Ambiguity as Grasp: The Reworking of Sense

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111788/1/jccm12080.pd

High-dose Chemotherapy and Autologous Stem Cell Rescue in Patients with High-risk Stage 3 Neuroblastoma: 10-Year Experience at a Single Center

High-dose chemotherapy and autologous stem cell rescue (HDCT/ASCR) was applied to improve the prognosis of patients with high-risk stage 3 neuroblastoma. From January 1997 to December 2006, 28 patients were newly diagnosed as stage 3 neuroblastoma. Nine of 11 patients with N-myc amplification and 5 of 17 patients without N-myc amplification (poor response in 2 patients, persistent residual tumor in 2 and relapse in 1) underwent single or tandem HDCT/ASCR. Patients without high-risk features received conventional treatment modalities only. While 8 of 9 patients underwent single HDCT/ASCR and the remaining one patient underwent tandem HDCT/ASCR during the early study period, all 5 patients underwent tandem HDCT/ASCR during the late period. Toxicities associated with HDCT/ASCR were tolerable and there was no treatment-related mortality. While the tumor relapsed in two of eight patients in single HDCT/ASCR group, all six patients in tandem HDCT/ASCR group remained relapse free. The 5-yr event-free survival (EFS) from diagnosis, in patients with N-myc amplification, was 71.6±14.0%. In addition, 12 of 14 patients who underwent HDCT/ASCR remained event free resulting in an 85.1±9.7% 5-yr EFS after the first HDCT/ASCR. The present study demonstrates that HDCT/ASCR may improve the survival of patients with high-risk stage 3 neuroblastoma

Canonical A-to-I and C-to-U RNA Editing Is Enriched at 3′UTRs and microRNA Target Sites in Multiple Mouse Tissues

RNA editing is a process that modifies RNA nucleotides and changes the efficiency and fidelity of the central dogma. Enzymes that catalyze RNA editing are required for life, and defects in RNA editing are associated with many diseases. Recent advances in sequencing have enabled the genome-wide identification of RNA editing sites in mammalian transcriptomes. Here, we demonstrate that canonical RNA editing (A-to-I and C-to-U) occurs in liver, white adipose, and bone tissues of the laboratory mouse, and we show that apparent non-canonical editing (all other possible base substitutions) is an artifact of current high-throughput sequencing technology. Further, we report that high-confidence canonical RNA editing sites can cause non-synonymous amino acid changes and are significantly enriched in 3′ UTRs, specifically at microRNA target sites, suggesting both regulatory and functional consequences for RNA editing

Exploiting evolutionary steering to induce collateral drug sensitivity in cancer

Drug resistance mediated by clonal evolution is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at a cost of decreased fecundity or increased sensitivity to another drug. These evolutionary trade-offs can be exploited using 'evolutionary steering' to control the tumour population and delay resistance. However, recapitulating cancer evolutionary dynamics experimentally remains challenging. Here, we present an approach for evolutionary steering based on a combination of single-cell barcoding, large populations of 108-109 cells grown without re-plating, longitudinal non-destructive monitoring of cancer clones, and mathematical modelling of tumour evolution. We demonstrate evolutionary steering in a lung cancer model, showing that it shifts the clonal composition of the tumour in our favour, leading to collateral sensitivity and proliferative costs. Genomic profiling revealed some of the mechanisms that drive evolved sensitivity. This approach allows modelling evolutionary steering strategies that can potentially control treatment resistance

Cancer stem cells display extremely large evolvability alternating plastic and rigid networks as a potential mechanism Network models, novel therapeutic target strategies, and the contributions of hypoxia, inflammation and cellular senescence

Cancer is increasingly perceived as a systems-level, network phenomenon. The major trend of malignant transformation can be described as a two-phase process, where an initial increase of network plasticity is followed by a decrease of plasticity at late stages of tumor development. The fluctuating intensity of stress factors, like hypoxia, inflammation and the either cooperative or hostile interactions of tumor inter-cellular networks, all increase the adaptation potential of cancer cells. This may lead to the bypass of cellular senescence, and to the development of cancer stem cells. We propose that the central tenet of cancer stem cell definition lies exactly in the indefinability of cancer stem cells. Actual properties of cancer stem cells depend on the individual "stress-history" of the given tumor. Cancer stem cells are characterized by an extremely large evolvability (i.e. a capacity to generate heritable phenotypic variation), which corresponds well with the defining hallmarks of cancer stem cells: the possession of the capacity to self-renew and to repeatedly re-build the heterogeneous lineages of cancer cells that comprise a tumor in new environments. Cancer stem cells represent a cell population, which is adapted to adapt. We argue that the high evolvability of cancer stem cells is helped by their repeated transitions between plastic (proliferative, symmetrically dividing) and rigid (quiescent, asymmetrically dividing, often more invasive) phenotypes having plastic and rigid networks. Thus, cancer stem cells reverse and replay cancer development multiple times. We describe network models potentially explaining cancer stem cell-like behavior. Finally, we propose novel strategies including combination therapies and multi-target drugs to overcome the Nietzschean dilemma of cancer stem cell targeting: "what does not kill me makes me stronger"

Maps of Open Chromatin Guide the Functional Follow-Up of Genome-Wide Association Signals: Application to Hematological Traits

Turning genetic discoveries identified in genome-wide association (GWA) studies into biological mechanisms is an important challenge in human genetics. Many GWA signals map outside exons, suggesting that the associated variants may lie within regulatory regions. We applied the formaldehyde-assisted isolation of regulatory elements (FAIRE) method in a megakaryocytic and an erythroblastoid cell line to map active regulatory elements at known loci associated with hematological quantitative traits, coronary artery disease, and myocardial infarction. We showed that the two cell types exhibit distinct patterns of open chromatin and that cell-specific open chromatin can guide the finding of functional variants. We identified an open chromatin region at chromosome 7q22.3 in megakaryocytes but not erythroblasts, which harbors the common non-coding sequence variant rs342293 known to be associated with platelet volume and function. Resequencing of this open chromatin region in 643 individuals provided strong evidence that rs342293 is the only putative causative variant in this region. We demonstrated that the C- and G-alleles differentially bind the transcription factor EVI1 affecting PIK3CG gene expression in platelets and macrophages. A protein–protein interaction network including up- and down-regulated genes in Pik3cg knockout mice indicated that PIK3CG is associated with gene pathways with an established role in platelet membrane biogenesis and thrombus formation. Thus, rs342293 is the functional common variant at this locus; to the best of our knowledge this is the first such variant to be elucidated among the known platelet quantitative trait loci (QTLs). Our data suggested a molecular mechanism by which a non-coding GWA index SNP modulates platelet phenotype

A reporting format for leaf-level gas exchange data and metadata

Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system