Next Article in Journal
Beta Blockers with Statins May Decrease All-Cause Mortality in Patients with Cardiovascular Diseases and Locally Advanced Unresectable Non-Small-Cell Lung Cancer after Chemoradiotherapy
Next Article in Special Issue
HER2 Oncogene as Molecular Target in Uterine Serous Carcinoma and Uterine Carcinosarcoma
Previous Article in Journal
Ex Vivo Model of Neuroblastoma Plasticity
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

An Overview of Ovarian Cancer: The Role of Cancer Stem Cells in Chemoresistance and a Precision Medicine Approach Targeting the Wnt Pathway with the Antagonist sFRP4

1
Cuor Stem Cellutions Pvt Ltd., Manipal Institute of Regenerative Medicine, Manipal Academy of Higher Education (MAHE), Bangalore 560 065, India
2
Division of Cancer Stem Cells and Cardiovascular Regeneration, Manipal Institute of Regenerative Medicine, Manipal Academy of Higher Education (MAHE), Bangalore 560 065, India
*
Author to whom correspondence should be addressed.
Cancers 2023, 15(4), 1275; https://doi.org/10.3390/cancers15041275
Submission received: 25 December 2022 / Revised: 11 February 2023 / Accepted: 14 February 2023 / Published: 17 February 2023

Abstract

:

Simple Summary

Ovarian cancer is one of the deadliest cancers in women and is unfortunately detected only in its later stages, by which time it will have metastasized to different organs. One of the major determinants of the rapid proliferation and spread of cancer is the presence of cancer stem cells (CSCs) within tumors. In this review, we discuss the emerging markers of ovarian cancer with respect to CSCs and circulating tumor cells. Cancer stem cell population is regulated by the Wnt signaling pathway, which is described in detail. This is relevant to comprehend the significance of Wnt in regulating the stem cell-like properties of cancer. Cancer stem cells are also responsible for enhancing chemoresistant properties and metastatic potential. Therefore, for a successful treatment regime, it is important to factor in drugs that are specific to CSCs. By targeting the promoters of CSCs, such as the Wnt signaling pathway, it is possible to suppress these cells specifically. Herein, we describe an inhibitor of Wnt, secreted frizzled related protein 4, which could be used to successfully destroy the cancer stem cells of ovarian cancer.

Abstract

Ovarian cancer is one of the most prevalent gynecological cancers, having a relatively high fatality rate with a low five-year chance of survival when detected in late stages. The early detection, treatment and prevention of metastasis is pertinent and a pressing research priority as many patients are diagnosed only in stage three of ovarian cancer. Despite surgical interventions, targeted immunotherapy and adjuvant chemotherapy, relapses are significantly higher than other cancers, suggesting the dire need to identify the root cause of metastasis and relapse and present more precise therapeutic options. In this review, we first describe types of ovarian cancers, the existing markers and treatment modalities. As ovarian cancer is driven and sustained by an elusive and highly chemoresistant population of cancer stem cells (CSCs), their role and the associated signature markers are exhaustively discussed. Non-invasive diagnostic markers, which can be identified early in the disease using circulating tumor cells (CTCs), are also described. The mechanism of the self-renewal, chemoresistance and metastasis of ovarian CSCs is regulated by the Wnt signaling pathway. Thus, its role in ovarian cancer in promoting stemness and metastasis is delineated. Based on our findings, we propose a novel strategy of Wnt inhibition using a well-known Wnt antagonist, secreted frizzled related protein 4 (sFRP4), wherein short micropeptides derived from the whole protein can be used as powerful inhibitors. The latest approaches to early diagnosis and novel treatment strategies emphasized in this review will help design precision medicine approaches for an effective capture and destruction of highly aggressive ovarian cancer.

1. Introduction

Ovarian cancer is the most lethal gynecological malignancy, with a 5-year survival rate of only 17% in the advanced stages [1]. Its prognosis is closely related to the stage at which the cancer is diagnosed [2]. Most patients remain relatively asymptomatic until the disease has spread beyond the ovaries and metastasized into the peritoneal space, producing non–specific symptoms such as dull abdominal pain or distension [3]. The rather occult nature of ovarian cancer makes it challenging to diagnose or screen the disease early. Although platinum chemotherapy is the most widely used treatment option, relapses remain high in these patients [4].
Ovarian cancer, despite its high lethality and low survival rate, does not have precise identification markers. Cancer stem cells are the key factor determining the drug response of the tumors and are usually identified by specific bonafide markers. In this review, we discuss the types of ovarian cancer and the existing diagnostic markers, chemo resistance conferred by CSCs and a unique panel for the identification of ovarian CSCs and circulating tumor cells. The role of Wnt in ovarian cancers, promoting stemness and metastasis, is a crucial factor in designing drug targets. An emerging antagonist of Wnt, secreted frizzled related protein 4 (sFRP4), has been recently found to be a promising agent to suppress CSCs. Could the functional peptides of sFRP4, in targeting ovarian cancers and their aggressive CSC population, evolve into a promising peptide drug panel for treating highly malignant and drug-resistant ovarian cancer? In this review, an overview of the existing challenges and evolving promising approaches and trends for ovarian cancer treatment is addressed.

2. Types of Ovarian Cancers

Most tumors from the ovary develop from one of the three components: the surface epithelium, germ cells and sex cord stroma. Epithelial ovarian carcinomas (EOC) account for the maximum number of cases and these are histologically subdivided broadly into five categories [5,6,7,8,9] as given in Table 1.
The definitive etiology and risk factors involved in the progression of ovarian cancer are not well studied but a few theories have been postulated, the majority having genetic links. Nulliparous women and those with longer reproductive years, i.e., early menarche and/or late menopause, are known to be at a higher risk for ovarian malignancy. On the contrary, multiparity and the use of oral contraceptive pills (OCPs), especially in pre- menopausal women and tubal ligation, prove to be protective factors. This is backed up by the incessant ovulation theory, which was hypothesized through a case control study conducted by Casagrande et al., where patients with factors accounting for “protected time”, i.e., longer periods of anovulation, through pregnancies and the use of OCPs had a significant reduction in the risk for developing ovarian cancer [10].
Among the epithelial ovarian cancers, the endometrioid and the clear cell type are known to be derived from ovarian endometriosis. A widely accepted theory is that of retrograde menstruation, which enhances iron-induced oxidative stress and in turn DNA damage. Some studies have even shown that gene mutations associated with endometriosis-associated ovarian cancers are normally found in the uterine and ovarian endometriotic epithelium [11]. High-grade serous ovarian carcinoma is considered the most aggressive type, accounting for the maximum number of deaths from ovarian cancer [12]. Women with BRCA1/2 germline mutations who underwent prophylactic salpingo-oophorectomy were found to have atypia of the tubal epithelium, raising the suspicion of the fallopian tube being the origin of serous ovarian cancers [13]. The retrograde menstruation theory holds good for the serous type too, with the DNA damage occurring more in the fimbriae of the fallopian tube as a result of chronic exposure to pooled blood in the pouch of Douglas. This process, along with the overexpression and the subsequent mutation of p53 at the mucosal cells of the fimbriae contribute to carcinogenesis [14].Table 1 elicits the distinct mutational profiles of the various subtypes of EOCs, suggesting that ovarian cancer is a highly heterogeneous disease. A more recent classification of OC is based on its grade and propensity for aggressive change, broadly categorizing it into Type I and Type II. Type I, which is the low-grade form, consists of low-grade serous, mucinous, endometrioid and clear cell whereas type II is the high-grade serous OC [15].

3. Existing Markers of Ovarian Cancer

Among the various cancer-detecting strategies, tumor markers have been used for decades as a starting point in the roadmap for cancer diagnosis. They are specific proteins and biomarkers released in blood in response to carcinogenesis and other inflammatory states. First identified by Bast et al. in 1981, CA-125 is the oldest and most widely used biomarker for epithelial ovarian cancer [16,17]. Although it is considered the standard tumor marker, it has low sensitivity in patients presenting in the early stages of the disease. Moreover, it is not a specific marker for ovarian cancer and is also observed to be elevated in endometriosis, menstruation, pelvic inflammatory disease, endometrioma, cirrhosis and pregnancy in some cases [12]. Studies showed that CA-125 was not often elevated in mucinous carcinoma, suggesting that it was not the most reliable marker for all histological subtypes of ovarian cancer [18]. CA-125 is also used as a prognostic tool to assess treatment response and recurrence, but over the years the urgent need for a more specific marker/combination of markers was emphasized, as the rise of CA-125 levels alone in an asymptomatic patient was not sufficient for diagnosis.
HE4 (WFDC2) is a glycoprotein belonging to the family of whey acidic proteins (WAP) and contains two WAP domains. It was initially isolated in human epididymis by Kirchhoff et al., but its presence outside the male reproductive system was noted eventually in further studies. Although it was weakly expressed in lung and colorectal adenocarcinoma, it was found to have significant expression in epithelial ovarian tumors, especially in the endometrioid subtype [19].
Statistical analysis showed a sensitivity of 72.9% for the HE4 marker alone when a comparative study between other markers such as CA-125, CA72-4, osteopontin, soluble mesothelin-related peptide and human epidermal growth factor 2 was performed by Moore et al., while Yanaranop and his team reported a specificity of 86% [16,20,21]. Studies also showed the efficacy of a combination of HE4 and CA-125 in the diagnostic algorithm and found an increased sensitivity at 92.9% [16,20]. Immunohistochemistry studies on tissues and oligonucleotide microarrays showed that the HE4 gene was strongly expressed in ovarian and endometrial lesions but not as much in endometriotic lesions [16,19]. This proved to be a significant differentiating factor from CA-125, which was overexpressed in endometriomas as well, enhancing the specificity of HE4 in ruling out benign ovarian lesions such as advanced endometriosis and ovarian endometrioma.
Moore and his team in 2009 proposed the Risk of Malignancy Algorithm (ROMA), which took into account HE4, CA-125 and the age of a patient presenting with a pelvic mass [22] and classified them as high risk or low risk (with the cut off for premenopausal women being 11.4% and 29.9% for postmenopausal women). Although it seemed to be a promising diagnostic tool, a study showed that it was not a satisfactory indicator to diagnose epithelial ovarian cancer in pre- menopausal women [23].
Prostatin (PSN), a trypsin-like protease normally found in prostatic and seminal fluids, was also studied as a potential biomarker when Costa et al. observed a significant overexpression in prostatin mRNA in epithelial ovarian cancers [24]. The combination of PSN and CA-125 has gained popularity over the years for its increased sensitivity (92%) and specificity (94%) in detecting early stage disease but the clinical use of PSN is yet to be rigorously assessed [12].
Transerythrin (TTR) has been found to be useful for the detection of stages I and II of epithelial ovarian cancer. Alpha fetoprotein (AFP) and beta HCG are used to detect the stages and treatment response of ovarian germ cell tumors. Inhibin A and B were found to be overexpressed in mucinous epithelial cancer and granulosa cell tumors [12,25].

4. Current Treatment Methods

Treating ovarian cancer requires a personalized and multi-disciplinary approach, taking into account the stage at which the patient is diagnosed (surgical staging) and their co-morbidities. A prospective study demonstrated a statistically significant difference in the benefit of chemotherapy and overall prognosis in patients whose cancer was optimally staged [26]. This reiterates the value of precise OC staging for future treatment assessment.
Debulking cytoreductive surgery, which consists of total abdominal hysterectomy (TAH) + bilateral salpingo-oophorectomy (BSO) followed by three to six cycles of chemotherapy, is the initial step in the management of OC, recommended by the Gynecologic Cancer Inter-Group (GCIG) [27]. Nodal metastases are also seen in up to 28% of serous OC patients in early stages; thus, removal of the pelvic- and para-aortic lymph nodes is recommended [28]. Platinum alkylating agents such as carboplatin or cisplatin, the former being preferred due to milder side effects, and taxanes such as paclitaxel or docetaxel are the mainstays of adjuvant chemotherapy. They are administered intravenously or intraperitoneally, but hyperthermic intraperitoneal chemotherapy (HIPEC) has been found to be more effective at targeting residual tumor in stage III disease [29,30].
Unfortunately, 75% of patients are diagnosed for the first time in advanced stages (FIGO stages III and IV) of OC or patients have returned with recurrent disease that has metastasized extensively. This has prompted physicians to adopt a more aggressive approach, i.e., pre-operative imaging followed by maximal cytoreduction. A meta-analysis by Bristow et al. [31] elucidated that, among all other prognostic variables, maximal cytoreduction and surgical follow up had the most significance in assessing the median survival of a patient with advanced OC. Along with primary debulking, total omentectomy is essential due to the high prevalence of occult metastasis in the supracolic omentum. Although platinum agents have shown considerable effect in the medical treatment of OC, at least half of patients require radical and supra-radical surgery. If the tumor is found to be unresectable in some patients intra-operatively, palliative chemotherapy alone is the treatment of choice [28,31]. Response and sensitivity to platinum chemotherapy is measured by disease remission in a platinum-free interval of 6-12 months. In platinum sensitive patients with recurrence and metastasis, combined chemotherapy with the same drugs is used. However, the limited chemotherapy options for platinum-resistance and refractory states, with the combination of trabectedin and liposomal doxorubicin being one such, led to the discovery of targeted immunotherapy and PARP inhibitors [32,33].

4.1. PARP (Poly(ADPribose) Polymerase) Inhibitors

The role of PARP inhibitors as a single therapeutic agent is most beneficial in HGSOC patients with BRCA mutations. PARP 1 plays an important role in DNA single stranded breakage (SSB) and double stranded breakage (DSB) repair through base excision repair mechanisms. BRCA genes, among other proteins in normal cells, are involved in the homologous recombination repair (HRR) of DSB. The inhibition of PARP in the presence of BRCA 1 and 2 mutations results in defective HRR and DSB repair leading to genomic instability and cell death. This is referred to as ‘synthetic lethality’, wherein the inactivation of two pathways simultaneously evokes a strong and selective apoptotic response in cancer cells [32,34]. The FDA-approved drugs at present are olaparib, niraparib and rucaparib [35]. Niraparib and its combination with some anti-angiogenic agents have proven to be effective in platinum-resistant states [36].

4.2. Anti-Angiogenic Therapy

The vascular endothelial growth factor (VEGF) pathway is the most common target for angiogenesis inhibition in many cancers including OC. Bevacizumab (avastin) is a monoclonal antibody that targets the VEGF pathway and is approved for use in advanced OC patients [37]. Over time, resistance to VEGF inhibitors was observed due to alternate angiogenic pathway adaptations. This is partially overcome when bevacizumab is used as an adjunct with PARP inhibitors and platinum chemotherapy [38].

4.3. Immunomodulators (Pembrolizumab, Dostarlimab)

Epithelial OC is considered an inflamed tumor, one that has a high percentage of CD8+ T cells and high PD 1 expression [39]. This plays a key role in suppressing host tumor immunity, which suggests that using immune checkpoint inhibitors that target PD1/PD L1 or cytotoxic T lymphocyte-associated protein 4 (CTLA-4) shows promising results in advanced OC with DNA mismatch repair deficiency (dMMR) [40].

4.4. Radiotherapy

Although ovarian cancer is known to be radiosensitive, the role of whole abdominal radiotherapy (WAR) is limited in standard care after the introduction of platinum-based chemotherapy [41]. This is attributed to post-radiation toxicity and the higher success rate of chemotherapy. Currently, stereotactic and palliative radiation are reserved for some patients with advanced, relapsed and non-resectable disease as salvage therapy. The primary benefit is symptom relief and marginally prolonged life expectancy [42]. The present treatment strategies for ovarian cancer are elaborated in Figure 1.
Complete remission is achieved with platinum chemotherapy and debulking surgery in a majority patients, but most of them experience a relapse [43]. Despite maintenance therapy with PARP inhibitors and targeted immunotherapy showing promising results in advanced disease [44], the long-term disease-free interval of ovarian cancer lasting around 10 years is still stagnant at 18% [45]. This shortcoming reflects the lack of a sufficient precision medicine approach addressing the molecular topography and chemo resistance in ovarian cancer cell lines.

5. Chemoresistance and Cancer Stem Cells in Ovarian Cancer

Cancer stem cells (CSCs) are a small subset of the stem cell population with properties such as self-renewal, differentiation and resistance to apoptosis, similar to tissue stem cells [46]. The distinguishing property of CSCs is that they have an exponentially higher potency to seed a new tumor and cause continued tumor progression compared to non-CSC tumor bulk. They remain in a quiescent state and are unaffected by chromosomal aberrations and ageing [47]. Cancer stem cells are characterized by resistance to radiation by virtue of their advanced DNA repair mechanism, conferred by their elevated MDM2 activity, which is a transcriptional target of p53 [48].
The presence of tumor-initiating cells in malignancies was initially discovered by Lapidot et al. in 1994 when they found the increased expression of certain cell surface markers (CD34+, CD38+) in relation to acute myeloid leukemia in an immunocompromised state [49]. Over time, the significant presence of CSCs in solid tumors became evident in metastatic sites such as malignant ascites. Analysis on ovarian tissue using immunohistochemistry for pluripotency-associated cell surface markers revealed a small sub-population of Nanog-positive cells in ovarian surface epithelium (OSE) [50]. This lent support to the theory that these are cancer stem cells, dormant in ovarian surface and tubal epithelium. Incidentally, the majority of ovarian cancer cells originate from OSE, validating the prominent role of CSCs in the progression and recurrence of ovarian cancer [51].
Cancer stem cells are identified by their unique profile of cell surface and intracellular markers. The panel of ovarian CSC markers that are reported include CD24, CD44, CD117, CD133, ALDH1, ABC transporter proteins, EpCAM, Nestin, Oct4, Nanog, Sox2, SSEA4 and SCF. Of these, CD24, CD44 and CD133 are a few of the prominent markers. CD24+ cells in ovarian cancer exhibit anoikis resistance, higher tumor growth, colony formation, EMT phenotype and possess stem-like properties such as self-renewal. CD133 expression is associated with poor prognosis and is also implicated in increased platinum resistance and metastasis. Nanog expression also modulates platinum resistance and EMT in ovarian cancer. A comprehensive list of ovarian-specific CSC markers and their role is summarized in Table 2.
The proliferative potential of CSCs is regulated by the tumor microenvironment and multiple pathways. Heterogeneity in the tumor microenvironment is a classic feature of ovarian cancer and the distinct mutational profile of epithelial ovarian cancer is what makes it unique and challenging among other cancers. The clonal evolution theory was proposed in 1976 [89], where longitudinal samples of a single patient’s OC cells before surgery and after recurrence, in ascitic cells from peritoneal dissemination, elicited a wide range of genomic diversity in tumor spheres at different locations [90]. The cellular plasticity that these tumors exhibit is primarily initiated in CSC niches and is the driving force for chemotherapeutic failure and disease progression in ovarian cancer. This occurs through phenotypic cellular changes brought about by interaction between the tumor cell and surrounding stroma or stochastic variations [27].
Multiple regulatory pathways such as Wnt, STAT3, Hedgehog, BMI1, Notch and NF-κB are abnormally activated and thus aid in the self-renewal of CSCs in ovarian cancer [91,92]. The dysregulated cell cycle and hyper-proliferation of CSCs are governed by modulators such as ß-catenin, MAPK, NF-kB, PAX6, FOXO3 and STAT2 [93,94]. For combating ovarian cancer, drugs are being designed to target self-renewal signaling pathways that can restrain the survival, differentiation and replication of stem cells. A few such drugs in clinical use are ipafricept (OMP-54F28) and DAPT (GSI-IX), which target the Wnt ligand (Wnt pathway) and γ-secretase (Notch pathway), respectively [95,96]. Besides ipafricept, there are several other potential therapeutic drugs that target the Wnt signaling pathway and are currently under clinical trials for multiple cancers. These include LGK-974 (WNT974; porcupine inhibitor) [97,98], ICG-001 (PRI-724; blocks the binding of β-catenin to CREB binding protein) [99], vantictumab (OMP-18R5; blocks Wnt/Fzd binding by targeting Fzd) [100].

6. Circulating Tumor Cells

The presence of circulating tumor cells (CTCs) in ovarian cancer is gaining clinical relevance [101]. Circulating tumor cells are cells that originate from the primary tumor bulk but break off into blood/lymphatic circulation. In recent years, studies established the hematogenous spread of ovarian cancer and this has attracted interest to develop non-invasive CTC-based tests to identify reliable diagnostic and prognostic markers for ovarian cancer [102]. Recently, one such study was conducted by isolating CTCs from 38 patients with advanced high-grade serous ovarian cancer. The results showed the higher expression of cancer stem cell markers CD24 and CD44 along with EMT-associated markers such as TIMP1 and CXCR4. The presence of these markers supports the hypothesis that CTCs exhibit molecular plasticity by expressing epithelial, mesenchymal and stem cell-like markers. This property helps in CTC migration and survival under hostile microenvironments and chemotherapeutic assault [103]. There is a correlation between CD24 expression in primary ovarian cancer tissue and lymph node metastasis, indicating the role of stem cell markers in metastasized OC [52]. Interestingly, tumor-derived exosomes isolated from patient plasma also showed a threefold increase in CD24 as identified by the Exosearch chip method [104]. These findings throw light on an exciting approach to develop efficient CD24-based non-invasive tests from CTCs in diagnosing and monitoring aggressive and metastatic ovarian cancer.

7. Role of Wnt Pathway and EMT in Ovarian Metastasis

Wnts are cysteine-rich glycoproteins secreted in the extracellular matrix. The Wnt pathway is a highly conserved evolutionary system, existing across species from invertebrates to mammals, and is responsible for various cellular processes such as proliferation, differentiation, apoptosis, tissue homeostasis and stem cell renewal [105]. Nineteen Wnt proteins couple with receptors and co-receptors in over seven protein families among which the frizzled protein functions as the principal Wnt receptor in mediating specific pathways [106]. Three fundamental Wnt pathways have been studied extensively: the canonical pathway, the non-canonical planar cell polarity pathway and the non-canonical Wnt/calcium pathway.
The canonical Wnt pathway is dependent on the dual function protein, beta catenin. In the absence of a Wnt ligand, the cytoplasmic beta catenin is phosphorylated by the actions of adenomatous polyposis coli (APC), Casein kinase 1 alpha (CK1α) and Glycogen synthase kinase 3β (GSK3β) present in Axin (a scaffold protein that constitutes the destruction complex) [93,107]. This results in the continuous degradation of β-catenin via the ubiquitin-proteasome pathway. The activation of the Wnt ligand occurs when it binds to the surface co-receptors comprising seven transmembrane frizzled proteins and low-density lipoprotein receptor-related protein 5 or 6 (LRP 5/6). This interaction results in the activation of the protein Disheveled (Dvl), which ultimately leads to the inactivation of the destruction complex by GSK3β inhibition. The stabilization of β-catenin in signal transduction is a key component of the Wnt/β catenin pathway functioning and this is achieved by Wnt ligand activation wherein the stabilized β-catenin translocates to the nucleus. The ultimate interaction and binding between the nuclear β-catenin and T cell factor/lymphoid enhancer factor (TCF/LEF) is what results in the wide variety of changes in gene expressions responsible for stem cell proliferation and renewal [107,108,109] (Figure 2).
The initial discovery of Wnt canonical signaling was associated with its role in tumorigenesis when the transcriptional activation of molecule Int 1 was found to induce mammary hyperplasia in mice through pro-viral insertion into the Wnt 1 locus [110,111]. Further studies revealed that the dysregulation of the Wnt/β-catenin pathway was a catalyst for the events in the pathogenesis of colorectal carcinoma. Mutations in the APC gene result in the loss of reorientation of the Wnt destruction complex, thereby initiating carcinogenesis [112]. The role of the Wnt/β-catenin pathway in ovarian cancer has been delineated due to its persistence in the XX gonad during gonadal development and its ability to regulate stemness in the ovarian stem cell niche [105,113]. The process of epithelial to mesenchymal transition (EMT) is one that has been rigorously researched for decades in the context of tumor progression. Epithelial to mesenchymal transition is known to generate hybrid E/M cells exhibiting cell plasticity, a property that has also been observed in normal ovarian surface epithelium [114,115]. These intermediate EMT states were subsequently found in ovarian cancer cell lines and in malignant ascites, suggesting the metastatic dissemination of cancer cells [105,116]. Through the reversible transition of cancer stem cells from epithelial phenotype to a more motile mesenchymal state, they acquire features such as stemness, invasion and resistance to therapy [116]. Slug and Snail are EMT regulating transcription factors. Ovarian cancer cell lines with an increased Snail/E-cadherin ratio were found to have more aggressive therapy-resistant characteristics [105,117]. A study by Zhao-Qui Wu [118] demonstrated the role of the Wnt/canonical axis in regulating Snail and Slug expressions, in turn suppressing BRCA1 expression. These processes urged researchers to shift focus to targeting the Wnt/β-catenin pathway and its antagonists/inhibitors as a potential treatment in advanced and chemo-resistant ovarian cancers.

8. Wnt Inhibition by sFRP4 Micropeptides: Potential Breakthrough in Ovarian Cancer Treatment?

The regulation of ovarian tumorigenesis by Wnt normally occurs extracellularly through its antagonists [119,120]. In cancers, the dysregulated Wnt pathway affects the negative feedback mechanism resulting in defective inhibitory regulation. Some of the known antagonists are sFRP, WIF-1 and Dickkopf proteins, among others [121]. They offer a mechanism by which hyper-activated Wnt signaling is suppressed.
sFRP4 is a glycoprotein modulator and the largest member of the sFRP family. It contains two domains: a cysteine-rich domain (CRD) that is homologous to the Wnt binding site of frizzled proteins and a netrin-like domain (NLD). It has apoptotic and anti-angiogenic properties, thus acting as a tumor suppressor [122]. sFRP4 was identified as a potent anti-CSC agent in several cancers such as breast, prostate, gliomas and ovarian cancer cell lines [123]. Pohl et al. demonstrated selective apoptotic response in tumor endothelium when SFRP was administered therapeutically [122]. In a study conducted in 2012 by Saran et al., sFRP4 levels were increased in chemosensitive ovarian cancer cell line A2780, and overexpression with sFRP4 resulted in sensitization to cisplatin in chemoresistant ovarian cancer cell line A2780Cis [120]. In recent years, various studies have clearly established the role of sFRP4 in targeting ovarian CSCs. sFRP4 has been shown to chemo-sensitize ovarian CSCs for the drug cisplatin, along with activating apoptosis via increased caspase 3/7 activity [123]. Similar studies have shown that the activation of sFRP4 by the inhibition of miR-181a has resulted in reducing cisplatin resistance and stemness in high-grade serous ovarian tumors (HGSOC) [124].
In our recently published report [125], it was observed that CSCs enriched from ovarian cancer cell lines PA-1 and SKOV-3 show a high expression of CSC markers such as CD24, CD44, Nanog, Oct4, ABCG2, ABCC2 and ABCC4. In this study, we used two synthetic micropeptides, the SC-301 of 17 amino acids and SC-401 of 20 amino acids, derived from the CRD and NLD domains, respectively, of sFRP4. Treatment with these micropeptides reduced the CSC marker expression and sensitized ovarian CSCs to cisplatin. Furthermore, there was upregulation of caspases, p53 and other key pro-apoptotic genes in addition to the expected inhibition of the Wnt/β-catenin pathway. In addition, it also significantly retarded the cell migration capacity of CSCs. Our study demonstrated novel protein interaction between β-catenin and CD24 in ovarian cancer, which was disrupted upon treatment with sFRP4 micropeptides. As CD24 is known to promote cell invasion and migration, this disruption could possibly attenuate these properties. We also performed an in vivo angiogenic chorioallantoic membrane (CAM) assay and it was shown that the treatment of sFRP4-derived micropeptides inhibited the angiogenic potential of ovarian CSCs, thereby indicating that these micropeptides are highly anti-angiogenic in vivo, a valuable property for tumor suppression. The micropeptides were also potent in suppressing autophagy, which is required for CSC survival [126]. The overall findings clearly demonstrate that sFRP4 micropeptides not only inhibit the Wnt/β-catenin pathway but also may play a key role in targeting chemoresistance, cell invasion and autophagy in ovarian CSCs (Figure 3).

9. Conclusions

To summarize, in this review we describe the existing prognostic and diagnostic markers in ovarian cancers and their level of specificity. The treatment strategies currently adopted by physicians globally shed light on the need for a more effective and precise panel of drugs, since relapses still remain alarmingly high. The significance of cancer stem cells in promoting chemoresistance and metastasis and the specific markers of CSCs and CTCs are described. The role of Wnt in regulating CSCs is further elaborated as the Wnt signaling pathway is one of the major determinants of the survival of CSCs. Novel targeted therapy addressing upregulated Wnt signaling would be the way forward to inhibit ovarian cancer stem cells. A natural antagonist of Wnt, the secreted frizzled related protein 4 has been well reported to increase chemotherapeutic response and decrease the CSC population. We describe how the short active peptide derivatives of sFRP4 could be the latest breakthrough in peptide-based drug compounds for the treatment of highly malignant and aggressive ovarian cancer.

Author Contributions

Conceptualization, L.V. and S.W., Writing—Original Draft Preparation, L.V., Writing—Review and Editing, L.V., S.M.S., N.G. and S.W., Visualization, L.V., S.M.S., N.G. and S.W., Funding Acquisition, S.W. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported partly by funding from the Department of Health Research, Ministry of Health and Family Welfare, India [R.11013/27/2021-GIA/HR] and the Department of Biotechnology, Ministry of Science and Technology, India [BT/PR41903/MED/97/527/2021].

Acknowledgments

M.S. is thankful for the TMA Pai scholarship and fellowship from the UGC, Govt of India.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Huang, J.; Chan, W.C.; Ngai, C.H.; Lok, V.; Zhang, L.; Lucero-Prisno, D.E., 3rd; Xu, W.; Zheng, Z.J.; Elcarte, E.; Withers, M.; et al. Worldwide Burden, Risk Factors, and Temporal Trends of Ovarian Cancer: A Global Study. Cancers 2022, 14, 2230. [Google Scholar] [CrossRef] [PubMed]
  2. Gaitskell, K.; Hermon, C.; Barnes, I.; Pirie, K.; Floud, S.; Green, J.; Beral, V.; Reeves, G.K. Ovarian cancer survival by stage, histotype, and pre-diagnostic lifestyle factors, in the prospective UK Million Women Study. Cancer Epidemiol. 2022, 76, 102074. [Google Scholar] [CrossRef] [PubMed]
  3. Cortés-Guiral, D.; Hübner, M.; Alyami, M.; Bhatt, A.; Ceelen, W.; Glehen, O.; Lordick, F.; Ramsay, R.; Sgarbura, O.; Van Der Speeten, K.; et al. Primary and metastatic peritoneal surface malignancies. Nat. Rev. Dis. Prim. 2021, 7, 91. [Google Scholar] [CrossRef] [PubMed]
  4. Marchetti, C.; De Felice, F.; Romito, A.; Iacobelli, V.; Sassu, C.M.; Corrado, G.; Ricci, C.; Scambia, G.; Fagotti, A. Chemotherapy resistance in epithelial ovarian cancer: Mechanisms and emerging treatments. Semin. Cancer Biol. 2021, 77, 144–166. [Google Scholar] [CrossRef]
  5. Zhong, F.; Zhu, T.; Pan, X.; Zhang, Y.; Yang, H.; Wang, X.; Hu, J.; Han, H.; Mei, L.; Chen, D.; et al. Comprehensive genomic profiling of high-grade serous ovarian carcinoma from Chinese patients identifies co-occurring mutations in the Ras/Raf pathway with TP53. Cancer Med. 2019, 8, 3928–3935. [Google Scholar] [CrossRef] [Green Version]
  6. Vang, R.; Shih Ie, M.; Kurman, R.J. Ovarian low-grade and high-grade serous carcinoma: Pathogenesis, clinicopathologic and molecular biologic features, and diagnostic problems. Adv. Anat. Pathol. 2009, 16, 267–282. [Google Scholar] [CrossRef] [Green Version]
  7. Chang, K.-L.; Lee, M.-Y.; Chao, W.-R.; Han, C.-P. The status of Her2 amplification and Kras mutations in mucinous ovarian carcinoma. Human Genom. 2016, 10, 40. [Google Scholar] [CrossRef] [Green Version]
  8. Kurman, R.J.; Shih Ie, M. Molecular pathogenesis and extraovarian origin of epithelial ovarian cancer--shifting the paradigm. Human Pathol. 2011, 42, 918–931. [Google Scholar] [CrossRef] [Green Version]
  9. Ackroyd, S.A.; Arguello, D.; Ramos, P.; Mahdi, H.; ElNaggar, A.; Winer, I.; Holloway, R.; Krivak, T.; Jones, N.; Turner, V.G.; et al. Molecular portraits of clear cell ovarian and endometrial carcinoma with comparison to clear cell renal cell carcinoma. Gynecol. Oncol. 2022, 169, 164–171. [Google Scholar] [CrossRef]
  10. Casagrande, J.T.; Louie, E.W.; Pike, M.C.; Roy, S.; Ross, R.K.; Henderson, B.E. “Incessant ovulation” and ovarian cancer. Lancet 1979, 2, 170–173. [Google Scholar] [CrossRef]
  11. Yachida, N.; Yoshihara, K.; Yamaguchi, M.; Suda, K.; Tamura, R.; Enomoto, T. How Does Endometriosis Lead to Ovarian Cancer? The Molecular Mechanism of Endometriosis-Associated Ovarian Cancer Development. Cancers 2021, 13, 1439. [Google Scholar] [CrossRef]
  12. Atallah, G.A.; Abd Aziz, N.H.; Teik, C.K.; Shafiee, M.N.; Kampan, N.C. New Predictive Biomarkers for Ovarian Cancer. Diagnostics 2021, 11, 465. [Google Scholar] [CrossRef] [PubMed]
  13. Weinberger, V.; Bednarikova, M.; Cibula, D.; Zikan, M. Serous tubal intraepithelial carcinoma (STIC)—Clinical impact and management. Expert Rev. Anticancer Ther. 2016, 16, 1311–1321. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Vercellini, P.; Crosignani, P.; Somigliana, E.; Viganò, P.; Buggio, L.; Bolis, G.; Fedele, L. The ‘incessant menstruation’ hypothesis: A mechanistic ovarian cancer model with implications for prevention. Human Reprod. 2011, 26, 2262–2273. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Koshiyama, M.; Matsumura, N.; Konishi, I. Recent concepts of ovarian carcinogenesis: Type I and type II. BioMed Res. Int. 2014, 2014, 934261. [Google Scholar] [CrossRef] [Green Version]
  16. Li, J.; Dowdy, S.; Tipton, T.; Podratz, K.; Lu, W.G.; Xie, X.; Jiang, S.W. HE4 as a biomarker for ovarian and endometrial cancer management. Expert Rev. Mol. Diagn. 2009, 9, 555–566. [Google Scholar] [CrossRef] [Green Version]
  17. Bast, R.C., Jr.; Feeney, M.; Lazarus, H.; Nadler, L.M.; Colvin, R.B.; Knapp, R.C. Reactivity of a monoclonal antibody with human ovarian carcinoma. J. Clin. Investig. 1981, 68, 1331–1337. [Google Scholar] [CrossRef] [Green Version]
  18. Terry, K.L.; Sluss, P.M.; Skates, S.J.; Mok, S.C.; Ye, B.; Vitonis, A.F.; Cramer, D.W. Blood and urine markers for ovarian cancer: A comprehensive review. Dis. Markers 2004, 20, 53–70. [Google Scholar] [CrossRef] [Green Version]
  19. Galgano, M.T.; Hampton, G.M.; Frierson, H.F., Jr. Comprehensive analysis of HE4 expression in normal and malignant human tissues. Mod. Pathol. 2006, 19, 847–853. [Google Scholar] [CrossRef] [Green Version]
  20. Dochez, V.; Caillon, H.; Vaucel, E.; Dimet, J.; Winer, N.; Ducarme, G. Biomarkers and algorithms for diagnosis of ovarian cancer: CA125, HE4, RMI and ROMA, a review. J. Ovarian Res. 2019, 12, 28. [Google Scholar] [CrossRef] [Green Version]
  21. Yanaranop, M.; Anakrat, V.; Siricharoenthai, S.; Nakrangsee, S.; Thinkhamrop, B. Is the Risk of Ovarian Malignancy Algorithm Better Than Other Tests for Predicting Ovarian Malignancy in Women with Pelvic Masses? Gynecol. Obstet. Investig. 2017, 82, 47–53. [Google Scholar] [CrossRef] [PubMed]
  22. Moore, R.G.; McMeekin, D.S.; Brown, A.K.; DiSilvestro, P.; Miller, M.C.; Allard, W.J.; Gajewski, W.; Kurman, R.; Bast, R.C., Jr.; Skates, S.J. A novel multiple marker bioassay utilizing HE4 and CA125 for the prediction of ovarian cancer in patients with a pelvic mass. Gynecol. Oncol. 2009, 112, 40–46. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Montagnana, M.; Danese, E.; Ruzzenente, O.; Bresciani, V.; Nuzzo, T.; Gelati, M.; Salvagno, G.L.; Franchi, M.; Lippi, G.; Guidi, G.C. The ROMA (Risk of Ovarian Malignancy Algorithm) for estimating the risk of epithelial ovarian cancer in women presenting with pelvic mass: Is it really useful? Clin. Chem. Lab. Med. 2011, 49, 521–525. [Google Scholar] [CrossRef] [PubMed]
  24. Costa, F.P.; Batista, E.L., Jr.; Zelmanowicz, A.; Svedman, C.; Devenz, G.; Alves, S.; Silva, A.S.; Garicochea, B. Prostasin, a potential tumor marker in ovarian cancer--a pilot study. Clinics 2009, 64, 641–644. [Google Scholar] [CrossRef] [Green Version]
  25. Walentowicz, P.; Krintus, M.; Sadlecki, P.; Grabiec, M.; Mankowska-Cyl, A.; Sokup, A.; Walentowicz-Sadlecka, M. Serum inhibin A and inhibin B levels in epithelial ovarian cancer patients. PLoS ONE 2014, 9, e90575. [Google Scholar] [CrossRef] [Green Version]
  26. Trimbos, J.B.; Vergote, I.; Bolis, G.; Vermorken, J.B.; Mangioni, C.; Madronal, C.; Franchi, M.; Tateo, S.; Zanetta, G.; Scarfone, G.; et al. Impact of adjuvant chemotherapy and surgical staging in early-stage ovarian carcinoma: European Organisation for Research and Treatment of Cancer-Adjuvant ChemoTherapy in Ovarian Neoplasm trial. J. Natl. Cancer Inst. 2003, 95, 113–125. [Google Scholar] [CrossRef] [Green Version]
  27. Kim, S.; Han, Y.; Kim, S.I.; Kim, H.S.; Kim, S.J.; Song, Y.S. Tumor evolution and chemoresistance in ovarian cancer. NPJ Precis. Oncol. 2018, 2, 20. [Google Scholar] [CrossRef] [Green Version]
  28. Pomel, C.; Jeyarajah, A.; Oram, D.; Shepherd, J.; Milliken, D.; Dauplat, J.; Reynolds, K. Cytoreductive surgery in ovarian cancer. Cancer Imaging 2007, 7, 210–215. [Google Scholar] [CrossRef] [Green Version]
  29. Chandra, A.; Pius, C.; Nabeel, M.; Nair, M.; Vishwanatha, J.K.; Ahmad, S.; Basha, R. Ovarian cancer: Current status and strategies for improving therapeutic outcomes. Cancer Med. 2019, 8, 7018–7031. [Google Scholar] [CrossRef] [Green Version]
  30. Riggs, M.J.; Pandalai, P.K.; Kim, J.; Dietrich, C.S. Hyperthermic Intraperitoneal Chemotherapy in Ovarian Cancer. Diagnostics 2020, 10, 43. [Google Scholar] [CrossRef] [Green Version]
  31. Bristow, R.E.; Tomacruz, R.S.; Armstrong, D.K.; Trimble, E.L.; Montz, F.J. Survival effect of maximal cytoreductive surgery for advanced ovarian carcinoma during the platinum era: A meta-analysis. J. Clin. Oncol. 2002, 20, 1248–1259. [Google Scholar] [CrossRef] [PubMed]
  32. Kim, A.; Ueda, Y.; Naka, T.; Enomoto, T. Therapeutic strategies in epithelial ovarian cancer. J. Exp. Clin. Cancer Res. 2012, 31, 14. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Gadducci, A.; Guarneri, V.; Peccatori, F.A.; Ronzino, G.; Scandurra, G.; Zamagni, C.; Zola, P.; Salutari, V. Current strategies for the targeted treatment of high-grade serous epithelial ovarian cancer and relevance of BRCA mutational status. J. Ovarian Res. 2019, 12, 9. [Google Scholar] [CrossRef] [Green Version]
  34. Drew, Y. The development of PARP inhibitors in ovarian cancer: From bench to bedside. Br. J. Cancer 2015, 113 (Suppl. 1), S3–S9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Redelico, T. Rucaparib and Niraparib in Advanced Ovarian Cancer. J. Adv. Pract. Oncol. 2019, 10, 402–408. [Google Scholar] [CrossRef]
  36. Liu, G.; Feng, Y.; Li, J.; Deng, T.; Yin, A.; Yan, L.; Zheng, M.; Xiong, Y.; Li, J.; Huang, Y.; et al. A novel combination of niraparib and anlotinib in platinum-resistant ovarian cancer: Efficacy and safety results from the phase II, multi-center ANNIE study. EClinicalMedicine 2022, 54, 101767. [Google Scholar] [CrossRef]
  37. Garcia, J.; Hurwitz, H.I.; Sandler, A.B.; Miles, D.; Coleman, R.L.; Deurloo, R.; Chinot, O.L. Bevacizumab (Avastin®) in cancer treatment: A review of 15 years of clinical experience and future outlook. Cancer Treat. Rev. 2020, 86, 102017. [Google Scholar] [CrossRef]
  38. Choi, H.J.; Armaiz Pena, G.N.; Pradeep, S.; Cho, M.S.; Coleman, R.L.; Sood, A.K. Anti-vascular therapies in ovarian cancer: Moving beyond anti-VEGF approaches. Cancer Metastasis Rev. 2015, 34, 19–40. [Google Scholar] [CrossRef] [Green Version]
  39. Palaia, I.; Tomao, F.; Sassu, C.M.; Musacchio, L.; Benedetti Panici, P. Immunotherapy for Ovarian Cancer: Recent Advances And Combination Therapeutic Approaches. Onco Targets Ther. 2020, 13, 6109–6129. [Google Scholar] [CrossRef]
  40. Hamanishi, J.; Mandai, M.; Iwasaki, M.; Okazaki, T.; Tanaka, Y.; Yamaguchi, K.; Higuchi, T.; Yagi, H.; Takakura, K.; Minato, N.; et al. Programmed cell death 1 ligand 1 and tumor-infiltrating CD8+ T lymphocytes are prognostic factors of human ovarian cancer. Proc. Natl. Acad. Sci. USA 2007, 104, 3360–3365. [Google Scholar] [CrossRef] [Green Version]
  41. Fields, E.C.; McGuire, W.P.; Lin, L.; Temkin, S.M. Radiation Treatment in Women with Ovarian Cancer: Past, Present, and Future. Front. Oncol. 2017, 7, 177. [Google Scholar] [CrossRef] [Green Version]
  42. Durno, K.; Powell, M.E. The role of radiotherapy in ovarian cancer. Int. J. Gynecol. Cancer 2022, 32, 366–371. [Google Scholar] [CrossRef] [PubMed]
  43. Kemp, Z.; Ledermann, J. Update on first-line treatment of advanced ovarian carcinoma. Int. J. Women’s Health 2013, 5, 45–51. [Google Scholar] [CrossRef] [Green Version]
  44. Miller, R.E.; Lewis, A.J.; Powell, M.E. PARP inhibitors and immunotherapy in ovarian and endometrial cancers. Br. J. Radiol. 2021, 94, 20210002. [Google Scholar] [CrossRef]
  45. Pitiyarachchi, O.; Friedlander, M.; Java, J.J.; Chan, J.K.; Armstrong, D.K.; Markman, M.; Herzog, T.J.; Monk, B.J.; Backes, F.; Secord, A.A.; et al. What proportion of patients with stage 3 ovarian cancer are potentially cured following intraperitoneal chemotherapy? Analysis of the long term (≥10 years) survivors in NRG/GOG randomized clinical trials of intraperitoneal and intravenous chemotherapy in stage III ovarian cancer. Gynecol. Oncol. 2022, 166, 410–416. [Google Scholar] [CrossRef] [PubMed]
  46. Yu, Z.; Pestell, T.G.; Lisanti, M.P.; Pestell, R.G. Cancer stem cells. Int. J. Biochem. Cell Biol. 2012, 44, 2144–2151. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Parte, S.; Bhartiya, D.; Telang, J.; Daithankar, V.; Salvi, V.; Zaveri, K.; Hinduja, I. Detection, characterization, and spontaneous differentiation in vitro of very small embryonic-like putative stem cells in adult mammalian ovary. Stem Cells Dev. 2011, 20, 1451–1464. [Google Scholar] [CrossRef]
  48. Skvortsova, I.; Debbage, P.; Kumar, V.; Skvortsov, S. Radiation resistance: Cancer stem cells (CSCs) and their enigmatic pro-survival signaling. Semin. Cancer Biol. 2015, 35, 39–44. [Google Scholar] [CrossRef]
  49. Lapidot, T.; Sirard, C.; Vormoor, J.; Murdoch, B.; Hoang, T.; Caceres-Cortes, J.; Minden, M.; Paterson, B.; Caligiuri, M.A.; Dick, J.E. A cell initiating human acute myeloid leukaemia after transplantation into SCID mice. Nature 1994, 367, 645–648. [Google Scholar] [CrossRef]
  50. Zong, X.; Nephew, K.P. Ovarian Cancer Stem Cells: Role in Metastasis and Opportunity for Therapeutic Targeting. Cancers 2019, 11, 934. [Google Scholar] [CrossRef] [Green Version]
  51. Xu, J.; Zheng, T.; Hong, W.; Ye, H.; Hu, C.; Zheng, Y. Mechanism for the Decision of Ovarian Surface Epithelial Stem Cells to Undergo Neo-Oogenesis or Ovarian Tumorigenesis. Cell. Physiol. Biochem. 2018, 50, 214–232. [Google Scholar] [CrossRef] [PubMed]
  52. Nakamura, K.; Terai, Y.; Tanabe, A.; Ono, Y.J.; Hayashi, M.; Maeda, K.; Fujiwara, S.; Ashihara, K.; Nakamura, M.; Tanaka, Y.; et al. CD24 expression is a marker for predicting clinical outcome and regulates the epithelial-mesenchymal transition in ovarian cancer via both the Akt and ERK pathways. Oncol. Rep. 2017, 37, 3189–3200. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Gao, M.Q.; Choi, Y.P.; Kang, S.; Youn, J.H.; Cho, N.H. CD24+ cells from hierarchically organized ovarian cancer are enriched in cancer stem cells. Oncogene 2010, 29, 2672–2680. [Google Scholar] [CrossRef] [Green Version]
  54. Burgos-Ojeda, D.; Wu, R.; McLean, K.; Chen, Y.C.; Talpaz, M.; Yoon, E.; Cho, K.R.; Buckanovich, R.J. CD24+ Ovarian Cancer Cells Are Enriched for Cancer-Initiating Cells and Dependent on JAK2 Signaling for Growth and Metastasis. Mol. Cancer Ther. 2015, 14, 1717–1727. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Zhou, J.; Du, Y.; Lu, Y.; Luan, B.; Xu, C.; Yu, Y.; Zhao, H. CD44 Expression Predicts Prognosis of Ovarian Cancer Patients Through Promoting Epithelial-Mesenchymal Transition (EMT) by Regulating Snail, ZEB1, and Caveolin-1. Front. Oncol. 2019, 9, 802. [Google Scholar] [CrossRef] [Green Version]
  56. Zhang, J.; Yuan, B.; Zhang, H.; Li, H. Human epithelial ovarian cancer cells expressing CD105, CD44 and CD106 surface markers exhibit increased invasive capacity and drug resistance. Oncol. Lett. 2019, 17, 5351–5360. [Google Scholar] [CrossRef] [Green Version]
  57. Motohara, T.; Fujimoto, K.; Tayama, S.; Narantuya, D.; Sakaguchi, I.; Tashiro, H.; Katabuchi, H. CD44 Variant 6 as a Predictive Biomarker for Distant Metastasis in Patients with Epithelial Ovarian Cancer. Obstet. Gynecol. 2016, 127, 1003–1011. [Google Scholar] [CrossRef] [PubMed]
  58. Stemberger-Papić, S.; Vrdoljak-Mozetic, D.; Ostojić, D.V.; Rubesa-Mihaljević, R.; Krigtofić, I.; Brncić-Fisher, A.; Kragević, M.; Eminović, S. Expression of CD133 and CD117 in 64 Serous Ovarian Cancer Cases. Coll. Antropol. 2015, 39, 745–753. [Google Scholar]
  59. Curley, M.D.; Therrien, V.A.; Cummings, C.L.; Sergent, P.A.; Koulouris, C.R.; Friel, A.M.; Roberts, D.J.; Seiden, M.V.; Scadden, D.T.; Rueda, B.R.; et al. CD133 expression defines a tumor initiating cell population in primary human ovarian cancer. Stem Cells 2009, 27, 2875–2883. [Google Scholar] [CrossRef]
  60. Nagare, R.P.; Sneha, S.; Sidhanth, C.; Roopa, S.; Murhekar, K.; Shirley, S.; Swaminathan, R.; Sridevi, V.; Ganesan, T.S. Expression of cancer stem cell markers CD24, EPHA1 and CD9 and their correlation with clinical outcome in epithelial ovarian tumours. Cancer Biomark. 2020, 28, 397–408. [Google Scholar] [CrossRef]
  61. Hwang, J.R.; Jo, K.; Lee, Y.; Sung, B.J.; Park, Y.W.; Lee, J.H. Upregulation of CD9 in ovarian cancer is related to the induction of TNF-α gene expression and constitutive NF-κB activation. Carcinogenesis 2012, 33, 77–83. [Google Scholar] [CrossRef] [PubMed]
  62. Bai, S.; Zhu, W.; Coffman, L.; Vlad, A.; Schwartz, L.E.; Elishaev, E.; Drapkin, R.; Buckanovich, R.J. CD105 Is Expressed in Ovarian Cancer Precursor Lesions and Is Required for Metastasis to the Ovary. Cancers 2019, 11, 1710. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Meng, E.; Mitra, A.; Tripathi, K.; Finan, M.A.; Scalici, J.; McClellan, S.; Madeira da Silva, L.; Reed, E.; Shevde, L.A.; Palle, K.; et al. ALDH1A1 maintains ovarian cancer stem cell-like properties by altered regulation of cell cycle checkpoint and DNA repair network signaling. PLoS ONE 2014, 9, e107142. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  64. Zhang, S.; Cui, B.; Lai, H.; Liu, G.; Ghia, E.M.; Widhopf, G.F., 2nd; Zhang, Z.; Wu, C.C.; Chen, L.; Wu, R.; et al. Ovarian cancer stem cells express ROR1, which can be targeted for anti-cancer-stem-cell therapy. Proc. Natl. Acad. Sci. USA 2014, 111, 17266–17271. [Google Scholar] [CrossRef] [Green Version]
  65. Ruan, Z.; Yang, X.; Cheng, W. OCT4 accelerates tumorigenesis through activating JAK/STAT signaling in ovarian cancer side population cells. Cancer Manag. Res. 2019, 11, 389–399. [Google Scholar] [CrossRef] [Green Version]
  66. Wu, D.; Xie, W.; Wang, H.; Chen, W.; Chen, X.; Sun, H. OCT4 Promotes Ovarian Cancer Cell Metastasis and Angiogenesis via Modulating VEGFR2/LRPPRC Pathway. Res. Sq. 2021. [Google Scholar] [CrossRef]
  67. Wen, Y.; Hou, Y.; Huang, Z.; Cai, J.; Wang, Z. SOX2 is required to maintain cancer stem cells in ovarian cancer. Cancer Sci. 2017, 108, 719–731. [Google Scholar] [CrossRef] [Green Version]
  68. Robinson, M.; Gilbert, S.F.; Waters, J.A.; Lujano-Olazaba, O.; Lara, J.; Alexander, L.J.; Green, S.E.; Burkeen, G.A.; Patrus, O.; Sarwar, Z.; et al. Characterization of SOX2, OCT4 and NANOG in Ovarian Cancer Tumor-Initiating Cells. Cancers 2021, 13, 262. [Google Scholar] [CrossRef]
  69. Lee, M.; Nam, E.J.; Kim, S.W.; Kim, S.; Kim, J.H.; Kim, Y.T. Prognostic impact of the cancer stem cell-related marker NANOG in ovarian serous carcinoma. Int. J. Gynecol. Cancer 2012, 22, 1489–1496. [Google Scholar] [CrossRef]
  70. Siu, M.K.; Wong, E.S.; Kong, D.S.; Chan, H.Y.; Jiang, L.; Wong, O.G.; Lam, E.W.; Chan, K.K.; Ngan, H.Y.; Le, X.F.; et al. Stem cell transcription factor NANOG controls cell migration and invasion via dysregulation of E-cadherin and FoxJ1 and contributes to adverse clinical outcome in ovarian cancers. Oncogene 2013, 32, 3500–3509. [Google Scholar] [CrossRef] [Green Version]
  71. Karvonen, H.; Arjama, M.; Kaleva, L.; Niininen, W.; Barker, H.; Koivisto-Korander, R.; Tapper, J.; Pakarinen, P.; Lassus, H.; Loukovaara, M.; et al. Glucocorticoids induce differentiation and chemoresistance in ovarian cancer by promoting ROR1-mediated stemness. Cell Death Dis. 2020, 11, 790. [Google Scholar] [CrossRef] [PubMed]
  72. Dou, J.; Jiang, C.; Wang, J.; Zhang, X.; Zhao, F.; Hu, W.; He, X.; Li, X.; Zou, D.; Gu, N. Using ABCG2-molecule-expressing side population cells to identify cancer stem-like cells in a human ovarian cell line. Cell Biol. Int. 2011, 35, 227–234. [Google Scholar] [CrossRef] [PubMed]
  73. Bagnoli, M.; Beretta, G.L.; Gatti, L.; Pilotti, S.; Alberti, P.; Tarantino, E.; Barbareschi, M.; Canevari, S.; Mezzanzanica, D.; Perego, P. Clinicopathological impact of ABCC1/MRP1 and ABCC4/MRP4 in epithelial ovarian carcinoma. BioMed Res. Int. 2013, 2013, 143202. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Jung, M.; Gao, J.; Cheung, L.; Bongers, A.; Somers, K.; Clifton, M.; Ramsay, E.E.; Russell, A.J.; Valli, E.; Gifford, A.J.; et al. ABCC4/MRP4 contributes to the aggressiveness of Myc-associated epithelial ovarian cancer. Int. J. Cancer 2020, 147, 2225–2238. [Google Scholar] [CrossRef] [PubMed]
  75. Onisim, A.; Iancu, M.; Vlad, C.; Kubelac, P.; Fetica, B.; Fulop, A.; Achimas-Cadariu, A.; Achimas-Cadariu, P. Expression of Nestin and CD133 in serous ovarian carcinoma. J. BUON 2016, 21, 1168–1175. [Google Scholar]
  76. Osman, W.M.; Shash, L.S.; Ahmed, N.S. Emerging Role of Nestin as an Angiogenesis and Cancer Stem Cell Marker in Epithelial Ovarian Cancer: Immunohistochemical Study. Appl. Immunohistochem. Mol. Morphol. 2017, 25, 571–580. [Google Scholar] [CrossRef] [PubMed]
  77. Mazzoldi, E.L.; Pavan, S.; Pilotto, G.; Leone, K.; Pagotto, A.; Frezzini, S.; Nicoletto, M.O.; Amadori, A.; Pastò, A. A juxtacrine/paracrine loop between C-Kit and stem cell factor promotes cancer stem cell survival in epithelial ovarian cancer. Cell Death Dis. 2019, 10, 412. [Google Scholar] [CrossRef] [Green Version]
  78. Oktem, G.; Sanci, M.; Bilir, A.; Yildirim, Y.; Kececi, S.D.; Ayla, S.; Inan, S. Cancer stem cell and embryonic development-associated molecules contribute to prognostic significance in ovarian cancer. Int. J. Gynecol. Cancer 2012, 22, 23–29. [Google Scholar] [CrossRef]
  79. Seo, E.J.; Kim, D.K.; Jang, I.H.; Choi, E.J.; Shin, S.H.; Lee, S.I.; Kwon, S.M.; Kim, K.H.; Suh, D.S.; Kim, J.H. Hypoxia-NOTCH1-SOX2 signaling is important for maintaining cancer stem cells in ovarian cancer. Oncotarget 2016, 7, 55624–55638. [Google Scholar] [CrossRef] [Green Version]
  80. Abd El hafez, A.; El-Hadaad, H.A. Immunohistochemical expression and prognostic relevance of Bmi-1, a stem cell factor, in epithelial ovarian cancer. Ann. Diagn. Pathol. 2014, 18, 58–62. [Google Scholar] [CrossRef]
  81. Zhao, Q.; Qian, Q.; Cao, D.; Yang, J.; Gui, T.; Shen, K. Role of BMI1 in epithelial ovarian cancer: Investigated via the CRISPR/Cas9 system and RNA sequencing. J. Ovarian Res. 2018, 11, 31. [Google Scholar] [CrossRef]
  82. Gil, M.; Komorowski, M.P.; Seshadri, M.; Rokita, H.; McGray, A.J.; Opyrchal, M.; Odunsi, K.O.; Kozbor, D. CXCL12/CXCR4 blockade by oncolytic virotherapy inhibits ovarian cancer growth by decreasing immunosuppression and targeting cancer-initiating cells. J. Immunol. 2014, 193, 5327–5337. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Sekiya, R.; Kajiyama, H.; Sakai, K.; Umezu, T.; Mizuno, M.; Shibata, K.; Yamamoto, E.; Fujiwara, S.; Nagasaka, T.; Kikkawa, F. Expression of CXCR4 indicates poor prognosis in patients with clear cell carcinoma of the ovary. Human Pathol. 2012, 43, 904–910. [Google Scholar] [CrossRef] [PubMed]
  84. Tayama, S.; Motohara, T.; Narantuya, D.; Li, C.; Fujimoto, K.; Sakaguchi, I.; Tashiro, H.; Saya, H.; Nagano, O.; Katabuchi, H. The impact of EpCAM expression on response to chemotherapy and clinical outcomes in patients with epithelial ovarian cancer. Oncotarget 2017, 8, 44312–44325. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  85. Spizzo, G.; Fong, D.; Wurm, M.; Ensinger, C.; Obrist, P.; Hofer, C.; Mazzoleni, G.; Gastl, G.; Went, P. EpCAM expression in primary tumour tissues and metastases: An immunohistochemical analysis. J. Clin. Pathol. 2011, 64, 415–420. [Google Scholar] [CrossRef] [Green Version]
  86. Motohara, T.; Masuko, S.; Ishimoto, T.; Yae, T.; Onishi, N.; Muraguchi, T.; Hirao, A.; Matsuzaki, Y.; Tashiro, H.; Katabuchi, H.; et al. Transient depletion of p53 followed by transduction of c-Myc and K-Ras converts ovarian stem-like cells into tumor-initiating cells. Carcinogenesis 2011, 32, 1597–1606. [Google Scholar] [CrossRef] [Green Version]
  87. Ye, F.; Li, Y.; Hu, Y.; Zhou, C.; Hu, Y.; Chen, H. Stage-specific embryonic antigen 4 expression in epithelial ovarian carcinoma. Int. J. Gynecol. Cancer 2010, 20, 958–964. [Google Scholar] [CrossRef] [PubMed]
  88. Cui, Y.; Wu, B.O.; Flamini, V.; Evans, B.A.J.; Zhou, D.; Jiang, W.G. Knockdown of EPHA1 Using CRISPR/CAS9 Suppresses Aggressive Properties of Ovarian Cancer Cells. Anticancer Res. 2017, 37, 4415–4424. [Google Scholar] [CrossRef] [Green Version]
  89. Castellarin, M.; Milne, K.; Zeng, T.; Tse, K.; Mayo, M.; Zhao, Y.; Webb, J.R.; Watson, P.H.; Nelson, B.H.; Holt, R.A. Clonal evolution of high-grade serous ovarian carcinoma from primary to recurrent disease. J. Pathol. 2013, 229, 515–524. [Google Scholar] [CrossRef]
  90. Bashashati, A.; Ha, G.; Tone, A.; Ding, J.; Prentice, L.M.; Roth, A.; Rosner, J.; Shumansky, K.; Kalloger, S.; Senz, J.; et al. Distinct evolutionary trajectories of primary high-grade serous ovarian cancers revealed through spatial mutational profiling. J. Pathol. 2013, 231, 21–34. [Google Scholar] [CrossRef] [Green Version]
  91. Takahashi-Yanaga, F.; Kahn, M. Targeting Wnt signaling: Can we safely eradicate cancer stem cells? Clin. Cancer Res. 2010, 16, 3153–3162. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  92. Borah, A.; Raveendran, S.; Rochani, A.; Maekawa, T.; Kumar, D.S. Targeting self-renewal pathways in cancer stem cells: Clinical implications for cancer therapy. Oncogenesis 2015, 4, e177. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  93. Arend, R.C.; Londoño-Joshi, A.I.; Straughn, J.M., Jr.; Buchsbaum, D.J. The Wnt/β-catenin pathway in ovarian cancer: A review. Gynecol. Oncol. 2013, 131, 772–779. [Google Scholar] [CrossRef] [PubMed]
  94. Xiang, T.; Long, H.; He, L.; Han, X.; Lin, K.; Liang, Z.; Zhuo, W.; Xie, R.; Zhu, B. Interleukin-17 produced by tumor microenvironment promotes self-renewal of CD133+ cancer stem-like cells in ovarian cancer. Oncogene 2015, 34, 165–176. [Google Scholar] [CrossRef]
  95. Jiang, L.Y.; Zhang, X.L.; Du, P.; Zheng, J.H. γ-Secretase Inhibitor, DAPT Inhibits Self-renewal and Stemness Maintenance of Ovarian Cancer Stem-like Cells In Vitro. Chin. J. Cancer Res. 2011, 23, 140–146. [Google Scholar] [CrossRef] [Green Version]
  96. Le, P.N.; McDermott, J.D.; Jimeno, A. Targeting the Wnt pathway in human cancers: Therapeutic targeting with a focus on OMP-54F28. Pharmacol. Ther. 2015, 146, 1–11. [Google Scholar] [CrossRef] [Green Version]
  97. Boone, J.D.; Arend, R.C.; Johnston, B.E.; Cooper, S.J.; Gilchrist, S.A.; Oelschlager, D.K.; Grizzle, W.E.; McGwin, G., Jr.; Gangrade, A.; Straughn, J.M., Jr.; et al. Targeting the Wnt/β-catenin pathway in primary ovarian cancer with the porcupine inhibitor WNT974. Lab. Investig. 2016, 96, 249–259. [Google Scholar] [CrossRef] [Green Version]
  98. Doo, D.W.; Meza-Perez, S.; Londoño, A.I.; Goldsberry, W.N.; Katre, A.A.; Boone, J.D.; Moore, D.J.; Hudson, C.T.; Betella, I.; McCaw, T.R.; et al. Inhibition of the Wnt/β-catenin pathway enhances antitumor immunity in ovarian cancer. Ther. Adv. Med. Oncol. 2020, 12, 1758835920913798. [Google Scholar] [CrossRef] [Green Version]
  99. Nagaraj, A.B.; Joseph, P.; Kovalenko, O.; Singh, S.; Armstrong, A.; Redline, R.; Resnick, K.; Zanotti, K.; Waggoner, S.; DiFeo, A. Critical role of Wnt/β-catenin signaling in driving epithelial ovarian cancer platinum resistance. Oncotarget 2015, 6, 23720–23734. [Google Scholar] [CrossRef] [Green Version]
  100. Diamond, J.R.; Becerra, C.; Richards, D.; Mita, A.; Osborne, C.; O’Shaughnessy, J.; Zhang, C.; Henner, R.; Kapoun, A.M.; Xu, L.; et al. Phase Ib clinical trial of the anti-frizzled antibody vantictumab (OMP-18R5) plus paclitaxel in patients with locally advanced or metastatic HER2-negative breast cancer. Breast Cancer Res. Treat. 2020, 184, 53–62. [Google Scholar] [CrossRef]
  101. Yousefi, M.; Rajaie, S.; Keyvani, V.; Bolandi, S.; Hasanzadeh, M.; Pasdar, A. Clinical significance of circulating tumor cell related markers in patients with epithelial ovarian cancer before and after adjuvant chemotherapy. Sci. Rep. 2021, 11, 10524. [Google Scholar] [CrossRef] [PubMed]
  102. Pradeep, S.; Kim, S.W.; Wu, S.Y.; Nishimura, M.; Chaluvally-Raghavan, P.; Miyake, T.; Pecot, C.V.; Kim, S.J.; Choi, H.J.; Bischoff, F.Z.; et al. Hematogenous metastasis of ovarian cancer: Rethinking mode of spread. Cancer Cell 2014, 26, 77–91. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  103. Abreu, M.; Cabezas-Sainz, P.; Alonso-Alconada, L.; Ferreirós, A.; Mondelo-Macía, P.; Lago-Lestón, R.M.; Abalo, A.; Díaz, E.; Palacios-Zambrano, S.; Rojo-Sebastian, A.; et al. Circulating Tumor Cells Characterization Revealed TIMP1 as a Potential Therapeutic Target in Ovarian Cancer. Cells 2020, 9, 1218. [Google Scholar] [CrossRef]
  104. Zhao, Z.; Yang, Y.; Zeng, Y.; He, M. A microfluidic ExoSearch chip for multiplexed exosome detection towards blood-based ovarian cancer diagnosis. Lab A Chip 2016, 16, 489–496. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  105. Teeuwssen, M.; Fodde, R. Wnt Signaling in Ovarian Cancer Stemness, EMT, and Therapy Resistance. J. Clin. Med. 2019, 8, 1658. [Google Scholar] [CrossRef] [Green Version]
  106. Niehrs, C. The complex world of WNT receptor signalling. Nat. Rev. Mol. Cell Biol. 2012, 13, 767–779. [Google Scholar] [CrossRef] [PubMed]
  107. Ge, X.; Wang, X. Role of Wnt canonical pathway in hematological malignancies. J. Hematol. Oncol. 2010, 3, 33. [Google Scholar] [CrossRef] [Green Version]
  108. Pai, S.G.; Carneiro, B.A.; Mota, J.M.; Costa, R.; Leite, C.A.; Barroso-Sousa, R.; Kaplan, J.B.; Chae, Y.K.; Giles, F.J. Wnt/beta-catenin pathway: Modulating anticancer immune response. J. Hematol. Oncol. 2017, 10, 101. [Google Scholar] [CrossRef] [Green Version]
  109. Zhang, Y.; Wang, X. Targeting the Wnt/β-catenin signaling pathway in cancer. J. Hematol. Oncol. 2020, 13, 165. [Google Scholar] [CrossRef]
  110. Tsukamoto, A.S.; Grosschedl, R.; Guzman, R.C.; Parslow, T.; Varmus, H.E. Expression of the int-1 gene in transgenic mice is associated with mammary gland hyperplasia and adenocarcinomas in male and female mice. Cell 1988, 55, 619–625. [Google Scholar] [CrossRef]
  111. Zhan, T.; Rindtorff, N.; Boutros, M. Wnt signaling in cancer. Oncogene 2017, 36, 1461–1473. [Google Scholar] [CrossRef] [PubMed]
  112. Parker, T.W.; Neufeld, K.L. APC controls Wnt-induced β-catenin destruction complex recruitment in human colonocytes. Sci. Rep. 2020, 10, 2957. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  113. Jeays-Ward, K.; Hoyle, C.; Brennan, J.; Dandonneau, M.; Alldus, G.; Capel, B.; Swain, A. Endothelial and steroidogenic cell migration are regulated by WNT4 in the developing mammalian gonad. Development 2003, 130, 3663–3670. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  114. Aiello, N.M.; Maddipati, R.; Norgard, R.J.; Balli, D.; Li, J.; Yuan, S.; Yamazoe, T.; Black, T.; Sahmoud, A.; Furth, E.E.; et al. EMT Subtype Influences Epithelial Plasticity and Mode of Cell Migration. Dev. Cell 2018, 45, 681–695. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  115. Hudson, L.G.; Zeineldin, R.; Stack, M.S. Phenotypic plasticity of neoplastic ovarian epithelium: Unique cadherin profiles in tumor progression. Clin. Exp. Metastasis 2008, 25, 643–655. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  116. Huang, R.Y.; Wong, M.K.; Tan, T.Z.; Kuay, K.T.; Ng, A.H.; Chung, V.Y.; Chu, Y.S.; Matsumura, N.; Lai, H.C.; Lee, Y.F.; et al. An EMT spectrum defines an anoikis-resistant and spheroidogenic intermediate mesenchymal state that is sensitive to e-cadherin restoration by a src-kinase inhibitor, saracatinib (AZD0530). Cell Death Dis. 2013, 4, e915. [Google Scholar] [CrossRef] [Green Version]
  117. Hojo, N.; Huisken, A.L.; Wang, H.; Chirshev, E.; Kim, N.S.; Nguyen, S.M.; Campos, H.; Glackin, C.A.; Ioffe, Y.J.; Unternaehrer, J.J. Snail knockdown reverses stemness and inhibits tumour growth in ovarian cancer. Sci. Rep. 2018, 8, 8704. [Google Scholar] [CrossRef] [Green Version]
  118. Wu, Z.Q.; Li, X.Y.; Hu, C.Y.; Ford, M.; Kleer, C.G.; Weiss, S.J. Canonical Wnt signaling regulates Slug activity and links epithelial-mesenchymal transition with epigenetic Breast Cancer 1, Early Onset (BRCA1) repression. Proc. Natl. Acad. Sci. USA 2012, 109, 16654–16659. [Google Scholar] [CrossRef] [Green Version]
  119. Jacob, F.; Ukegjini, K.; Nixdorf, S.; Ford, C.E.; Olivier, J.; Caduff, R.; Scurry, J.P.; Guertler, R.; Hornung, D.; Mueller, R.; et al. Loss of secreted frizzled-related protein 4 correlates with an aggressive phenotype and predicts poor outcome in ovarian cancer patients. PLoS ONE 2012, 7, e31885. [Google Scholar] [CrossRef] [Green Version]
  120. Saran, U.; Arfuso, F.; Zeps, N.; Dharmarajan, A. Secreted frizzled-related protein 4 expression is positively associated with responsiveness to cisplatin of ovarian cancer cell lines in vitro and with lower tumour grade in mucinous ovarian cancers. BMC Cell Biol. 2012, 13, 25. [Google Scholar] [CrossRef] [Green Version]
  121. Y, K.N.; Perumalsamy, N.K.; Warrier, S.; Perumalsamy, L.R.; Dharmarajan, A. Wnt antagonist as therapeutic targets in ovarian cancer. Int. J. Biochem. Cell Biol. 2022, 145, 106191. [Google Scholar] [CrossRef]
  122. Pohl, S.; Scott, R.; Arfuso, F.; Perumal, V.; Dharmarajan, A. Secreted frizzled-related protein 4 and its implications in cancer and apoptosis. Tumour Biol. 2015, 36, 143–152. [Google Scholar] [CrossRef] [PubMed]
  123. Deshmukh, A.; Kumar, S.; Arfuso, F.; Newsholme, P.; Dharmarajan, A. Secreted Frizzled-related protein 4 (sFRP4) chemo-sensitizes cancer stem cells derived from human breast, prostate, and ovary tumor cell lines. Sci. Rep. 2017, 7, 2256. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  124. Belur Nagaraj, A.; Knarr, M.; Sekhar, S.; Connor, R.S.; Joseph, P.; Kovalenko, O.; Fleming, A.; Surti, A.; Nurmemmedov, E.; Beltrame, L.; et al. The miR-181a-SFRP4 Axis Regulates Wnt Activation to Drive Stemness and Platinum Resistance in Ovarian Cancer. Cancer Res. 2021, 81, 2044–2055. [Google Scholar] [CrossRef] [PubMed]
  125. Sundaram, S.M.; Varier, L.; Fathima, K.Z.; Dharmarajan, A.; Warrier, S. Short peptide domains of the Wnt inhibitor sFRP4 target ovarian cancer stem cells by neutralizing the Wnt β-catenin pathway, disrupting the interaction between β-catenin and CD24 and suppressing autophagy. Life Sci. 2023, 316, 121384. [Google Scholar] [CrossRef] [PubMed]
  126. Sharif, T.; Martell, E.; Dai, C.; Kennedy, B.E.; Murphy, P.; Clements, D.R.; Kim, Y.; Lee, P.W.; Gujar, S.A. Autophagic homeostasis is required for the pluripotency of cancer stem cells. Autophagy 2017, 13, 264–284. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Figure 1. Summary of the widely used treatment strategies for ovarian cancer based on surgical staging and other treatment options in the case of disease recurrence.
Figure 1. Summary of the widely used treatment strategies for ovarian cancer based on surgical staging and other treatment options in the case of disease recurrence.
Cancers 15 01275 g001
Figure 2. Wnt signaling pathways. Wnt canonical (β-catenin dependent) and Wnt non-canonical (Planar cell polarity and Calcium) pathways. AP-1, Activation protein 1; APC, Adenomatosis polyposis coli; Ca2+, Calcium; CalN, Calcineurin; CAMKII, Calcium-calmodulin-dependent kinase II; Cdc42, Cell division control protein 42 homolog; CK1α, Casein kinase 1 alpha; CREB, cAMP response element-binding protein; DAAM1/2, Disheveled-associated activator of morphogenesis 1/2; DAG, Diacylglycerol; Dkk, Dickkopf; Dvl, Disheveled; FZD, Frizzled; GSK3β, Glycogen synthase kinase 3β; IP3, Inositol 1,4,5-triphosphate; JNK, c-Jun N-terminal kinase; LEF, Lymphoid enhancer-binding factors; LRP 5/6, Low-density lipoprotein receptor-related protein 5 or 6; MAP2K 4/7, Mitogen-activated protein kinase kinase 4/7; MAP3Ks, Mitogen-activated protein kinase kinase kinase; NFAT, Nuclear factor of activated T cells; NFκB, Nuclear factor kappa light chain enhancer of activated B cells; NLK, Nemo-like kinase; PDE, Phosphodiesterase; PKC, Protein kinase C; PKG, Protein kinase G; PLC, Phospholipase C; Rac, Ras-related C3 botulinum toxin substrate; RhoA, Ras homolog family member A; ROCK, Rho Kinase; ROR2, RAR-related orphan receptor 2; Ryk, receptor-like tyrosine kinase; sFRP, Secreted frizzled related protein; TCF, Transcription factors T cell factor; WIF, Wnt inhibitory factor; Wnt, Wingless-type MMTV integration site.
Figure 2. Wnt signaling pathways. Wnt canonical (β-catenin dependent) and Wnt non-canonical (Planar cell polarity and Calcium) pathways. AP-1, Activation protein 1; APC, Adenomatosis polyposis coli; Ca2+, Calcium; CalN, Calcineurin; CAMKII, Calcium-calmodulin-dependent kinase II; Cdc42, Cell division control protein 42 homolog; CK1α, Casein kinase 1 alpha; CREB, cAMP response element-binding protein; DAAM1/2, Disheveled-associated activator of morphogenesis 1/2; DAG, Diacylglycerol; Dkk, Dickkopf; Dvl, Disheveled; FZD, Frizzled; GSK3β, Glycogen synthase kinase 3β; IP3, Inositol 1,4,5-triphosphate; JNK, c-Jun N-terminal kinase; LEF, Lymphoid enhancer-binding factors; LRP 5/6, Low-density lipoprotein receptor-related protein 5 or 6; MAP2K 4/7, Mitogen-activated protein kinase kinase 4/7; MAP3Ks, Mitogen-activated protein kinase kinase kinase; NFAT, Nuclear factor of activated T cells; NFκB, Nuclear factor kappa light chain enhancer of activated B cells; NLK, Nemo-like kinase; PDE, Phosphodiesterase; PKC, Protein kinase C; PKG, Protein kinase G; PLC, Phospholipase C; Rac, Ras-related C3 botulinum toxin substrate; RhoA, Ras homolog family member A; ROCK, Rho Kinase; ROR2, RAR-related orphan receptor 2; Ryk, receptor-like tyrosine kinase; sFRP, Secreted frizzled related protein; TCF, Transcription factors T cell factor; WIF, Wnt inhibitory factor; Wnt, Wingless-type MMTV integration site.
Cancers 15 01275 g002
Figure 3. Differential inhibition of Wnt β-catenin-dependent signaling pathway by sFRP4 and its micropeptides. sFRP4 antagonizes Wnt β-catenin-dependent signaling pathway by (i) binding to FZD via its cysteine-rich domain (CRD) and (ii) binding with Wnt via its netrin-like domain (NLD). SC301 derived from CRD domain binds to FZD, whereas SC401 derived from NLD domain binds with Wnt. Inhibition of Wnt signaling leads to phosphorylation of β-catenin and its subsequent proteasomal degradation. Lack of β-catenin–TCF/LEF interaction in the nucleus causes suppression of angiogenesis and cancer stem cell (CSC) genes along with activation of apoptosis. CRD, Cysteine-rich domain; CSC, Cancer stem cell; NLD, Netrin-like domain.
Figure 3. Differential inhibition of Wnt β-catenin-dependent signaling pathway by sFRP4 and its micropeptides. sFRP4 antagonizes Wnt β-catenin-dependent signaling pathway by (i) binding to FZD via its cysteine-rich domain (CRD) and (ii) binding with Wnt via its netrin-like domain (NLD). SC301 derived from CRD domain binds to FZD, whereas SC401 derived from NLD domain binds with Wnt. Inhibition of Wnt signaling leads to phosphorylation of β-catenin and its subsequent proteasomal degradation. Lack of β-catenin–TCF/LEF interaction in the nucleus causes suppression of angiogenesis and cancer stem cell (CSC) genes along with activation of apoptosis. CRD, Cysteine-rich domain; CSC, Cancer stem cell; NLD, Netrin-like domain.
Cancers 15 01275 g003
Table 1. Major subtypes of epithelial ovarian cancer and mutations associated with them.
Table 1. Major subtypes of epithelial ovarian cancer and mutations associated with them.
CategoryHigh-Grade SerousLow-Grade SerousMucinousEndometrioidClear Cell
% in population70–743–52–67–2410–26
OriginFallopian tube epitheliumFallopian tube epitheliumUnknownEndometriosisEndometriosis
Associated mutationsTP53, PIK3CA, BRCA1/2KRAS, BRAF, ERB2KRAS, HER 2
amplification
CTNNB1,
PTEN
ARID1A, PIKC3A,
CTNNB1,
MSI
Table 2. Existing markers of ovarian cancer stem cell and their role in disease progression.
Table 2. Existing markers of ovarian cancer stem cell and their role in disease progression.
Ovarian CSC MarkersProtein TypeRole in Ovarian CSCsReference
CD24Mucin type glycoproteinPoor prognosis, EMT, self-renewal, quiescence, resistance, sphere-forming capacity[52,53,54]
CD44Cell-surface glycoproteinPoor prognosis, migration, invasion, drug resistance, poor differentiation, high rate of recurrence, predictive marker for distant metastasis[55,56,57]
CD117Receptor tyrosine kinasePoor prognosis[58]
CD133Pentaspan transmembrane glycoproteinSphere-forming capacity, increased tumorigenic capacity[54,59]
CD9TetraspaninsPoor prognosis, induces cell growth, activates NF-κB-signaling pathway[60,61]
CD105Endoglin (ENG)- Type I membrane glycoproteinDrug resistance, advanced disease stage, poor differentiation, high rate of recurrence, metastasis[56,62]
CD106Vascular cell adhesion moleculeDrug resistance, advanced disease stage, poor differentiation, high rate of recurrence[56]
ALDH1Cytosolic isoform of
acetaldehyde dehydrogenase
Chemoresistance, invasion, colony formation[63,64]
OCT4Transcription factorDrug resistance, proliferation, activates JAK/STAT signaling pathway, angiogenesis, metastasis[65,66]
SOX2Transcription factorSpheroid formation, cell proliferation, cell migration, chemoresistance, tumorigenicity, stemness, relapse[67,68]
NANOGTranscription factorPoor prognosis, migration, invasion[69,70]
ROR1Receptor tyrosine kinasesSelf-renewal, chemoresistance[64,71]
ABCG2ATP-binding cassette transporterDrug resistance, self-renewal, proliferation[72]
ABCC1ATP-binding cassette transporterGrading of cancer[73]
ABCC4ATP-binding cassette transporterRelapse, chemoresistance[73,74]
NESTINType VI intermediate filament proteinChemoresistance, poor prognosis, angiogenesis[75,76]
SCFUbiquitin ligasesPromote stemness properties[77]
NOTCH1Type 1 transmembrane proteinPrognosis, Sphere formation, drug resistance, modulates expression of genes such as SOX2, ALDH and ABC transporters[78,79]
Bmi-1Member of the Polycomb repressor complex 1Prognosis, cell growth, metastasis, anti-apoptotic function, chemoresistance[80,81]
CXCR4G-coupled chemokine receptorMaintaining stemness, prognosis[82,83]
EpCAMEpithelial cell adhesion/activating moleculeChemoresistance, metastasis, maintenance of stemness, tumor initiation[84,85,86]
SSEA4Sialyl-glycolipidAdvanced tumor stage, poorer tumor cell differentiation[87]
EPHA1Receptor tyrosine kinaseTumor aggressiveness, proliferation, invasion, migration[60,88]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Varier, L.; Sundaram, S.M.; Gamit, N.; Warrier, S. An Overview of Ovarian Cancer: The Role of Cancer Stem Cells in Chemoresistance and a Precision Medicine Approach Targeting the Wnt Pathway with the Antagonist sFRP4. Cancers 2023, 15, 1275. https://doi.org/10.3390/cancers15041275

AMA Style

Varier L, Sundaram SM, Gamit N, Warrier S. An Overview of Ovarian Cancer: The Role of Cancer Stem Cells in Chemoresistance and a Precision Medicine Approach Targeting the Wnt Pathway with the Antagonist sFRP4. Cancers. 2023; 15(4):1275. https://doi.org/10.3390/cancers15041275

Chicago/Turabian Style

Varier, Lavanya, S. Mohana Sundaram, Naisarg Gamit, and Sudha Warrier. 2023. "An Overview of Ovarian Cancer: The Role of Cancer Stem Cells in Chemoresistance and a Precision Medicine Approach Targeting the Wnt Pathway with the Antagonist sFRP4" Cancers 15, no. 4: 1275. https://doi.org/10.3390/cancers15041275

APA Style

Varier, L., Sundaram, S. M., Gamit, N., & Warrier, S. (2023). An Overview of Ovarian Cancer: The Role of Cancer Stem Cells in Chemoresistance and a Precision Medicine Approach Targeting the Wnt Pathway with the Antagonist sFRP4. Cancers, 15(4), 1275. https://doi.org/10.3390/cancers15041275

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop