PubMed Health⌕ Search

Biomedical subjects

Mark Schroeder

Publications and source records attributed to Mark Schroeder.

12 recordsLinked to original sources
PubMed2006

Retargeted oncolytic measles strains entering via the EGFRvIII receptor maintain significant antitumor activity against gliomas with increased tumor specificity.

Among the best-characterized genetic alterations in gliomas is the amplification of the epidermal growth factor receptor (EGFR) gene, present in approximately 40% of glioblastoma multiforme, and frequently associated with the EGFRvIII gene rearrangement. We have previously shown that attenuated vaccine strains of measles virus have potent antitumor activity against gliomas, and identified H protein mutations, which ablate recognition of the natural measles virus receptors CD46 and SLAM. Retargeted recombinant viruses were generated from the measles Edmonston-NSe vaccine strain displaying a single-chain antibody against EGFRvIII at the COOH terminus of H and containing the marker green fluorescent protein (GFP) gene in position 1. Two different H mutants were employed: H(SNS) (V451S, Y481N, and A527S)-CD46 blind, and H(AA) (Y481A and R533A)-CD46 and SLAM blind. MV-GFP virus was used as a positive control. Both EGFRvIII-retargeted viruses had significant antitumor activity against EGFRvIII-expressing glioblastoma multiforme but no cytopathic effect against normal cells. In an orthotopic model of EGFRvIII-expressing GBM39 xenografts, there was comparable therapeutic efficacy between retargeted strains and unmodified MV-GFP and statistically significant prolongation of survival in treated animals compared with the control group (P = 0.001). Formation of syncytia was observed in tumors treated with retargeted viruses, with a surrounding infiltrate consisting of macrophages and natural killer cells. In summary, EGFRvIII-retargeted oncolytic measles virus strains have comparable therapeutic efficacy with the unmodified MV-GFP strain against EGFRvIII-expressing glioma lines and xenografts with improved therapeutic index, a finding with potential translational implications in glioma virotherapy.

Animals↗
PubMed2006

Expanded protein information at SGD: new pages and proteome browser.

The recent explosion in protein data generated from both directed small-scale studies and large-scale proteomics efforts has greatly expanded the quantity of available protein information and has prompted the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) to enhance the depth and accessibility of protein annotations. In particular, we have expanded ongoing efforts to improve the integration of experimental information and sequence-based predictions and have redesigned the protein information web pages. A key feature of this redesign is the development of a GBrowse-derived interactive Proteome Browser customized to improve the visualization of sequence-based protein information. This Proteome Browser has enabled SGD to unify the display of hidden Markov model (HMM) domains, protein family HMMs, motifs, transmembrane regions, signal peptides, hydropathy plots and profile hits using several popular prediction algorithms. In addition, a physico-chemical properties page has been introduced to provide easy access to basic protein information. Improvements to the layout of the Protein Information page and integration of the Proteome Browser will facilitate the ongoing expansion of sequence-specific experimental information captured in SGD, including post-translational modifications and other user-defined annotations. Finally, SGD continues to improve upon the availability of genetic and physical interaction data in an ongoing collaboration with BioGRID by providing direct access to more than 82,000 manually-curated interactions.

Computer Graphics↗
PubMed2006

Genome Snapshot: a new resource at the Saccharomyces Genome Database (SGD) presenting an overview of the Saccharomyces cerevisiae genome.

Sequencing and annotation of the entire Saccharomyces cerevisiae genome has made it possible to gain a genome-wide perspective on yeast genes and gene products. To make this information available on an ongoing basis, the Saccharomyces Genome Database (SGD) (http://www.yeastgenome.org/) has created the Genome Snapshot (http://db.yeastgenome.org/cgi-bin/genomeSnapShot.pl). The Genome Snapshot summarizes the current state of knowledge about the genes and chromosomal features of S.cerevisiae. The information is organized into two categories: (i) number of each type of chromosomal feature annotated in the genome and (ii) number and distribution of genes annotated to Gene Ontology terms. Detailed lists are accessible through SGD's Advanced Search tool (http://db.yeastgenome.org/cgi-bin/search/featureSearch), and all the data presented on this page are available from the SGD ftp site (ftp://ftp.yeastgenome.org/yeast/).

Chromosomes, Fungal↗
PubMed2005

Mega2: data-handling for facilitating genetic linkage and association analyses.

UNLABELLED: Mega2, the manipulation environment for genetic analysis, transparently allows users to process genetic data for family-based or case/control studies accurately and efficiently. In addition to data validation checks, Mega2 provides analysis setup capabilities for a broad choice of commonly used genetic analysis programs, including SimWalk2, ASPEX, GeneHunter, SLINK, SIMULATE, S.A.G.E., SOLAR, Vitesse, Allegro, PREST, PAP, Loki, Merlin and MENDEL. AVAILABILITY: http://watson.hgen.pitt.edu/register/

Chromosome Mapping↗
PubMed2004

Gemcitabine and ISIS-2503 for patients with locally advanced or metastatic pancreatic adenocarcinoma: a North Central Cancer Treatment Group phase II trial.

PURPOSE: Gemcitabine remains the standard therapy for metastatic pancreatic adenocarcinoma (ACA), but has limited activity. ISIS-2503 is an antisense compound directed against H-ras with preclinical activity against pancreatic ACA in tumor models. The combination of ISIS-2503 and gemcitabine has been evaluated in a prior phase I study. METHODS: Patients with metastatic or locally advanced pancreatic ACA not amenable to surgery or local radiation received gemcitabine 1,000 mg/m(2) intravenously over 30 minutes on days 1 and 8 and ISIS-2503 6 mg/kg/d as a continuous intravenous infusion over 14 days of an every-3-weeks cycle. Responses were monitored by radiologic imaging every 6 weeks. RESULTS: Forty-eight eligible patients were enrolled, 43 with metastatic disease. Median follow-up was 12.6 months (range, 2.2 to 16.8 months) for living patients. A median of four cycles of treatment was given (range, 1 to 18 cycles). All patients were assessable for response and toxicity. The 6-month survival percentage was 57.5% (95% CI, 44.9% to 73.5%) and the median survival was 6.6 months. The response rate was 10.4% (one complete response, four partial responses). Clinically significant toxicity was limited except for one fatal pulmonary embolism. CONCLUSION: This study shows a promising response rate to the combination of gemcitabine and ISIS-2503 in patients with pancreatic ACA. The observed 6-month survival rate in these patients met our protocol-defined criteria for success. This regimen is tolerable, but is of unclear benefit. Additional studies evaluating the role of gemcitabine and ISIS-2503 in the treatment of pancreatic ACA should be considered.

Adenocarcinoma↗
PubMed2004

Saccharomyces Genome Database (SGD) provides tools to identify and analyze sequences from Saccharomyces cerevisiae and related sequences from other organisms.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/), a scientific database of the molecular biology and genetics of the yeast Saccharomyces cerevisiae, has recently developed several new resources that allow the comparison and integration of information on a genome-wide scale, enabling the user not only to find detailed information about individual genes, but also to make connections across groups of genes with common features and across different species. The Fungal Alignment Viewer displays alignments of sequences from multiple fungal genomes, while the Sequence Similarity Query tool displays PSI-BLAST alignments of each S.cerevisiae protein with similar proteins from any species whose sequences are contained in the non-redundant (nr) protein data set at NCBI. The Yeast Biochemical Pathways tool integrates groups of genes by their common roles in metabolism and displays the metabolic pathways in a graphical form. Finally, the Find Chromosomal Features search interface provides a versatile tool for querying multiple types of information in SGD.

Amino Acid Sequence↗
PubMed2004

Saccharomyces genome database: underlying principles and organisation.

A scientific database can be a powerful tool for biologists in an era where large-scale genomic analysis, combined with smaller-scale scientific results, provides new insights into the roles of genes and their products in the cell. However, the collection and assimilation of data is, in itself, not enough to make a database useful. The data must be incorporated into the database and presented to the user in an intuitive and biologically significant manner. Most importantly, this presentation must be driven by the user's point of view; that is, from a biological perspective. The success of a scientific database can therefore be measured by the response of its users - statistically, by usage numbers and, in a less quantifiable way, by its relationship with the community it serves and its ability to serve as a model for similar projects. Since its inception ten years ago, the Saccharomyces Genome Database (SGD) has seen a dramatic increase in its usage, has developed and maintained a positive working relationship with the yeast research community, and has served as a template for at least one other database. The success of SGD, as measured by these criteria, is due in large part to philosophies that have guided its mission and organisation since it was established in 1993. This paper aims to detail these philosophies and how they shape the organisation and presentation of the database.

Databases, Nucleic Acid↗
PubMed2003

Saccharomyces Genome Database (SGD) provides biochemical and structural information for budding yeast proteins.

The Saccharomyces Genome Database (SGD: http://genome-www.stanford.edu/Saccharomyces/) has recently developed new resources to provide more complete information about proteins from the budding yeast Saccharomyces cerevisiae. The PDB Homologs page provides structural information from the Protein Data Bank (PDB) about yeast proteins and/or their homologs. SGD has also created a resource that utilizes the eMOTIF database for motif information about a given protein. A third new resource is the Protein Information page, which contains protein physical and chemical properties, such as molecular weight and hydropathicity scores, predicted from the translated ORF sequence.

Amino Acid Motifs↗
PubMed2003

The Stanford Microarray Database: data access and quality assessment tools.

The Stanford Microarray Database (SMD; http://genome-www.stanford.edu/microarray/) serves as a microarray research database for Stanford investigators and their collaborators. In addition, SMD functions as a resource for the entire scientific community, by making freely available all of its source code and providing full public access to data published by SMD users, along with many tools to explore and analyze those data. SMD currently provides public access to data from 3500 microarrays, including data from 85 publications, and this total is increasing rapidly. In this article, we describe some of SMD's newer tools for accessing public data, assessing data quality and for data analysis.

Animals↗
PubMed2003

Decay rates of human mRNAs: correlation with functional characteristics and sequence attributes.

Although mRNA decay rates are a key determinant of the steady-state concentration for any given mRNA species, relatively little is known, on a population level, about what factors influence turnover rates and how these rates are integrated into cellular decisions. We decided to measure mRNA decay rates in two human cell lines with high-density oligonucleotide arrays that enable the measurement of decay rates simultaneously for thousands of mRNA species. Using existing annotation and the Gene Ontology hierarchy of biological processes, we assign mRNAs to functional classes at various levels of resolution and compare the decay rate statistics between these classes. The results show statistically significant organizational principles in the variation of decay rates among functional classes. In particular, transcription factor mRNAs have increased average decay rates compared with other transcripts and are enriched in "fast-decaying" mRNAs with half-lives <2 h. In contrast, we find that mRNAs for biosynthetic proteins have decreased average decay rates and are deficient in fast-decaying mRNAs. Our analysis of data from a previously published study of Saccharomyces cerevisiae mRNA decay shows the same functional organization of decay rates, implying that it is a general organizational scheme for eukaryotes. Additionally, we investigated the dependence of decay rates on sequence composition, that is, the presence or absence of short mRNA motifs in various regions of the mRNA transcript. Our analysis recovers the positive correlation of mRNA decay with known AU-rich mRNA motifs, but we also uncover further short mRNA motifs that show statistically significant correlation with decay. However, we also note that none of these motifs are strong predictors of mRNA decay rate, indicating that the regulation of mRNA decay is more complex and may involve the cooperative binding of several RNA-binding proteins at different sites.

Base Composition↗
PubMed2002

Saccharomyces Genome Database (SGD) provides secondary gene annotation using the Gene Ontology (GO).

The Saccharomyces Genome Database (SGD) resources, ranging from genetic and physical maps to genome-wide analysis tools, reflect the scientific progress in identifying genes and their functions over the last decade. As emphasis shifts from identification of the genes to identification of the role of their gene products in the cell, SGD seeks to provide its users with annotations that will allow relationships to be made between gene products, both within Saccharomyces cerevisiae and across species. To this end, SGD is annotating genes to the Gene Ontology (GO), a structured representation of biological knowledge that can be shared across species. The GO consists of three separate ontologies describing molecular function, biological process and cellular component. The goal is to use published information to associate each characterized S.cerevisiae gene product with one or more GO terms from each of the three ontologies. To be useful, this must be done in a manner that allows accurate associations based on experimental evidence, modifications to GO when necessary, and careful documentation of the annotations through evidence codes for given citations. Reaching this goal is an ongoing process at SGD. For information on the current progress of GO annotations at SGD and other participating databases, as well as a description of each of the three ontologies, please visit the GO Consortium page at http://www.geneontology.org. SGD gene associations to GO can be found by visiting our site at http://genome-www.stanford.edu/Saccharomyces/.

Animals↗