Developing methods for the context-specific reconstruction of metabolic models of cancer cells

Dissertação de mestrado em BioinformáticaThe recent advances in genome sequencing technologies and other high-throughput methodologies allowed the identification and quantification of individual cell components. These efforts led to the development of genome-scale metabolic models (GSMMs), not only for humans but also for several other organisms. These models have been used to predict cellular metabolic phenotypes under a variety of physiological conditions and contexts, proving to be useful in tasks such as drug discovery, biomarker identification and interactions between hosts and pathogens. Therefore, these models provide a useful tool for targeting diseases such as cancer, Alzheimer or tuberculosis. However, the usefulness of GSSMs is highly dependent on their capabilities to predict phenotypes in the array of different cell types that compose the human body, making the development of tissue/context-specific models mandatory. To address this issue, several methods have been proposed to integrate omics data, such as transcriptomics or proteomics, to improve the phenotype prediction abilities of GSSMs. Despite these efforts, these methods still have some limitations. In most cases, their usage is locked behind commercially licensed software platforms, or not available in a user-friendly fashion, thus restricting their use to users with programming or command-line knowledge. In this work, an open-source tool was developed for the reconstruction of tissue/context-specific models based on a generic template GSMM and the integration of omics data. The Tissue-Specific Model Reconstruction (TSM-Rec) tool was developed under the Python programming language and features the FASTCORE algorithm for the reconstruction of tissue/context-specific metabolic models. Its functionalities include the loading of omics data from a variety of omics databases, a set of filtering and transformation methods to adjust the data for integration with a template metabolic model, and finally the reconstruction of tissue/context-specific metabolic models. To evaluate the functionality of the developed tool, a cancer related case-study was carried. Using omics data from 314 glioma patients, the TSM-Rec tool was used to reconstruct metabolic models of different grade gliomas. A total of three models were generated, corresponding to grade II, III and IV gliomas. These models were analysed regarding their differences and similarities in reactions and pathways. This comparison highlighted biological processes common to all glioma grades, and pathways that are more prominent in each glioma model. The results show that the tool developed during this work can be useful for the reconstruction of cancer metabolic models, in a search for insights into cancer metabolism and possible approaches towards drug-target discovery.Os avanços recentes nas tecnologias de sequenciação de genomas e noutras metodologias experimentais de alto rendimento permitiram a identificação e quantificação dos diversos componentes celulares. Estes esforços levaram ao desenvolvimento de Modelos Metabólicos à Escala Genómica (MMEG) não só de humanos, mas também de diversos organismos. Estes modelos têm sido utilizados para a previsão de fenótipos metabólicos sob uma variedade de contextos e condições fisiológicas, mostrando a sua utilidade em áreas como a descoberta de fármacos, a identificação de biomarcadores ou interações entre hóspede e patógeno. Desta forma, estes modelos revelam-se ferramentas úteis para o estudo de doenças como o cancro, Alzheimer ou a tuberculose. Contudo, a utilidade dos MMEG está altamente dependente das suas capacidades de previsão de fenótipos nos diversostipos celulares que compõem o corpo humano, tornando o desenvolvimento de modelos específicos de tecidos uma tarefa obrigatória. Para resolver este problema, vários métodos têm proposto a integração de dados ómicos como os de transcriptómica ou proteómica para melhorar as capacidades preditivas dos MMEG. Apesar disso, estes métodos ainda sofrem de algumas limitações. Na maioria dos casos o seu uso está confinado a plataformas ou softwares com licenças comerciais, ou não está disponível numa ferramenta de fácil uso, limitando a sua utilização a utilizadores com conhecimentos de programação ou de linha de comandos. Neste trabalho, foi desenvolvida uma ferramenta de acesso livre para a reconstrução de modelos metabólicos específicos para tecidos tendo por base um MMEG genérico e a integração de dados ómicos. A ferramenta TSM-Rec (Tissue-Specific Model Reconstruction), foi desenvolvida na linguagem de programação Python e recorre ao algoritmo FASTCORE para efetuar a reconstrução de modelos metabólicos específicos. As suas funcionalidades permitem a leitura de dados ómicos de diversas bases de dados ómicas, a filtragem e transformação dos mesmos para permitir a sua integração com um modelo metabólico genérico e por fim, a reconstrução de modelos metabólicos específicos. De forma a avaliar o funcionamento da ferramenta desenvolvida, esta foi aplicada num caso de estudo de cancro. Recorrendo a dados ómicos de 314 pacientes com glioma, usou-se a ferramenta TSM-Rec para a reconstrução de modelos metabólicos de gliomas de diferentes graus. No total, foram desenvolvidos três modelos correspondentes a gliomas de grau II, grau III e grau IV. Estes modelos foram analisados no sentido de perceber as diferenças e as similaridades entre as reações e as vias metabólicas envolvidas em cada um dos modelos. Esta comparação permitiu isolar processos biológicos comuns a todos os graus de glioma, assim como vias metabólicas que se destacam em cada um dos graus. Os resultados obtidos demonstram que a ferramenta desenvolvida pode ser útil para a reconstrução de modelos metabólicos de cancro, na procura de um melhor conhecimento do metabolismo do cancro e possíveis abordagens para a descoberta de fármacos

Structure-Function Relationship of the Ligand-Binding Domain of the Fibroblast Growth Factor Receptor

The interactions between FGF and fibroblast growth factor receptors are responsible for the regulation of key cellular processes. FGF is important in both germ cell and embryonic developments. FGF continues to play important roles during adulthood by regulating embryogenesis, cell differentiation, and wound healing (1-7). The regulations of these cellular events are initiated through FGF binding to the fibroblast growth factor receptors. The complex formed by FGF and the receptor involves a key interaction with heparin. Through interactions with heparin, the FGF, FGFR and Heparin form a 2:2:2 complex (8). This complex formation results in autophosphorylation in the tyrosine kinase domain in the cytoplasm. The autophosphorylation events lead to downstream signaling that result in the regulation of previously mentioned cellular processes (9, 10). Mutations within the FGF or FGFR may interfere with signaling or protein stability. Changes in the signaling efficiency by FGF or the FGFR are shown to lead to disease states There exist many point mutations in the FGF receptor that result in craniofacial, hypogonadotropic hypogonadism, anosmia, and tumor development. Using site-directed mutagenesis we have shown non-covalent interactions formed by Kallmann syndrome linked mutations result in a loss-of-binding between FGF and the FGF receptor. This evidence has shown that the non-covalent ligand binding interactions lost are due to changes in the D2 structure or binding site. Additionally, the R203C mutation, linked to breast cancer, was tested and determined to break a D2 stabilizing cation-ð bond. The cation-ð stabilized the binding interaction with heparin and provides stability to the D2 domain. Although the decreased stability of the D2 domain supports a loss-of-function, we are currently investigating intermolecular disulfide bond formation between adjacent receptor. This is a known mechanism among FGF receptors that may lead to signaling in the absence of a ligand

【研究分野別】シーズ集 [英語版]

[英語版

Molecular profiling of primary head and neck squamous cell carcinoma and lymph node metastases

INTRODUCTION: The presence of lymph node metastases and/or extracapsular spread (ECS) has a significant impact on patient survival in Head and neck squamous cell carcinoma (HNSCC). Little is known about the molecular mechanisms associated with metastasis. A marker that could predict metastasis from primary tumour sampling could be of great clinical benefit for patients. Similarly in oropharyngeal squamous cell carcinoma (OPSCC), the molecular changes associated with human papilloma virus are incompletely understood. The impact of viral load has not been well explored and could help identify molecular markers associated with Human papillomavirus (HPV)-driven OPSCC. METHODS: Tissue samples were identified from Leeds Pathology Archive and nucleic acid extracted from these. This was processed into sequencing libraries and analysed for copy number alteration (CNA) and microRNA (miRNA) profiles in clinicopathologic groups relating to metastasis and HPV viral load. RESULTS: A panel of 14 CNAs was identified as associated with nodal metastasis and loss of 18q21.1-q21.32 was associated with ECS. The fraction of genome altered (FGA) was also increased in metastatic primary tumours. A panel of 19 CNAs was identified as associated with no detectable viral load and the FGA was found to be increased in this group of OPSCC. Twelve miRNAs were identified as associated with nodal metastasis. DISCUSSION: The CNA and miRNA profile of primary tumours was found to be largely similar, though not identical, highlighting the need to use metastatic tissue to attempt discovery of metastatic molecular markers. Integrating miRNA and CNA data suggested miRNA expression is not governed by CNA. Potentially translational marker for metastasis and OPSCC with no viral load have been identified

Study into the role of lactadherin as a tumour associated antigen and angiogenesis factor - investigating HuMc3 (Angiolix®) as a therapeutic antibody for cancer

Lactadherin is a glycoprotein thought to have roles in cancer progression, through ligation of integrins αvβ3 and/or αvβ5 on the surface of tumour cells and their vasculature. It is thought to promote tumour growth through activation of integrin signalling pathways in both tumour and vascular endothelial cells, leading to direct tumour expansion and indirect tumour growth through stimulation of angiogenesis. HuMc3 (Angiolix®) an antibody with affinity to the integrin binding EGF-like domain of lactadherin, has been shown to inhibit lactadherin association with αv integrin expressing cell lines. This work aimed to uncover whether through its disruption of lactadherin αvβ3 and/or αvβ5 integrin ligation, HuMc3 could prevent/slow the growth of lactadherin-overexpressing tumours. This work confirmed the ability of HuMc3 to inhibit lactadherin binding to both tumour cell and vascular endothelial cell αvβ3/αvβ5 integrins. It demonstrated a concentration-dependent growth inhibition of tumour xenografts in vivo alone and a greater effect for combination with a conventional chemotherapy drug than either therapy alone. In one tumour model HuMc3 showed a similar therapeutic effect when applied alone to an approved anti-vasculature anti-cancer therapeutic bevacizumab, though a lower effect was observed when both were applied with chemotherapy. HuMc3 showed no apparent therapeutic toxicity and in biodistribution studies, no specific uptake by any normal murine tissue. In addition, the in vivo data for HuMc3 compared fairly well with that published for other anti-cancer and anti-vasculature therapeutics approved/in clinical development. HuMc3 was therefore indicated to have the potential as a successful anti-cancer therapeutic for treatment of lactadherin over-expressing cancers. Further work may determine the optimal monotherapy concentration and may uncover better combinations with other targeted agents and conventional chemotherapy/radiotherapy. A major drawback of this work was however the lack of success of the in vitro assays, so the mode of action of HuMc3 could not be confirmed. Further work may involve repeating these assays under conditions shown successful in published work with other αvβ3/αvβ5 integrin ligand-mAb combinations, as well as repeating the in vivo work with inclusion of an isotypematched control antibody, tissue analysis to examine any changes to vascular density and with examination of the importance of antibody effector functions in the in vivo effect of HuMc