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

Assessing treatment outcomes in multiple sclerosis trials and in the clinical setting

Increasing numbers of drugs are being developed for the treatment of multiple sclerosis (MS). Measurement of relevant outcomes is key for assessing the efficacy of new drugs in clinical trials and for monitoring responses to disease-modifying drugs in individual patients. Most outcomes used in trial and clinical settings reflect either clinical or neuroimaging aspects of MS (such as relapse and accrual of disability or the presence of visible inflammation and brain tissue loss, respectively). However, most measures employed in clinical trials to assess treatment effects are not used in routine practice. In clinical trials, the appropriate choice of outcome measures is crucial because the results determine whether a drug is considered effective and therefore worthy of further development; in the clinic, outcome measures can guide treatment decisions, such as choosing a first-line disease-modifying drug or escalating to second-line treatment. This Review discusses clinical, neuroimaging and composite outcome measures for MS, including patient-reported outcome measures, used in both trials and the clinical setting. Its aim is to help clinicians and researchers navigate through the multiple options encountered when choosing an outcome measure. Barriers and limitations that need to be overcome to translate trial outcome measures into the clinical setting are also discussed

Practical Side-Channel Attacks against WPA-TKIP

status: publishe

Experimental Analysis of an Application-independent Energy Management

Abstract. In the near future more and more users will access Internet services by means of portable devices through wireless links. However, mobile computing is still strongly limited by the scarcity of energetic resources of portable devices. In this paper we propose and evaluate an application-independent energy management policy for a Wi-Fi hotspot scenario. Unlike the IEEE 802.11 Power Saving Mode, the proposed solution is able to adapt to the application traffic profile, thus saving a considerable amount of energy. For the same reason it is flexible, i.e., it exhibits good performance irrespectively of the specific network application, and even in the presence of concurrent applications. Experimental measurements performed on a prototype implementation with different traffic types have shown that our energy management policy is able to save up to 80 % of the energy consumed in a legacy architecture, without a significant degradation on the QoS perceived by the user. 1

Delivering content with LTE Broadcast 4

Nine decades of innovatio