Extraordinary Biomass-Burning Episode and Impact Winter Triggered by the Younger Dryas Cosmic Impact ∼12,800 Years Ago. 2. Lake, Marine, and Terrestrial Sediments

Part 1 of this study investigated evidence of biomass burning in global ice records, and here we continue to test the hypothesis that an impact event at the Younger Dryas boundary (YDB) caused an anomalously intense episode of biomass burning at ∼12.8 ka on a multicontinental scale (North and South America, Europe, and Asia). Quantitative analyses of charcoal and soot records from 152 lakes, marine cores, and terrestrial sequences reveal a major peak in biomass burning at the Younger Dryas (YD) onset that appears to be the highest during the latest Quaternary. For the Cretaceous-Tertiary boundary (K-Pg) impact event, concentrations of soot were previously utilized to estimate the global amount of biomass burned, and similar measurements suggest that wildfires at the YD onset rapidly consumed ∼10 million km2 of Earth’s surface, or ∼9% of Earth’s biomass, considerably more than for the K-Pg impact. Bayesian analyses and age regressions demonstrate that ages for YDB peaks in charcoal and soot across four continents are synchronous with the ages of an abundance peak in platinum in the Greenland Ice Sheet Project 2 (GISP2) ice core and of the YDB impact event (12,835–12,735 cal BP). Thus, existing evidence indicates that the YDB impact event caused an anomalously large episode of biomass burning, resulting in extensive atmospheric soot/dust loading that triggered an “impact winter.” This, in turn, triggered abrupt YD cooling and other climate changes, reinforced by climatic feedback mechanisms, including Arctic sea ice expansion, rerouting of North American continental runoff, and subsequent ocean circulation changes

Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies

Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin

© 2014 Elsevier Inc. Recent genomic analyses of pathologically defined tumor types identify 'within-a-tissue' disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-oforigin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pancancer subtypes. The multiplatform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All data sets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies