montopoli, 2020). Moreover, the PPP generates nicotinamide adenine dinucleotide phosphate NADP, crucial, for reductive metabolism and combating oxidative stress in tumor cells (J. Li et al., 2020). The PPP plays an essential role in supporting cancer cell survival and growth by generating pentose phosphate for nucleic acid synthesis and providing nicotinamide-adenine dinucleotide phosphate (NADPH), which is required for fatty acid synthesis and cell survival under stress conditions (Patra & Hay, 2014). Therefore, while glycolysis plays a significant role in providing energy, the PPP contributes to the biosynthesis of building blocks for rapidly proliferating tumor cells and redox homeostasis (Ge et al., 2020)

2.2.1. Dysregulated Pentose Phosphate Pathway

It has been shown that the expression of Glucose-6-phosphate dehydrogenase (G6PD) in tumor cells is higher compared with that in normal cells, and its expression is associated with lower survival rate in ovarian cancer patients (Sun, Suo, Li, Zhang, & Gao, 2018; H. C. Yang, Wu, Liu, Stern, & Chiu, 2016). Various studies have revealed the aberrant upregulation of G6PD in multiple types of cancer including ovarian cancer. Consequently, it influences many tumor-related biological processes such as cell cycle regulation, DNA synthesis, DNA repair, and anti-oxidative stress responses (X. Luo et al., 2023; Song, Sun, Zhang, & Shan, 2022; Wu et al., 2018). In addition, recent studies suggest that G6PD inhibitors have a significant effect on the reduction of tumor progression (Mele et al., 2018) and chemotherapy resistance (H. C. Yang et al., 2019). Thus, targeting G6PD with different approaches could pave the way for novel therapeutic targets for ovarian cancer. (Fig. 1).

2.2.2. Targeting Pentose Phosphate Pathway

G6PD overexpression has been associated with various types of cancer. G6PD serves as the pivotal rate-limiting enzyme in the PPP, playing a crucial role in cancer initiation and progression in HGSOC. G6PD is involved in promoting paclitaxel resistance by modulating the expression of glutathione S-transferase P1 (GSTP1), which contributes to chemotherapy resistance by detoxifying various anticancer drugs (Feng et al., 2020). Studies have primarily focused on two small-molecule inhibitors of G6PD,6-aminonicotinamide (6-AN) and dehydroepiandrosterone (DHEA) (Arbe et al., 2020; Mele et al., 2018). It was also demonstrated that 1 μM of 6-AN effectively suppresses G6PD. G6PD activity in paclitaxel-resistant ovarian tumor cells, leading to enhanced paclitaxel efficacy (Feng et al., 2020). This suggest that targeting this adaptive metabolic dependency could be a valuable approach for treating ovarian cancers.

Studies on human and mouse omental metastases, along with in vitro HGSOC models, have shown G6PD overexpression. Therefore, targeting G6PD has led to increased cell death within the omental microenvironment in vitro and reduced metastatic spread in vivo (Bose et al., 2022; Z. Wang et al., 2020). There are ongoing developments in G6PD inhibitors in preclinical and clinical stages, with some already being utilized as anticancer agents. Studies have demonstrated that the activation of STAT3 promotes ovarian cancer cell proliferation, colony formation, and resistance to Taxol by increasing G6PD expression and enhancing pentose-phosphate metabolism flux (Sheng, Feng, Quan, Sheng, & Zhang, 2022). Additionally, research has shown that in vitro established cisplatin-resistant spheroids exhibit elevated levels of G6PD and active glutathione. Furthermore, the administration of G6PD inhibitors with cisplatin effectively inhibited spheroid proliferation in vitro and significantly reduced peritoneal metastasis in mouse xenograft models (Yamawaki et al., 2021). However, the available G6PD inhibitors are notably scarce and limited. Wedelolactone, identified as a G6PD inhibitor, suggests that its mechanism involves the partial suppression of ovarian cancer by targeting G6PD(Z. Luo et al., 2021).

3. Lipid metabolism

Lipids play crucial roles in signal transduction, energy metabolism, and maintaining the structural integrity of cell membranes. However, an elevated levels of circulating lipids have been associated with the malignant progression of cancer, a phenomenon known as “lipotoxicity.” Lipotoxicity leads to oxidative stress, mitochondrial dysfunction, and impaired autophagy, which contribute to the progression of cancer (Yoon, Shaw, Haigis, & Greka, 2021). Lipids encompass a diverse group of biomolecules, mostly composed of fatty acids (FAs) and cholesterol. FAs, as the fundamental components of all lipids, can be classified into two main categories: unsaturated and saturated. FAs play a vital role in providing energy for the body and are essential components of different body membranes. Additionally, FAs act as secondary messengers in signaling pathways, contributing regulation of homeostasis and energy storage.

Recent studies have demonstrated that increased lipid uptake plays a crucial role in meeting increased energy demands of proliferating malignant cells (Y. Jin, Tan, Wu, & Ren, 2023). Furthermore, alterations in lipid metabolic genes have been observed in the early stages of ovarian cancer and tend to become more prevalent as the disease progresses. These findings emphasize lipid metabolism’s significance in supporting ovarian cancer’s growth and progression (Ji et al., 2020). Cancer associated alternations in lipid metabolism have been shown to impact tumor targeting immune responses.

3.1. Fatty acid metabolism

HGSOC cells exhibit distinct dysregulations, including alterations in FA transport, lipid biogenesis, storage and β-oxidation. Enhanced lipid accumulation in HGSOC patients significantly correlates with poor prognosis(Iwahashi et al., 2021). Recent studies highlight the crucial role of dysregulated fatty acid metabolism in the development and aggressiveness of ovarian cancer (Santos & Schulze, 2012). HGSOC relies on fatty acid oxidation and several inhibitors targeting FA metabolism that are currently in various stages of clinical trials. Thus, dysregulations in lipid metabolism, including alterations in key enzymes and pathways, play a crucial role in ovarian cancer pathogenesis. Lipid intermediates found in ascites and in fat containing cells of the omentum have been demonstrated to adversely impact T lymphocyte function. This impairment may inhibit the immune system’s anti-tumor activity (Dai, Song, & Di, 2020). Understanding and targeting these mechanisms could offer potential therapeutic strategies for improving patient outcomes. Therefore, targeting common FA enzyme pathways holds promise for finding a cure for ovarian cancer (Fig.2).

Figure 2.

Inhibitors of fatty acid metabolism in high-grade serous ovarian cancer

3.1.1. Targeting fatty acid metabolism

FASN inhibitors:

FASN is key enzyme involved in lipid synthesis, utilizing acetyl CoA derived from glucose metabolism to produce fatty acids such as palmitate. These fatty acids play a critical role in lipid signaling, cell proliferation, and triglyceride storage (Shah et al., 2006). Importantly FASN is upregulated in HGSOC, and its presence is associated with poorer prognosis and reduced survival rates in patients(Cai et al., 2015). Numerous studies have highlighted FASN inhibitors as potential therapeutic targets for ovarian cancer cells (Menendez & Lupu, 2007).

1. C75 and G28: C75 and G28 are pharmacologically derived synthetic inhibitors of FASN, have demonstrated the ability to reduce ovarian cancer cell growth in vitro and induce apoptosis(Veigel et al., 2015).

2. Cerulenin: FASN another inhibitor is cerulenin has shown efficacy in suppressing HER2/neu expression and inhibiting fatty acid biosynthesis in ovarian cancer mouse xenograft models, leading to increased survival rates (Menendez et al., 2004; Pizer et al., 1996)

3. C93 : Additionally, C93 small molecule FASN inhibitor has exhibited growth inhibition in carboplatin/paclitaxel-resistant ovarian cancer cells (Bauerschlag et al., 2015)

4. Compound 34: Compound 34 is a potent inhibitor of FASN and effectively inhibits the proliferation of A2780 ovarian cancer cells. This compound serves as a valuable in vivo tool that will enhance our understanding of FASN as a therapeutic target for cancer, obesity, and other human diseases (Lu et al., 2018)

Research has also identified miR-33b as a regulator of the TAK1/FASN/CPT1A/NF-κB pathway, impairing lipid metabolic activities and reducing the oncogenic properties of ovarian cancer cells (X. Wang et al., 2021). These findings collectively suggest that FASN is a promising ovarian cancer therapeutic target. Several FASN inhibitors are currently undergoing preclinical trials (Table 1).

ATP citrate lyase (ACLY) inhibitors:

ACLY is an essential enzyme that involved in the initial and rate-limiting step of de novo lipogenesis (Abramson, 2011; Zaidi, Swinnen, & Smans, 2012). It is frequently overexpressed in various tumor tissues, indicating significance in cancer biology. ACLY also serves as a link between glycolytic metabolism and lipid metabolism, highlighting the interplay between elevated glucose uptake and lipid metabolism in cancer cells(Granchi, 2018). It is often overexpressed in HGSOC, and its high expression correlates with poor clinical prognosis in patients. Genetic inhibition of ACLY by shRNA suppresses the proliferation of ovarian cancer cells(Y. Wang, Shen, Pang, Qiao, & Liu, 2012). Interestingly, knockdown of ACLY has been found to attenuate cisplatin resistance by inhibiting the PI3K-AKT pathway and activating the AMPK-ROS pathway(X. Wei et al., 2021). The overexpression of oxoglutarate dehydrogenase (OGDH) and ACLY in ovarian cancer has been associated with the ubiquitin-specific peptidase (USP13) (Han et al., 2016; G. Zhao et al., 2022) and genetic inhibition of USP13 has been shown to downregulate glucose oxidation, lipid biosynthesis, and oxidative phosphorylation, , thereby reducing the oncogenic potential of this aggressive disease(White et al., 2018). Bempedoic acid is the ACLY inhibitor developed from a long-chain hydrocarbon skeleton, inhibits lipid synthesis, and reduces non-high-density lipoprotein (HDL)-cholesterol in rats. Bempedoic acid has received FDA approval in 2020 as a lipid-lowering drug (Paton, 2020). These studies suggest that ACLY may serve as a potential therapeutic target in ovarian cancer.

Acetyl coenzyme A carboxylase (ACC) inhibitors:

ACC gene ACACA is frequently overexpressed in HGSOC and is often associated with a poor prognosis (Beckner et al., 2010). ACC plays a crucial role in inducing G0/G1cell cycle arrest and promoting apoptosis in ovarian cancer. This can be achieved by inhibiting ACC using the allosteric apoptosis in ovarian cancer by inhibition of TOFA and ND-246 (S. Li et al., 2013; Mukherjee, Wu, Barbour, & Fang, 2012). Additionally, ACC activity, influenced by metabolic signals such as increased AMPK activity, contributes to the resistance of ovarian cancer cells to chemotherapy(J. Yang et al., 2019).

Stearyl coenzyme A desaturase 1 (SCD1) inhibitors:

SCD1, an endoplasmic reticulum enzyme, plays a crucial role in converting mono-unsaturated fatty acids to saturated fatty acids, including oleats palmitolates(Koeberle, Löser, & Thürmer, 2016). Notably, SCD1 is overexpressed in various types of cancer(Falvella et al., 2002) (Fritz et al., 2010). SCD1 is also overexpressed in ovarian cancer stem cells(Roongta et al., 2011). Pharmacological inhibition of SCD1 has been shown to inhibit cell proliferation, particularly under conditions of limited exogenous lipids (von Roemeling et al., 2018). Study suggests that combining SCD1 inhibitors with ferroptosis inducers could provide a new, potentially effective, and less toxic treatment approach for ovarian cancer patients (Tesfay et al., 2019). Inhibition of SCD1 induces cellular stress and cell growth arrest, making it a potential cancer therapeutic target (Sen, Coleman, & Sen, 2023). Combinational treatment with SCD1/FADS2 inhibitors and cisplatin inhibitors and cisplatin synergistically repress tumor cell dissemination, offering a promising chemotherapeutic strategy against HGSOC peritoneal metastases (Xuan et al., 2022). SCD1 inhibitors emerge as a potential therapeutic option for treating ovarian cancer, highlighting SCD1 as a key regulator of cancer cell fate under metabolic stress and pointing to treatment strategies targeting lipid balance(G. Zhao et al., 2022).

Diacylglycerol O-Acyltransferase 1 (DGAT1) inhibitors:

DGAT1 plays a role in lipid toxification by catalyzing the conversion of diacylglycerol and fatty acyl-CoA to triacylglycerol. DGAT1 is overexpressed and is associated with poor patient survival in EOC patients (L. Xia, Wang, Cai, & Xu, 2021). However, DGAT1 as a potential target for ovarian cancer has not been studied. Recent studies demonstrated that shRNA mediated DGAT1 depletion halted lipid droplet formation, triggered tumor cell apoptosis, and significantly inhibited glioblastoma growth (X. Cheng et al., 2020). Thus, targeting DGAT1 potentialy could be a promising therapeutic approach for ovarian cancer.

Mitochondrial elongation factor 2 (MIEF2):

MIEF2 is essential in regulating mitochondrial fission. It is often overexpressed in ovarian cancer and leads to poor prognosis. MIEF2 may promote the progression of ovarian cancer by causing a shift in metabolism from OXPHOS to glycolysis (Furfaro et al., 2016). However, recent research has demonstrated that knockdown of MIEF2 levels by shRNA also significantly decrease free fatty acids, triglycerides, and cholesterol levels in ovarian cancer cell lines (S. Zhao et al., 2021). Therefore, MIEF2 can be a potential target for ovarian cancer.

3.2. Cholesterol metabolism

Cholesterol, a vital biomolecule, plays a crucial role in maintaining the structural integrity and fluidity of the plasma and cell membranes and serves as a precursor for essential compounds, , including vitamin D, bile acids, and steroid hormones(Rezen, Rozman, Pascussi, & Monostory, 2011). Cholesterol metabolism involves intricate processes. The initial step in cholesterol synthesis entails the conversion of acetate to mevalonate(Cerqueira et al., 2016). Acetyl-CoA, derived from mitochondrial glucose glycolysis, initiates this process. Subsequent synthesis steps occur in the endoplasmic reticulum (ER) and cytoplasm(Bloch, 1987). Dysregulated cholesterol homeostasis has been reported to enhance platinum resistance in HGSOC(Nieman et al., 2011)

3.2.1. Dysregulated cholesterol metabolism

Multiple, routes of cholesterol metabolism within cells have been identified, starting with the condensation of acetyl-CoA and acetoacetyl-CoA to form hydroxyl-methyl-glutaryl-coenzyme A (HMG-CoA). This process is catalyzed by HMG-CoA reductase (HMGCR/HMGR), the rate-limiting enzyme crucial for converting HMG-CoA to mevalonate (Goldstein & Brown, 1990). Mevalonate serves as a precursor for various compounds, including geranyl-pyrophosphate and farnesyl pyrophosphate, playing a role in the isoprenylation of intracellular G-proteins like Ras and Rho, regulating cell proliferation and apoptosis (Xu, Zhou, Tang, Xia, & Bi, 2020). The subsequent step involves the conversion of mevalonate to squalene, with mevalonate kinase transforming mevalonate into mevalonate-5-phosphate(Williamson & Kekwick, 1965). Through successive condensation reactions of activated isoprenes, squalene is produced with the assistance of squalene synthase. Further transformations are necessary for cholesterol synthesis, involving reactions catalyzed by squalene monooxygenase (SQLE) and lanosterol synthase. These enzymes facilitate the conversion of squalene into cholesterol through a series of successive reactions (Ačimovič & Rozman, 2013). Excess cholesterol is converted into cholesterol esters (CE) by acyl-CoA: sterol-O-Acyl transferase 1 (SOAT1) enzyme and is stored in lipid droplets (Long, Sun, Hassan, Qi, & Li, 2020). Multiple studies have provided correlative evidence supporting the involvement of cholesterol in cancer development and drug resistance in ovarian cancer (Criscuolo et al., 2020; Koeberle et al., 2016)

Recent studies have demonstrated the evidence of highlighting the significance of reprogrammed cholesterol metabolism in ovarian cancer. In studies conducted on a murine ovarian cancer model, mice subjected to a high-cholesterol diet exhibited increased tumor growth compared to control groups (S. He et al., 2019). The highly expressed proteins and enzymes involved in cholesterol metabolism play a pivotal role in promoting ovarian cancer progression. Cholesterol and its derivatives also contribute to proliferation and chemoresistance in ovarian cancer and play roles in shape the immunosuppressive tumor microenvironment(Goossens et al., 2019; Zheng, Li, Lu, Jiang, & Yang, 2018) (Fig 3).

Figure 3.

Inhibitors of cholesterol metabolism in high-grade serous ovarian cancer

3.2.2. Targeting cholesterol metabolism

HMG-CoA Reductase (HMGCR):

The oncogenic roles of HMGCR have been reported in different types of cancer, including gastric, liver, and breast cancers (Chushi et al., 2016; Dong et al., 2019; Göbel, Breining, Rauner, Hofbauer, & Rachner, 2019). HMGCR is also frequently overexpressed in ovarian cancer (de Wolf et al., 2017; Kato et al., 2010). Pharmacological inhibition of HMGCR using statin-like drugs has demonstrated effectiveness in suppressing cellular proliferation in monolayer and ovarian cancer spheroids, as well as inhibiting tumor growth in xenograft mouse models (Jones et al., 2017; Kato et al., 2010).

Statins are specific inhibitors of HMGCR, acting to block the mevalonate pathway (Istvan & Deisenhofer, 2001). Remarkably, the combination of statins with anti-PD1 antibodies has exhibited a more potent synergistic anti-tumor effect compared to individual treatments (Y. Xia et al., 2018). Therefore, statin-like drugs represent promising therapeutic options for ovarian cancer, as indicated by several conducted clinical trials (NCT0220138), (NCT04457089 and (NCT00585052) (Table 1). Notably, statins, particularly lipophilic statins, are clearly associated with a reduced risk of ovarian cancer occurrence(Akinwunmi, Vitonis, Titus, Terry, & Cramer, 2019).

Farnesyl-Diphosphate farnesyltransferase 1(FDFT1):

FDFT1 is recognized as an oncogenic enzyme, exerting its influence by promoting cell proliferation, elevating anti-apoptotic protein levels, and preventing ferroptosis by increasing squalene levels in specific cancer types. Conversely, it plays an anti-oncogenic role in ovarian cancers (N. T. Ha & Lee, 2020). There are several novel inhibitors of FDFT1 have been synthesized and isolated to mitigate cholesterol levels. These inhibitors can be categorized based on their structure (Wasko, Smits, Shull, Wiemer, & Hohl, 2011). The diverse range of inhibitors underscores ongoing efforts to explore FDFT1 as a potential therapeutic target in cancer treatment.

Squalene Epoxidase (SQLE):

SQLE is a crucial enzyme located in the endoplasmic reticulum, serving as a rate-limiting factor in the mevalonate pathway (Gill, Stevenson, Kristiana, & Brown, 2011). Recent studies have illuminated the overexpression of SQLE in ovarian cancer (D. N. Brown et al., 2016), with its high expression being correlated with poor progression-free survival (Gyorffy, Lánczky, & Szállási, 2012). The observed overexpression of SQLE has been linked to cellular protection from ferroptosis, suggesting that targeting SQLE could represent a novel approach for anti-tumor therapy(W. You et al., 2022). SQLE is now regarded as a potential target for the treatment of HGSOC, and its pharmacological inhibitor, terbinafine, shows promise as a targeted drug for this purpose (L. Ma et al., 2023). SQLE emerging as a promising novel therapeutic target in ovarian cancer treatment (Cirmena et al., 2018).

Sterol Regulatory Element-Binding Protein 2 (SREBP2):

SREBP2 functions as a key transcription factor regulating enzymes involved in cholesterol synthesis and transport (Eberlé, Hegarty, Bossard, Ferré, & Foufelle, 2004). Contrarily, despite its essential role in cholesterol homeostasis, SREBP2 has been implicated in enhancing chemotherapeutic drug resistance by upregulating cholesterol synthesis (Zheng et al., 2018). Moreover, SREBP2 plays a critical role in mediating ovarian cancer recurrence and promoting escape from cell cycle arrest following paclitaxel treatment (J. He, Siu, Ngan, & Chan, 2021). The expression of SREBP2 is regulated by the PI3K/AKT/mTOR signaling pathway(Düvel et al., 2010). SREBP2 knockout led to slower recovery rates of cell growth following paclitaxel treatment, compared to control cells (Xue et al., 2020). Therefore, targeting SREBP2 holds the potential to improve drug sensitivity and reduce the recurrence of ovarian cancer.

Sterol O-acyltransferase 1 (SOAT1):

SOAT1 is a membrane-bound enzyme that aids the esterification of cholesterol and fatty acids to cholesterol ester(Chang, Chang, Ohgami, & Yamauchi, 2006). The overexpression of SOAT1 has been observed in ovarian cancer (Ayyagari, Wang, Diaz-Sylvester, Groesch, & Brard, 2020). Avasimibe, an inhibitor of SOAT1 and a cholesterol-lowering drug, has demonstrated the ability to suppress ovarian cancer (Pal, Gandhi, Giridhar, & Yadav, 2013). As a result, various combined therapeutic strategies have been developed involving Avasimibe in combination with immunotherapies, including anti-PD1 antibodies, cancer stem cell-dendritic cell (CSC-DC) vaccines, and Kras peptide vaccines (X. Chen, Song, Xia, & Xu, 2017; Pan et al., 2019).

4. Amino acid metabolism

Amino acids are essential for protein synthesis and regulation of various cellular processes(Lieu, Nguyen, Rhyne, & Kim, 2020). Nine essential amino acids cannot be synthesized de novo and must be obtained from dietary protein. These include lysine, tryptophan, phenylalanine, methionine, threonine, isoleucine, leucine, valine, and histidine. On the other hand, non-essential amino acids can be synthesized within the body(Guedes et al., 2011). These are glycine, alanine, proline, tyrosine, serine, cysteine, asparagine, glutamine, aspartate, and glutamate. The metabolic networks of all amino acids are complex and highly interconnected (Z. Li & Zhang, 2016). Amino acids support the growth and proliferation of ovarian cancer cells (Z. Wei, Liu, Cheng, Yu, & Yi, 2020). Moreover, they have been implicated in immune responses against various types of cancer and associated with drug resistance in cancer therapy (Yoo & Han, 2022). Amino acid metabolism serves as an important mechanism through which resistant cancer cells acquire adaptive traits to counteract the effects of anticancer drugs (Zaal & Berkers, 2018). Amino acids are also involved in upregulated biosynthetic pathways and maintaining redox homeostasis balance (Z. Wei et al., 2020). Amino acids are required for proliferation under various stress conditions and serve as building blocks for protein synthesis, as well as substrates for glucose, lipid, and nucleic acid synthesis (H. X. Yuan, Xiong, & Guan, 2013). Amino acid metabolisms like glutamine and arginine are frequently dysregulated in HGSOC. These specific amino acids have gained significant interest in understanding cancer progression and in determining the most effective therapeutic approaches to target them (Fig. 4).

Figure 4.

Inhibitors of amino acid metabolism in high-grade serous ovarian cancer

4.1. Glutamine metabolism

Glutamine, a non-essential amino acid, plays a pivotal role in various cellular processes. It is involved in multiple biosynthetic pathways in proliferating cells, contributing to cell proliferation and energy production. Glutamine metabolism also contributes to the biosynthesis of hexosamine and certain non-essential amino acids (Hensley, Wasti, & DeBerardinis, 2013). Glutamine has been shown to have a crucial role in the biosynthetic pathways of proliferating ovarian cancer cells (J. Zhang, Pavlova, & Thompson, 2017). These highly proliferative cells can import or uptake glutamine via cell surface transporters. Notably, glutamine is specifically assimilated into cancer cells through a range of transporters, including system ASC (alanine/serine/cysteine) and the Na+-coupled neutral amino acid transporters (SNATs). Importantly, transporters such as ASCT2, SNAT1, SNAT2, and SNAT5 are frequently elevated in ovarian cancer cells (Bröer, Fairweather, & Bröer, 2018; Wise & Thompson, 2010)

Targeting individual steps of glutamine metabolism has exhibited promising outcomes in cancer treatment, leading to the identification of druggable targets and the advancement of anticancer drug candidates (Z. Wang et al., 2020). Many studies explored the role of glutamine metabolism in ovarian cancer and opened new avenues for targeting glutamine metabolism in ovarian cancer treatment. Recent studies have revealed a significant correlation between glutamine metabolism and the prognosis of ovarian cancer. It has been observed that many malignant tumors rely on glutamine metabolism called “glutamine addiction” for their survival(Wise & Thompson, 2010; Yu et al., 2021).

4.1.1. Dysregulated glutamine metabolism

Glutamine-addicted cancer cells depend on glutamine for viability, and their metabolism is reprogrammed for glutamine utilization through the Tricarboxylic acid cycle(TCA) (X. Yang, Li, Ren, Peng, & Fu, 2022). Cancer cells rely on glutamine for sustaining vital metabolic processes within the TCA cycle, which is commonly referred to as anaplerosis (Choi & Park, 2018). During this process, mitochondrial glutamate dehydrogenase 1 (GLUD1) plays a pivotal role by catalyzing the conversion of glutamate to alpha-ketoglutarate (α-KG). It is noteworthy that GLUD1 is frequently overexpressed in various cancer cell types, thereby promoting epithelial-mesenchymal transition and drug resistance (Q. Wang et al., 2022).

Glutaminase (GLS) is a rate-limiting enzyme that transforms from glutamine to glutamate. GLS is significantly overexpressed in ovarian cancer patients (L. Xia, Zhang, Wang, Zhang, & Nie, 2021). Its enzymatic activity is closely intertwined with critical aspects of tumor progression, including growth, angiogenesis, and immune response modulation (Masisi et al., 2020). Notably, GLS protein expression levels have been correlated with lower overall survival rates in ovarian cancer patients. Moreover, high-invasive ovarian cancer cells have been shown to rely heavily on glutamine for their survival in contrast to low-invasive cells, which exhibit independence from glutamine(Zhou et al., 2019). Studies have demonstrated that targeting glutamine metabolism alongside focal adhesion kinase exerts an additive inhibitory effect on the mammalian target of rapamycin (mTOR) pathway in spheroid cancer stem-like properties of ovarian clear cell carcinoma in vitro (Sato et al., 2017). Glutamine catabolism called glutaminolysis, begins with its conversion to glutamate, which is catalyzed by the GLS (Hassanein et al., 2013; Matés et al., 2013). Glutaminolysis significantly correlated with poor survival of ovarian cancer patients (Fasoulakis et al., 2023). Furthermore, the blockade of glutaminolysis has been found to enhance the sensitivity of ovarian cancer cells to PI3K/mTOR inhibition, with the involvement of STAT3 signaling pathways (Guo et al., 2016). The effects of glutamine blockade on the tumor microenvironment and explore strategies to maximize the utility of glutamine blockers as a cancer treatment (J. Jin, Byun, Choi, & Park, 2023). Studies also indicated glutamine metabolism, together with platinum-based chemotherapy, offers a potential treatment strategy, particularly in drug-resistant ovarian cancer (Hudson et al., 2016), An effective therapeutic strategy for involving alterations in the SWI/SNF complex, such as ARID1A mutations, is the pharmacological inhibition of glutaminase alone or combined with immune checkpoint blockade (Wu et al., 2021). Glutamine metabolism represents a promising target for ovarian cancer therapy, with various drugs showing potential efficacy.

4.1.2. Targeting glutamine metabolism

GLS1 inhibitors:

GLS has been overexpressed in HGSOC and correlates with poor survival outcome in patients(Cassago et al., 2012). GLS has been investigated extensively as a druggable target for ovarian cancer. The small molecule GLS inhibitors have been shown to exhibit anti-proliferative activity and reduce tumor burden (Fig. 3).

1. BPTES: bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl) ethyl sulfide (BPTES) is an allosteric inhibitor of GLS1 (Zimmermann et al., 2016). The study shows that BPTES treatment resulted in a significant reduction in the ability of glutamine-dependent ovarian cancer cells to form colonies(Haga & Ridley, 2016). By reducing cell growth, treatment with BPTES makes chemotherapy-resistant cancer cell lines susceptible to paclitaxel and cisplatin (Masamha & LaFontaine, 2018).

2. CB839: CB-839 has a small inhibitory effect on most tumors. However, it is showing synergistic effect on combining with other antitumor drugs. Multiple Phase I/II clinical trials have shown that CB-839 has well patient tolerance. Treatment of ovarian cancer mice using CB-839 prolongs the survival of the mice (L. Yuan et al., 2016). Studies also showed synergistic effects of CB-839 in combination with immune checkpoint inhibitor anti-PDL1 in an Arid1a-inactivated mouse ovarian cancer xenograft model(Wu et al., 2021). CB-839 was in a clinical trial combined with niraparib for patients having platinum-resistant ovarian cancer (NCT03944902). However, this study has been terminated.

3. Compound 968: The mechanism of allosteric inhibition of GLS1 by compound 968 differs from that of BPTES, as evidenced by distinct binding sites and maximal inhibition of GLS1 in its inactive state. Studies have revealed that compound 968 inhibits the growth of ovarian cancer cells by inducing G1-phase cell cycle arrest, promoting cell apoptosis, and inducing cellular stress. These findings suggest that targeting GLS1 represents a promising therapeutic strategy for ovarian cancer (L. Yuan et al., 2016).

4. V-9302: Glutamine transporter inhibitor, V-9302 a potent small molecule antagonist designed to target SLC1A5/ASCT2 (Schulte et al., 2018; X. Zhang et al., 2021).

5. DON (6-diazo-5-oxo-norleucine): DON competitively binds to the active site of glutamine, forming a covalent compound that irreversibly inhibits various metabolic enzymes that utilize glutamine, such as GLS, GS, and transaminase. Studies have shown that DON reduces the peritoneal adhesion of ovarian cancer in mice by inhibiting hyaluronan synthase activity (Kulkarni, Dakoulas, Miller, & Terse, 2017).

Recently, the new GLS1 inhibitor ACS-6274 has shown promising tolerability at biologically active doses, along with favorable pharmacokinetics in humans. It has also demonstrated significant pharmacodynamic target modulation and preliminary evidence of antitumor activity. A clinical trial (NCT03894540) is underway to evaluate rational combinations of ACS-6274 aimed to benefits for patients with ovarian cancer. Another GLS1 inhibitor IPN60090 has been also assessed both as a single agent and in combination therapies for patients with advanced solid tumors (NCT03894540)(Table 1).

Cystine/glutamate transporter cystine-glutamate exchange (xCT) inhibitors:

xCT also known as SLC7A11, is a key protein, plays a crucial role in promoting the synthesis of GSH (glutathione) and maintaining the intracellular redox balance. Notably, there are several inhibitors of xCT, including sulfasalazine, erastine, and sorafenib. The combination of erastine with docetaxel has been found to be an effective drug delivery method for patients with ovarian cancer who are resistant to chemotherapy(Dixon et al., 2014).

Alanine-serine-cysteine transporter 2 inhibitors:

The small molecule inhibitor L-Glutamyl-p-nitroanilide (GPNA) is known for its capacity to inhibit glutamine uptake and induce ROS enrichment through its binding to ASCT2. ASCT2 plays a key role in supplying compounds essential for tumor growth and progression, while also ensuring an ample energy supply (Choi & Park, 2018).

4.2. Arginine metabolism

Arginine is an essential amino acid with a positive charge that serves as a precursor for various important molecules such as amino acids, nitric oxide, polyamines, and creatine. It plays a significant role in tumor growth, proliferation, invasion, metastasis, and angiogenesis (L. Chen et al., 2023). The key enzymes in arginine metabolism include arginosuccinate synthase (ASS), arginosuccinate lyase (ASL), arginase, ornithine transcarboxylase(OTC), and the rate-limiting enzyme arginosuccinate synthetase 1 (ASS1), which catalyzes citrulline and aspartate conversion into arginosuccinate. These interconnected pathways promote tumorigenesis across various cell types (Keshet, Szlosarek, Carracedo, & Erez, 2018; Qiu, Huang, & Sui, 2015)

4.2.1. Dysregulated arginine metabolism

Arginine uptake into cells is facilitated by the cationic amino acid transporter Solute carrier family 7 (SLC7A1/CAT1) (Fay, Clegg, Uchida, Powers, & Ullman, 2014; Morris, 2007). Studies have shown that SLC7A1 is overexpressed in ovarian cancer and correlates with poorer survival rates and enhanced proliferation and migration (S. You et al., 2022). Conversely, discrepancies in ASS1 expression across ovarian cancer subtypes impact treatment responses and clinical outcomes (Delage et al., 2010; Dillon et al., 2004). However, arginine deprivation therapy’s efficacy shown potential treatment options for ovarian cancer(Ascierto et al., 2005; P. N. Cheng et al., 2007; Izzo et al., 2004; Morrow et al., 2013). Epigenetic modifications affecting ASS1 expression contribute to treatment resistance and disease progression (Allen et al., 2014)

Silencing ASS1 through epigenetic modification imparted ovarian cancer cells with resistance to platinum-based drugs resulting in treatment failure and clinical relapse in ovarian cancer patients(Nicholson et al., 2009). ASS1 impeded tumor angiogenesis, tumor proliferation and migration in vitro, further indicating that ASS1 might be a novel tumor suppressor (Huang et al., 2013). Moreover, nitric oxide synthesis, facilitated by arginine conversion via nitric oxide synthetase (NOS), plays a role in cancer cell proliferation, invasion, and drug resistance (Zou et al., 2020). Defective arginine synthesis, often associated with ASS1 deficiency, is common in cancer cells and offers insights into ovarian cancer pathophysiology. Metabolic reprogramming studies opens new avenue for diagnostic potential of metabolic biomarkers and treatment of ovarian cancer.

4.2.2. Targeting arginine metabolism

Preclinical investigations using pegzilarginase-mediated arginine degradation and patient-derived xenograft models highlight the potential of ASS1 as a diagnostic biomarker and target for precision medicine approaches in ovarian cancer (Agnello, Alters, & Rowlinson, 2020). Ovarian cancer cells treatment with HuArgI (Co)-PEG5000 also opens the way for further studies on the effect of arginine deprivation and autophagy induction on the migration of ovarian cancer (El-Mais, Fakhoury, Abdellatef, Abi-Habib, & El-Sibai, 2021).

Targeting arginine metabolism pathways holds promise for developing novel therapeutic strategies in ovarian cancer, with potential implications for other cancer types as well which still require more studies. The ASS1 expression levels in ovarian cancer cell lines are inversely correlated with the susceptibility to ADI-PEG20 is the basis of clinical trial (Cheon et al., 2015) (Fig. 4). The inverse correlation between ASS1 expression levels in ovarian cancer cell lines and susceptibility to ADI-PEG20 forms the basis for clinical trials, indicating a potential avenue for targeted therapy in ovarian cancer. The clinical trials for ADI-PEG20, specifically NCT 00056992 and NCT 00056992, have been completed in Phase 2. Additionally, NCT03254732 is currently in Phase 1 of clinical trials; however, it has unfortunately been terminated (Table 1).

5. Future directions

Metabolic alterations play a crucial role in the proliferation, metastasis, and treatment resistance of HGSOC. EOC cells sustain their rapid growth by increasing the uptake of glucose, amino acids, and lipids. Metastasis is facilitated by the utilization of nutrients and interactions within the microenvironment. Additionally, cancer cells undergo metabolic reprogramming in response to chemotherapy and targeted therapy. Numerous metabolic enzymes have been explored as potential targets for cancer therapy. However, the vulnerabilities of specific tumor types to inhibitors, whether used as single agent treatments or in combination with chemotherapy, radiation, targeted therapy, and immunotherapy, are still not fully understood. Targeting metabolism in ovarian cancer presents challenges due to potential adverse effects in patients. Most metabolic modulators developed lack specificity for cancer cells, which may result in toxicity to healthy tissues and potentially compromise immune functions. Moreover, current preclinical tumor models do not adequately reflect the metabolic and immunological diversity found in human tumors. Importantly, modern omics technologies can be employed to investigate potentially actionable metabolic liabilities in diagnostic biopsies HSOC patients. However, it is essential to recognize that several therapeutics commonly used in clinical cancer management may have significant metabolic effects in ovarian cancer. Nevertheless, advancements in targeted therapy and epigenetic modifications offer promising avenues for exploring new therapeutic strategies. Continued efforts are required to gain a deeper understanding of how ovarian cancer cells reprogram their metabolism to adapt in nutrient-deficient environments and develop chemoresistance. This, knowledge is vital for targeting these metabolic alterations, which can potentially synergize with other drugs and open new treatment options for ovarian cancer. Further research is required to unravel the complex mechanistic connections between ovarian cancer metabolism, and different targeting therapeutic options to treat this devastating disease.

It is also important to mention that ovarian cancer is a highly heterogeneous disease, characterized by significant variation in metabolic dependencies from one patient to another. This complexity underscores the necessity of developing novel therapeutic strategies that are personalized, rather than one-size-fits-all. By tailoring treatments based on each patient’s unique genetic makeup and specific tumor biology, we can enhance the efficacy of interventions, reduce resistance to therapy, and ultimately improve patient outcomes. Precision medicine, rooted in individualized approaches, holds the key to overcoming the challenges posed by the diverse nature of ovarian cancer.