Establishment and characterisation of testicular cancer patient-derived xenograft models for preclinical evaluation of novel therapeutic strategies

Testicular cancer (TC) is the most common solid tumour in young men. While cisplatin-based chemotherapy is highly effective in TC patients, chemoresistance still accounts for 10% of disease-related deaths. Pre-clinical models that faithfully reflect patient tumours are needed to assist in target discovery and drug development. Tumour pieces from eight TC patients were subcutaneously implanted in NOD scid gamma (NSG) mice. Three patient-derived xenograft (PDX) models of TC, including one chemoresistant model, were established containing yolk sac tumour and teratoma components. PDX models and corresponding patient tumours were characterised by H&E, Ki-67 and cyclophilin A immunohistochemistry, showing retention of histological subtypes over several passages. Whole-exome sequencing, copy number variation analysis and RNA-sequencing was performed on these TP53 wild type PDX tumours to assess the effects of passaging, showing high concordance of molecular features between passages. Cisplatin sensitivity of PDX models corresponded with patients' response to cisplatin-based chemotherapy. MDM2 and mTORC1/2 targeted drugs showed efficacy in the cisplatin sensitive PDX models. In conclusion, we describe three PDX models faithfully reflecting chemosensitivity of TC patients. These models can be used for mechanistic studies and pre-clinical validation of novel therapeutic strategies in testicular cancer

Cystatin C is glucocorticoid responsive, directs recruitment of Trem2+ macrophages, and predicts failure of cancer immunotherapy

Cystatin C (CyC), a secreted cysteine protease inhibitor, has unclear biological functions. Many patients exhibit elevated plasma CyC levels, particularly during glucocorticoid (GC) treatment. This study links GCs with CyC’s systemic regulation by utilizing genome-wide association and structural equation modeling to determine CyC production genetics in the UK Biobank. Both CyC production and a polygenic score (PGS) capturing predisposition to CyC production were associated with increased all-cause and cancer-specific mortality. We found that the GC receptor directly targets CyC, leading to GC-responsive CyC secretion in macrophages and cancer cells. CyC-knockout tumors displayed significantly reduced growth and diminished recruitment of TREM2+ macrophages, which have been connected to cancer immunotherapy failure. Furthermore, the CyC-production PGS predicted checkpoint immunotherapy failure in 685 patients with metastatic cancer from combined clinical trial cohorts. In conclusion, CyC may act as a GC effector pathway via TREM2+ macrophage recruitment and may be a potential target for combination cancer immunotherapy.publishedVersio

Conduits of Intratumor Heterogeneity: Centrosome Amplification, Centrosome Clustering and Mitotic Frequency

Tumor initiation and progression is dependent on the acquisition and accumulation of multiple driver mutations that acti­vate and fuel oncogenic pathways and deactivate tumor suppressor networks. This complex continuum of non-stochastic genetic changes in accompaniment with error-prone mitoses largely explains why tumors are a mosaic of different cells. Contrary to the long-held notion that tumors are dominated by genetically-identical cells, tumors often contain many different subsets of cells that are remarkably diverse and distinct. The extent of this intratumor heterogeneity has bewildered cancer biologists’ and clinicians alike, as this partly illuminates why most cancer treatments fail. Unsurprisingly, there is no “wonder” drug yet available which can target all the different sub-populations including rare clones, and conquer the war on cancer. Breast tumors harbor ginormous extent of intratumoral heterogeneity, both within primary and metastatic lesions. This revelation essentially calls into question mega clinical endeavors such as the Human Genome Project that have sequenced a single biopsy from a large tumor mass thus precluding realization of the fact that a single tumor mass comprises of cells that present a variety of flavors in genotypic compositions. It is also becoming recognized that intratumor clonal heterogeneity underlies therapeutic resistance. Thus to comprehend the clinical behavior and therapeutic management of tumors, it is imperative to recognize and understand how intratumor heterogeneity arises. To this end, my research proposes to study two main features/cellular traits of tumors that can be quantitatively evaluated as “surrogates” to represent tumor heterogeneity at various stages of the disease: (a) centrosome amplification and clustering, and (b) mitotic frequency. This study aims at interrogating how a collaborative interplay of these “vehicles” support the tumor’s evolutionary agenda, and how we can glean prognostic and predictive information from an accurate determination of these cellular traits

Interrogating the Mechanistic Basis for Cytokine-Mediated Glucocorticoid Resistance in Lymphoid-Driven Diseases

Glucocorticoids (GCs) are potently immunosuppressive due to their pro-apoptotic effects on lymphoid cells, leading to their utility in a wide range of clinical contexts including autoimmune diseases, hyperinflammatory conditions, and lymphoid malignancies. In addition, GCs are endogenously produced hormones that mediate a wide range of physiologic functions that are essential for life. As a result, cells of the immune system face constant exposure to GCs and therefore require intrinsic mechanisms by which to resist their pro-apoptotic effects under certain developmental and environmental conditions. The retention of these resistance mechanisms in lymphoid-driven diseases thereby poses a challenge to the clinical use of GCs in these contexts. Common -chain cytokines, through activation of the JAK/STAT signal transduction pathway, play essential roles in the differentiation, survival, and function of lymphoid cells. Here, we assess the interplay between GC activity and cytokine-mediated pro-survival signaling in two lymphoid-driven diseases, acute lymphoblastic leukemia and hemophagocytic lymphohistiocytosis, and demonstrate that cytokines are potent mediators of GC resistance. Mechanistically, we show that activation of STAT5 downstream of cytokine receptor signaling is necessary for cytokine-induced GC resistance. STAT5 functions as a transcription factor to upregulate expression of anti-apoptotic mediators, thereby reducing the apoptotic potential and promoting the survival of lymphoid cells. Through both genetic and pharmacologic approaches, we demonstrate that targeted inhibition of cytokine receptor signaling effectively restores GC sensitivity, and we establish the feasibility of this therapeutic approach in two in vivo models of disease

Representation and decision making in the immune system

The immune system has long been attributed cognitive capacities such as "recognition" of pathogenic agents; "memory" of previous infections; "regulation" of a cavalry of detector and effector cells; and "adaptation" to a changing environment and evolving threats. Ostensibly, in preventing disease the immune system must be capable of discriminating states of pathology in the organism; identifying causal agents or ``pathogens''; and correctly deploying lethal effector mechanisms. What is more, these behaviours must be learnt insomuch as the paternal genes cannot encode the pathogenic environment of the child. Insights into the mechanisms underlying these phenomena are of interest, not only to immunologists, but to computer scientists pushing the envelope of machine autonomy. This thesis approaches these phenomena from the perspective that immunological processes are inherently inferential processes. By considering the immune system as a statistical decision maker, we attempt to build a bridge between the traditionally distinct fields of biological modelling and statistical modelling. Through a mixture of novel theoretical and empirical analysis we assert the efficacy of competitive exclusion as a general principle that benefits both. For the immunologist, the statistical modelling perspective allows us to better determine that which is phenomenologically sufficient from the mass of observational data, providing quantitative insight that may offer relief from existing dichotomies. For the computer scientist, the biological modelling perspective results in a theoretically transparent and empirically effective numerical method that is able to finesse the trade-off between myopic greediness and intractability in domains such as sparse approximation, continuous learning and boosting weak heuristics. Together, we offer this as a modern reformulation of the interface between computer science and immunology, established in the seminal work of Perelson and collaborators, over 20 years ago.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Developing a cell-based fluorescent assay for screening Dicer-activating compounds

MicroRNAs are ~22 nucleotide long RNA strands which regulate gene expression by binding to the 3’UTRs of messenger RNAs. MicroRNAs are predicted to regulate about a half of all protein-coding genes in the human genome thus affecting many cellular processes. One crucial part of microRNA biogenesis is the cleaving of pre-miRNA strands into mature microRNAs by the type III RNase enzyme, Dicer. Dicer has been shown to be downregulated due to aging and in many disease states. Particularly central nervous system disorders are linked to dysregulated microRNA processing. According to the latest studies, Dicer is crucial to the survival of dopaminergic neurons and conditional Dicer knockout mice show severe nigrostriatal dopaminergic cell loss, which is a hallmark of Parkinson’s disease. By activating Dicer with a small-molecule drug, enoxacin, the survival of dopaminergic cells exposed to stress is significantly improved. However, enoxacin, which is a fluoroquinolone antibiotic, activates Dicer only at high concentrations (10-100 μM) and is polypharmacological, which may cause detrimental side effects. Therefore, enoxacin is not a suitable drug candidate for Dicer deficiencies and better Dicer-activating drug candidates are needed. The aim of this work was to develop a cell-based fluorescent assay to screen for Dicer-activating compounds. Assays which measure Dicer activity have already been developed, but they have some pitfalls which don’t make them optimal to use for high-throughput screening of Dicer-activating compounds. Some are cell-free enzyme-based assays and thus neglect Dicer in its native context. The RNA to be processed by Dicer does not represent a common mammalian RNA type. Most assays do not have internal normalizing factors, such as a second reporter protein to account for e.g. cell death, or the analysis method is not feasible for high-throughput screening data. Considering these disadvantages, the study started by designing a reporter plasmid in silico. The plasmid expresses two fluorescent proteins, mCherry (red) and EGFP (green), and a mCherry transcripttargeting siRNA implemented into a pre-miR155 backbone which is processed by Dicer. Thus, measuring the ratios of red and green fluorescence intensities will give an indication on Dicer activity. The plasmid also has additional regulatory elements for stabilizing expression levels. The plasmid was then produced by molecular cloning methods and its functionality was tested with Dicer-modulating compounds. The assay was optimised by testing it in different cell lines and varying assay parameters, and stable cell lines were created to make large-scale screening more convenient. Finally, a small-scale screen was done with ten pharmacologically active compounds. Transiently transfected, in Chinese hamster ovarian cells, mCherry silencing was too efficient for reliable detection of improvement in silencing efficiency due to floor effect. With an inducible, Tet-On, system in FLP-IN 293 T-Rex cells, the expression could be controlled by administering doxycycline and the improvement in silencing was quantifiable. The assay seemed to be functional after 72 hours and 120 hours of incubation using enoxacin (100 μM) as a positive control. However, the screening found no compounds to significantly reduce mCherry/EGFP fluorescence ratio and, additionally, the effect of enoxacin was abolished. Therefore, a more thorough analysis on the effects of enoxacin was done and, although statistically significant, enoxacin was only marginally effective in reducing mCherry/EGFP fluorescence ratio after 72 hours of treatment. It should be noted from the small-scale screening that metformin and BDNF, compounds previously shown to elevate Dicer levels, showed similar effects to enoxacin. The quality of the assay in terms of high-throughput screening was determined by calculating Zfactors and coefficients of variations for the experiments, which showed that the variability of the assay was acceptable, but the differences between controls was not large enough for reliable screening. In conclusion, the effects of metformin and BDNF should be further studied and regarding the assay, more optimisation is needed for large-scale, high-throughput, screening to be done with minimal resources.MikroRNA:t ovat noin 22 nukleotidiä pitkiä RNA-juosteita, jotka estävät geenien ilmentymistä sitoutumalla lähetti-RNA:n 3’UTR-alueille. MikroRNA:t osallistuvat laajalti moneen soluprosessiin säätelemällä noin puolta kaikista proteiineja koodaavista geeneistä. MikroRNA:n ilmentymisessä, eräs tärkeä vaihe on III tyypin RNaasin, Dicerin, suorittama pre-miRNA:n prosessointi valmiiksi mikroRNA-juosteeksi. Dicerin toiminnan ja ilmentymisen on mitattu heikentyvän ikääntymisen johdosta, sekä useissa eri taudeissa. Erityisesti keskushermostotautien ja mikroRNA prosessointiin liittyvien ongelmien välillä on löydetty yhteys. Tuoreimpien tutkimusten mukaan Dicerilla on tärkeä rooli myös dopaminergisten hermosolujen selviytymisen kannalta ja lisäksi Dicer muuntogeenisillä hiirillä mustatumakkeen dopamiinihermosolut kuolevat, joka on Parkinsonin taudin keskeisin patofysiologinen ilmiö. Dicerin aktiivisuuden tehostamisella, käyttäen enoksasiinia, on suojaava vaikutus dopamiinihermosoluille. Enoksasiini, joka on fluorokinoloneihin kuuluva antimikrobinen yhdiste, tehostaa Diceria vain suurilla pitoisuuksilla (10-100 μM). Lisäksi se on polyfarmakologinen voiden aiheuttaa paljon vakavia haittavaikutuksia, joten se ei ole optimaalinen lääkeaine Dicer-puutoksiin liitettyjen tautien hoitamiseen. Tämän erikoistyön tavoitteena oli kehittää solupohjainen, fluoresenssiin perustuva menetelmä, jolla voisi seuloa parempia Diceria aktivoivia yhdisteitä. Dicerin aktiivisuutta mittaavia menetelmiä on jo kehitetty aiemmin muutamia, mutta ne eivät ole optimaalisia Diceria-aktivoivien yhdisteiden seulomiseksi. Osa kokeista on entsyymipohjaisia eivätkä ne ota huomioon solunsisäistä endogeenistä Diceria. Kokeissa käytettävä RNA, jonka Dicer prosessoi, ei edusta yleisiä nisäkässolujen RNA-tyyppejä. Tietyissä kokeissa ei ole sisäistä suhteuttavaa tekijää (esimerkiksi toista fluoresoivaa proteiinia) tai niillä ei ole mahdollista suorittaa laajoja seulontoja. Työssä suunniteltiin ensiksi edellä mainitut puutteet huomioon ottaen reportteriplasmidi in silico. Plasmidi ilmentää kahta fluoresoivaa proteiinia, mCherry:ä (punainen) ja EGFP:tä,(vihreä) sekä mCherry:n ilmentymistä estävää siRNA-juostetta pre-miR155:n runkoon liitettynä, jonka Dicer prosessoi. Näin ollen, mittaamalla punaisen ja vihreän fluoresenssi-intensiteettien suhdetta, voidaan tutkia Dicerin aktiivisuutta. Plasmidissa on myös useita säätelyelementtejä ilmentymisen tasaamiseksi. Plasmidi valmistettiin molekyylikloonausmenetelmin ja sen toiminnollisuutta testattiin Dicerin aktiivisuuteen vaikuttavilla yhdisteillä. Seulontakoetta optimoitiin eri solulinjoilla ja olosuhdemuutoksilla, ja lisäksi valmistettiin stabiileja solulinjoja laajamittaisen seulonnan helpottamiseksi. Lopuksi suoritettiin pienen mittakaavan seulonta kymmenelle farmakologisesti aktiiviselle yhdisteelle. Ohimenevästi transfektoituna, Kiinanhamsterin munasarjasoluissa, mCherryn hiljentäminen oli niin tehokasta, että hiljentämisen tehostamista ei voitu luotettavasti mitata. Hallitsemalla ilmentymistä doksisykliinin avulla, Tet-On-systeemillä FLP-IN 293 T-Rex soluilla, saatiin ilmentymistä kontrolloitua ja mittaukset luotettaviksi. Seulontakoe saatiin toimimaan 72 tunnin ja 120 tunnin aikapisteillä käyttäen enoksasiinia positiivisena kontrollina. Seulonnasta ei löydetty mCherry/EGFP fluoresenssien suhdetta merkitsevästi vähentäviä yhdisteitä ja lisäksi enoksasiinin vaikutus ei ollut enää tilastollisesti merkitsevä. Tämän perusteella suoritettiin laajempi analyysi enoksasiinin vaikutuksista, missä havaittiin, että sen vaikutus mCherry/EGFP fluoresenssien suhteen vähentämisessä oli, vaikkakin tilastollisesti merkitsevä, hyvin vähäinen 72 tunnin kokeessa. Huomioitavaa pienen mittakaavan seulonnasta on, että metformiinin ja BDNF:n, joiden on aiemmin osoitettu lisäävän Dicerin ilmentymistä, vaikutukset olivat vastaavia enoksasiinin vaikutukseen. Seulontakokeen laatu laajamittaisen seulontakokeen suhteen määritettiin laskemalla kokeille Z-tekijän sekä hajonnan koeffisienttien arvot. Nämä osoittivat, että kokeen hajonta oli hyväksyttävä, mutta ero kontrollien välillä oli liian pieni, jotta koetta voisi käyttää luotettavasti seulomiseen. Tärkeimpinä johtopäätöksinä, metformiinin ja BDNF:n vaikutuksia Diceriin tulisi tutkia tarkemmin, ja koetta on optimoitava lisää, jotta laajamittaisia seulontoja voidaan suorittaa mahdollisimman vähillä resursseilla

LRH-1/NR5A2 interacts with the glucocorticoid receptor to regulate glucocorticoid resistance

Nuclear receptors are transcription factors with important functions in a variety of physiological and pathological processes. Targeting glucocorticoid receptor (GR) activity using glucocorticoids is a cornerstone in the treatment of patients with T cell acute lymphoblastic leukemia (T-ALL), and resistance to GC-induced cell death is associated with poor outcome and a high risk for relapse. Next to ligand-binding, heterodimerization with other transcription factors presents an important mechanism for the regulation of GR activity. Here, we describe a GC-induced direct association of the Liver Receptor Homolog-1 (LRH-1) with the GR in the nucleus, which results in reciprocal inhibition of transcriptional activity. Pharmacological and molecular interference with LRH-1 impairs proliferation and survival in T-ALL and causes a profound sensitization to GC-induced cell death, even in GC-resistant T-ALL. Our data illustrate that direct interaction between GR and LRH-1 critically regulates glucocorticoid sensitivity in T-ALL opening up new perspectives for developing innovative therapeutic approaches to treat GC-resistant T-ALL

Molecular dissection of colorectal cancer in pre-clinical models identifies biomarkers predicting sensitivity to EGFR inhibitors

Colorectal carcinoma represents a heterogeneous entity, with only a fraction of the tumours responding to available therapies, requiring a better molecular understanding of the disease in precision oncology. To address this challenge, the OncoTrack consortium recruited 106 CRC patients (stages I–IV) and developed a pre-clinical platform generating a compendium of drug sensitivity data totalling >4,000 assays testing 16 clinical drugs on patient-derived in vivo and in vitro models. This large biobank of 106 tumours, 35 organoids and 59 xenografts, with extensive omics data comparing donor tumours and derived models provides a resource for advancing our understanding of CRC. Models recapitulate many of the genetic and transcriptomic features of the donors, but defined less complex molecular sub-groups because of the loss of human stroma. Linking molecular profiles with drug sensitivity patterns identifies novel biomarkers, including a signature outperforming RAS/RAF mutations in predicting sensitivity to the EGFR inhibitor cetuximab

Computational Methods for the Analysis of Genomic Data and Biological Processes

In recent decades, new technologies have made remarkable progress in helping to understand biological systems. Rapid advances in genomic profiling techniques such as microarrays or high-performance sequencing have brought new opportunities and challenges in the fields of computational biology and bioinformatics. Such genetic sequencing techniques allow large amounts of data to be produced, whose analysis and cross-integration could provide a complete view of organisms. As a result, it is necessary to develop new techniques and algorithms that carry out an analysis of these data with reliability and efficiency. This Special Issue collected the latest advances in the field of computational methods for the analysis of gene expression data, and, in particular, the modeling of biological processes. Here we present eleven works selected to be published in this Special Issue due to their interest, quality, and originality

Mechanistic Insight and Translational Possibilities of Obesity-Breast Cancer Connection

Obesity is an independent risk factor for more than thirteen cancer types. In breast cancer context, obesity is strongly associated with higher incidence and poorer prognosis in postmenopausal patients. The management of breast cancer in obese patients is faced with numerous challenges, as dosing, toxicity and drug efficacy. Thus, it is highly demanded to investigate the in-depth mechanisms underlying the obesity-cancer connection and translate these fundamental mechanisms into clinical applications. To this end, we first searched for breast cancer phenotypes driven by the obese environment. In both patients and preclinical models, we identified enhanced stem-like traits in cancer cells exposed to the obese settings and it independently predicted breast cancer risks. Next, as obesity-induced elevated free fatty acid is a central phenotype in obese individuals, we established in vitro cancer cell models by long-term exposure to palmitic acid. Under this condition, cancer cells consistently dedifferentiated towards a cancer stem-like phenotype and displayed enhanced tumor initiation capacity. Mechanistically, we found that the obesity-induced phenotype was governed epigenetically through remodeling the chromatin landscape in cancer cells, specifically through increased chromatin occupancy of the transcription factor CCAAT/enhancer-binding protein beta (C/EBPB). We further identified Lipocalin 2 and Claudin 1 as the key downstream target genes of C/EBPB and functionally demonstrated the critical roles of C/EBPB and its targets in obesity-induced breast cancer initiation phenotypes. The second part of this thesis focuses on the investigation of endotrophin-induced physiological responses in human cells and the clinical translational potential. The cleavage product of collagen VI alpha 3 chain, endotrophin, is upregulated in obese states and has been previously reported as a stimulator for oncogenic transformation of mammary ductal epithelial cells in rodents. In addition, endotrophin presents pro-fibrotic, chemoattractant, pro-angiogenic and epithelial to mesenchymal transition induction properties in murine cells. Here, we demonstrated that the circulating levels of endotrophin is increased in breast cancer patients compared with healthy individuals. Recombinant human endotrophin exerted similar effects on human cell lines as in murine cells, suggesting that endotrophin is a viable target for breast cancer therapy. As such, we developed neutralizing antibodies targeting human endotrophin, and ultimately validated the effectiveness of such antibody in human breast cancer cell lines and human cell line-derived nude mouse models. In both in vitro and in vivo models, the antibody showed potent tumor growth inhibition and anti-cisplatin resistance functions, and thus provided the important stage towards developing targeted therapies for obese breast cancer patients.Doktorgradsavhandlin