<p>Adult prostate stem cells (PSC) are a rare epithelial progenitor population in the prostate. While essential for normal homeostasis, they have also been implicated in hyperplasia and cancer initiation. While studies have shown that inflammatory growth factors and cytokines can fuel stem cell expansion, the impact of inflammation on PSC is not well understood. To study the impact of inflammation on the prostate, the Ratliff laboratory developed the Prostate Ovalbumin Expressing Transgenic 3 (POET3), an inducible mouse model of abacterial T cell mediated prostate inflammation, which functions as a model for human autoimmune prostatitis. Previous studies using the POET3 demonstrated that inflammation increased proliferation and differentiation of PSC enrichments. Based on these findings, it was speculated that inflammation impacts prostate stem cells to enhance mechanisms of survival, possibly as a means of tissue protection.</p><p>Since androgen receptor (AR) signaling is the major driver of cellular differentiation and survival in the prostate, it was further hypothesized that inflammation promotes AR signaling in the PSC. To address this hypothesis, PSC and their resulting organoids from inflamed and non-inflamed (naïve) POET3 mice as well as human patient samples were assessed for AR and its signaling components.</p><p>These data were expanded by single cell mRNA sequencing using Fluidigm’s C1 platform, which revealed changes in stem cell populations, differential expression of interleukin 1 alpha (IL-1⍺) and its signaling components, and upregulation of various genes associated with immune regulation. Thus, experiments described herein probed the impacts of inflammation on AR, IL-1⍺, and T cell regulatory abilities in the PSC.</p>The results of these studies indicate that indeed, inflammation increases PSC survival. Inhibition of IL-1⍺ via inflammation-mediated up-regulation of IL-1 receptor antagonist (IL-1RA) promotes AR signaling, resulting in proliferation, differentiation, and AR target gene expression which can be modulated by Enzalutamide (a clinical AR inhibitor). Furthermore, PSC from inflamed mice are able to suppress cytotoxic T cell function in <i>ex vivo</i> assays. These studies set the foundation for new ways to treat proliferative diseases of the prostate by targeting IL-1⍺, AR, and immune regulation in the PSC.

Denna rapport syftar till att implementera en metod för att simulera cancerceller och skapa en ökad förståelse för hur Warburgeffekten, vilket är cancercellers användning av anaerob metabolism under aeroba förhållanden, påverkar cancerceller. Detta undersöks genom att simulera i en dator hur syrehalten påverkar andelen anaeroba cancerceller i en tumör och dess spridning. I studien undersöks fem olika syrenivåer. Simuleringen görs med en Cellular Automaton-modell och startar med ett mindre antal cancerceller i mitten av ett 200x200-rutnät, omgivna av friska celler. Cancercellerna och deras beslutsmekanismer modelleras med artificiella neurala nätverk och friska celler med fastställda regler. Cancercellerna kan vid delning muteras och ge upphov till nya beteenden som sedan blir en del av selektionsprocessen. Simuleringarna visar att cancercellerna, oberoende av syrehalten, sprider sig på ett likartat vis. Genom att vissa av cancercellerna övergår från aerob till anaerob metabolism så försurar cancertumören sin omgivning, vilket dödar friska celler. Syrehaltens påverkan på andelen anaeroba celler hos tumören visar sig ha betydelse, men det är främst hos den lägsta syrehalten en markant ökning av andelen anaeroba celler noteras. Noterbart är även att andelen anaeroba celler i den här studien, för alla syrehalter, är avsevärt lägre än de 60 % som påvisats i vissa studier av Warburgeffekten gjorda på levande celler.

Devant le grand nombre de tumeurs du sein triple négatif résistant aux traitements, il est essentiel de comprendre les mécanismes de résistance et de trouver de nouvelles molécules efficaces. En premier lieu, nous analysons deux ensembles de données pharmacogénomiques à grande échelle. Nous proposons une nouvelle classification basée sur des profils transcriptomiques de lignées cellulaires, selon un processus de sélection de gènes basé sur des réseaux biologiques. Notre classification moléculaire montre une plus grande homogénéité dans la réponse aux médicaments que lorsque l’on regroupe les lignées cellulaires en fonction de leur tissu d'origine. Elle permet également d’identifier des profils similaires de réponse aux traitements. Dans un second travail, nous étudions une cohorte de patients atteints d’un cancer du sein triple négatif ayant résisté à la chimiothérapie néoadjuvante. Nous effectuons des analyses moléculaires complètes basées sur du RNAseq et WES. Nous constatons une forte hétérogénéité moléculaire des tumeurs avant et après traitement. Bien que nous observons une évolution clonale sous traitement, aucun mécanisme récurrent de résistance n’a pu être identifié. Nos résultats suggèrent fortement que chaque tumeur a un profil moléculaire unique et qu'il est important d'étudier de grandes séries de tumeurs. Enfin, nous améliorons une méthode pour tester la surreprésentation de motifs connus de protéines de liaison à l'ARN, dans un ensemble donné de séquences régulées. Cet outil utilise une approche innovante pour contrôler la proportion de faux positifs qui n'est pas réalisé par l'algorithme existant. Nous montrons l'efficacité de notre approche en utilisant deux séries de données différentes. / Given the large number of treatment-resistant triple-negative breast cancers, it is essential to understand the mechanisms of resistance and to find new effective molecules. First, we analyze two large-scale pharmacogenomic datasets. We propose a novel classification based on transcriptomic profiles of cell lines, according to a biological network-driven gene selection process. Our molecular classification shows greater homogeneity in drug response than when cell lines are grouped according to their original tissue. It also helps identify similar patterns of treatment response. In a second analysis, we study a cohort of patients with triple-negative breast cancer who have resisted to neoadjuvant chemotherapy. We perform complete molecular analyzes based on RNAseq and WES. We observe a high molecular heterogeneity of tumors before and after treatment. Although we highlighted clonal evolution under treatment, no recurrent mechanism of resistance could be identified Our results strongly suggest that each tumor has a unique molecular profile and that that it is increasingly important to have large series of tumors. Finally, we are improving a method for testing the overrepresentation of known RNA binding protein motifs in a given set of regulated sequences. This tool uses an innovative approach to control the proportion of false positives that is not realized by the existing algorithm. We show the effectiveness of our approach using two different datasets.

Die Analyse von NGS Daten ist ein zentraler Aspekt der modernen genomischen Forschung. Bei der Extraktion von Daten aus den beiden am häufigsten verwendeten Quellorganismen bestehen jedoch vielfältige Problemstellungen. Im ersten Kapitel wird ein neuartiger Ansatz vorgestellt welcher einen Abstand zwischen Krebszellinienkulturen auf Grundlage ihrer kleinen genomischen Varianten bestimmt um die Kulturen zu identifizieren. Eine Voll-Exom sequenzierte Kultur wird durch paarweise Vergleiche zu Referenzdatensätzen identifiziert so ein gemessener Abstand geringer ist als dies bei nicht verwandten Kulturen zu erwarten wäre. Die Wirksamkeit der Methode wurde verifiziert, jedoch verbleiben Einschränkung da nur das Sequenzierformat des Voll-Exoms unterstützt wird. Daher wird im zweiten Kapitel eine publizierte Modifikation des Ansatzes vorgestellt welcher die Unterstützung der weitläufig genutzten Bulk RNA sowie der Panel-Sequenzierung ermöglicht. Die Ausweitung der Technologiebasis führt jedoch zu einer Verstärkung von Störeffekten welche zu Verletzungen der mathematischen Konditionen einer Abstandsmetrik führen. Daher werden die entstandenen Verletzungen durch statistische Verfahren zuerst quantifiziert und danach durch dynamische Schwellwertanpassungen erfolgreich kompensiert. Das dritte Kapitel stellt eine neuartige Daten-Aufwertungsmethode (Data-Augmentation) vor welche das Trainieren von maschinellen Lernmodellen in Abwesenheit von neoplastischen Trainingsdaten ermöglicht. Ein abstraktes Abstandsmaß wird zwischen neoplastischen Entitäten sowie Entitäten gesundem Ursprungs mittels einer transkriptomischen Dekonvolution hergestellt. Die Ausgabe der Dekonvolution erlaubt dann das effektive Vorhersagen von klinischen Eigenschaften von seltenen jedoch biologisch vielfältigen Krebsarten wobei die prädiktive Kraft des Verfahrens der des etablierten Goldstandard ebenbürtig ist. / The analysis of NGS data is a central aspect of modern Molecular Genetics and Oncology. The first scientific contribution is the development of a method which identifies Whole-exome-sequenced CCL via the quantification of a distance between their sets of small genomic variants. A distinguishing aspect of the method is that it was designed for the computer-based identification of NGS-sequenced CCL. An identification of an unknown CCL occurs when its abstract distance to a known CCL is smaller than is expected due to chance. The method performed favorably during benchmarks but only supported the Whole-exome-sequencing technology. The second contribution therefore extended the identification method by additionally supporting the Bulk mRNA-sequencing technology and Panel-sequencing format. However, the technological extension incurred predictive biases which detrimentally affected the quantification of abstract distances. Hence, statistical methods were introduced to quantify and compensate for confounding factors. The method revealed a heterogeneity-robust benchmark performance at the trade-off of a slightly reduced sensitivity compared to the Whole-exome-sequencing method. The third contribution is a method which trains Machine-Learning models for rare and diverse cancer types. Machine-Learning models are subsequently trained on these distances to predict clinically relevant characteristics. The performance of such-trained models was comparable to that of models trained on both the substituted neoplastic data and the gold-standard biomarker Ki-67. No proliferation rate-indicative features were utilized to predict clinical characteristics which is why the method can complement the proliferation rate-oriented pathological assessment of biopsies. The thesis revealed that the quantification of an abstract distance can address sources of erroneous NGS data analysis.

Die Dissertationsarbeit untersucht genetische Varianten in Zellkulturmodellen des metastatischen und kastrationsresistenten Prostatakarzinoms. Außerdem werden Mechanismen der Chemoresistenz, insbesondere der Resistenz gegen Cisplatin und Docetaxel in diesen Zelllinien untersucht. / This Dissertation evaluates genetic variants found in cell culture models of metastatic castration resistant prostate cancer. Furthermore, mechanisms of resistance against the chemotherapeutic drugs cisplatin and docetaxel are investigated in these cell lines.

<p>  </p> <p>Metastases are responsible for approximately 90% of all cancer-related deaths, with metastatic breast cancer (BC) holding a 5-year survival rate of only 27%. Recent research has highlighted a complex dynamic between cancer cells and the tumor microenvironment as essential for the formation of macrometastases. Within this field, tissue stiffening through matrix accumulation and altered matrix organization at the primary tumor site were recently linked with sustained proliferation and increased migration of tumor cells. Separately, elevated levels of the glycoprotein, fibronectin, were correlated to poor patient survival in BC and were linked to enhanced seeding of disseminated tumor cells at metastatic sites. Through my doctoral work, we have identified several mechanisms through which accumulated fibronectin impacts the metastatic potential of BC cells. First, we identified a transient increase in extracellular fibronectin in the lungs, which peaked before overt metastasis, coupled with a non-transient increase in total lung volume. To better recapitulate physiological conditions, we then developed a novel magnetically-actuated platform with the ability to apply tensile strain on cells at various amplitudes and frequencies in a high-throughput multi-well culture plate using suspended fibrillar fibronectin for 3D cell culture that is not reliant on a synthetic substrate. Using this as a biomimetic lung model, we found that cyclic mechanical force acted as a suppressor of cancer cell growth in a biomimetic lung model, implicating the accumulation and reorganization of extracellular matrix as an attempt by the cancer cells to alter the mechanical properties of the lung tissue and resist entering dormancy. However, our results showed that BC cells could not organize extracellular fibronectin independently. Instead, BC cells altered the accumulation and architecture of fibronectin by conditioning fibroblasts through soluble factors and extracellular vesicles. We observed that the fibronectin produced by conditioned fibroblasts varied as an effect of both the method of conditioning and the phenotype of the BC cell as the conditioning source. Taken together, these results have increased our knowledge of the relationship between disseminated breast cancer cells, fibroblasts, and fibronectin architecture in the early metastatic lung niche that paves the way for further investigation on targeting disseminated BC cells during early disease intervention in order to inhibit later overt metastatic outgrowth.</p>

No description available.

No description available.

<p>Polycomb repressive complex 1 (PRC1) is critical for mediating gene expression during development. Five chromobox (CBX) homolog proteins, CBX2,4,6,7,8, are incorporated into PRC1 complexes, where they mediate targeting to trimethylated lysine 27 of histone H3 (H3K27me3) via the N-terminal chromodomain (ChD). Individual CBX paralogs have been implicated as drug targets in cancer; however, high similarity in sequence and structure among the CBX ChDs provide a major obstacle in developing selective CBX ChD inhibitors. Here a selection of small, focused, DNA-encoded libraries (DELs) against multiple homologous ChDs was reported to identify modifications to a parental ligand that confer both selectivity and potency for the ChD of CBX8. This on-DNA, medicinal chemistry approach enabled the development of SW2_110A, a selective, cell-permeable inhibitor of the CBX8 ChD. SW2_110A binds CBX8 ChD with a Kd of 800 nM, with minimal 5-fold selectivity for CBX8 ChD over all other CBX paralogs in vitro. SW2_110A specifically inhibits the association of CBX8 with chromatin in cells and inhibits the proliferation of THP1 leukemia cells driven by the MLL-AF9 translocation. In THP1 cells, SW2_110A treatment significantly decreases expression of MLL-AF9 target genes, including HOXA9, validating the previously established role for CBX8 in MLL-AF9 transcriptional activation, and defining the ChD as necessary for this function. The success of SW2_110A provides great promise for the development of highly selective and cell permeable probes for the full CBX family. In addition, the approach taken provides a proof-of-principle demonstration of how DELs can be used iteratively for optimization of both ligand potency and selectivity.</p> <p>CBX2 is upregulated in a variety of cancers, particularly in advanced prostate cancers. Using CBX2 inhibitors to understand and target CBX2 in prostate cancer is highly desirable. Here, selections of focused DNA encoded libraries (DELs) were performed for the discovery of a selective CBX2 chromodomain probe, SW2_152F. SW2_152F binds to CBX2 ChD with a Kd of 80 nM and displays 24-1000-fold selectivity for CBX2 ChD over other CBX paralogs <em>in vitro</em>. SW2_152F is cell permeable, selectively inhibits CBX2 chromatin binding in cells, and blocks neuroendocrine differentiation of prostate cancer cell lines in response to androgen deprivation.</p> <p>Targeted covalent inhibitors (TCIs) are rationally designed inhibitors that bind to a target protein and specifically label a non-conserved amino acid on proteins by means of reactive moieties (warheads). TCIs typically function by two steps, in which inhibitors first non-covalently bind to the target protein and then covalent bond formation occurs between the inhibitor- warhead and a proximal nucleophile on protein. Covalent inhibitors or drugs have prolonged target engagement and enhanced pharmacokinetic potency in vivo, compared to non-covalent molecules. Strategies to develop effective warheads of TCIs have been reported for labeling different nucleophilic amino acid residues, of which cysteine and lysine are the most established for covalent labeling. Tyrosine is recently becoming an attractive nucleophile for TCIs as an alternative choice, yet currently developed warheads that label tyrosine do so with modest specificity over other side chains. Here, I report the development of novel Mannich electrophiles and use those electrophiles as covalent warheads on an inhibitor to specifically target tyrosine in protein labeling. To my knowledge, this is first demonstration of the use of Mannich electrophiles in covalent inhibitors. Specifically, I leveraged a previously developed CBX8 chromodomain inhibitor to specifically label a non-conserved tyrosine within CBX8 using cyclic imine derivatives as warheads. This ligand-directed, specific tyrosine conjugation on CBX8 but not on CBX2, significantly improves both the potency and selectivity of inhibition. Biochemical, proteomic, and cellular validation further showed the cyclic imine covalent inhibitors can increase both potency and selectivity to the target protein CBX8 in cells, serving as a robust chemical probe for target function evaluation and modulation. This new type of tyrosine labeling warhead is a useful addition to the toolbox of medicinal chemists for covalent inhibitor development.</p> <p>The following chapters are modified from following publications, with permissions from Sijie Wang, Emily C.Dykhuizen, and Casey J. Krusemark. </p> <p>Wang, S., Denton, K. E., Hobbs, K. F., Weaver, T., McFarlane, J. M., Connelly, K. E., Gignac, M.C., Milosevich, N., Hof, F., Paci, I., Musselman, C. A., Dykhuizen, E.C., Krusemark, C. J. Optimization of Ligands Using Focused DNA-Encoded Libraries To Develop a Selective, Cell-Permeable CBX8 Chromodomain Inhibitor. <em>ACS Chem Biol. </em>2020, 15, 112-131</p> <p>Wang, S., Alpsoy, A., Sood, S., Ordonez-Rubiano, S. C., Dhiman, A., Sun, Y., Krusemark, C. J., Dykhuizen, E. C. A Potent, Selective CBX2 Chromodomain Ligand and its Cellular Activity During Prostate Cancer Neuroendocrine Differentiation. <em>ChemBioChem.</em> 2021, 22, 2335-2344</p> <p>Wang, S., Ordonez-Rubiano, S. C., Dhiman, A., Jiao G., Strohmier B. P., Krusemark, C. J., Dykhuizen, E. C. Polycomb Group proteins in cancer: multifaceted functions and strategies for modulation Modulators. <em>NAR Cancer</em>. 2021, 3, zcab039</p>

<p>  </p> <p>Epstein-Barr virus (EBV) is a complex oncogenic symbiont. The molecular mechanisms governing EBV carcinogenesis remain elusive and the functional interactions between virus and host cells are incompletely defined. Some of the known mechanisms include viral integration into the host genome, expression and mutation(s) of viral genes and the host response to the virus. Despite decades of research there is a lack of effective treatment options for EBV-positive cancer patients underscoring an urgent need to further investigate the mechanisms underlying tumorigenesis as well as explore and develop personalized treatment strategies for patients with EBV-positive cancers. In Chapter 1, I introduce Epstein-Barr Virus (EBV), the two phases of EBV lifecycle and an overview of certain EBV-associated carcinomas. I will also discuss the underlying mechanisms and few current therapeutic strategies against EBV infection. Next, I will discuss some of the preclinical model systems and high-throughput computation techniques that are commonly used by researchers in the field of EBV.  </p> <p>In chapter 2, we have systematically analyzed RNA-sequencing from >1000 patients with 15 different cancer types, comparing virus and host factors of EBV+ to EBV- tissues to reveal novel insights into EBV-positive tumors. First, we observed that EBV preferentially integrates at highly accessible regions of the cancer genome with significant enrichment in super-enhancer architecture. Second, we determined that the expression of twelve EBV transcripts, including LMP1 and LMP2, correlated inversely with EBV reactivation signature. Over-expression of these genes significantly suppressed viral reactivation, consistent with a ‘Virostatic’ function. Third, we identified hundreds of novel frequent missense and nonsense variations in Virostatic genes in cancer samples, and that the variant genes failed to regulate their viral and cellular targets in cancer. Lastly, we were able to dichotomously classify EBV-positive tumors based on patterns of host interferon signature genes and immune checkpoint markers, such as PD-L1 and IDO1. </p> <p>In chapter 3, we probed the lifecycle of EBV on a cell-by-cell basis using single cell RNA sequencing (scRNA-seq) data from six EBV-immortalized lymphoblastoid cell lines (LCL). While the majority of LCLs comprised cells containing EBV in the latent phase of its life cycle, we identified two additional clusters that had distinct expression of both host and viral genes. Both clusters were high expressors of EBV Latent Membrane Protein-1 (LMP1) but differed in their expression of other EBV lytic genes, including glycoprotein gene GP350. We further probed into the transcriptional landscape of these clusters to identify potential regulators which will be discussed in further detail in the chapter. Importantly, I was able to demonstrate enhancing HIF1-a signaling by using Pevonedistat, a compound that stabilized HIF1-a can preferentially induce the transcriptional program specific to one of the three identified clusters. </p> <p>In Chapter 4, I describe some of my recent work. In this project, we have used an intuitive <em>in-silico </em>drug prediction approach to rapidly screen and identify FDA-approved or clinically available compounds that can be repurposed to induce lytic cycle in different EBV+ tumors. Using this strategy, we identified Ciclopirox, an antifungal drug, as a potent inducer of lytic cycle in EBV+ epithelial cancers. We used EBV+ GC cells to determine the effect of Ciclopirox on EBV reactivation as well as identify the underlying mechanisms. In summary, we discovered that reactivation of EBV lytic cycle by Ciclopirox is mediated by multiple pathways, two of the major ones being the HIF1-a and NF-kB pathways. Although, Ciclopirox treatment enhanced the killing effect of antiviral, further investigation is needed to effectively deliver this drug <em>in vivo.</em> Throughout this chapter, I have discussed findings that needs further investigation and proposed necessary experiments. Finally, in Chapter 5 I have summarized my work and described how our work can provide novel insights that can help delineate some of the complexities of host-pathogen interactions in EBV-associated malignancies. </p>