• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 7
  • 2
  • 1
  • Tagged with
  • 14
  • 14
  • 6
  • 4
  • 4
  • 3
  • 3
  • 3
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
11

Application of phylogenetic inference methods to quantify intra-tumour heterogeneity and evolution of breast cancers

Brown, David Norman 13 November 2017 (has links)
Cancer related mortality is almost always due to metastatic dissemination of the primary disease. While research into the biological mechanisms that drive the metastatic cascade continues to unravel its molecular underpinnings, progress in our understanding of biological phenomena such as tumour heterogeneity and its relevance to the origins of distant recurrence or the emergence of resistance to therapy has been limited.In parallel to major breakthroughs in the development of high throughput molecular techniques, researchers have begun to utilise next generation sequencing to explore the relationship between primary and matched metastatic tumours in diverse types of neoplasia. Despite small cohort sizes and often, a limited number of matched metastases for each patient, pioneering studies have uncovered hitherto unknown biological processes such as the occurrence of organ specific metastatic lineages, polyclonal seeding and homing of metastatic cells to the primary tumour bed. While yet other studies continue to highlight the potential of genomic analyses, at the time this thesis was started, an in-depth knowledge of disease progression and metastatic dissemination was currently lacking in breast cancers.Herein, we employed phylogenetic inference methods to investigate intra-tumour heterogeneity and evolution of breast cancers. A combination of whole exome sequencing, custom ultra-deep resequencing and copy number profiling were applied to primary tumours and their associated metastases from ten autopsied breast cancer patients. Two modes of metastatic progression were observed. In the majority of cases, all distant metastases clustered on a branch separate from their primary lesion. Clonal frequency analysis of somatic mutations showed that the metastases had a monoclonal origin and descended from a common metastatic precursor. Alternatively, the primary tumour was clustered alongside metastases with early branches leading to distant organs. This dichotomy coincided with the clinical history of the patients whereby multiple seeding events from the primary tumour alongside cascading metastasis-to-metastasis disseminations occurred in treatment naïve de novo metastatic patients, whereas descent from a common metastatic precursor was observed in patients who underwent primary surgery followed by systemic treatment. The data also showed that a distant metastasis can be horizontally cross-seeded and finally revealed a correlation between the extent of somatic point mutations private to the distant lesions and patient overall survival. In an unrelated dataset of relapsed breast cancer patients with matched primary and distant lesions profiled using whole genome sequencing, the landscape of somatic alterations confirmed the time dependency of copy number aberrations implying that cancer phylogenies can be dated using a molecular clock.The work presented here harnesses the strength of high throughput genomic techniques and state of the art phylogenetic tools to tell the evolutionary history of breast cancers. Our results show that the linear and parallel models of metastatic dissemination which have been held as near doctrines for many years are overstated point of views of cancer progression. Beyond the biological insights, these results suggest that surgical excision of the primary tumour in de novo metastatic breast cancers might reduce dissemination in selected cases hence providing a potential biological rationale for this practice. Similarly, there is no strong evidence of benefit in overall survival from surgical resection of oligo-metastases in breast cancer. From our analyses, metastatic lesions constitute an additional source of seeding and heterogeneity in advanced breast cancer. The data presented here is too small to derive practice-changing evidence, but supports the concept that resecting isolated metastases may be of clinical benefit in oligo-metastatic breast cancer patients. In both cases, results from larger prospective studies are warranted. / Doctorat en Sciences biomédicales et pharmaceutiques (Médecine) / info:eu-repo/semantics/nonPublished
12

Molecular Evolution of Odonata Opsins, Odonata Phylogenomics and Detection of False Positive Sequence Homology Using Machine Learning

Suvorov, Anton 01 March 2018 (has links)
My dissertation comprises three related topics of evolutionary and computational biology, which correspond to the three Chapters. Chapter 1 focuses on tempo and mode of evolution in visual genes, namely opsins, via duplication events and subsequent molecular adaptation in Odonata (dragonflies and damselflies). Gene duplication plays a central role in adaptation to novel environments by providing new genetic material for functional divergence and evolution of biological complexity. Odonata have the largest opsin repertoire of any insect currently known. In particular our results suggest that both the blue sensitive (BS) and long-wave sensitive (LWS) opsin classes were subjected to strong positive selection that greatly weakens after multiple duplication events, a pattern that is consistent with the permanent heterozygote model. Due to the immense interspecific variation and duplicability potential of opsin genes among odonates, they represent a unique model system to test hypotheses regarding opsin gene duplication and diversification at the molecular level. Chapter 2 primarily focuses on reconstruction of the phylogenetic backbone of Odonata using RNA-seq data. In order to reconstruct the evolutionary history of Odonata, we performed comprehensive phylotranscriptomic analyses of 83 species covering 75% of all extant odonate families. Using maximum likelihood, Bayesian, coalescent-based and alignment free tree inference frameworks we were able to test, refine and resolve previously controversial relationships within the order. In particular, we confirmed the monophyly of Zygoptera, recovered Gomphidae and Petaluridae as sister groups with high confidence and identified Calopterygoidea as monophyletic. Fossil calibration coupled with diversification analyses provided insight into key events that influenced the evolution of Odonata. Specifically, we determined that there was a possible mass extinction of ancient odonate diversity during the P-Tr crisis and a single odonate lineage persisted following this extinction event. Lastly, Chapter 3 focuses on identification of erroneously assigned sequence homology using the intelligent agents of machine learning techniques. Accurate detection of homologous relationships of biological sequences (DNA or amino acid) amongst organisms is an important and often difficult task that is essential to various evolutionary studies, ranging from building phylogenies to predicting functional gene annotations. We developed biologically informative features that can be extracted from multiple sequence alignments of putative homologous genes (orthologs and paralogs) and further utilized in context of guided experimentation to verify false positive outcomes.
13

A Likelihood Method to Estimate/Detect Gene Flow and A Distance Method to Estimate Species Trees in the Presence of Gene Flow

Cui, Lingfei January 2014 (has links)
No description available.
14

Models and methods for molecular phylogenetics

Catanzaro, Daniele 28 October 2008 (has links)
Un des buts principaux de la biologie évolutive et de la médecine moléculaire consiste à reconstruire les relations phylogénétiques entre organismes à partir de leurs séquences moléculaires. En littérature, cette question est connue sous le nom d’inférence phylogénétique et a d'importantes applications dans la recherche médicale et pharmaceutique, ainsi que dans l’immunologie, l’épidémiologie, et la dynamique des populations. L’accumulation récente de données de séquences d’ADN dans les bases de données publiques, ainsi que la facilité relative avec laquelle des données nouvelles peuvent être obtenues, rend l’inférence phylogénétique particulièrement difficile (l'inférence phylogénétique est un problème NP-Hard sous tous les critères d’optimalité connus), de telle manière que des nouveaux critères et des algorithmes efficaces doivent être développés. Cette thèse a pour but: (i) d’analyser les limites mathématiques et biologiques des critères utilisés en inférence phylogénétique, (ii) de développer de nouveaux algorithmes efficaces permettant d’analyser de plus grands jeux de données. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

Page generated in 0.0837 seconds