*Review* **Statins as Repurposed Drugs in Gynecological Cancer: A Review**

**Kai-Hung Wang <sup>1</sup> , Chin-Hung Liu <sup>2</sup> and Dah-Ching Ding 3,4,\***


**Abstract:** Discovering new drugs is an expensive and time-consuming process, including target identification, bioavailability, pharmacokinetic (PK) tests, pharmacodynamic (PD) tests, toxicity profiles, recommended dosage test, and observation of the side effects, etc. Repurposed drugs could bypass some steps, starting from phase II trials, and shorten the processes. Statins, also known as HMG-CoA inhibitors (HMGCR), are commonly used to manage and prevent various cardiovascular diseases and have been shown to improve the morbidity and mortality of patients. In addition to the inhibitory effects on the production of cholesterol, the beneficial effects of statins on the prognosis and risk of various cancers are also shown. Statins not only inhibited cell proliferation, metastasis, and chemoresistance but affected the tumor microenvironment (TME). Thus, statins have great potential to be repurposed in oncology. Hence, we review the meta-analysis, cohort, and case-control studies of statins in gynecological cancers, and elucidate how statins regulate cell proliferation, apoptosis, tumor growth, and metastasis. Although the results in gynecological cancers remain controversial and the effects of different statins in different histotypes of gynecological cancers and TME are needed to elucidate further, statins are excellent candidates and worthy of being repurposed drugs in treating gynecological cancers.

**Keywords:** statins; repurposed drugs; gynecological cancer; endometrial cancer; ovarian cancer; cervical cancer

#### **1. Introduction**

Gynecological cancer is any cancer that starts in a woman's reproductive organs, including cervical, endometrial, ovarian, vaginal, and vulvar cancer. The treatments generally include surgery, radiation therapy, chemotherapy, target therapy, and immunotherapy. Combination therapy is a trend worldwide. However, discovering new drugs or targets is always the mission against cancers. There is an established setting for new drug discovery from pre-clinical results, in vitro and in vivo, to human studies, phase I and II trials, and a phase III randomized controlled trial (RCT). It is expensive and takes over 10 years in all processes [1]. Thus, if the existing drugs could be repurposed, it can dramatically reduce costs and save time, benefiting patients who suffer from these malignant and lethal diseases.

Statins, as 3-hydroxy-3-methyl-glutaryl-CoA (HMG-CoA) reductase competitive inhibitors (HMGCR), are commonly used as lipid-lowering drugs, preventing cardiovascular diseases. However, the anti-cancer properties of statins have been investigated in recent decades, showing better prognoses in various types of cancer through various mechanisms [2,3]. The evidence of the anti-cancer effects of statins in gynecological cancers is sparse and controversial, thus, we review and assess the potential of statins as repurposed drugs in gynecological cancers.

**Citation:** Wang, K.-H.; Liu, C.-H.; Ding, D.-C. Statins as Repurposed Drugs in Gynecological Cancer: A Review. *Int. J. Mol. Sci.* **2022**, *23*, 13937. https://doi.org/10.3390/ ijms232213937

Academic Editor: Laura Paleari

Received: 30 October 2022 Accepted: 10 November 2022 Published: 11 November 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

#### **2. Cervical Cancer and Human Papillomavirus (HPV)**

Cervical cancer is the fourth most common cancer in women and the fourth highest mortality rate worldwide. Cervical cancer diagnoses for 6.6% of all cancer types with a mortality rate of 7.5% in 2018 [4]. For diagnosis of cervical cancer from cytologic examination, the precancerous stage includes low-grade squamous intra-epithelial lesion (LSIL or mild dysplasia) and high-grade squamous intra-epithelial lesion [HSIL or moderate dysplasia, severe dysplasia, and carcinoma in situ (CIS)], and the cancer types include squamous cell carcinoma (SCC), and adenocarcinoma. The diagnosis of cervical cancer from histologic examination includes cervical intraepithelial neoplasia 1 (CIN1), CIN2, and CIN3 and cancer lesions. LSIL is relatively equal to CIN1, while HSIL is relatively equal to CIN2 and CIN3 [5].

Human papillomavirus (HPV) has been defined as a carcinogen, especially the highrisk types, and the persistence of HPV infection was a necessary etiological cause of cervical cancer [6]. High-risk HPV (HR-HPV) types include HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68 [7]. Inoculation of HPV vaccines showed long-term efficacy and could prevent cervical cancer [8]. The ideal age for the administration of the HPV vaccines is 10 to 13 years. In low-resource settings, the simple and inexpensive way is to start with visual inspections only or in combination with HPV tests. In high-resource situations, it starts with cytologic tests (pap smear test) and HPV tests to screen cervical cancer patients [9].

#### **3. Endometrial Cancer and Its Risk Factors**

Endometrial cancer (EC) is the sixth most common cancer in females and the second most commonly diagnosed cancer of female reproductive organs. Around 417,000 new cases were detected, and 97,000 women died worldwide from the disease in 2020 [10] [11]. There are two main types of ECs that were characterized. Type I ECs, around ~80%, are mostly well differentiated with endometrioid histology and show a high level of estrogen receptor (ER). Type II ECs are poorly differentiated with serous or clear cell histology and show a high recurrence rate (80%~90%) within 3 years, representing a poor prognosis [12]. In addition, ECs can be low-grade (grades 1 and 2) tumors which are generally associated with a better prognosis, or high-grade carcinomas (grade 3) carrying an intermediate prognosis [13]. The risk factors for EC include high body mass index (BMI: kg/m<sup>2</sup> ), often with other components of metabolic syndrome (e.g., hypertension, diabetes), nulliparity or infertility, early menarche, and late menopause.

The relative risk (RR) for developing EC with metabolic syndrome was 1.89 [95% confidence interval (CI) 1.34 to 2.67, *p* < 0.001] among the components of metabolic syndrome. Obesity (BMI > 30) was associated with the greatest increase in RR of 2.21 (*p* < 0.001). Other components of the metabolic syndrome linked to endometrial cancer include hypertension, with a RR of 1.81 (*p* < 0.05). [14] Type II Diabetes mellitus (DM) showed an independent risk factor for EC, with an approximate doubling of risk [Odds ratio (OR) was 2.18, 95% CI 1.40 to 3.41] [15]. Among the causes of infertility, polycystic ovarian syndrome (PCOS) showed an increase in risk (OR = 2.79, 95% CI 1.31 to 5.95) [16]. Both early menarche (RR was 2.4 for women <12 vs. ≥15 years) [17], and late menopause (RR = 1.8 for women ≥55 versus <50 years) [18] are associated with increased risk for EC.

#### **4. Ovarian Cancer and Its Risk Factors**

Ovarian cancer is the leading disease of death in females diagnosed with gynecological cancers. In the meantime, it is women's fifth most frequent cause of death. There are approximately 21,750 new ovarian cancer cases in the US, comprising 1.2% of all cancer cases. The estimated number of deaths related to ovarian cancer was 13,940 in 2020 [19]. Among the ovarian cancer subtypes, type II high-grade serous carcinoma (HGSC) is the most prevalent and lethal, representing more than 70% of ovarian cancer. Type I tumor includes low-grade serous, endometrioid, clear-cell, and mucinous carcinomas, presenting at an early stage and carrying a good prognosis except for clear-cell [20]. HGSCs arise

from serous tubal intraepithelial carcinoma (STIC) in the fimbriae of the tube, undergoing malignant transformation and metastasizing to the nearby ovaries and peritoneum [21,22].

The risks of ovarian cancer were increasing in postmenopausal women and those with a family history of breast or ovarian cancer. At the same time, pregnancy, lactation, and oral contraceptive pills reduced the risks [23]. Moreover, obesity was an independent prognostic factor in addition to advanced tumor staging and positive ascites cytology. The hazard ratio (HR) of overall survival (OS) was 1.871, 95% CI 1.005 to 3.486 in all ovarian cancer patients, and the HR was elevated to 2.405, 95% CI 1.335 to 4.333 in pT3 stage patients [24].

#### **5. Statins, HMG-CoA Reductase Inhibitor (HMGCR) and the Role in the Tumor Microenvironment (TME)**

#### *5.1. Statins, Lipid-Lowering Drugs*

Statins are traditionally applied in cardiovascular diseases to reduce cholesterol [25] and could be divided into two groups: type-I derivatives (from fermentation, including mevastatin, lovastatin, pravastatin, and simvastatin), and type-II drugs (from the synthetic origin, including fluvastatin, atorvastatin, cerivastatin, pitavastatin, and rosuvastatin) [26,27]. The main role of statin in the mevalonate pathway is inhibiting HMG-CoA reductase (HMGCR), resulting in the depletion of LDL cholesterol [28] (Figure 1). The statins were used between 10–80 mg, and the metabolic pathway of statins was major through CYP3A4 [29] (Table 1). However, recent studies suggested that statins could have anti-tumor effects (Figures 1 and 2), from meta-analysis and bench, in vitro and in vivo. *Int. J. Mol. Sci.* **2022**, *23*, x FOR PEER REVIEW 4 of 17

**Figure 1.** The mevalonate pathway and the role of statin in regulating tumor progression and biosynthesis of cholesterol. **Figure 1.** The mevalonate pathway and the role of statin in regulating tumor progression and biosynthesis of cholesterol.

**Table 1.** The doses and metabolic pathway of statins.


CYP3A4: cytochrome P450, subfamily IIIA, polypeptide 4. CYP2C9: cytochrome P450, subfamily IIC, polypeptide 9. High dose: reduce LDL ≥ 50%, moderate dose: reduce LDL 30–49%, low dose: reduce LDL < 30%.

> **Figure 2.** The effects of statins on anti-tumor progression and tumor microenvironment (TME). TME includes immune cells and MSCs. Green arrows represent inhibitory effects, and red arrows repre-

> The most investigated statin in cancer is simvastatin. In general, the role of statins was tumor suppressor. Statins could induce cancer cell apoptosis through traditional

sent promoting effects.

*5.2. Statins in Cancer* 

**Figure 2.** The effects of statins on anti-tumor progression and tumor microenvironment (TME). TME includes immune cells and MSCs. Green arrows represent inhibitory effects, and red arrows repre-**Figure 2.** The effects of statins on anti-tumor progression and tumor microenvironment (TME). TME includes immune cells and MSCs. Green arrows represent inhibitory effects, and red arrows represent promoting effects.

**Figure 1.** The mevalonate pathway and the role of statin in regulating tumor progression and bio-

#### sent promoting effects. *5.2. Statins in Cancer*

synthesis of cholesterol.

*5.2. Statins in Cancer*  The most investigated statin in cancer is simvastatin. In general, the role of statins was tumor suppressor. Statins could induce cancer cell apoptosis through traditional The most investigated statin in cancer is simvastatin. In general, the role of statins was tumor suppressor. Statins could induce cancer cell apoptosis through traditional caspases cascade and inhibit cell proliferation, migration, invasion, epithelial-mesenchymal transition (EMT), and chemoresistances in various types of cancer (Figure 2), including breast, lung, pancreas, and liver cancer [30]. Statins induced apoptosis of cancer cells through NFκB and the canonical caspase pathway and reduced proliferation through MEK1/2, ERK1/2, and JNK pathways [31]. Statins also induced cell cycle arrest of cancer cells by activating AMPK and increasing p21 and p27 expression [32]. Simvastatin suppresses the invasion of cancer cells by decreasing Pituitary Tumor-Transforming Gene 1 (PTTG1) [33]. Furthermore, statins could also regulate epigenetic machinery resulting in cell cycle arrest. DNMTs could be the targets of statins and the downstream p16 protein [34] and p21 [35]. In conclusion, statins showed anti-tumor progression in various cancers (Figure 2).

#### *5.3. Statins in Immune Cells*

Mostly, statins showed anti-inflammatory effects and enhanced the number of regulatory T cells (Treg) [36], which may result in the suppression of the Th1 immune response [37]. In addition, statin treatment reduced the Th17 population [38]. Treg obtained immunosuppressive effects on immunotherapy. However, a high dose of Atorvastatin could reduce the in vitro function of conventional T and regulatory T (Treg) cells [39]. Furthermore, statins were associated with better clinical outcomes in patients treated with PD-1 inhibitors [40]. Statins plus Th1 cytokines or dendritic cells (DC)-based immunotherapy could suppress breast tumor growth [41]. Statins could stimulate immunogenicity and promote an antimelanoma immune response [42]. These data showed the conflicting roles of statins in immunotherapy. Thus, the roles of statins in immune cells and immunotherapy are needed to be elucidated.

#### *5.4. Statins in MSCs*

Statins had several effects on mesenchymal stem cells (MSCs). Statins could enhance the osteogenic differentiation, angiogenic potential, migration, homing, survival, and proliferation of MSCs [43], which may have improved therapeutic outcomes in regenerative medicine. The evidence of statins in regulating cancer-associated MSCs (CaMSCs) is limited. Simvastatin could decrease CCL3 expression from cancer cells and ICAM-1, VCAM1, IL-6, and CCL2 expression from CaMSCs, disrupting the crosstalk of the cancer cells and tumor microenvironments (TME) and inhibiting tumor progression [44]. Therefore, the roles of statins in the TME—not only in immune cells but also MSCs, especially CaMSCs— need further investigation.

#### **6. Statins as Potential Anti-Cancer Agents in Gynecological Cancers**

#### *6.1. Meta-Analysis in EC*

Statin use was associated with lower risks of EC (RR = 0.81, 95% CI 0.70 to 0.94, *p* = 0.001) but not with mortalities (HR = 0.71, 95% CI 0.64 to 0.80, *p* = 0.144) [45]. In another study, it was shown that statin use could increase overall survival (OS) (HR = 0.80, 95% CI 0.66 to 0.95) [46]. However, not all studies suggested positive results. It was shown that statin use did not reduce the risk of EC (RR = 0.88, 95% CI 0.78 to 1.00, *p* = 0.05), even in the long-term statin user (>5 years) (RR = 0.79, 95% CI 0.58 to 1.08, *p* = 0.14) [47]. There was also no protective effect on EC in another study (RR = 0.94, 95% CI 0.82 to 1.07) [48] (Table 2).


**Table 2.** Clinical studies of statins in endometrial cancer.

CI: confidence interval. RR: relative risk. OR: odds ratio. OS: overall survival. HR: hazard ratio. DSS: diseasespecific survival. PFS: progression-free survival.

#### *6.2. Cohort Studies in EC*

The results of statins use in EC are controversial, including no protective effects on risks (HR = 0.67; 95% CI: 0.39–1.17) [49], OS for type I (HR = 0.92, 95% CI 0.70 to 1.2) and type II (HR = 0.92, 95% CI 0.65 to 1.29, *p* = 0.62) EC patients [50]. There was no significant association in post-diagnostic use of statins (new users) (adjusted HR 0.83, 95% CI 0.64 to 1.08) [51] and no difference between statin users and nonusers in 5-year recurrence-free survival (82% vs. 83%; *p* = 0.508), disease-specific survival (86% vs. 84%; *p* = 0.549), or overall survival (77% vs. 75%; *p* = 0.901) [52] (Table 2).

In contrast, statin use decreased the mortalities in several studies, including OS (HR = 0.41, 95% CI 0.20 to 0.82) [53], OS (HR = 0.80; 95% CI 0.74–0.88) [3], disease-specific survival (DSS) (HR = 0.63, 95% CI 0.40 to 0.99), DSS in concurrent statin and aspirin user (HR = 0.25, 95% CI 0.09 to 0.70) [54], OS in hyperlipidemic patients (HR = 0.42; 95% CI 0.20 to 0.87; *p* = 0.02), PFS (HR = 0.47; 95% CI 0.23 to 0.95; *p* = 0.04) [55], OS in continuing (pre- and postdiagnosis) users (HR = 0.70, 95% CI 0.53 to 0.92), new (postdiagnosis only) users (HR = 0.43, 95% CI 0.29 to 0.65) [56]. Furthermore, statin use decreased EC-specific mortality in type I cancers (HR = 0.87; 95% CI 0.76 to 1.00), for hydrophilic statins (HR = 0.84; 95% CI 0.68 to 1.03) and the new user (HR = 0.75; 95% CI 0.59 to 0.95) [57]. In addition, the risk of EC for statin use was decreased (HR = 0.74, 95% CI 0.59 to 0.94) [58] (Table 2).

In summary, the effects of statins in treating EC are still controversial. However, large results suggested that statins may be potent drugs to decrease the risks and mortalities of EC, and are worth performing clinical trials.

#### **7. Meta-Analysis in Ovarian Cancer**

Statin use was not significantly associated with the risks (RR = 0.92, 95% CI 0.85 to 1.00) but decreased the mortality (HR = 0.78, 95% CI 0.73 to 0.83) of ovarian cancer [45]. Another study showed that statin use did not reduce the risk of ovarian cancer (RR = 0.88, 95% CI 0.76 to 1.03, *p* = 0.12). Furthermore, no association was found between long-term statin use (>5 years) and the risk of ovarian cancer (RR = 0.73, 95% CI 0.51 to 1.04, *p* = 0.08) [47]. It was shown that the risks were not significantly associated with statin type (lipophilic RR = 0.88, 95% CI 0.69 to 1.12; hydrophilic RR = 1.06, 95% CI 0.72 to 1.57), histotypes of ovarian cancer (serous: RR: 0.95, 95% CI 0.69 to 1.30; clear cells: RR = 1.17, 95% CI 0.74 to 1.86), and long-term user (RR = 0.77, 95% CI 0.54 to 1.10) [59] (Table 3).


**Table 3.** Clinical studies of statins in ovarian cancer.


\* Genetically proxied HMG-CoA reductase inhibition population contained single nucleotide polymorphism (SNP). CI: confidence interval. RR: relative risk. OS: overall survival. HR: hazard ratio.

Similar to previous studies, statin use was not associated with the risk (RR = 0.88, 95% CI 0.75 to 1.03) but could significantly decrease mortality (RR = 0.76, 95% CI 0.67 to 0.86) of ovarian cancer [60]. Another study showed that statin use decreased the risks (RR = 0.79, 95% CI, 0.64 to 0.98) of ovarian cancer, especially in long-term users (>5 years) (RR = 0.48, 95% CI 0.28 to 0.80) [61]. Post-diagnostic statin use could decrease OS (HR = 0.74, 95% CI 0.63 to 0.87) and cancer-specific mortality (HR = 0.87, 95% CI 0.80 to 0.95) [62]. This could be seen in another study, showing improved OS in statin users (HR: 0.76, 95% CI: 0.68–0.85) [63]. Intriguingly, genetically proxied HMG-CoA reductase inhibition equivalent to 1-mmol/L (38.7-mg/dL) reduction in LDL cholesterol, significantly decreased the risk of ovarian cancer (OR = 0.60, 95% CI 0.43 to 0.83) as well as in BRCA1/2 mutation carriers, (HR = 0.69, 95% CI 0.51 to 0.93). [64] (Table 3).

#### *Cohort Studies and Case-Control Studies in Ovarian Cancer*

There was no association between the risk of ovarian cancer and statin user, HR = 0.69, 95% CI 0.32–1.49 [49], OR = 0.98, 95% CI 0.87 to 1.10 [65], and HR = 0.99, 95% CI 0.78 to 1.25) [66]. Moreover, the risk was even higher (HR = 1.30, 95% CI 1.04–1.62), which was largely attributed to the effect of the hydrophilic statin, especially pravastatin (HR = 1.89, 95% CI 1.24–2.88) [58]. Statin use was not associated with mortalities of ovarian cancer, HR = 0.57, 95% CI 0.21–1.51 [67], HR = 0.90, 95% CI 0.78 to 1.04 [68], and HR = 0.90, 95% CI 0.70 to 1.15, including lipophilic statin use (HR = 0.82, 95% CI 0.61 to 1.11) and hydrophilic statins (HR = 1.04, 95% CI 0.72 to 1.49) [69], and even in the patients with hyperlipidemia

(HR = 0.80, 95% CI 0.50 to 1.29) [70]. However, the mortalities were significantly decreased in non-serous-papillary subtypes (HR = 0.23, 95% CI 0.05 to 0.96) [70] (Table 3).

On the contrary, statin use decreased the mortalities of ovarian cancer, HR = 0.45, 95% CI 0.23 to 0.88 [71], HR = 0.47, 95% CI 0.26 to 0.85 [72], HR = 0.81, 95% CI 0.72 to 0.90 [73], HR = 0.74, 95% CI 0.61 to 0.91 [74], and HR = 0.66, 95% CI 0.55 to 0.81 [75], both in serous (HR = 0.69, 95% CI 0.54 to 0.87) and non-serous (HR = 0.63, 95% CI 0.44 to 0.90) histologies [75]. It was also shown that statin use decreased mortality in another study, HR = 0.76, 95% CI 0.64 to 0.89 for all patients and HR = 0.80, 95%CI 0.67 to 0.96 for patients with serous types [76] (Table 3).

Because ovarian cancer has different histotypes, statin use did not show significant differences in risks in serous and clear cell types [59], but the mortality decreased [75,76]. The results of statin use in ovarian cancer patients remained controversial. Thus, additional studies are needed to elucidate the effects of different statins on different histotypes of ovarian cancer.

#### **8. Cohort Studies in Other Gynecological Cancers**

The HR association between the risk of cervical cancer and statin use was 0.83, 95% CI of 0.67 to 0.99. Statin use was associated with decreased total gynecological cancer mortality, (HR = 0.70, 95% CI 0.50 to 0.98) [77]. The statin use group had a better prognosis compared with the non-user (progression-free survival: HR = 0.062, 95% CI 0.008 to 0.517; overall survival: HR = 0.098, 95% CI 0.041–0.459) in cervical cancer patients [78] (Table 4). The effects of statin use against cervical cancer and vulvar cancer are not conclusive due to too few studies and case numbers [61]. In conclusion, statin use may obtain protective effects on cervical cancer, but the evidence is too few.


**Table 4.** Clinical studies of statins in other gynecological cancer.

CI: confidence interval. HR: hazard ratio.

#### **9. The Mechanisms of the Anti-Tumor Effects of Statins on Gynecological Cancer**

Simvastatin exhibits anti-metastatic and anti-tumorigenic effects in ECC-1 and Ishikawa EC cells through mitogen-activated protein kinase (MAPK) but not the Akt/mTOR pathway [79]. The drug for diabetes, metformin, combined with simvastatin, synergistically inhibited cell growth and induced Bim expression and apoptosis in RL95-2, HEC1B, and Ishikawa EC cells. The combination treatment of metformin and simvastatin upregulated phosphorylated AMPK (pAMPK) and downregulated downstream phosphorylated S6 (pS6), suggesting the mTOR pathway may regulate these anti-proliferative effects [80]. Lipophilic (lovastatin and simvastatin) but not hydrophilic (pravastatin) statins induced apoptosis in ovarian cancer cell lines A2780 and UCI 101; endometrial cancer cell line, Ishikawa; and cervical cancer cell line, HeLa, which all expressed high levels of HMG-CoA reductase [81] (Table 5).


**Table 5.** The preclinical studies of statin in gynecological cancers.

Lovastatin and Pravastatin decreased metastasis through RhoA signaling in vitro and in vivo of SKOV3 ovarian cancer cells [82]. In addition, lovastatin and atorvastatin induced apoptosis in Hey 1B and Ovcar-3 ovarian cancer cells and suppressed anchorageindependent growth of these cells through the JNK/Rac1/Cdc42 pathway [83]. Lovastatin synergizes with doxorubicin to induce apoptosis by a novel mevalonate-independent mechanism [84]. In the mogp-TAg mice model, the promoter of oviduct glycoprotein-1 was used to drive the expression of SV40 T-antigen, and serous tubal intraepithelial carcinomas (STICs) were developed in gynecologic tissues. Lovastatin significantly reduced the development of STICs in mogp-TAg mice and inhibited ovarian tumor growth in the mouse xenograft model. Furthermore, lovastatin induced autophagy in ovarian cancer cells in vitro [85]. Simvastatin inhibited the proliferation of ovarian clear cell RMG-1 and TOV21- G in vitro and tumor growth in vivo [86]. All statins except pravastatin demonstrated single-agent activity against monolayers (IC50 = 1–35 µM) and spheroids (IC50 = 1–13 µM) of ovarian cancer cells. Furthermore, simvastatin could activate and block autophagy through the Rab7/p62/LC3-II pathway, and the lipophilic statins, simvastatin, and fluvastatin were more potent than hydrophilic statins [87]. In the ID8 syngeneic mice model, simvastatin induced apoptosis and inhibit tumor growth of ovarian cancer [88]. In a K18 gT121+/− p53fl/fl Brca1fl/fl (KpB) mouse model, a unique serous ovarian cancer mouse

model specifically and somatically deletes Brca1 and p53 and inactivates the retinoblastoma (Rb) proteins; simvastatin reduced the orthotropic xenograft tumor. In vitro studies showed that simvastatin obtained anti-metastatic and anti-tumorigenic effects through MAPK and AKT/mTOR pathways [89] (Table 5).

Atorvastatin, fluvastatin, and simvastatin induced apoptosis in cervical cancer cells, CaSki, HeLa, and ViBo (established from a biopsy derived from a cervical tumor) [90]. Moreover, simvastatin reduced the phosphorylation of Raf, ERK1/2, Akt, and mTOR and prenylated Ras, resulting in the induction of apoptosis and inhibition of cervical cancer tumor growth. A combination of simvastatin and paclitaxel abolished tumor growth in vivo [91]. In addition, apoptosis and autophagy were induced by atorvastatin through the AMPK/Akt/mTOR pathway. The xenograft tumor was reduced when treated with atorvastatin [92] (Table 5).

In summary, statins showed great potential to reduce cell proliferation and tumor growth of gynecological cancer in vitro and in in vivo. Akt/mTOR is the most important pathway in regulating cell proliferation, and a combination of statins with chemo drugs could synergize the anti-tumorigenic effects. Based on this foundation, statins may be a candidate repurposed drug for gynecological cancers.

#### **10. Conclusions and Perspective**

The mevalonate pathway and lipid metabolism are linked to the key regulators, influencing gene expression, chromatin remodeling, cellular differentiation, stress response, and tumor microenvironment that collectively enhance tumor development [93]. Statins obtain pleiotropic roles to decrease tumor progression through mevalonate-dependent and independent pathways. Statins reduced the prenylated small GTPase and other signaling pathways, such as Akt/mTOR, to induce apoptosis and autophagy and inhibit cell proliferation and metastasis, resulting in anti-tumor development.

This review of statin use in gynecological cancers showed positive and negative results. Some studies cannot avoid confounders, including multiple comorbidities, lifestyle factors, health-related behaviors, stage and grade of disease, and other medications. The study or clinical trials of different statins (e.g., lipophilic or hydrophilic) on different histotypes of cancer (e.g., serous type or non-serous type; type I or type II) and in combination with chemo drugs are required to validate since there are only 3 trials on EC, 6 trials on ovarian cancer, compared to breast cancer which has 52 trials.

If statins are to be applied clinically to gynecological cancers, they may be used as a single agent. We advocate that using statins in combination with other drugs is more potent. In addition, the identification of the response prediction markers is just undergoing. In ovarian cancer cells, *VDAC1* and *LDLRAP1* were positively and negatively correlated with the response to statins, respectively [94].

The value of statins as therapeutic drugs against gynecological cancer is inestimable because the repurposing of inexpensive, commonly used, and FDA-approved medications to exploit their anti-cancer effects yields the development of cost-effective approaches to cancer therapy. Most important, it can directly benefit the patients, life-saving or prolonging.

**Author Contributions:** Conceptualization, K.-H.W., C.-H.L. and D.-C.D.; methodology, K.-H.W.; formal analysis, K.-H.W.; investigation, K.-H.W.; resources, K.-H.W.; data curation, K.-H.W.; writing—original draft preparation, K.-H.W. and D.-C.D.; writing—review and editing, D.-C.D. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Hualien Tzu Chi Hospital (TCRD 108-57, 108-49, 109-62, TCRD 111-071, TCRD 111-080) and the Buddhist Tzu Chi Medical Foundation (TCMF-EP 111-01, TCMF-CP 111-05).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


## *Review* **Emerging Roles of the** α**-Catenin Family Member** α**-Catulin in Development, Homeostasis and Cancer Progression**

**Mateusz Gielata, Kamila Karpi ´nska, Tomasz Pieczonka and Agnieszka Kobielak \***

Laboratory of the Molecular Biology of Cancer, Centre of New Technologies, University of Warsaw, 02-097 Warsaw, Poland

**\*** Correspondence: a.kobielak@cent.uw.edu.pl; Tel.: +48-22-55-43-735

**Abstract:** α-catulin, together with vinculin and the α-catenins, belongs to the vinculin family of proteins, best known for their actin-filament binding properties and crucial roles in cell-cell and cellsubstrate adhesion. In the past few years, an array of binding partners for α-catulin have surfaced, which has shed new light on the possible functions of this protein. Despite all this information, the molecular basis of how α-catulin acts in cells and controls a wide variety of signals during morphogenesis, tissue homeostasis, and cancer progression remains elusive. This review aims to highlight recent discoveries on how α-catulin is involved in a broad range of diverse biological processes with an emphasis on cancer progression.

**Keywords:** α-catulin; CTNNAL1; catenin; invasion; epithelial-mesenchymal transition; EMT; vascular mimicry

#### **1. Introduction**

Homeostasis in healthy tissues strongly depends on cadherin- and integrin-mediated, cell-to-cell and cell-to-extracellular matrix (ECM) adhesion, respectively [1]. Both types of adhesion are crucial for maintaining tissue architecture and sensing and responding to changes in their environments. Cadherins are transmembrane glycoproteins that mediate calcium-dependent cell-cell adhesion. Through their homophilic binding interactions, cadherins play a role in cell-sorting mechanisms, conferring adhesion specificities on cells. The regulated expression of cadherins also controls cell polarity and tissue morphology. Classical cadherins are located at adherens junctions and are characterized by five homologous repeats at the extracellular domain. In contrast, the intracellular classical cadherin cytoplasmic domain (CCD) binds armadillo family proteins β-catenin (Ctnnb1) and p120ctn (Ctnnd1). The interaction with β-catenin links cadherins to α-catenin and the actin cytoskeleton, whereas p120ctn is involved in cadherin turnover. By regulating contact formation and stability, cadherins play a crucial role in tissue morphogenesis and homeostasis [1].

The adhesion of cells to the extracellular matrix (ECM) is mainly mediated by integrins, which undergo a conformational change upon activation to recruit structural and signaling molecules. Thus, integrins not only mechanically couple the cytoskeleton to the ECM but also transmit molecular signaling cascades to regulate cellular functions in response to extracellular cues [1].

During tissue morphogenesis, wound healing or pathological alterations in diseases like cancer, the ability of cells to rapidly and reversibly change adhesive properties is a key feature. This cell plasticity is driven by the programs of the epithelial–mesenchymal transition (EMT) and mesenchymal–epithelial transition (MET), both of which play essential roles during normal embryogenesis and tissue homeostasis [2]. However, the aberrant activation of these processes can also drive different stages of cancer progression, including invasion, cell dissemination, metastatic colonization, and secondary tumor outgrowth [3]. EMT

**Citation:** Gielata, M.; Karpi ´nska, K.; Pieczonka, T.; Kobielak, A. Emerging Roles of the α-Catenin Family Member α-Catulin in Development, Homeostasis and Cancer Progression. *Int. J. Mol. Sci.* **2022**, *23*, 11962. https://doi.org/ 10.3390/ijms231911962

Academic Editor: Laura Paleari

Received: 14 September 2022 Accepted: 6 October 2022 Published: 8 October 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

enables physically connected epithelial cells to disassociate their characteristic classical cadherin/catenin cell-cell contacts, lose their apical-basolateral polarity, and increase expression and activity of integrins displaying leading-edge asymmetry to become motile and mesenchymal-like and capable of degrading the basement membrane. The events occurring during EMT include the downregulation of cytokeratins and E-cadherin, epithelial-specific markers, and an increase in mesenchymal markers, such as fibronectin, N-cadherin, and vimentin. Transcription factors, including Snail1/Snail, Snail2/Slug, Twist, and ZEB1, are well known to be involved in the orchestration of EMT. Cell–cell adhesion and cell–ECM sites contain overlapping functional constituents containing common and distinct proteins. The crosstalk between these adhesion sites is crucial to coordinate cell migration with dynamic interactions between cells. Because both integrins and cadherins associate with the cytoskeleton and many common signaling molecules, it is likely that the cell–ECM and cell–cell adhesion processes mediated by these two types of receptors act in a coordinated manner in regulating cellular functions [4]. Changes in expression or mutations of these proteins, especially cadherins, catenins, and integrins, are frequently associated with diseases ranging from developmental defects to carcinogenesis and metastasis [5–7]. It is well established that two significant hallmarks of cancer, namely loss of cell-to-cell adhesion and anchorage-independent growth, are both dependent on cell adhesion molecules. Vinculin and α-catenin are two related proteins that play crucial roles in those processes [4,8]. However, the function of their recently characterized homolog α-catulin is still poorly understood. α-catulin is a protein whose name is composed of "α-cat", which comes from α-catenin, and "ulin", which comes from vinculin as it is a homolog of α-catenin protein belonging to the vinculin superfamily. Despite the sequence homology and shared superfamily with α-catenin, α-catulin's localization and functions appear to differ. Multiple reports describe α-catulin as an important factor contributing to cancer cell migration and invasion; however, the exact molecular mechanism leading to this phenomenon remains unclear. A growing number of reported α-catulin-interacting partners and new connections imply even more complex regulatory functions for this protein. This review aims to highlight recent discoveries emphasizing how α-catulin is involved in the coordination of a network of signals and actin cytoskeleton regulation.

#### **2.** α**-Catulin—A Member of the** α**-Catenin Family**

Whereas all other catenins (β-catenin, plakoglobin and p120 catenin) share relatively high sequence homology and belong to the Armadillo family of proteins, vinculin and α-catenins differ in sequence and structural organization and form the vinculin family [9] together with the recently characterized homolog α-catulin [10]. Although it is well known that α-catenin is necessary for cadherin-catenin-mediated cell-cell adhesion, and vinculin is important for integrin-mediated cell-ECM adhesion and cell-cell adhesion, the function of α-catulin is still not well understood. α-catulin (catenin alpha like 1) protein is encoded by the *CTNNAL1* gene located on chromosome 9 in loci q31–32 (Figure 1B) positions 108,942,569–109,013,522 in a minus-strand orientation, resulting in a base length of 70,954 (https://www.genecards.org/cgi-bin/carddisp.pl?gene=CTNNAL1 (accessed on 5 September 2022)). The protein is 734 amino acids long and weighs 81,896 Da (https://www.uniprot.org/uniprotkb/Q9UBT7/entry (accessed on 5 September 2022)). However, two other alternative splicing isoforms have been described, one with substitution in positions 714–734 [10] and another with missing aa in positions 397–480 [11]. There is no 3D structure for α-catulin that has been deposited in the PDB file. The only available structure is the one predicted by AlphaFold (https://alphafold.ebi.ac.uk/ (accessed on 5 September 2022)) which still has a poor structural prognosis in some locations (Figure 1C). mRNA of α-catulin is widely expressed in the human body. It has been reported to be expressed in the thymus, prostate, testes, ovary, small intestine, colon [12], skeletal muscle, lung, heart, and placenta [10]. The human protein atlas also confirms that α-catulin protein is widely found in the human body, interestingly having the highest score in endocrine tissues, female and muscle tissues (proteinatlas.org). In 2002, Park

et al. demonstrated that when using the Blast tool and analyzing the *CTNNAL1* sequence, they reported having high similarity to α-catenin. The BESTFIT similarity alignment of α-catulin with its closest human homolog α-catenin showed 27% identity, and alignment with vinculin showed almost 20% identity (Figure 1A). They also showed that α-catulin is characterized by an extra 16 N-terminal amino acids not present in mammalian α-catenins. α-catulin and α-catenin homology is represented by two blocks; the first homology sequence is between α-catulin residues 18–524 and αN-catenin positions 2–504. The following sequence is a region of 110 amino acids present in α-catenin that is omitted in α-catulin. The second homologous block extends α-catulin residues 525–734 [12]. α-catulin also shows high sequence similarity with vinculin, hence being categorized as a part of the vinculin superfamily of proteins. The homology with vinculin, however, is lower, reaching 21%. The similarity is essentially high in the N-terminal domain of the protein, shown to have putative binding sites for β-catenin, talin, and α-actinin [10]. Amphipathic helices in the C-terminal region corresponding to α-catenin contain potential binding sites for the actin cytoskeleton. This region also contains potential binding sites for ZO-1, the protein important for tight junctions [10,12], another type of intercellular adhesion complex that forms the border between the apical and basolateral cell surface domains in polarized epithelia and controls paracellular permeability. Despite the sequence homology between α-catulin and α-catenin, their subcellular localization pattern is different as shown by Park et al. α-catulin localized to both the membrane-rich (pellet) fraction and the soluble (cytosolic) fraction, whereas α-catenin was found to localize almost exclusively to the membrane-rich fraction. They confirmed those results with two different experiments, one with high-speed fractionation into cytosolic and membrane-rich fractions followed by Western blotting, and the second with Myc-tagged α-catulin (pcDNA Myc:α-catulin) and indirect immunofluorescence. Despite the above-mentioned characteristics of α-catulin, it is still very poorly characterized. *Int. J. Mol. Sci.* **2022**, *23*, 11962 4 of 14

**Figure 1.** Structural features of α-catulin. (**A**) Table represents amino acid sequence similarities (%) between α-catulin, α-catenin and vinculin. α-catulin shares 27.09% homology with α-catenin and 19.15% with vinculin. (**B**) Schematic representation of α-catulin (CTNNAL1) gene on chromosome 9 locus 31.3. (**C**) Scheme shows the predicted 3D structure of α-catulin and α-catenin protein by

**Figure 1.** Structural features of α-catulin. (**A**) Table represents amino acid sequence similarities (%) between α-catulin, α-catenin and vinculin. α-catulin shares 27.09% homology with α-catenin and 19.15% with vinculin. (**B**) Schematic representation of α-catulin (CTNNAL1) gene on chromosome 9 locus 31.3. (**C**) Scheme shows the predicted 3D structure of α-catulin and α-catenin protein by AlphaFold. **Figure 1.** Structural features of α-catulin. (**A**) Table represents amino acid sequence similarities (%) between α-catulin, α-catenin and vinculin. α-catulin shares 27.09% homology with α-catenin and 19.15% with vinculin. (**B**) Schematic representation of α-catulin (CTNNAL1) gene on chromosome 9 locus 31.3. (**C**) Scheme shows the predicted 3D structure of α-catulin and α-catenin protein by AlphaFold.

#### **3. Binding Partners of** α**-Catulin**

One of the first described interacting partners of α-catulin is Lbc Rho guanine nucleotide exchange factor. Rho guanine nucleotide exchange factor (GEF) functions for the RhoA small GTPase protein [13]. RhoA is inactive when bound to the GDP, but when acted on by the Rho GEFs, GDP can be released, and GTP might be attached, leading to the activation of RhoA. Furthermore, active RhoA can bind to and activate distant effectors or enzymes. Interestingly, in this particular case, RhoA is a major regulator of the cell actin cytoskeleton [14]. One of the GEFs specific for Rho is a DH domain containing Lbc oncogenic product GEF [15,16]. All Lbc Rho GEF forms possess common C-terminal regions following DH domain cassette [17]. Park et al. showed a direct association between Lbc Rho GEF and α-catulin using three independent systems: yeast two-hybrid interaction, direct binding in vitro, and complex formation in mammalian cells. The required site of interaction within the Lbc C-terminal region was mapped to the ∼253-residue IDR (intrinsically disordered region). They also determined that the α-catulin site required for the interaction lies in the N-terminal residues 34–524. Coexpression of α-catulin and wt-Lbc led to increased GTP-Rho formation in cooperative action. This implies that α-catulin is an upstream regulator of Rho. Overall, the authors conclude that α-catulin acts as a scaffold protein for Lbc Rho GEF and facilitates Lbc-induced Rho signals [12,17].

α-Catulin has also been shown to interact with the dystrophin complex through direct interaction with dystrobrevin in *C. elegans.* This interaction is conserved and also present in mouse skeletal muscles [18]. Dystrophin has been known as a cause of Duchenne muscular dystrophy, yet dystrophin usually functions in protein complexes known as dystrophin-associated protein complex (DAPC) [19]. It had been previously shown that mutations in the CTNNAL1 gene lead to the interruption of DAPC localization near dense bodies [20]. In the above-mentioned publication, the reciprocal action of α-catulin with dystrobrevin was validated by co-immunoprecipitation as well as by mass spectrometry and yeast two-hybrid screen. The authors observed an increase in α-catulin expression levels in the skeletal muscle of dystrophin-deficient mice, where dystrophin-associated

protein complex is disassembled, and the link between the costamere and the sarcolemma is absent. To bind α-catulin, dystrobrevin requires a C-terminus as well as an α-helix H2 proximal to the C-terminal region [18]. Similar results have been obtained in other studies. Lyssand et al. showed that the C-terminal domain of dystrobrevin recruits α-catulin to the α1D-AR signalosome. Adrenergic receptors (ARs) and G protein-coupled receptors (GPCR) are important regulators of cardiovascular system function. Their function revolves around increasing blood pressure and promoting vascular remodeling. [21]. Sequence analysis revealed that, similar to α-catenin, α-catulin has a putative binding domain for β-catenin; therefore, a group led by Deniz Toksoz took a closer look into this interaction, mapping it to the N-terminal 163 amino acids of the protein [21,22]. When performing co-immunoprecipitation, they noticed that α-catulin indeed co-precipitates with β-catenin, but the amount of α-catulin associated with β-catenin appeared to be smaller than that of α-catenin associated with β-catenin. Given that endogenously in cells, the pool of β-catenin is naturally bound to α-catenin, these results were not surprising. α-catulin might associate with a different fraction of β-catenin than α-catenin does. There might be other pools of β-catenin, such as tyrosine phosphorylated β-catenin, in which protein interactions are altered [21,23–25]. Here, the authors additionally proposed the antiproliferative role of α-catulin, as it attenuates cyclin D1 transcription, leading to decreased cyclin D1 protein levels. They also observed that expression of α-catulin had a negative impact on cancer cell colony formation ability, leading to the statement that α-catulin modulates endogenous growth signaling pathways [21,22]. As β-catenin functions at the adherens junctions and also acts in the nucleus after stabilization of a pool of β-catenin in response to the upstream Wnt signals, it is crucial to further investigate the catulin-β-catenin interaction. Another α-catulin interacting protein was reported in the publication by Wiesner et al. in 2008. It was shown that α-catulin can modulate the NF-κB pathway by binding to IKK-β [21,26]. The NF-κB pathway plays a pivotal role in a variety of biological processes like innate and adaptive immune responses, tissue differentiation and apoptosis [21,27,28]. The targets of NF-κB include its own inhibitors IκBα and IκBβ [21,29]. Different extracellular stimuli activate the IκB kinases IKK-α and -β, which phosphorylate IκBα, which results in the degradation of IκBα and translocation of NF-κB to the nucleus [21,30]. Wiesner et al. provided evidence that α-catulin binds to IKK-β by immunoprecipitation. Moreover, they limited the interaction site in α-catulin to its C-terminal 87 amino acids. As α-catulin binds to IKK-β in the C terminus and to Lbc Rho GEF in the N-terminus, the authors claim that it may allow simultaneous stimulation of both pathways, being a bridge between those two. As there is evidence that both the NF-κB and RhoA signaling pathways play multiple roles in tumorigenesis, cell migration, invasion, and escape from apoptosis, α-catulin, as a linker of those two pathways, might serve as a crucial clinical target [21,26,31]. The interaction of α-catulin with Lbc, dystrophin complex and other proteins and resulting pathways activation have been represented in Figure 2.

Finally, α-catulin has been described as an interactor protein of human NEK1 protein kinase. NEK kinases are involved in regulating diverse cellular processes like the cell cycle, mitosis, cilia formation, and the DNA damage response and the etiology of polycystic kidney disease (PKD). α-catulin has been described as one of the 11 new binding proteins of NEK1. Moreover, it has been proven to interact with both regulatory and kinase domains (NRD and NKD) [32]. Interestingly, aberrant expression of NEKs appears to be involved in the initiation, maintenance, progression and metastasis of cancer and is associated with a poor prognosis [33]. A better understanding of NEK1 kinase interaction with α-catulin may lead to more successful clinical trials of NEK inhibitors.

sented in Figure 2.

**Figure 2.** Overview of the function of α-catulin in dystrophin complex. In blue circles, α-catulin and dystrophin complex are shown. The interaction occurs via dystrobrevin, highlighted in orange. Shown are distinct interactors of the complex as well as direct interactors of α-catulin. Enlarged is also integrin complex, having interactions indirectly via ECM and impacting cytoskeleton remodeling. Highlighted in red are key pathways and functions resulting from either interaction of the complex or α-catulin directly. **Figure 2.** Overview of the function of α-catulin in dystrophin complex. In blue circles, α-catulin and dystrophin complex are shown. The interaction occurs via dystrobrevin, highlighted in orange. Shown are distinct interactors of the complex as well as direct interactors of α-catulin. Enlarged is also integrin complex, having interactions indirectly via ECM and impacting cytoskeleton remodeling. Highlighted in red are key pathways and functions resulting from either interaction of the complex or α-catulin directly.

catulin-β-catenin interaction. Another α-catulin interacting protein was reported in the publication by Wiesner et al. in 2008. It was shown that α-catulin can modulate the NFκB pathway by binding to IKK-β [21,26]. The NF-κB pathway plays a pivotal role in a variety of biological processes like innate and adaptive immune responses, tissue differentiation and apoptosis [21,27,28]. The targets of NF-κB include its own inhibitors IκBα and IκBβ [21,29]. Different extracellular stimuli activate the IκB kinases IKK-α and -β, which phosphorylate IκBα, which results in the degradation of IκBα and translocation of NF-κB to the nucleus [21,30]. Wiesner et al. provided evidence that α-catulin binds to IKKβ by immunoprecipitation. Moreover, they limited the interaction site in α-catulin to its C-terminal 87 amino acids. As α-catulin binds to IKK-β in the C terminus and to Lbc Rho GEF in the N-terminus, the authors claim that it may allow simultaneous stimulation of both pathways, being a bridge between those two. As there is evidence that both the NFκB and RhoA signaling pathways play multiple roles in tumorigenesis, cell migration, invasion, and escape from apoptosis, α-catulin, as a linker of those two pathways, might serve as a crucial clinical target [21,26,31]. The interaction of α-catulin with Lbc, dystrophin complex and other proteins and resulting pathways activation have been repre-

#### Finally, α-catulin has been described as an interactor protein of human NEK1 protein **4.** α**-Catulin and Its Function during Development**

kinase. NEK kinases are involved in regulating diverse cellular processes like the cell cycle, mitosis, cilia formation, and the DNA damage response and the etiology of polycystic kidney disease (PKD). α-catulin has been described as one of the 11 new binding proteins of NEK1. Moreover, it has been proven to interact with both regulatory and kinase do-The plethora of interacting proteins indicates that α-catulin may play essential roles in various vital regulatory processes. Thus far, the important role of α-catulin has been shown in the process of neurulation during mouse development [34], where cell-cell and cell-ECM interactions are constantly under remodeling to enable proper architecture and function of forming tissues. The actin-cytoskeleton and actomyosin contractility integrated at the cellcell and cell-ECM adhesions cooperatively are crucial to shape the cells and tissues [35–37]. The adherens junctions are required for the transmission of force across an epithelium, and the actomyosin cortex, which spans the apical surface of an epithelium, transitions between elongation and active state of actin nucleation while still attached to the adherens junction, allowing for apical constriction, which is crucial, for example, during neurulation [37–39]. It is important that actomyosin machinery is located at the right place and time to generate the required force to pull the neural folds together [40]. Interestingly, α-catulin was shown to participate in the apical actomyosin network regulation by serving as a scaffold protein that may be important for properly directing Rho family GTPase signaling during neurulation. α-catulin-deficient mice show neural tube (NT) closure defects. They are embryonically lethal with massive disorganization of their neuroepithelium, extra bending, absence of apically localized actin filaments, nestin and phosphorylated myosin, and inappropriate basement membrane assembly due to very low expression of its components: laminin and fibronectin. The neuroepithelium of α-catulin deficient mice lack apically localized actin filaments and P-Mlc, which typically correlate with proper Rho-dependent cell constriction. In vitro studies performed in a three-dimensional model of MDCK cells showed that αcatulin is localized specifically at the apical parts of cells membranes and is important for proper cell polarization, organization of actomyosin cytoskeleton, stabilization of

intercellular junction as well as distribution of active Rho A. Taken together, data collected both from in vivo mouse model and in vitro 3D studies indicated a pivotal role of alphacatulin protein in neurulation during embryonic development, as it can act as a scaffold for RhoA in apical parts of cells, which results in correct spatial activation of downstream myosin to influence actin-myosin dynamics and the stability of cell-cell junctions, which allows generating the appropriate tension needed for the apical constriction of cells and proper bending of the neural plate [34].

#### **5. Role of** α**-Catulin in Homeostasis**

In the last decade, numerous studies have also demonstrated the importance of α-catulin in the maintenance of tissue homeostasis. A-catulin was reported to play potential functions in hematopoietic stem cells (HSCs), bronchial epithelium, muscles and intestine [18,20,41–45]. In hematopoietic stem cells, α-catulin is expressed only in a specific population of 0.02% of bone marrow hematopoietic cells. Generation of a mouse model with green fluorescent protein (GFP) knocked-in into the α-catulin locus allowed to show that α-catulin together with c-kit marks the population of cells that possess the long-term multilineage reconstitution ability of bone marrow after irradiation [41]. In addition, the distribution of α-catulin<sup>+</sup> c-kit1<sup>+</sup> cells indicates that HSCs are more common in the central marrow than near the bone surface [41,42]. Even though α-catulin proved to be a great marker for HSC visualization in the bone, the exact function of this protein in those cells was not established.

Furthermore, high expression of α-catulin was also detected in bronchial epithelium under ozone-stressed conditions. Results from this study suggest that elevated α-catulin expression may be a protective response aimed at maintaining airway epithelial integrity [43].

Moreover, in neuromuscular junctions, dystrobrevin utilizes α-catulin for proper neurotransmitter receptor (AChR) clustering on myotubes, indicating its important role in a synaptic machinery organization [44]. As an anchor protein that locates potassium channels and neurotransmitter receptors in specific nanodomains, α-catulin plays a key role in the physiological processes related to the neurosecretion as well as excitation of neurons and muscles. Dysfunction of this important protein may be linked to muscular and neurological disorders [20,44]. It has also been reported that α-catulin ortholog is a critical cytoskeletal regulator in C.elegans, crucial for the proper localization of calcium-dependent potassium channels in both neurons and muscles. In muscles, α-catulin, via the dystrophin complex, binds the calcium-dependent potassium channels near L-type calcium channels. In turn, in neurons, α-catulin controls the localization of the potassium channels independently of the dystrophin complex [20,21,46]. The interaction with dystrophin complex seems to be the best characterized so far for α-catulin.

Recent studies performed on Chinese patients with Hirschsprung disease revealed that α-catulin can be attributed to genetic factors or gene-gene interaction networks responsible for enteric neuronal dysfunction [45]. Interestingly, catulin expression was observed in the enteric innervation of newborn mice [34].

#### **6.** α**-Catulin in Cancer Invasion and Metastasis**

Even though α-catulin is overall a very poorly described protein, its participation in cancerogenesis and influence on cancer cell invasion and metastasis has been reported and researched in many papers. Both structural and signaling functions of α-catulin may play a role in cancer progression. As mentioned above, α-catulin in the N-terminal region contains binding sites for β-catenin, talin, α-actinin, and the actin cytoskeleton. This suggests that it may function as a cytoskeletal linker protein that is able to modulate cell migration [8]. Cell migration is a process that plays a pivotal role in carcinogenesis and participates in the metastasizing of cancer cells. Metastasis is a complex phenomenon that occurs in all types of cancers and is responsible for death [47]. It is based on the fact that cancer cells escape from the primary tumor, migrate, enter the lumen of blood and lymphatic vessels and reach distant organs, where they can repopulate the tumor mass [48,49]. Cancer cells need to ac-

quire a mesenchymal phenotype in the process called epithelial-to-mesenchymal transition (EMT) [50]. EMT is a phenomenon where cells downregulate proteins involved in apical cell-cell contact and adherence junction formation, such as E-cadherin and α-catenin, and start upregulating proteins specific for mesenchymal features of the cell, such as N-cadherin and vimentin, which results in the enhanced motility of the cells. This switch between relatively stable cell-cell contacts and an increase in motility is crucial for cancer invasion [51]. It has been observed that when α-catenin, a cell-cell junction protein, is conditionally lost in the epithelium, cells begin to demonstrate increased proliferation rates, migrative properties, and the squamous cell carcinoma (SCC) phenotype [52]. Using microarray analysis to compare mouse α-catenin cKO keratinocytes, which failed to form cell–cell junctions, and WT epithelial cells, it was observed that α-catulin is highly upregulated in the cells with increased motility and mesenchymal phenotypes [52]. This data suggested the participation of α-catulin in cancer progression and was further investigated by our group in a model of human head and neck squamous cell carcinoma (hHNSCC), which is a very aggressive tumor type and accounts for more than 450,000 malignancies diagnosed each year. Despite new treatment options, patients are still faced with a very high rate of recurrence and metastatic disease, with a 5-year survival rate of only 50% [53–55]. It was shown that α-catulin is upregulated in the metastatic cells in the xenotransplant in vivo model and also in vitro in the hSCC (human squamous cell carcinoma) cell line after EMT induction. Moreover, α-catulin is highly expressed at the invasion front and in migrating, metastatic streams of cells in human samples of HNSCC and in higher grades of tumor samples when compared with normal mucosa epithelium [56]. Most importantly, ablation of α-catulin in hSCC cells decreased the ability of these cells to migrate and invade in vitro and decreased their metastatic potential in vivo [56]. Given that the expression of α-catulin not only correlates with tumor grade, but also appears to be involved in the regulation of the invasive character of the HNSCC cells, it suggests that α-catulin may represent a novel yet critical mediator of oral cancer progression. As this type of cancer usually spreads locally, utilizing collective migration, α-catulin could be important for spatiotemporal fine-tuning of Rho GTPases within a group of cancer cells to control divergent cell-cell and cell-ECM adhesion as well as cytoskeletal functions to achieve cellular coordination and mechanocoupling. This is one of the options that will require further testing to better understand the role of catulin in the process of HNSCC invasion. As α-catulin expression and function correlated with the early onset of hSCC cell invasion, our group used the human α-catulin promoter fragment driving GFP expression to develop a reporter system. This unique system, for the first time, allowed us to isolate in vivo a small population of invasive cells at the human tumor invasion front [57]. After verifying the reporter system, we showed that cells highly expressing GFP driven from α-catulin expression localize at the invasion front in a spheroid model of hSCC cells. Additionally, this system marked the cells with higher migratory, invasive, and tumorigenic potential in vitro in the 3D model. Cells highly expressing α-catulin were also observed in a small population of invasive cells at the tumor front in the in vivo model of head and neck squamous cell carcinoma. Expression of GFP under α-catulin promoter correlated with the loss of an epithelial marker, E-cadherin expression, indicative of ongoing EMT. The reporter system allowed for isolation and transcriptional characterization of those highly invasive cells, providing a list of deregulated genes that are involved in cellular movement, ILK and integrin signalling, as well as axonal guidance signalling [57]. This functional genomic study of the purified population of invasive cells revealed enrichment in genes involved in cellular movement and invasion, providing a molecular profile of HNSCC invasive cells. Interestingly, this profile overlapped partially with the expression of signature genes related to partial EMT available from single-cell analysis of human HNSCC specimens [58]. This comparison strengthens the idea that α-catulin in this type of cancer might be important for spatiotemporal regulation of Rho GTPases within a group of cancer cells to control dynamic plasticity and crosstalk between cadherin-mediated cell-cell contact and integrin-dependent cell-ECM adhesion, which is crucial during collective invasion and

migration. Further research on catulin revealed that its role in cancer progression is not only limited to HNSCC specifically, which utilizes collective invasion for local spread. It was recently published that α-catulin is also expressed in human breast cancer samples and triple-negative breast cancer cell lines, and its expression correlates with tumor progression [59]. Breast cancer is now the most common cancer worldwide [60], and the worst outcome is presented by triple-negative breast cancer [61]. Knockdown of α-catulin in triple-negative human breast cancer cell lines MDA-MB-231 and HCC1806 revealed a decrease in the invasion capability of those cells in 3D spheroid model assays [59]. The use of a catulin-GFP-promoter-based reporter system in a 3D spheroid model of triple-negative breast cancer cell lines showed that the most invading cells co-express α-catulin and known EMT marker vimentin. Transcriptional profiling of GFP-positive cells isolated from tumors that formed after injection of a catulin-GFP triple-negative breast cancer cell line disclosed the list of deregulated genes involved in cellular movement and invasion and, interestingly, migration of endothelial cells [59]. Top pathways deregulated in the α-catulin GFP + cells involved epithelial adherens junction signaling and remodeling of epithelial adherens junctions. Special attention was paid to genes involved in the vasculature, as it was observed that tumor areas enriched in GFP+ cells presented visible dense vasculature. Surprisingly, some cells highly expressing GFP co-expressed MCAM (CD146), an endothelial marker but also a cellular surface receptor of different ligands, are actively involved in signaling in the numerous physiological and pathological processes involving metastases of different cancer types. Cells highly expressing GFP and co-expressing MCAM formed vasculogenic structures resembling vessels. This suggests that α-catulin marks highly invasive breast cancer cells that are characterized by increased plasticity and might participate in the process of vascular mimicry, allowing cancer cells to metastasize [59]. In addition, ablation of α-catulin in the in vivo model resulted in decreased tumor size and decreased stemness potential of cancer cells with lowered expression of CD44, which is known to be enriched in breast cancer (BC) stem cells [59]. These data implicate that α-catulin might play an important role in cancer type-specific tumor-microenvironment interplay. Moreover, it may be involved in the inflection of adhesive properties of tumor cells. The possible mechanism of increased α-catulin expression in invasive cancer cells might be explained by the research performed by Cassandri et al. [62]. They showed that zinc-finger protein 750 (ZNF750) is a negative regulator of the migration and invasion of breast cancer cells. It functions as a repressor of a prometastatic transcriptional program. This transcriptional program was shown to express genes that are involved in focal adhesion and extracellular matrix interactions with an emphasis on CTNNAL1. They showed that the expression of CTNNAL1 and LAMB3 contradictorily correlated with ZNF750 expression in a breast cancer model. ZNF750 recruits epigenetic modifiers KDM1A and HDAC1 to the promoter region of the α-catulin gene, which affects histone marks and trans activates these genomic sites. Additionally, they also showed gene expression analysis in cancer patient datasets that indicated ZNF750 and its targets to be negative prognostic factors in breast cancer [62]. In 2011, Fan et al. published a paper confirming the previously described participation of α-catulin in tumorigenesis. They showed that α-catulin expression is elevated in oral cancer cells versus normal cells. They also found that the knockdown of α-catulin resulted in the accumulation of cell populations in S and G2/M cell-cycle phases with decreased cyclin A and cyclin B1 expression. α-catulin knockdown induced cellular senescence as the major phenotype of cell death in two oral cancer cell lines, OC2 and A549. In patients, α-catulin expression correlated with tumor size, whereas α-catulin knockdown supressed tumorigenicity in xenograft models. Knockdown of α-catulin in cancer cells bearing either wild-type or mutant p53 was sufficient to trigger DNA damage response and eventually induce cellular senescence in vitro [63]. In addition to structural functions and regulation of actin cytoskeleton during cancer invasion and migration, α-catulin enhances cancer metastasis by influencing signaling pathways. Liang et al. showed that α-catulin expression correlates with the cell invasiveness potential in vitro and metastatic potential in vivo. It occurs via an ILK/NF-κB/integrin network where α-catulin directly interacts with ILK, which in turn

activates the ILK/Akt/NF-κB signaling pathway and upregulates fibronectin and integrin αvβ3. α-catulin as an integrin signaling adaptor might play a pivotal role in regulating integrin-mediated cellular functions via binding to ILK [64]. Later, the same scientific group focused on the participation of α-catulin in cancer stemness and EMT. They found that cells overexpressing α-catulin have genes such as *FGF2*, *BMI1*, *ALDH1A3*, *POU5F1* and *NANOG* upregulated. Additionally, high expression of α-catulin was required to maintain stemness in a lung cancer model, and klf5 was indicated as a new interacting protein that plays an important role in stemness maintenance by cooperating with α-catulin to enhance the transcription of *POU5F1* and *NANOG*. Knockdown of klf5 in cells overexpressing α-catulin abolished the sphere formation capacity. α-catulin not only interacts with klf5 but also protects this protein by blocking the WWP1-mediated proteasomal degradation of KLF5 [65]. The participation of α-catulin in cancer cell migration and invasion has also been proven in a melanoma cancer model. Kreiseder et al. showed that α-catulin is highly expressed in melanoma cells, resulting in reduced E-cadherin and increased N-cadherin expression. Upregulation of α-catulin promotes expression of EMT markers Snail/Slug and Zeb1/2; in addition, α-catulin regulated PTEN and RKIP, inhibitors of the NF-κB pathway. They also found MCAM, plakoglobin, and occludin to be altered in α-catulin-deficient cells. Their results further confirmed that α-catulin is not only responsible for the downregulation of E-cadherin but is also required for melanoma invasion by the upregulation of MMP 2 and 9 and the activation of ROCK/Rho [66]. They further studied the role of α-catulin and, in 2015, published a paper showing that α-catulin is responsible for the chemoresistance of melanoma cells to cisplatin. This reduction in cisplatin-mediated apoptosis of melanoma cancer cells is due to the fact that α-catulin is responsible for NF-κB, AP-1 activation and ERK phosphorylation, and, in the case of knockdown of α-catulin, the cisplatin-mediated apoptosis was shown to be enhanced [67].

#### **7. Conclusions**

α-catulin, together with vinculin and α-catenins, belongs to the vinculin family of proteins, best known for their actin-filament binding properties and crucial roles in cell-cell and cell-substrate adhesion; however, despite sequence homology, α-catulin seems to have independent roles. α-catulin has been shown to be important in inflammation, apoptotic resistance, cytoskeletal reorganization, senescence resistance, cancer progression, and EMT. Multiple binding proteins of α-catulin revealed in recent years suggest a molecular hub function, integrating a cytoskeleton with a number of signaling pathways. Unfortunately, the molecular mechanisms of α-catulin action are still poorly characterized and need further investigation, especially in the field of cancer progression.

Increased α-catulin expression was observed in the invading front of squamous cell carcinoma, and its depletion led to decreased invasion and metastasis in a xenograft transplant mouse model. α-catulin was also reported to be upregulated in a highly invasive non-small cell lung cancer cell line, as well as in breast and prostate cancer. Despite multiple reports describing α-catulin as an important factor contributing to cancer cell migration and invasion, the exact molecular mechanism leading to this phenotype remains unclear.

As α-catulin depletion was shown to have a strong effect on RhoA signaling and the actomyosin cytoskeleton arrangement, it will be crucial to further investigate the role of α-catulin in spatial RhoA distribution during cell migration. Further experiments encompassing mass spectrometry are currently underway in our laboratory in order to identify potential α-catulin interaction partners contributing to the front-rear stabilization of migrating cancer cells.

A question also remains about potential α-catulin and cadherin interactions. The role of α-catulin in the process of EMT and the switch between relatively stable cellcell contacts and an increase in motility, which is crucial for cancer invasion, is of great interest. Catulin expression was reported to be upregulated when α-catenin, a cell-cell junction protein, was conditionally lost in the epithelium, which was accompanied by an increased proliferation rate and migrative properties. Therefore, further investigations

at the structural, cellular, and functional levels are also needed to understand the exact sequence of molecular interactions and conformational changes operating between the cadherin/β-catenin/α-catenin complex and α-catulin and F-actin and tension-dependent remodeling of cell-cell adhesion.

An analysis of α-catulin dynamics using high-resolution live imaging should help us to map α-catulin's localisation and interactions in time and space. These could bring us closer to solving how α-catulin orchestrates adhesion and the actin cytoskeleton.

As α-catulin is broadly expressed and plays multiple physiological functions both during development and adult life, direct therapeutic strategies towards silencing its gene may not be applicable. On the other hand, targeted disruption of signaling pathways originating or ending at α-catulin may be a more promising therapeutic target.

**Author Contributions:** M.G. contributed: literature review and manuscript writing; K.K. contributed: literature review and manuscript writing; T.P. contributed: literature review and manuscript writing; A.K. contributed: literature review and manuscript writing. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was funded by the Polish National Science Center (NCN) grants: 2015/17/B/ NZ5/02551; 2017/25/B/NZ5/01597 and 2020/37/B/NZ5/03950 to A. Kobielak.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

