We have identified a t(8;9)(p21-23;p23-24) in seven male patients (mean age 50, range 32-74) with diverse hematologic malignancies and clinical outcomes: atypical chronic myeloid leukemia/chronic eosinophilic leukemia (n = 5), secondary acute myeloid leukemia (n = 1), and pre-B-cell acute lymphoblastic leukemia (n = 1). Initial fluorescence in situ hybridization studies of one patient indicated that the nonreceptor tyrosine kinase Janus-activated kinase 2 (JAK2) at 9p24 was disrupted. Rapid amplification of cDNA ends-PCR identified the 8p22 partner gene as human autoantigen pericentriolar material (PCM1), a gene encoding a large centrosomal protein with multiple coiled-coil domains. Reverse transcription-PCR and fluorescence in situ hybridization confirmed the fusion in this case and also identified PCM1-JAK2 in the six other t(8;9) patients. The breakpoints were variable in both genes, but in all cases the chimeric mRNA is predicted to encode a protein that retains several of the predicted coiled-coil domains from PCM1 and the entire tyrosine kinase domain of JAK2. Reciprocal JAK2-PCM1 mRNA was not detected in any patient. We conclude that human autoantigen pericentriolar material (PCM1)-JAK2 is a novel, recurrent fusion gene in hematologic malignancies. Patients with PCM1-JAK2 disease are attractive candidates for targeted signal transduction therapy. (Cancer Res 2005; 65(7): 2662-7)

Since the completion of the Human Genome project at the turn of the Century, there has been an unprecedented proliferation of genomic sequence data. A consequence of this is that the medical discoveries of the future will largely depend on our ability to process and analyse large genomic data sets, which continue to expand as the cost of sequencing decreases. Herein, we provide an overview of cloud computing and big data technologies, and discuss how such expertise can be used to deal with biology's big data sets. In particular, big data technologies such as the Apache Hadoop project, which provides distributed and parallelised data processing and analysis of petabyte (PB) scale data sets will be discussed, together with an overview of the current usage of Hadoop within the bioinformatics community.

Plasma NOx concentrations were raised in 22 acute painful crises in SCD. We have measured blood concentrations of nitric oxide metabolites (NOx) in sickle-cell disease (SCD), and shown that they are increased compared with healthy controls (P = 0.002), and haemoglobin E/beta-thalassaemic controls (P = 0.05). Concentrations in steady-state SCD were also higher than in healthy controls (P = 0.04) but not significantly different from the concentrations at the beginning of painful crises (P = 0.34). Importantly, in 12 regularly exchanged sicklers, the mean pre-transfusion NOx concentration did not differ significantly from the control population (P = 0.52), suggesting that the changes in NO metabolism can be reversed. It is unlikely that the increased concentrations of NOx in SCD result from anaemia or haemolysis as the untransfused haemoglobin E/beta-thalassaemics did not show increased levels.

SummaryHepatic venocclusive disease causes considerable morbidity and mortality following bone marrow transplantation. There are two hypotheses regarding the aetiology of this syndrome; firstly that changes in plasma coagulation factors and natural anticoagulants lead to a prothrombotic state and secondly that endothelial cell activation stimulates intravascular deposition of fibrin. We have investigated these mechanisms by measuring the changes in proteins C and S and factors VII and X in the post transplant period and by using the plasma concentration of factor Vila as an in vivo marker of potential endothelial cell tissue factor expression. Protein C fell in both allograft and autograft patients but more so in the allografts. Similar results were found for factors VII and X. These changes were predominantly due to hepatic dysfunction induced by the chemo-radiotherapy. Factor Vila levels were unchanged in both the allograft and autograft patients. We conclude that there is no convincing evidence for a procoagulant state following BMT as there are both anticoagulant and procoagulant changes. The absence of any changes in factor Vila levels suggests that tissue factor was not exposed to the general circulation following BMT but does not exclude focal expression at the sites of thrombosis.

The recent exponential growth of genomic databases has resulted in the common task of sequence alignment becoming one of the major bottlenecks in the field of computational biology. It is typical for these large datasets and complex computations to require cost prohibitive High Performance Computing (HPC) to function. As such, parallelised solutions have been proposed but many exhibit scalability limitations and are incapable of effectively processing "Big Data" - the name attributed to datasets that are extremely large, complex and require rapid processing. The Hadoop framework, comprised of distributed storage and a parallelised programming framework known as MapReduce, is specifically designed to work with such datasets but it is not trivial to efficiently redesign and implement bioinformatics algorithms according to this paradigm. The parallelisation strategy of "divide and conquer" for alignment algorithms can be applied to both data sets and input query sequences. However, scalability is still an issue due to memory constraints or large databases, with very large database segmentation leading to additional performance decline. Herein, we present Hadoop Blast (HBlast), a parallelised BLAST algorithm that proposes a flexible method to partition both databases and input query sequences using "virtual partitioning". HBlast presents improved scalability over existing solutions and well balanced computational work load while keeping database segmentation and recompilation to a minimum. Enhanced BLAST search performance on cheap memory constrained hardware has significant implications for in field clinical diagnostic testing; enabling faster and more accurate identification of pathogenic DNA in human blood or tissue samples.