deFuse: An Algorithm for Gene Fusion Discovery in Tumor RNA-Seq Data

Gene fusions created by somatic genomic rearrangements are known to play an important role in the onset and development of some cancers, such as lymphomas and sarcomas. RNA-Seq (whole transcriptome shotgun sequencing) is proving to be a useful tool for the discovery of novel gene fusions in cancer transcriptomes. However, algorithmic methods for the discovery of gene fusions using RNA-Seq data remain underdeveloped. We have developed deFuse, a novel computational method for fusion discovery in tumor RNA-Seq data. Unlike existing methods that use only unique best-hit alignments and consider only fusion boundaries at the ends of known exons, deFuse considers all alignments and all possible locations for fusion boundaries. As a result, deFuse is able to identify fusion sequences with demonstrably better sensitivity than previous approaches. To increase the specificity of our approach, we curated a list of 60 true positive and 61 true negative fusion sequences (as confirmed by RT-PCR), and have trained an adaboost classifier on 11 novel features of the sequence data. The resulting classifier has an estimated value of 0.91 for the area under the ROC curve. We have used deFuse to discover gene fusions in 40 ovarian tumor samples, one ovarian cancer cell line, and three sarcoma samples. We report herein the first gene fusions discovered in ovarian cancer. We conclude that gene fusions are not infrequent events in ovarian cancer and that these events have the potential to substantially alter the expression patterns of the genes involved; gene fusions should therefore be considered in efforts to comprehensively characterize the mutational profiles of ovarian cancer transcriptomes

Are patients with HHV-8 associated Castleman disease successfully treated with rituximab at risk of subsequently developing HHV-8 negative (idiopathic) Castleman disease?

Introduction: Multicentric Castleman disease (MCD) is a lymphoproliferative disorder characterized by lymph node histopathology and systemic symptoms. To our knowledge, there are no descriptions in the literature of long-term outcomes of human herpesvirus-8 (HHV-8)-associated MCD. Case Description: We report a case of a 70-year-old male living with human immunodeficiency virus and a history of human herpesvirus-8 (HHV-8)-associated MCD. The patient reported having had low-grade fever for two weeks. Extensive workup revealed systemic lymphadenopathy without evidence of autoimmune disease or malignancy. Lymph node biopsy was consistent with HHV-8-negative idiopathic MCD (iMCD). The patient was subsequently scheduled for anti-interleukin-6 therapy. Discussion: The present case is the first report of probable development of iMCD after long-term follow-up for HHV-8-associated MCD. The case illustrates the possible long-term consequences of MCD, suggesting the necessity of further research on the pathogenesis of CD. Conclusion: Given the uncertainty in the long-term outcomes of HHV-8-associated MCD, periodic surveillance of patients with a history of HHV-8-associated MCD is warranted. Prospective nationwide cohort studies comparing characteristics of HHV-8-associated MCD and iMCD would bring further insights

Detection of circulating tumour DNA is associated with inferior outcomes in Ewing sarcoma and osteosarcoma: a report from the Children's Oncology Group.

BackgroundNew prognostic markers are needed to identify patients with Ewing sarcoma (EWS) and osteosarcoma unlikely to benefit from standard therapy. We describe the incidence and association with outcome of circulating tumour DNA (ctDNA) using next-generation sequencing (NGS) assays.MethodsA NGS hybrid capture assay and an ultra-low-pass whole-genome sequencing assay were used to detect ctDNA in banked plasma from patients with EWS and osteosarcoma, respectively. Patients were coded as positive or negative for ctDNA and tested for association with clinical features and outcome.ResultsThe analytic cohort included 94 patients with EWS (82% from initial diagnosis) and 72 patients with primary localised osteosarcoma (100% from initial diagnosis). ctDNA was detectable in 53% and 57% of newly diagnosed patients with EWS and osteosarcoma, respectively. Among patients with newly diagnosed localised EWS, detectable ctDNA was associated with inferior 3-year event-free survival (48.6% vs. 82.1%; p = 0.006) and overall survival (79.8% vs. 92.6%; p = 0.01). In both EWS and osteosarcoma, risk of event and death increased with ctDNA levels.ConclusionsNGS assays agnostic of primary tumour sequencing results detect ctDNA in half of the plasma samples from patients with newly diagnosed EWS and osteosarcoma. Detectable ctDNA is associated with inferior outcomes

The landscape of chromosomal aberrations in breast cancer mouse models reveals driver-specific routes to tumorigenesis

Aneuploidy and copy-number alterations (CNAs) are a hallmark of human cancer. Although genetically engineered mouse models (GEMMs) are commonly used to model human cancer, their chromosomal landscapes remain underexplored. Here we use gene expression profiles to infer CNAs in 3,108 samples from 45 mouse models, providing the first comprehensive catalogue of chromosomal aberrations in cancer GEMMs. Mining this resource, we find that most chromosomal aberrations accumulate late during breast tumorigenesis, and observe marked differences in CNA prevalence between mouse mammary tumours initiated with distinct drivers. Some aberrations are recurrent and unique to specific GEMMs, suggesting distinct driver-dependent routes to tumorigenesis. Synteny-based comparison of mouse and human tumours narrows critical regions in CNAs, thereby identifying candidate driver genes. We experimentally validate that loss of Stratifin (SFN) promotes HER2-induced tumorigenesis in human cells. These results demonstrate the power of GEMM CNA analysis to inform the pathogenesis of human cancer

Glycolytic and Non-glycolytic Functions of Mycobacterium tuberculosis Fructose-1,6-bisphosphate Aldolase, an Essential Enzyme Produced by Replicating and Non-replicating Bacilli

The search for antituberculosis drugs active against persistent bacilli has led to our interest in metallodependent class II fructose- 1,6-bisphosphate aldolase (FBA-tb), a key enzyme of gluconeogenesis absent from mammalian cells. Knock-out experiments at the fba-tb locus indicated that this gene is required for the growth of Mycobacterium tuberculosis on gluconeogenetic substrates and in glucose-containing medium. Surface labeling and enzymatic activity measurements revealed that this enzyme was exported to the cell surface of M. tuberculosis and produced under various axenic growth conditions including oxygen depletion and hence by non-replicating bacilli. Importantly, FBA-tb was also produced in vivo in the lungs of infected guinea pigs and mice. FBA-tb bound human plasmin(ogen) and protected FBA-tb-bound plasmin from regulation by α 2-antiplasmin, suggestive of an involvement of this enzyme in host/pathogen interactions. The crystal structures of FBA-tb in the native form and in complex with a hydroxamate substrate analog were determined to 2.35- and 1.9-Å resolution, respectively. Whereas inhibitor attachment had no effect on the plasminogen binding activity of FBA-tb, it competed with the natural substrate of the enzyme, fructose 1,6-bisphosphate, and substantiated a previously unknown reaction mechanism associated with metallodependent aldolases involving recruitment of the catalytic zinc ion by the substrate upon active site binding. Altogether, our results highlight the potential of FBA-tb as a novel therapeutic target against both replicating and non-replicating bacilli.Fil: Santangelo, María de la Paz. State University of Colorado - Fort Collins; Estados Unidos. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gest, Petra M.. State University of Colorado - Fort Collins; Estados UnidosFil: Guerin, Marcelo E.. Universidad del País Vasco; EspañaFil: Coinçon, Mathieu. University of Montreal; CanadáFil: Pham, Ha. State University of Colorado - Fort Collins; Estados UnidosFil: Ryan, Gavin. State University of Colorado - Fort Collins; Estados UnidosFil: Puckett, Susan E.. Cornell University; Estados UnidosFil: Spencer, John S.. State University of Colorado - Fort Collins; Estados UnidosFil: Gonzalez Juarrero, Mercedes. State University of Colorado - Fort Collins; Estados UnidosFil: Daher, Racha. Universite de Paris XI. Institut de Chimie Moléculaire et des Matériaux d'Orsay; FranciaFil: Lenaerts, Anne J.. State University of Colorado - Fort Collins; Estados UnidosFil: Schnappinger, Dirk. Cornell University; Estados UnidosFil: Therisod, Michel. Universite de Paris XI. Institut de Chimie Moléculaire et des Matériaux d'Orsay; FranciaFil: Ehrt, Sabine. Cornell University; Estados UnidosFil: Sygusch, Jurgen. University of Montreal; CanadáFil: Jackson, Mary. State University of Colorado - Fort Collins; Estados Unido

Network Archaeology: Uncovering Ancient Networks from Present-day Interactions

Often questions arise about old or extinct networks. What proteins interacted in a long-extinct ancestor species of yeast? Who were the central players in the Last.fm social network 3 years ago? Our ability to answer such questions has been limited by the unavailability of past versions of networks. To overcome these limitations, we propose several algorithms for reconstructing a network's history of growth given only the network as it exists today and a generative model by which the network is believed to have evolved. Our likelihood-based method finds a probable previous state of the network by reversing the forward growth model. This approach retains node identities so that the history of individual nodes can be tracked. We apply these algorithms to uncover older, non-extant biological and social networks believed to have grown via several models, including duplication-mutation with complementarity, forest fire, and preferential attachment. Through experiments on both synthetic and real-world data, we find that our algorithms can estimate node arrival times, identify anchor nodes from which new nodes copy links, and can reveal significant features of networks that have long since disappeared.Comment: 16 pages, 10 figure

Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems

A generic mechanism - networked buffering - is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems. \ud \u