Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

International AIDS Society global scientific strategy: towards an HIV cure 2016

Antiretroviral therapy is not curative. Given the challenges in providing lifelong therapy to a global population of more than 35 million people living with HIV, there is intense interest in developing a cure for HIV infection. The International AIDS Society convened a group of international experts to develop a scientific strategy for research towards an HIV cure. This Perspective summarizes the group's strategy

Securing application with software partitioning: a case study using SGX

Application size and complexity are the underlying cause of numerous security vulnerabilities in code. In order to mitigate the risks arising from such vulnerabilities, various techniques have been proposed to isolate the execution of sensitive code from the rest of the application and from other software on the platform (e.g. the operating system). However, even with these partitioning techniques, it is not immediately clear exactly how they can and should be used to partition applications. What overall partitioning scheme should be followed; what granularity of the partitions should be. To some extent, this is dependent on the capabilities and performance of the partitioning technology in use. For this work, we focus on the upcoming Intel Software Guard Extensions (SGX) technology as the state-of-the-art in this field. SGX provides a trusted execution environment, called an enclave, that protects the integrity of the code and the confidentiality of the data inside it from other software, including the operating system. We present a novel framework consisting of four possible schemes under which an application can be partitioned. These schemes range from coarse-grained partitioning, in which the full application is included in a single enclave, through ultra-fine partitioning, in which each application secret is protected in an individual enclave. We explain the specific security benefits provided by each of the partitioning schemes and discuss how the performance of the application would be affected. To compare the different partitioning schemes, we have partitioned OpenSSL using four different schemes. We discuss SGX properties together with the implications of our design choices in this pape

Securing Application with Software Partitioning: A Case Study Using SGX

Application size and complexity are the underlying cause of numerous security vulnerabilities in code. In order to mitigate the risks arising from such vulnerabilities, various techniques have been proposed to isolate the execution of sensitive code from the rest of the application and from other software on the platform (e.g. the operating system). However, even with these partitioning techniques, it is not immediately clear exactly how they can and should be used to partition applications. What overall partitioning scheme should be followed; what granularity of the partitions should be. To some extent, this is dependent on the capabilities and performance of the partitioning technology in use. For this work, we focus on the upcoming Intel Software Guard Extensions (SGX) technology as the state-of-the-art in this field. SGX provides a trusted execution environment, called an enclave, that protects the integrity of the code and the confidentiality of the data inside it from other software, including the operating system. We present a novel framework consisting of four possible schemes under which an application can be partitioned. These schemes range from coarse-grained partitioning, in which the full application is included in a single enclave, through ultra-fine partitioning, in which each application secret is protected in an individual enclave. We explain the specific security benefits provided by each of the partitioning schemes and discuss how the performance of the application would be affected. To compare the different partitioning schemes, we have partitioned OpenSSL using four different schemes. We discuss SGX properties together with the implications of our design choices in this pape

Murine Genetically Engineered and Human Xenograft Models of Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is a genetically complex disease, with multiple factors having an impact on onset, progression, and response to therapy. Genetic differences/abnormalities have been found in hematopoietic stem cells from patients, as well as in B lymphocytes of individuals with Monoclonal B-cell lymphocytosis who may develop the disease. Furthermore, after the onset of CLL, additional genetic alterations occur over time, often causing disease worsening and altering patient outcomes. Therefore, being able to genetically engineer mouse models that mimic CLL or at least certain aspects of the disease will help us understand disease mechanisms and improve treatments. This notwithstanding, because neither the genetic aberrations responsible for leukemogenesis and progression nor the promoting factors that support these are likely identical in character or influences for all patients, genetically engineered mouse models will only completely mimic CLL when all of these factors are precisely defined. In addition, multiple genetically engineered models may be required because of the heterogeneity in susceptibility genes among patients that can have an effect on genetic and environmental characteristics influencing disease development and outcome. For these reasons, we review the major murine genetically engineered and human xenograft models in use at the present time, aiming to report the advantages and disadvantages of each. (C) 2014 Elsevier Inc. All rights reserved