IMR Press / FBL / Volume 28 / Issue 3 / DOI: 10.31083/j.fbl2803047
Open Access Review
Potential Therapeutic Targets in Ovarian Cancer: Autophagy and Metabolism
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1 Department of Medical and Biological Sciences, The Catholic University of Korea, 14662 Bucheon, Republic of Korea
2 Department of Biotechnology, The Catholic University of Korea, 14662 Bucheon, Republic of Korea
3 Department of Pathology, Yale University School of Medicine, New Haven, CT 06510, USA
*Correspondence: hyoon@catholic.ac.kr (Hyunho Yoon)
These authors contributed equally.
Front. Biosci. (Landmark Ed) 2023, 28(3), 47; https://doi.org/10.31083/j.fbl2803047
Submitted: 30 January 2023 | Revised: 18 February 2023 | Accepted: 1 March 2023 | Published: 10 March 2023
(This article belongs to the Special Issue Autophagy and Metabolism in Cancer)
Copyright: © 2023 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.
Abstract

Ovarian cancer (OC) is characterized by high mortality rates owing to late diagnosis and resistance to chemotherapy. Autophagy and metabolism play essential roles in the pathological process of cancer and have recently been proposed as potential targets for anticancer therapies. Autophagy is responsible for the catabolic clearance of functionally misfolded proteins and plays different roles depending on the stage and type of cancer. Thus, understanding and controlling autophagy is relevant for treating cancer. Autophagy intermediates can communicate with each other by providing substrates for glucose, amino acid, and lipid metabolism. Metabolites and metabolic regulatory genes modulate autophagy and influence the immune response. Therefore, autophagy and the functional manipulation of metabolism during starvation or overnutrition are being investigated as potential therapeutic targets. This review discusses the role of autophagy and metabolism in OC and highlights effective therapeutic strategies targeting these processes.

Keywords
ovarian cancer
autophagy
metabolism
metabolites
cancer therapeutics
1. Introduction

Ovarian cancer (OC) is a malignant tumor that develops in the ovary and is the most lethal among female genital cancers [1]. Most cases are closely related to heredity, which is mainly caused by mutations in genes such as BRCA1, BRCA2, BRIP1, RAD51C, and RAD51D. Epithelial ovarian cancer (EOC) is a type of cancer that arises from the tissue covering the ovary. EOC is the most common cause of gynecological cancer-related death and usually occurs in postmenopausal women [2]. BRCA1/2 germline mutations are the strongest known genetic risk factors for this type of cancer. In fact, these mutations are found in 6–15% of women with epithelial ovarian cancer. Knowing a patient’s BRCA1/2 status can be useful for counseling regarding expected survival. Studies have shown that BRCA1/2 carriers respond better than non-carriers to platinum-based chemotherapies, which are commonly used to treat ovarian cancer. As a result, carriers of BRCA1/2 mutations have a greater chance of survival, even though the disease is generally diagnosed at a later stage and higher grade [3]. Depending on their origin, ovarian cancers are classified into three types: epithelial, germ cell, and sex cord-stromal cancers [2]. Ovarian carcinosarcoma is known as malignant mixed Müller tumor. Ovarian carcinosarcoma is rare, biphasic consisting of epithelial and sarcoma components, accounting for only 1–4% of all ovarian cancers. Their prognosis is dismal, and most patients relapse within 1 year of completing initial treatment [4]. OC is difficult to treat due to ineffective screening strategies and delayed diagnosis [5]. CA-125, a serum molecule, is commonly used as an OC diagnostic biomarker [6]. Currently, promising biomarkers discovered by proteomic analysis include transferrin and apamin, which are potential secondary markers for CA-125 [7]. Recent proteomics analyses provide new treatment options that may reduce resistance to drug treatment in ovarian cancer, potentially improving patient outcomes [8]. However, these biomarkers still have limited sensitivity and specificity, which are insufficient for early OC detection [9]. Therefore, no single test or method is currently capable of the early diagnosis of OC.

OC can be highly dispersed after it arises from the primary site. OC metastasis is controlled by various cellular pathways and factors in the tumor microenvironment (TME) [10]. Tumor cells must change shape to migrate from where they originated, which explains why tumors that undergo epithelial-mesenchymal transition (EMT) can easily become more malignant [11]. A comprehensive understanding of the pathways involved in cancer development may be a key to cancer treatment. In particular, in EMT, various signaling pathways, such as transforming growth factor-β (TGF-β), Notch, Wnt/β-catenin, and PI3K-AKT-mTOR act as regulators [12, 13]. Dysregulation of these signaling pathways is critical for cell survival, growth, and proliferation in tumorigenesis, providing clinically useful targets for effectively enhancing OC survival [14, 15, 16, 17].

Autophagy is an intracellular degradation system that eliminates damaged organelles and misfolded proteins to maintain cell’s biological functions and homeostasis [18]. Autophagy removes damaged material and recycles it to create new building blocks or convert it into an energy source [19]. To date, three types of autophagy have been studied: macroautophagy, microautophagy, and chaperone-mediated autophagy. As macroautophagy has been the most widely studied, the term “autophagy” usually refers to macroautophagy. The autophagy system has a central lysosome containing more than 60 luminal hydrolases involved in the PI3K-AKT-mTOR, Ras-Raf-MAPK, TP53, and Beclin1 pathways, which play essential roles in cancer progression and metastasis [20, 21]. These findings suggest that cancer may be associated with autophagy dysregulation [21, 22]. Therefore, autophagy-mediated pathways may be potential targets for cancer-targeted therapies.

Cancer cell metabolism plays a crucial role in cancer progression and survival. As the persistent uncontrolled proliferative signal is one of the common cancer features, metabolic processes can promote cancer cell proliferation and motility [23]. Metabolic processes and their metabolites provide energy for uncontrolled growth through necessary nutrients and components that can modulate the expression of specific genes and proteins involved in tumorigenesis [24]. This review discusses the importance of autophagy and metabolism, including glucose, amino acid, and lipid metabolism in OC and the clinical potential of targeting these cellular processes in OC therapy.

2. Autophagy in Cancer

Autophagy plays various physiological roles and consists of several steps. Autophagy begins in preautophagosomal structures and templates the size and shape of the phgophore according to its cargo [25]. One of the major degradation mechanisms of autophagy is mediated by unique organelles called autophagosomes, which are double-membrane vesicles containing cytoplasmic components [26]. Autophagosomes can derive membranes from multiple sources, including the endoplasmic reticulum, Golgi apparatus, and plasma membranes [27]. Autophagy-related protein 8 (ATG8) on the surface of the autophagosome is removed by ATG4 and Ymr1, leading to autophagosome maturation [28]. After maturation, vesicles fuse with lysosomes or endosomes to form autophagolysosomes, and the cytoplasmic material is degraded by the catalytic activation of lysosomal hydrolases [29]. The fusion of autophagosomes and lysosomes is affected by soluble N-ethylmaleimide-sensitive-factor attachment protein receptor (SNARE) proteins, Rab family proteins, phosphoinositide 3-kinase (PI3K) complex, and Rubicon [30]. In particular, Rubicon is related to an increase in nonalcoholic fatty liver disease (NAFLD) by influencing the autophagosome-lysosome fusion stage [31].

As excessive self-consumption can be detrimental to the cell, autophagy is controlled by a series of proteins known as Unc-51-like kinase 1 (ULK1) and 2 (ULK2), which form complexes with ATG13, ATG101, and focal adhesion kinase (FAK) family kinase-interacting protein of 200 kDa (FIP200), which plays critical roles in autophagy initiation [32]. Autophagy is mainly regulated by the AMPK and mTORC1 patways. Autophagy is activated by AMPK when cells are in nutrient deprivation or oxidative stress. In contrast, mTORC1 inhibits autophagy by reducing UKL1 activation under nutrient-rich conditions [33, 34]. As such, autophagy is regulated to maintain normal cell homeostasis (Fig. 1).

Fig. 1.

Signaling pathways regulating autophagy. mTOR signaling is involved in the autophagy process, which is controlled by PTEN that is regulated by p53. Inactivated mTOR enhances autophagosome initiation through the ULK1 complex and the class III PI3K complex. In cancer cells, LC3-II is a protein attached to the autophagosome and is a marker of autophagy activity. mTOR-mediated complexes can be potential clinical targets. AMPK, AMP-activating protein kinase; FIP, FAK family kinase-interacting protein of 200 kDa; PTEN, Phosphatase and Tension Homolog; ULK1, Unc-51-like kinase 1; VPS24, Vacuolar protein sorting 24.

In cancer, autophagic processes are closely related to apoptosis and cell survival and can act as a double-edged sword [35, 36]. Several studies have revealed that the role of autophagy differs according to the stage of tumor development. Autophagy is a tumor suppressor in the early stages of tumorigenesis and can promote tumor progression in advanced stages [35]. Autophagy is mainly inhibited by the PI3K-AKT-mTOR axis, promoting the expression of various tumor suppressors, such as LKB1, TSC, and p53 [37, 38]. Beclin1 is deleted in several tumor types and is a tumor suppressor in mice [39]. In addition, depletion of the BECN1 gene encoding Beclin1 restricts tumor cell growth and metastasis in several cancers, including ovarian and breast cancers [40]. Conversely, tumor cells may be more dependent on autophagy for their survival. Autophagy plays an important role in tumor progression and is essential for tumor cell survival by RAS activation [41, 42]. Autophagy also promotes EMT and metastasis under starvation conditions [43, 44]. These studies indicate that effective regulation of autophagy in cancer can be a promising strategy for cancer treatment.

3. Metabolism in Cancer
3.1 Glucose Metabolism

Glucose synthesizes adenosine triphosphate (ATP), an essential energy source for most cells, including cancer cells. The absorbed glucose is converted into pyruvate by glycolysis. Under normoxic conditions, pyruvate enters the mitochondria and generates approximately 38 ATP molecules via the tricarboxylic acid (TCA) cycle. However, when oxygen is insufficient, pyruvic acid is converted to lactic acid, and only 2 ATP molecules are produced through anaerobic glycolysis. A completely different phenomenon occurs in tumors, called the Warburg effect (Fig. 2). Tumor cells use a less efficient process of ‘aerobic glycolysis’ despite having sufficient oxygen, to gain energy faster [45]. As markedly increasing glucose is a prominent feature of cancer, targeted cancer therapy is possible using the glucose analog radiotracer 18 fluoro-2-deoxy-D-glucose (FDG) [45].

Fig. 2.

Crosstalk between OC cells and metabolic reprogramming. Most cancer cells, including OC, increase glucose uptake and lactate production, which is called the Warburg effect. Aerobic glycolysis, glutamine catabolism, and lipid and nucleotide synthesis, support cell growth, migration, invasion, and metastasis in OC, which are potential clinical targets in OC treatment.

3.2 Amino Acid Metabolism

Amino acids are basic nutrients required to produce proteins necessary for tumor progression. Amino acids can be classified as essential and non-essential, both involved in cancer development. Cancer cells can settle the structure by the biosynthesis of proteins and nucleic acids, participate in redox reactions to alleviate oxidative stress and contribute to immune evasion [46, 47]. Unlike non-essential amino acids (NEAA) that are acquired through most cellular systems, essential amino acids are acquired by dietary intake. Branched-chain amino acids (BCAAs), such as leucine, isoleucine, and valine, can not only promote protein synthesis and oxidation, but also interact with the mTOR pathway during tumor growth, eventually leading to nucleotide synthesis [48, 49]. In particular, leucine, the most abundant amino acid, can trigger mTORC1 signaling by activating the sensor protein Sestrin2 [49, 50]. In addition, Sestrin2 inhibits mTORC1, which is strongly associated with cell growth and is regulated by protein/lipid synthesis and autophagy [49, 51, 52]. BCAAs can be beneficial in providing nitrogen and carbon groups, supplement energy, epigenetic modulation, and lipogenesis [46, 53]. In addition, BCAA metabolism can be a carbon frame for fatty acids and control fatty acid oxidation (FAO) [54]. Thus, upregulated BCAA can induce tumor growth, implying that BCAA-mediated metabolism may be an important target for cancer therapy.

Glutamine is an amino acid required for the proliferation of cancer cells because it contributes to the biosynthesis of various proteins, lipids, and nucleic acids by supplying carbon and nitrogen [46, 55]. Glutamine serves amide nitrogen of asparagine and can be converted to glutamate [53]. Some NEAAs like alanine, aspartate, and phosphoserine can be produced from glutamate [53]. Glutamine requirements in cancer cells are increased primarily through amino acid transporters such as alanine/serine/cysteine (ASC) [46]. Some types of cancer experience ‘glutamine addiction’, requiring glutamine for survival and relying on glutamine supplementation and new TCA cycles [46, 56]. Glutamine can also function in mTORC1pathway by promoting the outflow of essential amino acids and glutamine catabolism, thus inhibiting autophagy [57].

3.3 Lipid Metabolism

Lipids are efficient energy sources composed of fatty acids (FAs), triacylglycerols (TGs), waxes, phospholipids, sphingolipids, and isoprenoids. FAs are the major form of energy storage and are composed of TGs and glycerol [58]. FAO provides more usable energy, such as high-energy phosphates. Additionally, the degradation of lipids stored in lipid droplets (LDs) can be utilized through lipolysis and autophagy [59]. In cancer cells, lipid metabolism is regulated for membrane construction and energy storage, making second messengers for signaling pathways and providing ATP with FAO when more energy is required [60]. Therefore, de novo synthesis of FAs can be activated for tumor growth even under harsh conditions. Lipogenesis-related enzymes such as ATP citrate lyase, acetyl-CoA carboxylase, and fatty acid synthase are commonly overexpressed in tumors and can promote cell proliferation and survival [59, 61]. FAO can also modulate metabolic oxidative stress dealing with reactive oxygen species (ROS) in tumors [62]. Monoacylglycerol lipase converts monoacylglycerol to free fatty acids and glycerol during tumorigenesis, which may enhance the population of highly advanced cancer cells via the EMT [60, 61].

4. Autophagy in OC

Dysregulation of autophagy in OC is caused by factors [63], such as mutation of LC3 and Beclin1; tumor suppressors PTEN and p53; and growth factor pathways, PI3K-AKT-mTOR. LC3 are often lowly expressed in malignant cells, preventing the accumulation of LC3-marked autophagosomes in aggressive OC [64]. In addition, deletion of Beclin1, a tumor suppressor gene, was found in more than 50% of OCs [65], suggesting that the upregulation of LC3 and Beclin1 can be an effective treatment for OC. Overexpression of p53 inhibits autophagy, and the PI3K-AKT-mTOR axis upregulation activates autophagy by inactivating PTEN in OC cells [66, 67]. These results demonstrate that p53 and PTEN can be important regulators of autophagy in OC.

The TME affects tumor cell growth, metastasis, and immunity [68]. Direct or cytokine-mediated interactions between cancer cells and TME components promote tumor growth and metastasis [69, 70, 71]. The TME response to stressors, such as hypoxia and inflammation, responses tumor initiation and development. The interaction between the TME and autophagy in tumor cells can promote tumor development by protecting cells from stressors.

Various inflammatory factors in TME can induce autophagy. In TME, the cytokine IL-6 secreted by cancer-associated fibroblasts (CAFs) accumulates in the ascites of OC [72]. IL-6, which is associated with the invasiveness and metastasis of OC cells, induces autophagy by phosphorylating the signal transducer and the activator of transcription 3 (STAT3), inducing the expression of NS5ATP9 [73, 74]. In addition, lysophosphatidic acid (LPA), abundantly secreted from the TME of OC, increases the aggressiveness of OC and inhibits autophagy [75, 76], suggesting that even cytokines that induce aggressiveness in OCs may act differently in regulating autophagy.

5. Crosstalk between Autophagy and Metabolism in OC

Autophagy and metabolism commonly supply energy and nutrients to cells. Autophagy is strongly associated with cancer cell metabolism by maintaining cell metabolic processes [77]. For example, tumor cells increase glycolysis to obtain the necessary metabolic intermediates through mitochondrial metabolism [78]. To maintain mitochondrial metabolism, autophagy degrades membrane organelles to provide substrates, such as glycogen, amino acids, and lipids, suggesting that autophagy-mediated metabolites alter cancer cell function in OC (Fig. 3). In addition, autophagy itself is regulated by metabolic hormones and participates in cellular homeostasis by recycling metabolites [79].

Fig. 3.

Autophagy-mediated metabolism in OC. Autophagy and metabolic processes interact through the regulation of several proteins and signals. Under glucose deprivation, HK-II-mediated inhibition enhances the autophagy process by enhancing LPA and HIF1α. Free fatty acid-mediated AMPK activation also increases lipophagy. mTOR activation with α-KG reduces autophagy by regulating proteins, such as NO and citrulline. In lipid metabolism, lipophagy is reduced by the lipolysis of lipid droplets. HK-II, hexokinase-II; LPA, lysophosphatidic acid; HIF1α, hypoxia-inducible factor 1-alpha; AMPK, AMP-activating protein kinase; NO, nitric oxide; LD, lipid droplet; Arg, Arginine; α-KG, alpha-ketoglutarate.

5.1 Interaction between Autophagy and Glucose Metabolism in OC

Glucose metabolism plays an essential role in autophagy-regulated glycolysis in cancer cells. As mentioned above, glucose deprivation stimulates autophagy through AMPK activation and mTORC1 inactivation. In contrast, excess nutrients inhibit autophagy [80]. Conversely, activation of glucagon in the liver activates cyclic adenosine monophosphate (cAMP) production, which stimulates autophagy [81]. AMPK, induced under starvation, can stimulate the phosphorylation of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) to promote glycolysis [82]. GAPDH forms a complex with Rheb, and hexokinase-II (HK-II) inhibits mTOR by binding to mTORC1 [83]. These results imply that autophagy can be induced by HK-II-mediated mTOR inactivation. However, inhibition of HK-II promotes apoptosis under glucose-starvation conditions [83]. LPA, which is abundant in ascites, stimulates aerobic glycolysis in OC [84] and increases hypoxia-inducible factor 1-alpha (HIF1α) levels via Rac1-NOX-ROS signaling, upregulating the expression of HK-II and consequently leading to a glycolytic shift in OC cells [85]. Treatment with 3-bromopyruvate, an inhibitor of HK-II, significantly reduced tumor burden in an OC mouse model [84, 86], suggesting that aerobic glycolysis regulated by HK-II may be a therapeutic target for OC.

5.2 Interaction between Autophagy and Amino Acid Metabolism in OC

Amino acids are essential for the synthesis of proteins, nucleic acids, and lipids, which are important for cancer growth [87]. Amino acids and their metabolites play key roles in regulating mTORC1 and inhibiting autophagy [88]. In general, extracellular glutamine is critical for the survival of many tumor cells [89]. Interestingly, low-invasive OC cells are glutamine-independent for glucose metabolism, whereas highly invasive OC cells are glutamine-dependent [89]. Glutamine, metabolized by glutaminase (GLS), produces glutamate and ammonia. Glutamate is oxidatively deaminated by glutamate dehydrogenase (GLUD1) and converted to α-ketoglutarate (α-KG), a TCA cycle-replenishing substrate [90, 91]. In highly invasive OC cells, inhibition of the TCA cycle by glutamine reduces tumor cell invasiveness, whereas adding α-KG restores the invasive ability of OC cells [89]. Since α-KG is known to inhibit autophagy, whereas ammonia has been reported to induce autophagy [92, 93]. Thus, balance between ammonia and α-KG is important for the regulation of autophagy in OC.

Cancer cells also use arginine to grow and migrate [94]. Arginine depletion by arginine deiminase (ADI) inhibited the mTORC1 pathway to induce autophagy in many cancer cell types [95]. The arginine metabolites, nitric oxide (NO) and citrulline, can also inhibit autophagy by activating mTORC1 [96]. Arginine deficiency induces autophagy and poor viability in OC cells, suggesting that autophagy is important for tumor survival under stress [97, 98]. Rag GTPases are heterodimeric complexes composed of activated forms of Rag A/B and inactivated forms of Rag C/D, enhancing mTORC1 activation [99, 100]. Activation of Rag A/B requires CASTOR1, a homodimer or heterodimer of CASTOR1 and CASTOR2. Arginine can directly bind only to CASTOR1. Consequently, the CASTOR1–CASTOR2 complex is disrupted, leading to mTORC1 activation [101, 102]. Given that arginine can be an amino acid sensor to inhibit autophagy [103], joint targeting of autophagy and metabolic processes in mTORC1-activated cells can be a promising anti-OC strategy.

5.3 Interaction between Autophagy and Lipid Metabolism in OC

Lipid metabolism and autophagy interact during cancer progression. Lipophagy, an autophagy process, is a conserved secondary mechanism of lipid breakdown and alternative energy sources when nutrients are scarce [104, 105]. Lipids degraded by lipophagy are stored in LDs to provide the necessary energy to growing tumors [59]. During starvation, stored lipids are broken down to release free fatty acids, which are an efficient source of energy [59]. Acetyl coenzyme A (Acetyl-CoA), nicotinamide adenine dinucleotide (NADH), and flavin adenine dinucleotide hydroquinone (FADH2) produced by FAO can generate ATP to provide energy in a hypoxic tumor environment [59]. Increased FAO ratios in OC contribute to cisplatin resistance. Cisplatin, a platinum-based drug, is widely used for OC chemotherapy [106, 107]. These results suggest that supplemental and increased lipid storage of LDs is beneficial for proliferation and resistance in OC.

Lipophagy can be a double-edged sword that plays a role in cancer progression or inhibition. Lipid catabolism can be regulated by transcription factors, such as lysosomal acid lipase (LAL), or forkhead homeobox protein O1 (FOXO1) [108, 109], which control immature myeloid-derived suppressor cells (MDSCs). Increased MDSCs were known to regulating the immune response and promote tumor cell angiogenesis, invasion, and metastasis [110]. In contrast, LAL acts as a tumor suppressor to reduce the metastasis of lung and liver cancers [111]. Therefore, a comprehensive understanding of autophagy and lipid metabolism is essential, which may lead to new anticancer therapies for OC patients.

6. Crosstalk between Autophagy/Metabolism and Immune Cells in OC

Autophagy and metabolic processes in cancer cells are strongly associated with the immune system. Avoiding the immune destruction of cancer cells is a novel feature of cancer. Immune cells in the TME play an important role in OC [23]. EOC, an immunogenic tumor, is strongly associated with tumor-infiltrating lymphocytes (TILs) [112]. Several studies have shown the association between TIL and survival in OC, where patients with TIL were more likely to have a favorable outcome [113, 114]. However, response rates are only 10–15%, with drug resistance developing in early clinical trials, and no immune checkpoint inhibitors are currently approved by the FDA [115]. Since PD-L1 expression is rare in EOC, it is necessary to further investigate potential predictive biomarkers for immune checkpoint inhibitors and elucidate the key mechanisms regulating immune suppression in EOC. Phosphatase and tensin homolog (PTEN) is a protein and lipid phosphatase known to act as a tumor suppressor and an autophagy regulator gene [72, 116]. In OC, the inactivation of PTEN generally activates the PI3K-AKT signaling pathway, which inhibits T cell invasion [117]. In addition, PTEN can trigger the recruitment of immune cells such as natural killer (NK), dendritic (DCs), and T cells for antitumor immunity [118].

PTEN is also closely related to regulators of autophagy and metabolic processes. Inhibition of PI3K-AKT signaling by PTEN inhibits the mTOR pathway, which can regulate autophagy-sensing metabolic conditions [72, 119]. Further studies using PTEN transgenic mice demonstrated that PTEN induced an “anti-Warburg effect”, which is highly related to glucose metabolism [116, 120]. PTEN regulates the expression of glucose transporter 1 (GLUT1) in the plasma membrane by inhibiting AKT to reduce glucose uptake in OC [121]. These results suggest that various immune cells can be regulated by autophagy and metabolic processes via PTEN. Thus, loss of PTEN is relevant to the immune evasion of cancer cells including OC.

In addition, the interaction between programmed cell death-ligand-1 (PD-L1), mainly produced by macrophages, and programmed cell death-1 (PD-1) from lymphocytes is related to the immune processes in cancer [116, 122]. PD-L1 and PD-1 are well-known immune checkpoint inhibitors. In particular, PD-L1 regulates glucose metabolism in sarcomas and affects autophagy by activating mTORC1 in OC [123]. In general, PD-L1 negatively regulates T-cell function and is expressed in most tumor cells in the TME. One of the distinctive features of PD-L1 is the suppression of immune responses, especially in OC, where increased PD-L1 promotes the AKT-mTOR pathway for cell proliferation and induces BECN1-induced autophagy [124]. In patients with invasive EOC, high PD-1 and PD-L1 expression leads to beneficial survival outcomes [114, 122], suggesting that immune checkpoint inhibitors can modulate the proportion of immune cells in OC, which may include autophagy and metabolic processes.

7. Autophagy and Metabolic Targeted Therapy in OC

Correlation of autophagy and metabolism is critical in anticancer therapy since autophagy is a major contributor in cellular metabolism regulating metabolic homeostasis [81]. Therapeutic strategies targeting autophagy and metabolism are still being evaluated in several clinical and preclinical trials for OC (Table 1, Ref. [125, 126, 127, 128, 129, 130, 131]). Rapamycin, a well-known autophagy activator, affects the translational initiation of OCs via the mTORC1 pathway and eukaryotic translation initiation factor 4E (elF4E) [132]. Although rapamycin efficiently inhibits the activity of mTORC1 serine/threonine kinase, its clinical use has not been successful because of its low water solubility. Therefore, other effective mTORC1 inhibitors are being screened for regulating autophagy [133]. Bortezomib also inhibits autophagy by reducing cathepsin levels in OC and is particularly effective when combined with cisplatin [125]. Cisplatin is a classic platinum-based chemotherapy for OC. The fundamental mechanism of cisplatin is to bind DNA in the nucleus to hinder its transcriptional or replicational functions, resulting in cell death [134]. Although cisplatin has therapeutic properties, it can function synergistically with other therapies. In addition, combinations of PARP inhibitors with conventional chemotherapeutic agents that induce DNA strand breaks are also being considered. Given that inhibition of PARP in normal cells abolishes important mechanisms of DNA repair in these cells, chemotherapy-induced myelosuppression is enhanced. As such, a major concern with this multimodal treatment approach is the high risk of overlapping myelotoxicity. Consequently, dose adjustment of both regimens is recommended [135].

Table 1.Inhibitors targeting autophagy and metabolism in OC.
Cellular target Drug Function FDA-approval Reference
Autophagy Rapamycin Inhibits PI3K-AKT-mTOR signaling pathway Yes [128]
Bortezomib Inactivates proteasome active sites Yes [125]
Elaiophylin Arrests autophagic flux by alleviating lysosomal cathepsin activity No [126]
Danusertib Suppresses aurora kinase to induce apoptosis No [127]
Metabolism Daporinad Inhibits NAMPT No [129]
Triapine Downregulates RNR and sensitizes OC to PARP inhibitors No [130]
Pemetrexed Antimetabolite that represses thymidylate synthase Yes [131]
NAMPT, nicotinamide phosphoribosyltransferase; RNR, ribonucleotide reductase; PARP, poly (ADP-ribose) polymerase.

Elaiophyllin, another autophagic inhibitor, induces cell death in OC [126]. Elaiophyllin also directly induced apoptosis in vivo and sensitized an animal OC model to cisplatin [127]. Danusertib is an inhibitor of the aurora, a kinase that is essential for cell proliferation. Danusertib induces cell cycle arrest and autophagy by inhibiting the PI3K-AKT-mTOR signaling pathway in OC cell lines [127]. Notably, it inhibits the PI3K-AKT-mTOR signaling pathway in OC cell lines, leading to induced cell cycle arrest and autophagy, which ultimately inhibits cancer metastasis by reducing EMT through the vimentin regulation [127].

Metabolic modulators, such as daporinad, triapine, and pemetrexed, have been evaluated in patients with OC. Daporinad (APO866, FK866) is a nicotinamide phosphoribosyltransferase (NAMPT) inhibitor that affects more resistant cells than sensitive cells upon deprivation of NAD+ metabolic synthesis [136]. Moreover, carboplatin and daporinad combined showed better results in inhibiting resistant cell proliferation in OC [136]. Although daporinad has a feasible anticancer ability, it has failed in phase I/II clinical trials [137]. Triapine (3-aminopyridine-2-carboxaldehyde thiosemicarbazone), a small-molecule inhibitor, inactivated ribonucleotide reductase (RNR) to downregulate nucleotide metabolism [138]. Interestingly, continuous treatment with cisplatin followed by triapine showed a synergistic effect, whereas concurrent treatment with triapine and cisplatin showed an inverse correlation [138]. Pemetrexed has antitumor activity in OC by modulating thymidylate synthesis in purine metabolism, which is being studied in a cancer phase III trial [139, 140]. Given the propensity for OC in glutamine addicts and the association between glutamine and nucleotide metabolism, pemetrexed may be used to treat OC patients [141].

During glucose deprivation, HK-II facilitates the transition from glycolysis to autophagy by inhibiting mTORC1 binding. HK-II cooperates with extracellular signal-regulated kinase (ERK)-mediated autophagy to induce cisplatin-resistant OCs [142]. Thus, higher HK-II expression is strongly associated with progressive OC associated with tumor cell migration and invasion [143]. In particular, the glucose analog 2-deoxy-D-glucose (2-DG) can reverse autophagy in glucose deprivation by inhibiting HK-II glycolysis, while it inhibits glucose metabolism by reducing glucose uptake under calorie-restricted conditions [83, 144]. However, 2-DG remains in phase I clinical trials because 2-DG dramatically reduced white blood cell counts and glycemic index in patients with glioma and leukemia undergoing radiation therapy [145].

Resveratrol (3,5,4’-trihydroxystilbene) may be another promising therapy for modulating glucose metabolism in OC [144]. In a mouse model, resveratrol significantly reduced the cell growth of OCs [146]. In addition, resveratrol can induce a nutritionally deprived state through suppression of glucose uptake, lactate production, and reduction of AKT-mTOR signaling, eventually leading to starvation-induced autophagy [144]. The expression of ATG5 and ROS was positively correlated with resveratrol treatment, which could induce autophagy and apoptosis [147]. Resveratrol also affects IL-6-induced OC migration and inhibits cisplatin-induced EMT, demonstrating that resveratrol treatment can also be performed in advanced OC [147, 148]. In addition, resveratrol can be used in combination with conventional therapeutic adjuvants, especially in chemoresistant OC cells. Resveratrol can alleviate EMT by regulating EMT transcription factors and this effect can be enhanced when combined with cisplatin [149]. These studies suggest that therapeutic strategies targeting autophagy and metabolism could be promising, and the clinical evaluation of these treatments is ongoing in OC.

8. Conclusions

Autophagy can be either a tumor-suppressing or tumor-promoting process, depending on the oxidative stress, nutrient deficiency, chemotherapy, and the stage of cancer. In addition, metabolic regulation involving glucose, amino acids, and lipids, which are essential nutrients for cell survival, is an important feature of cancer cells. Numerous studies have suggested that regulating autophagy and cell metabolism can be a promising therapeutic strategy for OC treatment. Resveratrol has emerged as a possible anticancer treatment because it induces autophagy and modulates metabolism through multiple molecular signaling pathways. However, autophagy dysregulation enhances tumor cell growth by continuously providing nutrients. Given the complexity of the metabolic processes upregulated and/or downregulated within the TME in relation to cancer status and their tight interconnections, targeting metabolism is of great importance for treating cancer. Additionally, combining autophagy/metabolic targeted therapy with conventional therapies such as cisplatin can show strong beneficial outcomes in patients with OC. In conclusion, elucidating the autophagic process and regulation of metabolism may lead to precise strategies for OC treatment.

Author Contributions

Conceptualization—MP, SC, MS, and HY; writing - original draft preparation—MP, SC, MS, AK, KM, HK, and HY; writing - review and editing—MP, SC, MS, AK, KM, HK, and HY; supervision—HY; funding acquisition—HY; all authors have read and agreed to the published version of the manuscript.

Ethics Approval and Consent to Participate

Not applicable.

Acknowledgment

Not applicable.

Funding

This research was funded by Brain Korea 21 (BK21; # M2022B002600003).

Conflict of Interest

The authors declare no conflict of interest.

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