**Anti-tumor Activity and Epigenetic Impact of the Polyphenol Oleacein in Multiple Myeloma**

**Giada Juli 1, Manuela Oliverio 2, Dina Bellizzi 3, Maria Eugenia Gallo Cantafio 1, Katia Grillone 1, Giuseppe Passarino 3, Carmela Colica 4, Monica Nardi 2, Marco Rossi 1, Antonio Procopio 2, Pierosandro Tagliaferri 1, Pierfrancesco Tassone 1,\* and Nicola Amodio 1,\***


Received: 28 June 2019; Accepted: 11 July 2019; Published: 16 July 2019

**Abstract:** Olive oil contains different biologically active polyphenols, among which oleacein, the most abundant secoiridoid, has recently emerged for its beneficial properties in various disease contexts. By using in vitro models of human multiple myeloma (MM), we here investigated the anti-tumor potential of oleacein and the underlying bio-molecular sequelae. Within a low micromolar range, oleacein reduced the viability of MM primary samples and cell lines even in the presence of bone marrow stromal cells (BMSCs), while sparing healthy peripheral blood mononuclear cells. We also demonstrated that oleacein inhibited MM cell clonogenicity, prompted cell cycle blockade and triggered apoptosis. We evaluated the epigenetic impact of oleacein on MM cells, and observed dose-dependent accumulation of both acetylated histones and α-tubulin, along with down-regulation of several class I/II histone deacetylases (HDACs) both at the mRNA and protein level, providing evidence of the HDAC inhibitory activity of this compound; conversely, no effect on global DNA methylation was found. Mechanistically, HDACs inhibition by oleacein was associated with down-regulation of Sp1, the major transactivator of HDACs promoter, *via* Caspase 8 activation. Of potential translational significance, oleacein synergistically enhanced the in vitro anti-MM activity of the proteasome inhibitor carfilzomib. Altogether, these results indicate that oleacein is endowed with HDAC inhibitory properties, which associate with significant anti-MM activity both as single agent or in combination with carfilzomib. These findings may pave the way to novel potential anti-MM epi-therapeutic approaches based on natural agents.

**Keywords:** experimental therapeutics; HDAC; multiple myeloma; oleacein

#### **1. Introduction**

Multiple myeloma (MM) is a clonal B cell malignancy characterized by the accumulation of tumor plasma cells (PCs) in the bone marrow (BM), where different cell types establish a complex microenvironment that supports survival, proliferation and drug-resistance of the malignant clone. The last few years have witnessed a rapid development of drugs for the treatment of this malignancy, leading to increased extent and frequency of response and to the improvement in median overall survival of patients. However, despite such therapeutic advancements, MM eventually evolves into a drug-resistant phase leading to patients' death [1]. This finding has stimulated continuous investigation on new therapeutic options, as single agents or in combination with established anti-MM drugs. In this

regard, natural compounds have recently emerged as novel chemopreventive and/or therapeutic tools able to target oncogenic pathways involved in the pathogenesis of human malignancies. Significant anti-inflammatory, anti-oxidant and cytotoxic effects of natural agents have been demonstrated also in MM, either by epidemiologic or animal studies, and even by clinical trials [2]. Several natural compounds from various plants, fungi and marine organisms have been shown to target epigenetic events underpinning tumorigenesis, such as DNA methylation, histone modifications (methylation, acetylation and phosphorylation), and non-coding RNAs [3], known to be deeply dysregulated and representing valuable therapeutic targets in MM [2].

Polyphenols are important constituents of several plants and vegetables, recognized as powerful anti-oxidants endowed with anti-inflammatory, antimicrobial and antitumor activities [4]. Indeed, a major source of polyphenols is represented by extra virgin olive oil (EVOO), whose polyphenolic fraction includes simple phenols (tyrosol and hydroxytyrosol), secoiridoids (oleuropein, oleocanthal and oleacein), and lignans. EVOO-derived secoiridoids, characterized by the presence of elenoic acid or its derivatives in their molecular structure, have been shown to prevent obesity, osteoporosis, and neurodegeneration. Oleocanthal has shown anti-tumor activity in different types of tumors, including MM, hepatocellular carcinoma, breast, prostate, pancreatic cancers and melanoma [5–9]. The most abundant secoiridoid of EVOO is the dialdehydic form of elenolic acid conjugated with 3,4-(dihydroxyphenyl)ethanol (3,4-DHPEA-EDA), also known as oleacein, whose anti-oxidant, anti-inflammatory, and anti-microbial properties have recently emerged [10], while its effects on tumor biology are still poorly defined.

We here aimed to investigate the anti-tumor potential of oleacein against MM. Our results highlight a previously unknown epigenetic impact of oleacein on MM cells, with potential implications for the management of MM and possibly other malignancies.

#### **2. Results**

#### *2.1. Inhibitory E*ff*ects of Oleacein on MM Cell Viability and Survival*

Oleacein, whose chemical structure is reported in Figure 1A, was obtained by a green semi-synthetic modification of oleuropein as previously reported [11]. By using a panel of eight different MM cell lines carrying the major cytogenetic aberrations of MM, we sought to analyze the impact of oleacein on cell viability. MM cells were exposed to increasing doses of oleacein, and cell viability was assessed by Cell Titer Glo (CTG) assay. Noteworthy, a dose-dependent inhibition of cell viability was observed 48 h after oleacein treatment, with IC50s ranging from 5.0 to 20.0 μM (Figure 1B); conversely, oleacein did not affect the viability of PBMCs from healthy donors (Figure 1C), suggesting a favorable therapeutic index. We next evaluated the effects of oleacein on MM cells in the presence of the BM *milieu*, which is known to trigger drug-resistance [1]. Importantly, the inhibitory effect of oleacein was maintained even when MM cell lines, or primary CD138<sup>+</sup> cells purified from MM patients, were cultured in the presence of HS-5 stromal cells, thus suggesting that oleacein can overcome BM microenvironment-mediated pro-survival effects (Figure 1D). In addition, oleacein drastically suppressed the clonogenicity of MM cells in methylcellulose cultures (Figure 1E). Collectively, these data unveil an inhibitory activity of oleacein on MM cell viability and survival.

**Figure 1.** Effects of oleacein on multiple myeloma (MM) cell survival. (**A**) Chemical structure of oleacein. (**B**) Cell viability of MM cell lines as determined by Cell Titer Glo (CTG) assay 48 h after treatment with increasing doses of oleacein or vehicle (DMSO). (**C**) CTG assay performed on peripheral blood mononuclear cells (PBMCs) from three different healthy donors treated with oleacein for 48 h. (**D**) CTG assay in MM cell lines and primary CD138<sup>+</sup> cells from three MM patients (MM pt#1, #2 and#3) co-cultured on HS-5 stromal cells and treated for 48 h with 5.0μM oleacein. (**E**) Colony formation assay performed on MM cell lines treated for 14 days with oleacein; representative pictures of JJN3 colonies at day 14 are shown in the right panel (5× magnification). \* *p* < 0.05 as compared to vehicle-treated cells.

#### *2.2. Oleacein Triggers Cell Cycle Arrest and Apoptosis*

To unravel the biological sequelae of oleacein in MM, we first analyzed by flow cytometry the cell cycle profile of oleacein-treated cells after propidium iodide staining. As shown in Figure 2A, oleacein increased the percentage of hypodiploid cells (sub-G0 phase), and also induced the accumulation of cells in the G0/G1 phase; WB analysis showed a dose-dependent increase of cell cycle inhibitors p27KIP1 and p21CIP1 protein expression (Figure 2B), strengthening the capability of oleacein to trigger cell cycle blockade.

In order to confirm apoptosis induction, we performed Annexin V/7-AAD staining on MM cell lines after oleacein treatment. We found an increase in late apoptotic events, which ranged from 20 to 30% after treatment with oleacein 5.0 and 10.0 μM, respectively (Figure 2C); the increase in cleaved PARP1, caspase-3 and caspase-8 on oleacein-treated MM cell lines, as shown by Western Blot (WB), further confirmed apoptosis induction (Figure 2D); no activation of caspase-7 and -9 was observed (Supplementary Figure S1), thus indicating that oleacein predominantly activates the extrinsic apoptotic pathway. These results therefore indicate that oleacein may elicit anti-MM activity through modulation of cell cycle and apoptosis.

**Figure 2.** Oleacein triggers cell cycle blockade and apoptosis. (**A**) Cell cycle analysis was performed on NCI-H929 cells by PI staining, 24 h after treatment with oleacein or vehicle (DMSO). (**B**)Western Blot (WB) analysis of p27KIP1 and p21CIP1 in whole cell lysates from MM cells after treatment with oleacein for 24 h; actin was used as loading control. (**C**) Annexin V/7-AAD staining of MM cells after treatment with oleacein for 48 h; a representative experiment on NCI-H929 cells is shown on the left side. (**D**) WB of PARP1, cleaved caspase-3 and cleaved caspase-8 in NCI-H929 and JJN3 cell lines after 24 h of oleacein treatment; GAPDH was used as loading control. \* *p* < 0.05 as compared to vehicle-treated cells.

#### *2.3. HDAC Inhibitory Activity of Oleacein in MM*

Aberrant epigenetic patterns are common in MM, where they are frequently associated with disease onset and/or progression to advanced stages [12–14]. A large body of literature has highlighted the capability of several natural compounds to revert the altered epigenome of MM cells by counteracting key oncogenic epigenetic regulators [2]. On this basis, we investigated the epigenetic impact of oleacein on MM cells, by analyzing its effects both on global DNA methylation (GDM) and histone acetylation, the two major epigenetic mechanisms dysregulated in MM. Oleacein did not significantly modify the whole content of methylated cytosines in DNA from NCI-H929 and JJN3 cell lines (Figure 3A); in line with the latter finding, no significant changes in mRNA or protein levels of DNA methyltransferases (DNMT1, DNMT3A and DNMT3B) were observed upon oleacein treatment, as shown by QRT-PCR (Figure 3B) and WB analyses (Figure 3C). Conversely, oleacein induced a significant increase in acetylated histone H3, histone H4 (Figure 3D) and α-tubulin (Figure 3E). Collectively, these findings suggest that oleacein is able to modulate the acetylome of MM cells.

**Figure 3.** Oleacein affects the acetylome but not the methylome of MM cells. (**A**) Global DNA methylation was measured in MM cells treated for 24 h with oleacein, as reported in materials and methods. Quantitative Real Time PCR (QRT-PCR) (**B**) and WB analysis (**C**) of DNMT1, DNMT3A and DNMT3B in JJN3 cells treated for 24 h with oleacein; GAPDH was used as loading control. WB analysis of acetylated histone H3, histone H3, acetylated histone H4, histone H4 (**D**) and acetylated α-tubulin (**E**) in NCI-H929 and JJN3 cells treated with oleacein for 24 h; GAPDH was used as loading control.

Aberrant expression and/or activity of HDACs drive malignant transformation of tumor cells, thus making HDACs valuable therapeutic targets in MM [13,15]. We analyzed, in oleacein-treated JJN3 cells, the mRNA and protein expression of HDACs with established oncogenic role in MM. Intriguingly, oleacein induced down-regulation of several class I/II HDACs, namely HDAC1/2/3/4/6, both at mRNA (Figure 4A) and protein level (Figure 4B); moreover, biochemical fractionation experiments indicated that oleacein reduced both the nuclear and the cytoplasmic fraction of class II HDAC4 and HDAC6, which are known to shuttle between the nucleus and the cytoplasm (Figure 4C). To understand whether oleacein could act as a canonic HDAC inhibitor, we carried out an in vitro HDAC activity assay using JJN3 nuclear extracts. Incubation with oleacein did not induce any change in the HDAC activity recovered from nuclear extracts, differently from trichostatin A (TSA) or SAHA (Supplementary Figure S2), that were used as positive controls. This finding suggests that the impact of oleacein on the acetylome of MM cells does not occur via enzymatic HDAC inhibition. We therefore explored additional mechanisms accounting for oleacein effects on HDACs, and hypothesized that oleacein could transcriptionally regulate HDACs *via* Sp1. In fact, Sp1, a ubiquitous transcription factor endowed with oncogenic activity in hematologic and solid malignancies [12,13,16,17], was proven to act as a transcriptional activator of HDACs [18]. Interestingly, oleacein treatment induced down-regulation of Sp1 (Figure 4D), and this effect occurred in a caspase 8-dependent fashion, since it was abrogated by Z-IETD-FMK, a selective caspase 8 inhibitor (Figure 4E). These results indicate that oleacein effects on HDACs expression might be mediated by Sp1.

Sp1 is involved in negative feedback loops with miRNAs, like miR-29b [19–21] and miR-22 [22], both acting as tumor suppressors in MM [23,24]. As expected, oleacein-induced Sp1 inhibition was

paralleled by the upregulation of miR-29b and miR-22 (Supplementary Figure S3), thus strengthening the role of Sp1 pathway's inhibition in the anti-MM activity of oleacein.

**Figure 4.** Oleacein targets HDACs. QRT-PCR (**A**) and WB analysis (**B**) of HDAC1, HDAC2, HDAC3, HDAC4, HDAC6 in JJN3 cells treated with oleacein for 24 h; GAPDH was used as loading control. (**C**) WB analysis of HDAC4 and HDAC6 in nuclear (N) and cytoplasmic (C) protein fractions from JJN3 cells treated for 24 h with oleacein; histone H1 and GAPDH were used as nuclear and cytoplasmic marker, respectively. (**D**) WB analysis of Sp1 in JJN3 cells treated with oleacein for 24 h. (**E**) WB analysis of Sp1 in JJN3 cells treated with 5.0 μM oleacein with or without 20.0 μM Z-ITED-FMK; GAPDH was used as loading control. \* *p* < 0.05 as compared to vehicle-treated cells.

#### *2.4. Oleacein Enhances the Anti-MM Activity of Carfilzomib*

HDAC inhibitors (HDACi) are part of the therapeutic armamentarium against MM, and clinical studies have shown promising therapeutic activity of pan- or selective-HDACi when used within combination regimens [13]. On this basis, we investigated whether, similarly to pan-HDACi, oleacein treatment could trigger synergistic anti-MM activity in combination with clinically-relevant proteasome inhibitors. With this aim, NCI-H929 cells were treated with different concentrations of oleacein with or without bortezomib or carfilzomib, and subsequently cell viability was analyzed by CTG; the occurrence of synergism was assessed by Calcusyn. Interestingly, oleacein synergistically enhanced the effects of carfilzomib (CI < 1.0) on the inhibition of cell viability (Figure 5A), while combination with bortezomib was generally antagonistic (CI > 1.0; Supplementary Figure S4). Annexin V-7AAD staining of NCI-H929-treated cells indicated a higher apoptotic rate when oleacein was combined with carfilzomib, as compared to single agent treatment (Figure 5B). Accordingly, WB analysis showed increased cleavage of caspase 3 and superior Sp1 downregulation upon oleacein *plus* carfilzomib combination, thus confirming enhancement of apoptosis; moreover, oleacein *plus* carfilzomib enhanced downregulation of HDAC2, HDAC3, HDAC4 and HDAC6, with respect to single-agent treatment, which associated with increased histone H4 acetylation (Figure 5C). Collectively, these results indicate that the combination of olecein with carfilzomib results in significant acetylome derangement and apoptosis triggering of MM cells.

**Figure 5.** Oleacein enhances the anti-MM activity of carfilzomib. (**A**) CTG assay was performed on NCI-H929 cells treated with oleacein (2.5, 5.0 or 10.0 μM) and carfilzomib (0.1, 0.5 and 1.0 nM). Results are expressed as percentage of the viability of vehicle-treated cells. The right panel reports values of fraction affected (Fa) and combination indexes (CI) in a triplicate experiment, as calculated by the Calcusyn software. (**B**) Annexin V/7-AAD staining of NCI-H929 cells after treatment with vehicle (DMSO), 5.0 μM oleacein and 1.0 nM carfilzomib for 24 h; a representative FACS experiment is reported. (**C**). WB analysis of pro-Caspase 3, cleaved caspase 3, SP1, HDAC2, HDAC3, HDAC4, HDAC6, and acetylated histone H4 in NCI-H929 cells treated with carfilzomib (1.0 nM), oleacein (5.0 μM) or a combination of the two; α-tubulin or GAPDH were used as loading controls.

#### **3. Discussion**

Naturally occurring compounds endowed with anti-tumor activity have been found in different sources, such as vegetables, fruits, herbs and fermented products. These agents may act either by preventing the onset of primary cancer, or by antagonizing the evolution of pre-malignant and malignant lesions towards more aggressive stages. Noteworthy, experimental findings on a variety of natural compounds, including curcumin, resveratrol, celastrol and many others, have demonstrated significant advantages for the management of MM [2]. The molecular mechanisms underlying the anti-tumor activity of such compounds are diverse and only partially understood, with inhibition of oncogenic signal transduction pathways and modulation of the cellular epigenome being the most well documented. Regarding the epigenetic-modulating effects, it has been demonstrated that several natural agents, by targeting DNMTs [25], HDACs [26] or non-coding-RNAs [27], may revert aberrant epigenetic patterns implicated in the pathogenesis of human neoplasias, including MM [2].

Polyphenols found in the EVOO, a major component of mediterranean diet, have demonstrated to be protective against several diseases, including those of cardiovascular and metabolic origin [28]. The pro-active ingredient oleuropein and its derivative hydroxytyrosol have been widely studied, demonstrating many beneficial effects, both in vitro and in vivo, in experimental preclinical models [29]. Moreover, many studies have disclosed remarkable anti-tumor activity of oleuropein and hydroxytyrosol against several types of cancers [30]. However, the amount of oleuropein in the EVOO

is too low to fully explain the beneficial effects deriving from EVOO assumption with diet. In fact, the endogenous β-glucosidase released during the olive oil extraction process hydrolyzes oleuropein, generating a series of degradation products, all of which are less hydrophilic than the original natural secoiridoids, and therefore more soluble in the oily matrix extracted from the drupes. Thus, EVOO is scarce in oleuropein and much more abundant in its degradation product oleacein [31], thus making it one of the most plausible effectors of the biological activity of EVOO [11,32].

Oleacein can be obtained by a simple and environmentally friendly method, starting from the easily available natural oleuropein [11]. Recent preclinical studies have highlighted anti-microbial [33], anti-inflammatory [34], and protective effects of oleacein against diet-dependent metabolic alterations [35]; conversely, its anti-antitumor activity remains poorly characterized. We here provided the first evidence of the anti-tumor activity of oleacein against MM cells: importantly, oleacein triggered cell cycle arrest and apoptosis and reduced clonogenicity, without exerting any toxic effect on healthy PBMCs, thus suggesting a favorable therapeutic index of this agent. Moreover, oleacein cytotoxic effects were also observed against primary MM cells co-cultured with BM-derived stromal cells, demonstrating the capability of oleacein to overcome BM microenvironment-dependent drug resistance.

We sought to shed light on the molecular mechanisms underlying oleacein anti-tumor activity in MM. To this aim, we focused on epigenetic mechanisms, known to be a major target of several natural agents, and whose dysregulation has been largely implicated in the pathogenesis of MM [14]. Indeed, aberrant expression of effectors of the epigenetic machinery, including DNMTs [36], HDACs [13], polycomb genes [37,38] and non-coding RNAs [39,40], has been reported in MM and has been harnessed in the context of novel anti-tumor strategies [41].

Collectively, our data indicate a strong increase in acetylation of histones and of α-acetyl-tubulin upon oleacein treatment, while no effect on GDM could be observed. This finding highlights a novel HDAC inhibitory activity of oleacein in MM. We attempted to characterize the mechanisms underlying such HDAC inhibitory effects, and found out that oleacein could transcriptionally inhibit HDACs expression likely *via* targeting of Sp1, a known transactivator of HDACs' promoter. Since previous findings indicated that bortezomib-evoked transcriptional repression of HDACs by Sp1 occurs in a caspase 8-dependent fashion [18], we investigated whether oleacein effect on Sp1 could be similarly mediated by caspase 8. In agreement with this hypothesis, oleacein-induced Sp1 down-regulation was abrogated by the caspase 8 inhibitor Z-IETD-FMK.

Dysregulated transcription factors may drive down-regulation of tumor suppressor miRNAs in MM [12,40,42]. By establishing molecular feedback loops, Sp1, a pleiotropic transcription factor endowed with oncogenic activity in human malignancies [17], was shown to negatively affect the expression of miRNAs [40]. We have previously reported that miRNA dysregulation features prominently in the pathobiology of MM, with certain miRNAs, such as miR-125a-5p [43], miR-21 [44], miR-221 [45] and miR-17-92 cluster [46], highly expressed in MM and acting as oncogenes, while others such as miR-29b [20], miR-22 [24] and miR-125b [47], behave as tumor suppressors.

Consistent with inhibition of Sp1, oleacein triggered upregulation of tumor suppressive miRNAs, namely miR-29b [20] and miR-22 [24], which are known to be negatively regulated by this transcription factor [19,22]. These findings underscore the ability of oleacein to trigger a tumor suppressive miRNA network likely contributing to its cytotoxicity against MM cells.

Non-selective HDAC inhibitors, such as romidepsin, vorinostat and panobinostat, have shown a remarkable anti-MM effect in preclinical and clinical studies, with significant efficacy, along with reduced side effects, when given within combination regimens [13]; amongst pan-HDACi, panobinostat has been approved by FDA for MM treatment [48]. Having demonstrated its pan-HDAC inhibitory activity, and taking into account the promising clinical data which emerged from MM patients treated with proteasome inhibitors and pan-HDACi combination therapies, we also explored whether oleacein could enhance the anti-tumor activity of bortezomib or carfilzomib. Notably, when combined with carfilzomib, oleacein synergistically enhanced its in vitro cytotoxicity, with superior Sp1 and HDACs

down-regulation and a resultant increase in apoptosis of MM cells. A follow-up investigation is planned to evaluate the anti-tumor effect of oleacein-based treatments in the context of validated in vivo preclinical models of human MM.

#### **4. Materials and Methods**

#### *4.1. Chemicals*

A green semi-synthetic procedure was carried out to purify oleacein from Coratina cultivar olive leaves of Olea Europaea L. as reported; in detail, oleacein was directly extracted from a water solution of oleuropein in the presence of NaCl under microwave assistance at 180 ◦C; the crude extract was purified by flash chromatography on silica gel (eluent mixture: CHCl3/MeOH 95:5 v/v) [49]. The purity was determined by RP-HPLC, HRMS-ESI, 1H-and 13C-NMR, as previously reported [11]. Bortezomib and carfilzomib were purchased from Selleckchem (Houston, TX, USA) as DMSO stock-solutions.

#### *4.2. Cell Cultures*

MM cell lines NCI-H929, RPMI-8226, U266, MM1s and JJN3 were purchased from DSMZ, which certified authentication performed by short tandem repeat DNA typing; the bone marrow stromal cell line HS-5 was purchased from the American Type Culture Collection (Rockville, MD, USA); AMO-1 and AMO-BZB cells were kindly provided by Dr. C. Driessen (University of Tubingen, Tubingen, Germany). The most relevant characteristics of the MM cell lines used are reported in Supplementary Table S1. All these cell lines were immediately frozen and used from the original stock within 6 months. Human MM cell lines were cultured in RPMI-1640 media containing 10% FBS, 2 μmol/L glutamine, 100 U/mL penicillin, and 100 μg/mL streptomycin (GIBCO; Life Technologies, Carlsbad, CA, USA) and tested for mycoplasma contamination. Peripheral blood mononuclear cells (PBMCs) and CD138<sup>+</sup> cells from BM of MM patients were isolated by Ficoll-hypaque (Lonza Group, Basel, Switzerland), followed by anti-CD138 microbeads (Miltenyi Biotec, Bergish Gladbach, Germany) selection, in accordance with the Declaration of Helsinki following informed consent and Institutional Review Board (University of Catanzaro, Catanzaro, Italy) approval, as previously reported (institutional approval: n.120/2015) [50]; the purity of immunoselected cells was assessed by flow cytometry using a phycoerythrin-conjugated CD138 monoclonal antibody (BD Pharmingen, San Jose, CA, USA; clone DL-101) and was higher than 95%. In co-culture experiments, primary CD138<sup>+</sup> MM cells (2.5 <sup>×</sup> 105 cells) were plated in 24-well plates, and left separated from HS-5 stromal cells (2.5 <sup>×</sup> 105 cells) growing adherent to the plate by a transwell insert of 0.4 μm pore size (Corning, New York, NY, USA).

#### *4.3. Cell Viability, Apoptosis and Cell Cycle Assay*

Cell viability was evaluated by Cell Titer-Glo (CTG; Promega, Madison, Wisconsin, USA), as previously reported [12]. For colony formation assay, 200 cells were plated in triplicate in 1 mL of mixture composed of 1.1% methylcellulose (MethoCultTM STEMCELL Technologies, Cambridge, UK) in RPMI-1640 + 10% FBS. Crystal violet-stained colonies were scored after 2 weeks under an inverted microscope (Leica DM IL LED, Wetzlar, Germany) at 5× magnification using a grid. Apoptosis was evaluated by flow cytometric (FACS) analysis following Annexin V-7AAD staining (BD Pharmingen, San Jose, CA, USA). Drug interactions were assessed by CalcuSyn 2.0 software (Biosoft, Novosibirsk, Russia), which is based on the Chou-Talalay method. When combination index (CI) = 1, this equation represents the conservation isobologram and indicates additive effects; CI < 1 indicates synergism; CI > 1 indicates antagonism. Cell cycle distribution was evaluated by FACS analysis on MM cells previously treated with oleacein for 24 h, after staining with Propidium Iodide (PI). Cells were collected, washed twice with phosphate-buffered saline (PBS) and fixed in cold 70% ethanol at −20 ◦C. Before FACS analysis, cells were washed with PBS and stained in 50 μg/mL PI, 100 μg/mL RNase, 0.05% Nonidet P-40 for 1 h at room temperature in the dark. Cell cycle profiles were obtained using Attune NxT Flow Cytometer (Thermo Fisher Scientific, Waltham, MA, USA).

#### *4.4. Western Blot and Antibodies*

Whole cell protein extracts were prepared using NP40 lysis buffer containing Halt Protease Inhibitor cocktail (Invitrogen, Thermo Scientific, Carlsbad, CA, USA), separated using 4–12% Novex Bis-Tris SDS-acrylamide gels (Invitrogen), and electrotransferred on nitrocellulose membranes (Bio-Rad, Hercules, CA, USA), as described [39]. Then, nitrocellulose membranes were blocked with milk and probed over-night with primary antibodies at 4 ◦C; then membranes were washed three times in PBS-Tween and incubated with a secondary antibody conjugated with horseradish peroxidase for 2 h at room temperature. Chemiluminescence was detected using SuperSignal West Pico PLUS Chemiluminescent Substrate (Thermo Scientific). Western blot (WB) was performed using Cell Signaling antibodies: PARP (#9532), -Caspase-8 (#9746), -Caspase-3 (#9665), AcH3-Lysin 8 (K9) (#9649P), SP1 (#9389S), HDAC1 (#5356T), HDAC2 (#5113P), HDAC3 (3949P), HDAC4 (#7628S), HDAC6 (#7558P), histone H4 (#2935), histone H3 (#4499), α-tubulin (#2125). Ac-α tubulin (sc-23950), Ac-H4 Ser1/Lys 5/Lys8/Lys Lys 12 (sc-34263), Actin (sc-1616) and -GAPDH (sc-25778) were from Santa Cruz Biotechnology (Dallas, TX, USA); Dnmt1 (ab 13537), Dnmt3a (ab 13888) and Dnmt3b (ab 2851) were from abcam (Cambridge, UK). Densitometric analysis of blots was performed by LI-COR Image Studio Digits Ver 5.0 (Bad Homburg, Germany), expressed as a relative protein unit after normalization with appropriate housekeeping, and reported under each blot. Whole blots of all experiments presented in this study are reported as Supplementary Figures S5–S9.

#### *4.5. Reverse Transcription and Quantitative Real Time PCR (qRT-PCR)*

Total RNA was extracted from cells using TRIzol® reagent (Gibco, Life Technologies, Carlsbad, CA, USA), following the manufacturer's instructions. The RNA quantity and quality were assessed through NanoDrop® ND-1000 Spectrophotometer (Waltham, MA, USA). To evaluate transcript changes, 1000 ng of total RNA was reverse-transcribed to cDNA using the "High Capacity cDNA Reverse Transcription Kit" (Applied Biosystems, Carlsbad, CA, USA). The following single-tube TaqMan assays (Applied Biosystems, Carlsbad, CA, USA) were used to detect and quantify genes using the Viia7 DX real time PCR instrument (Life Technologies, Waltham, MA, USA): DNMT1 (Hs00154749\_m1), DNMT3a (Hs01027166\_m1), DNMT3b (Hs00171876\_m1), HDAC1 (Hs02621185\_s1), HDAC2 (Hs00231032\_m1), HDAC3 (Hs00187320\_m1), HDAC4 (Hs01041638\_m1), HDAC6 (Hs00195869\_m1), and GAPDH (Hs02786624 g1). miRNA expression levels were determined by TaqMan RT-PCR, using the single-tube TaqMan miRNA assays (hsa-miR-29b, assay ID 000413; hsa-miR-22, assay ID 000398, Applied Biosystems) to quantify mature miRNAs, by the use of the StepOne Thermocycler (Thermo Fisher Scientific, Waltham, MA, USA) and the sequence detection system, as previously reported [51]; miRNAs expression levels were normalized on RNU44 (assay ID 001094). Comparative real-time polymerase chain reaction (RT-PCR) was performed in triplicate.

#### *4.6. HDAC Activity Assay*

Nuclear extracts prepared using NE-PER Nuclear and Cytoplasmic Extraction Reagents kit (Thermo Scientific, catalog #78833) were mixed with Oleacein or DMSO, and then HDAC activity was determined according to the manufacturer's instructions (BioVision, Zurich, Switzerland; catalog #K331-100). Trichostatin A (TSA) and SAHA were used as positive controls.

#### *4.7. Quantification of Global 5-Methylcytosine Levels*

Global DNA methylation levels were determined by using 5-mC DNA ELISA kit (Zymo Research, Irvine, CA, USA) as described [52]. Briefly, 100ng of genomic DNA, brought to final volume to 100 μL with 5-mC coating buffer, was denatured at 98 ◦C for 5min, put in ice for 10' and then coated on the surface of the ELISA plate wells. After incubation at 37 ◦C for 1 h, the wells were washed thrice with 200 μL of 5-mC ELISA buffer and then incubated at 37 ◦C for 1 h with an antibody mix consisting of anti-5-mC (1:2000) and secondary (1:1000) antibodies. Then, the antibody mix was removed from the

wells through three consecutive washes with 200μL of 5-mC ELISA buffer. One-hundred microliters of HRP developer was added to each well and incubated at room temperature for 1 h. Absorbance at 405nm was measured using an ELISA plate reader. The percentage of 5-mC was calculated using the second-order regression equation of the standard curve that was constructed by using mixtures of the fully unmethylated and methylated control DNAs, provided by the manufacturer, to generate standards of known 5-mC percentage (0, 5, 10, 25, 50, 75 and 100%).

#### *4.8. Statistical Analysis*

Each experiment was performed at least three times, and values were reported as mean ±standard deviation. Data were analyzed using Student's t tests for two group comparisons or a one-way analysis of variance (ANOVA) for multiple comparisons using the Graphpad software (GraphPad Software, La Jolla, CA, USA). *p*-value < 0.05 was considered significant.

#### **5. Conclusions**

Our results indicate that oleacein, the most abundant EVOO secoiridoid, elicits significant anti-tumor activity by promoting cell cycle arrest and apoptosis, either as a single agent or in combination with the proteasome inhibitor carfilzomib. Moreover, our data highlight an epigenetic impact of oleacein in MM, as demonstrated by the impairment of the MM acetylome, likely *via* Sp1-dependent transcriptional inhibition of HDACs. Altogether, these findings provide the molecular rationale for potential epi-therapeutic anti-MM strategies based on natural agents.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2072-6694/11/7/990/s1, Figure S1: WB of pro-caspase 7, cleaved caspase 7, pro-caspase 9 and cleaved caspase 9 in NCI-H929 cells after 24 h of oleacein treatment, Figure S2: HDAC activity was determined in JJN3 cells treated with oleacein, as reported in materials and methods; TSA was used as positive control. Results are expressed as percentage of HDAC activity as compared to DMSO-treated cells, Figure S3: miR-29b and miR-22 expression levels were determined by qRT-PCR in JJN3 cells treated for 24 h with oleacein; miRNA expression was normalized on RNU44, Figure S4: CTG assay was performed on NCI-H929 cells treated with oleacein (2.5, 5.0 or 10.0 μM) and bortezomib (1.0, 2.0 and 5.0 nM). Results are expressed as percentage of the viability of vehicle-treated cells. The right panel reports values of fraction affected (Fa) and combination indexes (CI) in a triplicate experiment, as calculated by the Calcusyn software, Figure S5: whole blots for Figure 2, Figure S6: whole blots for Figure 3, Figure S7: whole blots for Figure 4, Figure S8: whole blots for Figure 5, Figure S9: whole blots for Figure S1. Table S1: Characteristics of the MM cell lines used in this study.

**Author Contributions:** Data curation, K.G. and M.N.; Formal analysis, M.R.; Investigation, G.J., M.O., D.B. and N.A.; Methodology, M.E.G.C., G.P. and A.P.; Resources, P.T.; Software, C.C.; Writing—original draft, P.T. (Pierosandro Tagliaferri), P.T. (Pierfrancesco Tassone) and N.A.; Writing—review & editing, N.A.

**Funding:** This work has been supported by Italian Association for Cancer Research (AIRC), "Innovative Immunotherapeutic Treatments of Human Cancer" Multi Unit Regional Project No. 16695 (co-financed by AIRC and CARICAL foundation) to Pierfrancesco Tassone.

**Acknowledgments:** We thank Ivana Criniti for editorial and laboratory assistances.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**


© 2019 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 (http://creativecommons.org/licenses/by/4.0/).

### *Article* **Divergent E**ff**ects of Daidzein and Its Metabolites on Estrogen-Induced Survival of Breast Cancer Cells**

#### **Emiliano Montalesi, Manuela Cipolletti, Patrizio Cracco, Marco Fiocchetti and Maria Marino \***

Department of Science, University Roma Tre, Viale Guglielmo Marconi 446, I-00146 Roma, Italy; emiliano.montalesi@uniroma3.it (E.M.); manuela.cipolletti@uniroma3.it (M.C.); patrizio.cracco95@live.it (P.C.); marco.fiocchetti@uniroma3.it (M.F.)

**\*** Correspondence: maria.marino@uniroma3.it; Tel.: +39-065733-6320

Received: 28 November 2019; Accepted: 23 December 2019; Published: 9 January 2020

**Abstract:** Although soy consumption is associated with breast cancer prevention, the low bioavailability and the extensive metabolism of soy-active components limit their clinical application. Here, the impact of daidzein (D) and its metabolites on estrogen-dependent anti-apoptotic pathway has been evaluated in breast cancer cells. In estrogen receptor α-positive breast cancer cells treated with D and its metabolites, single or in mixture, ERα activation and Neuroglobin (NGB) levels, an anti-apoptotic estrogen/ERα-inducible protein, were evaluated. Moreover, the apoptotic cascade activation, as well as the cell number after stimulation was assessed in the absence/presence of paclitaxel to determine the compound effects on cell susceptibility to a chemotherapeutic agent. Among the metabolites, only D-4- -sulfate maintains the anti-estrogenic effect of D, reducing the NGB levels and rendering breast cancer cells more prone to the paclitaxel treatment, whereas other metabolites showed estrogen mimetic effects, or even estrogen independent effects. Intriguingly, the co-stimulation of D and gut metabolites strongly reduced D effects. The results highlight the important and complex influence of metabolic transformation on isoflavones physiological effects and demonstrate the need to take biotransformation into account when assessing the potential health benefits of consumption of soy isoflavones in cancer.

**Keywords:** estrogen; estrogen receptor alpha; polyphenols; daidzein; daidzein metabolites; paclitaxel; apoptosis; breast cancer cells

#### **1. Introduction**

Plant-derived polyphenols are naturally occurring nonsteroidal compounds that play important roles in ecological functions such as pollinator attraction or protection from herbivores and UV irradiation [1]. Due to their molecular structure and size, some of these molecules, including lignans, flavonoids, and stilbenes, have a chemical structure that resembles that of human estrogens, in particular to 17-β-estradiol (E2) [2]. Among other, isoflavones, a class of flavonoids ranked among the most estrogenic compounds, bind to estrogen receptor subtypes (i.e., ERα and ERβ) [3,4] exerting estrogenic and/or antiestrogenic effects [1]. For isoflavones, the key to their bioactivity in human and animals seems to rely on their (anti)estrogenic activity. Indeed, due their antiestrogenic activities, isoflavone enriched diets are associated with a lower incidence of a variety of estrogen-related cancers, including breast, endometrial, and ovarian cancers [5,6].

The main dietary source of isoflavones in humans are soybean and soybean products, which contain mainly daidzein (7,4- -dihydroxyisoflavone, D) and genistein (7, 4- -dihydroxy-6-methoxyisoflavone), whose potential efficacy against breast cancer is well documented [7–12]. Although these data are promising for the use of these compounds as anticancer therapeutic agents, the therapeutic application of isoflavones is still limited, mainly due to their scarce bioavailability in human beings. In particular, D is almost completely metabolized by the gut microbiota and liver, resulting in

water-soluble metabolites (e.g., equol, d-sulfates, o-desmethylangolensin) [13]. Thus, not only D has a low concentration and persistence in the bloodstream, even when consumed in high quantities, but also its metabolites strongly overcome the concentrations of the precursor probably affecting D biological activities [14–18]. Nowadays, the possibility that the metabolites may mimic the anti-carcinogenic effect of D in endocrine-related cancers or may act as synergistic or antagonistic molecules of their precursor is still unknown. Previously, the ability of D, metabolites, to modulate ERβ subtype activities activating a pro-apoptotic cascade in HeLa cancer cells transfected with ERβ expression vector, has been reported [19]. The possibility that a similar scenario could be found also in the modulation of ERα-dependent activities important for breast cancer cell progression is intriguing.

Breast cancer is one of the most common fatal diseases in women. A considerably higher ERα/ERβ ratio is reported in some breast cancer types, when compared to a healthy tissue, namely because of a reduction in the ERβ level [20,21]. The 70% of breast cancers are ERα-positive, where this subtype of receptor mediates E2-induced cancer cell survival and proliferation [22–25]. In particular, we recently demonstrated that E2 stimulation rapidly enhances the ERαactivity (Ser118 phosphorylation and PI3K/AKT pathway activation) in breast cancer cells increasing the intracellular levels of an anti-apoptotic globin, neuroglobin (NGB) [22]. E2-induced NGB upregulation in cancer cells represents an inducible defense mechanism of E2-related human breast cancer rendering them insensitive to several injury including chemotherapy [22,26,27]. Indeed, NGB displays a pivotal role in the E2/ERα-induced anti-apoptotic pathway that abrogates the cell death induced by a chemotherapeutic agent (paclitaxel, Pacl) [22]. Intriguingly, the stilbene Resveratrol decreases NGB levels interfering with E2/ERα-induced NGB up-regulation potentiating Pacl pro-apoptotic effects [4]. In this study, we investigated the potential interference of daidzein on this pathway and evaluated if its metabolites produced mainly from gut microbiota (i.e., equol, Eq, and O-desmethylangolensin, O-DMA) and from both liver and gut enzymes (D-4'-sulfate, D4S, D-7-sulfate, D7S, and D-4',7-disulfate, DDS) mimic D effect or may act as synergistic or antagonistic molecules. The ERα positive breast cancer cells, MCF-7 and T47D, have been used as the experimental models.

#### **2. Results**

#### *2.1. E*ff*ect of D and Its Metabolites on NGB Levels in Breast Cancer Cells*

NGB levels were evaluated in MCF-7 cells pre-treated for 24 h with different concentrations of D (Figure 1a) and its metabolites ranging between 0.1 and 10 μM (Figure 1). E2 (10 nM, 24 h) was used as positive control. Eq and O-DMA (Figure 1b) and D7S, D4S, and DDS (Figure 1c) were selected as prototypes of the D metabolites mainly produced by gut microbiota and the liver, respectively. The results clearly indicate that daidzein (1–10 μM) and D4S (0.1–1 μM) reduced the basal level of NGB levels in MCF-7 cells. On the other hand, Eq, O-DMA, D7S, and DDS, like E2, increased the level of NGB (Figure 1a,b). For the successive experiments, D and its mimetic sulphate metabolite (i.e., D4S) were selected. In addition, Eq, one gut metabolite, was selected as negative control. All compounds were used at 1 μM concentration in successive experiments.

**Figure 1.** Effects of daidzein (**a**), equol and O-desmethylangolesin (**b**), daidzein-7-sulfate, daidzein-4- -sulfate and daidzein-7,4- -disulfate (**c**) on neuroglobin intracellular levels. (**a**–**c**) Western blot (top) and densitometric analyses (bottom) of NGB protein levels in MCF-7 cells treated for 24 h with the vehicle (DMSO), E2 (10 nM), D and its metabolites (0.1, 1.0, and 10 μM). The amount of proteins was normalized by comparison with tubulin levels. Data are the mean ± SD of four different experiments. *p* < 0.001 was determined with Student t test with respect to the vehicle (\*) treated samples. E2: estradiol; NGB: neuroglobin; DMSO: dimethyl sulfoxide; D: daidzein; Eq: equol; O-DMA: O-desmethylangolesin; D7S: daidzein-7-sulfate; D4S: daidzein-4- -sulfate; DDS: daidzein-7,4- -disulfate.

The modulation of NGB levels by D, D4S, and Eq (1 μM, 24 h) was also confirmed in T47D cells (Figure 2). Indeed, also in these ERα-positive cells, D and D4S significantly reduced the basal level of NGB, whereas Eq, like E2, increased the globin level (Figure 2).

#### *2.2. Mechanisms of D-, D4S-, and Eq Induced Modulation of NGB Levels*

The involvement of ERα in the effects of D and its metabolites has been confirmed by pre-treating MCF-7 cells with 100 nM of the ERαinhibitor Endoxifen (Endo) before compound stimulation. As shown in Figure 3a, endoxifen pre-treatment completely impairs E2- and Eq-induced NGB up-regulation as well as D- and D4S-induced NGB down-regulation, strongly corroborating the necessity of an active ERα to modulate NGB levels. In particular, E2 rapidly down-regulates ERα levels maintaining high its phosphorylation status (Figure 3b) while neither D nor its metabolites modify the receptor levels but still increase ERα phosphorylation, although at lower level than E2 (Figure 3b). As expected, endoxifen pre-treatment completely prevents the ERα activation by all compounds considered (Figure 3b).

**Figure 2.** Effects of daidzein, daidzein-4- -sulfate and equol on neuroglobin intracellular levels in T47D cells. Western blot (left) and densitometric analyses (right) of NGB protein levels in T47D cells treated for 24 h with the vehicle (DMSO), E2 (10 nM), D (1 μM), D4S (1 μM), or Eq (1 μM). The amount of proteins was normalized by comparison with tubulin levels. Data are the mean ± SD of three different experiments. *p* < 0.001 was determined with Student t-test with respect to the vehicle (\*) treated samples. DMSO: dimethyl sulfoxide; E2: estradiol; NGB: neuroglobin; D: daidzein; D4S: daidzein-4- -sulfate; Eq: equol.

ERα activation is the first step of a signal pathway triggered by E2 to enhance NGB levels. The activation of AKT is necessary to rapidly impair NGB degradation and assure NGB gene transcription via the CREBP transcription factor [28]. On the other hand, the ability of flavonoids (i.e., naringenin) to trigger the ERα-dependent activation of p38 has been demonstrated [29]. These evidences prompted us to evaluate if D and its metabolites trigger the activation of these kinases. Figure 4 shows that, as expected, E2 elicits the rapid and persistent activation of AKT enhancing its phosphorylation status in MCF-7 cells after both 1 h and 24 h of stimulation (Figure 4a,b). On the other hand, the hormone rapidly activates p38 phosphorylation (Figure 4c), but 24 h after stimulation, the phosphorylation status of p38 return similar to the control (Figure 4d). Completely different is the effect of D and its metabolites. Indeed, both D and D4S do not activate AKT phosphorylation, but these compounds, in particular D4S, trigger the rapid and persistent activation of p38 phosphorylation (Figure 4c,d). Endoxifen pretreatment prevents the D and D4S effects as well as that of E2, although 1 h after D4S stimulation the ER inhibitor does not completely impede p38 activation (Figure 4c), suggesting that an ERα-independent mechanism is at the root of the very high p38 phosphorylation induced by this sulphate metabolite. Similarly, Eq stimulation of MCF-7 cells rapidly activates AKT phosphorylation by an ERα-independent pathway, not prevented by endoxifen pre-treatment (Figure 4a). However, the Eq-induced AKT activation is transient, and indeed the level of kinase phosphorylation was similar to the control 24 h after Eq stimulation. Like D and D4S, Eq triggers the rapid and persistent ERα-dependent p38 activation (Figure 4c,d). As a whole, these data strongly sustain that daidzein does not share similar action mechanisms with all of its metabolites, at least 1 h after treatment.

**Figure 3.** Daidzein, daidzein-4- -sulfate and equol effect on ERα activation status. (**a**) Western blot (top) and densitometric analyses (bottom) of NGB protein levels in MCF-7 cells treated for 24 h with either vehicle (DMSO) or E2 (10 nM) or D, D4S and Eq (1 μM) in presence or absence of the ERα inhibitor Endoxifen (1 μM; 30 min pretreatment). The amount of proteins was normalized by comparison with tubulin levels. Data are the mean ± SD of three different experiments. *p* < 0.001 was determined with Student's t test with respect to the vehicle (\*) or E2-treated (◦) samples. (**b**) ERα activation by daidzein, daidzein-4- -sulfate and equol. The panel represents the ERαSer118 phosphorylation status calculated as the ratio pERα/ERα). Determined by Western blot analysis in MCF-7 cells exposed for 1h to either vehicle (DMSO) or E2 (10 nM) or D, D4S and Eq (1 μM) in presence or absence of ERα inhibitor Endoxifen (1 μM; 30 min pretreatment). The nitrocellulose was stripped and then probed with anti-ERα antibody. The pERα/ERα ratio was calculated with respect to tubulin obtained by densitometric analyses of three different experiments (mean ± SD). *p* < 0.001 was determined by Student t test with respect to vehicle (\*), E2-treated (◦) or Endox-untreated samples (#). DMSO: dimethyl sulfoxide; E2: estradiol; Endox: endoxifen; ERα: estrogen receptor α; NGB: neuroglobin; D: daidzein; D4S: daidzein-4- -sulfate; Eq: equol.

#### *2.3. Physiological Outcomes of D- and D4S-Induced E2*/*ER*α/*NGB Pathway Avoidance*

We previously demonstrated that the ability of Resveratrol to impair NGB accumulation rendered cancer cells more prone to the anticancer effect of the chemotherapeutic agent paclitaxel (Pacl) [4]. This evidence prompted us to evaluate if D and D4S also exhibit this ability. As expected, Pacl treatment (100 nM) reduces NGB levels (Figure 5a–c) with the parallel increase of cleaved PARP-1 (i.e., 86 kDa band), a well-known biomarker of late apoptotic events (Figure 5d–f), and reduction of cell number (Figure 5g). Cell pre-treatment with E2 strongly prevents all Pacl effects in MCF-7 cells still enhancing NGB levels (Figure 5a–c), cell number (Figure 5g), and strongly reducing Pacl-induced PARP-1 cleavage (Figure 5d–f). Although neither D nor D4S pre-treatment affected Pacl effects, both these compounds restored Pacl effects in the presence of E2 (Figure 5). The ability of D and D4S to restore Pacl effects on cell number is also confirmed in T47D cell line (Figure 5h).

**Figure 4.** Daidzein, daidzein-4- -sulfate and equol action mechanism. The phosphorylation of the Ser473 residue of AKT (pAKT) (**a**,**b**) and Thr180/Tyr182 residues on P-38 (**c**,**d**) was determined by western blot analysis in MCF-7 cells exposed for 1 h (**a**,**c**) and 24 h (**b**,**d**) to either vehicle (DMSO) or E2 (10 nM) in presence or absence of D, D4S and Eq (1 μM). The nitrocellulose was stripped and then and then probed with anti-AKT or anti-P38 antibodies. In the panels, the pAKT/AKT (**a**,**b**) and pP38/P38 (**c**,**d**) ratios are represented. These ratios are calculated with respect to tubulin obtained by densitometric analyses of three different experiments (mean ± SD). *p* < 0.001 was determined by Student t-test with respect to vehicle (\*) or Endox-untreated (◦) samples. AKT: protein kinase B; E2: estradiol; Endox: endoxifen; ERα: estrogen receptor α; NGB: neuroglobin; p38: p38 mitogen-activated protein kinase; D: daidzein; D4S: daidzein-4- -sulfate; Eq: equol.

**Figure 5.** Physiological outcomes of D- and D4S-induced E2/ERα/NGB pathway avoidance. Western blot (left) and densitometric analyses (right) of NGB levels (**a**–**c**) and PARP-1 cleavage (**d**–**f**) in MCF-7 cells. Cells were treated with D (**a**,**e**) or D4S (**b**,**d**) (1 μM) in presence or absence of Pacl (100 nM) for 24 h, with either vehicle or E2; some Pacl treated cells were co-stimulated with either E2 or D or E2 together with D (**a**,**e**) or E2 or D4S or E2 together with D4S (**b**,**d**). (**c**,**f**) panels are densitometries that summarize the D- and D4S-induced modulation of NGB and PARP-1 cleavage respectively. The amount of protein was normalized by comparison with tubulin levels. Data are the mean ± SD of three different experiments. *p* < 0.001 was determined with Student t test with respect to the vehicle (\*), Pacl-treated (◦) samples or D- and D4S-treated samples, co-stimulated with Pacl but not with E2 (+). Effects of cellular DNA content obtained from PI assay on MCF-7 (**g**) or T47D (**h**) cells. The cells were treated for 24 h with either vehicle (DMSO) or E2 (10 nM) or Pacl (100 nM; 24 h); some samples were treated with D or D4S (1 μM) in presence or absence of Pacl and in presence of absence of E2. Data are mean ± SD of five different experiments. (\*) *p* < 0.001 was calculated with Student t test versus vehicle or Pacl-treated (◦) samples or D- and D4S-treated samples, co-stimulated with Pacl but not with E2 (+). E2: estradiol; NGB: neuroglobin; DMSO: dimethyl sulfoxide; D: daidzein; Eq: equol; D4S: daidzein-4- -sulfate; Pacl: paclitaxel.

#### *2.4. Physiological Outcomes of D in Mixture with Its Metabolites*

Due to its extensive biotransformation in the human body, D in circulation and in tissue is mainly present as a mixture with its metabolites. In order to evaluate if D maintains its anti-estrogenic actions described before, MCF-7 cells were treated with a mixture of compounds containing microbiota-produced metabolites (i.e., Eq and O-DMA, 1 μM each, gut metabolites) or metabolites produced by the gut and in liver enzymes (i.e., D7S, DDS, and D4S, 1 μM each, S metabolites) in presence or absence of D (1 μM). Figure 6a shows that the concentration of mixtures does not exert cytotoxic effects, indeed, the DNA content, and consequently the cell number, remain constant in MCF-7 cells stimulated with mixture or with the single compounds. D maintains the ability to reduce

NGB levels only in the co-stimulation with the mixture of sulphate metabolites (S metab), whereas this isoflavone effect is completely impaired by co-stimulation with the gut metabolites (Figure 6b). Notably, the mixture of S metabolites reduces NGB levels with respect to the control, while the mixture of gut metabolites increases NGB levels with respect to the control (Figure 6b). More intriguing is the effect of mixtures on Pacl-induced apoptosis (Figure 6c,d). Like the single compounds (Figure 5), neither sulphate nor gut metabolites induce the PARP cleavage at the concentration tested, however, sulphate metabolites preserve the Pacl-induced PARP-1 cleavage even in the presence of D or of E2 (Figure 6c), while gut metabolites reduce the Pacl effects even in the presence of D (Figure 6d). This latter effect is more evident in the presence of E2 (Figure 6d). As per other experiments, identical results have been obtained in T47D (data not showed), confirming that the mixture effects is not dependent on cellular context.

**Figure 6.** Physiological outcomes of D in mixture with its metabolites. (**a**) Analyses of cellular DNA content obtained from PI assay, Western blot (left) and densitometric analyses (right) of NGB levels (**b**) in MCF-7 cells. (**c**,**d**) Western blot (up) and densitometric analyses (bottom) of PARP-1 cleavage in MCF-7 cells. The MCF-7 cells were treated for 24 h with either vehicle (DMSO) or E2 (10 nM) or D, D4S or Eq (1 μM); some samples were treated with all the sulfate metabolites (D4S, D7S and DDS, 1 μM each) or all the gut metabolites (Eq and O-DMA, 1 μM each) in presence or absence of D (1 μM). Data are mean ± SD of three different experiments. (\*) *p* < 0.001 was calculated with Student t test versus vehicle in (**a**). In **b**, data are the mean ± SD of five different experiments: *p* < 0.001 was determined with Student t test with respect to the vehicle (\*) or to D-treated samples co-stimulated with metabolites (◦). In (**c**,**d**), data are the mean ± SD of three different experiments. *p* < 0.001 was determined with Student *t* test with respect to the vehicle (\*) or Pacl-treated (◦) or E2 untreated samples co-stimulated with the metabolites (+). E2: estradiol; NGB: neuroglobin; DMSO: dimethyl sulfoxide; D: daidzein; Eq: equol; O-DMA: o-desmethylangolesin; D7S: daidzein-7-sulfate; D4S: daidzein-4- -sulfate; DDS: daidzein-7,4- -disulfate; Pacl: paclitaxel.

#### **3. Discussion**

Soy-derived isoflavones consumption has been largely recommended to the Western population for their possible vital role in maintaining human health through the regulation of metabolism and body weight, concurrent to the prevention of chronic and degenerative diseases including cancer and neurodegenerative disorders. Still, their short- and long-term effects have not been fully characterized, although some have cautioned that there may be harmful effects of overconsumption, especially in cases where compounds are isolated rather than consumed in a food matrix [30,31]. To further complicate this picture, isoflavones, once consumed as either aglycone or glycosides, enter a complex pathway of biotransformation that renders almost negligible the presence of the original molecule. The relative concentration of different metabolites in both plasma and tissues is determined by the specific contribution of intestinal microbiota and by de-conjugation/conjugation processes within the human body. Nowadays, available data on the estrogenic activity of D metabolites are restricted largely to Eq, whose production depends on the individual ability to host specific intestinal bacteria [32]. Once absorbed, daidzein is efficiently re-conjugated in the gut with either glucuronic acid or sulfate. Conjugation with sulfonic acid takes place also in the liver by hepatic sulfotransferase enzymes. Therefore, the plasma level of isoflavones in people on a soy-rich diet is very low (about 1–5 μM) [5,14], while they are present in the circulation predominantly in their glucuronide and sulfate forms [33].

Nowadays, the ability of D metabolites to maintain the effects of their precursor is largely unknown. The main aim of this study was to determine whether D metabolites produced by sulfotransferase and by microbiota enzymes maintain their anticancer effects, consisting in affecting ERα activities that are important for E2-induced resistance of breast cancer cells to chemotherapeutic injury. For this purpose, we utilized two human ERα positive breast cancer cells in which the pathway E2/ERα/NGB has been previously identified as pivotal for breast cancer cell susceptibility to the chemotherapeutic agent paclitaxel [22].

Our data indicate that, unlike E2 that induced NGB overexpression, 1–10 μM D reduced NGB levels under the basal level (i.e., vehicle -treated samples) in both MCF-7 and T47D breast cancer cells. This D effect was mimicked only by the D4S metabolite that reduced NGB levels at lower concentrations than D (i.e., 0.1–1 μM); while Eq and D7S showed an E2 like behavior, increasing NGB levels in a concentration dependent manner. Surprisingly, DDS and O-DMA increased NGB levels only at very low concentrations (i.e., 0.1 μM), and were ineffective at high concentrations (10 μM for DDS and 1 μM for O-DMA, respectively).

The differences between D and its metabolites in modulating NGB levels, as well as the different concentrations necessary to obtain the effect, suggest that D and its metabolites may trigger different signal transduction pathways. D4S and Eq were selected as representatives of the two contrasting effects to determine their mechanisms. Like E2, D, D4S, and Eq trigger ERαS118 phosphorylation, even if only E2 reduces the receptor levels, an important mechanism for E2-induced cancer cell proliferation [34]. Moreover, ERα is necessary for D and its metabolites to regulate NGB levels, confirming that D and its metabolites could bind to and activate ERα, as already reported [3]. However, downstream of ERα activation, D and its metabolites trigger divergent signal pathways. Indeed, differently from E2, D and D4S do not trigger AKT activation, which is pivotal for E2-induced NGB accumulation [28]. Instead, these compounds rapidly (1 h) and persistently (24 h) activate p38 kinase, whose activation is commonly shared among flavonoids (e.g., naringenin, quercetin) [29,35]. Upon receptor binding, naringenin modifies ERα conformation driving the receptor far from the plasma membrane (i.e., receptor de-palmitoylation) and decoupling its association with the active sub-unit of PI3K, but not with p38 kinase [24,29]. Consequently, AKT is not activated, whereas the persistent activation of p38 occurs, driving cancer cells to the activation of the apoptotic cascade that culminates with PARP cleavage [29]. A similar signal transduction pathway seems to be activated by D and D4S that at the concentrations used here (1 μM) do not affect the phosphorylation status of AKT, allowing the persistent p38 activation. On the other hand, Eq rapidly and transiently activates AKT phosphorylation that even if does not impair the persistent p38 activation, as E2 does, is sufficient to

accumulate NGB into the cells. Note that the D4S-induced p38 and Eq-induced AKT phosphorylation is ERα-independent, at least partially for D4S, sustaining that these metabolites could bind to other cellular receptors, including the Arylic Receptor [36,37], which, in turn, can interfere with the estrogenic signal. As a whole, the chemical structure of D and its metabolites allows different ERα conformations that, in turn, drive cells to physiological outcomes that differ from that triggered by E2 [24,38,39].

Paclitaxel, a first line therapeutic agent for breast cancer, is a prototype of chemotherapeutic agents, which action mechanism is well known [4]. As reported above, E2/ERα-induced NGB accumulation in cancer cells represents an anti-apoptotic pathway, which abrogates the cell death induced by a chemotherapeutic agent (paclitaxel, Pacl) [4]. The ability of NGB accumulation to act as a shield against Pacl has been further confirmed here. In fact, E2 pretreatment impairs Pacl reduction of NGB as well as its ability to reduce cell number and activate PARP cleavage. Although at the selected concentrations (1 μM) they do not affect cell number or PARP cleavage, D and D4S completely prevent E2 effects, allowing the Pacl-induced activation of a pro-apoptotic cascade, even in the presence of the hormone, sustaining that the anti-estrogenic activity is pivotal for rendering cancer cells more vulnerable to the chemotherapeutic drug. The anti-proliferative action of isoflavones and other plant-derived polyphenols in cancer cells has been widely reported and disputed. Nowadays, it is quite accepted that only high concentrations of isoflavones (≤10 μM), very far from the concentration present in the plasma after a meal rich in polyphenols, could activate a mitochondrial-dependent apoptotic cascade, while low concentrations of these compounds result less active or, even, increase cancer cell proliferation [6–9]. Our data confirm that low concentrations of D and D4S are unable to trigger apoptosis or enhance Pacl effects, but acting as anti-estrogenic compounds, they can avoid the E2-induced anti-apoptotic effect on this chemotherapeutic drug.

The current study indicates, for the first time, that just D4S but no other metabolites retain the D anti-estrogenic activity. This effect is maintained when cancer cells were co-treated with D and mixtures of S metabolites, containing also D7S and DDS. On the contrary, the mixture of gut metabolites, containing Eq and O-DMA, completely impairs D effects, resulting in estrogen mimetic action. Identical results have been obtained in both MCF-7 and T47D (not completely reported), suggesting that the effect is not dependent on the cellular context. These results highlight the need to use physiologically relevant metabolites when investigating the putative beneficial properties of polyphenols against cancer.

#### **4. Materials and Methods**

#### *4.1. Reagents*

The Bradford protein assay and the chemiluminescence reagents for Western blot Clarity Western ECL Substrate were obtained from Bio-Rad Laboratories (Hercules, CA, USA). The anti-phospho-ERα (pERα Ser118) antibody and anti-phospho-AKT (pAKT Ser473) were purchased from Cell Signalling Technology Inc. (Beverly, MA, USA). The anti-α-tubulin and anti-NGB antibodies were purchased from Merck (Darmstadt, D). Specific antibodies against AKT, ERα (HC20), and poly [ADP-ribose] polymerase 1 (PARP-1) were obtained from Santa Cruz Biotechnology (Santa Cruz, CA, USA). The ERα inhibitor endoxifen was purchased from Tocris (Ballwin, MO, USA). All the other products were from Merck. Analytical and reagent grade products were used without further purification.

#### *4.2. Cell Culture and Treatment*

Human breast cancer cells MCF-7 and T47D (American Type Culture Collection, LGC Standards S.r.l., Milano, Italy) were grown in air containing 5% CO2 in either modified, phenol red free, Dulbecco's Modified Eagle's Medium (DMEM) medium. Ten percent (*v*/*v*) of charcoal-stripped fetal calf serum, L-glutamine (2 mM), gentamicin (0.1 mg/mL), and penicillin (100 U/mL) were added to the media before use. Cells were used at passage 4–8, as previously described [28]. Cell line authentication was periodically performed by the amplification of multiple short tandem repeat loci by BMR genomics

S.r.l (Padova, Italy). Cells were treated for 24 h with either vehicle (DMSO/phosphate-buffered saline, 1:10; *v*/*v*) or E2 (1 or 10 nM) or D and/or its metabolites (0.1, 1.0, and 10 μM) or Pacl (100 nM) or the metabolites mixtures. Two different metabolite mixtures were used for cell treatment, Sulphate metabolites (S metab) and Gut metabolites (Gut metab). The mixture of S metab was constituted by D4S (1 μM), D7S (1 μM) and DDS (1 μM), while that of Gut metab was constituted by Equol (1 μM) and O-DMA (1 μM). When indicated, endoxifen (1 μM) was added 30 min before compound administration, or E2 (10 nM) was added 4 h before Pacl addition (0.1, 1, and 100 nM) for 24 h. The E2 concentrations were selected on the bases of dose-response experiments already performed [40].

#### *4.3. Western Blot Assay*

Briefly, after the treatments, cells were lysed and proteins were solubilized in the YY buffer (50 mM HEPES at pH 7.5, 10% glycerol, 150 mM NaCl, 1% Triton X-100, 1 mM EDTA, and 1 mM EGTA) containing 0.70% (*w*/*v*) sodium dodecyl sulfate (SDS). Total proteins were quantified using the Bradford protein assay. Solubilized proteins (20 μg) were resolved by 7% or 15% SDS-polyacrylamide gel electrophoresis at 100 V for 1 h at 24.0 ◦C and then transferred to nitrocellulose with the Trans-Blot Turbo Transfer System (Bio-Rad) for 7 min. The nitrocellulose was treated with 5% (*w*/*v*) bovine serum albumin in 138.0 mM NaCl, 25.0 mM Tris, pH 8.0, at 24.0 ◦C for 1 h. Nitrocellulose was probed overnight at 4.0 ◦C with either anti-NGB (final dilution, 1:1000), or anti-pERα (final dilution, 1:1000), or anti-pAKT (final dilution, 1:1000), or anti p-38 (final dilution 1:1000), or anti-PARP-1 (final dilution, 1:1000) antibodies. The nitrocellulose was stripped by Restore Western Blot Stripping Buffer (Pierce Chemical, Rockford, IL) for 10 min at room temperature and then probed with either anti-ERα (final dilution, 1:1000) or anti-AKT (final dilution 1:1000) or anti-p38 (final dilution, 1:1000) or anti-α-tubulin (final dilution, 1:30,000) antibodies to normalize the protein loaded. The antibody reactivity was detected with ECL chemiluminescence Western blotting detection reagent using a ChemiDoc XRS+ Imaging System (Bio-Rad Laboratories, Hercules, CA, USA). Densitometric analyses were performed by the ImageJ software for Microsoft Windows (National Institute of Health, Bethesda, Rockville, MD, USA).

#### *4.4. Cellular DNA Content, Propidium Iodide (PI) Assay*

Cells were grown up to 80% confluence in 96-well plate and treated with the selected compounds. The cells were fixed and permeabilized with cold ethanol (EtOH) 70% for 15 min at−20 ◦C. EtOH solution were removed and the cells were incubated with PI buffer for 30 min in the dark. The solution was removed, and the cells were rinsed with PBS solution. The fluorescence was revealed (excitation wavelength: 537 nm; emission wavelength: 621 nm) with TECAN Spark 20 M multimode microplate reader (Life Science, Milano, Italy).

#### *4.5. Statistical Analysis*

The statistical analysis was performed by Student's t test to compare two sets of data by INSTAT software system for Windows. In all cases, *p* < 0.05 was considered significant.

#### **5. Conclusions**

Breast cancer, as well as lung, bronchial, and colorectal cancer, are estimated to be the three most commonly diagnosed types of malignancies. In particular, breast cancer alone accounts for 29% of all new cancers among women and the age of its onset is rapidly decreasing [41]. ERα activation status and signaling is considered one of the major drivers stimulating breast cancer proliferation, survival, and invasion [23–25]. The importance of ERα lies within its prognostic value, as it identifies patients that could benefit from the endocrine therapy [25]. Although the use of ERα antagonists has led to a considerable decline in breast cancer mortality, many patients become resistant to this therapy and developed metastatic tumors [24,41]. These observations have sparked the need for alternative approaches, increasing a sustained interest in soy isoflavones as a promising therapeutic option in

breast cancer chemoprevention or as an adjuvant for chemotherapeutic agents. These claims lead patients with increased breast cancer risk to take into consideration supplementing their diet with soy or soy derivates, assuming that a high consumption might reduce the cancer risk [30,42]. Unfortunately, the increased economic interests in soy isoflavones has not yet been paralleled by the deciphering of the cellular and molecular mechanisms underlying their potential chemo-preventive role, which remains obscure.

The data reported here strongly sustain the need to examine in deep the effect and the action mechanisms of soy isoflavone. In particular, the activity of gut microbiota should be investigated in patients before isoflavone consumption, due to its key role in the metabolism and bioavailability of isoflavones [43], microflora influencing factors also require consideration. As examples, a high-carbohydrate milieu causes more extensive biotransformation, greatly enhancing Eq formation, and a *Clostridium* sp. strain that converts D principally to O-DMA has been identified from gut microbiota. These bio-transformations could render isoflavones less active [44] and reduce the efficacy of the chemotherapeutic treatment. Moreover, concerns could arise also among healthy individuals who regularly consume soy products. Indeed, Equol and O-DMA producer individuals may be subjected to a long exposure to potent estrogenic compounds. Those who are not, on the other hand, will be mostly exposed to anti-estrogenic compounds.

**Author Contributions:** Conceptualization, M.M. and E.M.; methodology, E.M., M.C., and P.C.; formal analysis, M.M. and E.M.; investigation, E.M., M.C., and P.C.; resources, M.M and M.F.; data curation, M.M. and E.M.; writing-original draft preparation, M.M.; writing-review and editing, M.M., M.C., M.F., E.M, and P.C.; supervision and funding acquisition, M.M. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by a grant from PRIN-MIUR 2017 (Prot. 2017SNRXH3) to M.M. The grant of Excellence Department, MIUR (Legge 232/2016, Articolo 1, Comma 314–337), is gratefully acknowledged.

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

#### **References**


© 2020 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 (http://creativecommons.org/licenses/by/4.0/).

#### *Article*

## **Gigantol Targets Cancer Stem Cells and Destabilizes Tumors via the Suppression of the PI3K**/**AKT and JAK**/**STAT Pathways in Ectopic Lung Cancer Xenografts**

#### **Nattanan Losuwannarak 1,2, Arnatchai Maiuthed 1, Nakarin Kitkumthorn 3, Asada Leelahavanichkul 4, Sittiruk Roytrakul <sup>5</sup> and Pithi Chanvorachote 1,2,\***


Received: 5 November 2019; Accepted: 11 December 2019; Published: 17 December 2019

**Abstract:** Lung cancer has long been recognized as an important world heath concern due to its high incidence and death rate. The failure of treatment strategies, as well as the regrowth of the disease driven by cancer stem cells (CSCs) residing in the tumor, lead to the urgent need for a novel CSC-targeting therapy. Here, we utilized proteome alteration analysis and ectopic tumor xenografts to gain insight on how gigantol, a bibenzyl compound from orchid species, could attenuate CSCs and reduce tumor integrity. The proteomics revealed that gigantol affected several functional proteins influencing the properties of CSCs, especially cell proliferation and survival. Importantly, the PI3K/AKT/mTOR and JAK/STAT related pathways were found to be suppressed by gigantol, while the JNK signal was enhanced. The in vivo nude mice model confirmed that pretreatment of the cells with gigantol prior to a tumor becoming established could decrease the cell division and tumor maintenance. The results indicated that gigantol decreased the relative tumor weight with dramatically reduced tumor cell proliferation, as indicated by Ki-67 labeling. Although gigantol only slightly altered the epithelial-to-mesenchymal and angiogenesis statuses, the gigantol-treated group showed a dramatic loss of tumor integrity as compared with the well-grown tumor mass of the untreated control. This study reveals the effects of gigantol on tumor initiation, growth, and maintain in the scope that the cells at the first step of tumor initiation have lesser CSC property than the control untreated cells. This study reveals novel insights into the anti-tumor mechanisms of gigantol focused on CSC targeting and destabilizing tumor integrity via suppression of the PI3K/AKT/mTOR and JAK/STAT pathways. This data supports the potential of gigantol to be further developed as a drug for lung cancer.

**Keywords:** gigantol; AKT; JAK/STAT; cancer stem cell; tumor maintenance; tumor density; lung cancer; proteomics

#### **1. Introduction**

A new paradigm shift in the field of cancer cell biology is being driven by the concept of a key cancer cell population controlling the whole tumor, termed "cancer stem cells (CSCs)" [1]. CSCs from various types of cancers share a number of conservation properties, such as self-renewal ability, the generation of multiple types of differentiated cancer cells to drive tumor growth and heterogeneity, and resistance to chemotherapy via an upsurge of the DNA repair system and drug efflux transporter [2]. Therapeutic strategies targeting CSCs, including CSC direct eradication, CSC differentiation into tumor bulk cells, deletion of the supportive signals from a CSC niche, and suppression of CSC pathways, could lead to effective cancer therapy [3].

In lung adenocarcinoma, CSCs from patients were found to be less than 1.5% of the whole tumor cell population [4], but this small subpopulation was still substantial for tumorigenesis and tumor relapse [5]. The key driving pathways of CSCs, such as the PI3K/AKT/mTOR and JAK/STAT3 signals, were found to be significantly increased in cancers with high CSC properties, and hence investigations of many small molecules targeting such pathways are ongoing in clinical trials [6,7]. Protein kinase B (PKB) or AKT, which is, in fact, frequently upregulated in lung cancer plays a key role in cell survival and proliferation [8]. The activation of AKT was shown to be related with cisplatin resistance in lung cancer cells [9]. The roles of AKT on the properties of CSCs and their survival have been demonstrated in several key studies [10,11]. Likewise, signal transducer and activator of transcription 3 (STAT3) activation has been associated with poor prognosis as well as augmented CSCs [12]. A higher level of phosphorylated STAT3 (active STAT3) contributed to epithelial-to-mesenchymal transition (EMT) as well as increased CSC-like phenotypes of non-small cell lung cancer cells (NSCLCs), while the inhibition of STAT3 caused the opposite effects [13]. Instead of bulk non-CSC tumor clearance, the targeting of AKT and STAT3 is believed to be a promising anti-cancer strategy that could lead to the tumor collapse and prevention of the relapse of the disease [14,15].

Recently, natural compounds from plants have garnered increasing attention either as potential drugs or lead compounds in drug discovery research [16,17]. The key benefits of natural compounds are the abundance of plants, compound diversity, and cost effectiveness. In focusing on CSCs and tumor growth inhibition, previous studies have reported the promising activities of the bibenzyl derivative chrysotoxine in the suppression of AKT and Src [18]. In vivo studies further revealed that the bibenzyl derivative moscatilin reduced tumor volumes of lung and esophageal cancer xenografts [19,20]. Gigantol, a bibenzyl compound, is one of the polyphenolic components frequently found in traditional Chinese medicine, and has been shown to have several pharmacological effects, e.g., anti-inflammatory, amelioration of diabetic nephropathy and cataract, and anti-cancer [21–23]. The structure of gigantol consists of a bibenzyl core (Figure 1A). In vitro studies reported that gigantol triggered the apoptotic cell death of lung cancer cell lines but was not toxic to keratinocytes [24].

Our previous studies revealed several effects of noncytotoxic concentrations of gigantol on NSCLCs [25–28]. Pretreatment of 5 to 20 μM of gigantol showed a reduction of the tumor-forming capacity of NSCLCs, represented by significantly suppressing the anchorage-independent growth. In addition, with a single pretreatment of gigantol, the ability of cancer cells to form spheroids, a critical hallmark of CSCs, was abundantly suppressed [25]. These data indicated that the cancer cells had lost their self-renewal capability, which was confirmed by Western blot results showing the downregulation of octamer-binding transcription factor 4 (Oct 4) and Nanog, essential transcription factors for self-renewal and CSC-like phenotype maintenance [25]. Altogether, gigantol has the potential to attenuate tumorigenesis. However, certain information regarding the tumor growth attenuation mechanism and key evidence in animal models are still required. In this study, a subcutaneous xenograft model, as well as proteomic analysis of tumor growth regulatory pathways, were performed to help illustrate a clearer picture of how gigantol could suppress lung cancer.

#### **2. Results**

#### *2.1. Determination of Noncytotoxic Concentrations of Gigantol*

Treatment of human NSCLCs H460 with 10 to 20 μM of gigantol for 24 and 48 h had a nonsignificant effect on survival of the cells, while a significant reduction of cell survival could be first detected in response to gigantol at a concentration of 50 μM (Figure 1B). Moreover, cell viability evaluation revealed that gigantol exhibited less toxicity to human lung epithelial cells BEAS-2B as compared with lung cancer cells. Confirmation of cell death, either via apoptosis or necrosis, was detected under a fluorescent microscope after staining with Hoechst 33342 and propidium iodide (PI), as described in the Materials and Methods section. The nuclear staining results revealed that condensed and fragmented nuclei of apoptosis cells could be observed only in the cells treated with gigantol at 200 μM. It is worth indicating that treatment with gigantol at all concentrations (0 to 200 μM) caused no necrosis (Figure 1C,D). Noncytotoxic concentrations of gigantol (0 to 20 μM) were used in subsequent experiments.

#### *2.2. Functional Classification and Enrichment Analysis of the Down- and Upregulated Proteins in Gigantol-Treated Cells*

In total, 4351 proteins were identified from the control cells, while 3745 proteins were identified from the gigantol-treated cells. The protein lists from the control and gigantol-treated cells were input to a Venn diagram and 2373 proteins (54.54%) were identified as being only from the control cells, 1767 proteins (47.18%) only from the gigantol-treated cells, and 1978 proteins from both groups (Figure 2A). The protein lists that were uniquely found in the control or gigantol-treated cells were subjected to further bioinformatic analysis (the lists of proteins are in Table S1).

The down- and upregulated protein lists were categorized into three ontologies, molecular function, biological process, and cellular component using Panther software (conducted on 8 October 2019). The most overrepresented molecular functions were binding (38.3% down- and 35.6% upregulated proteins) and catalytic activity (32.0% down- and 35.6% upregulated proteins) (Figure 2B). The most overrepresented biological process categories were cellular process (31.8% down- and 32.6% upregulated proteins), and metabolic process (21.0% down- and 19.8% upregulated proteins) (Figure 2C). The most overrepresented cellular component categories were cell (39.4% down- and 40.2% upregulated proteins) and organelle (33.6% down- and 32.2% upregulated proteins) (Figure 2D).

The two protein lists were input to Enrichr software to identify the enriched biological processes associated with the down- and upregulated proteins after treating with gigantol (conducted on 8 October 2019). Enrichment terms from the Gene Ontology (GO) biological process of downregulated proteins in gigantol-treated cells are involved in macromolecule biosynthesis, DNA-templated transcription, gene expression, protein phosphorylation, cytoskeleton organization, and telomere maintenance. In contrast, enrichment biological processes of upregulated proteins in gigantol-treated cells are involved in intracellular signal transduction, protein phosphorylation, gene expression, and protein biosynthesis processes (Table 1; The full lists of the enriched biological processes of down- and upregulated proteins altered by gigantol are in Tables S2 and S3).

#### *2.3. Protein–Protein Interaction Networks of the Down- and Upregulated Proteins in Gigantol-Treated Cells*

Kinases are vital enzymes that regulate intracellular signaling. Several oncogenes and tumor suppressor genes are kinase enzymes or proteins linked to protein kinase activity. Therefore, the proteins that linked to the GO term "protein phosphorylation (GO:0006468)" obtained from Enrichr were subjected to protein-protein interaction network analysis with the Search Tool for Retrieval of Interacting Genes/Proteins (STRING) database in order to determine the significant kinase pathways affected by gigantol.


**Table 1.** First 10 ranking enrichment terms from the GO biological process of down- and upregulated proteins in gigantol-treated cells.

The 97 proteins that were downregulated and 67 proteins that were upregulated in gigantol-treated cells obtained from the GO term "protein phosphorylation (GO: 0006468)" were separately input to the STRING software (conducted on 8 October 2019). The resulting networks were presented (Figure 3A,C), and the significant nodes were determined from both the down- and upregulated protein lists. The top 10% of the downregulated proteins that had the most protein interactions were the following: MTOR, PIK3CA, JAK1, JAK2, PIK3CD, ERBB2, CHEK1, IGF1R, PTK2, ALK, and JAK3. Whereas, the top 10% of the upregulated proteins that had the most protein interactions were the following: AKT1, MAPK1, ABL1, MAPK8, CDK2, and PAK2.

The significant nodes of downregulated proteins were then analyzed for the pathways involved in CSCs using STRING, as shown in Figure 3A. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database (https://www.genome.jp/kegg/), the significant proteins that were downregulated by gigantol treatment were involved primarily in the PI3K/AKT and JAK/STAT signaling pathways (Figure 3B). These pathways were indicated as signaling pathways regulating the pluripotency of stem cells. Whereas, the significant nodes of the upregulated proteins were related to the ErbB signaling pathway, which supported the CSCs' properties (Figure 3D). Interestingly, gigantol was previously shown to potentially suppress cancer cells growth, anoikis-resistance, and cancer stemness [25–27]. Regarding the data, the downregulated kinase proteins that were affected by gigantol treatment were linked to the many well-known pathways associated with tumorigenesis and CSC maintenance.

We further confirmed that the gigantol target pathways were crucial for CSC maintenance. The list of proteins involved in CSC regulation was extracted from the KEGG pathway database, using the term "hsa04550: Signaling pathways regulating pluripotency of stem cells—Homo sapiens (human)", and mapped with our H460 proteomic profiles (conducted on 28 October 2019.). In total, 50 proteins were represented in the KEGG pathway, 12 proteins were significantly upregulated, 20 proteins were significantly downregulated, and 18 proteins were not significantly altered by gigantol (Figure 4A). Remarkably, the downregulated proteins affected by gigantol were mostly linked to the PI3K/AKT and JAK/STAT pathways (protein lists of the two pathways were obtained from KEGG pathway database "hsa04151: PI3K-AKT signaling pathway—Homo sapiens (human)" and "hsa04630: JAK-STAT signaling pathway—Homo sapiens (human)"; conducted on 28 October 2019.). Nevertheless, the levels of proteins belonging to the Wnt pathway, another pathway related to CSCs, were not significantly changed.

**Figure 2.** H460 cells were treated with 20 μM of gigantol or its vehicle (0.004% DMSO) for 24 h before the whole-cell lysates were collected. The experiment was performed in biological triplicates. (**A**) Venn diagram showing the difference in proteins expressions between the control and gigantol-treated H460 cells. Three functional classifications of the 2373 down- and 1767 upregulated proteins affected by gigantol treatment using Panther software: (**B**) molecular function, (**C**) biological process, and (**D**) cellular component.

**Figure 3.** Networks presenting the functional protein-protein interactions of the (**A**) 97 down- and (**C**) 67 upregulated proteins related to the GO term "protein phosphorylation" (GO:0006468). The significant nodes of each network are identified and rebuilt as a network of CSC linked pathways. (**B**) According to the KEGG pathways database, significant nodes of the downregulated proteins were labeled with red for the PI3K-AKT signaling pathway (hsa04151) with FDR 4.08e−13 and blue for the JAK-STAT signaling pathway (hsa04630) with false discovery rate (FDR) 2.80e−09. (**D**) Significant nodes of upregulated proteins were labeled with red for the ErbB signaling pathway (hsa04012) with FDR 1.28 <sup>×</sup> <sup>10</sup>−<sup>9</sup>

**Figure 4.** (**A**) Heatmap representing the levels of proteins associated with the signaling pathways regulating the pluripotency of stem cells in the control and gigantol-treated H460 cells (left and right columns of the heatmap, respectively). Proteins belonging to each pathway are listed to the right. (**B**) CSC markers and key kinases of AKT and STAT3 were determined by Western blotting and (**C**) the immunoblot signal intensities were quantified by densitometry. The uncropped protein bands are in Figure S2 (S2A: The protein bands from Figure 4B; S2B: The protein bands from Figure 4D). (**D**) The effects of gigantol on AKT, STATS3, and CSC markers were confirmed in two other NSCLC cell lines, A549 and H292, and (**E**) the relative protein levels were quantified. The mean data from each experiment was normalized to the GAPDH results. The experiment was performed biologically triplicated. Data represent the means ± SD (*n* = 3) \* indicates *p* < 0.05 as compared with the control group (student's *t*-test).

To confirm, the key proteins of PI3K/AKT and JAK/STAT pathways including AKT, phosphorylated Akt (S473), STAT3, phosphorylated STAT3 (S727), and CSC markers were determined by Western blot analysis using the same cell population of proteomics and xenograft experiments. The band density of active form of Akt (phosphorylated AKT) and active STAT3 (phosphorylated STAT3) was normalized with their own total forms in order to determine the levels of activation. The results showed that gigantol could inhibit the activation of AKT and STAT3. In addition, the CSC makers (CD133 and ALHD1A1) were found to be significantly reduced in response to gigantol treatment (Figure 4B,C). Moreover, the effect of gigantol on PI3K/AKT, JAK/STAT, and CSC markers was confirmed in other NSCLC cells (A549 and H292 cells) (Figure 4D,E). It was quite clear that the PI3K/AKT and JAK/STAT signaling pathways were the target pathways of gigantol on CSC maintenance in NSCLCs. It was possible that gigantol could show some effects on tumor formation and its integrity in vivo by means of CSC suppression.

#### *2.4. Gigantol Negatively Regulates Tumor Cell Growth in Vivo*

The concept of the in vivo xenograft was to compare the ability to form and maintain a tumor between the untreated control and gigantol-treated H460 cells. This experiment revealed the effects of gigantol on the cancer cells whether the CSC or other survival signals were suppressed by the treatment at the time of inoculation. The pretreatment procedure excluded the direct anticancer effect of the compound on the tumor cell after mice implantation.

After injection of lung cancer cells into two flanks of each mouse, most mice generated palpable tumors on day seven and most control tumors had reached their endpoint size on day 13. Figure 5A demonstrates that every mouse had a similar growth rate (indicated by body weight) in a normal range. The results showed that most gigantol-treated tumors were lighter than their paired control tumors (Figure 5B,C). However, the average weights of the tumors were only slightly different (control group mean = 966 ± 154.4 mg, gigantol group mean = 698 ± 154.5 mg, *n* = 5, *p* = 0.255, Student's *t*-test). Tumor growth rates varied between the mice, but the mean tumor growth rates of the control and gigantol groups were not different (Figure 5D,E). The dissected tumor densities were compared, and the results showed that the gigantol groups had lower tumor densities than their paired untreated controls (Figure 5F).

#### *2.5. Histological Observation Showed Lower Viable Tumor Areas in the Gigantol-Treated Tumors*

Having shown that gigantol pretreatment caused tumors with a lesser density as compared with the untreated control, we wish to emphasize this phenomenon as previous studies have indicated that changes in tumor density, as indicated by CT imaging showing a loss of tumor mass, can be a potential assessment for anti-cancer drug action [29,30]. Cross-section slices of the tumors were co-stained by hematoxylin and eosin (H&E), and, then, were photographed. The macro-morphology of the tumor structure was similar among all the tumors (small nodules packed within a tumor lobe, surrounded with fibrous tissues), whereas the percentage of intact and non-viable tumor cells of the two groups were dramatically different. Figure 6 demonstrates that while the control tumors exhibited a dense viable tumor mass, the gigantol tumors showed a substantial loss of tumor mass, as indicated by a hollowing with the magenta staining of cells or pale pink cells without nuclear staining.

#### *2.6. Gigantol Suppresses Tumor Cells Proliferation but not Tumor Vasculature.*

Two pairs of tumors were selected for Ki-67 and α-smooth muscle actin (α-SMA) immunohistochemistry (IHC) staining. The hot spots and cold spots of Ki-67 positive cells are shown in Figure 7A. The mean percentage of Ki-67 positive cells of the control group was 62.45 ± 0.3951 and that of the gigantol-treated group was 49.49 ± 0.7348 (*p*-value = 0.0041, Student's *t*-test, *n* = 2, Figure 7B).

The α-SMA signals from cancer cells in all tumors were so low that they could not be scored (Figure 7C). This result indicated that both the control and gigantol groups had a low level of mesenchymal-like phenotypes. Figure 7D presents mature vessels covered by pericytes. The number of vessels per area detected by α-SMA staining was similar in all the tumors.

**Figure 5.** (**A**) Graph showing mice body weights starting at the day of cancer cell inoculation. There was no significant change of the body weights until the day of termination. (**B**) Untreated (upper row) and gigantol-treated (lower row) tumors were dissected and photographed at day 13 after inoculation. Scale bars represent 10 mm in length. (**C**) Graph showing grouped means of the control and gigantol tumor weights. The 5 different markers represent each pair of tumors. The gigantol-treated tumors had lower tumor weights as compared with their own control tumors, except for mouse 3. (**D**) Graph presenting the mean growth rate of the control and gigantol groups. (**E**) Four graphs demonstrating the individual tumor growth rate of each mouse (tumor growth of mouse 5 could not be accomplished because the gigantol-treated tumor was not palpable and measured until the day of termination). (**F**) Tumor density was calculated as weight by volume. The horizon lines represent means of each group.

**Figure 6.** Hematoxylin and eosin staining showing intratumor morphology (20×). Percentages of necrotic areas as compared with their total areas are shown at the lower-right edge of each picture. Scale bars at the lower-left edge of each picture represent 500 μm lengths.

**Figure 7.** (**A**) Immunohistochemistry (IHC) staining demonstrating 200-fold magnified pictures of hot spots and cold spots from the control and gigantol-treated tumors. The percentages of Ki-67 positive cells as compared with total cells are displayed under their pictures. (**B**) Graph showing the means of %Ki-67 positive cells. The gigantol-treated tumors have lower Ki-67 positive cells than the control tumors. \* indicates *p* < 0.05 as compared with the control group (Student's *t*-test). (**C**) α-SMA IHC staining of cancer cells in both edge and center areas of tumors showing no difference of signal levels (200×). The numbers of mature tumor vessels per areas between the control and gigantol groups were not different. (**D**) Pictures showing vessel distribution among the tumor mass (100×). Arrow indicates a vessel (400×).

#### **3. Discussion**

According to the increasing trend of cancer incidence and mortality, the development of novel anti-cancer therapies is highly needed. Among malignant tumors, lung cancer has been shown to be the main cause of cancer-related mortality and treatment failure [31], leading to the requirement for effective therapeutic options. Previous studies have reported the potential anti-cancer activities of gigantol, one of the most widely studied bibenzyls. Gigantol has exhibited cytotoxicity against various types of cancer cells, such as breast, liver, and lung cancer cells [24,32,33]. Moreover, gigantol could attenuate certain aggressive phenotypes that bring about tumor progression and metastasis, including proliferation, migration, invasion, anoikis-resistance, and anchorage-independent growth [25–28].

Proteomics analysis (Figure S1).demonstrated that PI3K/AKT/mTOR and JAK/STAT were among the most affected proteins in response to gigantol treatment. The key kinases belonging to the PI3K/AKT/mTOR axis, including phosphoinositide 3-kinases (PI3Ks, α and δ isoforms) and mammalian target of rapamycin (mTOR), were significantly decreased in the gigantol-treated cells (Figure 3A,B). Both isoforms of PI3K can activate phosphatidylinositol (3,4,5)-trisphosphate (PIP3), an upstream activator of AKT [34]. In addition, PI3K can trigger an AKT-independent mechanism, which transduces signals through serine/threonine-protein kinase Sgk3 (SGK3) and mTOR complex 2 (mTORC2) [35]. Consistently, our proteomic results showed the suppression of key proteins of the PI3K-mediated AKT-independent pathway, such as PIK3CA, PIK3CD, SGK3, MTOR, and RICTOR, which were simultaneously downregulated (Table S1).

Janus kinase 1 and 2 (JAK1 and JAK2) are transducers of the heteromeric receptors of interleukin 6 and 10 (IL-6 and IL-10), which activate signal transducer and activator of transcription 3 (STAT3). STAT3 was shown to mediate cancer cell survival, proliferation, angiogenesis, and metastasis, as well as maintaining the CSC phenotypes [7,36]. Although the STAT3 protein could not be detected in our proteomic profiles due to its low abundance, its downstream target genes, including cyclin D1 and c-Myc, were downregulated [12] (Table S1). JAK3 is an upstream regulator of STAT5 and STAT6. An accumulating data exercise revealed that inhibition of the JAK3 signaling could reduce cancer progression [37]. It is possible that the suppression of JAK/STAT signaling by gigantol should attenuate CSC in lung cancer. In addition, the mitogen-activated protein kinase 8 (MAPK8) or c-Jun N-terminal kinase (JNK) protein level was found to be induced by gigantol treatment (Figure 3D). JNK plays a role in controlling cancer cell death. The activation of JNK is necessary for intrinsic and extrinsic apoptosis, and autophagic cell death [38]. JNK signaling has been reported as a vital molecular mechanism of many anti-cancer-agents-induced cancer cell death and inactivation of such a protein led to cancer cell resistance to death stimuli [39,40]. An early upregulation of JNK by gigantol before the cancer cells encountered the stressful conditions in the tumor possibly led to stress induced JNK hyperactivation, which subsequently promoted the expression of proapoptotic proteins [38].

Recent evidence has suggested that CSCs functions as a seed of tumors. Not only do the CSCs use their ability of self-renewal and differentiation for tumor establishing, but also implicate cancer progression, metastasis, and disease relapse [1]. Regarding this matter, our previous work unraveled new information that gigantol could suppress CSC activity and discontinue their role in maintaining tumor [2,41]. This finding is quite in agreement with the previous study indicating that CSCs play a key role in tumor maintenance. This study revealed the effect of gigantol of PI3K/AKT and JAK/STAT3 suppression on the tumor initiation, growth, and maintenance based on the concept that the cells at the first step of tumor initiation had lesser CSC property than the control untreated cells.

In this study, the lung cancer cells were treated with a noncytotoxic concentration of gigantol prior to inoculation into mice subcutaneous skins. The same populations of gigantol-treated cells were subjected to proteomics. This experimental design displays the clear mechanism of gigantol treatment in attenuation of the CSC-supportive PI3K/AKT/mTOR and JAK/STAT3 signals at the time of tumor initiation. Although this experiment used only a single treatment with low dose, gigantol could inhibit the tumor growth rate (Figure 5E). Tumors from the gigantol-pretreated cells had lower weights and densities (Figure 5C,F). Furthermore, the histological tumor integrity was determined. Previous studies have either demonstrated or proposed that the tumor density can be a promising assessment of anti-cancer drug evaluation as they have given more accuracy on the assessment of an anti-cancer drug response and have contributed to better treatment outcomes [29,30,42]. We observed the cross-sectional histology of the tumors to assess the integrity of intact cell viable areas as compared with the cell death areas as recommended in the guideline [43]. Interestingly, our results indicated that most of the gigantol-treated tumors had a dramatic loss of tumor mass as compared with those of the untreated controls (Figure 6). Consistently, the intratumor structure and tumor phenotype of Ki-67 labeling showed that the gigantol-treated tumors had lower proliferative cancer cells (Figure 7A,B). However, we found that the EMT properties of cancer cells observed by α-SMA staining was not altered by treatment with gigantol (Figure 7C). Also, the angiogenic capability of both groups of tumors was not different (Figure 7D). The phenotypic observation revealed that the pretreatment with gigantol did not have an effect on tumor neoangiogenesis. Further investigation on gigantol-mediated stromal cell-induced angiogenesis is thus suggested.

This study was designed in a manner of a pharmacological study that minimized the confounding factors in the system and focused on the effect of gigantol on the cancer cells. We could assume from the results that gigantol treatment altered the tumor-promoting activities of the cells prior to the process of tumor inoculation and such alteration attenuated the ability of the cancer cell to grow and maintain a tumor, resulting in a reduced tumor mass with viable cancer cell loss. Although our results helped us scope the direct action of the compound on NSCLCs, further investigation is necessary, including the injection of the substance into a tumor or animal after tumor formation to gain more insights.

#### **4. Materials and Methods**

#### *4.1. Cell Line Cultures*

Human NSCLC H460 and normal bronchus epithelial cell BEAS-2B lines were purchased from the American Type Culture Collection (Manassas, VA, USA) and were cultured in Roswell Park Memorial Institute (RPMI) 1640 medium and Dulbecco's modified Eagle medium (DMEM), respectively, supplemented with 10% fetal bovine serum, 2 mM L-glutamine, and 100 units/mL each of penicillin and streptomycin in a humidified atmosphere with 5% CO2 at 37 ◦C.

#### *4.2. Animals*

Six-week old male BALB/cAJcl nude mice were purchased from Nomura Siam International (Samut Prakan, Thailand). Five mice were maintained in one cage under strictly hygiene housing with controlled temperature (23 ± 2 ◦C) and light/dark cycle (12 h light/12 h dark) at the Animal House of Faculty of Medicine, Chulalongkorn University. The study was approved by the Institutional Animal Care and Use Committee of the Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand (ethical reference number CULAC 001/2561). Animal welfare and experimental procedures were strictly carried out in accordance with The Eighth Edition of the Guide for the Care and Use of Laboratory Animals (NRC 2011) [44]. All efforts were made to minimize animals' suffering and to reduce the number of animals used.

#### *4.3. Chemicals and Reagents*

Gigantol was extracted from stems of Dendrobium draconis Rchb.f., as previously described [45] and dissolved in dimethylsulfoxide (DMSO) at the indicated working concentrations. 3-(4,5-Dimethylthiazol-2-yl) 2,5-diphenyltetrazolium bromide (MTT), Hoechst 33342, propidium iodide (PI), bovine serum albumin (BSA), dimethyl sulfoxide (DMSO), cocktail protease inhibitor, hematoxylin, and eosin were purchased from Sigma chemical, Inc. (Chemical Express, Bangkok, Thailand). RPMI-1640 medium, DMEM, phosphate buffer saline (PBS), glutamine, penicillin, and streptomycin were purchased from Gibco company (Gibthai, Bangkok, Thailand). Primary antibodies against CD133, ALDH1A1, total AKT, phosphorylated AKT (Ser473), total STAT3, phosphorylated STAT3

(Ser727), and GAPDH, horseradish peroxidase labeled secondary antibodies, and RIPA lysis buffer were purchase from Cell Signaling Technology (Theera Trading, Bangkok, Thailand). Pentobarbital sodium injection was purchased from Ceva Sante Animal (VET AGRITECH, Nonthaburi, Thailand). 3,3- -Diaminobenzidine tetrahydrochloride hydrate was purchased from TCI Co., LTD (Chemical Express, Bangkok, Thailand). Primary antibodies of Ki-67 and α-SMA and matched secondary antibodies were purchased from DAKO (Medicare Supply, Bangkok, Thailand).

#### *4.4. Cell Viability Assay*

In order to elucidate the possible tumor suppression activity of gigantol, first, we selected the concentrations of the compound that caused no toxicity to the cancer cells. Cell viability was determined by plating cells at a density of 10,000 cells per well in 96-well plates. The cells were allowed to adhere overnight, medium was removed, and medium with various concentrations of gigantol (0 to 200 μM) or 0.1% DMSO was added. After 24 to 48 h of treatment, the number of viable cells were measured with the use of MTT assay. Medium was aspirated and 0.4 mg/mL of MTT in PBS was added to each well. The plate was then incubated at 37 ◦C, 5% CO2 for 3 h. Afterwards, the resulting formazan crystal was dissolved in 100 μL of DMSO and subjected to a 570 nm absorbance reading via a microplate reader (ClarioStar, BMG Labtech, Germany). The assay was performed biological triplicate.

#### *4.5. Cell Death Determination Assay*

Nuclear co-staining with Hoechst 33342 and propidium iodide (PI) was used to determine apoptotic and necrotic cell death. Cells were treated with gigantol as described in cell viability assay. Then, cells were incubated with 10 μM of Hoechst 33342 and 5 μM PI for 30 min at 37 ◦C. Cells were visualized and imaged under a fluorescence microscope (Nikon eclipse Ts2 with Nikon DS Fi3 camera). Apoptotic cell could be detected by Hoechst 33342 nuclear staining, showing condensed nucleus and fragmented nuclei of apoptotic bodies. Necrotic cell could be detected by PI staining.

#### *4.6. Sample Preparation*

H460 cells were treated with 20 μM gigantol or 0.01% DMSO (vehicle) for 24 h. The cells were lysed with 0.5% SDS. Total protein amount collected from each sample was measured with Lowry assay with bovine serum albumin as a standard [46]. Equal protein amount from 3 independent biological samples were pooled. Fifty micrograms of protein from control or gigantol treated cells were subjected to in-solution digestion. Samples were completely dissolved in 10 mM ammonium bicarbonate (AMBIC), reduced disulfide bonds using 5 mM dithiothreitol (DTT) in 10 mM AMBIC at 60 ◦C for 1 h and alkylation of sulfhydryl groups by using 15 mM Iodoacetamide (IAA) in 10 mM AMBIC, at room temperature for 45 min in the dark. For digestion, samples were mixed with 50 ng/μL of sequencing grade trypsin (1:20 ratio) (Promega, Walldorf, Germany) and incubated at 37 ◦C overnight. Prior to LC-MS/MS analysis, the digested samples must be dried and protonated with 0.1% formic acid before injection into LC-MS/MS.

#### *4.7. Liquid Chromatography-Tandem Mass Spectrometry (LC-MS*/*MS)*

The LC-MS/MS was used to determine the quantification of the peptides from the digested samples. The tryptic peptide samples were prepared for injection into an Ultimate3000 Nano/Capillary LC System (Thermo Scientific, Gloucester, UK) coupled to a Hybrid quadrupole Q-Tof impact II™ (Bruker Daltonics, Coventry, UK) equipped with a Nano-captive spray ion source. Briefly, peptides were enriched on a μ-Precolumn 300 μm i.d. × 5 mm C18 Pepmap 100, 5 μm, 100 A (Thermo Scientific, UK), separated on a 75 μm I.D. × 15 cm and packed with Acclaim PepMap RSLC C18, 2 μm, 100Å, nanoViper (Thermo Scientific, UK). Solvent A and B containing 0.1% formic acid in water and 0.1% formic acid in 80% acetonitrile, respectively, were supplied on the analytical column. A gradient of 5% to 55% solvent B was used to elute the peptides at a constant flow rate of 0.30 μL/min for 30 min. Electrospray ionization was carried out at 1.6 kV using the CaptiveSpray. Mass spectra (MS) and

MS/MS spectra were obtained in the positive-ion mode over the range (m/z) 150–2200 (Compass 1.9 software, Bruker Daltonics).

#### *4.8. Bioinformatics and Data Analysis*

MaxQuant 1.6.6.0 was used to quantify the proteins in individual samples using the Andromeda search engine to correlate MS/MS spectra to the Uniprot Homo sapiens database [47]. The following parameters were used for data processing: maximum of two miss cleavages, mass tolerance of 20 ppm for main search, trypsin as digesting enzyme, carbamidomethylation of cysteine as fixed modification, and the oxidation of methionine and acetylation of the protein N-terminus as variable modifications. Only peptides with a minimum of 7 amino acids, as well as at least one unique peptide, were required for protein identification. Only proteins with at least two peptides, and at least one unique peptide, were considered as being identified and used for further data analysis.

The gene list enrichment analysis was conducted using Enrichr software (https://amp.pharm. mssm.edu/Enrichr/) [48]. Protein organization and biological action was investigated conforming to protein analysis through evolutionary relationships (Panther software; http://pantherdb.org/) protein classification [49]. A Venn diagram (analyzed by jVenn software; http://jvenn.toulouse.inra.fr/app/ index.html) was used to show the differences between protein lists originating from different differential analyses [50]. The Search Tool for Retrieval of Interacting Genes/Proteins (STRING) software version 11 (https://string-db.org/cgi/input.pl) was used to analyze the common and the forecasted functional interaction networks between identified proteins [51]. Cytoscape 3.7.2 (https://cytoscape.org/) was utilized to analyze the significant nodes from protein–protein interaction networks [52]. The significant nodes analysis was modified from Rezaei-Tavirani (2017) [53]. The degree values, which were determined by an amount of interacted proteins with the node, were analyzed and the top 10% of the nodes based on degree value were selected as significant nodes. The heatmap visualization and statistical analyses were conducted using the MultiExperiment Viewer (MeV) in the TM4 suite software (http://mev.tm4.org/#/welcome) [54].

#### *4.9. Western Blot Analysis*

Cells were lysed with RIPA lysis buffer containing 20 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1 mM Na2EDTA, 1 mM EGTA, 1% NP-40, 1% sodium deoxycholate, 2.5 mM sodium pyrophosphate, 1 mM beta-glycerophosphate, 1 mM Na3VO4, 1 μg/mL leupeptin, and cocktail protease inhibitor mixture for 30 minutes on ice. The protein contents of the cell lysates were evaluated by Lowry assay. Samples with equal amounts of protein (60 μg) were run in the SDS-PAGE before they were transferred onto 0.45 mm nitrocellulose membranes (Bio-Rad, Hercules, California, United States). Transferred membranes were blocked for 1 h in 5% non-fat dry milk in Tris-buffered saline with Tween 20 (25mM Tris-HCl, pH 7.5, 125 mM NaCl, and 0.05% Tween 20) and incubated overnight with specific primary antibodies against CD133, ALDH1A1, total AKT, phosphorylated AKT (Ser473), total STAT3, phosphorylated STAT3 (Ser727), and GAPDH. Membranes were washed three times with Tris-buffered saline with Tween 20 and incubated with appropriate horseradish peroxidase labeled secondary antibodies for 2 h at room temperature. The immune complexes were detected by Clarity and Clarity Max ECL Western Blotting Substrates (Bio-Rad) and imaged with ImageQuant LAS 4000 biomolecular imager (GE Healthcare, Chicago, Illinois, United States).

#### *4.10. Subcutaneous Tumor Xenograft Procedure*

The scheme of experimental design is shown in Figure 8. The human NSCLCs were prepared prior to the tumor establishment. The H460 cells were cultured in medium with 20 μM of gigantol or vehicle for 48 h (5 individual sets of cancer cell cultures). Then, the 70% confluent monolayer lung cancer cells were trypsinized, suspended in Hank's saline buffer solution and counted by TC20 automated cell counter (Bio-Rad). Each cell suspension was adjusted to a concentration of viable 5 × 106 cells per 100 μL. The cancer cell suspensions were kept on ice and rapidly transferred to an in vivo subcutaneous xenograft operation.

**Figure 8.** Scheme showing the in vivo experimental procedures.

To minimize variation between animal bodies, one mouse was assigned to bear both control and its paired gigantol-treated tumor. One flank of a mouse was inoculated subcutaneously with viable 5 × 106 cells of untreated cells and another flank with gigantol pretreated cells. Mice were weighed, and the tumors were observed every 2 days. When a tumor was palpable, the mouse would be observed daily. Vernier Caliper was used to measure the most length and its own orthogonal most width of each tumor. Tumor volumes were calculated by the formula (length × width × width)/2. Tumor growth rates were verified by means of plotting calculated tumor volumes by days. Mice were not exposed to gigantol throughout the experiment. Once control or treatment tumor reached its endpoint size (20 mm in diameter), the tumor-bearing mouse was euthanized by intraperitoneal injection of pentobarbital sodium solution (>150 mg/kg) [55] and then the tumors were dissected, washed with ice-cold PBS, weighed, and photographed with a ruler. The tumors were weighed and immediately fixed with 4% paraformaldehyde for 24 h. Tumors were embedded in paraffin blocks, sliced and stained with hematoxylin and eosin (H&E) for further histologic observation. Necrotic and total areas of tumor slices were determined using ImageJ software [56].

#### *4.11. Immunohistochemistry Staining of Ki-67 and* α*-SMA*

Two pairs of tumor slides were selected for staining with Ki-67 (dilution 1:300) and α-smooth muscle actin (α-SMA, dilution 1:100) antibodies and, then, were visualized by incubation with 3,3- -diaminobenzidine. Slides were observed under a brightfield microscope (Nikon eclipse E600 with Nikon DXM1200F camera).

The level of Ki-67 assessment was modified from Jang (2017) [57]. Areas with the highest (hot spot) and the lowest (cold spot) numbers of positive cells (indicated by dark brown staining in nucleus) were selected and the percentages of the positive cells as compared with total cells were calculated. Averages of %Ki-67 positive cells were calculated from the summed total and Ki-67 positive cells from all hot spots and cold spots of the two mice.

α-SMA, a marker of mesenchymal phenotype, was used to detect cancer cells with EMT-like phenotype, endothelial cells, and vascular pericytes [58]. For angiogenesis determination, edge and center areas of each tumor were selected and the number of mature blood vessels (indicated by circular lining of cells labeled with high signal of α-SMA) were counted.

#### *4.12. Statistical Analysis*

One-way analysis of variance (one-way ANOVA) and student's *t*-test were performed to conduct statistical analysis (GraphPad Prism 7.0). Data were expressed as mean ± standard deviation (SD) and values of *p* < 0.05 were indicative of significant differences.

#### **5. Conclusions**

Data from this study demonstrated that pretreatment with gigantol can suppress tumor growth, reduce tumor density, and attenuate the tumor maintenance of NSCLCs. This information can benefit and encourage further investigation of this useful compound to be used for anti-cancer approaches.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2072-6694/11/12/2032/s1, Figure S1: The workflow for proteomics analysis, Figure S2: The uncropped images of Western blot bands, Table S1: The lists of proteins which were downregulated, upregulated, and not significantly altered by the effects of gigantol, Table S2: GO biological process enrichment analysis results of the significantly downregulated proteins from Enrichr software, Table S3: GO biological process enrichment analysis results of the significantly upregulated proteins from Enrichr software.

**Author Contributions:** Conceptualization, P.C.; data curation, N.L. and P.C.; formal analysis, N.L., N.K., and S.R.; funding acquisition, P.C.; investigation, N.L.; methodology, P.C., N.L., and A.M.; project administration, P.C.; resources, P.C., S.R., and A.L.; supervision, P.C., S.R., and A.L.; validation, N.L., A.M., N.K., and P.C.; visualization, N.L.; writing—original draft, P.C. and N.L.; writing—review and editing, P.C. and N.L.

**Funding:** This work was supported by a grant from the Thailand Research Fund (grant number RSA6180036).

**Acknowledgments:** The authors would like to thank Boonchoo Sritularak for offering orchid extract, Yodying Yingchutrakul for LC-MS/MS technical support, and Panomwat Amornphimoltham for in vivo experiment support. In addition, the authors would like to acknowledge the Pharmaceutical Research Instrument Center, Faculty of Pharmaceutical Sciences, Chulalongkorn University for providing equipment.

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

#### **References**


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