Respiratory muscle strength as a predictive biomarker for survival in amyotrophic lateral sclerosis

Rationale: Biomarkers for survival in amyotrophic lateral sclerosis (ALS) would facilitate the development of novel drugs. Although respiratory muscle weakness is a known predictor of poor prognosis, a comprehensive comparison of different tests is lacking. Objectives: To compare the predictive power of invasive and noninvasive respiratory muscle strength assessments for survival or ventilator-free survival, up to 3 years. Methods: From a previously published report respiratory muscle strength measurements were available for 78 patients with ALS. Time to death and/or ventilation were ascertained. Receiver operating characteristic analysis was used to determine the cutoff point of each parameter. Measurements and Main Results: Each respiratory muscle strength assessment individually achieved statistical significance for prediction of survival or ventilator-free survival. In multivariate analysis sniff trans-diaphragmatic and esophageal pressure, twitch trans-diaphragmatic pressure (Tw Pdi), age, and maximal static expiratory mouth pressure were significant predictors of ventilation-free survival and Tw Pdi and maximal static expiratory mouth pressure for absolute survival. Although all measures had good specificity, there were differing sensitivities. All cutoff points for the VC were greater than 80% of normal, except for prediction of 3-month outcomes. Sequential data showed a linear decline for direct measures of respiratory muscle strength, whereas VC showed little to no decline until 12 months before death/ventilation. Conclusions: The most powerful biomarker for mortality stratification was Tw Pdi, but the predictive power of sniff nasal inspiratory pressure was also excellent. A VC within normal range suggested a good prognosis at 3 months but was of little other value

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