Showing papers by "Vladimir Brusic published in 2000"

Melan-A/MART-151–73 represents an immunogenic HLA-DR4-restricted epitope recognized by melanoma-reactive CD4+ T cells

Abstract: The human Melan-A/MART-1 gene encodes an HLA-A2-restricted peptide epitope recognized by melanoma-reactive CD8+ cytotoxic T lymphocytes. Here we report that this gene also encodes at least one HLA-DR4-presented peptide recognized by CD4+ T cells. The Melan-A/MART-151–73 peptide was able to induce the in vitro expansion of specific CD4+ T cells derived from normal DR4+ donors or from DR4+ patients with melanoma when pulsed onto autologous dendritic cells. CD4+ responder T cells specifically produced IFN-γ in response to, and also lysed, T2.DR4 cells pulsed with the Melan-A/MART-151–73 peptide and DR4+ melanoma target cells naturally expressing the Melan-A/MART-1 gene product. Interestingly, CD4+ T cell immunoreactivity against the Melan-A/MART-151–73 peptide typically coexisted with a high frequency of anti-Melan-A/MART-127–35 reactive CD8+ T cells in freshly isolated blood harvested from HLA-A2+/DR4+ patients with melanoma. Taken together, these data support the use of this Melan-A/MART-1 DR4-restricted melanoma epitope in future immunotherapeutic trials designed to generate, augment, and quantitate specific CD4+ T cell responses against melanoma in vivo.

NY-ESO-1 Encodes DRB1*0401-restricted Epitopes Recognized by Melanoma-reactive CD4+ T Cells

Abstract: The NY-ESO-1 gene is expressed by a range of human tumors and encodes HLA-A2-restricted melanoma peptides recognized by CD8+ CTLs. Here we report that the NY-ESO-1 gene also encodes two overlapping, but non-cross-reactive, HLA-DRB1*0401-presented peptides that are recognized by CD4+ T cells. The NY-ESO-1(119-143) peptide was able to induce specific CD4+ T cells in vitro from both an HLA-DRB1*0401+ normal donor and an HLA-DRB1*0401+ patient with melanoma. Bulk and cloned CD4+ T cells produced IFN-gamma specifically in response to, and also lysed, T2.DR4 cells pulsed with peptide NY-ESO-1(119-143) and the autologous tumor cell line, but not a DRB1*0401+ melanoma cell line that does not express NY-ESO-1. Interestingly, the NY-ESO119-143 peptide contains two overlapping putative "core" epitopes recognized by non-cross-reactive anti-NY-ESO-1(119-143) CD4+ T-cell clones. Taken together, these data support the use of this novel DR4-restricted tumor peptide, NY-ESO-1(119-143), or its two "sub-epitopes" in immunotherapeutic trials designed to generate or enhance specific CD4+ T-cell responses against tumors expressing NY-ESO-1 in vivo.

FIMM, a database of functional molecular immunology

Abstract: FIMM database (http://sdmckrdlorgsg:8080/fimm ) contains data relevant to functional molecular immunology, focusing on cellular immunology It contains fully referenced data on protein antigens, major histocompatibility complex (MHC) molecules, MHC-associated peptides and relevant disease associations FIMM has a set of search tools for extraction of information and results are presented as lists or as reports

Data warehousing in molecular biology.

Abstract: In the business and healthcare sectors data warehousing has provided effective solutions for information usage and knowledge discovery from databases. However, data warehousing applications in the biological research and development (R&D) sector are lagging far behind. The fuzziness and complexity of biological data represent a major challenge in data warehousing for molecular biology. By combining experiences in other domains with our findings from building a model database, we have defined the requirements for data warehousing in molecular biology.

A system,method and interface for building biological databases using templates

Abstract: With the above and other objects in mind, the present invention provides a general system, method, and interfaces for building and integrating databases based on combining template modules using multiple dimensions, or views, to data and templates for database tools. The method may be applicable to domains characterised by complex data where multiple different views to data need to be combined for extraction of information. An example application is from bioinformatics, where multiple databases using this system and method may be built. The information extraction and data management is based on using templates, each of which is designed for a specific purpose.

Computational Design of Proteinous Drug Employing Hidden Markov Model

Abstract: Major histocompatibility complex (MHC) molecules bind antigenic peptides and present them forrecognitionbytheimmunesystem. MHCmoleculesplayanessentialrolein theinitiationandreg-ulationofTcellmediatedimmuneresponses. PeptidesthatbindMHCrepresentpromisingtargetsforthedevelopmentofvaccinesandtherapiesforautoimmunediseasesandcancer. AtypicalhumanMHCclassII(HLA-DR)bindingpeptideis9-35aminoacidlong. Ithasa9-residuebindingcoreandflanking sequences that protrude from the HLA peptide-binding groove. Prediction methods usingweightmatrices,artificialneuralnetworks(ANN),orfuzzyneuralnetworkswerereportedpreviously[1,2,3]. Allofthesemethodsrequiretheidentificationofpeptidebindingcoresformodelbuilding.The peptide alignment step is critical because it is computationally difficult and in some cases anincorrectregionofapeptidemaybeassignedasabindingcore. Inthisstudy,wedescribeahiddenMarkovmodel(HMM)-basedmethodforpredictionofHLA-DR-bindingpeptides. Thismethoddoesnotrequirethealignmentstepformodelbuilding.