Naringenin Attenuates Metabolic Disturbances in C-26 Cancer Cachexia Mouse Model

Naringenin Attenuates Metabolic Disturbances in C-26 Cancer Cachexia Mouse Model:

Transitional Study for Human Application

Thesis

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in

the Graduate School of The Ohio State University

Yuko Nishikawa

Graduate Program in Food Science and Technology

The Ohio State University

2019

Thesis Committee

Dr. Yael Vodovotz, Advisor

Dr. Martha A. Belury, Co-Advisor

Dr. Steven K. Clinton

Dr. Christopher Simons

Copyrighted by

Yuko Nishikawa

2019

Abstract

Cancer cachexia is a wasting disease which leads to poor disease prognosis and survival. Cachexia affects about 80% of advanced cancer patients and causes up to one- third of all cancer-related deaths. To date, effective treatment that directly targets cancer cachexia to improve longevity and quality of life is lacking. Metabolic disturbance is the underlying driver of the pathogenesis and progression of cancer cachexia. Common observations in cancer patients presenting cachexia include elevated inflammation, insulin resistance, dyslipidemia, and increased energy expenditure resulting in body weight loss that is irreversible by nutrition therapies. The use of metabolic modulators to improve these metabolic disturbances in some studies successfully slowed cachexia development, suggesting the importance of metabolic regulation in cancer cachexia treatment.

Naringenin is a flavonoid found primarily in citrus fruits. Stemming from several epidemiological findings of the inverse associations of consumption of naringenin- containing foods and cancer incidence, a number of studies have explored anticancer activities and other bioactivities of naringenin. Naringenin has shown anti-cancer properties in many human cell lines and has successfully improved the inflammatory status, insulin tolerance, plasma glucose, and lipid profiles in mice. The results of some ii animal studies have suggested that naringenin supplementation during weight loss may help maintain lean body mass while regulating diet-induced metabolic disturbances.

These observations have pointed to the potential use of naringenin to combat cachexia, a disease of metabolic disturbance, in cancer population by attenuation of tumor growth and metabolic disturbances, as well as the protection of the lean body mass.

The first objective of this study was to determine the effect of dietary naringenin on the well-established C-26 cancer cachexia mouse model. We hypothesized that two- percent dietary naringenin would improve the metabolic disturbances in the C-26 model, slowing the progression of cachexia symptoms. Male CD2F1 mice were provided with either a control diet or a two percent naringenin diet, and each diet group was divided into a tumor and a no-tumor group. To our surprise, naringenin fed tumor mice exhibited weight loss and anorexia earlier than the control diet tumor mice. However, the early onset of anorexia and weight loss was not a predictor of worse outcomes in this study, since naringenin improved the inflammatory status, insulin sensitivity, activity, muscle function, and survival. These results confirmed naringenin's positive metabolism- regulating effects and its favorable impact on the outcomes of disease in the C-26 model.

The second objective was to begin to provide a method for translation of the beneficial health effects of naringenin suggested by animal studies to human application.

Although the first part of the study observed positive effects of naringenin on metabolic regulation, the concentration of naringenin used in our C-26 study was not directly translatable to the quantity that a human can achieve by consuming regular naringenin- containing foods. We hypothesized that the use of lyophilized naringenin-rich grapefruit

iii juice and cyclodextrin in a confection would improve the naringenin bioavailability and increase its concentration. Cyclodextrin is a cyclic compound that has the ability to surround a hydrophobic, poorly soluble compound inside its cavity. By doing so, cyclodextrin encapsulation can improve the solubility and the bioavailability of naringenin. Since there is no universal food-safe complexation method for naringenin and

β-cyclodextrin, two different methods were tested to encapsulate naringenin and naringin: the stirring method and the kneading method. The analyses of complexation efficiency by differential scanning calorimetry (DSC) and proton nuclear magnetic resonance (H-

NMR) revealed that the stirring method was more efficient for the complexation of β- cyclodextrin with both naringin and naringenin.

As a preliminary study for the future bioavailability tests, mice were fed with four different types of confections (sucrose, grapefruit confection (GFC), GFC with three percent naringenin, GFC with naringin equivalent to three percent naringenin) after a 12- hour fast and monitored for 2.5 hours. None of the mice finished consuming 1.6 grams of confection in 2.5 hours, and voluntary ingestion of the confection was found to be not suitable for a bioavailability studies, suggesting the need to oral gavage mice or to utilize a larger animal model.

Acknowledgments

I would like to thank my advisor, Dr. Vodovotz for allowing me to join such an exciting research environment, further allowing me to explore the area of my interest, and providing me with the opportunity to connect with researchers in other fields by introducing me to the Belury lab. I would also like to thank former and current Vodovotz lab members and officemates for giving me opportunities to learn important life skills. I would also like to express sincere gratitude to Dr. Belury for guiding me through the last half of my academic life as a master’s student in the nutrition field. I want to thank

Deena, Austin, Rachel, Taylor, and other Belury lab members for sparing their precious time to help me with this study and for providing me with emotional support. I am grateful to the other members of my committee, Dr. Clinton and Dr. Simons, for giving me the motivation to challenge myself academically with their expertise.

Support from Wes, Amanda, Emily, and my mentor, Dr. Parkin, has helped me propel through my academic life by restoring my energy and fueling my passion for food science.

Vita

2008………………………………………… B.A. Arts and Science, Kwansei Gakuin

University, Hyogo, Japan

2009 to 2013………………………………… School Teacher, Hyogo Prefectural Board

of Education, Hyogo, Japan

2017…………………………………………. B.S. Food Science, University of

Wisconsin-Madison, Madison, WI

2017 to Present………………………………. Graduate Research Associate, Department

of Food Science and Technology, The

Ohio State University, Columbus OH

Fields of Study

Major Field: Food Science and Technology

Table of Contents

Abstract ...... ii Acknowledgments...... v Vita ...... vi Table of Contents ...... vii List of Tables ...... x List of Figures ...... xi Chapter 1. Literature Review ...... 1 1.1 Cancer Cachexia ...... 1 1.1.1 Definition, Prevalence, and Impact of Cancer Cachexia ...... 1 1.1.2 Metabolic Disturbance and Cancer Cachexia ...... 3 1.1.3 Multi-organ Symptoms of Cancer Cachexia and Brain Function ...... 11 1.1.4 Suggested Mechanisms of Muscle Wasting in Cancer Cachexia ...... 15 1.1.5 Traditional Treatment for Cancer Cachexia ...... 19 1.1.6 C-26 Mouse Model for Human Cancer Cachexia Study ...... 23 1.2 Naringenin ...... 27 1.2.1 Flavonoids and Bioactivities ...... 27 1.2.2 Food Sources of Naringenin ...... 32 1.2.3 Metabolism and Bioavailability of Naringenin Species ...... 33 1.2.4 Naringenin and Inflammation ...... 35 1.2.5 Naringenin and Glucose Metabolism...... 36 1.2.6 Naringenin and Lipid Metabolism ...... 37 1.2.7 Naringenin and Energy Expenditure ...... 38 1.2.8 Naringenin and Brain Functions ...... 38 1.2.9 Naringenin and Cancer ...... 40 1.3 Cyclodextrin ...... 42 vii

1.3.1 Cyclodextrin Chemistry and Applications ...... 42 1.3.2 Cyclodextrin Complexation Methods ...... 46 1.3.3 Methods of Complexation Verification ...... 49 Chapter 2. Naringenin Attenuates Metabolic Disturbances in C-26 Cachexia Model ..... 51 2.1 Abstract ...... 51 2.2 Introduction ...... 52 2.3 Materials and Methods ...... 53 2.3.1 Colon-26 Adenocarcinoma Cell Culture ...... 53 2.3.2 Animals, Diets and Experimental Procedures ...... 54 2.3.3 Body Weight and Food Intake ...... 57 2.3.4 EchoMRI ...... 57 2.3.5 Grip Strength ...... 57 2.3.6 Insulin Tolerance Test...... 57 2.3.7 Necropsy ...... 58 2.3.8 Plasma Analysis ...... 58 2.3.9 Statistical Analysis ...... 58 2.4 Results ...... 59 2.4.1. Effects of Tumor and Dietary Naringenin on Body Weight and Food Intake 59 2.4.2. Effects of Tumor and Dietary Naringenin on Body Composition ...... 61 2.4.3. Grip Strength ...... 63 2.4.4. Effects of Tumor and Naringenin on Insulin Tolerance ...... 64 2.4.5. Effects of Tumor and Dietary Naringenin on Tissue Weights ...... 65 2.4.6. Effects of Tumor and Dietary Naringenin on Plasma IL-6 and Adiponectin 67 2.5 Discussion ...... 68 Chapter 3. Transition Study: Confection Application of Naringenin to Target Human Metabolic Syndrome ...... 70 3.1 Abstract ...... 70 3.2 Introduction ...... 71 3.3 Materials and Methods ...... 74 3.3.1. Comparison of Naringenin Contents in Naringenin-containing Foods ...... 74 3.3.2. Confection Preparation and Analysis of Naringenin Content...... 75

viii

3.3.3. Confection Preparation for Animal Feeding Trial ...... 76 3.3.4. Feeding Behavior Trial of Naringenin Confections ...... 77 3.3.5. Complexation of Cyclodextrin and Naringenin / Naringin ...... 77 3.3.6 Analysis of Complexation Efficiency ...... 78 3.4 Results ...... 79 3.4.1. Comparison of Naringenin Contents in Naringenin-containing Foods and Confection ...... 79 3.4.2 Feeding Behavior Trial of Naringenin Confections ...... 80 3.4.3 Complexation of Cyclodextrin and Naringenin / Naringin by Stirring and Kneading ...... 81 3.5 Discussion ...... 86 References ...... 88

List of Tables

Table 1. Main subgroups of flavonoids, the individual compounds, and food sources. ... 31 Table 2. Composition of experimental diets...... 55 Table 3. Grapefruit confection formula...... 75 Table 4. Grapefruit confection formula for animal feeding trial...... 76 Table 5. Tentative Identification and concentration of naringenin species in naringenin- containing food ...... 79 Table 6. Chemical shifts of H-NMR of β-CD protons with and without naringenin / naringin...... 84

List of Figures

Figure 1. Major signaling pathways responsible for skeletal muscle synthesis...... 19 Figure 2. Chemical structure of a cyclodextrin...... 45 Figure 3. Formation of an inclusion complex between a hydrophobic molecule and a cyclodextrin...... 46 Figure 4. Possible mode of naringenin inclusion by cyclodextrin...... 50 Figure 5. Timeline of naringenin cachexia study...... 56 Figure 6. Effects of tumor and dietary naringenin on food intake and body weight...... 60 Figure 7. Effects of tumor and dietary naringenin on the change in body composition .. 62 Figure 8. Effects of tumor and dietary naringenin on muscle function ...... 63 Figure 9. Effects of tumor and dietary naringenin on insulin sensitivity...... 64 Figure 10. Effects of tumor and dietary naringenin on tissue weights ...... 66 Figure 11. Effects of dietary naringenin on plasma IL-6...... 67 Figure 12. Effects of tumor and dietary naringenin on HMW and total adiponectin...... 67 Figure 13. DSC thermograms of naringenin/naringin β-cyclodextrin complex prepared by stirring and keading methods...... 82 Figure 14. H-NMR Spectrum of β-cyclodextrin and naringenin/ naringin- β-cyclodextrin complex prepared by different methods...... 83 Figure 15. Change in H-NMR chemical shift of β-CD before and after complexation. .. 85

Chapter 1. Literature Review

1.1 Cancer Cachexia

1.1.1 Definition, Prevalence, and Impact of Cancer Cachexia

Cancer cachexia is a multifactorial syndrome characterized by progressive skeletal muscle loss with or without adipose tissue loss. Many factors contribute to wasting, including changes in metabolic pathways, tissues, and organs (Argiles et al., 2014). Cancer cachexia leads to weakness, loss of volitional effort, resistance to antineoplastic therapies, and decreased survival.

Quality of life and overall survival of patients are affected as the symptoms of cancer cachexia progress (Williams et al., 1999). The muscle wasting in cancer cachexia cannot be prevented or reversed by conventional nutritional therapies due to negative nitrogen and energy balance resulting from the development of abnormal energy metabolism and anorexia.

Precachexia involves anorexia and metabolic disturbances such as glucose intolerance and insulin resistance and may progress to cachexia and then to refractory cachexia. Diagnostic criteria for cancer cachexia are body weight loss of greater than five percent over the past six months, two percent body weight loss for the individuals with a body-mass index (BMI) of less than 20kg/m2, or sarcopenia accompanied with weight loss of more than two percent. When precachexia advances to refractory cachexia, patients become unresponsive to anticancer treatment and expected survival becomes less than three months (Fearon et al., 2011).

Since cachexia is a multifactorial disease, weight loss by itself may not accurately predict the loss of lean mass. Physical function and psychosocial assessments also play important roles in the staging of cancer cachexia. The importance of physical performance, anorexia, and quality of life are emphasized as components of scoring system of cachexia staging along with body weight loss, body composition, and biochemical measurement of metabolic disturbance markers

(Argiles et al., 2011).

Cachexia in cancer patients is associated with increased morbidity and mortality, and almost one-third of cancer-related death is estimated to be from cachexia (Warren, 1932; Tisdale,

2009). The risk of pathogenesis and the rate of progression of cachexia depends on the type, sites, and the stages of cancers. In general, patients with gastrointestinal cancer and pancreatic cancer are more prone to cachexia compared to other types of cancer (Tisdale, 2009; Fearon et al., 2012). Seventy percent of patients with esophageal, gastric and pancreatic cancers developed cachexia in a study, and close to 80% of advanced cancer patients are reported to develop cachexia, showing prevalence of cachexia in certain population of cancer patients (Andreyev et al., 1998; Argiles et al., 2014; Bruera, 1997).

The impact of cancer cachexia on the prognosis, survival, and their quality of life is prominent.

In a study which examined the effect of weight loss on the outcome of chemotherapy in esophagus, stomach, pancreas, colon or rectum cancers, a significant increase in dose-limiting toxicity of chemotherapy was observed (Andreyev et al, 1998). In patients with weight loss, significant decrease in overall survival, quality of life, response, and performance status were reported compared to patients with no weight loss in the same study, showing the impact of the presence of cachexia in cancer patients.

1.1.2 Metabolic Disturbance and Cancer Cachexia

Alterations in carbohydrate, lipid and amino acid metabolisms are well-known characteristics of cancer cachexia. These metabolic disturbances are suggested to play some role in the wasting of cancer cachexia.

It has long been known that glucose intolerance and insulin resistance is a common metabolic alteration observed in cancer patients (Rohdenburg, Bernhard, & Krehbiel, 1919; Glicksman&

Rawson, 1956). The role of insulin resistance in the pathogenesis of cancer cachexia has been suggested by some prior studies in the Belury lab (Asp et al., 2010; Asp et al., 2011). Insulin resistance is likely to develop before the onset of weight loss, and the link between insulin resistance and alteration of substrate utilization is suggested to drive metabolism toward the catabolic state and anabolic resistance that accompanies insulin resistance (Yoshikawa et al.,1999). In a study where an insulin sensitizer was used in a cachexia-inducing animal model, improvement in insulin-stimulated glucose uptake and delayed weight loss were observed in early cachectic phase while no such effect was observed in late-stage cachectic mice (Asp et al.,

2011). The insulin sensitizer suppressed tumor-induced increases in lipid utilization and decreases in glucose utilization in the muscle by normalizing transcript levels of genes involved in the substrate utilization shift; pyruvate dehydrogenase kinase-4 (PDK4), peroxisome proliferator-activated receptor delta (PPAR-δ), and uncoupling protein-2 (UCP2). Slowed development of insulin resistance was shown to protect against the energy substrate utilization shift at the transcriptional level, supporting the suggested link between insulin desensitization and the onset of wasting. This protective effect against the shift in the transcription of substrate utilization genes was only present at the early stage of cancer cachexia before the substrate utilization shift is triggered. Hence, the difference in the observation between early stage and late 3 stage may indicate the power of “vicious cycle” of reprogrammed metabolism (Schwartsburd,

2019), suggesting the difficulty of reversing the cycle after metabolic disturbances are perpetuated.

A theory of the development of insulin resistance in the pathogenesis of cachexia in the host can be explained by the concept that cancer cells orchestrate metabolism to satisfy their energy requirement. Although some differences may exist depending on the cancer types, most cancer cells seem to require glucose as the major source of energy for its metabolism and growth

(Norton, Burt & Brennan, 1980; Holroyde et al., 1975; Schwartsburd, 2019). Since the mechanism of glucose uptake by cancer cells is not dependent on insulin, blunted responses to insulin of the host makes glucose more available to the tumor than to other insulin-responsive tissues such as skeletal muscles. The majority of amino acids broken down by muscle protein degradation in cachexia become substrates for gluconeogenesis in the liver (Mitch& Goldberg,

1995). Furthermore, skeletal muscle degradation presents the tumor with an abundance of glucose, which allows glucose-dependent cancer cells to proliferate. Indeed, a 40% increase in hepatic glucose production rate was observed in cancer patients who were losing weight (Tayek,

1992). Tumor resection from gastrointestinal cancer patients was shown to decrease glucose utilization (Shaw& Wolfe, 1987), suggesting the direct role of the tumor on the alteration of glucose metabolism. Similarly, restoration of insulin resistance was observed after surgical removal of the tumor from cancer patients (Yoshikawa, Noguchi, & Matsumoto, 1994).

Therefore, it is likely that the tumors in this study modulated insulin sensitivity in some way, which in turn triggered the alteration in substrate utilization.

Although the pathological mechanisms of how the presence of tumor influences host glucose metabolism are not fully understood, it is largely agreed that the tumor itself induces metabolic alterations by producing specific signaling molecules including pro-inflammatory cytokines such as tumor necrosis factor-α (TNF-α), interferon-γ (INF-γ), and interleukin-6 (IL-6) (DeWys,

1982). One study showed the ability of TNF-α to inhibit insulin-stimulated glucose uptake by decreasing autophosphorylation of insulin receptors and phosphorylation of insulin receptor substrates (Hotamisligil et al., 1994). Increased plasma TNF-α levels was associated with insulin resistance, and the association between elevated TNF-α and insulin resistance has been observed in both cancer and pregnancy, where more glucose is required as a fuel for the proliferation of cancer or embryonic cells, respectively (Schwartsburd, 2019).

In addition to the potential contribution of pro-inflammatory cytokines on insulin resistance, systemic inflammation is suggested to participate in cancer-mediated catabolic programming through some other channels (Schwartsburd, 2019). Another potential role of the aforementioned pro-inflammatory cytokines on the metabolic system involves the alteration in energy expenditure and lipid metabolism. Increased lipolysis and fatty acid oxidation, decreased lipogenesis, and dyslipidemia are often observed in cancer cachexia patients (Dahlman et al.,

2010; Ebadi & Mazurak, 2014; Das& Hoefler, 2013).

Lipid metabolism may have an important role in the initiation and progression of cachexia

(Das and Hoefler, 2013). Loss of adipose tissue prior to skeletal muscle loss has been reported in progressive cancer cachexia (Fouladiun et al., 2005; Dahlman et al., 2010), and the potential protective effect of having large adipose depots against cachexia called the “obesity paradox” has been suggested (Banh et al., 2019; Martin et al., 2013).

Processes that can collectively lead to the loss of adipose stores in cachectic patients are 1) decreased uptake of serum triglycerides, 2) decreased de novo biosynthesis in adipose tissue, and

3)increased lipolysis in adipose tissue (Thompson et al., 1993; Das& Hoefler, 2013). Although indicators of lipid metabolism alteration including depletion of adipose depots, increased resting energy expenditure, and dyslipidemia are commonly observed in cachectic patients, how the presence of tumor induces these changes is not yet completely understood. One potential mechanism by which cytokines may alter lipid metabolism is the suppression of lipoprotein lipase availability or activity (Das& Hoefler, 2013). Lipoprotein lipase is found on the surface of endothelial cells in white adipose tissue, and it is responsible for the hydrolysis of triglyceride in the serum. Lipoprotein lipase facilitates cellular uptake of fatty acids and maintains the regular supply of fatty acids to adipocytes for storage (Kawakami et al., 1986; Thompson et al., 1993).

TNF-α and leukemia inhibitory factor (LIF), a cytokine which has overlapping functions with that of TNF-α, IL-6, and IL-1, were reported to decrease the activity and mRNA expression of lipoprotein lipase (Berg, Fraker, & Alexander, 1994). Decreased lipoprotein lipase activity is reported in patients with gastric and colorectal carcinoma, as well as in animal cancer models

(Nomura et al., 1997; Lanza-Jacoby et al., 1984; López-Soriano et al., 1996), and it agrees with the increase in the serum levels of triacylglyceride and low-density lipoproteins and very-low- density lipoproteins seen in cancer patients (Das& Hoefler, 2013). While TNF-α suppresses lipoprotein lipase activity and white adipose stores in general (Kawakami et al., 1986; Das&

Hoefler, 2013; Nomura et al., 1997), the effect of IL-6 on lipid deposition through the suppression of lipoprotein lipase is controversial, since some observed a correlation of IL-6 and

6 lipoprotein lipase activity while others did not (Nomura et al., 1997; Nara-Ashizawa et al., 2001;

Berg, Fraker, & Alexander, 1994).

The second mechanism of lipid metabolism alteration that leads to adipose depot depletion in cancer cachexia may involve decreased lipogenesis. In an animal model of cancer-induced hypertriglyceridemia, decreases in the lipogenic enzyme activities in the liver and adipose tissues were observed in the later stage of tumor development during the18 to 32 days after the inoculation of AC33, a rat mammary adenocarcinoma, into male Lewis rats (Lanza-Jacoby et al.,

1984). Decreased lipogenesis in white adipose and skeletal muscles, and increased liver lipogenesis were observed during the 4 to 7 days after the inoculation of Yoshida ascites hepatoma-130 (YAH-130), in a murine cachectic model which uses female Wister rats (Lopez-

Soriano et al. 1996). Increased liver lipogenesis may explain the hyperlipidemia observed in the

AC33 model. The conflicting results with regards to liver lipogenesis in these two studies may be explained by the difference in the speed of cancer progression from strain difference, sex difference, cancer cell types, or injected cell counts, as the initial increase in lipogenesis followed by a decrease at later stage seems to be the general course of change. Indeed, rats inoculated with AC33 were reported to have died after 30 to 35 days of inoculation while rats inoculated with YAH-130 reached 99% decrease in food intake by ten days after inoculation

(Marzabal et al., 1993). It is likely that the lipogenesis decreases as cachexia progress, participating in the shift to lipid metabolism in cachexia.

It is well-accepted that lipolysis plays the most prominent role in fat loss in cancer cachexia

(Ebadi& Mazurak, 2014; Das & Hoefler, 2013; Zuijdgeest-van Leeuwen et al., 2000). Elevated fasting plasma glycerol and free fatty acids observed in advanced cancer patients with weight

7 loss suggest increased lipolysis and delipidation of fat depots in the population (Agustsson, 2007;

Zuijdgeest-van Leeuwen et al., 2000; Das et al., 2011). Hormone-sensitive lipase and adipose triglyceride lipase, intercellular enzymes which are involved in the hydrolysis of stored triacylglycerols to free fatty acids and glycerols, are responsible for the mobilization of lipid. A higher level of adipose triglyceride lipase has been observed in adipose tissue of cachectic patients compared to non-cachectic cancer patients (Das et al., 2011). Increased hormone- sensitive lipase both at mRNA expression and protein levels have also been observed in cachectic cancer patients compared to weight-stable cancer patients (Thompson et al., 1993;

Agustsson et al., 2007). A recent study published by Cao et al. (2010) found that the β1- adrenoceptor, a membrane protein in adipocytes, was elevated in cachectic patients compared to non-weight losing cancer patients. In the same study, it was also confirmed that both protein levels and RNA expression of hormone-sensitive lipase were elevated in cachectic patients. The observation of increased β1-adrenoceptors may explain the findings of elevated hormone- sensitive lipase activity and increased rate of lipolysis with no significant change in the levels of mediators between cachectic and non-cachectic cancer patients (Ebadi & Mazurak, 2014).

Increased circulating levels of fatty acids were associated with the increased rate of tumor growth in animal models of cancer (Sauer et al., 1986); therefore, adipose tissue lipolysis also likely supports tumor growth. This idea of increased lipolysis supporting tumor growth again fits the concept of cancer cells orchestrating metabolism to satisfy their energy requirement.

Increased circulating fatty acids from enhanced lipolysis can undergo mitochondrial oxidation for energy production (Ebadi& Mazurak, 2014). However, there is an increased likelihood of energy being dissipated as heat in “beiging” white adipose tissue through

8 uncoupling fatty acid oxidation from ATP production by uncoupling protein-1 (UPC-1) (Cao et al., 2011). The term beiging explains the darkening of adipose tissue from increased brown adipocytes rich in mitochondria. UPC-1 is a marker of uncoupling of respiration during energy production to dissipate energy as heat, and it is highly expressed in mitochondria in brown and beige adipocytes (Wu et al., 2012). Change in the phenotype from white to beige adipose tissue have been observed before skeletal muscle atrophy starts in cachexia (Petruzzelli et al., 2014;

Han et al., 2018), and the degree of beiging increases as the cachexia develops (Petruzelli et al.,

2014). Excess energy expenditure from thermogenesis in this phenomenon is likely to contribute to the accelerated adipose tissue depletion in cachexia. Higher resting energy expenditure seen in cachexia is often attributed to activated thermogenesis by increased brown adipocytes in cancer cachexia (Kir et al., 2014). Increased UCP-1, decreased lipid droplet sizes, and established markers such as peroxisome proliferator-activated receptor gamma coactivator 1 α (Pgc1α),

Peroxisome proliferator-activated receptor gamma (Pparγ), cell death-inducing DFFA-like effector A (Cidea), and PR domain containing 16 (Prdm16) are used as indicators of increased mitochondria in the tissue (Petruzelli et al., 2014). Potential involvement of IL-6 in the browning of white adipose tissue was suggested using IL-6 receptor knockout mice implanted with B16 melanoma cells. These mice showed a significant decrease in UCP-1 protein levels (Petruzelli et al., 2014). To demonstrate that the addition of IL-6 had the reciprocal effect, adipocyte cell lines were treated with recombinant murine IL-6, and a significant increase in Ucp1 mRNA levels was observed, further supporting the involvement of IL-6 in the browning process. Prolonged β- adrenergic stimulation is known to induce adipocyte beiging and results in increased energy expenditure (Himms-Hagen et al., 1994). Increased expression of β-adrenoceptor in cachectic

9 patients (Cao et al., 2010) may be responsible for the further beiging of white adipose tissues by reproducing the enhanced effect of β-adrenergic stimulation, adding to the speed of wasting.

In animals and humans, substrate utilization for energy production can be measured using metabolic cages or chambers (Leonard, 2012; Passdmore, 1963; McLean, & Tobin, 1988). These chambers measure oxygen consumed and carbon dioxide output as an indirect measurement of substrate utilization. Respiratory Exchange Ratio (RER) is the ratio of the amount of carbon dioxide exhaled to the amount of oxygen inhaled. A greater oxygen intake in comparison to the carbon dioxide exhaled yields a lower RER value, indicative that an organism or patient is using more lipid for energy rather than glucose (Mtaweh et al., 2018). In cachexia, total substrate utilization measured by total respiratory exchange ratio shifts to a lower value, cognisant of more dependence on lipids for energy production. In line with this idea, the shift away from glucose metabolism, enhanced protein degradation, and increased lipid mobilization that is causing wasting of tissues in the host all seem to benefit the tumor in return. The metabolic changes and mechanisms of cachexia are complex and still not well understood. It is likely that crosstalk between major modulators of the carbohydrate, protein, and lipid metabolism pathways are involved in the development of this disease. Therefore, targeting multiple sites of the pathways or common participants in each pathway may be required to stop the cycle of metabolic disturbances in cachexia.

1.1.3 Multi-organ Symptoms of Cancer Cachexia and Brain Function

As demonstrated in the former subsection, the symptoms of cancer cachexia do not only involve cancer-containing tissues, but they also promote metabolic dysregulation in normal cells in other distant tissues (Schwartsburd, 2019). Because of their physiological functions, skeletal muscles and adipose tissues are major targets of the wasting characteristic of cancer cachexia.

The involvement of the immune system, including elevated immune response and increased circulation of pro-inflammatory cytokines, has been studied extensively for its effect on the tissue wasting in adipose tissue and skeletal muscle. While these tissues are clearly affected by cancer cachexia based on wasting properties, there are other organs which may be less focused or not as visible yet still affected in cancer cachexia. Other sites that are likely to be affected by cachexia include liver, gastrointestinal tract, heart, and brain (Argiles et al., 2014; Porporato,

2016). It is possible that the impact of cancer cachexia on these tissues may occur earlier than wasting and may contribute to the severity of wasting in the disease. Therefore, it is important to consider the roles of these tissues in cancer cachexia development.

The liver is an active participant in the metabolic disturbances and muscle wasting that occurs during cancer cachexia. During cancer progression, the liver receives lactate produced by glucose fermentation in the tumor, and converts it back to glucose, providing the tumor with more fuel (Tayek, 1992; Schwartsburd, 2019). This inefficient glucose carbon recycling system called the Cori cycle is elevated in cancer patients, and is estimated to account for three fourth of total glucose production (Tayek& Katz, 1997) and more than a ten percent increase in whole- body energy expenditure in the advanced cancer population (Holroyde et al., 1975; Eden, et al.,

1984). During muscle wasting due to cancer cachexia, most amino acids broken down from skeletal muscles are transported to the liver for gluconeogenesis, further providing glucose for 11 the tumor (Mitch& Goldberg, 1996). Cachexia also induces acute phase protein synthesis in the liver in an effort to maintain hepatic export protein synthesis rate when protein intake is decreased (Fearon et al., 2012). The degree of acute phase protein response, measured by elevated levels of serum C-reactive protein, is a strong predictor of shortened survival in cachectic patients (Fearon, 1992). Patients with the acute-phase response, measured by plasma

C-reactive protein concentrations, have higher resting energy expenditure compared to patients with no acute-phase response (Zuijdgeest-van Leeuwen et al., 2000; Johnson et al., 2008).

Therefore, the response of the liver to the physiological change induced by cancer may be predictive of poor prognosis in cancer cachexia. It seems reasonable to consider the liver as one of the targets for cachexia treatment given its proposed role in energy expenditure and wasting of muscle proteins.

The main effects of cachexia on the gastrointestinal tract include altered ghrelin production and change in microflora and malabsorption (Bindels & Delzenne, 2013). Ghrelin is a peptide mainly produced in the stomach which increases appetite. Elevated levels of ghrelin are observed in cachectic patients (Wolf et al., 2006). This seemingly conflicting elevation of ghrelin in cachexia is speculated as an endocrine response to the ghrelin resistance found in patients

(Argiles et al., 2014). Modulation of gut microbiota from reduced food intake has been shown to affect the levels of systemic inflammatory cytokines, including IL-6 and IL-4 in mice with cancer cachexia in a leukemia model. When lactobacilli levels were restored in this model, E3 ligases responsible for muscle atrophy in gastrocnemius and tibialis muscles were reduced

(Bindels et al., 2012; Bindels & Delzenne, 2013), suggesting a potential role of the gastrointestinal tract in muscle atrophy.

The decline in the cardiac muscle function has been reported in a colon-26 murine model of cachexia (Tian et al., 2010). In addition to the risk of cardiac failure in later-stage cachexia, insufficient heart function in cachectic patients may present an explanation for the severe fatigue often experienced by cachectic patients.

Many of frequently reported but overlooked symptoms of cancer cachexia seem to originate in the brain. Such features of cancer cachexia include: decreases in voluntary movement, fatigue, weakness, chronic pain, hypogeusia, hyposmia, chronic nausea, early satiety, anhedonia, depression, anxiety, and diminished mental capacity (Grossberg, Scarlett, & Marks, 2010; Plata-

Salaman, 1996; Nipp et al., 2018). Many studies suggest the involvement of pro-inflammatory cytokines in the cachexia-related change in the central nervous system. These cytokines may in- turn drive alterations in the release and function of neurotransmitters, peptides and neuropeptides, hormones, and other cytokines (Turrin & Plata-Salaman, 2000; Grossberg,

Scarlett, & Marks, 2010). Anorexia, depression, weakness, reduced mental capacity, and loss of volitional effort can all be attributed to change in brain functions as a response to the signals triggered by the abnormality in the body as part of evolutionary “defense mechanisms”

(Grossberg, Scarlet, & Marks, 2010). Identifying therapeutic targets that prevent these debilitating marginal symptoms may improve prognosis and quality of life and reduce muscle wasting in patients suffering from cancer cachexia.

The impact of depression-like symptoms on the progression of cachexia is notable: they diminish the patient’s motivation to battle the condition (Grossberg, Scarlett, & Marks, 2010), leading to increased morbidity and mortality. Markedly high plasma concentrations of IL-6 were observed in cancer patients with depression compared to cancer patients who did not have

13 depression (Musselman et al., 2001). Pro-inflammatory cytokines such as IL-1, IL-6, IL-8, TNF-

α, IFN-α, IFN-γ, are known to stimulate unfavorable neurological symptoms (Turrin & Plata-

Salaman, 1999). The ability of the peripheral immune response to communicate with the brain has been long proposed (del Ray & Besedovsky, 2019; Turrin & Plata-Salaman, 2000), and expression of cytokines as well as neuropeptides in the central nervous system upon inflammatory stimulation has been confirmed and linked to depression (Erta, Quintana, &

Hidalgo, 2012). Immune response and major depression are both known to activate the hypothalamus; therefore, this may be one of the major locations in the brain affected by cancer cachexia (Maes et al., 1993; Sapolsky et al., 1987).

In addition to its role in the immune response and depression, the hypothalamus is also responsible for energy homeostasis. The responsibility provides even more convincing evidence of the involvement of the hypothalamus in symptoms associated with cancer cachexia. Several hypothalamic nuclei have been found to have specific roles in the regulation of appetite and energy metabolism (Hetherington & Ranson, 1940). In anorexic tumor-bearing rats, altered levels of neuropeptide Y, a stimulant of feeding behavior, and reduction of corticotropin- releasing factor, a feeding behavior inhibitor, were observed in the hypothalamus (McCarthy et al., 1993). The directions of alteration of neuropeptide Y in the anorexic rats were dependent on the sites in the study, and it was increased in the arcuate nucleus and decreased in the paraventricular nucleus. The involvement of hypothalamus in cachexia may be causing the depression and anorexia to be present as a cluster. Indeed, depression and inadequate nutritional food intake in cancer patients seem to be strongly linked. In colorectal cancer patients, depression was found to most significantly predict for increased nutritional risk (Daudt et al.,

2012), providing further evidence supporting the involvement of the hypothalamus in the development of these symptoms that may in part drive the wasting signature to cancer cachexia.

A consequence of multi-organ symptoms in cancer cachexia is the accelerated decline in health due to synergistic interactions of affected parts of the body. These simultaneous and unfavorable changes greatly impact the quality of life of patients with cancer cachexia.

Interventions targeting cancer cachexia should focus not only on the more visible tissues which are going through wasting, but other tissues that play an important role in the cachexia pathogenesis, development, and wellbeing of patients.

1.1.4 Suggested Mechanisms of Muscle Wasting in Cancer Cachexia

Muscle wasting can be caused by an increase in skeletal muscle degradation and decrease in protein synthesis, resulting in unbalanced rates of protein synthesis and degradation. Preferential loss of protein from skeletal muscles is known to take place in certain cancers, and selective muscle loss is understood to be regulated via specific shifts in the transcription of participants in the major muscle synthesis and muscle break down pathways (Mitch& Goldberg, 1996;

Schiaffino et al., 2013). The muscle synthesis system consists of two major pathways: the IGF1-

Akt-mTOR pathway and the myostatin-Smad2/3 pathway.

Figure 1 shows the major signaling pathway for the skeletal muscle synthesis. In the IGF1-

Akt-mTOR pathway, IGF1 stimulates mTOR activity to encourage protein synthesis and muscle growth through PI3K-Akt. In the myostatin-Smad2/3 pathway, follistatin negatively regulates

Activin A, a TGFβ superfamily member, and induces muscle growth by inhibiting the activity of

Smad3. Myostatin, another member of TGFβ super family, also interferes with the Akt-mTOR pathway and negatively regulates the protein synthesis. Akt from IGF1-Akt-mTOR pathway and

Smad3 of myostatin-Smad2/3 pathway have an ability to interact directly, and it may be involved in cross-talk between the IGF1 pathway and myostatin or activin A. Any inhibition or stimulation of participants of the involved pathways or upstream of the pathways to cause suppression in IGF1-Akt-mTOR activity or suppression in myostatin-Smad2/3 activity can reduce the rate of muscle protein synthesis.

Although these protein synthesis pathways play important roles in muscle atrophy, hyperactivation of the main degradation pathways is understood to play a greater role in acute muscle atrophy seen in many pathological conditions including cancer cachexia (Schiaffino et al., 2013). There are two major protein degradation pathways: the ubiquitin-proteasomal and autophagic-lysosomal pathways.

In the ubiquitin-proteasomal pathway, proteins are covalently linked to their co-factor, ubiquitin by ubiquitin-protein ligase (E3) after activation by ATP-requiring enzyme E1.

Ubiquitinated proteins are then transported by E2. The 26S proteasome, which catalyzes protein degradation, recognizes and rapidly degrades ubiquitinated protein substrates into small peptides.

These small peptides are further broken down into amino acids by hydrolysis. The protein selectivity of E2 and E3 is the key to the degradation of certain targets such as muscle proteins during this process.

Identification of muscle-specific E3 ubiquitin ligases has demonstrated the impact of the ubiquitin-proteasomal pathway in muscle wasting in cancer cachexia. Two genes encoding muscle-specific ubiquitin ligases, atrogin-1/MAFbx and Muscle RING finger 1 (MuRF1), were

16 found to be universally elevated in a variety of diseases that lead to muscle atrophy (Bodine et al., 2001) MAFbx or MuRF1 deficient mice were found resistant to muscle atrophy (Bodine et al., 2001), suggesting the requirement of these two E3 ubiquitin ligases in the atrophying process.

In cancer cachexia, transcriptional changes in the genes encoding for the participants of the ubiquitin-proteasomal pathway seem to be a promising marker of cachexia pathogenesis.

Transcription of these genes, not limited to MAFbx and MuRF1, is elevated in cachectic muscles both in animal models and patients of cancer cachexia (Williams et al., 1999; Lorite et al., 1998).

Increased mRNA levels of ubiquitin carrier protein E2 and the C9 proteasome subunit, as well as increased levels of ubiquitin-conjugated proteins, were observed in gastrocnemius muscle of a cachexia-inducing murine tumor (MAC16) model (Lorite et al., 1998). Similarly, mRNA expression of ubiquitin and 20S proteasome subunit, HC3, HC5, HC7, and HC9 were observed in the rectus abdominis muscle of cancer patients (Williams et al., 1999). Of the two major protein degradation pathways, ubiquitin proteasomal system is understood to have more impact on the muscle wasting in cachexia than autophagic-lysosomal pathways (Mitch& Goldberg,

1996).

Genes encoding for the participants of the ubiquitin-proteasomal pathway are termed

“atrogenes” (Sandri et al., 2006). In a normal condition, activation of these atrogenes is blocked by Akt/PKB phosphorylation through negative regulation of Forkhead box O (FoxO) (Sandri et al., 2006). However, when the activity of Akt/PKB decreases, FoxO transcription factors are activated by hypophosphorylation, leading to an elevated level of atrogene expression. FoxO activation was confirmed to induce a reduction of muscle fiber cross-sectional area (Sandri et al.,

2004). Since insulin and IGF-1 are known to activate Akt/PKB, a reduction of these hormones can lead to increased FoxO activity in atrophying muscles.

PGC-1α, a PPARγ-coactivator protein, and one of the primary regulators of mitochondrial content and oxidative metabolism, negatively regulates FoxO through different channel than aforementioned Akt/PKB phosphorylation. A decrease in PGC-1α was observed in the muscles of a rodent cancer cachexia model, and transgenic overexpression of PGC-1α in a mouse model lead to smaller induction of atrogin-1 and MuRF1 than control (Sandri et al., 2006). These results demonstrate that PGC-1α protects against muscle atrophy by reducing the activity of FoxO, leading to suppressed transcription of the key atrogenes.

Figure 1. Major signaling pathways responsible for skeletal muscle synthesis.

1.1.5 Traditional Treatment for Cancer Cachexia

Along with anti-neoplastic treatments to target tumors, some cancer patients receive treatments to improve cancer cachexia symptoms. Therapies that have been traditionally used to target symptoms of cancer cachexia include the use of appetite stimulants and nutritional therapies. Relatively new approaches such as anti-inflammatory therapy and exercises are also emerging as a potential treatment for cancer cachexia (Morley, von Haehling, & Anker, 2014). It is well-understood that anorexia is one of the symptoms of cancer cachexia, and side-effects of

19 anti-neoplastic treatments may also lead to decreased food intake, and acceleration of the progression of cachexia where the rate of catabolism increases and physical functions declines.

As a result of the accelerated decline in health conditions due to reduced food intake and altered metabolism, patients experience prolonged hospitalization or declined response to anti-neoplastic therapies. For this reason, interventions which target cancer cachexia to maintain health-related quality of life and performance status play an important role in cancer treatment.

Traditionally, the main therapeutic approach to cancer cachexia has been in nutrition.

However, implementation of treatments specifically targeting cachexia or nutritional status of cachectic patients does not seem to be commonly advised by physicians even in a hospice where they focus on palliative care (Flynn et al., 2018). Although more than 70% of medical documents recorded nutritional impact symptoms in cachectic patients receiving palliative care, only about

40% of nutritional status was documented by physicians (Flynn et al., 2018). The rate of malnutrition in cancer patients is estimated to be 98% (Alkan et al., 2016). Despite the prevalence of nutritional problems in cachexia, these problems are under-addressed. Difficulty in the assessment of cachexia due to its multifactorial symptoms, especially at its early stage seems to complicate the timing and practice of cachexia management by medical professionals. Indeed, cachexia is often unaddressed or overlooked in the care of patients with advanced cancer

(Laviano et al., 2005).

For most patients who receive some forms of care for cachexia, the care focuses on improvement in nutritional intake to attenuate weight loss either by direct nutritional intervention, pharmacological agents such as megestrol acetate to increase appetite, or treatment

20 of depression as a significant predictor of anorexia (Alkan et al., 2016; Melstrom et al., 2007;

Daudt et al., 2012).

In a meta-analysis where the effectiveness of three different nutritional interventions, dietary counseling, parenteral, and fluid therapies was compared, no difference or only slight differences in the effectiveness of these interventions were observed depending on the conditions of cancer cachexia patients (Tobberup et al., 2019). Dietary counseling has been used for patients with functioning gastrointestinal tract as a means of nutritional intervention. Parenteral nutrition treatment, where patients intravenously receive nutrition, is often used in advanced cancer patients who cannot achieve the adequate amount of oral food or calorie intake due to existing medical conditions although it is not limited to patients whose only viable option of feeding is parenteral nutrition treatment. Most common types of cancers in patients who received parenteral nutrition treatments in a meta-analysis were gastric, colorectal, pancreatic, and gynecological cancers, which overlap with the population susceptible to cachexia. There was no difference between the overall effectiveness of parenteral nutrition and dietetic counseling during anti- neoplastic treatments on physical function in patients with functional gastrointestinal tracts. For the patients whose only viable feeding option was parenteral nutrition treatment, physical functions may improve only when the patients are undergoing anti-neoplastic treatment.

Parenteral nutrition therapy may be transiently superior in the improvement or maintenance of

BMI and fat-free mass in malnourished patients with functioning gastrointestinal tract who are undergoing anti-neoplastic treatment over dietetic counseling. However, in many cases, the use of nutritional interventions is limited to attenuate weight loss, and it does not completely stop the process (Ng&Lowry, 1991).

Megestrol acetate is a progestational drug that is approved for clinical use for cachexia care. Megastrol increases food intake and fat deposit through stimulation of appetite.

Unfortunately, in cancer patients, there was no change observed in the quality of life nor survival

(Ruiz-Garcia et al., 2018). Body weight improvement by the administration of pregestational drugs are suggested to be mainly from fat and an increase in body water, and no improvement in lean mass is observed (Argiles et al., 2001). Thrombotic episodes may be an adverse side effect of progestational drugs, further imposing difficulty in its clinical use, especially in more vulnerable populations (Bruera, 1997). Corticosteroids are another pharmacological agents which target cachexia symptoms. Although corticosteroids are suggested to improve anorexia and weakness in cancer patients, the effect is only temporary and lasts up to one month, and no reduction in mortality was reported (Eduaro, 1997; Melstrom et al., 2007). Furthermore, long- term use of corticosteroids is reported to cause side effects, including immunosuppression, weakness, osteoporosis, and delirium (Argiles at al., 2001).

In recent years, the use of drugs or neutraceuticals (Kalra, 2003) to target metabolism is an emerging focus of cachexia therapy (Argiles et al., 2001). For example, several studies suggested the effect of ω3-polyunsaturated fatty acids on favorable changes in both animal model of cancer cachexia (Beck et al., 1991; Tisdale, 1993) and human cachectic patients

(Wigmore et al., 1996; Fearon et al., 2003). The suggested mechanism largely involves the modulation of metabolism, including inhibition of lipolysis (Du et al., 2015), reduction of inflammation (Calder, 2006), attenuation of proteolysis (Whitehouse et al., 2001), and elevation of phosphorylation of anabolic markers (Smith et al., 2011).

Although different forms of nutritional interventions and some pharmacological agents have presented suggestive beneficial effects in a specific group of cancer patients to attenuate the decline in body mass and quality of life in some cases, they are part of palliative care and does not reverse the altered metabolism nor improve survival (Dy et al., 2008; Argiles et al., 2001; ).

Traditional interventions for cancer cachexia are not enough as a treatment, and direct curative treatment for cancer cachexia seem to be lacking in the current clinical setting. The continuing development of pharmacological approaches to counteract the metabolic changes is desired to target the complex symptoms of cachexia collectively with existing nutritional interventions.

1.1.6 C-26 Mouse Model for Human Cancer Cachexia Study

The lack of therapies targeting cancer cachexia can be explained by its complexity and lack of knowledge attributed to the difficulty in designing appropriate clinical trials to understand the underlying mechanisms (Ballaro, Costelli, & Penna, 2016). Multifactorial mechanisms of the disease and difficulty controlling for the inherent heterogeneity both in symptoms and patient behaviors would likely confound the outcome of clinical trials of potential cancer cachexia therapies. To overcome these heterogeneities, genetically identical animal models are often used to study cachexia.

For an animal model to be suitable for a translational study to study human disease, the model needs to closely mimic the human condition. However, because of the interspecies differences and heterogeneous symptoms of human cancer, there is no one animal model that perfectly simulates the variety of conditions and the wide range of driving mechanisms in

23 patients with cancer cachexia. Therefore, it needs to be noted that an animal model should be carefully selected to match the primary outcomes of the study. There are a number of mouse models of cancer cachexia described in the literature, and some of these models respond differently to the same treatment (Pin et al., 2015; Ballaro, Costelli, & Penna, 2016). These inter- model variabilities can be attributed to the difference in the main mechanisms or strongest driver of cachexia development between different animal models and illustrates the importance of selecting a model that intersects with the primary research question.

Murine Colon 26 (C-26) is a mouse xenograft model which uses CD2F1 strain (BALB/c

DBA/2) of mice and an undifferentiated carcinoma induced by carcinogen N-nitroso-N- methylurethan named Colon 26 adenocarcinoma (Corbett et al., 1975). C-26 is a common model used in translational studies to understand the mechanisms of cancer cachexia (Murphy et al.,

2012; Talbert et al., 2014).

The main mechanism of cachexia development in the C-26 model is understood to be from systemic inflammation. A high level of IL-6 is shown to drive cancer cachexia in this model

(Talbert et al., 2014; Fujimoto-Ouchi et al., 1995). In human cachexia, elevated cytokine levels are thought to be the predominant cause of metabolic abnormalities, although the degree of dependency on IL-6 may differ between human and the C-26 model (Bruera 1997).

The injection of C-26 in this model is shown to reduce body mass by 30 to 40% (tumor-free body weight), muscle mass by 20 to 30%, and fat mass by 70% (Tanaka et al., 1990; Bonetto et al., 2017). Loss of these tissues are commonly observed in cachectic patients. In humans, a 32 % reduction in body weight, a 75% reduction in skeletal muscle protein mass, and an 85% reduction in body fat were observed in cachectic patients with lung cancer (Fearon, 1992; Das &

Hoefler, 2013). Therefore, the relative impact of cachexia on changes to the body, muscle, and fat mass in the C-26 model and humans is comparable.

Development of anorexia in the C-26 model was described by a significant reduction in cumulative food intake ten days after C-26 inoculation (Tanaka et al., 1990). However, unlike some other animal models of cancer cachexia, the major cause of weight loss in the C-26 model is not from the reduced food intake, since the onset of weight loss occurred earlier than the significant reduction in food intake in this study. Comparatively, in human cancer cachexia, wasting is not solely from anorexia, but altered metabolism seems to play a bigger role. In the C-

26 model, it needs to be noted that tumor injection sites may affect whether anorexia develops.

While anorexia was observed after intraperitoneal injection, studies in which subcutaneous and intramuscular injections were used on the C-26 model did not report reduced food intake

(Dwarkasing et al., 2015; Matsuyama et al., 2015). Sources of C-26 cell lines, passage number, and implantation by different laboratories are also suggested as potential variables which affect the severity of cachexia (Murphy et al., 2012).

Like human cancer cachexia where the major cause of cachexia death is from respiratory failure, decrease in cardiac muscle mass and diaphragm muscle functions have been observed in

C-26 tumor-bearing mice (Murphy et al., 2012; Bonetto et al., 2017). Reduced skeletal muscle functions, which is also common in human cachexia, were confirmed by grip strength and rotarod tests performed on C-26 mice with cancer cachexia. C-26 mice with cancer cachexia also exhibit reduced locomotor activity, parallel with reduced levels of physical activity observed in cachectic patients (Murphy et al., 2012).

Regarding metabolic alterations, a significantly lower percentage of carbohydrate oxidation and a significantly higher percentage of fat oxidation of total energy expenditure were observed in C-26 tumor-bearing mice during both light and dark cycles (Murphy et al., 2012). This observation follows the shift observed in cachectic cancer patients (Hansell et al., 1986).

Development of insulin resistance and glucose tolerance are other impaired metabolic functions observed in patients with cancer cachexia. The C-26 model was also found to develop insulin resistance before weight loss (Asp et al., 2010). Increases in serum acute-phase proteins and decreases in drug-metabolizing enzymes are other similar metabolism-related alterations of C-26 model to human cachexia. These similarities support the use of the C-26 model to study hepatic acute-phase response and increased susceptibility to drug toxicity often observed in the later stage of human cachexia.

The similarity in the shift in the regulation of muscle-atrophy related genes between human and C-26 model was also observed. Increased mRNA expressions of MuRF-1 and atrogin-1 observed in C-26 tumor-bearing mice indicates the involvement of ubiquitin ligase system in the muscle atrophy of the model (Murphy et al., 2012.). Along with the similarity in the muscle- fiber-type specific atrophy pattern in cancer-induced muscle wasting between human and C-26 model discussed in the muscle fiber section, it provides an opportunity to explore cachexia with the focus on ubiquitin ligase pathway and muscle fiber types.

In addition to the similarities listed above, the benefit of using the C-26 model may be that the tumor burden when the wasted phenotype occurs in this model is closer to that of human cancer cachexia. Cachexia can occur in C-26 model at about two percent of tumor burden

26 compared to other cachexia inducing animal models such as Lewis lung carcinoma model in which tumor mass becomes 20 to 30% of the body weight (Ballaro, Costelli, & Penna, 2016).

Some known limitations in C-26 models are the relatively short period between the starting point of cachexia and death. This rapid progression compared to the gradual development of cachexia in human may cause missed observations in some areas.

Despite some potential limitations, C-26 model is suitable as a preclinical study model to address questions of cachexia in many areas as it mimics both functional and metabolic impairments observed in human cancer cachexia. It is important for the endpoints of studies using C-26 model to focus on the shared features with human cancer cachexia to maximize the translatability of the findings to a clinical condition.

1.2 Naringenin

1.2.1 Flavonoids and Bioactivities

Flavonoids are a class of phytochemicals that have been drawing increased attention over the past 25 years due to their wide range of therapeutic applications (Perez-Vizcaino, & Fraga,

2018). Phytochemicals are defined as natural compounds synthesized as secondary metabolites in plants, and the main classes of phytochemicals include carotenoids, alkaloids, nitrogen- containing compounds, organosulfur compounds, and phenolics (Budisan et al., 2017).

Flavonoids are a subclass of phenolics, and other class of phenolics include phenolic acids, stilbenes, coumarins, and tannins (Budisan et al., 2017). Over 6000 flavonoids have been identified to date (Harborne & Williams, 2000), and flavonoids can be further broken down into

27 more than 10 subgroups. Flavonoid subgroups include flavanols, flavanones, flavones, flavonols, flavanonols, isoflavones, and anthocyanins (representative flavonoids and food sources in each subgroup are listed in Table 1.) (Yao et al., 2004). Flavonoid intake in the US adults are estimated to be 200.1±8.9mg/day, and major dietary sources consist of tea, citrus fruit and juices, berries, wine, and apples (Kim, Vance, & Chun, 2006). Many epidemiological studies have found inverse relationships between flavonoid-containing-food intake and incidence of diseases (Kim et al., 2016; Li et al., 2010; De Stefani et al.; Freedman et al., 2007; Voorrips et al., 2000 Erlund, 2004). Biological and chemical functions of flavonoids can be vastly different depending on which subgroup they belong to (Erlund, 2004).

Among many suggested health benefits of flavonoids, cancer, cardiovascular diseases, and metabolic diseases are considered as the main targets of flavonoid functions (Lu, Xiao, &

Zhang, 2013; Kim, Vance, & Chun, 2016). Specificity nor mechanisms of action through which flavonoids affect physiological functions remain unknown in many areas. However, specific classes of flavonoids seem to be more studied for certain health conditions, including cancer sites and types, than the others, and the difference in the most studied target health conditions may reflect the specificity of the bioactivities of each flavonoid. For example, in the most studied flavonoid quercetin (Erlund, 2004), antioxidative (Gong et al., 2009; Lin et al., 2017), anti- cancer (Rivera et al., 2016; Russo, Russoa, & Spagnuoloa,2014), anti-inflammation (Shree

2017), anti-aggregatory (Shree 2017; Jiang et al., 2019), anti-diabetic (Kim et al., 2011) and blood-pressure-lowering (Egert et al., 2009; Edwards, 2007) effects have been reported, widely covering the main targets of flavonoid bioactivities in general.

Epidemiological findings of associations of citrus consumption and lower cancer incidence drew expert’s attention to anticancer properties of flavanones (Erlund, 2004), leading to extensive study in the chemoprevention and anti-cancer. Major flavanones include hesperetin, naringenin, eriodictyol, isosakuranetin, and their glycosides (Khan, Huma, & Dangles, 2013). In addition to the anticancer activity of flavanones as the main focus, radical scavenging, anti- inflammatory, cardio protective, lipid-lowering, and insulin-like effects have been reported

(Patel, Singh, & Patel, 2018; Khan, Huma, & Dangles, 2013).

Although bioactivity of flavonoids is expected to be beneficial in health promotion or disease prevention in many cases, some studies suggest unfavorable effects of flavonoids on health conditions. Antioxidative activity of flavonoids was found to cause a decline in muscle mass (Espinosa, Henriquez-Olguin, & Jaimovich, 2016; Assi et al., 2016). Weight loss and premature death in C-26 model was observed when flavonoids such as catechins or quercetin were supplemented to cachectic mice (Espinosa, Henriquez-Olguin, & Jaimovich, 2016; Assi et al., 2016). On the contrary, there are other studies that have shown protective effects of flavonoids against skeletal muscle atrophy in animal models of cachexia. Epigallocatechin-3- gallate (EGCG) were shown to attenuate muscle loss in tumor-bearing mice, while EGCG encouraged skeletal muscle loss in non-tumor mice (Wang et al., 2011). Luteolin was suggested to improve the inflammatory status and down-regulate the expression of atrogenes in Lewis lung cancer mouse model of cachexia (Chen et al., 2018). These seemingly conflicting results may be due to the difference in the type of flavonoid, dose, study design, cancer types, and other factors.

As can be seen in the above example, in the study of flavonoid bioactivity, there remain many

29 uncertainties. Further exploration in these knowledge gaps is required to better understand the bioactivity of flavonoids for future application to human disease prevention and treatment.

Table 1. Main subgroups of flavonoids, the individual compounds, and food sources.

Note: Reprinted from “Flavonoids in Food and Their Health Benefits”, by Yao et al., 2004, Plant Foods for Human Nutrition, 59, p.115. © Springer Science+Business Media, Inc. 2004.

1.2.2 Food Sources of Naringenin

Naringenin is found in grapefruit at high concentrations predominantly as its glycoside, naringin (naringenin-7-neohesperidoside), and it makes up 70% of total naringenin species found in grapefruits (Erlund, 2004). Naringin is responsible for the bitterness of grapefruits, along with neohesperidin (Zhang, 2007; Lester, Manthey, & Buslig, 2007). Organically grown grapefruits were found to have a higher concentration of naringin and tasted more bitter than conventional grapefruits (Lester, Manthey, & Buslig, 2007). Tomatoes, other citrus fruits, and herbs in the

Lamiaceae family were also reported to contain naringenin species. In tomatoes, naringenin is present as either naringenin chalcone or aglycone, and in herbs in the Lamiaceae family, naringenin is mainly present as prunin (naringenin-7-O-glucoside) (Tamasi et al., 2019; Zheng &

Wang, 2001; Kosar, Dorman, & Hiltunen, 2005). Compared to naringenin in grapefruits, naringenin in tomatoes, other citrus fruits, and herbs are found either in much lower concentrations, in the part that are not usually consumed, or in foods that are not consumed in a large amount (Asikin et al., 2012; Bhagwat, Haytowitz, &Holden, 2014), leaving grapefruit as good source of naringenin.

Naringenin content in commercial grapefruit juice varies greatly depending on the batch, brand, and place of origin (Ho et al., 2000). The mean content of naringenin species in commercial grapefruit juices from multiple studies was reported as 40.5 mg/mL for naringin with the range of 10.1-86.6mg/100mL and 10.7mg/mL for narirutin (naringenin 7-O-rutinoside) with the range of 2.6-12.2mg/100mL with usually non-detectable or low levels of naringenin (Zhang,

2007).

1.2.3 Metabolism and Bioavailability of Naringenin Species

Flavonoids found in nature are mainly present as glycosides, and aglycone form is rare.

In many food sources of naringenin, most forms are present as glycosides. Naringenin glycosides are known to have lower bioavailability than their aglycone (Hsiu et al., 2002). Removal of the hydrophilic sugar moiety of naringenin glycosides is usually required for passive diffusion across the mammalian small intestine brush border (Scalbert& Williamson, 2000).

The removal of the sugar is suggested to take place in the food itself, in the manmmalian gastrointestinal mucosa, or by colon microflora (Scalbert& Williamson, 2000). Glycosides can be hydrolyzed by bacterial enzymes in the large intestine, and further catabolism of some aglycones into phenolic acids takes place in the large intestine. These products of hydrolysis are suggested to then be absorbed in the upper part of the large intestine (Bokkenheuser, Shackleton,

& Winter, 1987). Glucuronidation and sulfation of flavonoids also occur during absorption into the intestinal wall (Hsiu et al., 2002). In addition to the hydrolysis by bacterial enzymes, a recent study also suggested the hydrolysis of flavonoid glucosides taking place in the oral cavity (Walle et al., 2005). Hydrolysis of glucosides by β-glucosidase in the small-intestine epithelial cells also has been proposed by animal studies (Ioku et al., 1998; Day et al., 1998), further adding to the potential sites of flavonoid glycoside break down. In addition to the passive diffusions after cleavage of sugar moiety, absorption of flavonoid glycosides in the small intestine through a sodium-dependent glucose transporter has been proposed and observed in animal studies

(Hollman et al., 1995; Wolffram et al., 2000). Therefore, it is likely that flavonoid absorption does not only depend on the hydrolysis by the bacterial enzymes in the large intestine, but involves other sites of the body.

In a study where a naringenin glycoside narirutin was orally administrated to rats, 0.5% of free-form naringenin and 12.7% of naringenin glucuronide was observed in the plasma 33

(Choudhury et al., 1999), suggesting the hydrolysis of a fraction of the glycoside entered through the oral route. In humans, consumption of citrus juice and citrus fruit-containing diet (estimated

29mg naringenin/day) significantly elevated the plasma levels of naringenin compared to individuals consuming a low fruit low vegetable diet with no citrus food (non-detectable level of naringenin/day) after a five-week intervention (Erlund et al., 2002), suggesting the bioavailability of dietary naringenin sources. In another human bioavailability study, one-time grapefruit juice consumption provided high peak plasma concentration of naringenin (1628µg/L) with a half-life of 1.3 hours (Erlund et al., 2001). Another study reported the peak plasma concentration of naringenin 3.5 hours after the ingestion of aglycone naringenin, and an elimination half-life of 2.31±0.40 hours (Kanaze et al., 2007). Cumulative urinary recovery data in the same study was found to be as low as 5.81±0.81% of the ingested dose of naringenin, suggesting the relatively low bioavailability of naringenin species, even in the aglycone form.

Many studies involving human clinical trials observed high inter-individual variation in the plasma naringenin levels regardless of the forms of naringenin (Radtke, Linseisen, & Wolfram,

2002; Kanaze et al., 2007; Erlund et al., 2001), suggesting that bioavailability of naringenin may depend on the individual. Inherent variability in the gut microflora and ability to convert naringenin species to more bioavailable form may be one of the causes of the observed variability in the naringenin bioavailability.

Accumulation of naringenin in the body tissues has been observed in an animal model

(Ke et al., 2016). After 11-week exposure of mice to a naringenin-containing diet, naringenin was found in plasma, perigonadal adipose tissue, subcutaneous adipose tissue, and skeletal muscles, (Ke et al., 2016), showing the ability of naringenin to reach and accumulate in the body tissues after continued oral administration.

Although the above study did not have data for the accumulation of naringenin in the brain, ability of naringenin and its derivatives to pass blood-brain barrier has been suggested using bioinformatics (Lawal, Olotu, & Soliman, 2018). In an animal model, intravenous injection of naringenin in rats resulted in the appearance of naringenin in the cerebral cortex 10 minutes after the administration (Peng et al., 1998). In the study, the concentration of naringenin found in the brain tissue was lower than the naringenin in plasma, and free-form naringenin to glucuronide conjugate naringenin ratio was higher in the brain tissue compared to plasma, suggesting the ability of a fraction of free-form naringenin to enter the brain from the blood.

1.2.4 Naringenin and Inflammation

Multiple in vitro and in vivo studies have shown the anti-inflammatory effects of naringenin. Mice macrophages infected with C.trachomatis produced inflammatory cytokines including TNF, IL-1β, IL-1α. IL-10, and IL-6, and they were down-regulated by naringenin via inhibition of p38 mitogen-activated protein kinase (MAPK), a pivotal kinase in inflammatory diseases which controls the production of cytokines (Yilma et al., 2013; Huang, Han,& Hui,

2010). TNFα and IL-10 protein levels and mRNA expression of IL-33 were suppressed in the skin of a mouse model of superoxide-anion-donor-induced inflammation after oral administration of 50mg/kg naringenin (Manchope et al., 2016). In a mouse model of gout arthritis, naringenin modulated the cytokine production at the site of monosodium urate induced inflammation, suppressing the production of IL-1β, TNF-α, IL-6, IL-7 and IL-10 via inhibition of nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB) activation (Ruiz-

Miyazawa et al., 2018). Reduction of pro-inflammatory cytokines TNFα and IL-β1 by naringenin

35 is also observed in the brain of mice exposed to chronic social defeat stress, suggesting naringenin’s anti-inflammatory capacity to also act in the brain (Umukoro et al., 2018).

1.2.5 Naringenin and Glucose Metabolism

Several studies have suggested glucose-clearing and insulin-sensitizing effects of naringenin. In a study where the effect of naringenin on skeletal muscle glucose uptake was measured, stimulation of glucose uptake in myotubes was observed while myoblasts did not show such effect, suggesting the involvement of glucose transporter type 4 (GLUT4) in the naringenin-stimulated glucose uptake (Zygmunt et al., 2010). In Fao rat hepatoma cells with induced gluconeogenesis, the addition of naringenin was found to attenuate glucose production while the glycoside naringin did not have such effect (Purushotham, Tian, &Belury, 2007). This observation suggests the effect of naringenin, but not naringin at the site of action, on inhibition of hepatic gluconeogenesis and potential attenuation of hyperglycemia. Hyperinsulinemia induced by diet in LDL receptor-null mice was reduced by a three-percent supplementation of naringenin (Mulvihill et al., 2009). The normalizing effects of naringenin on insulin sensitivity, hyperglycemia, and glucose utilization were also observed in the same study. In an obese mouse model, supplementation of three-percent naringenin reduced the fasting plasma glucose (Ke et al., 2016). Suppression of carbohydrate absorption has been suggested as a mechanism of the glucose-lowering effect seen in naringenin supplemented animal models of hyperglycemia by a few studies (Ortiz-Andrae et al., 2008; Priscilla et al., 2013). Inhibition of the MAPK pathway through phosphorylation of insulin receptor substrate one (IRS1) is another suggested mechanism which contributes to insulin sensitization observed upon consumption of 0.02%

36 naringin diet in a mouse model of metabolic syndrome (Pu et al., 2011). Improvement in the lipid profile is also considered a contributor to the improved insulin sensitivity in naringenin supplemented mice (Mulvihill et al., 2009).

1.2.6 Naringenin and Lipid Metabolism

The ability of naringenin to modulate lipid metabolism has been proposed in several studies. Naringenin supplementation at three percent prevented deposition of triglyceride and cholesterol ester in the muscle of the mice with diet-induced dyslipidemia (Mulvihill et al.,

2009). In an obese mouse model, naringenin supplementation resulted in decreased diacylglyceride levels in muscles, while plasma cholesterol and triglycerides were unchanged

(Ke et al., 2016). A six-week supplementation of 0.02% of naringenin significantly decreased plasma cholesterol and triglyceride concentrations while maintaining high-density lipoprotein concentration (Kim et al., 2006). lipid-lowering effect of naringenin is also observed in the liver in this study, and suppression of hepatic 30 hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase activity is suggested as the cause of hypolipidemic effect provided by naringenin supplementation (Kim et al., 2006). In a mouse model of metabolic syndrome induced by a high- fat diet, downregulation of lipid-metabolism-related genes encoding for enzymes responsible for fatty acid synthesis (SERBP-1c, FAS, and ACCα) were also observed (Pu et al., 2012). In the same study, mRNA level of PPARγ, another regulator of lipogenesis, was elevated for high-fat- fed mice but was normalized by naringin. Therefore, naringenin may modulate lipid metabolism through down-regulation of enzymes involved in cholesterol synthesis, fatty acid synthesis, and lipogenesis.

1.2.7 Naringenin and Energy Expenditure

Naringenin has also been suggested to affect energy metabolism. Over a 50% decrease in the epididymal and subcutaneous adiposity in a mouse model of metabolic disturbances have been observed upon supplementation of dietary naringenin at three percent (Ke et al., 2015). In this study, induction of mRNA expression of fatty acid synthase and participants of hepatic gluconeogenesis was observed in the naringenin supplemented group, suggesting the change in energy metabolism and substrate utilization induced by naringenin. In another study of Ke et al.

(2016), supplementation of naringenin to obese ovariectomized mice was found to cause a two- fold increase in their locomotor activity. Similarly to the former study, naringenin-fed mice in this study was found to have 40% greater transcript of peroxisome proliferator-activated receptor-γcoactivator one alpha (PGC1α) in the muscle, suggesting the potential increase in the mitochondrial energy metabolism (Liang& Ward, 2006). In a mouse model of dyslipidemia, naringenin increased hepatic fatty acid oxidation through PGC1α, and energy expenditure measured by the indirect calorimeter was also increased, likely leading to the observed dose- dependent attenuation of adiposity (Mulvihill et al., 2009). In both of the above studies that observed decreases in adiposity, lean mass remained unaffected (Ke et al., 2015; Mulvihill et al.,

2009), suggesting the selective targeting of adipose tissue by naringenin-induced energy expenditure.

1.2.8 Naringenin and Brain Functions

The observation of increased locomotor activity in naringenin-fed mice (Ke et al., 2016) may reflect naringenin-induced changes in the brain. Several studies have suggested the effect of

38 naringenin on the central nervous system (Joshi, Kulkarni, & Wairkar, 2018; Park et al., 2014; Yi et al., 2012). Protective effects of naringenin in neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease have been proposed in animal studies (Khan et al., 2012;

Zbarsky et al., 2005). In a rat model of Alzheimer’s disease, two-week oral administration of naringenin at 50mg/kg prior to the injection of intracerebroventricular-streptozotocin significantly improved the damage to hippocampal neurons and brain functions (Khan et al.,

2012). Another rat model of Parkinson’s disease showed protective effects of naringenin against declines in dopamine levels and tyrosine hydroxylase-positive cells (Zbarsky et al., 2005). The common mode of action of naringenin in these neurodegenerative diseases is suggested to be the protection against oxidative stress.

A few animal studies have suggested Anti-depressive effect of naringenin (Yi et al.,

2010; Yi et al., 2012; Umukoro et al., 2018). Naringenin supplementation to mice exposed to chronic social defeat stress was shown to improve the inflammatory status (Umukoro et al.,

2018). The likely involvement of pro-inflammatory cytokines in the development of depression is discussed in section 1.1.3, and regulation of inflammation may contribute to the improvement of depression. In recent years, the central role of brain-derived neurotrophic factor (BDNF) was emphasized in the antidepressant activity (Quevedo, Comim, & Gavioli, 2009). Down-regulation of BDNF has been shown in mice exposed to stress, and parallel development of depression-like behavior was observed with the reduction of BDNF (Yi et al., 2014). Chronic naringenin treatment of these mice promoted BDNF signaling in the hippocampus, leading to dose- dependent improvement in the stress-induced anhedonia, suggesting the enhancing effect of naringenin on the BDNF signaling.

In a mice study where BDNF heterozygous and wild-type mice were compared, BDNF heterozygous mice gained weight with significant variance, and only the mice that gained weight among the heterozygous group exhibited a two-fold increase in locomotor activity measured by beam breaks (Kerine, Liebi, & Parada, 2000), suggesting the involvement of BDNF in energy homeostasis. BDNF protein is most abundant in the hippocampus and hypothalamus (Nawa,

Carnahan, & Gall, 1995), and the observation in the naringenin-induced promotion of BDNF signaling in the hippocampus in the study of Yi et al. (2014) may also be taking place in the hypothalamus, affecting the locomotor activity and food intake of the naringenin fed-mice observed in the study by Ke et al. (2016).

1.2.9 Naringenin and Cancer

Epidemiological studies have found associations between naringenin-containing foods and lower incidence of certain types of cancers. In a case-control study, tomatoes and oranges were associated with stronger protective effects against the occurrence of laryngeal cancer (De

Stefani et al., 2000). Flavanone intake was associated with a 20% lower risk of head and neck cancer in a prospective cohort study (Sun et al., 2018). In other prospective cohort studies,

Rutaceae family (citrus fruit) consumption was shown to have a significant protective effect on esophageal squamous cell carcinoma (Freedman et al., 2007), and higher consumption of orange and grapefruit juice had a significant protective effect on the relative risk of lung cancer

(Voorrips et al., 2000). Another prospective study that focused on citrus consumption and different types of cancers found inverse correlations between the consumption of citrus and all- cancer incidence (Li et al., 2010).

Findings of the associations between naringenin-containing foods and lower incidence of certain types of cancers lead to the investigation of the chemo-preventive and anti-cancer properties of flavanones, including naringenin. Naringenin has been shown to induce cytotoxic, apoptotic, and antiproliferative activities in various human cancer cells, including lung, colon, cervix, breast, liver, pancreas, prostate, melanoma, and leukemia (Kanno et al., 2005; Manthey &

Guthrie, 2002). In the study of Kanno et al. (2005), lower naringenin-induced cytotoxicity was observed in Caco-2 cells while higher cytotoxicity was seen in leukemia, compared to other cell lines, suggesting potential specificity of the action.

Suggested mechanisms of anti-cancer effects include the promotion of apoptosis (Lim et al., 2017; Park et al., 2017; Sabarinathan et al., 2010). In both androgen-receptor negative and androgen-receptor positive human prostate cancer cell lines, naringenin induced reactive oxygen species (ROS) production and apoptosis through over-phosphorylation of AKT (Lim et al.,

2017). Overactivation of AKT was found to sensitize cells to ROS-mediated apoptosis by downregulating antioxidant proteins related to FoxO (Lim et al., 2017; Los et al., 2009). A similar observation was made in a human pancreatic cancer cell line, where the elevation of ROS following downregulation of peroxiredoxin one (Prdx-1), an antioxidant enzyme, induced apoptosis by upregulating apoptosis signal-regulation kinase one (ASK1) (Park et al., 2017). In the prostate cancer cell study, reduced phosphorylation of extracellular signal-regulated kinase one (ERK1), ERK2, p53 and p38 were observed in the androgen-receptor positive cell line, indicating the involvement of MAPK signaling pathway in the suppression of proliferation by naringenin (Park et al., 2017) in addition to AKT and ROS mediated anti-cancer activity.

In a breast cancer cell line, naringenin induced inhibition of insulin-stimulated glucose uptake by suppressing PI3K activity, GLUT4 translocation, as well as MAPK activity through

41 inhibition of the phosphorylation of p44 and p42 MAPK (Harmon & Patel, 2004). Cell proliferation was again reduced through regulation of AKT and MAPK by naringenin in this study, while it was through inhibition of these pathways as opposed to overactivation of AKT discussed in the former paragraph. Indeed, inhibition of AKT phosphorylation seems to be the more common mechanism of anti-proliferation of cancer cells in general. Inhibition of AKT signal transduction by naringenin has been observed as the major mechanism of anti-cancer activity in gastric cancer cell lines (Bao et al., 2016; Zhang et al., 2016), a lung cancer cell line along with matrix metalloproteinase (MMP) -2 and 9 inhibition (Chang et al, 2017), and a leukemia cell line along with inhibition of p53 (Park et al., 2008) in recent findings. These findings may suggest that the action of naringenin on cancer cells may not be limited to be through a single signaling pathway, nor is it one-directional.

1.3 Cyclodextrin

1.3.1 Cyclodextrin Chemistry and Applications

Cyclodextrins are conical, truncated compounds that consist of α-1,4 glycosidic-linked glucopyranose units in the C1 conformations (Figure 2). They are produced by intramolecular transglycosylation of starch, catalyzed by a bacterial enzyme, cyclodextrin glycosyltransferase

(CGTase) (Martinez Mora et al., 2012). Cyclodextrins exist in different sizes depending on the number of glucopyranose units and are confirmed to require six and above units in a ring to be stable (Sundararajan & Rao, 1970). A Greek letter denotes the number of glucose; α- is for six units, β- for seven units, γ- for eight units and so on. The number of glucose molecules on the ring provides each type of cyclodextrins unique characteristics by affecting chemical and

42 physical features such as solubility, cavity size, molecular weight, diffusion constant, rigidity of the structure, crystalline water content, and resistance to enzymatic hydrolysis (Szetijli, 1998;

Mazzobre et al., 2011; Bender& Komiyama, 1978; Loftsson & Brewster, 2010).

A cyclodextrin molecule has a hydrophobic cavity and a hydrophilic external surface. In an aqueous environment, cyclodextrins spontaneously trap poorly soluble compound inside the hydrophobic cavity (Schematic representation of the reaction presented in Figure 3). This process is called complexation of a guest molecule. The major driving force of the complexation is the release of the excess free energy by the removal of water from the cyclodextrin cavity

(Szetjli, 1998). Since replacement of the water in the hydrophobic cavity of a cyclodextrin with the hydrophobic guest molecule is energetically favored, when a molecule that is less polar than water collides with the cyclodextrin in an aqueous environment, the water in the cavity readily escapes, leaving part of or the whole guest molecule to reside within the cyclodextrin molecule.

In some cases, two or three cyclodextrin molecules can contain one guest molecule (Mazzobre et al., 2011). The stability of cyclodextrin-guest molecule complex depends on the solvent, geometrical fit, hydrophobicity of the ligand and the host cavity, and specific local interactions between surface atoms (Singh et al., 2002). By exploiting the unique characteristic of each type of cyclodextrins, selective precipitation, where different solvents can be used to separate certain type of cyclodextrins, or selective encapsulation of target molecules have been made possible

(Bender & Komiyama, 1978). Many different variations of parent cyclodextrins (α-, β-, and γ- cyclodextrin) are chemically engineered for specific purposes (Szejtli, 1998), and these modified cyclodextrins have been shown to discriminate between positional isomers, functional groups, and enantiomers (Singh, Sharma, & Banerjee, 2002). This ability to selectively trap target molecules gives cyclodextrins a wide range of application in many fields, including food,

43 pharmaceutical, cosmetics, textiles, packing, separation, environmental protection, and fermentation (Mazzobre et al., 2011; Singh et al., 2002).

One of the classic applications of cyclodextrins is for the improvement of drug functions in the pharmaceutical field (Singh et al., 2002). There are a number of commercialized pharmaceuticals that use cyclodextrins for different purposes, including intravenous solutions, parenteral solutions, ointments, suppositories, sublingual medications, intramuscular solutions, nasal sprays, eye drops, and orally ingested tablets and chewables (Loftsson & Brewster, 2010;

Sharma & Baldi, 2016). The functions of cyclodextrins as an excipient in these pharmaceuticals include an increase in bioavailability, reduction of toxicity and irritancy, improvement of nasal, oral, ocular, rectal, trans-dermal delivery efficiencies, and controlled release (Uekama, Hirayama

& Irie, 1998).

Cyclodextrins have numerous applications in the food industry and have GRAS status. One of the many applications of cyclodextrins in food is for the removal of unwanted tastes and odors

(Singh et al., 2002). Debittering of citrus juices have been successfully achieved by mixing cyclodextrins in the juice to form complexes with bitter compounds, naringenin and limonin

(Konno et al., 1980). The controlled release of food constituents that cyclodextrins can provide is also quite useful for the food industry (Astray et al., 2009). Cyclodextrins were shown to effectively control release of antimicrobial or radical scavenging substances in foods to extend self-life by suppressing the rate of microbial growth and oxidation (Marques et al., 2019; Kfoury et al., 2015). Additionally, cyclodextrins can protect food components that are sensitive to oxygen, light, or heat, and improve shelf-life, and they can improve the nutritional value or other qualities of a food by solubilization of food colorings or vitamins (Astray, et al., 2009). The addition of β-cyclodextrin as a stabilizing agent was shown to retain the volatile aroma

44 compounds during thermal processing conditions. Depending on the thermal property, varying responses of cyclodextrins in the retention efficiency of volatiles was observed (Jouquand,

Ducruet, & Giampaoli, 2004), which may provide opportunities to modify their function by processing temperatures. Cyclodextrins can also be used as processing aids. Removal of cholesterol from animal products can be achieved by mixing cyclodextrins with cholesterol containing foods and removing the aqueous phase which contains the solubilized cyclodextrin- cholesterol complex (Hedges, 1998). Phenolic compounds and polyphenol oxidases in fruit juices can be successfully removed by the addition of cyclodextrins, which aid to prevent the browning reaction by the enzymes and the substrates (Del Valle, 2004).

Similarly, controlled release of cyclodextrins in packaging containing antimicrobial, antioxidative, and insect repelling compounds can improve shelf stability of food products (Chen et al., 2019; Wicochea-Rodríguez et al., 2019). For environmental applications, a variety of modified cyclodextrins, including polymers or cross-linked cyclodextrins, have been used to trap volatile organic compounds or to remove toxic and carcinogenic substances, heavy metals, and other pollutants from water or soil (Sikder et al., 2019).

The unique properties of cyclodextrins provide great value in many applications in a variety of fields. Novel uses of cyclodextrins are actively being explored in many different research fields, and expansion of the use of cyclodextrins and its derivatives in the future is expected.

Figure 2. Chemical structure of a cyclodextrin. Adapted from “A review on cyclodextrin encapsulation of essential oils and volatiles” by Cabral Marques, H.M., 2010, Flavor and Fragrance Journal, 25 (5), p.p.314 Copyright 2010 John Wiley & Sons, Ltd.

Figure 3. Formation of an inclusion complex between a hydrophobic molecule and a cyclodextrin. 1. Displacement of polar water molecules from the apolar cyclodextrin cavity. 2. An increasing number of hydrogen bonds are formed as the displaced water returns to the pool. 3. Reduction of the repulsive interactions between the hydrophobic guest molecule and the aqueous environment. 4. Increase in hydrophobic interactions as the guest inserts itself into the apolar cyclodextrin cavity, Adapted from “A review on cyclodextrin encapsulation of essential oils and volatiles” by Cabral Marques, H.M., 2010, Flavor and Fragrance Journal, 25 (5), p.p.317 Copyright 2010 John Wiley & Sons, Ltd.

1.3.2 Cyclodextrin Complexation Methods

Complexation of cyclodextrins uses water as a dissolution of both cyclodextrins and its guest molecules (Hedges, 1998). Since the driving force of complex formation is the elevated free energy produced by water in the hydrophobic cavity of a cyclodextrin, water is required in any complexation method.

One traditional procedure of cyclodextrin complexation is to stir or shake an aqueous solution containing both cyclodextrins and their guest molecules (Szejtli, 1982). For this method, cyclodextrins are not completely dissolved but is a slurry. The guest molecules are stirred with

46 the cyclodextrins, and heat can be added during the mixing if necessary. The duration of mixing depends on the guest molecule and the intensity of the stirring (Hedges, 1998). When complexation is complete, uncomplexed cyclodextrins can be filtered out, and the filtrate is the complexed solution.

The coprecipitation method has been mostly used in the laboratory for small scale complexation (Hedges, 1998). To allow precipitation of the complex, solubility of the complex needs to be exceeded by first heating the cyclodextrin solution before adding the guest molecules. The guest molecules are stirred in while the mixture is cooling, and the precipitated complex is collected. Alternatively, the guest molecules and cyclodextrins can be added to water and shaken until solubility equilibrium is reached (Cabral Marques, 2010). In a study where ketoconazole (KZ) was complexed with β-cyclodextrin, a 1:1 drug to β-cyclodextrin molar ratio provided 97% of yield, and 1:2 ratio provided 99.9% yield using coprecipitation (Marzouk et al.,

2010).

Another common method of cyclodextrin complexation is kneading. A dough is formed by adding a small amount of water to cyclodextrins, and the guest molecules are added to the dough without any solvent. This method requires special equipment, such as an extruder or a d-blade mixer, and is not usually performed in the laboratory (Hedges, 1998). KZ-β-cyclodextrin complexation yielded 95.6% for kneading method for 1:1 ratio, and 98.9% for 1:2 ratio

(Marzouk et al., 2010), and the complexation efficiency of the kneading method for KZ was comparable to that of the coprecipitation method.

Hot melt extrusion can be considered a kneading method with added heat and pressure. High pressure, high temperature, and shear produced by an extruder is used to encourage the complexation process. Thiry et al. (2015) reported that the viscosity of some of the cyclodextrin

47 mixture became an issue in this processing method. However, cyclodextrins were successfully complexed with itraconazole in presence of a polymer to make a ternary complex (Thiry et al.,

2015). The faster processing and no requirement for solvent evaporation are also suggested as benefits of this complexation method (Bruce et al., 2005; Thiry et al., 2015). Therefore, the hot melt extrusion method may be a good option for large-scale continuous manufacturing of heat- stable compounds (Thiry et al., 2016).

Lyophilization has also been used for preparation of the cyclodextrin inclusion complex. This method involves stirring of cyclodextrins and guest molecules in an aqueous environment and is similar to the stirring method. After the mixture is stirred at room temperature for 24 hours

(Karathanos et al., 2007) the mixture is frozen and dried under the vacuum. It is likely that some, if not all complexation takes place during the stirring, and freeze drying may not contribute much to the complexation. However, this method is suitable for obtaining a dry sample without applying heat, and is therefore suitable for thermolabile guest molecules (Cabral Marques, 2010).

In a study where black pepper oleoresin was used as a guest molecule, the lyophilization method presented a lower complexation efficiency of 79.3% when compared with the kneading method, which provided the complexation efficiency of 90.2% (Ozdemir et al., 2018). Therefore, the lyophilization method may not be the most useful for black pepper oleoresin and the compounds that has similar physical and chemical features to it. The lyophilization may only be useful when a guest molecule is required to be protected from heat exposure, and when the operation cost of freeze-drier can meet the need.

The methods of complexation elaborated on above are based on the same overarching principle. The heat, shear, and mobility of the molecules differ depending on the method used, and these factors are likely to determine the duration, force, and optimal temperature of the

48 processing required until the complexation is completed. The compatibility of the method with a guest molecule needs to be considered to protect the guest molecule during processing. For each specific molecule, experimental determination of the most efficient method of complexation should be performed to determine which complexation method yields the highest percentage of complexation of the cyclodextrins and guest molecules.

1.3.3 Methods of Complexation Verification

Multiple methods can be used for the verification of the cyclodextrin-guest complex formation. Differential scanning calorimetry (DSC) is a common method to verify the formation of a cyclodextrin-guest complex (Karathanos et al., 2007). An endothermic peak for either melting temperature or boiling temperature can be used to identify the guest molecules.

Disappearance of this peak for the guest molecules can be used as evidence for complexation

(Cabral Marques, 2010).

Nuclear Magnetic Resonance Spectroscopy is thought to provide the most direct evidence of complexation (Cabral Marquez, 2010). When a guest molecule is incorporated in to the cyclodextrin cavity, hydrogen atoms inside the cavity (H-3 and H-5) are shielded by the guest molecule (Yang et al, 2013; Figure 4), showing an upfield shift of the resonant frequency. The outer hydrogen atoms remain the same or show only a slight upfield shift, indicating little or no interaction with the guest molecules.

Fourier transform infrared spectroscopy (FT-IR) has been used to obtain evidence of complexation, using shifts of bands of the guest molecule. This method requires the identification of bands specific to the guest molecule. Because of the small proportion of the

49 guest molecule mass in most complexes, altered bands of the included part of the guest molecule may not be presented clearly (Cabral Marques, 2010). However, FT-IR analyses have been utilized in many cyclodextrin complexation studies in combination with multiple other analyses to provide additional support of the complexation verification (Thiry et al., 2017; Ficarra et al.,

2002; Salustio).

Power X-ray diffractometry is widely used in the characterization of the cyclodextrin-guest complex. Empirically discovered characteristic peaks of a complex at two diffraction angles of 5 to 7 and 11 to 12, can be used to identify the inclusion status (Yoshi et al., 1992). When the guest molecule is liquid, X-ray powder diffraction is thought to be most useful method of complexation detection. Since the diffraction pattern is not produced by the liquid, a new crystal lattice indicates that the guest molecule has formed a complex with the cyclodextrin (Cabral

Marques, 2010).

The strength of evidence each analytical method can provide varies. Some of these methods may be used as (semi-)quantitative measure, while others may not. Subsequently, it is best to combine multiple methods to more accurately understand the complexation status and efficiency.

Figure 4. Possible mode of naringenin inclusion by cyclodextrin.

Adapted from “Preparation and characterization of inclusion complexes of naringenin with β-cyclodextrin or its derivative” by Yang et al., 2013, Carbohydrate Polymers, 98(2013), p.867. Copyright 2013 Elsevier Ltd.

Chapter 2. Naringenin Attenuates Metabolic Disturbances in C-26 Cachexia Model

2.1 Abstract

Cachexia in cancer patients leads to poor prognosis and survival. Nearly one-third of cancer-related death is estimated to be from cachexia, yet effective therapies are lacking, and cachexia is often overlooked in clinical settings. Metabolic disturbances such as insulin resistance, elevated inflammation, and accelerated energy metabolism are characteristics of cachexia. In cancer patients, metabolic disturbances are understood to be responsible for the pathogenesis of cachexia. Some animal studies have successfully slowed cancer cachexia development by increasing insulin sensitivity. Other pharmacological approaches have suggested the benefit of targeting metabolic disturbances to slow cachexia development in cancer.

Conversely, in obese animal models, naringenin has been suggested to improve dyslipidemia, insulin sensitivity, and muscle retention through increased locomotor activity. In this study, the metabolism-regulating effects of naringenin in cancer cachexia were explored in a well- established animal model of cancer cachexia. Male CD2F1 mice inoculated with colon-26 adenocarcinoma were used to assess the effect of two percent dietary naringenin on the metabolic disturbances and other markers of cachexia. Food intake, body weight, body composition, grip strength, and insulin tolerance were measured pre-necropsy. Plasma IL-6 and adiponectin and tissue weights were analyzed post-necropsy for the assessment of the severity of cachexia. Interestingly, the two percent dietary naringenin encouraged weight loss and anorexia development in the C-26 model, which is not usually favorable in cachexia. However, naringenin

51 supplementation improved muscle function, insulin sensitivity, inflammatory status, and survival in the C-26 model, suggesting the importance of metabolic regulation in cancer cachexia over body weight retention.

2.2 Introduction

Cancer cachexia is a multifactorial disease characterized by progressive skeletal muscle loss, which cannot be reversed by conventional nutritional means (Argiles et al., 2014). Many factors contribute to the progression of the disease, including changes in metabolic pathways, brain, and other tissues. When the symptoms of cachexia progress, patients develop resistance to antineoplastic therapies, leading to accelerated progression of the disease and decreased survival

(Williams et al., 1999).

Traditional therapies that directly target cachexia include nutritional therapies and the use of pharmacological agents or treatment of depression to improve appetite (Alkan et al., 2016;

Melstrom et al., 2007; Daudt et al., 2012). However, these traditional interventions do not improve survival nor are commonly advised by physicians (Flynn et al., 2018; Dy et al., 2008;

Argiles et al., 2001). Relatively new approaches that target inflammation and metabolic disturbances have shown some benefit to attenuation of cachexia in cancer patients (Morley, von

Haehling, & Anker, 2014). Further advancement of the research in this area is desired to establish a more effective therapy for cancer cachexia.

Naringenin has been studied for its anti-cancer and metabolism-regulating properties

(Erluns, 2004). Many different types of human cancer cell lines have shown anti-proliferative and cytotoxic effects of naringenin through modulation of MAPK or AKT pathways (Kanno et al., 2005; Sabarinathan et al., 2010; Lim et al., 2017; Park et al., 2017; Harmon & Patel, 2004; 52

Bao et al., 2016; Zhang et al., 2016; Chang et al, 2017; Park et al., 2008). Improvements in insulin sensitivity, fasting glucose, lipid profile, and adiposity were observed upon oral supplementation of naringenin in two animal models of metabolic syndrome (Ke et al., 2016;

Mulvihill et al., 2009). Importantly, the lean mass remained unaffected in these studies that observed reductions in adiposity. These observations of anti-cancer and metabolism regulation make naringenin a candidate therapeutic for cancer cachexia treatment. However, whether naringenin posesses the same metabolism regulating effects on cancer cachexia is unknown.

This study aims to investigate whether naringenin has similar metabolism regulating and leanmass protecting effects in a mouse model of cachexia. C-26 is a well-established mouse model that mimics human cachexia conditions, and exhibits body weight loss, skeletal muscle loss, and elevation of IL-6 (Murphy et al., 2012; Talbert et al., 2014). In this study, male CD2F1 mice and Colon-26 adenocarcinoma were used to examine the effect of two percent dietary naringenin on the metabolic disturbances, tissue wasting, and physical functions in cachexia.

2.3 Materials and Methods

2.3.1 Colon-26 Adenocarcinoma Cell Culture

Colon-26 adenocarcinoma cells were cultured in Roswell Park Memorial Institute media

(RPMI 1640) + L-glutamine (Sigma-Aldrich, St. Louis, MO, USA) supplemented with five- percent fetal bovine serum and one percent Penicillin-Streptomycin at 37℃ with five percent

CO2.

2.3.2 Animals, Diets and Experimental Procedures

Twenty-to-28 day old male CD2F1 mice were obtained from Charles River (Wilmington,

MA, USA) and acclimated to the new environment for six days. Mice were individually housed at 22±0.5℃ on a 12-hour light/dark cycle, with free access to food and water. After the acclimation period, mice were randomized by body weight into two diet groups. CON group

(n=21) received a semi-purified diet (D12450J, Research Diets Inc. New Brunswick, NJ, USA,

Table 2), and NAR group (n=23) received control diet supplemented with two-percent naringenin (Sigma-Aldrich, St. Louis, MO, USA) prepared by Research Diets Inc (composition of experimental diets are shown in Table 2). After 13 days of acclimation to the diet, mice in each group were randomized by body weight into no-tumor (-) group and tumor (+) group. The final groups consisted of CON(+) (n=11), CON(-) (n=10), NAR(+) (n=12), NAR(-) (n=11).

Between 13 to 26 days after mice were started on the experimental diets, mice in tumor groups were inoculated with a 1mL 1×106 cell suspension of Colon-26 adenocarcinoma in phosphate buffered saline (PBS), and mice in no-tumor groups were inoculated with 1mL PBS when their body weight reached 18g. Study timeline is shown in Figure 5.

Table 2. Composition of experimental diets.

CON NAR (D12450J) Nutrient g% kcal% g% kcal% Protein 19.2 20 18.9 20 Carbohydrate 67.3 70 66 70 Fat 4.3 10 4.2 10 kcal/g 3.85 3.77 Ingredient g kcal g kcal Casein 200 800 200 800 L-Cystine 3 12 3 12 Corn Starch 506.2 2024.8 506.2 2024.8 Maltodextrin 10 125 500 125 500 Sucrose 68.8 275.2 68.8 275.2 Cellulose, BW200 50 0 50 0 Soybean Oil 25 225 25 225 Lard 20 180 20 180 Mineral Mix S10026 10 0 10 0 DiCalcium Phosphate 13 0 13 0 Calcium Carbonate 5.5 0 5.5 0 Potassium Citrate・1 H2O 16.5 0 16.5 0 Vitamin Mix V10001 10 40 10 40 Chlorine Bitartrate 2 0 2 0 Naringenin 0 0 21.5 0 FD&C Yellow Dye #5 0.04 0 0.05 0 FD&C Blue Dye #1 0.01 0 0 0 Naringenin % 0 2

Figure 5. Timeline of naringenin cachexia study. NAR: naringenin diet, CON: control diet, (+): tumor, (-): no tumor, C-26: Colon-26 adenocarcinoma, PBS: phosphate buffered saline, ITT: insulin tolerance test. The day of C-26/ PBS inoculation was set as day 0. Male CD2F1 mice were randomized by body weight into NAR or CON diet groups from day -29 to -15. The length of the mice on the study diets depend on the time it took each mouse to reach 18g of body weight. Grip strength and echoMRI measurements were made on day -1, 7, and 12 as measurements of muscle function and body composition respectively. Insulin tolerance test was performed on day 11, and necropsy were performed on day 13. Images in the figure were retrieved from https://www.criver.com , https://www.echomri.com , https://www.columbusinstruments.com .

2.3.3 Body Weight and Food Intake

Body weight and food intake of mice were measured daily.

2.3.4 EchoMRI

Body composition of mice was measured by EchoMRI (Houston, TX, USA) at three timepoints: day -1, 7, and 12.

2.3.5 Grip Strength

Mice were acclimated to grip strength test for two weeks prior to measurement. Grip strength of the forelimbs and hind limbs were measured on day -1, 7, and 12. All measurements were taken in triplicate, with at least 5 minutes of rest between measurements for each animal.

2.3.6 Insulin Tolerance Test

Mice were fasted for six hours prior to the start of the insulin tolerance test. Insulin tolerance test was performed on day 11. Blood glucose was monitored at the time points of 0, 15,

30, 45, 60, 90, and 120 minutes after the injection of 0.75 units of insulin. Total insulin tolerance is expressed as area under the blood glucose curve.

2.3.7 Necropsy

Mice were euthanized 13 days after the inoculation of C-26 cells / PBS under isoflurane, followed by cervical dislocation after 6-hour semi-fasting; mice had access to HydroGel

(Cincinnati Lab Supply, Inc., Cincinnati, OH, USA) during the 6 hours prior to euthanasia.

Blood was collected by cardiac puncture, deposited into EDTA-coated blood collection tubes, centrifuged, and the top layer of plasma was collected. Tissues were collected, weighed, and immediately flash-frozen in liquid nitrogen at the site. Plasma and frozen tissues were stored at -

80℃ until further analysis. All procedures were approved by the Institutional Animal Care and

Use Committee at The Ohio State University.

2.3.8 Plasma Analysis

Plasma IL-6 levels were measured by IL-6 Mouse ELISA kit eBioscience (Invitrogen,

Carlsbad, CA, USA) according to the manufacturer’s instructions. Plasma adiponectin levels were measured by Mouse HMW & Total Adiponectin ELISA (Alpco, Salem, NH, USA) according to the manufacturer’s instructions.

2.3.9 Statistical Analysis

All data are presented as mean ± standard deviation. Analysis was performed using

STATA IC 15 (StataCorp LLC. College Station, TX, USA). Significance was determined using two-tailed unpaired student’s t-test and one-way ANOVA with p＜0.05 considered significant.

2.4 Results

2.4.1. Effects of Tumor and Dietary Naringenin on Body Weight and Food Intake

Dietary naringenin significantly reduced the food intake in the tumor group six days after the inoculation of C-26 (Figure 6). Naringenin caused a six-day earlier onset of anorexia in the tumor group. Body weight (tumor weight included) of NAR (+) did not become significantly lower than NAR(-) until four days after the onset of anorexia. The body weight (tumor weight included) of CON(+) became significantly lower than CON(-) 12 days after the inoculation of C-

26/ PBS, which was one day after the onset of anorexia in the control diet group.

Figure 6. Effects of tumor and dietary naringenin on food intake and body weight. Bar graph represents the daily food intake (right axis). Food intake of NAR(+) (n=12) became significantly lower than NAR (-) and CON (+) 6 days after the C-26 inoculation. Food intake of CON(+) (n=11) became significantly lower than CON(-) (n=10) and NAR(+) on 12 days after the C-26 inoculation. On day 13, food intake of CON(+) (3 mice died by the time of measurement on the 13th day, n=8) became lower than the food intake of NAR(+). Line graph represents the body weight (left axis). All body weights include tumor weight. ◎: Body weight of NAR(+) (n=12) became significantly lower than the body weight of CON(+) (n=10) six days after the C-26 inoculation. ＊: Body weight of NAR(+) became significantly lower than the body weight of NAR(-) (n=11) 10days after the C-26/PBS inoculation. ▲: Body weight of CON(+) (n=8, 3 mice died prior to measurement) became significantly lower than the body weight of CON(+) 13 days after the inoculation of C-26/ PBS. Significance between groups were measured by one-way ANOVA, with p＜0.05 considered significant.

2.4.2. Effects of Tumor and Dietary Naringenin on Body Composition

Dietary naringenin reduced the proportion of fat mass regardless of the tumor status by seven days after the C-26/ PBS inoculation (Figure 7-A). Naringenin fed groups continued to have less adipose mass than the control diet groups on 12 days after inoculation. Presence of tumor significantly decreased the absolute adipose mass in NAR(+) and CON(+) from day seven to day 12 after the C-26 inoculation, and adipose mass in NAR(+) group was depleted by day 12

(Figure 7-B).

The proportion of lean mass to body weight was higher in naringenin fed groups seven days after the inoculation of C-26 /PBS regardless of the tumor status. While the tumor did not affect the proportion of lean mass in control-diet fed group, presence of tumor significantly increased the proportion of lean mass in naringenin fed group (Figure 7-C). Increase in the absolute lean mass was observed in control diet groups at different time points depending on the tumor status: from day -1 to day 7 in tumor-bearing mice and from day 7 to 12 in non-tumor mice (Figure 7-D) while neither of naringenin fed groups achieved a significant increase in absolute lean mass at any time point.

A B z 20 B 3.5 x B 18 b yz 3.0 16 b A xy y B y 14 A 2.5 ab a a 12 a 2.0 B 10 1.5 A

8 Fat Mass FatMass (g) 6 1.0 4 x 0.5 Fat Mass/ FatMass/ BodyWeight (%) 2 b 0 0.0 -1 7 12 -1 7 12 C Days after Inoculation D Days after Inoculation 120 18 y

100 x B A y a b ac A B B yz z c AB 80 17 x x

60 a A

40 Mass Lean (g) 16 ab 20

LeanMass/ BodyWeight (%) b 0 15 -1 7 12 -1 7 12 Days after Inoculation Days after Inoculation

Figure 7. Effects of tumor and dietary naringenin on the change in body composition Body composition of mice were obtained by echoMRI at three time points: 1day before, 7 days after, and 12 days after the inoculation of C-26/ PBS. Significance between groups were measured by one-way ANOVA, with p＜0.05 considered significant. ■NAR(+) (n=12), ■NAR(-) (n=11), ●CON(+) (n=11 for day -1 and day 7, n=10 for day 12 since once mouse died prior to measurement), ●CON(-) (n=10). (A) Intergroup comparison of average % fat mass for each day of measurement. (B) Change in average fat mass over time for each group. (C) Intergroup comparison of average % lean mass for each day of measurement. (D) Change in average lean mass over time for each group.

2.4.3. Grip Strength

Presence of a tumor significantly decreased forelimb muscle functions in both diet groups

12 days after C-26 inoculation, but to different degrees (Figure 8-A). The forelimb muscle function of the naringenin-fed group was less affected by the tumor than the control-fed group, providing significantly higher grip strength than the control diet group (Figure 8-A). Presence of tumor decreased hindlimb function only in the control diet group 12 days after the C-26 inoculation, and not in naringenin fed group (Figure 8-B). Dietary naringenin tended to protect against the muscle function decline in both forelimb and hind limb in the presence of a tumor.

B A b B 180 a a ab B 120 160 a a A 100 a b

g) 140 - C 120 80 100 60 80

60 40 Grip Strength Grip (g)

Grip Strength Grip ( 40 20 20 0 0 -1 7 12 -1 7 12 Day after Inoculation Day after Inoculation

Figure 8. Effects of tumor and dietary naringenin on muscle function Muscle function was measured with grip strength of forelimb and hindlimb at three time points: one day before the inoculation of C-26/ PBS and 7 days and 12 days post-inoculation.

Measurements were taken in triplicates and resuls aret is presented as mean±standard ＜ deviation. Significnce between groups were measured by one-way ANOVA, with p 0.05 considered significant. ■NAR(+) (n=12), ■NAR(-) (n=11), ■CON(+) (n=11 for day -1 and day 7, n=10 for day 12 since once mouse died prior to measurement), ■CON(-) (n=10). (A) forelimb grip strength. Data is presented in a negative gram force in tenstion mode. (B) Hindlimb grip strength. Data is prenented in a positive gram force in compression mode.

2.4.4. Effects of Tumor and Naringenin on Insulin Tolerance

Although the effects of neither tumor nor naringenin reached significance on the total insulin sensitivity calculated by the area under the blood glucose curve (Figure 9-A), naringenin improved the blood glucose response to insulin in tumor-bearing mice at 4 time points during the insulin tolerance test: 15, 45, 60, and 90 minutes (Figure 9-C). No effect of naringenin was observed in the blood glucose response at any time point in the non-tumor group (Figure 9-B).

B NAR(-) 60 CON(-) 40 20 A 6000 NAR (+) 0 0 30 60 90 120 b -20 4000 NAR (-) CON (+) -40 2000 ab

-60 BloodGlucose (mg/dL) ab a CON (-) 0 -80 Time (min)

-2000 (mg*min/dL) -4000 NAR(+)

Area Area Under BG Curve C 60 -6000 CON(+) 40 -8000 20 0 0 * 30 60 90 120 -20 * -40 * *

Blood Glucose BloodGlucose (mg/dL) -60 -80 Time (min)

Figure 9. Effects of tumor and dietary naringenin on insulin sensitivity.

Insulin sensitivity was measured on 11th day post-inoculation. 0.75 U of insulin was injected to each mouse at time 0. Results are presented as mean±standard deviation. Significance between groups were measured by student’s t-test, and one-way ANOVA with p＜0.05 considered significant. ■NAR(+) (n=12), ■NAR(-) (n=11), ■CON(+) (n=11), ■CON(-) (n=10). (A) Total insulin sensitivity. Area under the blood glucose curve after injection of insulin was used to represent total insulin sensitivity. (B) Blood glucose response of non- tumor group to insulin (C) Blood glucose response of tumor group to insulin

2.4.5. Effects of Tumor and Dietary Naringenin on Tissue Weights

The presence of the tumor caused an enlargement of the spleen in both tumor-bearing groups, but at different degrees (Figure 10-A). Naringenin significantly suppressed the enlargement of the spleen in the tumor group, indicating the alleviation of the overburden on the spleen by improving the circulating levels of endocrine factors and immune cells induced in response to tumor-induced physiological changes (Bronte & Pittet, 2013). While no effect of either tumor or naringenin was observed in the quadriceps and tibialis anterior muscle proportion, naringenin improved the proportion of gastrocnemius muscle in the tumor group

(Figure 10-A). The presence of tumor significantly reduced the proportion of adipose tissues regardless of the diet (Figure 10-A). In tumor-bearing mice, naringenin significantly reduced inguinal fat and epididymal fat while no significant reduction was observed in brown adipose tissue compared to the control diet group. Naringenin significantly reduced the proportion of all adipose tissues in no-tumor mice (Figure 10-A). Naringenin did not affect the proportion (Figure

10-B) nor absolute mass of the tumor (data not shown).

A B

2.5 C

d c 10 2.0 BC B b 8 b 1.5 A c c AB B B a 6

1.0 free free Tissue BW mass

- a a 4 free free Tissue BW mass A - b b a

0.5 2

% Tumor % % Tumor % 0.0 0 Spleen Quad (L) TA GA Ing Epi BAT Tumor

Figure 10. Effects of tumor and dietary naringenin on tissue weights All tissues were collected on day 13 and weighed during the necropsy. Results are presented as mean±standard deviation. All results are presented as percentage of tumor-free body weight. Significance between groups were measured by one-way ANOVA with p＜0.05 considered significant. ■NAR(+) (n=12), ■NAR(-) (n=11), ■CON(+) (n=8), ■CON(-) (n=10). (A) Percent tumor-free tissue weights. Quad (L): left quadriceps muscle, TA: tibialis anterior muscle, GA: gastrocnemius muscle, Ing: inguinal fat, Epi: epididymal fat, BAT: brown adipose tissue. (B) Percent tumor-free tumor weight.

2.4.6. Effects of Tumor and Dietary Naringenin on Plasma IL-6 and Adiponectin

Most of the plasma IL-6 levels for non-tumor group were below the detection limit, and hence, data is not presented. In tumor-bearing mice, naringenin significantly suppressed plasma

IL-6 levels (Figure 11).

The presence of the tumor reduced the total plasma adiponectin levels regardless of diet.

High molecular weight adiponectin was also reduced by the presence of the tumor, only in naringenin-fed mice (Figure 12-A). The ratio of high molecular weight adiponectin to total adiponectin was elevated in both tumor mice, yet at different degrees (Figure 12-B). Naringenin attenuated the increase of high molecular weight to total ratio of adiponectin in tumor-bearing mice. B a A 2000 20.00 A 90 18.00 1800 B 80 1600 16.00 µg/mL) C 70 1400 14.00

1200 60 12.00 C 50

1000 10.00 6 6 (pg/mL)

- 800 8.00 40 A A 600 6.00 B 30

AdiponectinConc. ( B a 400 b a a Plasma Plasma IL 4.00 20 200 b 2.00 10 0 Serum 0.00 0 Total Adiponectin HMW Adiponectin % HMW/Total Figure 11. Effects of dietary Adiponectin naringenin on plasma IL-6. Figure 12. Effects of tumor and dietary naringenin on HMW ■NAR(+) (n=4), and total adiponectin. ■CON(+) (n=5). ± Results are presented as Results are presented as mean standard deviation. Analytical duplicates were prepared for each samples. mean±standard deviation. Significance between groups were measured by one-way Significance between groups ANOVA with p＜0.05 considered significant. were measured by student’s ■NAR(+) (n=10), ■NAR(-) (n=10), ■CON(+) (n=6), t-test with p＜0.05 ■CON(-) (n=10). (A) Total plasma adiponectin and plasma considered significant. high molecular adiponectin.

(B) Ratio of plasma high molecular adiponectin to total

adiponectin. Data presented in percent.

2.5 Discussion

Metabolic disturbances have been suggested in the pathogenesis and progression of cancer cachexia (Dodesini et al., 2007; Yoshikawa et al., 1999; Asp et al., 2010). Progression of cachexia leads to decreased physical and mental functions, resistance to antineoplastic therapies, and decreased survival (Williams et al., 1999; Argiles et al., 2014). Injection of C-26 cells induced cachexia measured by anorexia and body weight loss in CD2F1 mice as expected in this study. Tumor-bearing mice exhibited metabolic disturbances, inducing insulin resistance and elevation of pro-inflammatory cytokine IL-6. We observed that the two percent dietary naringenin induces anorexia faster than the control diet in tumor-bearing mice. Although body weight loss was observed after the onset of anorexia for both diet groups, the presence of tumor may have affected the observation, since the measured body weight included tumor weight, and tumor weight gain likely to have masked the body weight loss.

Surprisingly, the early onset of anorexia and earlier weight loss did not predict a worse metabolic state or survival of the tumor-bearing mice. To our knowledge, this is the first study that reported the early onset of anorexia and weight loss as non-predictor of the severity of cancer-induced cachexia. While three tumor-bearing mice in the higher body weight group fed the control diet died by the end of the study, all of the naringenin-fed-tumor bearing mice with lower mean body mass survived. Improvement of metabolic markers such as plasma IL-6, adiponectin, and insulin sensitivity in the naringenin group as well attenuated deterioration of muscle mass and function at the end of study support the observation of improved health status in naringenin-fed mice.

Dietary naringenin attenuated the development of insulin resistance and normalized the plasma level of IL-6 in tumor-bearing mice. Since naringenin did not affect the tumor mass, the mechanism of overall improvement in the metabolic markers and survival is not likely from the 68 suppression of tumor growth. Dietary naringenin seems to have protected the muscle function measured by grip strength at the end of the study in tumor-bearing mice, and it reflects our observations of higher activity and greater volitional energy in the naringenin-fed group among the tumor-bearing mice. In a past study, increased locomotor activity and protected quadriceps mass were observed upon supplementation of Naringenin in an obese ovariectomized mouse model (Ke et al., 2016), supporting our observation of protected muscle mass and increased activity in the naringenin-fed mice.

Adipose depots were depleted only in naringenin-fed tumor-bearing mice. The wasting in naringenin-fed tumor-bearing mice seemed to selectively target adipose tissue rather than the lean mass, although depletion of adipose at the end of the study likely began to contribute to the depletion of the lean mass. From the observation of selective adipose depletion in naringenin model, having greater adipose depots at the onset of disease may protect the naringenin-fed group. However, this “obesity paradox” suggested by some studies (Banh et al., 2019; Martin et al., 2013) may apply only to the naringenin-fed group in this study since the greater adipose depots in the control diet group did not lead to a better outcome than the naringenin group with less adipose depots.

Chapter 3. Transition Study: Confection Application of Naringenin to Target Human

Metabolic Syndrome

3.1 Abstract

Our study investigating the effect of dietary naringenin on progression of cancer cachexia in the C-26 mouse model revealed that naringenin elicited protective metabolic effects. Although the results of the study suggest the potential of naringenin to target human metabolic syndrome, the concentration of naringenin used in this study is not easily achievable by the consumption of conventional naringenin-containing foods. We hypothesized that the use of lyophilized naringenin-rich grapefruit juice combined withβ-cyclodextrin in a confection would improve the delivery efficiency and the dose gap of naringenin between animal studies and human consumption. After confirming the concentration of potential naringenin sources of the confection, we explored the methods of food-safe complexation of naringin and naringenin in β- cyclodextrin, using the ability of β-cyclodextrin to entrap hydrophobic molecules inside of its cavity. The stirring method was confirmed to provide high efficacy of complexation for both naringenin and naringin with cyclodextrin by H-NMR and DSC analyses. A preliminary feeding trial was performed using C57BL/6 mice to study the suitability of the gel confections as a naringenin delivery vehicle for future animal bioavailability studies. Because mice did not finish consuming the confection after 2.5 hours, it was confirmed that the confection was unsuitable as a delivery vehicle for a mouse bioavailability study with voluntary consumption, suggesting the need to use oral gavage for mice or to utilize larger animal models.

3.2 Introduction

Naringin and its aglycone naringenin are flavonoids found in grapefruits and tomatoes

(Kawaii et al., 1999; Davies &Hobson, 1981). Naringenin species are known to have antioxidative and anti-inflammatory (Ke et al., 2017; Alam et al., 2014), hypolipidemic and cholesterol lowering (Wilcox, Borradaile& Huff, 1999; Mulvihill et al., 2009), antiatherogenic

(Mir& Tiku, 2015), glucose clearing (Shulman et al., 2011; Ke et al., 2017), and anticancer bioactivities (Wilcox, Borradaile& Huff, 1999; Ke et al., 2016).

In our study investigating the impact of naringenin consumption in the murine c-26 model of cancer cachexia, naringenin was shown to improve metabolic dysregulation, including inflammatory status and insulin resistance. Naringenin also decreased adipose depots in our C-26 model, which is consistent with observations in obese ovariectomized mice (Ke et al., 2016) and a mouse model of metabolic syndrome (Mulvihil et al., 2009).

Despite the reported variety of positive metabolic effects of naringenin, its bioavailability is a limiting factor due to low solubility and slow absorption (Zhang et al., 2013). Many animal models which observed bioactivity of naringenin, including our C-26 study, used high doses of naringenin (Mulvihill et al., 2009; Ke et al., 2017). These high doses are not biologically relevant amounts that humans can achieve by consuming foods such as grapefruit or tomato products. For example, a diet including three percent of naringenin in a mouse study translates to 17 liters of grapefruit juice for human consumption (Ke et al., 2016). Therefore, improvement of bioavailability is a critical step to translate bioavailability studies in experimental animal models to food products for human consumption. We hypothesize that the complexation of naringenin species with β-cyclodextrin in a solute-concentrated gel grapefruit confection will bridge the dosage gap between animal studies and feasible human consumption by improving bioavailability and maximizing the concentration of the bioactive naringenin. 71

Gel confections prove to be an advantageous delivery vehicle due to their familiarity, convenience, and the ability to include high concentration of target compound to achieve the desired bioactive effects (Santiago, Soccol, & Castro, 2017; Dille, Hattrem, & Draget, 2018).

The functional food market is an expanding area which continues to attract consumers (Smith&

Charter, 2010), and use of phytochemicals have been drawing increased attention over the past

25 years due to their wide range of health-promoting applications (Perez-Vizcaino, & Fraga,

2018). As opposed to pharmaceutical therapeutics, using food as a delivery vehicle of a compound with known health benefits is a more accessible and sustainable approach to the consumers because of the nature of the appeal of confection in addition to the expected health benefits (Schmidt, Morrow & White, 1998).

Formulation of a functional confection involves optimization of flavor and nutrient contents and enhancement of bioavailability of the target compounds, naringenin and naringin. In grapefruits, naringenin is present as a glycoside. This form of naringenin is reported to have lower bioavailability than the aglycone naringenin, and not many studies have explored the bioactivity of the compound (Felgines at al., 2000; Purushotham, Tian & Belury, 2009). Ficcara et al. (2002) showed the successful complexation of both naringenin and naringin with β- cyclodextrin. Cyclodextrin is a cyclic carbohydrate with a hydrophobic cavity which can entrap hydrophobic compounds to improve solubility. Since improved delivery efficiency is one of the key processes of functional food development, complexation of naringenin with cyclodextrin has the potential to improve the bioavailability by increasing the solubility. The magnitude of solubility improvement of naringenin by complexation is reported to be up to 500-fold (Shulman et al., 2011). In an animal study, a 7.4-fold increase in the bioavailability of naringenin was observed when complexed with hydroxypropyl-β-cyclodextrin (Shulman et al., 2011). If the

72 same level of increase in the bioavailability can be achieved in grapefruit juice, the 17 liters of graprfruit juice would decrease to 2.3 liters for human to reach the same level of dosage as the animal study that used three percent of dietary naringenin.

Complexation of naringenin with cyclodextrin and the use of grapefruit juice may provide another benefit to the confection: improvement of the palatability of a bitter naringenin- containing product. Like many other flavonoids in natural forms (Drewnowski & Gomez-

Carneros, 2000), the bitterness of naringin may cause low palatability. However, complexation of naringenin may resolve the problem by masking the bitterness of naringenin species in the confection. Indeed, debittering processes using cyclodextrins have been employed by grapefruit product manufacturers as a means of product palatability improvement for the past three decades

(Shaw, Tatum & Wilson, 1984; Shaw & Buslig, 1986). Therefore, the use of β-cyclodextrin may mask the bitterness in addition to the improving bioavailability (Szejitli& Szente, 2005). The use of grapefruit juice may also add to the quality of the confection. When bitterness is presented with a citrus flavor, palatability is known to improve (Szejitli& Szente, 2005). Therefore, grapefruit juice as the main component of the confection is expected to improve the palatability of the product by providing a familiar citrus flavor often associated with bitterness.

Few studies have explored the effects of the forms of naringenin species, complexation, and concentration on the bioavailability of naringenin species delivered in functional food.

Exploration of delivery efficiency for the development of functional food would provide a novel approach to a potential improvement of human metabolic syndromes.

3.3 Materials and Methods

3.3.1. Comparison of Naringenin Contents in Naringenin-containing Foods

Star Ruby grapefruits (Citrus paradisi Macfadyen), ruby red pulp free grapefruit juice

(The Kroger Co., Cincinnati, OH), grapefruit juice (Simply Grapefruit), and tomatoes were purchased from local supermarkets. Tomatoes were steam-retorted prior to lyophilization. Raw materials were frozen in a -40℃ freezer for more than 24 hours and lyophilized for 72 hours or until dry. During the lyophilization, the highest temperature the drying chamber has reached was

42 ℃. Lyophilized samples were ground into a powder and stirred in a commercial freezer until analysis.

Naringenin content was determined using Agilent 1100 Series HPLC connected to a photodiode detector (Agilent Technologies, Santa Clara, CA) with naringenin standard obtained from Indofine Chemical Co. (Hillsborough, NJ). For each preparation, 3mL of 70% methanol was added to 0.5g of powdered samples and sonicated for 10 minutes, followed by centrifugation for 10 minutes. The supernatant was collected in a tube, and sonication and centrifugation were repeated total of three times until 9mL of the extract was obtained. The extract was filtered through 13mm, 0.2µm pore nylon filter. 10µL of each sample was injected into HPLC equipped with 3.5µm C18 beads column of 7.5cm length and 4.5mm diameter. HPLC chromatogram was obtained using a flow rate of 1.3mL/min with a binary solvent system containing 0.1% formic acid (Aq) as solvent (A), and 100% Acetonitrile as solvent (B), with the concentrations of solvent (B) 0% at 0min, 20% at 10min, 30% at 12min, 50% at 14min, and 100% at 16min. The chromatogram was obtained at the wavelength of 288nm.

3.3.2. Confection Preparation and Analysis of Naringenin Content

The grapefruit confection formula was adopted from a former member of Vodovotz lab

(Niezgoda, 2015. Table 3.) and the procedure was modified to improve the ease of processing and the uniformity of ingredient distribution.

Citric acid water of pH 3.4 was prepared using a stock prepared from granulated citric acid (Tale & Lyle, Hoffman Estates, IL). Half of the sucralose-based non-caloric sweetener

(Apriva™, The Kroger Co., Cincinnati, OH) was mixed with sample powder to prevent clumping at the later mixing step. Remaining sucralose-based sweetener was dissolved in the citric acid water and heated until it reached a rolling boil. The mixture was removed from heat, and agar powder (TIC Gums, Belcamp, MD) was stirred in, and the mixture was returned to a boil and cooked for 5 minutes. Thickened agar mixture was poured onto the sample powder + sweetener mixture in an electric blender, and blended. The mixture was deposited into molds and cooled at room temperature until solidified in a sealed container.

Naringenin content of the confection was analyzed using the same procedure as in section

3.3.1. The confection was flash frozen in liquid nitrogen and ground into smaller pieces using mortar and pestle as a pretreatment for extraction.

Table 3. Grapefruit confection formula. Grapefruit Confection Formula Weight %

Water+ citric acid (pH3.4) 40%

Grapefruit Powder 54% Sucralose sweetener 4% Agar 2% Total 100%

3.3.3. Confection Preparation for Animal Feeding Trial

To study the effect of concentration and types of naringenin species in the confection on the eating behavior and the suitability of the gel confection as a delivery vehicle for a future animal bioavailability study, four different formulation of confection was prepared: control confection (CC), grapefruit confection (GFC), three-percent naringin GFC (GFC-NGIN), and three-percent naringenin GFC (GFC-NNIN). For three-percent spiked confections, equivalent moles of naringenin species to three percent (w/w) naringenin was used. The formula for each confection is shown in Table 4.

Table 4. Grapefruit confection formula for animal

feeding trial.

Weight % GFC- GFC- Group GFC CC NGIN NNIN Naringenin 0.0% 3.0% 0.0% 0.0%

Naringin 6.4% 0.0% 0.0% 0.0% water+ citric 40.0% 40.0% 40.0% 40.0% acid (pH3.4) GF powder 47.6% 51.0% 54.0% 0.0%

Sucralose 4.0% 4.0% 4.0% 4.0% sweetener Agar 2.0% 2.0% 2.0% 2.0%

Sucrose 0.0% 0.0% 0.0% 54.0%

Total 100% 100% 100% 100%

3.3.4. Feeding Behavior Trial of Naringenin Confections

Confections were adjusted to 1.6g per piece before the study. Each mouse in the four groups of C57BL/6 mice (n=3 per group) was singly kept in a cage and fasted for 12 hours prior to the trial. One piece of confection was placed in a cage, and behaviors of mice were monitored by direct observation and manually recorded for 2.5 hours. After the first 30 minutes, lights were turned off for 30 minutes to examine the difference in the behavior between the light and dark environments.

3.3.5. Complexation of Cyclodextrin and Naringenin / Naringin

3.3.5.1 Kneading Complexation of Naringenin / Naringin with Cyclodextrin For kneading preparation, ~ 400µL of 50% ethanol was added to 0.5mmols of β- cyclodextrin (Acros Organics™, Fisher Scientific, Hampton, NH) by drop by drop until the mixture formed a firm paste using pestle and motor. To the paste, 0.5mmols of dry Naringin

(Acros Organics™, Fisher Scientific, Hampton, NH) or naringenin (Indofine Chemical Co.,

Hillsborough, NJ) was added and kneaded for 40 minutes manually. When the mixture started to appear dry, a drop of 50% ethanol was added. The mixture was dried at 60℃ under 28in Hg vacuum for two hours.

3.3.5.2 Stirring Complexation of Naringenin / Naringin with Cyclodextrin For stirring preparation, 0.15mmols of naringenin or naringin and 0.05mmols of β- cyclodextrin was added to 50mL of 25% ethanol and stirred for five days at room temperature.

After the stirring, ethanol was evaporated by boiling the mixture until temperature shifts up to

77 water boiling temperature, and the mixture was cooled to room temperature. The cooled mixture was filtered with 45µm pore filter to remove uncomplexed naringenin. The filtrate was dried at

60℃ under 28in Hg vacuum for two hours.

3.3.6 Analysis of Complexation Efficiency

Complexation efficiency of the samples prepared by kneading method and stirring method was analyzed using two different methods: differential scanning calorimetry (DSC) and proton nuclear magnetic resonance (H-NMR).

3.3.6.1 Differential Scanning Calorimetry (DSC) Differential scanning calorimetry was used to evaluate the complexation status of naringenin and naringin each prepared either by stirring method or kneading method. Two milligrams of each sample were prepared in a crimpled standard aluminum pan in triplicate and subjected to heat ramp of 10℃/min from 25℃ to 280℃ using DSC 2500 (TA Instruments, New

Castle, DE). Endothermic peaks of naringenin (Tm ~255℃, Yang et al., 2013) and naringin (Tm

~163℃, Kanaze, et al., 2006) and their disappearance was used as an indication of complexation.

3.3.6.2 Proton Nuclear Magnetic Resonance (H-NMR) H-NMR was used to evaluate the complexation status of naringenin and naringin each prepared either by stirring method or kneading method. In a vial, 1mg of the sample was dissolved in 0.6mL of 99.9% D2O (MagniSolv™, MilliporeSigma, Burlington, MA) by vortexing.

Dissolved sample was transferred to an NMR tube, and H-NMR spectrum of the sample was obtained using Avance III HD Ultrashield 600MHz (Bruker, Billerica, MA) at 298.0K with an

78 acquisition mode of digital quadrature detection and a pulse program of zgpr for a presaturation of water signals with FID resolution of 0.29Hz.

Change in the chemical shifts of the H-3 and H-5 of cyclodextrin from H-NMR spectrum of uncomplexed β-cyclodextrin was used as an indicator of successful complexation for the samples prepared with stirring and kneading methods.

3.4 Results

3.4.1. Comparison of Naringenin Contents in Naringenin-containing Foods and Confection

The concentrations of naringenin-containing foods are presented in Table 5. Grapefruits and grapefruit juice contained a greater amount of naringenin species than tomatoes. Grapefruit peel was confirmed to contain more naringenin than the flesh or juice.

Table 5. Tentative Identification and concentration of naringenin species in naringenin- containing food Concentration (mg/g) Compound Grapefruit Grapefruit Tomato Whole GF Grapefruit Grapefruit (tentative Juice Confection, Powder Powder Juice Rind ID) Powder, made with (TP) (WGF) Powder, Powder Ruby Red GFP (GFC) yellow (GFR) (GFP) (GFPY) Naringin 4.45±0.38 2.51±0.15 ND 9.50±0.13 3.08±0.03 19.57±0.33 Naringenin ND ND 0.40±0.01 ND ND ND Prunin 0.17±0.01 0.08±0.004 ND 0.23±0.008 0.08±0.01 0.27±0.01 Narirutin 1.66±0.15 0.91±0.06 ND 2.65±0.02 1.39±0.02 3.18±0.10 ND: not detected. WGF consists of seed, caroel, and endcarp of grapefruit. Results are presented as mean ± standard deviation.

3.4.2 Feeding Behavior Trial of Naringenin Confections

None of the mice consumed more than 20% of the confection. The consumed amount was not statistically significant between the groups (data not shown). Significance between groups was measured by one-way ANOVA using STATA IC 15 (StataCorp LLC. College

Station, TX, USA) with p＜0.05 considered significant.

3.4.3 Complexation of Cyclodextrin and Naringenin / Naringin by Stirring and Kneading

In DSC, both naringenin and naringin endothermic peaks completely disappeared for the sample prepared by the stirring method (Figure 13-A, 12-B), indicating high complexation efficiency of β-cyclodextrin with naringenin/naringin. The naringin peak remained in the sample prepared by the kneading method (Figure 13-A), indicating no or inefficient complexation with

β-cyclodextrin. The naringenin peak partially disappeared, indicating inefficient complexation

(Figure 13-B).

H-NMR chemical shifts show greater changes in H-3 and H-5 compared to other protons after the complexation for both stirring and kneading methods (Figure 14; Figure 15). As suggested by Yang et al., (2013), the stretch in a chemical shift at H-3 and H-5 indicates the interaction of protons between cyclodextrin and naringenin/ naringin, hence, successful complexation. This measure is only semi-quantitative and combined with the DSC results, efficient complexation of naringenin/naringin with β-cyclodextrin by the stirring method and partial complexation of naringenin/naringin with β-cyclodextrin by the kneading method is suggested.

Naringin Naringenin

A B

0.4 0.5

0.2

0.0 0.0

-0.2

-0.4 Tm: 163℃ -0.5 -0.6

0.4 0.2 -0.10

Heat Flow (W/g)Heat Flow -0.8 0.0 -0.15 -1.0 -0.2 -0.4 -0.20

Heat Flow (W/g)Heat Flow up) (Exo -1.0 -0.6 Tm: 255℃ -0.25 -0.8

-1.0 -0.30 Physical Mix Physical Mix -1.2 -1.2 Kneading 240 245 250 255 260 Kneading -0.35 o 150 155 160 165 170 Temperature ( C) Stirring -1.5 Stirring -1.4 0 50 100 150 200 250 300 0 50 100 150 200 250 300 Temperature (oC) Temperature (oC)

Figure 13. DSC thermograms of naringenin/naringin β-cyclodextrin complex prepared by stirring and keading methods. (A)Naringin β-cyclodextrin complex. (B) Naringenin β-cyclodextrin complex.

Figure 14. H-NMR Spectrum of β-cyclodextrin and naringenin/ naringin- β-cyclodextrin complex prepared by different methods. (A) Cyclodextrin only (B) Naringin-β-cyclodextrin complex prepared by stirring method (C) Naringenin-β-cyclodextrin complex prepared by stirring method (D) Naringin-β-cyclodextrin complex prepared by kneading method (E) Naringenin- β-cyclodextrin complex prepared by kneading method.

Table 6. Chemical shifts of H-NMR of β-CD protons with and without naringenin / naringin. Protons H-1 H-2 H-3 H-4 H-5 H-6 δ (ppm) d dd t t m m β-CD 4.998 3.5794 3.89 3.5093 3.7831 3.7991 β-CD-NGIN (knead) 4.9847 3.5697 3.8473 3.5048 3.7029 3.775 Δknead NGIN -0.0133 -0.0097 -0.0427 -0.0045 -0.0802 -0.0241 β-CD-Nnin (knead) 4.9836 3.5657 3.8605 3.5001 3.7148 3.7757

Δknead Nnin -0.0144 -0.0137 -0.0295 -0.0092 -0.0683 -0.0234 β-CD-NGIN (stir) 4.9743 3.56 3.8196 3.4972 3.6307 3.756

Δmix NGIN -0.0237 -0.0194 -0.0704 -0.0121 -0.1524 -0.0431 β-CD-Nnin (stir) 4.9821 3.5648 3.8545 3.4999 3.7003 3.7713 Δmix Nnin -0.0159 -0.0146 -0.0355 -0.0094 -0.0828 -0.0278

d, dd, t, and m denote number of peaks. β-CD: beta-cyclodextrin, NGIN: naringin, Nnin: naringenin. Knead: prepared by kneading method, mix: prepared by stirring method. Δ: difference between the chemical shift of uncomplexed β-cyclodextrin.

A B β-CD Protons β-CD Protons 1 2 3 4 5 6 1 2 3 4 5 6 0 0

-0.05 -0.025

-0.1 -0.05

(ppm)

Δδ Δδ -0.15 -0.075

-0.2 Δknead NGIN Δstir NGIN -0.1 Δknead Nnin Δstir Nnin

Figure 15. Change in H-NMR chemical shift of β-CD before and after complexation. (A) Naringin (B) Naringenin

3.5 Discussion

Translation of animal studies to human application requires intensive research and development to ensure efficacy and safety. In this study, bioavailability improvement of naringenin species for future animal bioavailability studies is explored as a part of the transition to the human application.

Ruby red grapefruit juice was confirmed as a good source of naringenin species and is therefore a suitable ingredient of the confection for human consumption after lyophilizing. The prepared confection was confirmed to contain the expected amount of naringenin species, indicating minimal loss of the bioactive during processing.

Complexation of naringenin or naringin with β-cyclodextrin was more efficient when the stirring method was employed. This finding that the stirring method was superior to the kneading method makes scaling up the product to industrial levels more feasible, since stirring is a more accessible processing method at a large scale than kneading, which would require special equipment or greater energy. Although an aqueous gel confection has been suggested as a relevant delivery vehicle in a published study (Hovard, Teilmann

& Abelson, 2015), our preliminary study confirmed that the voluntary ingestion of the agar-based grapefruit confection was not suitable for a bioavailability study in mice. Oral gavage or the use of a larger animal model is recommended for future bioavailability studies. Although direct observation of mice did not discriminate the preference of the confection depending on the formulation, human sensory testing will be a meaningful measure to test the acceptability of the confection, as well as the bitterness masking effect of cyclodextrin. It would also be important to test the effect of the addition of

86 cyclodextrin to the original confection by comparing stabilities and physical properties of these two confections to confirm the suitability of new formula to scale up to human clinical trials. As a pre-translational study, this study has made clear of the next steps to take for the future human application of the confection as a functional food.

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