Recent developments in StemBase: a tool to study gene expression in human and murine stem cells

<p>Abstract</p> <p>Background</p> <p>Currently one of the largest online repositories for human and mouse stem cell gene expression data, StemBase was first designed as a simple web-interface to DNA microarray data generated by the Canadian Stem Cell Network to facilitate the discovery of gene functions relevant to stem cell control and differentiation.</p> <p>Findings</p> <p>Since its creation, StemBase has grown in both size and scope into a system with analysis tools that examine either the whole database at once, or slices of data, based on tissue type, cell type or gene of interest. As of September 1, 2008, StemBase contains gene expression data (microarray and Serial Analysis of Gene Expression) from 210 stem cell samples in 60 different experiments.</p> <p>Conclusion</p> <p>StemBase can be used to study gene expression in human and murine stem cells and is available at <url>http://www.stembase.ca</url>.</p

MedlineRanker: flexible ranking of biomedical literature

The biomedical literature is represented by millions of abstracts available in the Medline database. These abstracts can be queried with the PubMed interface, which provides a keyword-based Boolean search engine. This approach shows limitations in the retrieval of abstracts related to very specific topics, as it is difficult for a non-expert user to find all of the most relevant keywords related to a biomedical topic. Additionally, when searching for more general topics, the same approach may return hundreds of unranked references. To address these issues, text mining tools have been developed to help scientists focus on relevant abstracts. We have implemented the MedlineRanker webserver, which allows a flexible ranking of Medline for a topic of interest without expert knowledge. Given some abstracts related to a topic, the program deduces automatically the most discriminative words in comparison to a random selection. These words are used to score other abstracts, including those from not yet annotated recent publications, which can be then ranked by relevance. We show that our tool can be highly accurate and that it is able to process millions of abstracts in a practical amount of time. MedlineRanker is free for use and is available at http://cbdm.mdc-berlin.de/tools/medlineranker

Detection of Alpha-Rod Protein Repeats Using a Neural Network and Application to Huntingtin

A growing number of solved protein structures display an elongated structural domain, denoted here as alpha-rod, composed of stacked pairs of anti-parallel alpha-helices. Alpha-rods are flexible and expose a large surface, which makes them suitable for protein interaction. Although most likely originating by tandem duplication of a two-helix unit, their detection using sequence similarity between repeats is poor. Here, we show that alpha-rod repeats can be detected using a neural network. The network detects more repeats than are identified by domain databases using multiple profiles, with a low level of false positives (<10%). We identify alpha-rod repeats in approximately 0.4% of proteins in eukaryotic genomes. We then investigate the results for all human proteins, identifying alpha-rod repeats for the first time in six protein families, including proteins STAG1-3, SERAC1, and PSMD1-2 & 5. We also characterize a short version of these repeats in eight protein families of Archaeal, Bacterial, and Fungal species. Finally, we demonstrate the utility of these predictions in directing experimental work to demarcate three alpha-rods in huntingtin, a protein mutated in Huntington's disease. Using yeast two hybrid analysis and an immunoprecipitation technique, we show that the huntingtin fragments containing alpha-rods associate with each other. This is the first definition of domains in huntingtin and the first validation of predicted interactions between fragments of huntingtin, which sets up directions toward functional characterization of this protein. An implementation of the repeat detection algorithm is available as a Web server with a simple graphical output: http://www.ogic.ca/projects/ard. This can be further visualized using BiasViz, a graphic tool for representation of multiple sequence alignments

Genomic basis for RNA alterations in cancer

Transcript alterations often result from somatic changes in cancer genomes. Various forms of RNA alterations have been described in cancer, including overexpression, altered splicing and gene fusions; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer

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

Genomic basis for RNA alterations in cancer.

Transcript alterations often result from somatic changes in cancer genomes1. Various forms of RNA alterations have been described in cancer, including overexpression2, altered splicing3 and gene fusions4; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)5. Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer

Concerted down-regulation of immune-system related genes predicts metastasis in colorectal carcinoma

BACKGROUND: This study aimed at the identification of prognostic gene expression markers in early primary colorectal carcinomas without metastasis at the time point of surgery by analyzing genome-wide gene expression profiles using oligonucleotide microarrays. METHODS: Cryo-conserved tumor specimens from 45 patients with early colorectal cancers were examined, with the majority of them being UICC stage II or earlier and with a follow-up time of 41-115 months. Gene expression profiling was performed using Whole Human Genome 4x44K Oligonucleotide Microarrays. Validation of microarray data was performed on five of the genes in a smaller cohort. RESULTS: Using a novel algorithm based on the recursive application of support vector machines (SVMs), we selected a signature of 44 probes that discriminated between patients developing later metastasis and patients with a good prognosis. Interestingly, almost half of the genes was related to the patients' immune response and showed reduced expression in the metastatic cases. CONCLUSIONS: Whereas up to now gene signatures containing genes with various biological functions have been described for prediction of metastasis in CRC, in this study metastasis could be well predicted by a set of gene expression markers consisting exclusively of genes related to the MHC class II complex involved in immune response. Thus, our data emphasize that the proper function of a comprehensive network of immune response genes is of vital importance for the survival of colorectal cancer patients

Current Wildland Fire Patterns and Challenges in Europe: A Synthesis of National Perspectives

Changes in climate, land use, and land management impact the occurrence and severity of wildland fires in many parts of the world. This is particularly evident in Europe, where ongoing changes in land use have strongly modified fire patterns over the last decades. Although satellite data by the European Forest Fire Information System provide large-scale wildland fire statistics across European countries, there is still a crucial need to collect and summarize in-depth local analysis and understanding of the wildland fire condition and associated challenges across Europe. This article aims to provide a general overview of the current wildland fire patterns and challenges as perceived by national representatives, supplemented by national fire statistics (2009–2018) across Europe. For each of the 31 countries included, we present a perspective authored by scientists or practitioners from each respective country, representing a wide range of disciplines and cultural backgrounds. The authors were selected from members of the COST Action “Fire and the Earth System: Science & Society” funded by the European Commission with the aim to share knowledge and improve communication about wildland fire. Where relevant, a brief overview of key studies, particular wildland fire challenges a country is facing, and an overview of notable recent fire events are also presented. Key perceived challenges included (1) the lack of consistent and detailed records for wildland fire events, within and across countries, (2) an increase in wildland fires that pose a risk to properties and human life due to high population densities and sprawl into forested regions, and (3) the view that, irrespective of changes in management, climate change is likely to increase the frequency and impact of wildland fires in the coming decades. Addressing challenge (1) will not only be valuable in advancing national and pan-European wildland fire management strategies, but also in evaluating perceptions (2) and (3) against more robust quantitative evidence

A local human Vδ1 T cell population is associated with survival in nonsmall-cell lung cancer

Murine tissues harbor signature γδ T cell compartments with profound yet differential impacts on carcinogenesis. Conversely, human tissue-resident γδ cells are less well defined. In the present study, we show that human lung tissues harbor a resident Vδ1 γδ T cell population. Moreover, we demonstrate that Vδ1 T cells with resident memory and effector memory phenotypes were enriched in lung tumors compared with nontumor lung tissues. Intratumoral Vδ1 T cells possessed stem-like features and were skewed toward cytolysis and helper T cell type 1 function, akin to intratumoral natural killer and CD8+ T cells considered beneficial to the patient. Indeed, ongoing remission post-surgery was significantly associated with the numbers of CD45RA−CD27− effector memory Vδ1 T cells in tumors and, most strikingly, with the numbers of CD103+ tissue-resident Vδ1 T cells in nonmalignant lung tissues. Our findings offer basic insights into human body surface immunology that collectively support integrating Vδ1 T cell biology into immunotherapeutic strategies for nonsmall cell lung cancer