An Experimental Model of Prostatic Inflammation for Drug Discovery

There is increasing evidence to support a significant role for chronic non-bacterial, prostatic inflammation in the development of human voiding dysfunction and prostate cancer. Their increased prevalence with age suggests that the decrease of testosterone concentration and/or the ratio of testosterone-to-estradiol in serum may have a role in their development. The main objective of this study was to explore prostatic inflammation and its relationship with voiding dysfunction and prostate carcinogenesis by developing an experimental model. A novel selective estrogen receptor modulator (SERM), fispemifene, was tested for the prevention and treatment of prostatic inflammation in this model. Combined treatment of adult Noble rats with testosterone and estradiol for 3 to 6 weeks induced gradually developing prostatic inflammation in the dorsolateral prostatic lobes. Inflammatory cells, mainly T-lymphocytes, were first seen around capillaries. Thereafter, the lymphocytes migrated into the stroma and into periglandular space. When the treatment time was extended to 13 weeks, the number of inflamed acini increased. Urodynamical recordings indicated voiding dysfunction. When the animals had an above normal testosterone and estradiol concentrations but still had a decreased testosterone-to-estradiol ratio in serum, they developed obstructive voiding. Furthermore, they developed precancerous lesions and prostate cancers in the ducts of the dorsolateral prostatic lobes. Interestingly, inflammatory infiltrates were observed adjacent to precancerous lesions but not in the adjacency of adenocarcinomas suggesting that inflammation has a role in the early stages of prostate carcinogenesis. Fispemifene, a novel SERM tested in this experimental model, showed anti-inflammatory action by attenuating the number of inflamed acini in the dorsolateral prostate. Fispemifene exhibited also antiestrogenic properties by decreasing expression of estrogen-induced biomarkers in the acinar epithelium. These findings suggest that SERMs could be considered as a new therapeutic possibility in the prevention and in the treatment of chronic prostatic inflammation

Luminescence-based assay methods in drug discovery

The drug discovery process is facing new challenges in the evaluation process of the lead compounds as the number of new compounds synthesized is increasing. The potentiality of test compounds is most frequently assayed through the binding of the test compound to the target molecule or receptor, or measuring functional secondary effects caused by the test compound in the target model cells, tissues or organism. Modern homogeneous high-throughput-screening (HTS) assays for purified estrogen receptors (ER) utilize various luminescence based detection methods. Fluorescence polarization (FP) is a standard method for ER ligand binding assay. It was used to demonstrate the performance of two-photon excitation of fluorescence (TPFE) vs. the conventional one-photon excitation method. As result, the TPFE method showed improved dynamics and was found to be comparable with the conventional method. It also held potential for efficient miniaturization. Other luminescence based ER assays utilize energy transfer from a long-lifetime luminescent label e.g. lanthanide chelates (Eu, Tb) to a prompt luminescent label, the signal being read in a time-resolved mode. As an alternative to this method, a new single-label (Eu) time-resolved detection method was developed, based on the quenching of the label by a soluble quencher molecule when displaced from the receptor to the solution phase by an unlabeled competing ligand. The new method was paralleled with the standard FP method. It was shown to yield comparable results with the FP method and found to hold a significantly higher signal-tobackground ratio than FP. Cell-based functional assays for determining the extent of cell surface adhesion molecule (CAM) expression combined with microscopy analysis of the target molecules would provide improved information content, compared to an expression level assay alone. In this work, immune response was simulated by exposing endothelial cells to cytokine stimulation and the resulting increase in the level of adhesion molecule expression was analyzed on fixed cells by means of immunocytochemistry utilizing specific long-lifetime luminophore labeled antibodies against chosen adhesion molecules. Results showed that the method was capable of use in amulti-parametric assay for protein expression levels of several CAMs simultaneously, combined with analysis of the cellular localization of the chosen adhesion molecules through time-resolved luminescence microscopy inspection.

Probing MST1 Kinase Sequence and Structure for Rational Drug Discovery (Targeting diabetes by blocking protein-protein interactions)

Apoptotic beta cell death is an underlying cause majorly for type I and to a lesser extent for type II diabetes. Recently, MST1 kinase was identified as a key apoptotic agent in diabetic condition. In this study, I have examined MST1 and closely related kinases namely, MST2, MST3 and MST4, aiming to tackle diabetes by exploring ways to selectively block MST1 kinase activity. The first investigation was directed towards evaluating possibilities of selectively blocking the ATP binding site of MST1 kinase that is essential for the activity of the enzymes. Structure and sequence analyses of this site however revealed a near absolute conservation between the MSTs and very few changes with other kinases. The observed residue variations also displayed similar physicochemical properties making it hard for selective inhibition of the enzyme. Second, possibilities for allosteric inhibition of the enzyme were evaluated. Analysis of the recognized allosteric site also posed the same problem as the MSTs shared almost all of the same residues. The third analysis was made on the SARAH domain, which is required for the dimerization and activation of MST1 and MST2 kinases. MST3 and MST4 lack this domain, hence selectivity against these two kinases can be achieved. Other proteins with SARAH domains such as the RASSF proteins were also examined. Their interaction with the MST1 SARAH domain were evaluated to mimic their binding pattern and design a peptide inhibitor that interferes with MST1 SARAH dimerization. In molecular simulations the RASSF5 SARAH domain was shown to strongly interact with the MST1 SARAH domain and possibly preventing MST1 SARAH dimerization. Based on this, the peptidic inhibitor was suggested to be based on the sequence of RASSF5 SARAH domain. Since the MST2 kinase also interacts with RASSF5 SARAH domain, absolute selectivity might not be achieved.

Study of ligand-based virtual screening tools in computer-aided drug design

Virtual screening is a central technique in drug discovery today. Millions of molecules can be tested in silico with the aim to only select the most promising and test them experimentally. The topic of this thesis is ligand-based virtual screening tools which take existing active molecules as starting point for finding new drug candidates. One goal of this thesis was to build a model that gives the probability that two molecules are biologically similar as function of one or more chemical similarity scores. Another important goal was to evaluate how well different ligand-based virtual screening tools are able to distinguish active molecules from inactives. One more criterion set for the virtual screening tools was their applicability in scaffold-hopping, i.e. finding new active chemotypes. In the first part of the work, a link was defined between the abstract chemical similarity score given by a screening tool and the probability that the two molecules are biologically similar. These results help to decide objectively which virtual screening hits to test experimentally. The work also resulted in a new type of data fusion method when using two or more tools. In the second part, five ligand-based virtual screening tools were evaluated and their performance was found to be generally poor. Three reasons for this were proposed: false negatives in the benchmark sets, active molecules that do not share the binding mode, and activity cliffs. In the third part of the study, a novel visualization and quantification method is presented for evaluation of the scaffold-hopping ability of virtual screening tools.

A Farewell to Flat Biology. Three-dimensional Cell Culture Models in Cancer Drug Target Identification and Validation

Cells of epithelial origin, e.g. from breast and prostate cancers, effectively differentiate into complex multicellular structures when cultured in three-dimensions (3D) instead of conventional two-dimensional (2D) adherent surfaces. The spectrum of different organotypic morphologies is highly dependent on the culture environment that can be either non-adherent or scaffold-based. When embedded in physiological extracellular matrices (ECMs), such as laminin-rich basement membrane extracts, normal epithelial cells differentiate into acinar spheroids reminiscent of glandular ductal structures. Transformed cancer cells, in contrast, typically fail to undergo acinar morphogenic patterns, forming poorly differentiated or invasive multicellular structures. The 3D cancer spheroids are widely accepted to better recapitulate various tumorigenic processes and drug responses. So far, however, 3D models have been employed predominantly in the Academia, whereas the pharmaceutical industry has yet to adopt a more widely and routine use. This is mainly due to poor characterisation of cell models, lack of standardised workflows and high throughput cell culture platforms, and the availability of proper readout and quantification tools. In this thesis, a complete workflow has been established entailing well-characterised 3D cell culture models for prostate cancer, a standardised 3D cell culture routine based on high-throughput-ready platform, automated image acquisition with concomitant morphometric image analysis, and data visualisation, in order to enable large-scale high-content screens. Our integrated suite of software and statistical analysis tools were optimised and validated using a comprehensive panel of prostate cancer cell lines and 3D models. The tools quantify multiple key cancer-relevant morphological features, ranging from cancer cell invasion through multicellular differentiation to growth, and detect dynamic changes both in morphology and function, such as cell death and apoptosis, in response to experimental perturbations including RNA interference and small molecule inhibitors. Our panel of cell lines included many non-transformed and most currently available classic prostate cancer cell lines, which were characterised for their morphogenetic properties in 3D laminin-rich ECM. The phenotypes and gene expression profiles were evaluated concerning their relevance for pre-clinical drug discovery, disease modelling and basic research. In addition, a spontaneous model for invasive transformation was discovered, displaying a highdegree of epithelial plasticity. This plasticity is mediated by an abundant bioactive serum lipid, lysophosphatidic acid (LPA), and its receptor LPAR1. The invasive transformation was caused by abrupt cytoskeletal rearrangement through impaired G protein alpha 12/13 and RhoA/ROCK, and mediated by upregulated adenylyl cyclase/cyclic AMP (cAMP)/protein kinase A, and Rac/ PAK pathways. The spontaneous invasion model tangibly exemplifies the biological relevance of organotypic cell culture models. Overall, this thesis work underlines the power of novel morphometric screening tools in drug discovery.

High Throughput Purification of Combinatorial Libraries by Preparative LC/MS

Viime vuosien nopea kehitys on kiihdyttänyt uusien lääkkeiden kehittämisprosessia. Kombinatorinen kemia on tehnyt mahdolliseksi syntetisoida suuria kokoelmia rakenteeltaan toisistaan poikkeavia molekyylejä, nk. kombinatorisia kirjastoja, biologista seulontaa varten. Siinä molekyylien rakenteeseen liittyvä aktiivisuus tutkitaan useilla erilaisilla biologisilla testeillä mahdollisten "osumien" löytämiseksi, joista osasta saatetaan myöhemmin kehittää uusia lääkeaineita. Jotta biologisten tutkimusten tulokset olisivat luotettavia, on syntetisoitujen komponenttien oltava mahdollisimman puhtaita. Tämän vuoksi tarvitaan HTP-puhdistusta korkealaatuisten komponenttien ja luotettavan biologisen tiedon takaamiseksi. Jatkuvasti kasvavat tuotantovaatimukset ovat johtaneet näiden puhdistustekniikoiden automatisointiin ja rinnakkaistamiseen. Preparatiivinen LC/MS soveltuu kombinatoristen kirjastojen nopeaan ja tehokkaaseen puhdistamiseen. Monet tekijät, esimerkiksi erotuskolonnin ominaisuudet sekä virtausgradientti, vaikuttavat preparatiivisen LC/MS puhdistusprosessin tehokkuuteen. Nämä parametrit on optimoitava parhaan tuloksen saamiseksi. Tässä työssä tutkittiin emäksisiä komponentteja erilaisissa virtausolosuhteissa. Menetelmä kombinatoristen kirjastojen puhtaustason määrittämiseksi LC/MS-puhdistuksen jälkeen optimoitiin ja määritettiin puhtaus joillekin komponenteille eri kirjastoista ennen puhdistusta.

Simulation methods in the modelling of bioaffinity assays

Computational model-based simulation methods were developed for the modelling of bioaffinity assays. Bioaffinity-based methods are widely used to quantify a biological substance in biological research, development and in routine clinical in vitro diagnostics. Bioaffinity assays are based on the high affinity and structural specificity between the binding biomolecules. The simulation methods developed are based on the mechanistic assay model, which relies on the chemical reaction kinetics and describes the forming of a bound component as a function of time from the initial binding interaction. The simulation methods were focused on studying the behaviour and the reliability of bioaffinity assay and the possibilities the modelling methods of binding reaction kinetics provide, such as predicting assay results even before the binding reaction has reached equilibrium. For example, a rapid quantitative result from a clinical bioaffinity assay sample can be very significant, e.g. even the smallest elevation of a heart muscle marker reveals a cardiac injury. The simulation methods were used to identify critical error factors in rapid bioaffinity assays. A new kinetic calibration method was developed to calibrate a measurement system by kinetic measurement data utilizing only one standard concentration. A nodebased method was developed to model multi-component binding reactions, which have been a challenge to traditional numerical methods. The node-method was also used to model protein adsorption as an example of nonspecific binding of biomolecules. These methods have been compared with the experimental data from practice and can be utilized in in vitro diagnostics, drug discovery and in medical imaging.

Biomolecular screening for inhibitors of butyrylcholinesterase : identification and characterization using in vitro and in silico tools

Drug discovery is a continuous process where researchers are constantly trying to find new and better drugs for the treatment of various conditions. Alzheimer’s disease, a neurodegenerative disease mostly affecting the elderly, has a complex etiology with several possible drug targets. Some of these targets have been known for years while other new targets and theories have emerged more recently. Cholinesterase inhibitors are the major class of drugs currently used for the symptomatic treatment of Alzheimer’s disease. In the Alzheimer’s disease brain there is a deficit of acetylcholine and an impairment in signal transmission. Acetylcholinesterase has therefore been the main target as this is the main enzyme hydrolysing acetylcholine and ending neurotransmission. It is believed that by inhibiting acetylcholinesterase the cholinergic signalling can be enhanced and the cognitive symptoms that arise in Alzheimer’s disease can be improved. Butyrylcholinesterase, the second enzyme of the cholinesterase family, has more recently attracted interest among researchers. Its function is still not fully known, but it is believed to play a role in several diseases, one of them being Alzheimer’s disease. In this contribution the aim has primarily been to identify butyrylcholinesterase inhibitors to be used as drug molecules or molecular probes in the future. Both synthetic and natural compounds in diverse and targeted screening libraries have been used for this purpose. The active compounds have been further characterized regarding their potencies, cytotoxicity, and furthermore, in two of the publications, the inhibitors ability to also inhibit Aβ aggregation in an attempt to discover bifunctional compounds. Further, in silico methods were used to evaluate the binding position of the active compounds with the enzyme targets. Mostly to differentiate between the selectivity towards acetylcholinesterase and butyrylcholinesterase, but also to assess the structural features required for enzyme inhibition. We also evaluated the compounds, active and non-active, in chemical space using the web-based tool ChemGPS-NP to try and determine the relevant chemical space occupied by cholinesterase inhibitors. In this study, we have succeeded in finding potent butyrylcholinesterase inhibitors with a diverse set of structures, nine chemical classes in total. In addition, some of the compounds are bifunctional as they also inhibit Aβ aggregation. The data gathered from all publications regarding the chemical space occupied by butyrylcholinesterase inhibitors we believe will give an insight into the chemically active space occupied by this type of inhibitors and will hopefully facilitate future screening and result in an even deeper knowledge of butyrylcholinesterase inhibitors.

From protein structure to function with bioinformatics

It has long been known that amino acids are the building blocks for proteins and govern their folding into specific three-dimensional structures. However, the details of this process are still unknown and represent one of the main problems in structural bioinformatics, which is a highly active research area with the focus on the prediction of three-dimensional structure and its relationship to protein function. The protein structure prediction procedure encompasses several different steps from searches and analyses of sequences and structures, through sequence alignment to the creation of the structural model. Careful evaluation and analysis ultimately results in a hypothetical structure, which can be used to study biological phenomena in, for example, research at the molecular level, biotechnology and especially in drug discovery and development. In this thesis, the structures of five proteins were modeled with templatebased methods, which use proteins with known structures (templates) to model related or structurally similar proteins. The resulting models were an important asset for the interpretation and explanation of biological phenomena, such as amino acids and interaction networks that are essential for the function and/or ligand specificity of the studied proteins. The five proteins represent different case studies with their own challenges like varying template availability, which resulted in a different structure prediction process. This thesis presents the techniques and considerations, which should be taken into account in the modeling procedure to overcome limitations and produce a hypothetical and reliable three-dimensional structure. As each project shows, the reliability is highly dependent on the extensive incorporation of experimental data or known literature and, although experimental verification of in silico results is always desirable to increase the reliability, the presented projects show that also the experimental studies can greatly benefit from structural models. With the help of in silico studies, the experiments can be targeted and precisely designed, thereby saving both money and time. As the programs used in structural bioinformatics are constantly improved and the range of templates increases through structural genomics efforts, the mutual benefits between in silico and experimental studies become even more prominent. Hence, reliable models for protein three-dimensional structures achieved through careful planning and thoughtful executions are, and will continue to be, valuable and indispensable sources for structural information to be combined with functional data.

Unconventional integrin-ligand interactions

Integrins are cell surface adhesion and signaling receptors. Cells use integrins to attach to the extracellular matrix and to other cells, as well as for sensing their environment. In addition to adhesion and migration, integrins have been shown to be important for many biological processes including apoptosis, cell proliferation, and differentiation into specific tissues. Many important next generation biological drugs inhibit integrin functions. Thus, research into interactions between integrins and their ligands under different physiological and pathological conditions is not only of academic interest, but is also important for the field of drug discovery. In this Ph.D. project, the functions of integrin-ligand interactions were studied under different physiologically interesting conditions including 1) human echovirus 1 binding to integrin α2β1, 2) integrin α2β1 binding to collagen under flow conditions, 3) integrin α2β1 binding to a ligand in the presence of the angiogenesis inhibitor histidine rich glycoprotein (HRG) and 4) integrin binding to posttranslationally citrullinated ligands. As a result of the project, we could show that for each condition the integrin-ligand interaction is somewhat unconventional. 1) Echovirus 1 binds only to non-activated conformations of integrin α2β1. 2) Surprisingly, the non-activated conformation is also the primary conformation of integrin α2β1 when it binds to collagen under flow conditions, like when platelets adhere to subendothelial collagen in vascular injuries. In addition, the pre-activation of integrin α2β1 does not increase adhesion under flow. 3) HRG binds to integrin α2β1 through a low-affinity interaction that inhibits integrin binding to collagen. This shows that low affinity interactions could be biologically relevant and possibly regulate angiogenesis. 4) The citrullination of collagen, a posttranslational modification reported to occur in rheumatoid arthritis, specifically inhibits the binding of integrin α10β1 and α11β1, but does not affect the binding of α1β1 ja α2β1. On the other hand, the citrullination of isoDGR in fibronectin and RGD in pro-TGF- β:n inhibit integrin binding completely. Citrullination seems to be an inflammation related process and integrin ligands become citrullinated frequently in vivo. This Ph.D. thesis suggests that unconventional interaction mechanisms between integrins and their ligands, such as posttranslational modifications, low affinity interactions, and non-activated integrin conformations, can have an important role in pathological processes. The study of these kinds of integrin-ligand interactions is important for understanding biological phenomena more deeply. The research might also be beneficial for the development of integrin based therapies for treating diseases.

Globalization of pharmaceutical R&D. Pharmaceutical R&D governance forms in People's Republic of China

Yrityksen selviytyminen ja menestyminen ovat riippuvaisia sen kyvystä innovoida, luoda tietoa ja hyödyntää tietämystä ja keksintöjä (Dunk ja Kilgore 2001). Yrityksen menestyminen erityisesti korkean teknologian alalla on siten suoraan riippuvainen sen T&T:stä, johon tehdyt investoinnit tuovat merkittäviä taloudellisia etuja yritykselle uusien tuotteiden, palveluiden ja prosessien muodossa (McEvily ja Chakravarthy 1999). Teknologinen etumatka ja sen tuotteistaminen innovatiivisiksi tarjoamiksi mahdollistaa monopolististen etujen saavuttamisen yrityksen kansainvälisessä kilpailussa (Lall 1977). Tämä kaltainen kilpailuetu voidaan saavuttaa yrityksen kyvyllä yhdistää maantieteellisesti hajautettu T&T:nsä tehokkaaksi verkostoksi (Porter 1986). Boehen (2008) mukaan T&T:n globalisoitumista voidaan johtaa eri hallintömuodoilla: T&T:n kansainvälistymisellä, T&T:n ulkomaille sijoittamisella ja T&T ulkomaille ulkoistamisella. T&T:n globalisoituminen on osa 2000-luvun taloudellista muutosta, ja sille on esitetty useita vaikuttavia tekijöitä, kuten kustannuserot, työvoimaresurssit, erityisosaamiskeskukset, paikallinen teknologia osaaminen ja kohdemarkkinoiden potentiaali (bardhan 2006; Norwood, ym. 2006; von Zedtwitz ja Gassmann 2002). Tutkimuksen on osoitettu eroavan tuotekehityksestä ja eri tekijöiden on osoitettu vaikuttavan niihin (von Zedtwitz ja Gassmann 2002; Leifer ja Triscari 1987). Samoin T&T on osoitettu olevan jatkumo perustavanlaatuisesta soveltavaan ja lääkekehityksen muodostavan vastaavan T&T jatkumon (Lall 1980; Iansiti 1993), jonka yksittäiset osat vaikuttavat sen hallintomuotoon. Tutkimus esittää eri tekijöitä voivan hyödyntää hallintomuodosta riippuen. Tätä tutkimusta varten tutkija haastatteli lääketeollisuuden johtajia Kiinassa vahvistaakseen tai hylätäkseen eri tekijöitä ja niiden suhdetta lääketeollisen T&T:n hallintomuotoihin. Markkinoiden todettiin olevan ensisijainen tekijä mutta myös kustannuserojen, insentiivien, työvoimaresurssien ja erityisosaamiskeskusten merkitys T&T:n globalisoitumiseen vaikuttavina tekijöinä vahvistettiin yhdessä perusvaatimusten ja riskitekijöiden kanssa. Tutkimuksessa vahvistetaan myös lääketeollisen T&T-jatkumon vaikutus ja esitetään viitekehys hallintomuodoille.

Globalization of pharmaceutical R&D Pharmaceutical R&D governance forms in People's Republic of China

Firm's survival and success, which are dependent on its ability to innovate, to create knowledge and to capitalize on inventions and know-how, is in essence directly linked to its R&D process (Dunk and Kilgore 2001). Especially in technology driven industries, such as the pharmaceuticals, there are significant positive returns to R&D investments through introduction of new or improved products and services (McEvily and Chakravarthy 1999). Technological lead and its transformation to innovative products as fruits of corporate R&D can be seen as monopolistic advantage that helps enterprises to compete in today’s market (Lall 1977). This competitive advantage can be derived from corporation's ability to integrate its activities across geographic locations (Porter 1986). According to Boehe (2008) globalization of R&D can executed with different governance forms: R&D internationalization, R&D offshoring or R&D offshore outsourcing. Globalization of R&D is intervened with the changes in global economy of the 21st century. Some studies argue for its influencing factors to be access to vast skilled labor pools and centers of excellence (Bardhan 2006). Other studies indicate the R&D cost differentials between countries to be the major expected benefit (Norwood et al. 2006). Von Zedtwitz and Gassmann (2002) presented benefits as divided to accessing markets and customers or to accessing local science and technology. This study proposes that based on governance form distinct factor derived benefits can be capitalized. To corroborate or refute factors and their relations on R&D globalization governance forms, an empirical study based on expert interviews of pharmaceutical directors was conducted in the People's Republic of China. The market was found to be the major influencing factor. Local requirements and adaptation were corroborated as factors connected with markets. Furthermore, influencing factors, such as labour, centers of excellence, cost, financial incentives were corroborated together with conditional and risk factors. Furthermore this research argues that the globalization of pharmaceutical R&D is dependent on the financial, scientific and operational requirements of the drug discovery stage. And thus establishes the influence of drug discovery's stages continuum on pharmaceutical R&D globalization. Finally, a R&D globalization governance form decision framework is proposed based on the frameworks presented in literature and author's corroborated empirical findings.

High-Throughput Screening for Novel Prostate Cancer Drug Targets –Getting Personal

Prostate cancers form a heterogeneous group of diseases and there is a need for novel biomarkers, and for more efficient and targeted methods of treatment. In this thesis, the potential of microarray data, RNA interference (RNAi) and compound screens were utilized in order to identify novel biomarkers, drug targets and drugs for future personalized prostate cancer therapeutics. First, a bioinformatic mRNA expression analysis covering 9873 human tissue and cell samples, including 349 prostate cancer and 147 normal prostate samples, was used to distinguish in silico prevalidated putative prostate cancer biomarkers and drug targets. Second, RNAi based high-throughput (HT) functional profiling of 295 prostate and prostate cancer tissue specific genes was performed in cultured prostate cancer cells. Third, a HT compound screen approach using a library of 4910 drugs and drug-like molecules was exploited to identify potential drugs inhibiting prostate cancer cell growth. Nine candidate drug targets, with biomarker potential, and one cancer selective compound were validated in vitro and in vivo. In addition to androgen receptor (AR) signaling, endoplasmic reticulum (ER) function, arachidonic acid (AA) pathway, redox homeostasis and mitosis were identified as vital processes in prostate cancer cells. ERG oncogene positive cancer cells exhibited sensitivity to induction of oxidative and ER stress, whereas advanced and castrate-resistant prostate cancer (CRPC) could be potentially targeted through AR signaling and mitosis. In conclusion, this thesis illustrates the power of systems biological data analysis in the discovery of potential vulnerabilities present in prostate cancer cells, as well as novel options for personalized cancer management.

The spindle assembly checkpoint as a drug target - Novel small-molecule inhibitors of Aurora kinases

Cell division (mitosis) is a fundamental process in the life cycle of a cell. Equal distribution of chromosomes between the daughter cells is essential for the viability and well-being of an organism: loss of fidelity of cell division is a contributing factor in human cancer and also gives rise to miscarriages and genetic birth defects. For maintaining the proper chromosome number, a cell must carefully monitor cell division in order to detect and correct mistakes before they are translated into chromosomal imbalance. For this purpose an evolutionarily conserved mechanism termed the spindle assembly checkpoint (SAC) has evolved. The SAC comprises a complex network of proteins that relay and amplify mitosis-regulating signals created by assemblages called kinetochores (KTs). Importantly, minor defects in SAC signaling can cause loss or gain of individual chromosomes (aneuploidy) which promotes tumorigenesis while complete failure of SAC results in cell death. The latter event has raised interest in discovery of low molecular weight (LMW) compounds targeting the SAC that could be developed into new anti-cancer therapeutics. In this study, we performed a cell-based, phenotypic high-throughput screen (HTS) to identify novel LMW compounds that inhibit SAC function and result in loss of cancer cell viability. Altogether, we screened 65 000 compounds and identified eight that forced the cells prematurely out of mitosis. The flavonoids fisetin and eupatorin, as well as the synthetic compounds termed SACi2 and SACi4, were characterized in more detail utilizing versatile cell-based and biochemical assays. To identify the molecular targets of these SAC-suppressing compounds, we investigated the conditions in which SAC activity became abrogated. Eupatorin, SACi2 and SACi4 preferentially abolished the tensionsensitive arm of the SAC, whereas fisetin lowered also the SAC activity evoked by lack of attachments between microtubules (MTs) and KTs. Consistent with the abrogation of SAC in response to low tension, our data indicate that all four compounds inhibited the activity of Aurora B kinase. This essential mitotic protein is required for correction of erratic MT-KT attachments, normal SAC signaling and execution of cytokinesis. Furthermore, eupatorin, SACi2 and SACi4 also inhibited Aurora A kinase that controls the centrosome maturation and separation and formation of the mitotic spindle apparatus. In line with the established profound mitotic roles of Aurora kinases, these small compounds perturbed SAC function, caused spindle abnormalities, such as multi- and monopolarity and fragmentation of centrosomes, and resulted in polyploidy due to defects in cytokinesis. Moreover, the compounds dramatically reduced viability of cancer cells. Taken together, using a cell-based HTS we were able to identify new LMW compounds targeting the SAC. We demonstrated for the first time a novel function for flavonoids as cellular inhibitors of Aurora kinases. Collectively, our data support the concept that loss of mitotic fidelity due to a non-functional SAC can reduce the viability of cancer cells, a phenomenon that may possess therapeutic value and fuel development of new anti-cancer drugs.