69 Characterization of Phenotypes Generated by Expression of the Bwa enzyme in Drosophila melanogaster to Develop a Colorectal Cancer Treatment Screen

Abstract

Sphingolipids are a class of bioactive lipids which have been linked to cancer and tumor formation. As such, modulation of sphingolipid metabolism offers opportunities to develop novel colorectal cancer therapeutics. However, due to organismal complexity, determination of treatment efficacy is difficult. As such, a method to reliably screen novel colorectal cancer therapeutics is needed. In this project we utilize the UAS-Gal4 transgene expression system in Drosophila to characterize the effects of expressing Brainwashing (Bwa), an enzyme that promotes tumor formation and cell proliferation. Characterization of phenotypes generated by Bwa expression will aid in future development of a colorectal cancer treatment screen based on phenotypic comparison. It was hypothesized that due to the link between Bwa and cell proliferation, an increase in selected tissue size would be observed. Our results show that Bwa upregulation does cause significant increases in selected tissue size, indicative of cell growth. This provides further evidence that Bwa upregulation can cause cell proliferation or tumorigenesis. However, the phenotypic difference was not as robust as expected, limiting the efficacy of this technique to be used for treatment screening. Despite this limited efficacy, examination of the phenotypes generated by Bwa expression in Drosophila expands upon our understanding of sphingolipid metabolism. Additionally, the statistically significant results provide a proof of concept for development of future treatment screens. Development of such a screen will aid in identification of life-saving colorectal cancer therapeutics.

Index Terms—ACER2, Ceramide, Dacer, Drug, Sphingosine-1-Phosphate

Introduction

Sphingolipids are a class of bioactive lipids that are directly involved in signal transduction and cell proliferation [1]. Changes in sphingolipid metabolism and the enzymes involved have been strongly linked to colorectal cancer [2]. Because of this link to colorectal cancer, regulation of the enzymes involved in sphingolipid metabolism represents a promising opportunity to develop new cancer treatments [3]. However, biological constraints and the number of treatment options make efficient examination of treatment efficacy difficult. Therefore, a means to more adequately screen sphingolipid-targeted cancer treatments is needed. Identification of treatments will allow for regulation of sphingolipid metabolites, helping to control both signal transduction and cell proliferation.

Although many sphingolipids have been implicated in cancer, certain metabolites play larger roles than others [30]. Notably, it has been shown that the ratio of the sphingolipid metabolites sphingosine- 1-phosphate (S1P) to ceramides (Cer) is a key indicator of colon tumorigenesis, with elevated levels of S1P compared to Cer leading to tumor growth [4]. Both S1P and Cer are affected by the activity of the enzyme Human Alkaline Ceramidase 2 (ACER2). Research has shown ACER2 upregulation induces a cancer phenotype by simultaneously increasing the levels of S1P while decreasing the levels of Cer [3], [5], thereby promoting cell division.

However, examination of the sphingolipid metabolic pathway in humans is difficult, as human research is expensive and time consuming [20]. The model organism Drosophila Melanogaster, better known as the common fruit fly, provides an inexpensive and efficient alternative [6]. Many signaling and metabolic pathways found in humans are conserved in Drosophila [7], [8]. Of note is the Drosophila orthologue to the ACER2 enzyme: The Brainwashing (Bwa) enzyme [9]. However, much is unknown regarding the phenotypes generated by Bwa expression in Drosophila. Determination of these phenotypes would allow for future examination of treatment options through phenotypic comparison, with a reversal of the Bwa-induced phenotype indicative of treatment efficacy. The orthology between Bwa and ACER2 indicates that treatments found to regulate Bwa activity are likely to also regulate ACER2 activity.

Thus, this project aims to characterize the phenotypes of Bwa expression in Drosophila melanogaster to support future development of an effective cancer treatment screen. This characterization will be accomplished using the UAS-Gal4 transgene expression system. As the Bwa enzyme is orthologous to the ACER2 enzyme, which is known to induce cell proliferation, we hypothesized that Bwa- expressing populations will show an increase in selected tissue size. Because of the direct link between Bwa and ACER2, identification of the phenotypes generated by Bwa expression will help to develop a comprehensive cancer treatment screen, allowing for identification of life-saving cancer treatments for humans through phenotype comparison.

Background

Sphingolipids are a major class of eukaryotic lipids characterized by having a backbone of sphingoid bases [9]. Discovered in 1874, they were originally thought to be solely structural components of lipid bilayers [10]. However, further research indicated sphingolipids play important roles in many biological processes, such as cell division, differentiation, and cell death [11]. Because of this bioactivity, it is no surprise sphingolipids have been implicated in many conditions, including diabetes [11], cancer [13], and metabolic disorders such as liver disease [14]. Current research indicates that many of these conditions are in part caused by changes in sphingolipid metabolism [4], [31], a tightly regulated process in cells.

Alterations in sphingolipid metabolism lead to an imbalance in the levels of sphingolipid metabolites in cells. This imbalance disrupts many cell signaling pathways, and as such has been linked to many types of cancer, including colorectal tumor formation [13]. Research has shown that ceramide, the central molecule in sphingolipid metabolism, induces antiproliferative responses in cells, such as apoptosis and cell growth inhibition [17]. Although some research has indicated elevated levels of ceramide in certain cancers [4], it is generally accepted that higher levels of ceramide inhibit cell growth. In contrast, lower levels of ceramide, coupled with higher concentrations of other metabolites, have been shown to promote cell division and tumor formation [11]. The sphingolipid metabolites sphingosine-1-phosphate (S1P), ceramide-1-phosphate, glucosylceramides (GlcCer), and lactosylceramides (LacCer) are associated with increased cell proliferation, survival, and migration, all events linked with tumorigenesis [18]. Specifically, it has been shown that the ratio of S1P to ceramide is a key predictor of colon cancer [3]. This ratio of S1P to ceramide is regulated by the human Alkaline Ceramidase 2 (ACER2), which helps convert ceramide to S1P through hydrolysis [19]. This robust link between regulation of sphingolipid metabolite levels and tumorigenesis opens intriguing options for development of cancer therapies focused on regulating sphingolipid metabolite levels [3].

However, despite substantial current research focusing on the biochemical pathways involving sphingolipid metabolism [15], much is still unknown. Understanding these complex biological systems is critical if we are ever to develop effective cancer therapies based on regulation of sphingolipid metabolism. Current understanding is based on the sphingolipid metabolite Ceramide, which forms a sort of biological nexus within the pathway [16]. Ceramide acts as a substrate for the synthesis of many other sphingolipid metabolites, such as ceramide-1-phosphate and sphingosine. Furthermore, ceramide-based signaling intermediates can promote opposing cellular processes, leading to a delicate state of homeostasis [11]. Disruption of this balance, typically caused by defective degradation enzymes, can lead to accumulation of sphingolipid metabolites, triggering pathogenesis [11]. Current research efforts are exploring how regulation of these degradation enzymes can reduce incidences of diseases such as atherosclerosis [31], diabetes, and cancer [13].

Unfortunately, examining the sphingolipid metabolic pathway in humans comes with various hurdles, namely cost, time-constraints, and ethical implications [20]. The model organism Drosophila Melanogaster, otherwise known as the common fruit fly, provides an efficient and effective alternative. Performing research using Drosophila is both cheap and efficient, while being relatively free of ethical concerns. In addition, the genome of Drosophila Melanogaster is 60% homologous to humans, meaning many genes and metabolic pathways are conserved [7], including the sphingolipid metabolic pathway [21]. This homology allows for discoveries made using Drosophila to be used as a foundation for further human research. All these factors make Drosophila an ideal model to study the sphingolipid metabolic pathway.

One such enzyme conserved between humans and Drosophila is the previously mentioned Human Alkaline Ceramidase 2 (ACER2), which regulates the ratio of S1P to Ceramide [19]. The Drosophila ortholog to the ACER2 enzyme is the Brainwashing (Bwa) enzyme [9], named because expression causes abnormality in the corpora pedunculata of the brain [24]. Although the mechanism of action of Bwa is still unclear, with some studies finding contradicting results [24], [43], this orthology between Bwa and ACER2 allows for research performed using Bwa to be applied to ACER2. For example, one could perform an experiment examining the interactions between various drugs and the Bwa enzyme. If it were discovered a drug has inhibitory effects with respect to Bwa, it could be said with reasonable confidence it will have a similar interaction with the ACER2 enzyme.

In addition to the ability to draw parallels between human and Drosophila enzymes, gene expression in Drosophila can be tightly regulated through the UAS-Gal4 transcriptional activation system. This ability allows for easy manipulation of protein and gene expression levels which is critical to understanding specific interactions. The UAS-Gal4 system, derived from the UAS binding domain and associated transcriptional activator Gal4 in yeast [25], allows for spatiotemporal regulation of gene expression in vivo. The system functions by replacing the galactose metabolic genes normally controlled by UAS and Gal4 with a specified gene of interest (GOI) [26]. Various genetic mechanisms such as P-element transposition and gene trap screens help to limit expression of the GOI outside of specified tissues [28], allowing the researcher to select where they would like gene expression to occur. This ability to regulate gene expression in select tissues allows for robust determination of the effects of gene expression in Drosophila. For example, a researcher could use the UAS-Gal4 system to selectively over-express Bwa in the Drosophila midgut, allowing for identification of the effects of altering sphingolipid metabolism in the midgut. This ability, in conjunction with the parallels that can be drawn between Drosophila and humans, allows for many genetic and enzymatic conditions in the sphingolipid metabolic pathway to be examined with relative ease.

Genetic tools like the UAS-Gal4 system help to determine many interactions in complex signaling pathways such as the sphingolipid metabolic pathway in Drosophila. Although regulation of sphingolipid metabolism provides a promising opportunity to develop new anti-cancer treatments, an understanding of the effects and phenotypes generated by expression of the genes and enzymes involved is crucial before development even begins. Understanding the phenotypic expression of enzymes involved in sphingolipid metabolism will help to develop and screen anti-cancer treatment candidates. Drosophila Melanogaster is uniquely suited to characterize these, thereby helping to develop future treatment options for cancer patients.

Methods

Study Design

This experiment characterized the phenotypes generated by expression of Bwa in Drosophila melanogaster to support future development an effective cancer treatment screen. Because of the proliferation inducing nature of Bwa, I hypothesized that upregulating Bwa expression in select tissues would lead to an increase in size. To accomplish this, the UAS-Gal4 transgene expression system was used to upregulate and knock down Bwa expression in the eyes and head of Drosophila. Four Gal-4 driver lines with targets in the eyes and head were crossed with various Bwa-inhibiting or Bwa- inducing genes, as well as a wild-type control. Five days after eclosing, 12 to 15 progenies of each condition were isolated using specified phenotypic markers, and subsequently dissected and imaged. The eye and head sizes of the collected progeny were characterized and compared to the wild-type control. Statistical analysis was performed to determine statistically significant differences between conditions.

Expansion and Isolation of Driver Lines

To begin, the driver lines Ey-Gal4 (II) (Bloomington Drosophila Stock Center 5534) (BAE #316), Ey- Gal4 tm2/tm6b (BAE #900), GMR-Gal4/CyO (BAE #313), and GMR-Gal4/cyO ; UAS-GFP/tm6b (BAE #425) were obtained from the general lab BAE stocks. The Ey-Gal4 lines drive gene expression in the eyes of Drosophila, while the GMR-Gal4 lines drive expression in the eyes and head. Multiple driver lines were selected to minimize variation from off-target effects. It was decided to drive, and thereby characterize, expression in the eyes and head, as both tissues are visible and allow for easy inspection, which is essential for an efficient phenotypic screen. At least 20 flies from each line were transferred to bottles containing 50 mL of glucose media (Archon Scientific, 82% Water, 0.572% Agar, 5.34% Cornmeal, 3.81% Yeast, 7.63% Glucose, monohydrate, 0.48% Propionic Acid, 0.08% Methylparaben, 0.29% Ethanol) and incubated in a 25-degree Celsius incubator. Bottles were plugged with foam plugs (Genesee Scientific, Droso-plugs, Plastic bottle compatible). Each Drosophila line was transferred to fresh bottles every week for the next four weeks. This allowed for rapid expansion of the driver lines’ populations. After three weeks, collection and storage of virgin progeny began to prepare to set up genetic crosses. Virgin females were transferred to 100 wide PS vials containing 15 mL glucose media (Archon Scientific, 82% Water, 0.572% Agar, 5.34% Cornmeal, 3.81% Yeast, 7.63% Glucose, monohydrate, 0.48% Propionic Acid, 0.08% Methylparaben, 0.29% Ethanol) and stored in an 18-degree Celsius incubator. Vials were sealed with 28.5 mm diameter 51-102W cotton balls (Genesee Scientific). Virgin females are identifiable from their lighter coloration, larger size, and presence of the meconium, as opposed to non-virgin females. Use of virgins allows for regulation of gene expression, mitigating the possibility of generating unwanted progeny.

Set-up and Maintenance of Genetic Crosses

Once at least 60 virgins from each of the four driver lines were collected, the genetic crosses were set up. Virgin females from each driver line were crossed with wild-type w1118 males, UAS-bwaORF (MR #92) males, UAS-bwaRNAi (BDSC 29409) males, and bwae02081 (BDSC 18012) males. UAS-bwaORF flies correspond to an Open Reading Frame for Bwa, leading to over-expression. UAS-bwaRNAi is an interfering RNA line intended to suppress expression of Bwa. Bwae02081 is a heterozygous mutant line used to reduce Bwa expression levels by half. Both RNAi and mutant versions of Bwa were used to ensure effective knockdown of the gene. Wild type w1118 flies were used as a control to be compared to.

Fifteen virgin females from each of the four driver lines were transferred to Archon Scientific wide vials containing 12 mL glucose media, along with five males for each of the four specified genes, generating a total of 16 crosses. All crosses were kept in an 18° C incubator. Each set of flies was transferred to new vials three days after setting up, and then once every seven days for the next three weeks to ensure progeny generation. Deceased adult flies were removed using forceps during each transfer to ensure healthy growth of the progeny.

Isolation and Dissection of Desired Progeny

Four weeks following the initiation of the genetic crosses, sufficient progeny had eclosed and were collected. Following collection, the CyO and TM6B phenotypic markers along with sex characteristics were used to select for the desired gene-expressing female progeny. Once isolated, the gene- expressing progeny were transferred to new vials where they were incubated at 18° C for five days.

After incubation, the progeny were anesthetized with CO2 and dissected under a Leica S9i digital stereo microscope. Dissection was performed using forceps to remove the head of each fly. The dissected samples were transferred to a 100-millimeter diameter by 15-millimeter depth agarose plates with 100 microgram/milliliter ampicillin agarose (Fischer Scientific) to allow for easy arrangement for image acquisition. Two images for each sample were taken: one with the eye directly faced at the camera, and one from a head-on view to characterize head size.

Image Acquisition and Quantification

Once arranged on the agarose plates, a Dell Latitude 5430 14-inch laptop was connected to the 10 MP camera associated with the Leica S9i microscope. Images were acquired using the Microsoft Windows 10 Camera Application. Images were saved in the .jpg file format and later converted to the .tiff file format.

Image quantification was performed using the ImageJ software (version 1.53). The lasso tool was used to trace around the exterior of either the eye or head to measure the size in pixels. Measurements were recorded in Microsoft Excel Version 16. Both the eye and head size of each sample was characterized, utilizing both picture angles taken previously, and a scale bar of 0.5 inches was added to each sample image to provide image context.

Data Analysis

Following acquisition, the data was imported into GraphPad Prism (version 9.5.0.). Two scatter plots were made for each driver line, with one detailing measured eye size in pixels and the other head size in pixels. Following this, a statistical analysis was performed. Because of the tendency of the data to be non-normally distributed, as well as the data being recorded in pixel counts, a non-parametric Mann-Whitney test was performed comparing each condition to the control to determine statistical significance. The generated p-value for each condition was placed in a table, allowing for easy comparison. Conditions with a p-value less than 0.05 are denoted with an asterisk in the figure graphs. Additionally, the mean, standard deviation, and percent change from control of each condition was recorded in an excel spreadsheet.

Results

Images and data from each generated Drosophila phenotype were compiled into figures, beginning with the Ey-Gal4/II driver (Fig. 1), followed by the Ey-Gal4 – TM2 driver (Fig. 2), the GMR-Gal4, UASGFP driver (Fig. 3), and the GMR-Gal4/+ driver (Fig. 4). The mean pixel count, standard deviation, percent change, and p-values for the eye and head size of each condition were compiled in Tables I through VII. The data from each condition was obtained through imaging dissected progeny collected from the respective genetic crosses. Phenotypic markers were used in genotype determination.

Overexpression of Bwa using the Ey-Gal4/II driver (Fig. 1) yielded a statistically significant increase from the control in eye size (P = 0.0086) of 107.0% (Table I). Inhibition of Bwa, observed through expressing bwaRNAi and bwae02081 (mutant), indicated no significant increase or decrease in eye size when driven with Ey-Gal4/II. Similarly, no significant change in head size was seen in any condition was seen when driven with the Ey-Gal4/II driver.

TABLE 1:  Eye Size Pixel Counts – Ey-Gal4/II

*Pixel counts are reported as mean +/- one standard deviation

TABLE 2:  Head Size Pixel Counts – Ey-Gal4/II

*Pixel counts are reported as mean +/- one standard deviation

Phenotypic characterization of transgene expression using the Ey-Gal4 – TM2 driver (Fig. 2) indicated a statistically significant increase in eye size when Bwa is over-expressed (105.4%, P = 0.0303) as compared to no Bwa expression. No difference in eye size was observed in Bwa-inhibiting conditions (bwaRNAi and bwae02081). Similar to the Ey-Gal4/II driver, no statistically significant change in head size was observed.

TABLE 3: Eye Size Pixel Counts – Ey-Gal4 – TM2

*Pixel counts are reported as mean +/- one standard

TABLE 4: Head Size Pixel Counts – Ey-Gal4 – TM2

*Pixel counts are reported as mean +/- one standard deviation

Examination of Bwa-overexpression driven with the GMR-Gal4 UASGFP driver (Fig. 3) showed a significant increase in both eye and head size (110.4%, P = 0.0068, and 111.0%, P = 0.0001 respectively) compared to the control. As anticipated, no significant difference was seen in eye size under the bwaRNAi condition (105.7%, P = 0.1782). Unexpectedly, a significant increase in head size was observed under the bwae02081 (mutant) condition (106.2%, P = 0.0049). Examination of the bwaRNAi condition showed no statistical difference in either eye or head size.

TABLE 5: EYE SIZE PIXEL COUNTS – GMR-GAL4 – UASGFP/+

*Pixel counts are reported as mean +/- one standard deviation

TABLE 6: HEAD SIZE PIXEL COUNTS – GMR-GAL4 – UASGFP/+

*Pixel counts are reported as mean +/- one standard deviation

Examining transgene expression of Bwa using the GMR-Gal4/+ driver (Fig. 4) yielded comparable results to the GMR-Gal4, UASGFP driver conditions. As before, Bwa-overexpression showed a significant increase in both eye and head size (109.0%, P = 0.0036, and 110.6%, P = 0.0001 respectively) compared to the control. Additionally, no increase in eye size was observed under the bwae02081 (mutant) condition (105.8%, P = 0.363), yet a statistically significant increase in head size was characterized (107.8%, P = 0.0001). Examination of the bwaRNAi condition indicated no significant difference compared to the control.

TABLE 7: Eye Size Pixel Counts – GMR-Gal4/+

*Pixel counts are reported as mean +/- one standard deviation

TABLE 8:  Head Size Pixel Counts – GMR-Gal4/+

*Pixel counts are reported as mean +/- one standard deviation

Sphingolipids are a class of lipids that are directly involved in signal transduction and cell proliferation [1], and as such, have been strongly linked to colorectal cancer [2]. Due to the link between alterations in sphingolipid metabolism and tumorigenesis [2], modulation of sphingolipid metabolism represents a promising way to develop novel cancer treatments [3]. However, determination of treatment efficacy is hampered by biological complexity and treatment quantity [40]. Thus, this project aimed to support future development of an effective cancer treatment screen by characterizing the phenotypic expression of Brainwashing (Bwa), an enzyme involved in sphingolipid metabolism in Drosophila.

The Bwa enzyme is an alkaline ceramidase that has been linked to cell proliferation and tumorigenesis [8], [24], [41]. Due to this link, it was hypothesized that increasing Bwa expression (bwaORF) would lead to an increase in selective tissue size. This was studied using the UAS-Gal4 transgene expression system [25], [26], to upregulate and inhibit Bwa expression in Drosophila. It was discovered that Bwa over-expression led to an increase in both eye and head size when Bwa expression was targeted towards those areas. However, the generated phenotype was not as robust as expected, thereby limiting its potential to be used as a marker in treatment screens. Despite this limitation, this research helped to lay the foundation for further phenotypic characterization. This foundation will aid in development of a future comprehensive cancer treatment screen, helping to identify life-saving treatments for patients suffering from colorectal cancer.

Phenotypic characterization of Bwa expression patterns indicates that Bwa over-expression does cause a measurable increase in eye and head size (see Fig. 1-4 and Tables I-VIII) when gene expression is targeted to those areas. These findings imply that Bwa over-expression in tissues does cause an increase in either cell count or cell size, both characteristics of tumors and cancer cells [34]. Of the four driver lines used (Ey-Gal4/II, Ey-Gal4 – TM2, GMR-Gal4, UASGFP, and GMR-Gal4/+), the GMR-Gal4 lines (see Fig. 3-4) exhibited larger increases in tissue sizes under Bwa over-expressing conditions. This difference implies the GMR-Gal4 driver lines may have stronger expression characteristics compared to the Ey-Gal4 drivers used. Despite this strength of expression, none of the characterized phenotypes showed as large an increase in tissue size as expected, limiting their viability for use in a treatment screen. However, the statistical significance of the tissue size increase indicates that characterization of Bwa expression patterns in other tissues may be a viable technique that could be used in future treatment screens.

Phenotypic characterization of Bwa inhibiting (bwaRNAi) or Bwa mutant (bwae02081) expression patterns yielded variable results. It was expected that Bwa inhibition, either through bwaRNAi or the Bwa mutant, would yield either a decrease or no change in eye and head size. The results of driver lines expressing bwaRNAi aligned with this hypothesis, as no significant increase in eye or head size was observed in all driver lines (see Fig. 1-4 and Tables I-VIII). However, upon quantifying samples from both GMR-Gal4 driver lines, it was observed that Bwa mutant expressing samples did show a significant increase in head size (see Fig. 3-4). This increase is most likely due to some genetic background effect, possibly caused by the separate development of the two strains of flies over time. To correct this, future comparisons should outcross the bwae02081 (mutant) line with the w1118 control line. This would control for genetic differences, allowing for just the effect of the mutant gene to be examined.

The results of this project are supported by the current literature on Bwa expression and sphingolipid metabolism in Drosophila. The results of this project suggest that alterations in the enzymes involved in sphingolipid metabolism can lead to increased tissue size, suggestive of increased cell growth or proliferation (see Fig. 1-4). This correlates with other studies which show that mutations in sphingolipid regulatory enzymes can affect cell growth and survival in many tissues [21] [24], including the muscles and retinas.

On a larger scale, this project aims to help develop a future cancer treatment screen focused on identifying methods to regulate sphingolipid metabolism. Current research agrees that this is a viable approach, with many studies investigating the use of drugs to target sphingolipid metabolism [35].

Identification of treatments targeting sphingolipid regulation will help to improve clinical outcomes for patients suffering from cancer, diabetes, and other serious diseases [35].

The methodology and study design of this project were robust, but there were various limitations. Specifically, an image tracing tool in the ImageJ software was used to quantify pixel counts in samples. Select samples were lower in contrast than others, making it difficult to determine tissue borders in some cases. Care was taken to ensure accurate measurements, but this quantification method did increase the risk of human error influencing specific pixel counts.

Completion of the project shows that characterization of Bwa expression patterns may be a viable method for developing an effective treatment screen. This project serves as a proof of concept for further development of treatment screens based on Bwa expression patterns. It is notable that a Drosophila-based treatment screen would generally allow for identification of human therapeutics, as much of the sphingolipid metabolic pathway is conserved between humans and Drosophila [7], [8], [39].

Although the generated phenotype was not as drastic as other generated Drosophila phenotypes [32], this project showed that Bwa over-expression does cause a measurable increase in tissue size. This increase, along with no significant change seen under bwaRNAi conditions, implies that treatments targeting Bwa inhibition could be screened based on phenotypic comparison. In this scenario, Bwa over-expressing flies would be grown on selected treatments. If no increase in tissue size compared to the control was observed, it would imply that said treatment has Bwa inhibiting effects.

In addition to being a proof of concept for treatment screen development, the measurable increase in eye and head size caused by Bwa over-expression implies a certain degree of cell growth. Although cell counts were not performed, this observation supports the link between Bwa over-expression and cell division/tumorigenesis [8], [24], [41]. This link indicates that regulation of Bwa enzyme activity may aid in treatment for colorectal cancer.

Further work focusing on the characterization of Bwa phenotypic expression patterns in the developing wing discs, ovaries, and testes of Drosophila is ongoing. If these results prove significant, work will begin in developing a cancer treatment screen protocol. This will involve growing Bwa- expressing flies on various FDA approved drugs and quantifying any observed phenotypic alterations. This will help to identify potential candidates for drug repurposing.

Additional future work focuses on examining the role Bwa plays in the damage response of Drosophila. Changes in the damage response of organisms have been linked to increased inflammation and tumor formation [33]. Understanding the molecular interactions of the Bwa enzyme will aid in furthering our understanding of tumor formation.

This project aimed to provide a foundation for developing a future colorectal cancer treatment screen based on sphingolipid metabolism modulation. Colorectal cancer is the second most common cancer that affects both men and women [42]. It is the second leading cause of cancer-related death in the world and accounts for 12.6% of all cancer treatment costs [36], [37]. Characterization of Bwa enzyme expression aids in successful development of a cancer treatment screen that would help to identify life- saving colorectal cancer treatments, improving outcomes for anyone who suffers from this disease.

Acknowledgements

Special thanks to Dr. Bruce A. Edgar, PhD, and the Bruce Edgar Lab as well as Dr. Mahi Rahman, PhD, and Chloe Kraft. Additional thanks to the Huntsman Cancer Institute (HCI) and the National Institutes of Health (NIH) Grant R35 GM140900 for resources and funding. Additional thanks to the Undergraduate Research Opportunities Program for funding and support.

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