Changes of monocyte human leukocyte antigen-DR expression as a reliable predictor of mortality in severe sepsis

INTRODUCTION: Many studies have shown that monocyte human leukocyte antigen-DR (mHLA-DR) expression may be a good predictor for mortality in severe septic patients. On the contrary, other studies found mHLA-DR was not a useful prognostic marker in severe sepsis. Few studies have taken changes of mHLA-DR during treatment into consideration. The objective of this study was to estimate the prognostic value of changes of mHLA-DR to predict mortality in severe sepsis. METHODS: In this prospective observational study, mHLA-DR was measured by flow cytometry in peripheral blood from 79 adult patients with severe sepsis. mHLA-DR levels were determined on day 0, 3, 7 after admission to the surgical intensive care unit (SICU) with a diagnosis of severe sepsis. ΔmHLA-DR(3 )and ΔmHLA-DR(7 )were defined as the changes in mHLA-DR value on day 3 and day 7 compared to that on day 0. Data were compared between 28-day survivors and non-survivors. Receiver operating characteristic (ROC) curves were plotted to measure the performance and discriminating threshold of ΔmHLA-DR(3), ΔmHLA-DR(7), ΔmHLA-DR(7-3), mHLA-DR(0), mHLA-DR(3 )and mHLA-DR(7 )in predicting mortality of severe sepsis. RESULTS: ROC curve analysis showed that ΔmHLA-DR(3 )and ΔmHLA-DR(7 )were reliable indicators of mortality in severe sepsis. A ΔmHLA-DR(3 )value of 4.8% allowed discrimination between survivors and non-survivors with a sensitivity of 89.0% and a specificity of 93.7%; similarly, ΔmHLA-DR(7 )value of 9% allowed discrimination between survivors and non-survivors with a sensitivity of 85.7% and a specificity of 90.0%. Patients with ΔmHLA-DR(3 )≤4.8% had higher mortality than those with ΔmHLA-DR(3 )> 4.8% (71.4% vs. 2.0%, OR 125.00, 95% CI 13.93 to 1121.67); patients with ΔmHLA-DR(7 )≤9% had higher mortality than those with ΔmHLA-DR(7 )> 9% (52.9% vs. 2.0%, OR 54.00, 95% CI 5.99 to 486.08). The mean change of mHLA-DR significantly increased in the survivor group with the passage of time; from day 0 to day 3 and day 7, changes were 6.45 and 16.90 (P < 0.05), respectively. CONCLUSIONS: The change of mHLA-DR over time may be a reliable predictor for mortality in patients with severe sepsis

Yin-Cold

Traditional Chinese Medicine (TCM) therapies should be tailored according to the different syndrome types. In order to identify the relationship between the TCM Yin-cold (YC) or Yang-heat (YH) syndrome types and the EGFR gene status, we prospectively studied 310 NSCLC patients. TCM YH or YC was diagnosed by three TCM experts. TCM symptoms and signs were entered into a binary cluster analysis. The relationships between the EGFR gene status, YH or YC syndrome types, and classification by cluster analysis were analyzed using the chi-square test and multivariate logistic regression. In the 299 patients who had their EGFR gene tested, 45.24% YC (76/168) and 25.95% YH (34/131) patients had EGFR mutations (p=0.001). Among the 292 patients entered into the cluster analysis, 132 were classified into group A, with signs and symptoms similar to YC, whereas 160 group B patients were similar to YH. In the 281 patients with EGFR tested, 45.67% group A (58/127) and 28.57% group B patients (44/154) had EGFR mutations (p=0.003). The EGFR status was independently correlated with TCM syndrome type and classification by cluster analysis on multivariate logistic regression. NSCLC patients with YC were more likely to have EGFR gene mutations

Chinese Medicine Was Associated with the Epidermal Growth Factor Receptor Gene Status in Non-Small Cell Lung Cancer Patients: Confirmation of a TCM Concept

Traditional Chinese Medicine (TCM) therapies should be tailored according to the different syndrome types. In order to identify the relationship between the TCM Yin-cold (YC) or Yang-heat (YH) syndrome types and the EGFR gene status, we prospectively studied 310 NSCLC patients. TCM YH or YC was diagnosed by three TCM experts. TCM symptoms and signs were entered into a binary cluster analysis. The relationships between the EGFR gene status, YH or YC syndrome types, and classification by cluster analysis were analyzed using the chi-square test and multivariate logistic regression. In the 299 patients who had their EGFR gene tested, 45.24% YC (76/168) and 25.95% YH (34/131) patients had EGFR mutations ( = 0.001). Among the 292 patients entered into the cluster analysis, 132 were classified into group A, with signs and symptoms similar to YC, whereas 160 group B patients were similar to YH. In the 281 patients with EGFR tested, 45.67% group A (58/127) and 28.57% group B patients (44/154) had EGFR mutations ( = 0.003). The EGFR status was independently correlated with TCM syndrome type and classification by cluster analysis on multivariate logistic regression. NSCLC patients with YC were more likely to have EGFR gene mutations

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

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