Angioimmunoblastic T cell lymphoma (AITL) and peripheral T cell lymphoma not-otherwise-specified (PTCL, NOS) have poor prognosis and lack actionable targets for directed therapies in most cases. Here we report the identification of FYN-TRAF3IP2 as a novel highly recurrent oncogenic gene fusion in AITL and PTCL, NOS tumors. Mechanistically, FYN-TRAF3IP2 triggers aberrant NF-κB activity by engaging TRAF6 downstream of T cell receptor signaling. Moreover, FYN-TRAF3IP2 expression in hematopoietic progenitors induces NF-κB-driven T cell transformation in mice and cooperates with loss of the Tet2 tumor suppressor in PTCL development. Therapeutically, abrogation of NF-κB signaling in FYN-TRAF3IP2-induced tumors via IκB kinase inhibitors delivers strong anti-lymphoma effects in vitro and in vivo. These results formally demonstrate an oncogenic role for FYN-TRAF3IP2 and NF-κB signaling in the pathogenesis of PTCL.

Thesis (PhD)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: See item for full text / AFRIKAANSE OPSOMMING: Sien item vir volteks

Cancer is a leading cause of death worldwide, resulting in an estimated 1.6 million mortalities and 600,000 new cases in the US alone in 2015. Gene fusions, hybrid genes formed from two originally separated genes, are known drivers of cancer. However, gene fusions have also been found in healthy cells due to routine errors in replication. This project aims to understand the role of gene fusion in cancer. Specifically, we seek to achieve two goals. First, we would like to develop a computational method that predicts if a gene fusion event is associated with the cancer or healthy sample. Second, we would like to use this information to determine and characterize molecular mechanisms behind the gene fusion events. Recent studies have attempted to address these problems, but without explicit consideration of the fact that there are overlapping fusion events in both cancer and healthy cells. Here, we address this problem using FUsion Enriched Learning of CANcer Mutations (FUELCAN), a semi-supervised model, which classifies all overlapping fusion events as unlabeled to start. The model is trained using the known cancer and healthy samples and tested using the unlabeled dataset. Unlabeled data is classified as associated with healthy or cancer samples and the top 20 data points are put back into the training set. The process continues until all have been appropriately classified. Three datasets were analyzed from Acute Lymphoblastic Leukemia (ALL), breast cancer and colorectal cancer. We obtained similar results for both supervised and semi-supervised classification. To improve our model, we assessed the functional landscape of gene fusion events and observed that the pathway neighbors of both gene fusion partners are differentially expressed in each cancer dataset. The significant neighbors are also shown to have direct connections to cancer pathways and functions, indicating that these gene fusions are important for cancer development. Future directions include applying the acquired transcriptomic knowledge to our machine learning algorithm, counting transcription factors and kinases within the gene fusion events and their neighbors and assessing the differences between upstream and downstream effects within the pathway neighbors.

Abstract not available

Many alpha-helical membrane proteins contain internal symmetries, indicating that they might have evolved through a gene duplication and fusion event Here, we have characterized internal duplications among membrane proteins of known structure and in three complete genomes We found that the majority of large transmembrane (TM) proteins contain an internal duplication The duplications found showed a large variability both in the number of TM-segments included and in their orientation Surprisingly, an approximately equal number of antiparallel duplications and parallel duplications were found However, of all 11 superfamilies with an internal duplication, only for one, the AcrB Multidrug Efflux Pump, the duplicated unit could be found in its nonduplicated form An evolutionary analysis of the AcrB homologs indicates that several independent fusions have occurred, including the fusion of the SecD and SecF proteins into the 12-TM-protein SecDF in Brucella and Staphylococcus aureus In one additional case, the Vitamin B-12 transporter-like ABC transporters, the protein had undergone an additional fusion to form protein with 20 TM-helices in several bacterial genomes Finally, homologs to all human membrane proteins were used to detect the presence of duplicated and nonduplicated proteins This confirmed that only in rare cases can homologs with different duplication status be found, although internal symmetry is frequent among these proteins One possible explanation is that it is frequent that duplication and fusion events happen simultaneously and that there is almost always a strong selective advantage for the fused form / <p>authorCount :4</p>

Thesis (Ph. D.)--Carleton University, 1992. / Also available in electronic format on the Internet.

<p>Orthology identification is central to comparative and evolutionary genomics and is an active area of research. Despite a recent shift towards tree reconciliation and other phylogenetic methods, previous comparisons between different algorithms relied on real datasets where true orthology relationships are unknown and did not conclusively show whether phylogenetic methods truly outperform sequence similarity-based methods. Using simulated datasets generated from programs we developed, we show that tree reconciliation does perform better than similarity-based methods when the true species phylogeny is known. Even slight deviations in the species phylogeny can have adverse effects on the performance of reconciliation algorithms and in those cases similarity-based methods may perform better. Fusion and fission complicate orthology identification and are not explicitly considered in most existing algorithms. Programs designed specifically to investigate fusion and fission events are either unavailable or are not specific enough to identify events affecting orthologous genes. We developed a pipeline of programs called FusionFinder that perform this task, gaining new insights to the contributions of fusion and fission to bacterial protein evolution and uncover an unexpected abundance of fissions in <em>Bacillus anthracis</em> that to our knowledge yet to be reported.</p> / Master of Science (MS)

Background: Prostate cancer (PCa) is one of the most prevalent cancers worldwide. The clinical manifestations and molecular characteristics of PCa are highly variable. Aggressive types require radical treatment, whereas indolent ones may be suitable for active surveillance or organ-preserving focal therapies. Patient stratification by clinical or pathological risk categories still lacks sufficient precision. Incorporating molecular biomarkers, such as transcriptome-wide expression signatures, improves patient stratification but so far excludes chromosomal rearrangements. In this study, we investigated gene fusions in PCa, characterized potential novel candidates, and explored their role as prognostic markers for PCa progression. Methods: We analyzed 630 patients in four cohorts with varying traits regarding sequencing protocols, sample conservation, and PCa risk group. The datasets included transcriptome-wide expression and matched clinical follow-up data to detect and characterize gene fusions in PCa. With the fusion calling software Arriba, we computationally predicted gene fusions. Following detection, we annotated the gene fusions using published databases for gene fusions in cancer. To relate the occurrence of gene fusions to Gleason Grading Groups and disease prognosis, we performed survival analyses using the Kaplan–Meier estimator, log-rank test, and Cox regression. Results: Our analyses identified two potential novel gene fusions, MBTTPS2,L0XNC01::SMS and AMACR::AMACR . These fusions were detected in all four studied cohorts, providing compelling evidence for the validity of these fusions and their relevance in PCa. We also found that the number of gene fusions detected in a patient sample was significantly associated with the time to biochemical recurrence in two of the four cohorts (log-rank test, p-value < 0.05 for both cohorts). This was also confirmed after adjusting the prognostic model for Gleason Grading Groups (Cox regression, p-values < 0.05). Conclusions: Our gene fusion characterization workflow revealed two potential novel fusions specific for PCa. We found evidence that the number of gene fusions was associated with the prognosis of PCa. However, as the quantitative correlations were only moderately strong, further validation and assessment of clinical value is required before potential application.

An efficient system for or 'Agrobacterium'-mediated transformation of <i>Brassica carinata</i> was used together with a promoterless <i> gus</i>::<i>nptII</i> gene fusion to isolate putative promoter sequences. Cotyledonary petioles were transformed using the promoterless gene fusion construct. Only transformation events in which the promoterless gene fusion had integrated downstream from plant regulatory sequences were expected to produce viable tissue under kanamycin selection. Forty-two transgenic plants were recovered. Transformation efficiency was approximately 0.6%. Regenerated plants were screened for GUS expression in different tissues and organs by histological and fluorometric assays. Tissue-specific GUS expression was detected (stigmas, seed coat, leaf edges and vascular tissue) in some plants, while strong constitutive GUS expression was detected in others (based on GUS histological assays). Using subgenomic libraries, putative promoter fragments were isolated from the plants which exhibited GUS expression in stigmas, leaf edges and constitutively. A putative promoter fragment from a plant which exhibited GUS expression only in the stigma was fused with the gus gene and reintroduced by <i>Agrobacterium </i> -mediated transformation into <i>B. napus, B. carinata, Arabidopsis' and tobacco </i>. GUS expression was observed in the stigma of <i>B. napus </i> but not in ' B. carinata'. In <i>Arabidopsis </i> and tobacco GUS expression. was not tissue specific (weakly constitutive or restricted to two or more tissues). The 3' DNA sequence (15 kb) flanking the <i> gus</i>::<i>nptII </i> insert in the plant with GUS expression in the stigma was also isolated using a subgenomic library. A gene for a cytochrome P450 like protein was discovered on the minus DNA strand of the 3' sequence with a start codon approximately 6.5 kb from the T-DNA left border.

Gene-fusions are a prevalent class of genetic variants that are often employed as cancer biomarkers and therapeutic targets. In recent years, high-throughput sequencing of the cellular genome and transcriptome have emerged as a promising approach for the investigation of gene-fusions at the DNA and RNA level. Although, large volumes of sequencing data and complexity of gene-fusion structures presents unique computational challenges. This dissertation describes research that first addresses the bioinformatics challenges associated with the analysis of the massive volumes of sequencing data by developing bioinformatics pipeline and more applied integrated computational workflows. Application of high-throughput sequencing and the proposed bioinformatics approaches for the breast and ovarian cancer study reveals unexpected complex structures of gene-fusions and their functional significance in the onset and progression of cancer. Integrative analysis of gene-fusions at DNA and RNA level shows the key importance of the regulation of gene-fusion at the transcription level in cancer.