Evaluation and intercomparison of global atmospheric transport models using Rn-222 and other short-lived tracers

Simulations of Rn-222 and other short-lived tracers are used to evaluate and intercompare the representations of convective and synoptic processes in 20 global atmospheric transport models. Results show that most established three-dimensional models simulate vertical mixing in the troposphere to within the constraints offered by the observed mean Rn-222 concentrations and that subgrid parameterization of convection is essential for this purpose. However, none of the models captures the observed variability of Rn-222 concentrations in the upper troposphere, and none reproduces the high Rn-222 concentrations measured at 200 hPa over Hawaii. The established three-dimensional models reproduce the frequency and magnitude of high- Rn-222 episodes observed at Crozet Island in the Indian Ocean, demonstrating that they can resolve the synoptic-scale transport of continental plumes with no significant numerical diffusion. Large differences between models are found in the rates of meridional transport in the upper troposphere (interhemispheric exchange, exchange between tropics and high latitudes). The four two-dimensional models which participated in the intercomparison tend to underestimate the rate of vertical transport from the lower to the upper troposphere but show concentrations of Rn-222 in the lower troposphere that are comparable to the zonal mean values in the three-dimensional models

A Genomics-Based Classification of Human Lung Tumors

We characterized genome alterations in 1255 clinically annotated lung tumors of all histological subgroups to identify genetically defined and clinically relevant subtypes. More than 55% of all cases had at least one oncogenic genome alteration potentially amenable to specific therapeutic intervention, including several personalized treatment approaches that are already in clinical evaluation. Marked differences in the pattern of genomic alterations existed between and within histological subtypes, thus challenging the original histomorphological diagnosis. Immunohistochemical studies confirmed many of these reassigned subtypes. The reassignment eliminated almost all cases of large cell carcinomas, some of which had therapeutically relevant alterations. Prospective testing of our genomics-based diagnostic algorithm in 5145 lung cancer patients enabled a genome-based diagnosis in 3863 (75%) patients, confirmed the feasibility of rational reassignments of large cell lung cancer, and led to improvement in overall survival in patients with EGFR-mutant or ALK-rearranged cancers. Thus, our findings provide support for broad implementation of genome-based diagnosis of lung cancer

Integrative genome analyses identify key somatic driver mutations of small-cell lung cancer

Small-cell lung cancer (SCLC) is an aggressive lung tumor subtype with poor prognosis. We sequenced 29 SCLC exomes, 2 genomes and 15 transcriptomes and found an extremely high mutation rate of 7.4 ± 1 protein-changing mutations per million base pairs. Therefore, we conducted integrated analyses of the various data sets to identify pathogenetically relevant mutated genes. In all cases, we found evidence for inactivation of TP53 and RB1 and identified recurrent mutations in the CREBBP, EP300 and MLL genes that encode histone modifiers. Furthermore, we observed mutations in PTEN, SLIT2 and EPHA7, as well as focal amplifications of the FGFR1 tyrosine kinase gene. Finally, we detected many of the alterations found in humans in SCLC tumors from Tp53 and Rb1 double knockout mice. Our study implicates histone modification as a major feature of SCLC, reveals potentially therapeutically tractable genomic alterations and provides a generalizable framework for the identification of biologically relevant genes in the context of high mutational background