Regulation of lymphocyte response in vitro and in vivo

CD4+ T helper (Th) cells have an important role in the defence against diverse pathogens. Th cells can differentiate into several functionally distinct subtypes including Th1 and Th2 cells. Th1 cells are important for eradicating intracellular pathogens, whereas Th2 cells pro¬tect our body against extracellular parasites. However if uncontrolled, Th cells can mediate immunopathology such as asthma or allergies, but inappropriate Th response can also lead to autoimmune diseases such as multiple sclerosis or type 1 diabetes. Deeper knowledge of the regulation of the lymphocyte response both in vitro and in vivo is important for un¬derstanding the pathogenesis of immune-mediated diseases and microbe-host interactions. In the work presented in this thesis, the first goal was to elucidate the role of novel factors, PIM kinases and c-FLIP in the regulation of human Th cell differentiation. The oncogenic serine-threonine kinases of the PIM family were shown to be preferentially expressed in Th1 cells and in addition, by using RNA interference, they were also shown to be positive regulators of Th1 differentiation. The PIM depletion experiments suggest that PIM kinases promote the expression of the hallmark cytokine of Th1 cells, IFNγ, and influence the IL12/STAT4 pathway during the early Th1 cell differentiation. In addition to cytokine and T cell receptor (TCR) induced pathways, caspase activity has been shown to regulate Th cell proliferation. In the work presented in this thesis, the two isoforms of the caspase regulator protein, c-FLIP, were shown to be differentially ex¬pressed in Th1 and Th2 cells. Both of the isoforms were up-regulated in response to TCR activation, but the expression of the short isoform was selectively induced by IL4, the Th2 inducing cytokine. Furthermore, the c-FLIP isoforms had distinct and opposite roles during the early differentiation of Th1 and Th2 cells. The knockdown of the long isoform of c-FLIP led to the induction of Th1 marker genes, such as IFNγ and TBET, whereas the depletion of c-FLIP short down-regulated Th2 marker genes IL-4 and GATA3. The third goal was to elucidate the gene expression profiles characterizing the T- and B-lymphocyte responses in vivo during experimental infection by intracellular bacte¬rium Chlamydia pneumoniae. Previously, it has been shown that CD8+ and CD4+ T cells are important for the protection against Chlamydia pneumoniae. In this study, the analysis revealed up-regulation of interferon induced genes during recurrent infection underlining the importance of IFNγ secreted by Th1 and CD8+ T cells in the protection against this pathogen. Taken together, in this study novel regulators of Th cell differ¬entiation were discovered and in addition the gene expression profiles of lymphocytes induced by Chlamydia pneumoniae infection were characterized.

Biomedical Event Extraction with Machine Learning

Biomedical natural language processing (BioNLP) is a subfield of natural language processing, an area of computational linguistics concerned with developing programs that work with natural language: written texts and speech. Biomedical relation extraction concerns the detection of semantic relations such as protein-protein interactions (PPI) from scientific texts. The aim is to enhance information retrieval by detecting relations between concepts, not just individual concepts as with a keyword search. In recent years, events have been proposed as a more detailed alternative for simple pairwise PPI relations. Events provide a systematic, structural representation for annotating the content of natural language texts. Events are characterized by annotated trigger words, directed and typed arguments and the ability to nest other events. For example, the sentence “Protein A causes protein B to bind protein C” can be annotated with the nested event structure CAUSE(A, BIND(B, C)). Converted to such formal representations, the information of natural language texts can be used by computational applications. Biomedical event annotations were introduced by the BioInfer and GENIA corpora, and event extraction was popularized by the BioNLP'09 Shared Task on Event Extraction. In this thesis we present a method for automated event extraction, implemented as the Turku Event Extraction System (TEES). A unified graph format is defined for representing event annotations and the problem of extracting complex event structures is decomposed into a number of independent classification tasks. These classification tasks are solved using SVM and RLS classifiers, utilizing rich feature representations built from full dependency parsing. Building on earlier work on pairwise relation extraction and using a generalized graph representation, the resulting TEES system is capable of detecting binary relations as well as complex event structures. We show that this event extraction system has good performance, reaching the first place in the BioNLP'09 Shared Task on Event Extraction. Subsequently, TEES has achieved several first ranks in the BioNLP'11 and BioNLP'13 Shared Tasks, as well as shown competitive performance in the binary relation Drug-Drug Interaction Extraction 2011 and 2013 shared tasks. The Turku Event Extraction System is published as a freely available open-source project, documenting the research in detail as well as making the method available for practical applications. In particular, in this thesis we describe the application of the event extraction method to PubMed-scale text mining, showing how the developed approach not only shows good performance, but is generalizable and applicable to large-scale real-world text mining projects. Finally, we discuss related literature, summarize the contributions of the work and present some thoughts on future directions for biomedical event extraction. This thesis includes and builds on six original research publications. The first of these introduces the analysis of dependency parses that leads to development of TEES. The entries in the three BioNLP Shared Tasks, as well as in the DDIExtraction 2011 task are covered in four publications, and the sixth one demonstrates the application of the system to PubMed-scale text mining.

Role and Function of c-Jun Protein Complex in Cancer Cell Behavior

Transcription factors play a crucial role in the regulation of cell behavior by modulating gene expression profiles. Previous studies have described a dual role for the AP-1 family transcription factor c-Jun in the regulation of cellular fate. In various cell types weak and transient activations of c-Jun N-terminal kinase (JNK) and c-Jun appear to contribute to proliferation and survival, whereas strong and prolonged activation of JNK and c-Jun result in apoptosis. These opposite roles played by c-Jun are cell type specific and the molecular mechanisms defining these antonymous c-Jun-mediated responses remain incompletely understood. c-Jun activity in transformed cells is regulated by signalling cascades downstream of oncoproteins such as Ras and Raf. In addition, the pro-proliferative role and the survival promoting function for c-Jun has been described in various cancer models. Furthermore, c-Jun was described to be overexpressed in different cancer types. However, the molecular mechanisms by which c-Jun exerts these oncogenic functions are not all clearly established. Therefore it is of primary interest to further identify molecular mechanisms and functions for c-Jun in cancer. Regulation of gene expression is tightly dependent on accurate protein-protein interactions. Therefore, co-factors for c-Jun may define the functions for c-Jun in cancer. Identification of protein-protein interactions promoting cancer may provide novel possibilities for cancer treatment. In this study, we show that DNA topoisomerase I (TopoI) is a transcriptional co-factor for c-Jun. Moreover, c-Jun and TopoI together promote expression of epidermal growth factor receptor (EGFR) in cancer cells. We also show that the clinically used TopoI inhibitor topotecan reduces EGFR expression. Importantly, the effect of TopoI on EGFR transcription was shown to depend on c-Jun as Jun-/- cells or cells treated with JNK inhibitor SP600125 are resistant to topotecan treatment both in regulation of EGFR expression and cell proliferation. Moreover, c-Jun regulates the nucleolar localization and the function of the ribonucleic acid (RNA) helicase DDX21, a previously identified member of c-Jun protein complex. In addition, c-Jun stimulates rRNA processing by supporting DDX21 rRNA binding. Finally, this study characterizes a DDX21 dependent expression of cyclin dependent kinase (Cdk) 6, a correlation of DDX21 expression with prostate cancer progression and a substrate binding dependency of DDX21 nucleolar localization in prostate cancer cells. Taken together, the results of this study validate the c-Jun-TopoI interaction and precise the c-Jun-DDX21 interaction. Moreover, these results show the importance for protein-protein interaction in the regulation of their cellular functions in cancer cell behavior. Finally, the results presented here disclose new exciting therapeutic opportunities for cancer treatment.

Ankle-brachial index, high-sensitivity C-reactive protein and endothelial function in a cardiovascular risk population

Atherosclerotic vascular disease is the leading cause of death in the Western world. Its main three manifestations are coronary heart disease, cerebrovascular disease, and peripheral arterial disease. Asymptomatic peripheral arterial disease is usually diagnosed using the ankle brachial index, and values ≤ 0.90 are used to determine the diagnosis. The classical risk factors of peripheral arterial disease, such as smoking and diabetes, are well known and early interventions are mandatory to improve the prognosis. What is not well known is the role of inflammation as a risk factor. Yet, a novel approach to cardiovascular diseases is the measurement of endothelial function. In this thesis, we studied the ankle-brachial index, C-reactive protein and endothelial function in a cardiovascular risk population. A total of 2856 subjects were invited to the study and 2085 (73%) responded. From these subjects, a cohort of 1756 risk persons was screened. We excluded the subjects with previously known cardiovascular disease or diabetes, because they were already under systematic follow-up. Out of the study subjects, 983 (56%) were women and 773 (44%) men. The ankle brachial index and high-sensitivity C-reactive protein were measured from 1047 subjects. Endothelial function was assessed by measuring reactive hyperemia pulse amplitude tonometry from 66 subjects with borderline peripheral arterial disease. In this study, smoking was a crucial risk factor for peripheral arterial disease. Subclinical peripheral arterial disease seems to be more common in hypertensive patients even without comorbidities. The measurement of the ankle brachial index is an efficient method to identify patients at an increased cardiovascular risk. High-sensitivity C-reactive protein did not correlate with the ankle brachial index or peripheral arterial disease. Instead, it correlated with measures of obesity. In a cardiovascular risk population with borderline peripheral arterial disease, nearly every fourth subject had endothelial dysfunction. This might point out a subgroup of individuals in need of more intensive treatment for their risk factors.