Evaluation of SOAT1 Protein As a Potential Drug Target in Glioblastoma

Author Claudia Wöß

Submission Department of EVALUATION OF Biophysics

Thesis Supervisor SOAT1 PROTEIN AS A A. Univ.-Prof. Dr. Christoph Romanin POTENTIAL DRUG Assistant Thesis Supervisor TARGET IN Mag.a Dr.in Sabine Spiegl-Kreinecker

GLIOBLASTOMA CELL October 2019

LINES

Master’s Thesis to confer the academic degree of Master of Science in the Master’s Program Molecular Biology

JOHANNES KEPLER UNIVERSITÄT LINZ Altenberger Straße 69 4040 Linz, Österreich jku.at DVR 0093696

SWORN DECLARATION

I hereby declare under oath that the submitted Master’s Thesis has been written solely by me without any third-party assistance, information other than provided sources or aids have not been used and those used have been fully documented. Sources for literal, paraphrased and cited quotes have been accurately credited.

The submitted document here present is identical to the electronically submitted text document.

Place, Date Linz, 17.10.2019

Signature

Danksagung

An dieser Stelle möchte ich mich bei all jenen bedanken, die mich während meiner Masterarbeit durch ihre fachliche und persönliche Unterstützung motiviert haben und zur Entstehung dieser Arbeit beigetragen haben.

Mein besonderer Dank gilt Frau Mag.a Dr.in Sabine Spiegl-Kreinecker, die es mir ermöglicht hat in Ihrem Labor an diesem interessanten und aktuellen Thema zu forschen und mich bestmöglichst betreut hat. Ohne die Einblicke und Beteiligung im Laboralltag, die hilfreichen Fragestellungen und die konstruktive Kritik wäre diese Arbeit nicht zustande gekommen. Auch bei ihrem Team, das mich während der Arbeit tatkräftig unterstützt hat, möchte ich mich herzlich bedanken.

Ich bedanke mich bei Univ.-Prof. Dr. Christoph Romanin für die hilfreichen Anregungen und interessanten Ideen während der Erstellung dieser Arbeit und die offizielle Betreuung im Rahmen meines Studiums.

Abstract

Glioblastomas are malignant Grade IV brain tumors characterized as one of the most aggressive and lethal cancer. Standard treatment after surgery includes combined radio- chemotherapy with Temozolomide most commonly followed by adjuvant Temozolomide treatment. However, despite abrasive therapy the median survival time is between 12 and 15 months after initial diagnosis. Hence new treatment strategies are urgently necessary. Metabolic reprogramming is a hallmark of cancer cells. Especially elevated lipid levels have been indicated in gliomas, thus promoting enhanced tumor growth. Oncogenic signaling mainly via the EGFR/PI3K/Akt pathway is known to be responsible for raised lipogenesis, through upregulation of the sterol-regulatory element-binding protein 1 (SREBP-1). SREBP-1 functions as the master transcription factor that controls lipid metabolism. In non-malignant cells SREBP-1 activation is negatively regulated by endoplasmic reticulum cholesterol, thus SREBP-1 is inactivated at high cellular cholesterol levels. Glioblastoma cells preconceived a mechanism to bypass this negative regulation pathway, through the enzyme Sterol O-acyltransferase (SOAT). SOAT1 utilizes cholesterol and long chain fatty acyl-CoA to produce cholesteryl esters, which are than stored in lipid droplets (LDs). Because of this mechanism, intracellular cholesterol is maintained at low levels and SREBP-1 remains active. Since there is already an inhibitor for SOAT1, called Avasimibe, this key enzyme presents as target to suppress glioblastoma growth via inhibition of SREBP-1.

The aim of this thesis was to identify the SOAT1 expression status in low grade and high grade gliomas and to determine if there is a significant difference between those categories. The methods RT-PCR and also real-time qRT-PCR were used for analysis. Moreover, the effect of avasimibe on glioblastoma cell lines was monitored by a cell viability assay (EZ4U). Additionally, lipid droplets were stained with BODIPY493/503 and morphological features for apoptosis were investigated under the microscope. The results revealed a significant higher SOAT1 expression in high grade gliomas in comparison to low grade gliomas. Moreover, metastases that occurred in the brain were also tested and especially the melanoma-derived cell lines showed high SOAT1 expression. LDs could be stained in cells with elevated SOAT1 expression. The cell viability assay demonstrated an IC50 value of 12.5µM in the glioblastoma cell line T98G and downregulation of SOAT1 could be observed. One melanoma metastasis cell line showed an IC50 value of 9.1 µM and high apoptosis after treatment with avasimibe. Other glioblastoma cell lines were not sensitive to the inhibitor and showed barley a decrease in cell viability. To summarize, SOAT1 is overexpressed in high grad gliomas and therefore a potential target for cancer treatment, but further studies are necessary to validate the inhibitor avasimibe as potential therapeutic strategy.

III

Kurzzusammenfassung

Glioblastome sind bösartige Grad IV Hirntumore die als eine der aggressivsten und tödlichsten Krebsarten gelten. Nach einer operativen Entfernung besteht die Standardbehandlung aus Strahlentherapie und Chemotherapie mit Temozolomide. Trotzdem liegt die durchschnittliche Überlebensrate nach der Erstdiagnose nur bei 12 bis 15 Monaten. Deshalb ist es notwendig neue Therapieansätze zu finden. Veränderte metabolische Stoffwechselvorgänge sind ein Hauptmerkmal von Krebszellen, wobei ein besonders erhöhter Lipidstoffwechsel im Glioblastom gefunden wurde, welcher für ein starkes Wachstum verantwortlich ist. Onkogene Signalnetzwerke, speziell der EGFR/PI3K/Akt Weg, verursachen erhöhte Lipidsynthese durch Verstärkung des SREBP-1 Transkriptionsfaktors, der wiederrum Hauptregulator des Lipidstoffwechsel ist. Die Aktivierung von SREBP-1 wird durch negative Rückkopplung über intrazelluläres Cholesterol geregelt, weshalb es bei erhöhten Werten zu einer Inaktivierung von SREBP-1 kommt. In Krebszellen wird diese negative Regulation durch das Enzym Sterol O-acyltransferase (SOAT) umgangen, welches Cholesterol verestert und in Fetttröpfchen speichert. Dadurch ist es möglich, dass intrazelluläres Cholesterol niedrig bleibt und SREBP-1 nicht inhibiert wird. Zusätzlich dienen die Fettvesikel als Energiereservoir. Da es bereits einen Inhibitor (Avasimibe) für das Enzym SOAT1 gibt, besteht die Möglichkeit eine Hemmung von SOAT1 und damit eine Erhöhung von Cholesterol in der Zelle zu bewirken, wodurch SREBP-1 inaktiviert wird und das Tumorwachstum gehemmt wird.

Das Ziel dieser Masterarbeit lag darin den SOAT1 Status in hochgradigen und niedriggradigen glialen Hirntumoren festzustellen und zu überprüfen, ob ein signifikanter Unterschied vorliegt. Verschiedene Metastasen, die aus Hirngewebe isoliert wurden, sind ebenfalls überprüft worden. Die Analyse erfolgte mit RT-PCR und quantitativer RT-PCR. Die Auswirkung von Avasimibe auf die Zelle wurde mittels des Zellvitalitättests (EZ4U) untersucht. Die Färbung von Lipidvesikel mit BODIPY493/503 wurde in den Zelllinien mit hoher SOAT1 Expression erfolgreich getestet. Die Resultate zeigen eine signifikant höhere SOAT1 Expression in hochgradigen Tumoren. Besonders in Melanom Metastasen wurden ebenfalls hohe SOAT1 Werte beobachtet. Das Glioblastom T98G zeigte einen IC50 Wert von 12,5 µM. Bei einer getesteten Melanom Zelllinie konnte ein IC50 von 9.1 µM bestimmt werden und starke Apoptose wurde beobachtet. Andere Glioblastome ließen keine Reaktion auf den Inhibitor erkennen. Zusammenfassend zeigt sich, dass SOAT1 ein potentielles Ziel zur Behandlung des Glioblastoms darstellt da eine hohe Expression vorliegt, jedoch der Inhibitor Avasimibe genauer getestet werden muss, weil einige aggressive Zelllinien keine Sensitivität zeigen.

Table of Contents

1. Introduction ...... 1 1.1. Classification of central nervous system tumors ...... 1 1.2. Lipid metabolism in cancer cells ...... 5 1.2.1. Sterol regulatory element-binding protein SREBP-1 ...... 12 1.2.2. Sterol O-acyltransferase (SOAT) ...... 15 1.2.3. Lipid droplets (LDs) ...... 18 1.3. Avasimibe (CI-1011) ...... 21 2. Goal of the Master's thesis ...... 23 3. Materials and Methods ...... 24 3.1. Cell culture ...... 24 3.2. RNA-Analysis ...... 26 3.2.1. Isolation of RNA ...... 26 3.2.2. Reverse transcription PCR, RT-PCR ...... 27 3.2.3. Real-time quantitative reverse transcription PCR, qRT-PCR ...... 29 3.3. Cell viability assay (EZ4U) ...... 33 3.4. Effects of the inhibitor Avasimibe ...... 36 3.5. Protein-Analysis ...... 37 3.5.1. Protein isolation ...... 37 3.5.2. Determination of protein concentration ...... 39 3.5.3. Western Blot ...... 40 3.6. Lipid staining assay-BODIPY ...... 42 4. Results ...... 43 4.1. SOAT1 expression ...... 43 4.1.1. Semi-quantitative reverse transcription PCR ...... 43 4.1.2. Real-time qRT-PCR ...... 47 4.2. Cell viability assay ...... 50 4.3. Effect of the SOAT1 inhibitor Avasimibe on GBM cells ...... 56 4.4. Lipid droplet staining assay-BODIPY ...... 60 4.5. Western Blot analysis of SOAT1 and SREBP-1 ...... 63 5. Discussion ...... 69 6. References ...... 72 7. List of figures ...... 92 8. List of tables...... 92 9. Appendix ...... 93

Abbreviation aA Anaplastic astrocytoma III AA arachidonic acid ABC ATP-binding cassette transporter family (subfamily A-G) ACAT Acyl-coenzyme A:cholesterol acyltransferase 1 ACC Acetyl-CoA carboxylase ACLY ATP citrate lyase ACSL (1,3,5) Long-chain-fatty-acid-CoA ligase (1,3,5) ADRP Adipophilin / Perilipin-2 AI and AII astrocytoma grade I and II Akt AKT serine/threonine kinase AMPK 5'-AMP-activated protein kinase catalytic subunit alpha-2 aOA Anaplastic oligoastrocytoma III aODG Anaplastic oligodendroglioma grade III ATGL Adipose triglyceride lipase ATRX ATRX chromatin remodeler bHLH-ZIP The basic-helix-loop-helix-leucine zipper BRAF B-Raf proto-oncogene, serine/threonine kinase CD36 Scavenger receptor class B member 1 CE Cholesteryl ester CerS Ceramide synthase CHO Chinese hamster ovary cells CIDE cell death inducing DFFA like effector CNS Central nervous system CoA Coenzym A CR-CSC colorectal cancer stem cell Ct Cycle threshold DGAT Acyl-CoA:diacylglycerol acetyltransferase DMSO Dimethylsulfoxid EGFR Epidermal growth factor receptor EIF2α Eukaryotic Initiation Factor 2 α ER Endoplasmic reticulum FA Fatty acid FASN Fatty acid synthase FCS Fetal calf serum G Glioblastoma GAPDH Glyceraldehyde-3-phosphate dehydrogenase GS Gliosarcoma HGG High grade glioma HIF-1/ HIF-1α Hypoxia-inducible factor 1 HMG-CR 3-Hydroxy-3-methylglutaryl-coenzyme-A reductase HMG-CS Hydroxymethylglutaryl-CoA synthase HSL Hormone-sensitive lipase IC50 Half-maximal inhibitory concentration value IDH Isocitrate dehydrogenase IDOL inducible degrader of the LDLR Insig Insulin-induced gene product VI

LD Lipid droplet LDL Low density lipoprotein LDLR Low density lipoprotein receptor LGG Low grade glioma LXR Nuclear Liver X Receptor LXRE LXR response element MGMT Methylated-DNA--protein-cysteine methyltransferase miR microRNA mTOR Mechanistic target of rapamycin kinase MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide myc MYC proto-oncogene, bHLH transcription factor NADPH Nicotinamidadenindinukleotidphosphat NOS Not otherwise specified OA Oligoastrocytoma grade II ODG Oligodendroglioma grade II PARP Poly(ADP-ribose) polymerase

PGE2 Prostaglandin E2 PI3K Phosphoinositide 3-kinase PL Phospholipid PTEN Phosphatase and tensin homolog Rab Ras-related protein Rab RPLP0/36B4 Acidic ribosomal phosphoprotein P0 RT-PCR Reverse transcription polymerase reaction S1P and S2P Site-1 protease and Site-2 protease SCAP SREBP cleavage-activating protein SCD1 Stearoyl-CoA desaturase-1 SDS Sodium dodecyl sulfate SLC-(1A5 and 25A1) Solute carrier family 1 member 5 and family 25 member 1 SOAT Sterol O-acyltransferase 1 SREBP Sterol regulatory element-binding protein SREs Sterol regulatory elements TAG triacylglycerol TERT Telomerase-Reverse-Transkriptase TMD Transmembrane domain TMZ Temozolomide TP53 Tumor protein p53 UTR Untranslated region WHO World health organization

VII

1. Introduction

1.1. Classification of central nervous system tumors

Classification of central nervous system (CNS) tumors relies on the guidelines of the WHO released in 2016. In contrast to the guidelines of 2007, molecular parameters were added to histology to define tumor entities. The new classification allows assigning tumors to molecular distinct subgroups, all of which presenting a different course of disease. In the absence of molecular testing tumors are designated as NOS (not otherwise specified). This indicates that an additional molecular workup is required. [2]

The WHO grading is divided into four categories, based on histopathological findings. Histological characteristics include atypia, anaplasia, mitotic activity, microvascular proliferation and necrosis. Low-grade gliomas (LGG) include WHO grade I and II tumors. WHO grade I are benign tumors and WHO grade II indicate increased cellularity and atypia. Malignant transformation of tumors promotes the attribution to high-grade gliomas (HGG), which comprise the WHO grade III and grade IV tumors. WHO grade III tumors demonstrate nuclear atypia and mitotic activity, while grade IV is additionally identified via micro vascular proliferation and/or necrosis. [3]

Pilocytic astrocytoma Pilocytic astrocytoma belong to the low grade glioma and have a WHO I grading, hence they have low proliferation potential and can often be cured by surgery.[2] The appearance is frequent in younger patients in the cerebellum. Genetically pilocytic astrocytomas are characterized by frequent BRAF alterations and lack of IDH and TP53 mutations. [2,5]

Diffuse gliomas According to the 2016 WHO classification of CNS tumors, based on phenotypical and molecular features, all adult diffuse gliomas (astrocytic or oligodendroglial) are grouped together in respect to IDH-mutation and 1p19q co-deletion status (Fig.1). The classification of diffuse gliomas is composed of the WHO grade II and grade III astrocytic tumors, the grade II and III oligodendrogliomas, the grade IV glioblastomas additionally to diffuse gliomas of childhood and midline gliomas. [2]

Figure 1 Overview of adult diffuse glioma a) Histological classification according to the 2016 WHO guidelines of diffuse adult glioma with key molecular alterations, including IDH status and 1p19q status. The Kaplan-Meier survival curves from 1989-2012 are demonstrated for each tumor category. b) The frequency of an ATRX and/or TERT mutation is presented in each tumor subtype (pie chart) in addition to the relative proportion of IDH-TERT-mutant and 1p19q status. c) The methylation status of the WHO 2016 subtypes is displayed. [4]

Diffuse astrocytoma WHO grade II and anaplastic astrocytoma WHO grade III Diffuse astrocytoma and anaplastic astrocytoma are classified into IDH-mutant and IDH-wild type (Fig.1a), whereby the majority of those WHO grade II and III tumors present IDH alterations. Gemistocytic astrocytomas belong additionally as a subgroup to the WHO classification of diffuse astrocytoma, IDH-mutant. [2] Diffuse astrocytoma grade II have a tendency for progression into high grade tumors, like anaplastic astrocytoma and “secondary” glioblastoma. [6]. Another molecular parameter typically found in WHO grad II and III astrocytoma is the intact status of 1p19q.[2,7] Patients with astrocytoma IDH-wild type are in average 52 years old at the time of diagnosis. However, patients with WHO grade III astrocytoma are significantly older, than patients with WHO grade II. In comparison, the IDH-mutant patients are younger when diagnosed, to be specific 36 years in average, with no median age difference between WHO grade II and III.[8] WHO Grade II and III astrocytoma indicate a better prognosis, when the IDH-mutant is diagnosed.[2] The median overall survival in IDH-mutant tumors is 9.3 years in comparison to 1.9 years of patients with IDH-wild type diagnosis.[8] Furthermore, astrocytoma display a difference in the telomere enhanced maintenance regulated via ATRX and TERT (Fig.1b). ATRX and TERT mutations are mainly mutual exclusive.[9,10] Astrocytoma IDH-wild type tumors demonstrate a TERT mutation in 60%, while in comparison 10% indicate an ATRX alteration. The survival statistics are improved in the TERT-wild type classification. Astrocytoma IDH-mutant tumors present a reversed outcome with 78% ATRX mutation and 5% TERT mutation. [8]

Oligodendroglioma The genetic classification of oligodendroglioma requires an IDH gene mutation combined with a 1p/19q co-deletion. [2] The median diagnosis age is 44 years and the median overall survival is 17.5 years. However, patients with WHO grade II tumors are significantly younger than patients with WHO grade III. Oligodendrogliomas are characterized by 94% TERT mutation (Fig.1b). The overall survival is significantly worse in TERT-wild type tumors. [8] Histological oligodendrogliomas appear with nuclei that are round and uniform, additionally to perinuclear halos (‘fried-egg appearance’) and numerous branching vessels (‘chicken-wire’ vasculature). The difference between oligodendroglioma WHO grade II and anaplastic oligodendroglioma WHO grade III is identified by the number of mitoses (>6 six per ten high power fields), microvascular proliferation and necrosis. [11]

Oligoastrocytoma Oligoastrocytoma WHO grade II and anaplastic Oligoastrocytoma WHO grade III have histological components of both oligodendroglioma and astrocytoma.[2,12] Looking at the genotype a majority of these tumors can be classified as either astrocytoma (TP53, ATRX mutation) or oligodendroglioma (1p/19q co-deletion).[12] Therefore, the 2016 WHO guidelines recommend that the designation of oligoastrocytoma NOS is only assigned when molecular testing is not performed. However, there are tumors reported, which present heterogeneity in a subset of tumor tissue with genetic alterations of both astrocytoma and oligodendroglioma, leading to the assumption that there are “true” oligoastrocytomas. [13,14]

Glioblastoma Glioblastomas WHO grade IV (GBM) are the most frequent of all malignant brain and other CNS tumors and are also the most aggressive primary brain tumors with a poor median survival. [8,15] Within the recently updated WHO classification, GBMs are divided into IDH-wild type and IDH-mutant tumors (Fig.1a). Furthermore, the IDH-wild type glioblastoma classification includes the epithelioid glioblastoma, giant cell glioblastoma and gliosarcoma in the WHO 2016 guidelines.[2] GBM IDH-wild type frequently represent the clinically defined de novo or primary GBM, whereas GBM IDH-mutant correspond to the formerly designated “secondary” GBM, which develop from prior lower grade lesions. [16,17] Glioblastoma IDH-mutant patients have a median age at diagnosis of 38 years and a median overall survival of 3.6 years. The IDH-mutant glioblastoma classification is characterized by a high ATRX alteration (63%) and low TERT mutation (12%) (Fig.1b). In comparison, the IDH-wild type glioblastomas have a median diagnosis age of 59 years and the worst prognosis with an overall survival of 1.2 years. A majority of IDH-wild type tumors demonstrates a TERT promoter mutation with 77% (Fig.1b). Only 3% of patients present an ATRX mutation alone, which results in improved survival statistics. [8] Glioblastomas IDH-wild type indicate a MGMT promoter methylation of ~40%, in comparison to ~90% in glioblastoma IDH-mutant. [45,60,61] Frequent molecular aberrations in glioblastoma IDH-wild type include an EGFR amplification in addition to a chromosome 7 gain and a chromosome 10 loss. [21] Glioblastoma IDH-mutant tumors indicate a significant correlation between IDH1 mutation and TP53 mutation and additionally between IDH1 mutation and LOH 19q. EGFR amplification is inverse associated with IDH-mutant GBM, therefore an indicator for primary glioblastoma.[16,17] Furthermore, IDH-mutant GBMs demonstrate chromothripsis with a large number of alternating, intrachromosomal breakpoints. [22]

1.2. Lipid metabolism in cancer cells

Metabolic reprogramming is an emerging hallmark of cancer cells. Alterations in the metabolism are essential to provide energy and biomass for enhanced cell growth and proliferation in neoplastic disease development. [23] An essential metabolic change that affects cancer cells is the alteration of the lipogenic pathway with increased de novo fatty acid synthesis and elevated expression of crucial metabolic enzymes.[24,25]

Lipid classification Lipids are a comprehensive class of biomolecules with a distinct chemical and compositional diversity regarding the structure, location and number of double bonds and chain length. [26] The fatty acyl structure is used as a precursor for the synthesis of many different types of lipids with various functions in the cell. [26,27] Cell membranes can differ in their structural lipid components depending on the organism, cell type or stage of the cell cycle. The major membrane lipids are the sphingolipids and glycerophospholipids with phosphatidylcholine, phosphatidylethanolamine, phosphatidylglycerol and phosphatidylserine.[26,28] Sterols are the essential non-polar lipids of the cell membranes. The main sterol is cholesterol, which affects the membrane fluidity and structure.[28,29] Other lipids that are generated are phosphoinositides, eicosanoids and sphingolipids, which operate in signaling pathways. [30]

Lipid synthesis in mammalian cells The lipid supply is compensated through exogenous (dietary) metabolism, endogenous synthesis or transformation from stored capacity. The main fraction of fatty acids (FA) is delivered via dietary sources in healthy cells.[31] The exogenous lipid uptake into the cell is conducted via the plasma membrane fatty acid transporter CD36. CD36, a class B scavenger receptor, is expressed on various cells and tissues. Ligands of CD36 include long chain FAs, native and oxidized lipoproteins, thrombospondin-1 and amyloid-B.[31] De novo lipid synthesis, is a complex multistep process (Fig.2).[31,32] One of the first pathways to deliver substrate for fatty acid synthesis is glycolysis, which is located in the cytosol. During glycolysis one molecule of glucose is cleaved into two molecules of pyruvate. Pyruvate is actively transported from the cytosol into the mitochondrial matrix via the mitochondrial pyruvate carrier. There the pyruvate dehydrogenase complex decarboxylates pyruvate producing NADH, CO2 and acetyl-CoA. The next step is the insertion of acetyl-CoA into the citric acid cycle. The enzyme citrate synthase facilitates the transfer of the acetyl group to oxaloacetate to produce citric acid (citrate). [32]

Figure 2 Lipid biosynthesis

Schematic representation of the key pathways involved in lipid and cholesterol synthesis, linked to glucose-or glutamine metabolism. In addition, the upregulated signaling pathways of cancer cells and the targets are included in the overview. [25]

Citrate, the precursor for FA synthesis, can be further converted in the citric acid cycle or transported to the cytosol, via the mitochondrial citrate carrier (SLC25A1) in exchange for malat. The process is required, due to the inability of acetyl-CoA to cross the mitochondrial membrane [32,33] ATP citrate lyase (ACLY) is the key cytosolic enzyme that converts mitochondrial derived citrate into acetyl-CoA. ACLY catalyzes in an ATP-dependent reaction the formation of citrate and coenzyme A to oxaloacetate and acetyl-CoA.[34] Acetyl-CoA carboxylase (ACC) promotes the first committed step in fatty acid synthesis. There are two isoforms termed ACC1 (also known as ACCα) and ACC2 (ACCβ). ACC is a multi-domain protein that contains a biotin carboxylase, a biotin carboxyl carrier protein and a carboxyltransferase domain. ACC catalyzes in an ATP dependent reaction the irreversible carboxylation of acetyl-CoA to malonyl-CoA. [31] The key metabolic enzyme that implements the terminal step of FA synthesis is the fatty acid synthase (FASN). FASN operates as a homodimer and contains seven catalytic elements necessary for the reaction of acetyl-CoA and malonyl-CoA to form the 16-carbon saturated FA palmitic acid. The acyltransferase domain brings acetyl-CoA and malonyl-CoA onto the enzyme, followed by a repeated condensation process to elongate the acetyl group by two carbon units derived from malonyl-CoA. [31]

Stearoyl-CoA desaturase (SCD) implements the reaction of monounsaturated FAs from saturated FAs, which build the basic structure for various lipid classes. SCD is an ER enzyme that catalyzes the insertion of the first double bond in the cis-delta-9 position. The main precursor is palmitoyl- and stearoyl-CoA, which is synthesized to palmitoleoyl-CoA and oleoyl-CoA. The monounsaturated FAs are further synthesized to polyunsaturated FAs by fatty acid desaturase (FADS). Polyunsaturated FAs are used as substrate for the synthesis of triglycerides (TAG), cholesterol esters (CE) and phospholipids (PL). [35]

The transport mechanism in the bloodstream is conducted by lipoproteins e.g. LDL, which is transported into the cell via the LDL receptor (LDLR).[25,29] After endocytosis, LDL is processed in the lysosome to free cholesterol.[25] Exogenous uptake and de novo synthesis both contribute to the sustainment of cholesterol levels in the cell. [29] The first step in cholesterol synthesis is the transformation to acetoacetyl-CoA by thiolase 2 from two molecules of acetyl-CoA. The condensation reaction of acetyl-CoA with acetoacetyl-CoA, catalyzed by HMG-CS, yields the product HMG-CoA. The enzyme HMG-CR executes the reduction of HMG-CoA to mevalonic acid, which is synthesized in subsequent reactions to cholesterol.[29] Cholesterol efflux is conducted via the ABC transporter family that are characterized into seven subfamilies (A–G). The ATP-binding cassette transporter A1 (ABCA1) exports phospholipids and cholesterol.[36] The liver X receptors LXRα and LXRβ are ligand activated transcription factors, enabled by a rise in cholesterol levels including oxysterol. [35] Oxysterol binds to LXR in the nucleus and activates the transcription of ABCA1, which transport excess cellular cholesterol outside of the cell. [25]

Nutrient sources for lipid synthesis Glucose is the most important carbon resource for energy generating pathways and lipid synthesis.[32] FAs are esterified to the glycerol-3-phosphate backbone, which is produced in the glycerol-3-phosphate pathway that requires glucose for the synthesis. [35] Glutamine is an additional source for carbon and nitrogen and can therefore be included into the citric acid cycle to generate ATP or to serve as precursor for lipid synthesis. The first step to integrate glutamine into the citric acid cycle is the conversion of glutamine to glutamate by glutaminase. Deamination of glutamate, driven by the enzyme glutamate dehydrogenase, provides the product - ketoglutarate that is introduced into the citric acid cycle [32]

Aberrant lipid synthesis and metabolic reprogramming in cancer Cancer cells have in comparison to non-malignant cells an expanded metabolic need to compensate for the rapid cell division and therefore require biomass and energy. A necessary mechanism to comply with the metabolic alterations is through oncogenic mutations in signaling pathways (Fig.2).[23,25] The oncogenic signaling, of phosphatidylinositol 3-kinase (PI3K) and its downstream targets AKT serine/threonine kinase (Akt) and mammalian target of rapamycin (mTOR), alters the metabolism in cancer cells. The changes enhance glycolytic flux and fatty acid synthesis through activating e.g. hypoxia-inducible factor–1α (HIF-1α) and sterol regulatory element–binding protein (SREBP).[37,38] The key metabolic enzymes of fatty acid synthesis and lipid metabolism are highly expressed in different forms of cancer.[39-65] However, those enzymes are not only regulated via transcription factors in cancer cells. In fact, modification of the enzymes via phosphorylation, acetylation and ubiquitination plays a crucial role in activation, stabilization and degradation during the elevated cancer metabolism. [38,44,45]

ACLY expression is raised in cancer tissue of breast [39], liver [40], lung [41], and bladder [42]. ACLY is controlled by SREBP-1 [25,43] and additionally regulated via the PI3K-Akt signaling pathway. Akt phosphorylates ACLY at the serine 454 position [44] and overexpression of phosphorylated ACLY significantly correlates with tumor differentiation and poorer prognosis in lung adenocarcinoma patients. [41] The ACLY protein is acetylated on three lysine residues in response to high glucose. Acetylation results in an increased stability of ACLY, because of blocked ubiquitylation and degradation. Stabilization of ACLY leads to an increase in lipogenesis, cell proliferation and enhances tumor growth in xenograft studies of lung cancer.[45]

ACC1 (ACCα) is highly expressed in different forms of cancer including breast [46], prostate [47], liver [48], squamous cell carcinoma of head and neck [49] and glioblastoma [50]. At transcriptional level ACC is regulated via SREBP-1 and furthermore a short-term regulation occurs by reversible phosphorylation. ACC is an important downstream target of the AMP-activated protein kinase (AMPK), which phosphorylates ACC and promotes inactivity. [38] Inhibition of ACC promotes suppression of de novo fatty acid synthesis in prostate cancer cells [51,52], breast cancer cells and in non-small cell lung cancer. [53,54]

SCD1 is overexpressed in prostate cancer tissue [55], ovarian cancer tissue [56] and colorectal cancer tissue. SCD1 represents in cancer cells an important role in the monounsaturated FA to saturated FA ratio and the composition of lipid fraction. [55,57] SCD1 inhibition results in a reduction of monounsaturated FA levels, changes in the lipid composition and a reduction in migration and invasion. [55,57]

FASN is elevated in different tumor classifications including breast [58], prostate [59], ovarian [60,61], lung [62] and urothelial carcinoma [63]. In human breast cancer FASN is upregulated at hypoxic conditions, via activation of Akt and HIF-1, subsequently to an induction of SREBP-1 the major regulator of FASN. High FASN expression correlates with poor prognosis of cancer patients. [60,65] Respectively, the inhibition of key metabolic enzymes ACLY, ACC, SCD1 and FASN, in different tumor classifications, demonstrates a significant inhibition of cancer cell growth in vitro and in vivo. Targeting the different enzymes of de novo fatty acid synthesis presents therefore as a potential therapy strategy in cancer treatment.

Metabolic reprogramming of cholesterol homeostasis in cancer Carcinogenesis is a complex process that includes alterations in the cholesterol metabolism and mevalonate pathway.[66-68] The mevalonate pathway enzymes and especially the rate-limiting enzyme HMG-CR, required for cholesterol synthesis [29], contribute to tumorigenesis [66]. Breast cancer patients with enhanced levels of HMG-CR demonstrate poor prognosis and reduced survival. Furthermore, high expression of the mevalonate pathway genes HMG-CS1, mevalonate diphosphate decarboxylase, farnesyl pyrophosphate synthase, and acetoacetyl-CoA thiolase 2 correlate with poor outcome of breast cancer patients. [66] HMG-CR can be inhibited reversible and competitive with statin treatment, however the sensitivity in cancer cells is differential and therefore not eligible for all cancer classifications. [67,68] To exemplify, HMG-CR is upregulated in statin resistant breast cancer cell lines [67] and furthermore variation in HMG-CR regulation of multiple myeloma cells indicates a differential sensitivity to statin induced apoptosis.[68]

The transcription factors SREBP and LXR are the main regulators that increase cholesterol homeostasis in cancer cells. SREBP promotes the expression of the LDLR, which is highly upregulated in different forms of cancer.[69,70] LDLR overexpression leads to an elevation of LDL uptake into tumor cells and to more aggressive behavior, including a higher risk of recurrence [69] and cell migration [70]. Increasing the cholesterol efflux is a promising target in tumor cells, where cholesterol levels are enhanced. Activation of LXR via agonists like T0901317, Withaferin A, and 22(R)-hydroxycholesterol leads to an inhibition in the proliferation of different cancer cell lines. [71,72] Additionally activation of LXR significantly reduces LDLR levels by activating the inducible degrader of the LDL receptor (IDOL).[73] IDOL degrades LDLR through an ubiquitin ligase activity, limiting LDL uptake into the cell, therefore demonstrating anti-tumor effects. [73,74]

Glucose and Glutamine reprogramming in cancer cells The increased glycolytic pathway in cancer cells supplies subsidiary pathways with a carbon source to maintain the high metabolic demand for biomolecules.[23,25,75] The oncogenic activity of Akt enhances the glycolysis by upregulating the expression and translocation of glucose transporters additionally to phosphorylating key glycolytic enzymes e.g. hexokinase 2. Oncogenic Akt and mTOR leads to an elevated expression of HIF-1, which upregulates the GLUT1-4 transporters and hexokinase 2. Furthermore oncogenic Myc cooperates with HIF-1 in the activation process of genes that encode glycolytic proteins. [37] Cancer cells supply intermediates of the citric acid cycle to synthesize proteins, lipids and nucleic acids, therefore compensation is necessary. The process where different intermediates are resupplied into the citric acid cycle is termed anaplerosis. Glutamine plays an important role in the anaplerotic flux, due to its function as nitrogen and carbon donor. [75,76] c-Myc promotes the upregulation of glutaminase and glutamine transporters including SLC1A5 in cancer cells, to synthesis glutamate and subsequently resupply α-ketoglutarate into the citric acid cycle. Tumor growth and short survival times correlated with an elevation of SLC1A5. [76]

Lipid metabolism in glioblastoma Glioblastoma tumor tissue demonstrates high levels of lipids, compared to normal brain tissue, additionally to an elevation of unsaturated FAs and cholesterol esters. [77,78] Cholesterol metabolism and lipid synthesis is linked to EGFR/PI3K signaling in glioblastoma. EGFR amplification and EGFRvIII activating mutation promote increased tumor growth and survival in GBM.[50, 73] To exemplify, U87 EGFRvIII cells differ in their metabolic profile from U87 control cells, with enhanced lipid synthesis, a higher metabolic rate and elevated cell proliferation. [79] Furthermore, EGFRvIII expression leads to an elevation in lipogenesis through PI3K-SREBP-1 mediated upregulation of LDLR.[73] In comparison to normal brain tissue, GBM tissue and cells display upregulated LDLR and an the LDL uptake is 3-to 4-fold increased.[80]

LXR activates the cholesterol efflux transporter ABCA1 and ABCG1 and promotes inhibition of LDLR protein expression via IDOL degradation. Activation of LXR via an agonist is therefore a potential target in GBM treatment.[73,80] In vitro the LXR agonist GW3965 leads to a dose dependent inhibition of growth, a decrease in LDLR and an increase of ABCA1 and IDOL, while in vivo the tumor growth is additionally inhibited by 59%.[73] Similar results are obtained with LXR-623, a partial agonist for LXRα and a full agonist for LXRβ. [80] The LXR-IDOL-LDLR pathway is therefore an interesting target in cancer therapy of GBM.[73]

GBM cells demonstrate that SREBP-1 activity is necessary to maintain cancer cell proliferation and tumor growth via upregulation of ACC, FASN and SCD1.[1] GBM tumor tissue represents a significant higher staining of nuclear SREBP-1, ACC and FASN in comparison to normal brain tissue. Additionally there is a correlation between EGFR-Akt signaling and the SREBP1-ACC- FASN fatty synthesis pathway in clinical GBM samples.[50] FASN status displays a positive coherence to the WHO tumor grade of glioma samples, with high expression in glioblastoma, while non-malignant tissue indicates absence. [81]

ACC1 and ACC2 have similar mRNA and protein levels in U87 and U87 EGFRvIII cells, however ACC1 is in both cell lines the prevailing isoform. Inhibition of ACC leads to a reduction of de novo lipogenesis in both cell lines with a higher sensitivity in U87 EGFRvIII cells.[79] SCD1 is significantly elevated in temozolomide (TMZ) resistant glioblastoma cell lines, while SCD1 knockdown results in an enhanced sensitivity to TMZ. Treatment with the SCD1 inhibitor A939572 and TMZ demonstrates a combined effect in the inhibition of resistant GBM cells. SCD1 could be used as a biomolecular marker in predicting TMZ chemosensitivity. [82] Moreover, SCD1 plays an important role in glioblastoma stem-like cells via the synthesis of unsaturated FAs, which is crucial due to the otherwise toxic accumulation of saturated fatty acids. Treatment of SCD1 with the inhibitor CAY demonstrates promising results in glioblastoma mouse models. [83]

1.2.1. Sterol regulatory element-binding protein SREBP-1

Sterol regulatory element-binding proteins (SREBPs) are master transcription factors that control lipid metabolism, through regulation of genes involved in cholesterol and fatty acid synthesis.[43,84] SREBPs are membrane-bound and belong to the basic-helix-loop-helix-leucine zipper (bHLH-Zip) family class. [84] The structure is composed of two hydrophobic membrane- spanning regions, separated by a short hydrophilic loop of about 30 amino acids, which projects into the lumen of the ER. Both amino- and carboxyl-terminus are inside the cytoplasm. The amino terminus contains the bHLH-Zip region that binds to the DNA and the transactivation domain, while the carboxyl terminus is required for regulatory functions. [84-87]

Three SREBP isoforms are encoded in the mammalian genome termed SREBP-1a, SREBP-1c and SREBP-2. The SREBF1 gene, located on human chromosome 17p11.2, encodes SREBP-1a and −1c. The 5’ ends of SREBP-1a and SREBP-1c are located on separate exons

(exon 1a and exon 1c). SREBP-1a is characterized by a longer NH2- terminal acidic domain in contrast to SREBP-1c. SREBP-2 is derived from the SREBF2 gene on human chromosome 22q13.2.[88] SREBP-1a promotes increased activity compared to SREBP-1c, because of the longer transactivation domain. SREBP-1a regulates genes involved in FA and cholesterol synthesis. The main task of SREBP-1c is the regulation of genes required for FA synthesis. SREBP-2 promotes the expression of genes involved in cholesterol synthesis and uptake. In addition, gene promoters of lipogenic enzyme are stronger activated via SREBP-1a than SREBP-2. [43]

SREBP operates as a transcription factor after a two-step proteolytic cleavage from the 125kDa inactive precursor that is located in the ER membrane. [84,89] The cleaved active N-terminal fragment of 68kDa moves to the nucleus to activate transcription of genes involved in cholesterogenesis and lipogenesis.[43,84] The domain of the bHLH-Zip transcription factor consists of a conserved arginine residue. However, the SREBP gene family possesses at this position a tyrosine residue. Because of the amino acid substitution, the SREBPs bind to the palindromic DNA sequence termed E-box (5′-CANNTG-3′) and to the sterol regulatory element (SRE) sequence (5′-TCACNCCAC-3′). [43,87,90,91]

SREBPs are tightly controlled via the feedback mechanism system of sensing membrane cholesterol levels.[84] During high cholesterol SREBPs are associated with two integral membrane proteins, to be specific with SREBP cleavage-activating protein (SCAP) and insulin- induced gene product (INSIG). Because of this interaction, the transport to the Golgi and the proteolytic cleavage of the precursor is not possible and the complex is retained in the ER membrane (Fig. 3). [92-99]

SCAP is comprised of eight transmembrane helices and seven loops with an interaction between loops 1 and 7, demonstrated in chinese hamster ovary cells (CHO).[92,95,94] The cholesterol binding site in the first loop is necessary to facilitate the sterol-dependent trafficking of the SREBP/SCAP complex. [96] When cholesterol levels increase and cholesterol binds to loop 1, dissociation between loop 1 and 7 occurs, resulting in a conformational change in SCAP. Moreover, this promotes an alteration of the cytosolic loop 6 conformation, where the hexapeptide MELADL is located. [93] The Sec23/Sec24 complex of COPII coat proteins binds to the MELADL sequence in SCAP, which is essential for the translocation. Due to the conformational change, the MELADL sequence is not accessible.[97] Furthermore, INSIG-1 binds to SCAP in a sterol dependent fashion, thereby playing an important role in the retention of the SCAP/SREBP complex in the ER. [98] INSIG-2 binds additionally to the SCAP/SREBP complex, however only when sterol is present. [99] SCAP is additionally regulated via N-glycosylation, which is essential for the trafficking and activation of the complex. The SCAP protein is modified at asparagine (N) position N263, N590 and N641 with three N-linked oligosaccharides in response to glucose.[100]

Figure 3 Activation and cleavage of SREBP-1

High sterol levels keep the SCAP/SREBP complex in the ER membrane tied to Insig. Upon ER depletion the SCAP/SREBP complex transfers to the Golgi. There the precursor is cleaved to the mature form by S1P and S2P. The released N-terminal fragment migrates to the nucleus and activates target genes important in lipid and cholesterol synthesis. [11]

A decrease in ER cholesterol and the subsequent conformational change of SCAP leads to accessibility of the MELADL sequence and an interaction with the subunit of the COPII trafficking complex, thus promoting the movement of the SCAP/SREBP complex from the ER to the Golgi apparatus (Fig. 3). [97] SREBPs are cleaved in the Golgi via Site-1 protease at the loop region, continued by another cleavage executed by site-2 protease in the first membrane spanning region. This results in the release of the N-terminal transcriptionally active region of SREBP. [101,102]

SREBP-1 is highly expressed in different forms of cancer including in glioblastoma [50,73] prostate cancer [103], endometrial cancer [104], breast cancers [105], hepatocellular carcinoma [106,107], ovarian cancer [108] and pancreatic cancer [109]. SREBP-1 in cancer is essential for increased cell proliferation and tumor growth.

SREBP-1 mediated lipogenesis plays an important role in glioblastoma, because it prevents aberrant accumulation of saturated FAs and lipotoxicity, via regulation of SCD1. SREBP-1 knockdown in glioblastoma cells can lead to an increase in phospho-EIF2α providing a clear evidence of ER stress additionally to a significant elevation of cleaved-PARP, which indicates lipotoxicity. GBM cancer cell lines with constitutively activated PI3K/Akt signaling maintain sterol sensitivity. Furthermore, the SCAP dependent activation pathway of SREBP-1 is not altered in GBM cells, because inhibition of SCAP results in a decrease in the SREBP-1 activity. Knockdown of SREBP-1 and SCAP in U87 xenograft leads to a reduction in tumor growth, while SREBP-2 knockdown promotes no significant decline. [110] In vivo GMB tumor growth can additionally be decreased via the inhibitor Fatostatin, that blocks the dissociation from INSIG, followed by a restricted translocation from the SCAP/SREBP-1 complex to the Golgi. [110,111]

Moreover, EGFR-signaling highly activates SREBP-1 by PI3K/Akt in glioblastoma [50] and the SREBP-1 activation is controlled by enhanced glucose uptake and subsequently upregulation of SCAP N-glycosylation. Therefore targeting the SCAP N-glycosylation in EGFRvIII-driven glioblastoma affects the activation of SREBP-1.[112] GBM patients with an EGFR amplification and/or mutation have a positive correlation between SREBP-1 expression and three members of the miRNA-29 family (miR-29a, -29b and -29c). In vitro experiments in glioblastoma cells demonstrate that knockdown of SCAP or SREBP-1 leads to a significant downregulation of miR-29. SREBP-1 binds to the SRE motif in the miR-29 promoters, which is significantly promoted by EGF stimulation. In addition, miR-29 is a negative regulator by binding to the 3’-UTR of SREBP-1 and SCAP mRNAs, leading to an inhibition of expression. Transfection of miR-29 into U87/EGFRvIII xenograft inhibits the GBM tumor growth, prolongs overall survival and leads to a suppression of SCAP and SREBP-1 expression in GBM tumor tissues. [113]

SREBP-1 presents as an important target in cancer treatment, due to its role in lipogenesis and tumor growth. [73,103-109] Because of the complex activation pathway, different therapeutic approaches are possible in developing clinically effective inhibitors. In summary, targeting SREBP-1 can be implemented via the feedback mechanism system of sensing membrane cholesterol levels, targeting the translocation of SCAP/SREBP-1 from the ER to the Golgi, inhibition of SCAP N-glycosylation or via the negative regulator miRNA-29. [84,110-113]

1.2.2. Sterol O-acyltransferase (SOAT)

Sterols exist in all eukaryotic cells.[26] Cholesterol is the major sterol of mammalian cells and plays an important role in membrane fluidity, reinforcement of membranes and diffusion rates. [26,29] Furthermore it is an essential component of lipid rafts and the precursor for steroid hormones. [28,29] Cholesterol is stored in the cell as neutral lipid, in the form of cholesteryl ester, to keep the intracellular cholesterol balance and to prevent the accumulation of cholesterol in membranes and thus cytotoxicity. [114,115] Sterol O-acyltransferase (SOAT) also known as Acyl-CoA:cholesterol acyltransferase (ACAT) is an endoplasmic reticulum enzyme that catalyzes the synthesis of cholesteryl ester. [114] According to the HGNC-database ACAT and SOAT are acronyms for the same gene (HGNC:11177), however the alternative names are widely used and can therefore be confused with acetyl-CoA acetyltransferase 1 (ACAT1, HGNC:93). In this thesis the name SOAT is used for the gene HGNC:11177 as uniform abbreviation.

SOAT uses long-chain fatty acyl-coenzyme-A and cholesterol as substrate, for production of cholesteryl ester and coenzyme-A. [114] There are two human isoenzymes of SOAT. SOAT1 is located on chromosome 1q25, while the position of SOAT2 is chromosome 12q13.[114,116] SOAT1 encodes four mRNA species (7.0, 4.3, 3.6, and 2.8 kb). [117] The main expression of SOAT1 occurs in hepatocytes, neurons, adrenal glands, sebaceous glands and macrophages, but also in other tissues and cell types.[114,118,119] Atherosclerosis is characterized by accumulation of CE in the arterial intima. [115] SOAT1 is highly expressed in macrophage foam cells that are located in atherosclerotic lesions of aorta, but not in smooth muscle cells. [120] SOAT2 is mainly expressed in fetal liver and small intestine.[119] SOAT belongs to the membrane-bound O-acyltransferase enzyme family, which are multi-span membrane proteins with 8–12 transmembrane domains. [121]

Human SOAT1 is a homotetrameric enzyme, demonstrated in CHO cells, [122] with nine transmembrane domains including an active site (His 460) located in the TMD7 (Fig. 4) [123]. On the cytoplasmic side, near the N-terminus, is a hydrophilic segment located with a dimerization domain.[124] SOAT1 includes 3 loops, which are located at the luminal side of the ER and 5 loops at the cytoplasmic side. Mutational analysis in CHO cells indicates that TMD7 and TMD8 have helical coil rich domains with two distinct functional sides. One side operates in substrate binding and catalysis and in contrast the other side is important in subunit interaction. [125] Human SOAT1 demonstrates in CHO cells that the substrate saturation curve of cholesterol is highly sigmoidal and that SOAT1 is allosteric regulated by cholesterol. [126] The activation is based on the stereo specific interactions between cholesterol and SOAT1. Cholesterol is a better activator than oxysterol. [127,128] In addition, oleoyl coenzyme A is the preferential fatty acyl-CoA for SOAT1.[129]

Figure 4 Amino acid sequence of human SOAT1

The nine transmembrane domain model of SOAT1 is demonstrated with the dimerization motif near the N-terminus in the cytoplasm. TMD7 and TMD8 are located in the red rectangle. The green amino acids demonstrate conserved residues in SOAT1, SOAT2 and DGAT1. The large green circle, in TMD7, indicates the active site His-460. [125]

Cholesteryl ester accumulation, in addition to elevated expression of SOAT1, provides cancer cells with a mechanism to sustain high metabolic activity for growth and to reduce the toxic effects of free excess cholesterol.[130-132] In malignant cells the esterification via SOAT1 is furthermore important, because low intracellular cholesterol, inhibits the SREBP-1 negative feedback regulation.[1] This leads to a growth advantage for cancer cells. SOAT1 is highly expressed in pancreatic cancer [130], prostate cancer [131], breast cancer [132] and glioblastoma [1]. Pancreatic cancer tissue demonstrates high accumulation of cholesteryl ester with 60-90%, while in normal tissue the CE levels range around 10-20%. Moreover, the CE levels of 18:1 (e.g. cholesteryl oleate) and 18:2 (e.g. cholesteryl linoleate) are increased. SOAT1 is highly expressed and correlates with poor patient survival, while SOAT2 expression indicates no differences between normal tissues and cancer tissue. [130] High-grade prostate cancer and metastases demonstrate also a significant accumulation of CE in lipid droplets with cholesteryl oleate (18:1) as the main fraction. [131] In vitro SOAT1 knockdown results in a reduction of CE accumulation and a decrease in proliferation, migration and invasion. [130-132] SOAT1 knockdown in orthotopic mouse model of pancreatic cancer promotes significantly smaller tumors, a reduction in metastatic lesions and the CE levels are significantly diminished in the tumor tissue. [130]

The lipid configuration in cerebral tissue can be investigated with the 1 H- and 13C-NMR analysis method. High grade brain tumors demonstrate an increased presence of triglycerides and cholesteryl esters, which correlated to the degree of vascular proliferation, in contrast to normal brain tissue and low grade brain tumors. Healthy brain tissue indicates an absence in CE. Low grade tumors have a similar 1 H-NMR spectra and 13C-NMR spectra to healthy brain tissue, while the spectra reveal a significant presence of CE and triglycerides in glioblastoma and high grade gliomas.[133] In addition, the proton NMR spectra, of lipid extracts from the cerebrospinal fluid, demonstrate cholesterol, CE and choline-containing phospholipids in brain tumor patients, in contrast to patients with motor neuron disease or meningitis. [134]

SOAT1 is highly expressed in glioblastoma tumor tissue, in comparison to LGG patients and healthy brain tissue. In addition, SOAT1 is essential in the esterification of cholesterol and the storage in lipid droplets, which correlated with the tissue of GBM patients. SOAT2 is on the contrary not detected in GBM tumor tissue. Knockdown of SOAT1 in GBM cell lines and primary glioblastoma cells leads to a reduction in cholesteryl ester, diminishes LD formation and the cell viability is reduced. SOAT1 knockdown, in the U87/EGFRvIII and primary GBM orthotopic xenograft intracranial GBM-bearing mice, demonstrates a decrease in tumor growth and a significant longer survival time. Inhibition of cholesteryl ester formation could trigger the SREBP negative feedback loop regulation, through enhancing ER membrane cholesterol. In vitro knockdown of SOAT1 indicates a reduction of the N-terminal cleaved SREBP-1 form and thus a significant repression of SREBP-1 activation. ACC, FASN and SCD1, the downstream targets of SREBP-1, are diminished due to SOAT1 knockdown. Moreover, the de novo lipid synthesis demonstrates a decrease. Retardation of SOAT1, and therefore a reduction of SREBP-1 regulated fatty acidy synthesis, results in a decline in glioblastoma cell growth.[1]

In respect to the mentioned cancer types, SOAT1 overexpression affects tumor aggressiveness and correlates with poor patient survival. The reduction of CE via SOAT1 inhibition impairs cancer adhesion, invasion, migration and leads to a suppression of tumor growth.[130-132] Therefore SOAT1 presents as a viable pharmacologic target for treatment against tumors with increased cholesteryl esters and a highly lipogenic phenotype.

1.2.3. Lipid droplets (LDs)

The synthesis of sterols and fatty acids in the cell metabolism requires chemical energy. The storage in the form of cholesteryl esters and triglycerides in lipid droplets is necessary, for the transformation of the chemical energy to a biological inert form. Hydrolysis and re-esterification of lipid droplets is an important resource in the cell. [136] The esterification of free excess cholesterol to cholesteryl ester and the storage in lipid droplets is mediated by SOAT, while the last step of TAG synthesis is catalyzed by Diacylglycerol O-acyltransferase (DGAT1, DGAT2). [114,136]

Lipid droplets are cytoplasmic, spherical heterogeneous organelles that consist of a core of neutral lipids. The outside of the lipid droplets is characterized by a monolayer of phospholipids, especially phosphatidylcholine and lysophosphatidylcholine with a unique fatty acid composition, including variable ratios of saturated and unsaturated chains.[137] Long-chain-fatty-acid-CoA ligase (ACSL5) and the ceramide synthase (CerS) cooperate with DGAT2 in the synthesis of acylceramide. In addition to neutral lipids, acylceramide can be stored in LDs, via the formation of the ACSL5-CerS-DGAT2 complex on LDs. Inhibition of acylceramide synthesis promotes an increase of ceramide concentration, which leads to augmentation of ceramide-mediated apoptosis. Hence, LDs are necessary for storage of potential toxic biomolecules. [138]

Figure 5 Lipid droplet at the endoplasmic reticulum membrane The picture demonstrates the lipid droplet association at the ER-membrane of macrophages analyzed with freeze- fracture microscopy. Both ER membranes partially surround the lipid droplet. [139]

LD biogenesis occurs in the ER, but the exact mechanism is not fully known. One theory is that after the synthesis of neutral lipids, the transfer into the LDs is facilitated at the endoplasmic reticulum membrane. The synthesis is associated with a cup shaped region of the ER membrane that partially surrounds the droplet (Fig. 5).[139] A second model, analyzed in different organisms, states that neutral lipids are synthesized between the two leaflets of the ER membrane. The accumulation of lipids leads to the formation of a lens or blister, which grows until it buds from the ER. [140-142]

Different proteins are embedded or adherent to the surface of the lipid droplet with various assignments in generation, growth, transport, catabolism and contact to other organelles. [143-149] ADRP is one of the main surface proteins on lipid droplets. Different Rab proteins are located around the LDs, however only in lower ratios than Rab18. Rab18 is essential in regulating the distance between the ER derived membrane and the LDs. [147] ACSL3 facilitates the formation of LDs and regulates the maintenance including local synthesis of neutral lipids.[148] Estradiol 17-beta-dehydrogenase11 promotes LD aggregation and TAG accumulation.[149] Lipid droplets can increase in size trough fusion with other LDs, which is mediated by the Cell death activator protein family (CIDEA, CIDEB and CIDEC). [143]

In contrast to esterification, the stored triglycerides from LDs are enzymatically hydrolyzed by different lipases, in a process termed lipolysis. Adipose triglyceride lipase (ATGL) and hormone- sensitive lipase (HSL) can cleave the first ester bond of triglycerides.[150,151] HSL can further cleave diglycerides to monoglycerides. The monoglyceride lipase breaks down the last ester bond of monoglyceride, resulting in free FAs and glycerol.[151] Both ATGL and HSL can induce lipolysis and located to the LD surface.[150-153] The regulation between the storage of neutral lipids in LDs and the release is necessary to prevent lipotoxicity and ER stress. ATGL overexpression promotes an increase in non-esterified free FAs, resulting in an enhancement of ER stress markers. On the contrary, the expression of ACSL1 induces the storage of neutral lipids in LDs and therefore protect against ER stress.[154] A second path to break down CE and TAG from LDs is via autophagy, also termed lipophagy. Lipid droplets are surrounded by a double-membrane autophagosome, which fuses with the lysosome to facilitate the formation of an autolysomes, where the LDs are degraded.[155]

In inflammatory cells, e.g. mast cells, the lipid droplets play a crucial role in the regulation of arachidonic acid. [156] Arachidonic acid (AA) is a polyunsaturated FA, which serves as a precursor for the synthesis of eicosanoids. [30] LDs in mast cells store AA in the triacylglycerol pool.[156] The necessary enzyme for releasing the esterified AA from the lipid droplets is cytosolic phospholipase A2, which locates to the LD surface to release AA. [157]

Lipid droplets were first observed in 1963 in human mammary carcinoma.[158] Since then elevated accumulation of LDs, accompanied by high levels of cholesteryl esters, have been observed in different cancer types including pancreas [130], prostate [131], breast [132], colon [159] and glioblastoma [1]. LDs are essential for the regulation and storage of fatty acids, in addition to the modulation of cholesterol homeostasis during augmented proliferation in malignant cells.[130,160]. Elevation of intracellular free cholesterol, via inhibition of cholesterol esterification leads to an increase in ER stress and apoptosis. Therefore, the storage of unsaturated FAs in LDs is necessary to protect the cancer cells from polyunsaturated FAs induced oxidative stress and lipotoxicity. Hence, lipid droplets emerge as antioxidant and pro-survival organelles, which protect cancer cells.[160] Patients with colon adenocarcinoma present increased accumulation of lipid bodies (LDs), high expression of cyclooxygenase-2 and prostaglandin E synthase, in addition to an enhanced production of prostaglandin E2

(PGE2).Therefore, lipid bodies operate as cytoplasmic production sites for the lipid mediator

PGE2 in colon cancer.[159] Colorectal cancer patients demonstrate increased levels of lipid droplets in colorectal cancer stem cell (CR-CSC).The subcutaneously injection of CR‐CSC LDsHigh and LDsLow in immune‐compromised mice, results in a distinct tumor growth. The tumorigenic potential of CR-CSC with low levels of LDs leads to smaller tumors. Thus, a higher LD accumulation in CR-CSC cells, facilitates an increased tumorigenic potential.[161]

In glioblastoma patient tissue the accumulation of LDs is highly upregulated in comparison to the WHO grade II-III gliomas. Anaplastic oligodendroglioma present moderate LD levels and in WHO grade II oligodendroglioma and WHO grade II to III astrocytoma the lipid droplets exist infrequently. Grade I pilocytic astrocytoma (PA) demonstrates no LDs. LDs do not occur in the normal brain tissue. In addition, primary glioblastoma orthotopic mouse model indicates high levels of LDs. The overall survival of GBM patients correlates with increased LD accumulation. The amount of lipid droplets significantly correlates with Ki67 positive percentage in GBM. The formation of lipid droplets is blocked through inhibition of cholesterol esterification mediated by SOAT1, which further leads to a suppression of growth. [1]

With regard to the aforementioned tumor entities, LDs are associated with highly aggressive tumor phenotypes. Furthermore, cancer cells with enhanced accumulation of LDs correlate with an advanced disease stage and cancer progression. In contrast, normal tissue lacks an increase in lipid droplets. Accumulation of TAG and cholesteryl ester in LDs serves as energy and biomolecule resource in the elevated growth and proliferation of cancer cells, thus repression of LDs presents as a promising treatment target.[130-132] Moreover, the storage of arachidonic acid in LDs and the increased synthesis of PGE2, establishes a link between inflammation and cancer.[156,159] Additionally, lipid droplets may serve as diagnostic biomarker in the referred cancer tissue. 20

1.3. Avasimibe (CI-1011)

The last 20 years, different SOAT inhibitors have been brought to the market. The numerous inhibitors are distinguishable in their structure, which includes sulfonyl urea based compounds (e.g. CI-1011/avasimibe, PD 138142-15), imidazole/midazoline compounds (e.g. RP-73163) fatty acyl amides (e.g. CI-976, CP113818) and urea based compounds (e.g., DuP128, FR145237, CL 277,082, PD132301-2). [114]

Avasimibe (CI-1011) is an orally bioavailable SOAT inhibitor.[162] Initially, avasimibe was developed for the treatment of atherosclerosis and hyperlipidaemia, since SOAT plays an important role in the accumulation of CE in the arterial intima and in foam cell formation of atherosclerosis.[120,162] Clinical trials with avasimibe, in patients with combined hyperlipidemia and hypoalphalipoproteinemia, demonstrate a reduction in plasma levels of total triglycerides and very low-density lipoprotein cholesterol. However total cholesterol, low-density lipoprotein cholesterol and HDL-C or apolipoprotein B indicate no apparent effect. [163] In addition, when the impact on the progression of coronary atherosclerosis is analyzed, the results demonstrate no favorably effects on lipid profiles or coronary atherosclerosis after the treatment. [164] Another disadvantage is that avasimibe is an inducer of the human pregnane X receptor and promotes the activation of Cytochrome P450 3A4, which is responsible for drug-drug interaction. [165] As a consequence avasimibe was not further pursued as drug for hypercholesterolemia and cardiovascular disease.

However, avasimibe inhibition of SOAT1 demonstrates antitumoral properties in malignant cells, including repression of tumor growth.[1,130,131] Therefore avasimibe has been tested as a cancer chemotherapeutic agent in several different cancer classifications including glioblastoma [1], pancreas [130], prostate [131] and as a chemo-immunotherapy in CD8+ T-cells in melanoma [166].

Avasimibe treatment in pancreatic cancer cells leads to blocked cholesteryl ester accumulation and a decline in LDL uptake. Pancreatic cancer cells are more sensitive to inhibition with avasimibe than normal pancreatic cells. Furthermore, in vitro avasimibe treatment reduces the migration and invasion rates. Avasimibe, in combination with human serum albumin, intraperitoneally injected (15 mg/kg per day) into pancreatic orthotopic mouse models results in a reduction of tumor size, tumor growth rates, LD number and depletion in cholesteryl ester accumulation. In addition, avasimibe treatment facilitates ER stress resulting in apoptosis of pancreatic cancer cells. [130] In vitro avasimibe treatment of prostate cancer cells promotes a significant suppression of cholesteryl ester accumulation, a decline in cell viability and results in apoptosis or cell cycle arrest. Moreover, migration and invasion are impaired. [131]

In vivo avasimibe treatment in prostate cancer xenograft promotes a significant reduction of tumor growth and tumor weight. SREBP-1 and LDLR expression in addition to SREBP-1 cleavage and LDL uptake is decreased after inhibition of SOAT1 with avasimibe. [131]

Figure 6 Effects of Avasimibe The effect of SOAT1 inhibition with Avasimibe prevents cholesteryl ester formation and storage in Lipid droplets. Therefore the intracellular ER cholesterol is increased and the negative feedback regulation of SREBP causes a reduction in activation. When SREBP is decreased then all its downstream targets are less expressed including ACC, FASN and SCD1, which diminishes fatty acid synthesis and decreases tumor growth. [1]

In glioblastoma the SOAT1 pharmacologic inhibition with avasimibe leads to diminished levels of cholesteryl esters and blocked LD formation (Fig.6). GBM cell growth is inhibited in a dose dependent manner in contrast to normal human astrocytes, which are not affected by avasimibe. Repression leads to a reduction in SREBP-1 cleavage and activation in addition to a suppression of the target genes ACC, FASN and SCD1. Moreover, the de novo lipid synthesis is decreased after the treatment. Avasimibe presents as treatment option in targeting glioblastomas, through repression of SOAT1 and thus inducing the feedback inhibition of SREBP-1 resulting in a suppression lipogenesis and tumor growth. [1] In respect to the mentioned tumor entities, avasimibe treatment indicates promising results in metabolically active tumors, with a lipogenic phenotype. Pharmacological inhibition of SOAT1 via avasimibe demonstrates an effect on exaggerated lipogenesis, LDL-cholesterol uptake, intracellular cholesterol homoeostasis, cholesteryl ester synthesis and the SREBP-1 upregulated lipid synthesis. SOAT1 is a viable pharmacologic target in cancer treatment, because avasimibe demonstrated a good safety profile in human clinical trials on cardiovascular patients. [163]

2. Goal of the Master's thesis

High grade gliomas, especially GBM, are metabolically active tumors with enhanced lipogenesis [1]. The focus of the master thesis was the identification of contributors in lipid metabolism, which could provide new strategies in cancer treatment. The aim was to analyze the expression and the magnitude of sterol O-acyltransferase1 (SOAT1/also named acyl-CoA:cholesterol acyltransferase1, ACAT1) in a panel of brain tumor derived cell cultures. For this purpose the SOAT1 expression was investigated by semi-quantitative RT-PCR and real-time qRT-PCR in a large cohort of different tumor entities.

Within this master thesis the impact of the SOAT1 inhibitor avasimibe on cell viability was assessed with the EZ4U cell proliferation and cytotoxicity assay. The effect of the inhibitor on cell growth, including morphological characteristics indicative for apoptotic cell death, was analyzed by microscopic examination. In addition, the objective was to demonstrate the influence of the inhibited SOAT1 on sterol regulatory element-binding protein-1 (SREBP-1) through Western Blot analysis. In this study the fluorescence lipid dye BODIPY 493/503 was used to stain the lipid droplets in untreated and avasimibe treated brain tumor derived cell cultures in two well chamber slides.

3. Materials and Methods

3.1. Cell culture

During surgery glioma tissue was obtained and transferred to the “Theoretische Neurochirurgie” laboratory for further processing. Cell cultures were established according to the lab protocols published in Spiegl-Kreinecker S, Pirker C et al [167], stored in an incubator at 37°C and supplied with 5% CO2. All cell cultures were periodically checked for Mycoplasma contamination. If there was enough tumor tissue, parts were placed in pre-chilled cryotubes, snap-frozen in liquid nitrogen and stored at -80°C. Histological verification was performed in the Division of Neuropathology (Head: Prof.Serge Weis) at the Neuromed Campus of the Kepler University Hospital and is based on the WHO 2007 (before 2016) and WHO 2016 criteria, respectively.

Cell isolation from brain tumor specimens and cultivation of primo-cell cultures Under sterile conditions (the laminar flow hood) the resected tumor tissue was cut mechanically into small pieces and, together with RPMI1640 growth medium, transferred to a 12.5 or 25 ccm cell culture flask. RPMI1640 was supplemented with 7% FCS and 5% Penicillin/Streptomycin

(10.000U/ml). Subsequently, the flask was placed into the incubator (37°C/5%CO2). After a 48h incubation period only half of the medium was exchanged to keep the tissue particles inside the flasks. Cell cultivation with antibiotics was kept up to 3 weeks after cell culture establishment. Passaging was performed before cells reached confluence and the adherent tumor cells were dissociated with 0.05% Trypsin/EDTA. For this purpose the growth medium was removed with a vacuum pump and the adherent cells rinsed with Trypsin/EDTA, which was removed immediately. Again the cells were exposed to Trypsin/EDTA and incubated (37°C/5%CO2) for several minutes to let the cells detach from the surface. Subsequent to visual inspection using an inverted microscope, the reaction was stopped with growth medium and the suspension culture divided according to growth behavior of the individual cell cultures. Up to the first passage the medium was changed two times a week.

Cryopreservation of cells For long-term storage and to keep a backup for further investigations, cells were cryo preserved. Hence, the cells were detached from the bottom of the culture flask as described above. The cell suspension was transferred into a falcon tube, and centrifuged for 5 minutes at room temperature with 1100 rpm. The resulting cell pellet was suspended in “freezing” medium containing RPM1640, FCS and DMSO and stored in liquid nitrogen.

Thawing of cells If necessary, cells were taken out of the liquid nitrogen tank and gradually thawed starting with cold RPMI1640 - 7 % FCS growth medium. After centrifugation (5min/900rpm) the cell pellet was resuspended with pre-warmed RPMI1640 - 7% FCS supplemented with Penicillin/Streptomycin, the cell suspension transferred into a culture flask which was then placed in the incubator

(37°C/5% CO2) for further cultivation.

3.2. RNA-Analysis

3.2.1. Isolation of RNA

Total RNA was isolated from brain tumor cell cultures either out of culture flasks or 6-well plates using the innuSOLV RNA reagent. According to the manufacturer’s instructions the RNA extraction with innuSOLV is a single-step liquid phase separation method. It is based on a composition of phenol and guanidine isothiocyanate in a monophasic solution. Addition of chloroform and centrifugation provides three phases; to be specific a red organic phase at the bottom, a white intermediate phase and on top there is a colorless liquid phase that includes the RNA. Afterwards precipitation of RNA is conducted with alcohol.

The cells were treated with innuSOLV for 1 minute and the suspension was transferred into a 1.5 mL tube followed by addition of 200 µL chloroform. The sample was positioned on a vortex mixer for 15 seconds and afterwards incubated for 10 minutes at room temperature and then centrifugation with 10.700 rpm at 4°C for 15 minutes. The clear aqueous phase on top containing the RNA was conveyed into a new 1.5 mL tube and ice cold isopropanol was added half the volume of the RNA solution. The sample was vortexed, incubated for 20 minutes at room temperature and then centrifuged with 10.700 rpm at 4°C for 15 minutes. The resulting RNA pellet was washed with 500 µL of ice cold 75% ethanol before centrifugation with 10.700 rpm at 4°C for 15 minutes. In the next step, the ethanol was completely but carefully removed and the RNA pellet was left to dry for about 5 minutes. Depending on the size of the pellet it was diluted in 30 to 50 µL of nuclease free water. The RNA concentration was measured on a photometer at 254 nm and afterwards the RNA was stored at -80°C.

3.2.2. Reverse transcription PCR, RT-PCR

The expression of SOAT1 in various cell lines was measured by reverse transcription PCR (RT-PCR). RNA was isolated from cells with innuSOLV RNA reagent as described previously. A total of 50 ng RNA was used as template. Through application of the QIAGEN OneStep RT-PCR kit, the reverse transcription and amplification were performed in one reaction. In detail, the enzyme reverse transcriptase transcribes mRNA to a complementary singe-stranded DNA strand (cDNA) in a process called reverse transcription. Afterwards, DNA polymerase converts the single-stranded cDNA into double-stranded DNA, which is necessary as template for the PCR reaction. Past the reverse transcription reaction, a heating step of 95°C for 15 minutes is needed in order to activate the HotStarTaq DNA Polymerase. Additionally, it inactivates the reverse transcriptase enzyme. Furthermore, this process disposes of primer dimers and high background. For reference purpose and to normalization the gene expression data the housekeeping gene Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used, because it is expressed constitutively in every cell. GAPDH is a key enzyme in glycolysis and therefore involved in the regulation of basic, cellular functions and thus required for the survival of cells.

All reagents were thawed on ice, vortexed and centrifuged shortly before they were used to insure a homogeneous solution. The RNA samples were stored at -80°C and ahead of PCR reaction they were diluted on ice to a total of 50 ng RNA with RNAse free water. The reaction mix, for the required sample size, was established for every primer pair (GAPDH and SOAT1) according to Table 1.

Table 1 Reaction components for one-time preparation of RT-PCR

QIAGEN OneStep RT-PCR kit 1x preparation 5x Buffer 5 µL dNTP Mix 1 µL Primer fw. (0.4µM) (1:10) 1 µL Primer rev. (0.4µM) (1:10) 1 µL Enzyme Mix 1 µL

One sample tube for PCR reaction included always 25 µL of total volume, hence 5 µL of Q-solution, water volume dependent on the dilution of the RNA, 9 µL of the master mix and in the end the RNA sample was added. The negative control, for GAPDH and SOAT1, consisted of 5 µL Q-solution, 11 µL nuclease free water and 9 µL of the reaction mix. The PCR tubes were shortly centrifuged and then positioned into the thermo cycler. Reaction conditions and primer sequences are outlined in Table 2.

Table 2 Primer sequence and reaction condition RT-PCR

GAPDH fw. primer 5’-CGGGAAGCTTGTGATCAATGG-3’ GAPDH rev. primer 5’-GGCAGTGATGGCATGGACTG-3’ SOAT1 fw. primer 5’-CCACTGGTCCAGATGAGTTTAG-3’ SOAT1 rev. primer 5’-GGGAACATGCAGAGTACCTTT-3

Step Temperature Time

Reverse transcription 50°C 30 min Initial PCR activation step 95°C 15 min 3-step cycling 1) Denaturation 94°C 30 sec 2) Annealing 56°C 40 sec 3) Extension 72°C 40 sec Number of cycles 22 cycles for GAPDH and 30 cycles for SOAT1 Final extension 72°C 10 min Hold 4°C ∞

After the PCR reaction 2.5 µL of 10 x PCR sample buffer was appended to the PCR tubes. Gel electrophoresis was utilized to separate DNA fragments according to their size on a 6% polyacrylamide gel. A sample volume of 11 µL was loaded on the gel, which was operated at 80 V for approximately one hour. Once the fragments were separated, the gel was stained in the dark for 45 min with the fluorescent nucleic acid dye Gelred. For the preparation of the Gelred solution 15 µL were diluted in 50 mL of nuclease free water but this process should not be performed directly before application. Better results were obtained when the Geldred was prepared a day earlier before the usage. The experiment was evaluated by taking a UV-fluorescent picture and the measurements were evaluated with the corresponding FusionCapt Advance SL4 16.15 software (VilberLourmat).

3.2.3. Real-time quantitative reverse transcription PCR, qRT-PCR

To find the most sensitive method, SOAT1 expression was additionally analyzed with real-time qRT-PCR. For this investigation a total of 20 ng RNA was used as template and the reaction was set up using the Rotor-Gene SYBR®Green RT-PCR Kit. In one step reverse transcription and PCR reaction were performed on the Rotor Gene Q (Qiagen). The experiments were carried out in triplicates and analyzed with the associated software.

Quantitative reverse-transcriptase PCR is a method by which the amount of the PCR product can be determined in real-time. It measures PCR amplification as it occurs, meaning that amplification of DNA is detected in real-time, after each cycle with the help of a fluorescent reporter. Collection of information occurs in the exponential growth (log) phase, when the quantity of the PCR product is directly proportional to the amount of template DNA that existed in the sample (Fig.7A). [168,169]

Quantitative real-time PCR is one of the primarily applied analytical methods in gene expression assays, with real-time fluorescence reporters. The method used in this thesis is based on a non-sequence specific DNA-binding dye called SYBR green. SYBR Green is a fluorescence dye that binds to the minor groove of the DNA and only intercalates into the double strand, therefore it can’t bind to single-stranded DNA. When SYBR Green is unbound in the solution it emits only little fluorescence, but upon binding to the dsDNA the signal intensifies over 1000-fold. Hence, the fluorescent measurement is rendered at the end of the elongation step of each PCR cycle to monitor the increase in the amount of amplified DNA. The disadvantage is that the dye binds to all dsDNA, including nonspecific PCR products and primer dimers, therefore provoking inaccuracy. [168,169]

Thus, it is important to analyze the melting curves, since all PCR products of the same primers should have equal melting temperature except if there are contaminations or primer dimers. After the PCR process is done the thermocycler is able to do a melting curve analysis. The temperature is raised and a change in fluorescence is recorded, meaning that when the double strands of DNA disaggregate the fluorescence signal drops. The change in fluorescence signal with the time (Y-axis) is plotted as a function of temperature (X-axis). Therefore, the melting peaks can be compared (Fig.7B). If there is an artifact in the sample, it can be identified by lower temperatures, since it is a very short DNA fragment. Another possibility is that there are broader peaks or an additional smaller peak. [168,169]

A B

Figure 7 Overview of real-time RT-PCR graphs

A) Theoretical example of the real-time RT-PCR phases. [169] B) The graph shows a melt analysis of SOAT1 and 36B4. The first peak demonstrates SOAT1 and the second one 36B4. dF/dT is indicated on the Y-axis, while the temperature is on the X-axis C) Evaluation of real-time RT-PCR curves of 36B4 (first) and SOAT1 (second) from the Rotor Gene Q software. 36B4 is more abundant than SOAT1, hence it crosses the cycle threshold in an earlier cycle.

The PCR reaction is classified into different phases (Fig.7A). In the beginning, usually the first 10–15 cycles, the fluorescence emission is low and has not exceeded the background noise, hence baseline fluorescence can be calculated at this time. The early exponential phase includes the fluorescence signal that has an intensity, which is significantly above the background noise, the so called threshold line. The PCR cycle where the sample reaches the level of the baseline is called the cycle threshold (Ct) or crossing point (CP). The Ct value represents the starting copy number in the original template and therefore can be used to calculate the experimental results (Fig.7C). In the next phase the amplification occurs exponentially, meaning doubling of the quantity of initial DNA, assuming 100% reaction efficiency. [168,169]

During this process the reagent components are consumed, hence the reaction will be reduced and therefore a non exponential phase is reached. Eventually the process enters the plateau phase, where several critical buffer components will no longer be available and PCR reaction stops. [168,169]

Relative quantification rests upon either an external standard or a reference sample, hence the results are expressed as target to reference ratio. Relative expression can be calculated through application of the comparative Ct (2 −ΔΔCt) method, which was used in this experiment. It is a mathematical equation that calculates the relative expression of the target gene normalized to the housekeeping gene 36B4 and relative to a calibrator, such as an untreated sample or another cell line. [168,169]The housekeeping gene 36B4 also known as acidic ribosomal phosphoprotein P0 (RPLP0) is an integral part of the 60S subunit of the ribosome complex. 36B4 is a stable housekeeping gene for reference purpose in quantitative real-time PCR. [170] Relative quantification is calculated by 2-ΔΔCt, where ΔΔCt = ΔCt(sample) - ΔCt(calibrator) and ΔCt is the Ct of the target gene subtracted from the Ct of the housekeeping gene.

All reagents were thawed on ice, vortexed and centrifuged shortly before usage to insure a homogeneous solution. The RNA samples were stored at -80°C and ahead of PCR reaction they were diluted on ice to a total of 20 ng RNA per tube with RNAse free water. The Rotor-Gene SYBR® Green RT-PCR Kit was used to establish one master mix for every primer pair (36B4 and SOAT1), depending on the required sample size, according to Table 3.

Table 3 Reaction components for one-time preparation of qRT-PCR

Rotor-Gene SYBR®Green RT-PCR kit 1x preparation Rotor-Gene SYBR-Green RT-PCR buffer 5 µL Primer S (1:10 diluted from stock, c= 10pmol/µL) 0.5 µL Primer AS (1:10 diluted from stock, c= 10pmol/µL) 0.5 µL Rotor-Gene RT Mix 0.1 µL

Quad stripes were utilized with a total volume of 10 µL per tube, hence 6.1 µL of the master mix solution was placed into the stripes followed by 3.9 µL of diluted RNA. The negative control comprised of 6.1 µL master mix and 3.9 µL of RNAse free water. The tubes were then put into the rotor gene thermocycler under the following settings demonstrated in Table 4. Data evaluation was performed with the rotor-gene Q series software and GraphPad Prism.

Table 4 Primer sequence and cycling conditions qRT-PCR

SOAT1 fw. primer 5’-CCACTGGTCCAGATGAGTTTAG-3’ SOAT1rev. primer 5’-GGGAACATGCAGAGTACCTTT-3’ 36B4u primer 5’-CAGCAAGTGGGAAGGTGTAATCC-3’ 36B4d primer 5’-CCCATTCTATCAACGGGTACAA-3’ Step Temperature Time Reverse transcription 55°C 10 min PCR initial activation step 95°C 5 min Two-step cycling 1) Denaturation 95°C 5 sec 2) Combined annealing/extension 60°C 10 sec Number of cycles 45 cycles for 36B4 and SOAT1 Melt conditions between 60 °C and 95°C/Rising 1°C each step

3.3. Cell viability assay (EZ4U)

To determine the effect of the SOAT1 inhibitor avasimibe on the viability of brain tumor cell lines the easy for you EZ4U kit was employed. The cells were seeded in 96-well plates with different concentrations of avasimibe, which was diluted in DMSO. Hence, a DMSO control group was analyzed in addition to an untreated reference control. To obtain an equal cell density with only healthy cells, trypan blue staining was used to count and assess the cells, before they were seeded into the 96-well plates. Trypan blue is a large negatively charged molecule that cannot pass the intact cell membrane of living cells, therefore the dye is excluded, and the cytoplasm appears clear in microscopic analysis. In dead cells the dye passes through the porous cell membrane and enters the cytoplasm, where it interacts with proteins in the cytosol showing a blue color. After 24h to allow cell adhesion and 72h of avasimibe treatment the cells were evaluated with the EZ4U test.

EZ4U is, according to the instructions of the manufacturer, a non-radioactive cell proliferation and cytotoxicity assay. It is based on conversion of uncolored tetrazolium salts to colored formazan derivatives in the mitochondria of viable cells with active metabolism. Hence this method can be applied to analyze the effects of drug screenings and cytotoxic chemicals on cells. In the past, application of this method was based on monotetrazolium salts (MTT), which have insoluble formazan as end product. The precipitate both inside and outside of the cell had to be solubilized, with a combination of organic solvent and detergent. Thus, it could only be used as end point method, since once the resolubilisation procedure was performed no additional incubation was possible. New generation monotetrazolium salts like XTT, MTS and WST-1 need an intermediate electron acceptor (IEAs) that facilitates dye reduction and forms soluble formazan product, therefore making a real-time assessment possible. [171] The EZ4U assay is based on this principle, thus the water soluble formazan can be measured several times during the incubation period of 2-5h. The measurements were rendered on a microplate reader at 450 nm and 620 nm reference. The reference wavelength between 620-690 nm is necessary to correct for nonspecific background.

The glioblastoma cell lines that were selected for the assay were examined under the microscope in their culture flasks before the experiment. The confluence of the cells was between 70-100%. The lamina flow hood was cleaned with mycoplasma-off spray and the RPMI 1640 medium and Trypsin-EDTA were pre-warmed to 37°C in the water bath. The cell medium was discarded, with a glass pasteur pipette connected to a vacuum pump, without disruption of the cell monolayer.

The cell layer was rinsed with 0.5 mL of Trypsin-EDTA to get rid of residual medium, which was immediately aspirated. Afterwards 1 mL of Trypsin-EDTA was added into the flasks to detach the cells from the surface. They were placed in the incubator at 37°C for 2 minutes and past that they were gently tapped. The displacement of cells was controlled under the microscope. The reaction of Trypsin-EDTA was stopped with 4 mL medium and the whole suspension was transferred into a falcon. To make sure that no cells were left behind, the culture flasks were rinsed with 5 mL medium, which was conveyed into the same falcon. Centrifugation at room temperature for 5 minutes and 1100 rpm was next. The medium was discarded, and the cell pellet was dissolved in 1 mL medium. The sample was stirred thoroughly to receive a homogeneous suspension. 10 µL of the cell suspension was mixed with 10 µL of Trypan Blue solution 0.4% and then transferred into the Neubauer chamber for counting. Depending on the growth rate and confluence either 1*104 or 1.5*103 cells were seeded per 100 µL and well into the plates.

After the cells were counted, and the cell concentration was known, they were diluted to the necessary amount. To exemplify, untreated control cells, DMSO treated cells and the concentrations of 2.5 µM, 5µM, 7.5 µM and 10 µM avasimibe were experimented on in triplicate. With three extra wells for safety there were 21 wells needed with 100 µL each making it a total of 2.1 mL cell suspension per glioblastoma cell line with 21*104 cells (1*104 per well*21 wells). For instance, the cell line BTL2 was counted and had 114*104 cells/1 mL, for this reason the dilution was calculated to 184 µL cell suspension and 1916 µL medium. From this attenuation 100 µL was pipetted into the wells of a 96-well plate. Three different cell lines were analyzed on one plate with a medium border around them. The cell density of the wells was controlled under the microscope and then the 96-well plates were cited in the incubator for 24 hours to allow cell adhesion. For further sustainment of those cell lines new T-25 flasks were filled with 5 mL medium and two tropes of the original cell suspension were transferred into the new flasks.

On the second day avasimibe was added to the cells. 1 mg of avasimibe (MW: 501,72 g/mol) was weighed in under the lamina flow hood and dissolved in 1 mL DMSO, which resulted in a stock solution of 2 mM. Aliquots were stored at -20°C. The DMSO concentration did not exceed 1% during all experiments performed. The DMSO control group was adapted to the highest concentration used (10µM avasimibe), to make sure that the results are due to avasimibe inhibition and not because of DMSO.Since there were already 100 µL of cell suspension per well, a two times avasimibe working concentration was prepared in pre-warmed medium.For instance, the 10 µM avasimibe end concentration was generated by manufacturing a 20 µM working concentration.

For this purpose, 10 µL of the stock solution was dissolved in 990 µL medium.(c1 * V1= c2 * V2→

2000 µM * V1 = 20 µM * 1mL). 100 µL of a 2x working solution was pipetted into the well, establishing a 1x end concentration with a total volume of 200 µL per well. The 96-well plates were positioned in the incubator for 72 hours with routine microscopic examination.

After three days the EZ4U assay was prepared to determine the results of the cell viability after exposure to avasimibe. The substrate of EZ4U was dissolved in 2.5 mL of activator solution, which was pre-warmed to 37°C. The dye solution can be diluted (1:10) either directly in the sample well or in an extra step in pre-warmed medium, but then the wells must be drained without disturbing the cell layer. Three wells from the medium border were used as blanks for calculation of background noise. The incubation period depended on the metabolic capacity of the cells and was able to take between 2 to 5 hours at 37°C. The plates were shaken on the microplate reader for 3 seconds and afterwards the absorbance was measured at 450 nm. The reference absorption, to adjust for nonspecific background values like cell debris, fingerprints or other potential interferences was measured at 620 nm. The incubation period was completed when the untreated control group had absorption values around one or after the 5 hours were over. The substrate blank values were subtracted before analysis of the data. The dose- response curve between avasimibe concentration and cell viability was calculated in GraphPad Prism. For verification of EZ4U 1.5*103 cells, 0.75*103 cells, 0.375*103 cells and 0.19*103 cells were seeded in triplicate and incubated for 72 hours. The EZ4U results showed a linear connection between the cell count and the absorption values.

3.4. Effects of the inhibitor Avasimibe

In this experiment the gene expression of SOAT1 mRNA was measured in response to drug treatment with avasimibe and morphological characteristics indicative for apoptotic cell death were monitored. In relative quantification analysis the changes in gene expression of the target was compared relative to an untreated control group. In this experiment SOAT1 mRNA was quantified after exposure to avasimibe and analyzed by real-time qRT-PCR with the housekeeping gene 36B4 and partially controlled with RT-PCR and GAPDH. In addition, the morphological features of tumor cell lines submitted to avasimibe treatment were photographed and documented in microscopic examination. 5*104cells/well were seeded in 6-well plates in duplicate. 5 µM avasimibe, 10 µM avasimibe, a DMSO control group and an untreated cell group were examined. The cells were exposed to avasimibe for 24 hours and 48 hours and then the RNA was isolated with innuSOLV RNA Reagent, measured and diluted for real-time PCR as described earlier.

The process of seeding the cells in 6-well plates, meaning extraction of cells from the culture flasks and counting in the neubauer chamber, was performed exactly the same as already described in the cell viability assay. Dilution of cell count was calculated, and 5*104 cell were seeded in 2 mL medium per well. The cells were incubated for 24 hours to allow cell adhesion. Before exposure to avasimibe photos were taken, to document the original state of the cells post treatment. A 2x avasimibe working concentration was established the same way as it was explained in cell viability assay. 1 mL of medium was discarded from the wells without disturbance of the cell layer and 1 mL of the 2x working concentration was placed in the wells to obtain a 1x end concentration. The plates were swayed carefully and put into the incubator. To keep records of changes in cell morphology microscopic examination was rendered after 24 hours and 48 hours during treatment. The RNA was isolated from one plate after 24 hours of avasimibe exposure and the other one after 48 hours. Cell morphological features were documented on both days. Total RNA was isolated from cells with innuSOLV RNA Reagent as described earlier. A total of 20 ng RNA per tube was used for real-time PCR with the Rotor-Gene SYBR® Green RT-PCR Kit. The untreated control group, the DMSO group, the 5 µM and 10 µM avasimibe concentration were analyzed in triplicate in comparison to 36B4 gene.

3.5. Protein-Analysis

3.5.1. Protein isolation

NE-PER Nuclear and Cytoplasmic Extraction Reagents The NE-PER nuclear and cytoplasmic extraction kit was employed, to separate and prepare cytoplasmic and nuclear fractions of cultured cells. The aim was to obtain active proteins, which were not denatured. Cell membrane disruption and release of cytoplasmic contents was achieved with the first two reagents and afterwards the nucleus was extracted through centrifugation. The third reaction agent extracted the proteins from the nuclei. Before the usage of CER I and NER the addition of a protease inhibitor from a concentrated stock was necessary. All preparation steps were performed on ice with cold reagents. The cell culture flask was put on ice and with the help of a cell scraper the cells were dispensed from the surface. The medium with cells was transferred into a 50 mL falcon and centrifuged at 4°C for 5 minutes and 500g. The supernatant was discarded, and the pellet was wash with ice cold PBS and centrifuged at 4°C for 3 minutes and 500g. The supernatant was again depraved so that the pellet was as dry as possible. The exact combination of volume needed, was applied as described in the Table 5 and depended on the amount of the pellet.

Table 5 Schematic overview of the NE-PER nuclear and cytoplasmic extraction kit

Packed cell Volume [µL] CER I [µL] CER II [µL] NER I [µL] 10 100 5.5 50 20 200 11 100 50 500 27.5 250 100 1000 55 500

Ice cold CER I was put to the pellet and the tube was positioned on the vortex mixer for 15 seconds at the highest setting. The sample was incubated on ice for 10 minutes and after that the CER II reagent was added, followed by vortexing for 5 seconds and another incubation period for 1 minute. Before centrifugation at 4°C for 5 minutes and 16000 g the sample was again put on the vortexer for 5 seconds. The supernatant was then transferred into a fresh cold Eppendorf tube and labeled cytoplasmic extract. The pellet, which contained the nuclei, was suspended in ice cold NER and subsequently placed on the vortexer for 15 seconds at the highest setting. This process was continued every 10 minutes to a total of 40 minutes. Centrifugation at 4°C for 10 minutes and 16000 g was necessary to obtain the nuclear extract in the supernatant which was conveyed into a new cold Eppendorf tube and labeled nuclear fraction. The protein samples were stored at -80°C afterwards.

Protein isolation with Triton X-100 and RIPA Buffer

All preparation steps were performed on ice with cold reagents. The cell culture flask was positioned on ice and with the help of a cell scraper the cells were dispensed from the surface of the flask. The medium with cells was transferred into a 50 mL falcon and centrifuged at 4°C for 10 minutes and 1700 rpm. The supernatant was discarded, and the pellet was wash with ice cold PBS and sited on the vortexer. Afterwards the sample was centrifuged again at 4°C for 10 minutes and 1700 rpm. The supernatant was removed, and the pellet was suspended in 150-300 µL lysis buffer, depending on the volume of the pellet. The lysis buffer consisted of 300 mM NaCL, 50 mM Tris buffer and 0.5 % Triton-X with a pH of 7.6. For 100 mL buffer 1.752 g NaCl and 0.6055 g Tris were weighed in and dissolved in distilled water on a magnetic stirrer. 500 µL of Triton- X was added and the solution was raised to 100 mL with distilled water. The protease inhibitor was subjoined briefly before the usage of the lysis buffer. In general, 60 µL of protease inhibitor was necessary for 1.5 mL lysis buffer. After addition to the pellet the sample was incubated for 10 minutes and often placed on the vortexer in between the incubation period. For better protein extraction some samples were treated with a homogenizer rode (IKA) for a few seconds. Another method tested for disruption of cell membrane was sonication with different amounts of cycle repetition and amplitude. Exposure time was between 10 and 15 seconds in an ice water bath, followed by incubation periods on ice in between the cycles. The specimen was centrifuged at 4°C for 15 minutes and 11200 rpm. The protein samples were stored in aliquots at -80°C.

For protein isolation with RIPA buffer the same protocol was used. To determine the best extraction results three different RIPA buffer were applied with 150 mM NaCl, 300 mM NaCl and 500 mM NaCl. The other components required were 0.1% SDS, 1% NP-40, 0.5% sodium deoxycholate, 50 mM TRIS/HCL and a pH of 7.4. For 50 mL RIPA Buffer 0.05 g SDS (288.38 g/mol), 0.438 g NaCL (150 mM, 58.4 g/mol), 500 µL NP-40, 0.25 g Na-Doc and 0.394 g TRIS/HCL (157.6 g/mol) were needed. pH was adjusted with a pH-meter.

3.5.2. Determination of protein concentration

The Micro BCA Protein Assay Kit was applied for colorimetric detection and quantitation of total protein concentration after protein isolation. Per manufacturer’s instructions the proteins can reduce Cu+2 to Cu+1 in an alkaline environment, for which reason bicinchoninic acid (BCA) can be used as detection reagent for Cu+1. Chelation between two molecules of bicinchoninic acid with one cuprous ion (Cu+1) constitutes an end product that has a purple color and is water soluble. Furthermore, the complex has a strong absorbance at 562 nm, with linearity to rising protein concentration. With this assay it is possible to measure a protein concentration from 0.5 to 20 µg/mL, thus it was employed after all three protein extraction methods.

The protein samples that were stored at -80°C were diluted 1:100, meaning 5 µL of sample and 495 µL of distilled water. The preparation of the Albumin (BSA) standard [2 mg/mL] dilution series included nine different concentrations (200, 100, 50, 25, 12.5, 6.25, 3.125, 1.563 and 0.78 µg/mL). For the highest convergence 900 µL distilled water was combined with 100 µL BSA standard. For the following lower concentrations 500 µL distilled water were always joined with 500 µL of the next higher concentration. Therefore, the dilution series was established from the highest to the lowest concentration.

To determine the total volume of the working reagent needed, the formula (# standards + # sample) × (# replicates) × (volume of working reagent per well) was applied. Measurements of the specimens, blanks and BSA standards were set in triplicate. The preparation of the working reagent included the combination of 25 parts Micro BCA Reagent MA and 24 parts Reagent MB with 1 part of Reagent MC (25:24:1, reagent MA: MB: MC). 150 µL of blank, sample or standard were added to the wells of a 96-well plate. Afterwards 150 µL of the working reagent was adjoined and then the plate was slewed carefully. Subsequently the plate was placed for 2 hours in an incubator at 37°C. The measurements were performed on a microplate reader. The plates were shaken for 3 seconds and then measured at 562 nm. Afterwards the data was analyzed in excel with the help of the albumin calibration curve.

3.5.3. Western Blot

Western blots were conducted with whole cell protein extracts form cell culture homogenized in RIPA buffer, Triton X-100 buffer or the NE-PER nuclear and cytoplasmic extraction reagents kit. Proteins were separated according to their mass through gel electrophoresis SDS-PAGE on 10% or 12% gels for SOAT1 and 7.5% for SREBP-1 and afterwards transferred to a polyvinylidene difluoride (PVDF) membrane under semi-dry conditions. The membrane was then blocked to prevent nonspecific binding of antibodies to the surface of the membrane. SOAT1 (#sc-69836, Santa cruz) and SREBP-1 (#557036, BD pharmingen) were the primary antibodies, while the Rabbit anti-Mouse IgG (H+L) horseradish peroxidase (HRP) was used as a secondary antibody. For highly sensitive chemiluminescent detection the Amersham ECL Prime Western Blotting Detection Reagent was employed.

Different running gels were applied depending on whether SOAT1 or SREBP-1 were analyzed. For SOAT1 a 10% or 12% running gel was necessary and for SREBP-1 a 7.5%, due to the high protein mass of the precursor form (125 kDa). The 12% running gel consisted of 6.54 mL distilled water, 3.75 mL TRIS pH 8.8, 4.5 mL 40% acrylamid, 75 µL 10% APS, 10 µL TEMED and 150 µL 20% SDS. The 7.5% running gel persisted of 8.24 mL distilled water, 3.75 mL TRIS pH 8.8, 2.8 mL 40% acrylamid, 75 µL 10% APS, 10 µL TEMED and 150 µL 20% SDS. After the running gel was poured 200 µL of methanol were placed on it. Past polymerization the methanol was discarded, and the 4.5% stacking gel was put on top. The stacking gel consisted of 3.1 mL distilled water, 1.25 mL TRIS pH 6.8, 563 µL 40% acrylamid, 25 µL 10% APS, 5 µL TEMED and 50 µL 20% SDS. The samples were diluted to an amount of 25 µg, 30 µg or 50 µg protein with distilled water and then the two times laemmli buffer was added.

Some samples were heated to 95°C for 5 minutes. The laemmli buffer was established by adding 2.5 mL TRIS pH 6.8, 2 mL glycerin, 0.4 g SDS, 0.31 g DTT, 0.1 mg bromphenolblue and filled up to 10 mL with distilled water. The aliquots were stored at -20°C. The settings were 80 V for 2-2.5 hours. As running buffer, a Tris/Glycine/SDS solution from BioRad was used. 100 mL of a tenfold concentrate was diluted with 900 mL distilled water. All slots were rinsed with running buffer. During the running time of the SDS PAGE the blotting buffer was manufactured. For this purpose 5.82 g Tris (48mM), 2.93 g glycine (39 mM), 0.375 g 10% SDS and 200 mL of 20% methanol were combined and raised to 1000 mL with distilled water.

After SDS-PAGE the gel was soaked for 20 minutes in the blotting buffer on the shaker. The PVDF membrane was activated in methanol for 1 minute, then 2 minutes in distilled water and subsequently 10 minutes in blotting buffer. The PVDF membrane was laid on two extra thick blotting papers without air bubbles. The gel was put onto the membrane and afterwards another two pieces of blotting paper were used. Blotting took place at 15 V for 45 minutes under semi-dry conditions. To verify, if the transfer of protein from the gel to the membrane was complete, the membrane was stained for 5 minutes in Ponceau S solution and then transcribed on photographic paper. Ponceau S staining on PVDF is reversible by washing the stained membrane with water. During the time it took for SDS PAGE to finish, the washing solution and blocking solution were manufactured. For the TBST solution 100 mL of 10X-TBS, 900 mL distilled water and 1 mL Tween20 were assembled. Depending on the experiment different blocking solutions were utilized. 1% non-fat milk (0.5 g) and 0.5% BSA (0.25g) were dissolved in 50 mL TBST and placed on the magnetic stirrer. Also 5% non-fat milk and 10% non-fat milk TBST solutions were tried.

The membranes were set on the shaker in blocking solution for 1 hour. Afterwards they were incubated with SOAT1 or SREBP-1 either for 1 hour at room temperature or overnight at 4°C. The membranes were washed with TBST three times for 10 minutes. Meanwhile the secondary antibody was prepared by a 1:5000 dilution in blocking buffer. Incubation with the secondary antibody took place for 1 hour on the shaker. Subsequently the membranes were washed four times for 15 minutes each with TBST. For detection 2 mL of Super Signal Western Dura Substrate was needed. Incubation took place in the dark for 5 minutes and evaluation was performed on the chemi doc (fusion). Illumination time was dependent on the intensity of the protein band. For reference purpose ß-actin was used. After detection the membrane was washed three times with TBST for 10 minutes each and then incubated in blocking solution for 30 minutes. The ß-actin antibody was incubated for 1 hour and afterwards the membrane was washed again with TBST three times for 10 minutes each. The secondary antibody was placed on the membrane for 1 hour followed by four times of 15 minutes washing process with TBST. For detection the membrane was incubated again for 5 minutes in the dark with western dura substrate and analyzed.

3.6. Lipid staining assay-BODIPY

For verification of lipid droplets in brain tumor cells the fluorescent lipid dye 4,4-difluoro- 1,3,5,7,8-pentamethyl-4-bora-3a,4a-diaza-s-indacene (BODIPY493/503) was used. According to the manufacturer BODIPY is a lipophilic, long-wavelength absorption and fluorescence dye with a nonpolar structure. Especially the 493/503 analog is specific for cellular lipid droplets staining. The wavelength range has a fluorescence excitation maximum of 500 nm to ~650 nm and an emission maximum from 510 nm to ~665 nm. The chamber slides employed have a modified CC2 growth surface, which imitates poly-D-lysine coating and makes binding for fastidious cells like neurons ideal. Vectashieldantifade mounting medium with DAPI sustains fluorescence and inhibits quick photobleaching of fluorescence dyes. It includes DAPI, which serves as marker for the nucleus, because when bound to DNA it reveals a blue fluorescence.

1 mg of BODIPY (262.1085 g/mol) was weighed in and dissolved in 1 mL absolute ethanol that resulted in a stock solution with a concentration of 3.8 mM. Aliquots were stored protected from light at -20°C. A 10 µM working concentration was established through combination of 2.6 µL stock solution and 997.4 µL absolute ethanol. The necessary concentrations (0.5 µM, 1 µM and 2µM BODIPY) needed were directly diluted in the medium of the chamber slides from the working solution. 1*104 cells were seeded per well in 1 mL medium as previously described in the cell viability assay. The chamber slides were set in the incubator for 24 hours to allow cell adhesion. For control experiments oleic acid was added to the cells, to see if the outcome in lipid droplet staining would be different. A 3 mM stock solution was diluted to a 100 µM oleic acid concentration through removal of 33.33 µL medium from the chamber and addition of 33.33 µL oleic acid (3 mM) directly into the well. Staining for 1 µM BODIPY solution was performed by displacement of 100 µL medium from the wells and addition of 100 µL working concentration. Incubation lasted for 30 minutes in the dark. Afterwards the medium was completely removed, and 1 mL of paraformaldehyde was added and incubated for 10 minutes without light for cell fixation. The paraformaldehyd was discarded and the well was rinsed with 1 mL of PBS. The chamber was removed from the object slide. 1 drop of Vectashieldantifade mounting medium with DAPI was put on the cells and the cover slip was placed on top. For visualization a confocal microscope was used (Carl Zeiss) and pictures of lipid droplets were taken.

4. Results

4.1. SOAT1 expression

Using semi-quantitative and qRT-PCR the SOAT1 expression was analyzed in different brain tumor-derived cell lines. The aim was to determine the expression level of SOAT1 in diverse tumor classifications. In addition, the question was if there is a significant expression difference of SOAT1 among low grade gliomas and high grade gliomas and as well between low grad gliomas and glioblastoma. Furthermore, the expression status of SOAT1 was necessary to select the cell lines for cell viability assays and BODIPY staining of lipid droplets, respectively.

4.1.1. Semi-quantitative reverse transcription PCR

The SOAT1 expression level in various cancer classifications (Tab.6) was measured by reverse transcription PCR in comparison to the reference housekeeping gene GAPDH. Analysis was executed with the FusionCapt Advance SL4 16.15 software (VilberLourmat). Statistical analysis was performed with the help of Excel and GraphPad Prism. Assessment of statistical significance was sustained by using the unpaired Student t test (P<0.05).

Table 6 Classification of cancer cell lines

Low grade glioma (LGG) High grade glioma (HGG) Tumor metastases Astrocytoma grade I Anaplastic astrocytoma III Met. Melanoma Astrocytoma grade II Anaplastic oligodendroglioma III Met. Mammary CA Oligodendroglioma grade II Anaplastic oligoastrocytoma III Met. Prostate Oligoastrocytoma grade II Glioblastoma Met. Mesothelioma Gliosarcoma Met. Adenocarcinoma Met. Urothelial carcinoma

Different tumor cell lines were categorized either in low grade gliomas, which included the WHO grade I and II, while the classification of high grade gliomas comprised the WHO grade III and IV brain tumors (Tab.6). In addition, to low grade gliomas and high grade gliomas the expression level of SOAT1 in different brain tumor derived metastases cell lines was analyzed (Tab.6). Furthermore, the international human Caucasian glioblastoma cell line T98G was precisely investigated. RNA extracted from epilepsy surgery tissue served as control “normal tissue”.

The analysis of all cancer classifications, including the different forms of metastases, is shown in Figure 8. In total 15 various tumor classes were analyzed with a sample size of 102 cell lines and overall 22 glioblastoma (Fig.8). The corresponding statistical results are shown in Table 7 for LGG and HGG and in Table 8 the brain tumor derived metastases cell lines are displayed.

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Figure 8 SOAT1 expression in primary and secondary brain tumors analyzed by RT-PCR

Table 7 Results of SOAT1 expression in primary and secondary brain tumors analyzed with RT-PCR

Low grade gliomas High grade gliomas Classification AI AII OAII ODGII aAIII aOAIII aODGIII G GS Number 11 12 6 5 6 6 4 22 2 Mean 1.228 1.367 1.275 1.48 1.609 1.856 2.049 1.549 1.642 Std. Deviation 0.4235 0.2722 0.2072 0.299 0.503 0.406 0.4293 0.3746 0.9984 Std. Error of 0.1277 0.0786 0.0846 0.134 0.205 0.166 0.215 0.0799 0.706 Mean

Table 8 Results of SOAT1 expression in tumor metastases analyzed with RT-PCR

Tumor metastases Met. Met. Met. Met. Met. Met. Classification melanoma mesothelioma prostate mammary CA adeno CA urothelCA Number 11 2 2 5 1 1 Mean 1.849 1.88 1.385 1.222 1.35 0.488 Std. 0.6671 1.348 0.06859 0.4649 0 0 Deviation Std. Error of 0.2011 0.9535 0.0485 0.2079 0 0 Mean

After the SOAT1 expression was determined in all tumor classifications of LGG and HGG (Tab.7), the analysis of significance was conducted with the unpaired two-tailed Student t-test. The requirements of an unpaired t-test were confirmed and the significance value was defined to P<0.05. The outcome of the unpaired two-tailed Student t-test demonstrated that low grade gliomas (mean ± SD, n = 34) 1.323 ± 0.3229 had a significant lower expression of SOAT1, than high grade gliomas (mean ± SD, n = 40) 1.659 ±0.4445 with a p-value of 0.0005, demonstrated in Figure 9A. Statistical analysis of low grade gliomas next to only glioblastoma (mean ± SD, n = 22) 1.549 ± 0.3746 revealed that there was additionally a difference between those two classifications (Fig.9B). Results verified a significant higher SOAT1 expression in glioblastoma with a p-value of 0.0195 than in low grade gliomas (Fig.9B).

A B p= 0.0005 p= 0.0195

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Figure 9 Data visualization of unpaired t-test results after RT-PCR analysis

To determine the significant difference in SOAT1 expression an unpaired two-tailed t-test (P<0.05) was established in GraphPad Prism. A) The results demonstrate LGG (1.323 ± 0.3229) and HGG (1.659 ±0.4445) with a significant difference in SOAT1 expression. B) SOAT1 differs also between LGG and G (1.549 ± 0.3746) significantly.

The Grubbs outlier test (α=0.05) was conducted for the category of astrocytoma grade I and for astrocytoma grade II, due to a very high SOAT1 expression value in one cell line in each classification. Statistical analysis confirmed these two cell lines as outliers in their respective classification and also in the categorization of low grade glioma, hence they were not included in the unpaired t-test calculation for LGG and in the analysis demonstrated in Figure 8. The reason behind this high SOAT1 magnitude was that GAPDH revealed a very weak signal and since GAPDH was used as reference control for the calculation, the SOAT1 expression seemed extraordinarily high. The weak GAPDH was verified in repetition experiments.

The results of the investigated metastases revealed that the melanoma cell lines had an elevated expression of SOAT1 with (mean ± SD, n = 11) 1.849 ± 0.6671 (Tab.8) compared to low grade gliomas. Within this subgroup three cell lines demonstrated a very high expression of SOAT1. In particular BTL1423 had the second upmost expression of all specimens tested. This was also confirmed by real-time RT-PCR, hence it was chosen for quantification of cell viability after exposure to avasimibe. Moreover, cancer cell lines of prostate and breast did not show elevated SOAT1 expression equivalent to the high levels of melanoma metastases.

The epilepsy surgery was classified as not tumorous, but changes couldn’t be excluded since it was removed in the course of an etiopathology. The urothelial carcinoma had one of the lowest expression values in real-time RT-PCR and RT-PCR, which is why it was chosen for analysis of avasimibe effects in cell lines with low SOAT1 expression. The mesothelioma metastases appeared to have diverse occurrences in the RT-PCR outcome, however their values were very similar in real-time RT-PCR. This was a result of a difference in the reference genes. Therefore, the two mesothelioma cell lines were alike in SOAT1 expression in real-time RT-PCR, but not in RT-PCR. The two gliosarcoma cell lines showed in both real-time qRT-PCR and RT-PCR a grand difference in SOAT1 expression

4.1.2. Real-time qRT-PCR

Real-time quantitative reverse transcription PCR was used to assess the expression of SOAT1 in comparison to the housekeeping gene 36B4. It is therefore possible to calculate the ∆CT of SOAT1 with ∆CT= (CT SOAT1 - CT 36B4). Compared to other common reference genes the transcript levels of 36B4 are very reliable and consistent for gene expression studies. Results for relative quantification of SOAT1 gene expression were evaluated and normalized to the reference cell line T98G with the ΔΔCT method (2-(sample ∆CT- reference ∆CT). T98G had a very stable expression of SOAT1 during real-time qRT-PCR, therefore it was chosen as signifier control set as 1(Fig.10). Statistical analysis was performed after evaluation with the rotor gene software and the help of Excel and GraphPad Prism. The 15 cancer classifications, with the identical cell lines analyzed by RT-PCR, including gliomas and a variety of brain metastases, the international GBM cell line T98G and the epilepsy surgery sample were investigated by real-time qRT-PCR. (Fig.10) The corresponding SOAT1 expression results of the low grade and high grade gliomas are demonstrated in Table 9, while the outcome of the brain metastases cell lines is displayed in Table 10.

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Figure 10 SOAT1 expression in primary and secondary brain tumors analyzed by real-time qRT-PCR

Table 9 Results of SOAT1 expression in LGG and HGG analyzed with real-time qRT-PCR

Low grade gliomas High grade gliomas Classification AI AII OAII ODGII aAIII aOAIII aODGIII G GS Number 12 13 6 5 6 6 4 20 2 Mean 0.558 0.4007 0.3902 0.5053 0.499 0.662 0.7451 0.6056 0.8788 Std. 0.166 0.1391 0.1631 0.1768 0.154 0.263 0.3181 0.2002 0.4743 Deviation Std. Error of 0.048 0.0386 0.0666 0.0791 0.063 0.108 0.1591 0.0448 0.3354 Mean

Table 10 Results of SOAT1 expression in tumor metastases analyzed with real-time qRT-PCR

Tumor metastases

Classification Met. Met. Met. Met. Met. Met. melanoma mesothelioma mammary CA prostate adeno CA urothel.CA Number 11 2 5 2 1 1 Mean 1.181 0.4467 0.6393 0.5564 0.5035 0.2232 Std. Deviation 0.555 0.03718 0.2866 0.05988 0 0 Std. Error of 0.1673 0.02629 0.1282 0.04234 0 0 Mean

Statistical analysis, with an unpaired two-tailed t-test (P<0.05), of the real-time qRT-PCR data revealed that low grade gliomas (mean ± SD, n = 36) 0.4658 ± 0.1683 significantly differ in the SOAT1 expression from high grade gliomas (mean ± SD, n = 38) 0.6268 ± 0.2355 with a p-value of 0.0012 (Fig.11A). In addition, low grade gliomas were also significantly distinguishable from glioblastoma (mean ± SD, n = 20) 0.6056 ± 0.2002 in SOAT1 expression with a p-value of 0.0074 (Fig.11B).

The international human Caucasian glioblastoma cell line T98G is cited in the graph at one, because it was used as normalization reference for the calculation of relative gene expression with the ΔΔCT method. Compared to the other glioblastomas and high grade gliomas it had a very high SOAT1 expression, which was also confirmed with RT-PCR. Therefore, T98G was one of the main cell lines evaluated in all the experiments performed. Moreover the melanoma metastases cell lines demonstrate in real-time qRT-PCR high SOAT1 expression 1.181±0.555 compared to low grade gliomas and additionally to high grade gliomas. (Tab.10)

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Figure 11 Data visualization of unpaired t-test results after real-time qRT-PCR analysis

To determine the significant difference in SOAT1 expression an unpaired two-tailed t-test (P<0.05) was established in GraphPad Prism. A) The results demonstrate LGG 0.4658 ± 0.1683 and HGG 0.6268 ± 0.2355 with a significant difference in SOAT1 expression. B) SOAT1 differs also between LGG and Glioblastoma 0.6056 ± 0.2002 significantly.

In conclusion the data evaluated with real-time qRT-PCR and RT-PCR demonstrated that SOAT1 expression was increased in high grade tumors and also glioblastomas in comparison to low grade gliomas. There were small differences between the expression levels depending on the housekeeping gene and method used, but overall the final result was very similar. A significant difference between high grade and low grade tumors could be proven. The information of SOAT1 expression status received determined the cell lines used for cell viability assay, protein isolation, BODIPY staining and downregulation experiments.

4.2. Cell viability assay

The task was to determine if there is a concentration dependent decrease in cell viability after treatment with the SOAT1 inhibitor avasimibe. The half-maximal inhibitory concentration (IC50) value declares the concentration that is responsible for a decline to 50 % viable cells in comparison to the untreated control. Calculations of IC50 values were rendered from dose- response curves after data evaluation. To investigate the possible influence of different avasimibe concentrations on diverse cell lines, a cell viability assay (EZ4U) was applied. For this purpose, 1.5*103 cells or 1*104 cells, depending on the growth rate and confluence, were seeded in triplicate into 96-well plates and cultured for 24 hours to enable cell adhesion. Exposure of cell lines to avasimibe was tested in a concentration dependent manner. Additionally, to the control group with medium, the effects of DMSO on cell viability were tested, due to the fact that DMSO was used as solvent for avasimibe. DMSO concentration did not exceed 1% in the highest concentration used during all experiments. Data from the quantification of cell viability confirmed that all cell lines remained viable at the DMSO concentrations used. The cells were exposed to avasimibe for 72h with 2.5 µM, 5 µM, 7.5 µM and 10 µM. The cell lines that showed no sensitivity to the inhibitor were also examined with 15 µM and 20 µM. For verification of EZ4U 1.5*103 cells, 0.75*103 cells, 0.375*103 cells and 0.19*103 cells were seeded in triplicate in 96-well plates and incubated for 72 hours. The results reveal a linear connection between the various amounts of seeded cells and the absorption values. On the basis of this calibration line it could be determined, that less cells can be differentiated from a control group. The cells treated with avasimibe were normalized to the untreated cells in the control wells. The evaluation of the data set was performed in GraphPad Prism and Excel.

The stable glioblastoma cell line BTL2 represented high SOAT1 expression levels in real-time RT-PCR and RT-PCR experiments. Hence it was selected to determine, if there is a concentration dependent decrease in cell viability provoked by avasimibe (Fig.12A). The cell line was tested in several separated experiments with 2.5 µM, 5 µM, 7.5 µM, 10 µM avasimibe concentrations and in different passages. However, treatment of the cells showed no apparent half maximal inhibitory concentration values and no significant sensitivity to avasimibe.

Since BTL2 was already cultivated to a high passage the idea was to test this particular cell line also in a low passage. In this case the theory was that a different outcome could be obtained, if the cells were closer to the original tumor. But the results suggested no significant impact of avasimibe on BTL2 cells screened in a low passage (Fig.12A). No IC50 value was reached and no decisive decrease in cell viability could be observed. Statistical analysis of the mean value showed that approximatively 78% (0.778 ± 0.223, n = 4) of the cells were viable at 10 µM concentration at the end of the assay. Because of the absence in reaction to avasimibe, BTL2 was also tested with higher concentrations meaning 15 µM and 20 µM (Fig.12D). The outcome revealed 80% viable cells at the maximum concentration of 20 µM, therefore no change could be verified, even though raised concentrations were applied. In conclusion this glioblastoma cell line did not react in a significant concentration dependent manner to avasimibe and it was not possible to get an IC50 value.

The next glioblastoma cell line tested was BTL53, which is also a stable cell line, but in comparison to BTL2 it had low SOAT1 expression. To investigate the possible effect of avasimibe on cell lines with low SOAT1 expression BTL53 was exposed to the inhibitor, in an advanced passage and also in a low passage (Fig.12B). The results indicated that there was no apparent sensitivity to the inhibitor, because the cell viability in this glioblastoma cell line did not decrease significantly. There were also no changes between BTL53 cells in a low passage and high passage. Hence, the next approach for BTL53 was also the implementation of higher concentrations (Fig.12D). Nevertheless, no evidence was found that pharmacological inhibition of SOAT1 with avasimibe reduced cell viability. At 20 µM there was no meaningful response and roughly 80% of the cells stayed viable in the end.

BTL276 is a stable glioblastoma cell line with moderate SOAT1 expression in real-time RT-PCR and RT-PCR. The effects of avasimibe on cell survival varied in this cell line more than in the other ones examined (Fig.12C). BTL276 was tested four times in different passages. The data from the first experiment resulted in 82% viable cells at the end of the assay at 10 µM avasimibe concentration. However, when this cell line was analyzed a second time, an IC50 value at 9.35 µM was obtained and approximately 46% cells stayed viable at 10 µM. The third repetition yielded again less impact on cell survival with 71% at the highest concentration used. Therefore, BTL276 was investigated a fourth time, which indicated barely an IC50 value with a decrease to 55% viable cells. In comparison to the first two glioblastoma cell lines BTL276 showed more concentration dependent effects to avasimibe, but also a strong variation in results. Even though the setup was the same and no specific occurrences happened during the experimental process to explain the variation.

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BTL2 glioblastoma BTL53 glioblastoma

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Figure 12 Results of cell viability assay in three different glioblastoma

1.5*103 cells were seeded in 96-well plates in triplicate and incubated with (2.5, 5, 7.5 and 10 µM) avasimibe for 72 hours. The cell viability was assessed with the EZ4U assay and the dose response curves were established in GraphPad Prism. In the Graph the half-maximal inhibitory concentration (IC50) value that declares the concentration when a decline to 50 % viable cells is reached, is indicated by a line. A) The glioblastoma BTL2 showed no IC50 value in the high passage and low passage(red line) cell line and demonstrated a cell viability of 78% at 10 µM. B) The glioblastoma cell line BTL53 reacted even less to the inhibitor in low passage (red line) and high passage. C) The glioblastoma cell line BTL276 revealed a decrease in cell viability to 46% and 55% in two experiments but also reacted not as sensitive in two further tests. D) BTL2 and BTL53 were additionally treated with 15µM and 20µM avasimibe, however no significant results were obtained.

T98G is a commercially available international human Caucasian glioblastoma cell line that was precisely investigated, because of its high SOAT1 expression. The cell line was tested three times with 2.5-10 µM avasimibe in different passages (Fig.13A). Exposure to the inhibitor resulted in a concentration dependent decrease in cell viability but an IC50 value was nearly missed at 10 µM avasimibe concentration. Approximately 51%, 55% and 59% cells stayed viable at the end of the assay with an average of 55% (0.548 ± 0.088, n=3). Since the data suggested that an IC50 value was almost reached, T98G was also treated with 15 µM and 20 µM. The results revealed that there is an IC50 value at 12.45 µM avasimibe concentration (Fig.13C). The outcome confirmed that the cell line T98G reacts in a concentration dependent manner to avasimibe.

Due to the fact that the melanoma metastases showed very high SOAT1 expression values in both expression study methods, the cell line BTL1423 was screened as well. BTL1423 is a melanoma brain metastasis derived cell line with elevated SOAT1 expression and it was examined in a low passage number. The possible effect of avasimibe was investigated twice, with convergence reaching from 2.5-10 µM (Fig.13B). Results confirmed a concentration dependent decrease in cell viability. The first outcome demonstrated an IC50 value at 9.4 µM avasimibe and at 10 µM roughly 48 % cells stayed viable. The second trial indicated an IC50 value at 8.2 µM avasimibe and approximately 47% viable cells at the end of the assay. Although BTL1423 showed already a significant concentration dependent diminish in cell viability it was also examined with higher concentrations. The third repetition revealed an IC50 value of 9.7 µM. At 20 µM avasimibe concentration the cell viability significantly dropped to 25% viable cells (Fig.13C). In summary, BTL1423 represented the most promising results of all cell lines tested, with the highest decrease in cell viability. To further verify this outcome other melanoma metastases cell lines should be exposed to avasimibe.

A T98 glioblastoma B BTL1423 melanoma

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Figure 13 Comparison of cell viability results in T98G and BTL1423

A) The international glioblastoma cell line indicated cell viabilities of 51%, 55% and 59% at the end of the assay, almost reaching and IC50 value. B) The melanoma cell line BTL1423 showed an IC50 value of 9.4 µM and 8.2 µM. C) T98G and BTL1423 were additionally treated with concentrations of 15µM and 20 µM avasimibe, which resulted in an IC50 value of 12.45 µM for T98G and BTL1423 decreased to a cell viability of 25% at 20 µM. Those two cell lines revealed the highest sensitivity to the inhibitor.

The glioblastoma cell line BTL2183 had low SOAT1 expression and was only tested once in a low passage with 2.5-10 µM (Fig.14A). The cell line appeared to have a small concentration dependent decline, but an IC50 value was not reached and the cell viability stayed at 57% when treated with 10 µM avasimibe concentration. For a precise declaration this cell line has to be tested further but in comparison to the gliosarcoma cell line shown in Figure 14A, BTL2183 revealed slightly more sensitivity. BTL2164 is an urothelial carcinoma metastasis that had one of the lowest SOAT1 expression values of all cell models investigated, therefore it was chosen for treatment with avasimibe but it did not reach an IC50 value when treated with 2.5 -20 µM avasimibe (Fig.14B).

The gliosarcoma cell line BTL385 had moderate SOAT1 expression and was investigated with 2.5-20 µM avasimibe. BTL385 did not show significant changes in cell viability in the experiment where a concentration of 10 µM was tested (Fig.14A). Therefore, a higher concentration of 20 µM avasimibe was also used but the cell viability did not subside meaningful (Fig.14B). The gliosarcoma and the urothelial carcinoma did not exhibit significant sensitivity to avasimibe at high concentrations and no half maximal inhibitory concentrations values could be reached.

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Figure 14 Results of cell viability in different cell lines

A) The glioblastoma cell line BTL2183 was tested one time, which resulted in a decrease to 57% viable cells at 10 µM. The gliosarcoma BTL385 did not decrease below 90% cell viability and showed no sensitivity to the inhibitor. B) The urothelial carcinoma BTL2164

and the gliosarcoma BTL385 did not significantly react to the inhibitor, when tested until 20 µM avasimibe concentration, therefore no IC50 value could be observed.

4.3. Effect of the SOAT1 inhibitor Avasimibe on GBM cells

The aim was to investigate the effects of avasimibe on cells with high and low SOAT1 expression. Therefore, 5*104cells cells were seeded in 6-well plates and cultivated in the absence and presence of avasimibe for 24 hours and 48 hours. An untreated control was included and the experiment was set up in duplicates. Additionally, cells were also examined with a DMSO control, to monitor the effect of the carrier solvent on morphological appearances. Morphological characteristics indicative for apoptotic cell death e.g. cell shape, cell shrinkage, detachment from the surface in addition to variation of cell density were documented through microscopic examination. Visual inspection revealed no obvious changes in morphological features under DMSO exposition.

Seven cell models with varying SOAT1 expression and sensitivity against avasimibe, analyzed by the MTT-test, were examined (Table.11). Out of these, four GBM cell models were exposed to 5 and 10 µM avasimibe and pictures were taken after 24h and 48h, respectively (Fig.15). Furthermore, one gliosarcoma cell line was investigated with moderate SOAT1 expression and two brain metastasis derived cell lines were analyzed. The melanoma brain metastasis cell line BTL1423 demonstrated high SOAT1 expression, while in contrast the urothelial carcinoma metastasis cell line BTL2164 had very low SOAT1 expression. (Table.11)

Table 11 SOAT1 expression of cell models and response to avasimibe

Cell line Classification SOAT1 expression [∆∆CT] Avasimibe IC50 [µM] BTL2 GBM 1.9 >20 T98G GBM 1.5 12.45 BTL276 GBM 0.7 >20 BTL53 GBM 0.6 >20 BTL385 Gliosarcoma 1.2 >20 BTL1423 Melanoma 1.8 9.1 BTL2164 Urothelial carcinoma 0.2 >20

Low SOAT1 expression High SOAT1 expression

A) BTL53 B) BTL276 C) T98G D) BTL2

CO.

DMSO

5µM

10µM

Figure 15 Effect of avasimibe on GBM cell growth

GBM cells with low SOAT1 expression (A and B) and high SOAT1 expression (C and D) were exposed to 5 µM and 10 µM avasimibe for 24 hours and 48 hours. Representative examples are given to demonstrate cell growth and cell density after 48h of avasimibe treatment. DMSO was used as vehicle control.

Exposition of the GBM models BTL53 and BTL276, both with low SOAT1 expression (Table.11), revealed resistance against avasimibe. The cells appeared unaffected after a 24h and 48h incubation period with avasimibe as shown in Figure 15A and 15B. Cells with apoptosis were not present and the cell density was not decreased. A similar effect was shown for the gliosarcoma cell line BTL385 with moderate SOAT1 expression (Table.11).

The GBM cell line BTL2 demonstrated high SOAT1 expression (Table.11), but treatment with avasimibe presented no indication of apoptosis (Fig.15D). After an incubation period of 48h with 10 µM avasimibe, the cells did not reveal cell shrinkage, round-up or detachment from the surface of the 6-well plate and the cell density was not significantly decreased. Regardless of the high SOAT1 status observed in BTL2, no evidence of an impact of avasimibe could be seen.

The glioblastoma cell line T98G presented high SOAT1 expression and an IC50 value of 12.45 µM avasimibe in cell viability assay (Table.11). Microscopic examination of the cell morphology after 10 µM avasimibe treatment for 48 hours showed that a fraction of cells appeared to exhibit apoptotic cell death, because cell shrinkage and round-up of cells was observed (Fig.15C). Regarding the IC50 value of 12.45µM, T98G was further examined with avasimibe concentrations of 15 µM and 20 µM (Fig.16). Increased avasimibe concentrations provoked cell shrinkage, round-up and detachment from the surface of T98G cells even after 24h. Exposure for 48h caused high levels of apoptotic appearing cells combined with low cell density at 15 µM avasimibe concentration. Treatment with 20 µM for 48h resulted in major cell death with only very few viable cells, that did not indicate apoptosis (Fig.16).

T98G control 15µM 20µM

Figure 16 Effect of higher avasimibe concentrations of T98G T98G cells were exposed to 15 µM and 20 µM avasimibe for 24 hours and 48 hours. Representative examples are given to demonstrate cell growth and cell density after 48h of avasimibe treatment.

With regard to brain metastases derived cell lines, the melanoma metastasis cell line BTL1423 with high SOAT1 expression and sensitivity against avasimibe (IC50 = 9.1µM) was examined. Accordingly, a significant impact on cell survival after avasimibe treatment was observed. After 24h incubation the cell density was markedly decreased and a fraction of cells indicated apoptosis at 10 µM, in comparison to the control group and the 5 µM avasimibe concentration. Although cell shrinkage, detachment from the surface and decrease of cell density was observed under 5µM avasimibe exposure for 48h, the by far highest response was obtained after 10 µM/48h avasimibe treatment (Fig.17). The cell density was significantly reduced and only a small percentage of viable cells was present.

BTL1423 control DMSO 5 µM 10 µM

Figure 17 Effect of avasimibe on BTL1423 cell growth

BTL1423 cells were exposed to 5 µM and 10 µM avasimibe for 24 hours and 48 hours. Representative examples are given to demonstrate cell growth and cell density after 48h of avasimibe treatment. DMSO was used as vehicle control.

In contrast, in the urothelial carcinoma metastasis cell line BTL2164 with the lowest SOAT1 expression of all cell lines examined. However, no influence of avasimibe on cell growth and survival became obvious, neither after 24h nor 48h drug exposure.

In summary, the cell lines T98G and BTL1423 with high SOAT1 expression showed sensitivity against avasimibe, whereas in SOAT1 low cell models BTL276 and BTL53 no effects of avasimibe became visible. Interestingly, despite high expression of SOAT1 the cell line BTL2 did not respond to the SOAT1 inhibitor avasimibe.

4.4. Lipid droplet staining assay-BODIPY

The fluorescence lipid dye BODIPY 493/503 was used to determine the presence of lipid droplets in glioblastoma cell lines. The aim was to see if LDs were present in the cell lines with high SOAT1 expression and if there was a difference in the amount between them. For this purpose, 1*104 cells were seeded in two well chamber slides and after an incubation period of 24 hours to allow cell adhesion 0.5 µM, 1 µM or 2 µM BODIPY was tested. In addition, Vectashield antifade mounting medium with DAPI was applied to stain the cell nucleus. Oleic acid is the major end product of de novo fatty acid synthesis and was therefore used as positive control, because it is a potent inducer of triglyceride synthesis and storage. The cells were incubated for 72 h with a concentration of 0.1 mM oleic acid. The number of lipid droplets was not quantified in this experiment, instead only microscopic observation of lipid droplets in various cell lines was exercised.

A B

Figure 18 LD staining with BODIPY and effects of avasimibe in T98G

1*104 cells of T98G were seeded in two well chamber slides and stained with 2µM BODIPY493/503 (green). The nucleus was dyed with Vetashield antifade mounting medium including DAPI (blue). Confocal microscopic examination was performed after 72h. A) Control cells were seeded in medium. They demonstrated a high appearance of lipid droplets. B) Treatment with 10 µM avasimibe was implemented for 48h. Although the inhibitor was used, staining still showed a high number of LDs in T98G.

To examine the correlation between high SOAT1 expression in glioblastoma and the prevalence of lipid droplets T98G was investigated closely, since this cell line presented as one of the highest SOAT1 expression targets. The cells were dyed with 2 µM BODIPY. Microscopic examination of the cells showed a high occurrence of lipid droplets around the cell nucleus, but also throughout the cytoplasm with a difference in size (Fig.18A).

Furthermore, the effect of avasimibe on lipid droplets was investigated in this cell line, since the inhibitor should decrease cholesterol esterification by impeding SOAT1 and therefore blocking LD synthesis. 10 µM concentration was added to one well of the chamber slide for 48 h, while the other one was used as control. Examination demonstrated no significant difference in size and amount of lipid droplets between the control chamber and the treated one. In addition, DAPI staining revealed no changes like apoptotic nuclei in the cell line T98G (Fig.18B).

A B

C D

Figure 19 LD staining with BODIPY and oleic acid

The glioblastoma cell line BTL2 and BTL53 were seeded in two well chamber slides and stained with 2µM BODIPY after 72h. The effect of oleic acid on LD formation was tested. A) BTL2 untreated control cells showed a high number of LDs. B) BTL2 oleic acid control demonstrated a considerably increased lipid droplet yield. Especially the size of individual

LDs was enhanced tremendously. C) No significant LD occurrence could be observed in the control of BTL53. D) After treatment with OA the BTL53 cells indicated LD formation.

The glioblastoma cell line BTL2 was also chosen because of high SOAT1 expression and BTL53 was selected due to a low SOAT1 status. Both cell lines were stained with 2 µM BODIPY. Elevated lipid droplets were observed in BTL2 (Fig.19A), but to a smaller extent than in comparison with T98G. In contrast to the amount of lipid droplets observed in those high SOAT1 expression cell lines BTL53 did not reveal any lipid droplets (Fig.19C), when stained with 2 µM BODIPY but DAPI staining was in order. For this reason, the incubation with oleic acid was tested to see whether or not it would affect the extent of lipid droplets especially in BTL53 where no evidence of LDs was seen. Furthermore, the question was if LD generation could be increased in BTL2, where they were already present in a high amount.

The usage provoked an increase in lipid droplets in number and especially in size in BTL2 (Fig.19B). After treatment with oleic acid even BTL53, which had none before, revealed now lipid droplets around the nucleus with some also very large in size (Fig.19D). This effect was also observed in another study published in HepG2 cell. In this publication the HepG2 cells were treated with 100 µM and 400 μM oleic acid, which increased the number and size of LDs and also raised the level of polar lipids, triacylglycerides and cholesterol esters in lipid droplets. A gain in concentration of OA produced an even bigger effect in the proportion of already large LDs. [172] In addition another publication observed that in glioblastoma cell lines treatment with oleic acid inhibited and lowered SOAT1 knockdown induced cell death. [1]

To confirm that SOAT1 expression values correlate with lipid droplets other cell lines must be examined with BODIPY. Moreover, avasimibe studies on LDs have to be investigated in more detail and to a bigger extent, especially the difference between low grade glioma and high grade glioma in correlation to LD formation.

4.5. Western Blot analysis of SOAT1 and SREBP-1

The aim of this method was to determine the SOAT1 protein status of glioblastoma cell lines and to observe the effects of avasimibe at protein level. Since treatment of cells with avasimibe could manage inhibition of SOAT1 and furthermore lead to affectation of SREBP-1 activation, both proteins were investigated by western blot analysis. SOAT1 is a multi-span integral membrane protein localized in the endoplasmic reticulum, as is the precursor of SREBP-1 transcription factor, while the mature form is transported to the nucleus after proteolytic cleavage. Membrane protein analysis can present challenging, because integral membrane proteins reside in the lipid membrane and they aren’t soluble in water. Hence to study SOAT1 it had to be distributed in aqueous solution first, which was achieved by using different detergents.

Detergents are soluble amphipathic molecules that have a polar (hydrophilic) head group and a nonpolar (hydrophobic) tail group. With an increasing detergent concentration, above the critical micellar concentration (CMC), they are able to form micelles. Due to the unpolar transmembrane helices of the integral membrane proteins they are hydrophobe and insoluble in water. During solubilization proteins migrate from the membrane to the micelles, which form a spherical complex around them. In this formation the polar heads face to the outside and the hydrophobic tails point to the inside, thus enclosing the hydrophobic region of the membrane protein. It is necessary to consider the sensitivity of the desired target to the detergent, because solubilization is a severe process that must be optimized to avoid protein loss, protein inactivation, denaturation and aggregation. [173,174]

Several methods for SOAT1 and SREBP-1 extraction were used, since the amount of the target proteins isolated wasn’t very high. On the one hand RIPA buffer with sodium dodecyl sulfate (SDS) was employed, which is an ionic detergent and on the other hand protein extraction was conducted with Triton X-100, that is a nonionic and milder detergent. In addition, the nuclear and cytoplasmic extraction kit was utilized as a secondary test method. [174]

In addition, the IKA homogenizer rod was applied for mechanical cell disruption, at which the cells get grinded and dispersed by rotating blades. The second technique for physical cell lyses applied was sonication that uses high frequency sound waves to shear the cells. [173,174] After protein isolation the obtained amount was measured with the Micro BCA Protein Assay Kit and afterwards SDS-PAGE and Western Blot was conducted.

One of the main issues with SOAT1 protein isolation was the extraction process of the integral membrane protein. Even though different detergents were used, to optimize the amount of SOAT1 protein, in the end the yield of SOAT1 was not enough to even consider experiments with avasimibe in 6-well plates. The focus therefore stayed on improving the quantity of SOAT1, throughout the isolation process.

The protein extraction starts with a cell disruption process to receive a suspension of membrane fragments/vesicles, soluble proteins, cell debris and remaining intact cells. One of the first steps after cell lysis often is membrane preparation, to isolate the targeted membrane with the integral membrane protein and thereby purifying and increasing the yield. Differential centrifugation is the most frequently applied process for membrane division, because of the different sedimentation rates of the cell components. For example, unbroken cells can be removed through filtration of the homogenate or low speed centrifugation. Afterwards the centrifugation at 600 g for 10 minutes sediments the nuclei. Further centrifugation of always the supernatant yields the different cell constituents. The mitochondrial fraction, lysosomes and peroxisomes are obtained by centrifugation at 15000g for 5 minutes. It is followed by a centrifugation at 100000g for 60 minutes to receive the plasma membrane, fragments of the endoplasmic reticulum and polyribsomes. Since a force of 100000g necessitates an ultracentrifuge to obtain the fragments of the endoplasmic reticulum, which was not available during the experiments, differential centrifugation to yield a higher amount of SOAT1 was not possible. Hence, only total cell lysate with different detergents was used for SOAT1 and SREBP-1 Western Blot. [173,174]

Additionally, in the experiment two different techniques for cell disruption were tested. On the one hand sonication was employed, which uses high frequency sound to provide the necessary energy to disrupt the cell membrane, in combination with a lysis buffer. The cells were placed in an ultrasonic bath with ice water. They were treated two times for 10 second each, with an incubation period in between to prevent protein loss, due to overheating by sonication. The method resulted in no significant increase in total protein concentration and the Western Blot showed no significant difference to the cell lysate treated without sonication.

On the other hand, a homogenizer rode, which is based on the rotor-stator principle, was applied for cell lysis. According to manufacturer’s instructions the medium with cells is drawn in the dispersion head, where a rotor lies within a stationary stator. The suspension is then moved radially through the slots, thus developing strong shear forces to disrupt the cells. The disadvantage of this method was strong foam formation, especially when used with RIPA lysis buffer, due to the SDS detergent. The foam was adhered to the rode and purging it wasn’t an option, since the protein solution would be diluted. Hence there was a slight loss in protein concentration in comparison to only chemical cell lysis. Therefore, this method was not further perused.

Another issue that arose was a very strong unspecific binding of the SOAT1 antibody during Western Blot analysis, which was very problematic, since the amount of SOAT1 protein was sparse. Due to the faint band of the SOAT1 protein at 50 kDa the chemiluminescent detection time had to be longer, but the unspecific band was considerably stronger in antibody binding and positioned around 37 kDa. Therefore, it overshadowed the SOAT1 protein band at 50 kDa or moved it into the background, when the exposure time was extended. A few different methods, to reduce the strong binding of the antibody to the unspecific sample, were tried. Heating to 95°C for 5 minutes did not provide a different result in Western Blot analysis. To rule out insufficient blocking, three different solutions were tested. 1% non-fat milk with 0.5% BSA in TBST, 5% non-fat milk and 10% non-fat milk in TBST were also applied, but no changes in the antibody binding, in any of the different blocking solutions, could be observed.

The HRP conjugated secondary antibody and the substrate were ensured to work according to the manufacturer’s specifications. Additionally, this method was well established in other experiments. The primary antibody was a mouse monoclonal antibody against the recombinant protein corresponding to amino acids 1-131 of SOAT1 of human origin (50kDa). It was tested in different concentrations that resulted in no alterations in the unspecific binding of the antibody. The company tested the antibody in THP-1 cell lysate and also detected a non-specific band around 37 kDa in their published Western Blot data but did not further evaluate this signal.

The SOAT1 protein isolation with Triton X-100 lysis buffer indicated a slightly less effective solubilization of SOAT1, in comparison to the experiments with RIPA buffer, which could be due to the stronger effect of the ionic detergent SDS used in RIPA. Western Blots, where Triton X- 100 buffer was used, demonstrated a significant stronger unspecific binding of the SOAT1 antibody around 37 kDa, than to the SOAT1 target protein at 50 kDa. In Figure 20A an exemplary image of a Triton X-100 Western Blot can be seen.

The melanoma cell lines BTL1423 and BTL1693 did not reveal an intense SOAT1 protein signal, even though both cell lines had a high SOAT1 expression status (Fig.20A). Moreover, the glioblastoma cell lines BTL53 and BTL385 showed merely faint protein bands. Only the glioblastoma cell line BTL2 indicated a meaningful SOAT1 protein value.

The RIPA buffer yielded better results of SOAT1 protein solubilization, but also showed a strong binding of the antibody to the unspecific sample at 37 kDa (Fig.20B). Because the solubility of membrane proteins is influenced by the ionic strength of the buffer and ionic strength of the medium is maintained by NaCl, different concentrations were used for RIPA buffer assembly. Results between RIPA buffer with 150 mM NaCl and 300 mL NaCl did not differ significantly. A different quantity of protein concentration was loaded on the gel to test if there would be a difference in signal intensity. There was no distinction possible between 25 µg and 30 µg, but when 50 µg protein was used the signal to noise ratio was too high, causing worse visualization after chemiluminescent detection and additional protein bands could be seen. The glioblastoma cell line BTL53 revealed a stronger signal in the experiments with RIPA buffer, than in Triton X- 100 analysis (Fig.20). In the Western Blot shown in Figure 20B the cell lines BTL53 and T98G were analyzed in the course of homogenization and normal sample preparation. There was no significant difference in SOAT1 protein between those two techniques. The Thermo scientific NE-PER nuclear and cytoplasmic extraction kit allowed to separate and prepare a cytoplasmic fraction and a nuclear fraction.

The results of the glioblastoma cell line T98G and BTL53 with this extraction method were very similar to the analysis with RIPA buffer in signal intensity of SOAT1 and can be observed in the exemplary Figure 20B. T98G showed no difference in the cytoplasmic fraction compared to the nuclear. BTL53 indicated in the nuclear fraction of the western blot in Figure 20B no signal, but in other experiments a SOAT1 signal could be detected.

Figure 20 Western Blot analysis of SOAT1

Different forms of protein isolation were tested for SOAT1. Two exemplary images demonstrate the results. A) Triton X-100 buffer analysis indicated a significant stronger unspecific binding of the SOAT1 antibody around 37 kDa than to SOAT1 at 50 kDa. Additionally, SOAT1 presented as double band, which could be due to the existing isoforms. The double signal is stronger than in RIPA buffer analysis. B) Extraction with RIPA buffer showed also an unspecific binding at 37 kDa. Homogenization of T98G and BTL53 didn’t present significant stronger results (abbreviation ho.). The T98G cytosolic and nuclear fraction revealed similar findings to RIPA buffer analysis. The BTL53 cytosolic fraction was similar to the experiments with RIPA buffer, only the nuclear fraction showed no signal in this exemplary image.

Sterol regulatory element binding transcription factor 1 (SREBP-1) is detected by the IgG-2A4 antibody, through the N-terminal (basic helix-loop-helix) domain, in both the 125 kDa precursor and the N-terminal cleavage mature fragment. According to the manufacturer’s instructions the cleaved fragment migrates between 60-70 kDa and can present as a cluster of bands on SDS-PAGE, due to phosphorylated forms. SREBP-1 was analyzed with RIPA buffer, Triton X-100 lysis buffer and the NE-PER nuclear and cytoplasmic extraction kit (Fig.21). Because of alternative splicing, there are 6 isoforms of SREBP-1, therefore it can appear as double band on SDS-PAGE in the precursor.

The SREBP-1 precursor form showed a strong signal in the cytoplasmic fraction of the BTL53 and BTL385 cells and a fainter one in the nuclear extraction part, when analyzed with the NE-PER kit (Fig.21A). The cytoplasmic solution also included in both cell lines the mature form. Another signal could be observed in the exemplary image of the nuclear fraction in BTL53, but it was around 80 kDa. In comparison to this extraction method, it was not possible to significantly illustrate the mature form of SREBP-1 in the RIPA buffer analysis (Fig.21B). The precursor can be observed as double signal at 125 kDa and around 60 kDa there is a slight shadow, but it is not significant since the exposure time was already 20 minutes. Additionally, to a simple protein isolation with lysis buffer, sonication and homogenization were tested. Both methods did not result in significant changes compared to the plain protein extraction. The Triton X-100 buffer was less effective than the RIPA buffer and the NE-PER kit and secondary the mature form couldn’t be observed (Fig.21).

Figure 21 Western Blot analysis of SREBP-1

Different forms of protein isolation were tested for SREBP-1. Two exemplary images demonstrate the results. A) The SREBP-1 precursor at 125 kDa and the mature form between 60-70 kDa were revealed with the NE-PER nuclear and cytoplasmic extraction kit. B) The sequential arrangement of the RIPA buffer isolation from 1-8 included T98G 25 µg, T98G 30 µg, T98G 25 µg homogenized, T98G 30 µg homogenized, BTL53 25 µg, BTL53 30 µg, BTL53 25 µg homogenized, BTL53 30 µg homogenized. No significant difference between 25 µg and 30 µg protein concentration could be observed. Additionally no variation between the homogenization method and the normal extraction were seen. The mature form of SREBP-1 could not be demonstrated with the RIPA buffer analysis.

5. Discussion

The prognosis for high grade gliomas is still poor and new successful treatment options are necessary. GBM is a metabolically active tumor showing enhanced lipogenesis resulting in increased lipid levels which promote tumor growth [1,50,73,175]. Therefore, identifying components of the lipid metabolism, which are involved in tumorigenesis may provide a new strategy to treat cancer including gliomas. The aim of the current thesis was to analyze 1) whether and to which extent the ER-located sterol O-acyltransferase (SOAT/also named acyl- CoA:cholesterol acyltransferase, ACAT) is expressed in a panel of brain tumors derived cell cultures, 2) the impact of SOAT1 inhibition on cell viability and cell growth and 3) the influence of this blockade on sterol regulatory element-binding protein-1 (SREBP-1).

SOAT1 mRNA expression

SOAT1, the central mediator of cholesterol esterification converts ER cholesterol to cholesterol esters that are then stored in lipid droplets, which serve as an energy reservoir during cell growth. This mechanism prevents the negative feedback loop of SREBP-1 suppression and facilitates a highly active lipid metabolism in cancer cells [1]. Within this master thesis SOAT1 expression was investigated by semi-quantitative and real-time qRT-PCR in a very large panel of 106 brain tumor derived primo-cell cultures and cell lines including low (n= 36) and high grade (n=43) gliomas, brain metastases (n=23), meningioma (n=1) and osteosarcoma (n=1). Tissue from epilepsy surgery was in the midrange of SOAT1 expression (Fig.10) and included as non-tumor tissue. The data revealed SOAT1 expression at varying levels in the various tumor subgroups and mean expression levels were significantly different between high and low grade gliomas (p=0.0012). As far as it is known, this is the first study showing SOAT1 expression in such a large cohort of different tumor entities. High SOAT1 expression in GBM is in accordance with the literature, however by now only a few GBM cell lines were tested [1; 176]. Additionally, high SOAT1 expression levels were also found in cell lines derived from melanoma brain metastases. To the best of our knowledge these are the first data on SOAT1 expression in melanomas so far.

Impact of SOAT1 inhibition on cell viability and cell growth

Based on the fact that GBM are highly positive for SOAT1 expression, the SOAT1 inhibitor avasimibe was tested in selected GBM cell lines in different passage numbers (high versus low). Surprisingly, irrespective of the extent of SOAT1 expression level and passage number the effect of avasimibe, on cell viability, cell growth and SOAT1 expression was modest. The by far highest sensitivity against avasimibe was found in T98G (IC50 12.45 µM) and the melanoma brain metastasis derived cell line BTL1423 (IC50 9.1 µM). These results were reflected by showing a distinct decrease in cell growth after avasimibe exposure in the respective cell lines. At the moment little is known about SOAT1 mediated cholesterol esterification in melanomas. In the analyzed panel the melanoma metastases were high in SOAT1 expression (mean 1.8) comparable to high grade gliomas (mean 1.7) and accordingly, a very good response to the SOAT1 inhibitor avasimibe was obvious in the one melanoma cell line tested. However, downregulation of SOAT1 after avasimibe exposition could not be detected in the analyzed T98G and melanoma metastasis BTL1423. This was in contrast to the results published by Bemlih et al [176], who showed avasimibe induced concentration-dependent (2.5 and 7.5 µM) downregulation of SOAT1 mRNA in GBM. Interestingly, one would expect the blocking of SOAT1 to result in inhibition of the enzyme accompanied by downregulation of downstream targets such as SREBP-1 or FASN. However, the effect on SREBP-1 regulated lipogenesis enzymes (e.g. FASN, ACC, SCD1) was missing in this paper [176].This was proved by Geng et al [1] by using a shSOAT1 vector induced knockdown, which led to significant inhibition of SREBP-1 activation followed by downregulation of the aforementioned enzymes. Unfortunately, establishing a SREBP-1 western blot was tricky and time consuming. Therefore, the impact of avasimibe on selected cell lines of the panel could not be tested and adequate results were not able to be obtained within the time-frame of this master thesis.

Another effect of SOAT1 inhibition is the blockade of LD formation [1]. Large amounts of LDs were found in GBM, which inversely correlated with overall survival [1]. In the study the staining of LDs was successfully performed and high amounts of LDs were detected in GBM cell lines, yet, in contrast to Geng et al [1] failed to decrease under avasimibe treatment.

Impact of SOAT1 inhibition on SREBP-1

The transcription factor SREBP-1 is a key regulator of the fatty acid and cholesterol biosynthesis [177] and known to be activated in GBM [175, 178]. SREBP-1 activity is linked to sterol levels because of regulation via the negative feedback mechanism [179]. Additionally to sterol-mediated regulation, SREBP-1 has been demonstrated to be activated by the PI3K/Akt pathway in cancer cells [180]. Inhibition of SOAT1 by avasimibe was accompanied by downregulation of the N-terminal cleavage form of SREBP-1, normally acting as transcription factor in the nuclei [1]. Ongoing experiments will clarify the impact of SREBP-1 inhibition by targeting SOAT1 and the PI3K/Akt pathway on the lipid synthesis and cell growth of GBM cells analyzed for SOAT1 in the current thesis and additionally GBM patient survival.

Summing up the data revealed that SOAT1 is highly expressed in GBM and melanoma metastases. However, for GBM there is no clear-cut association between SOAT1 expression and the response to the SOAT1 inhibitor avasimibe. For melanoma metastases the first investigations revealed promising results and further experiments are aimed to profoundly study the effect of targeting the lipid metabolism via SOAT1. In conclusion, SOAT1 is a promising therapeutic target for selected tumors, but further studies are needed to clarify the impact of lipid metabolism inhibition on SREBP-1-regulated downstream lipogenesis factors and its importance in the clinical situation.

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7. List of figures

Figure 1 Overview of adult diffuse glioma ...... 2 Figure 2 Lipid biosynthesis...... 6 Figure 3 Activation and cleavage of SREBP-1 ...... 13 Figure 4 Amino acid sequence of human SOAT1 ...... 16 Figure 5 Lipid droplet at the endoplasmic reticulum membrane ...... 18 Figure 6 Effects of Avasimibe ...... 22 Figure 7 Overview of real-time RT-PCR graphs ...... 30 Figure 8 SOAT1 expression in primary and secondary brain tumors analyzed by RT-PCR ...... 44 Figure 9 Data visualization of unpaired t-test results after RT-PCR analysis ...... 45 Figure 10 SOAT1 expression in primary and secondary brain tumors analyzed by real-time qRT- PCR ...... 47 Figure 11 Data visualization of unpaired t-test results after real-time qRT-PCR analysis ...... 49 Figure 12 Results of cell viability assay in three different glioblastoma ...... 52 Figure 13 Comparison of cell viability results in T98G and BTL1423 ...... 54 Figure 14 Results of cell viability in different cell lines ...... 55 Figure 15 Effect of avasimibe on GBM cell growth ...... 57 Figure 16 Effect of higher avasimibe concentrations of T98G ...... 58 Figure 17 Effect of avasimibe on BTL1423 cell growth...... 59 Figure 18 LD staining with BODIPY and effects of avasimibe in T98G ...... 60 Figure 19 LD staining with BODIPY and oleic acid ...... 61 Figure 20 Western Blot analysis of SOAT1 ...... 67 Figure 21 Western Blot analysis of SREBP-1 ...... 68

8. List of tables

Table 1 Reaction components for one-time preparation of RT-PCR ...... 27 Table 2 Primer sequence and reaction condition RT-PCR ...... 28 Table 3 Reaction components for one-time preparation of qRT-PCR ...... 31 Table 4 Primer sequence and cycling conditions qRT-PCR ...... 32 Table 5 Schematic overview of the NE-PER nuclear and cytoplasmic extraction kit ...... 37 Table 6 Classification of cancer cell lines ...... 43 Table 7 Results of SOAT1 expression in primary and secondary brain tumors analyzed with RT- PCR ...... 44 Table 8 Results of SOAT1 expression in tumor metastases analyzed with RT-PCR ...... 45 Table 9 Results of SOAT1 expression in LGG and HGG analyzed with real-time qRT-PCR ...... 48 Table 10 Results of SOAT1 expression in tumor metastases analyzed with real-time qRT-PCR ...... 48 Table 11 SOAT1 expression of cell models and response to avasimibe ...... 56

9. Appendix

Material list

Product Manufacturer Catalog number 10 X TGS Buffer BIO RAD 161-0732 10X TBS BIO RAD 170-6435 Acrylamide/Bis Solution 40% BIO RAD 161-0146 29:1 500ML AmershamHybond P 0.45 GE healthcare life sciences PVDF 150mmx4m 1 roll/PK amersham 10600029 APS Ammonium persulfate SIGMA lifescience molecular 100g A9164 Avasimibe SIGMA lifescience PZ0190-5MG BODIPY 493/503 ThermoFisher Scientific D3922 Boricacid SIGMA lifescience B7901-500G Bovine Serum Albumin SIGMA lifescience A8022_50G Bromphenolblau SIGMA B-8026 5g Chamber slides ThermoFisher Scientific 154852PK Chloroform SIGMA C-2432 DimethylSulfoxide (DMSO) SIGMA lifescience D2650-100ML ECL™ Prime Western GE healthcare life Blotting System sciences amersham RPN2232 EDTA SIGMA lifescience E5134-250G Ethanol absolut Merck 1009832500 Extra Thick BlotPaper BIO RAD 1703968 Protean 14x16cm EZ4U easy for you cell Biomedica BI5000 viability assay FBS, heat Inactivated (Fetal Bovine Serum, qualified,heat Life Technologies Gibco 10500-064 inactivated, E.U.-approved, South America Origin) Ficoll400 SIGMA lifescience F2637-10G GAPDH Primer antisense EurofinsGenomics GAPDH Primer sense EurofinsGenomics GELRED Nucleic acid gel BIOTIUM No41003 stain Glycine 500 g SIGMA lifescience G8898 Igepal CA630 SIGMA lifescience I8896-50ML InnuSOLV RNA Reagent Analyticjena 845-SB-2090100 MagicMark™ XP Western Invitrogen LC5602 Protein Standard Methanol 2,5L MERCK 1060082500 MicroBCA Protein assay Kit PAA 23235 Mycoplasma Off Minerva Biolabs 117048 Na-Doc Applichem A1531,0025 NE-PER nuclear and cytoplasmic extraction Thermoscientific 78833 reagent PBS PAA H15-001 Penicillin-Streptomycin Gibco/Life technologies 151400122 Perfect DNA ladder Novagen 70539-0,5 ml

Ponceau S solution SIGMA lifescience P7170-1L Precision Plus Protein BIO RAD 161-0374 Standards -dual color Proteases inhibitor Merck 5391341 QIAGEN OneStep RT-PCR Qiagen Kit 210212 Rotor-Gene SYBR Green Qiagen RT-PCR Kit 204174 Rabbit anti-Mouse IgG (H+L) Thermofisherscientific 31450 Secondary Antibody, HRP RPMI 1640 Medium with L- ThermoFisher Scientific Glutamine 21875034 SDS (Sodiumdodecylsulfate) SIGMA Aldrich 25g L4509-25g SOAT1 Santa cruzbiotechnology sc-69836 SOAT1 Primer fw EurofinsGenomics SOAT1 Primer rv EurofinsGenomics Sodiumchloride Calbiochem 567441-500G SREBP-1 BD pharmingen 557036 TEMED BIO RAD 161-0800 Triton-X SIGMA lifescience T8787-100ML Trizmabase 500g SIGMA lifescience T-1503 Trizma Hydrochloride SIGMA lifescience T3253-500G Trockenmilch- fixmilch Maresi instant 300g Trypan Blue solution 0.4% SIGMA-aldrich 93595 Trypsin EDTA 0,05%, 100 ml Gibcoby Life Technologies 25300-054 Tween20 100 mL SIGMA lifescience P5927 Vectashield Vector H-1200