Foliar physiognomic record of climatic conditions during dormancy: Climate Leaf Analysis Multivariate Program (CLAMP) and the cold month mean temperature

The extent to which the leaves of woody dicots encode in their physiognomy the climatic conditions that exist during dormancy was tested by sampling 20 sites along an approximately west-east transect across European Russia, the Crimean Peninsula, Western Siberia, and central Eastern Siberia. This transect encompassed the most extreme mean annual temperature range recorded in the modern world where vegetation exists. Climate Leaf Analysis Multivariate Program (CLAMP) revealed little change in calibration of the warm month mean temperature compared with the PHYSG3AR data set derived from less extreme sites primarily in North America and Japan, but significant change with respect to the cold month mean temperature (CMMT) calibration. Although CLAMP underestimated the CMMT by up to 9°C in the coldest sites, the addition of the transect sites improved CLAMP's performance at low temperatures. This suggests that winter cold is encoded in foliar physiognomy even though the leaves are functional only during the late spring and summer months. This increase in performance was, however, at the cost of decreasing precision. Precipitation predictive capabilities were only slightly affected, but calibration of key climatic variables such as enthalpy, used in determining palaeoaltitude, remained more or less unchanged after the inclusion of the cold transect samples. © 2004 by The University of Chicago. All rights reseved

Eocene–early Oligocene climate and vegetation change in southern China: Evidence from the Maoming Basin

Although the Eocene-Oligocene climate transition marks a critical point in the development of the ‘icehouse’ global climate of the present little is known about this important change in the terrestrial realm at low latitudes. Our palynological study of the Shangcun Formation shows it to be early Oligocene in age: palyno-assemblages in the lower part of the formation indicate a cool interval dominated by conifer pollen in the earliest Oligocene followed by a warmer regime in the second half of the early Oligocene. To quantify middle Eocene to late early Oligocene climate conditions at low (~ 20°N) palaeolatitudes in southern Asia several thousand leaf fossil specimens from the Maoming Basin, southern China, were subjected to a multivariate (CLAMP) analysis of leaf form. For terrestrial palaeoclimate comparisons to be valid the palaeoaltitude at which the proxy data are obtained must be known. We find that leaves preserved in the Youganwo (middle Eocene), Huangniuling (late Eocene) and Shangcun (early Oligocene) formations were likely to have been deposited well above sea level at different palaeoelevations. In the Youganwo Formation fine-grained sediments were deposited at an altitude of ~ 1.5 km, after which the basin dropped to ~ 0.5 km by the time the upper Huangniuling sediments were deposited. The basin floor then rose again by 0.5 km reaching an altitude of approximately 1 km in which the Shangcun Formation fine-grained sediments were accumulated. Within the context of these elevation changes the prevailing climates experienced by the Youganwo, Lower Huangniuling, Upper Huangniuling and Shangcun fossil floras were humid subtropical with hot summers and warm winters, but witnessed a progressive increase in rainfall seasonality. By the early Oligocene rainfall seasonality was similar to that of the modern monsoonal climate of Guangdong Province, southern China. All floras show leaf physiognomic spectra most similar to those growing under the influence of the modern Indonesia-Australia Monsoon, but with no evidence of any adaptation to today's South or East Asia Monsoon regimes. The Upper Huangniuling Flora, rich in dipterocarp plant megafossils, grew in the warmest conditions with the highest cold month mean temperature and at the lowest altitude

Comprehensive molecular characterization of gastric adenocarcinoma

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies

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