Hypofractionated Stereotactic Ablative Radiotherapy for Recurrent or Oligometastatic Tumours in Children and Young Adults

AIMS Cancer remains a leading cause of death in children and adolescents in the developed world. Despite advances in oncological management, rates of primary treatment failure remain significant. Radiation of recurrent or metastatic disease improves survival in adults but there is little data to support clinical decision making in the paediatric/teenage and young adult population. Materials And Methods We present a retrospective case series of 14 patients treated with stereotactic ablative body radiotherapy or stereotactic radiosurgery at The Royal Marsden Hospital from September 2011 to December 2015. Eligible patients were aged <25 years, with Lansky/Karnofsky performance status ≥60 with confirmed relapsed or metastatic tumour in fewer than three sites. Follow-up was in accordance with standard clinical care and included regular outpatient review and radiological surveillance. Local control, progression-free survival and overall survival are presented. RESULTS Data for 14 patients with 18 treated lesions were included. The median patient age was 15 years (range 5–20 years). Nine patients were treated for local recurrence and five for metastatic lesions. All patients had already undergone multiple previous treatments. Eleven patients had undergone previous radiotherapy. The median interval between the completion of initial radiotherapy and reirradiation was 29.0 months (range 0.2–49.5 months). The median follow-up was 3.4 years (range 0.28–6.4 years). The 1-year local control rate was 78.6% and the 2-year local control rate was 57.1%. Overall median survival was 58.4 months (95% confidence interval 33.8–82.9 months). Cumulative biologically effective doses (BED) over 200 Gy were associated with late toxicity (P = 0.04). CONCLUSION Radical doses of short-course hypofractionated radiotherapy can achieve excellent local control and may contribute to the prolongation of overall survival. There is a need for prospective trials exploring the use of ablative radiotherapy in metastatic disease in paediatric/teenage and young adult patients in order to establish safe and effective treatment schedules

Optoacoustic solitons in Bragg gratings

Optical gap solitons, which exist due to a balance of nonlinearity and dispersion due to a Bragg grating, can couple to acoustic waves through electrostriction. This gives rise to a new species of ``gap-acoustic'' solitons (GASs), for which we find exact analytic solutions. The GAS consists of an optical pulse similar to the optical gap soliton, dressed by an accompanying phonon pulse. Close to the speed of sound, the phonon component is large. In subsonic (supersonic) solitons, the phonon pulse is a positive (negative) density variation. Coupling to the acoustic field damps the solitons' oscillatory instability, and gives rise to a distinct instability for supersonic solitons, which may make the GAS decelerate and change direction, ultimately making the soliton subsonic.Comment: 5 pages, 3 figure

MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

Abstract Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw.http://deepblue.lib.umich.edu/bitstream/2027.42/78256/1/1471-2105-11-504.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/2/1471-2105-11-504-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/3/1471-2105-11-504-S2.ZIPhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/4/1471-2105-11-504.pdfPeer Reviewe

Tandem application of C-C bond-forming reactions with reductive ozonolysis

Several variants of reductive ozonolysis, defined here as the in situ generation of aldehydes or ketones during ozonolytic cleavage of alkenes, are demonstrated to work effectively in tandem with a number of C-C bond-forming reactions. For reactions involving basic nucleophiles (1,2- addition of Grignard reagents, Wittig or Horner-Emmons olefinations, and directed Aldol reactions of lithium enolates) the one-pot process offers a rapid and high-yielding alternative to traditional two-step protocols

Predicting cell types and genetic variations contributing to disease by combining GWAS and epigenetic data

Genome-wide association studies (GWASs) identify single nucleotide polymorphisms (SNPs) that are enriched in individuals suffering from a given disease. Most disease-associated SNPs fall into non-coding regions, so that it is not straightforward to infer phenotype or function; moreover, many SNPs are in tight genetic linkage, so that a SNP identified as associated with a particular disease may not itself be causal, but rather signify the presence of a linked SNP that is functionally relevant to disease pathogenesis. Here, we present an analysis method that takes advantage of the recent rapid accumulation of epigenomics data to address these problems for some SNPs. Using asthma as a prototypic example; we show that non-coding disease-associated SNPs are enriched in genomic regions that function as regulators of transcription, such as enhancers and promoters. Identifying enhancers based on the presence of the histone modification marks such as H3K4me1 in different cell types, we show that the location of enhancers is highly cell-type specific. We use these findings to predict which SNPs are likely to be directly contributing to disease based on their presence in regulatory regions, and in which cell types their effect is expected to be detectable. Moreover, we can also predict which cell types contribute to a disease based on overlap of the disease-associated SNPs with the locations of enhancers present in a given cell type. Finally, we suggest that it will be possible to re-analyze GWAS studies with much higher power by limiting the SNPs considered to those in coding or regulatory regions of cell types relevant to a given disease

Severe Acute Respiratory Syndrome–associated Coronavirus Infection

Whether severe acute respiratory syndrome–associated coronavirus (SARS-CoV) infection can be asymptomatic is unclear. We examined the seroprevalence of SARS-CoV among 674 healthcare workers from a hospital in which a SARS outbreak had occurred. A total of 353 (52%) experienced mild self-limiting illnesses, and 321 (48%) were asymptomatic throughout the course of these observations. None of these healthcare workers had antibody to SARS CoV, indicating that subclinical or mild infection attributable to SARS CoV in adults is rare

Unveiling the complexity of the maize transcriptome by single-molecule long-read sequencing

Zea mays is an important genetic model for elucidating transcriptional networks. Uncertainties about the complete structure of mRNA transcripts limit the progress of research in this system. Here, using single-molecule sequencing technology, we produce 111,151 transcripts from 6 tissues capturing approximately 70% of the genes annotated in maize RefGen_v3 genome. A large proportion of transcripts (57%) represent novel, sometimes tissue-specific, isoforms of known genes and 3% correspond to novel gene loci. In other cases, the identified transcripts have improved existing gene models. Averaging across all six tissues, 90% of the splice junctions are supported by short reads from matched tissues. In addition, we identified a large number of novel long non-coding RNAs and fusion transcripts and found that DNA methylation plays an important role in generating various isoforms. Our results show that characterization of the maize B73 transcriptome is far from complete, and that maize gene expression is more complex than previously thought

CMS: A web-based system for visualization and analysis of genome-wide methylation data of human cancers

DNA methylation of promoter CpG islands is associated with gene suppression, and its unique genome-wide profiles have been linked to tumor progression. Coupled with high-throughput sequencing technologies, it can now efficiently determine genome-wide methylation profiles in cancer cells. Also, experimental and computational technologies make it possible to find the functional relationship between cancer-specific methylation patterns and their clinicopathological parameters.Cancer methylome system (CMS) is a web-based database application designed for the visualization, comparison and statistical analysis of human cancer-specific DNA methylation. Methylation intensities were obtained from MBDCap-sequencing, pre-processed and stored in the database. 191 patient samples (169 tumor and 22 normal specimen) and 41 breast cancer cell-lines are deposited in the database, comprising about 6.6 billion uniquely mapped sequence reads. This provides comprehensive and genome-wide epigenetic portraits of human breast cancer and endometrial cancer to date. Two views are proposed for users to better understand methylation structure at the genomic level or systemic methylation alteration at the gene level. In addition, a variety of annotation tracks are provided to cover genomic information. CMS includes important analytic functions for interpretation of methylation data, such as the detection of differentially methylated regions, statistical calculation of global methylation intensities, multiple gene sets of biologically significant categories, interactivity with UCSC via custom-track data. We also present examples of discoveries utilizing the framework.CMS provides visualization and analytic functions for cancer methylome datasets. A comprehensive collection of datasets, a variety of embedded analytic functions and extensive applications with biological and translational significance make this system powerful and unique in cancer methylation research. CMS is freely accessible at: http://cbbiweb.uthscsa.edu/KMethylomes/