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Biomedical subjects

Pascal Hingamp

Publications and source records attributed to Pascal Hingamp.

9 recordsLinked to original sources
PubMed2006

MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies.

BACKGROUND: High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option.GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. RESULTS: MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. CONCLUSION: MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and industry service providers alike.

Cloning, Molecular↗
PubMed2005

Mice lacking the UBC4-testis gene have a delay in postnatal testis development but normal spermatogenesis and fertility.

Activation of ubiquitination occurs during spermatogenesis and is dependent on the induction of isoforms of the UBC4 family of ubiquitin-conjugating enzymes. The UBC4-testis isoform is testis specific, is induced in round spermatids, and demonstrates biochemical functions distinct from a ubiquitously expressed isoform UBC4-1. To explore further the function of UBC4-testis, mice bearing inactivation of this gene were produced. Homozygous (-/-) mice showed normal body growth and fertility. Although testis weight and morphology were normal in testes from adult mice, examination of young mice during the first wave of spermatogenesis revealed that testes were approximately 10% smaller in weight at 40 and 45 days of age but had become normal at 65 days of age. Overall protein content, levels of ubiquitinated proteins, and ubiquitin-conjugating activity did not differ between wild-type and homozygous (-/-) mice. Spermatid number, as well as the motility of spermatozoa isolated from the epididymis, was also normal in homozygous (-/-) mice. To determine whether the germ cells lacking UBC4-testis might be more sensitive to stress, testes from wild-type and knockout mice were exposed to heat stress by implantation in the abdominal cavity. Testes from both strains of mice showed similar rates of degeneration in response to heat. The lack of an obvious phenotype did not appear to be due to induction of other UBC4 isoforms, as shown by two-dimensional gel immunoblotting. Our data indicate that UBC4-testis plays a role in early maturation of the testis and suggest that the many UBC4 isoforms have mixed redundant and specific functions.

Animals↗
PubMed2003

DNA microarray data and contextual analysis of correlation graphs.

BACKGROUND: DNA microarrays are used to produce large sets of expression measurements from which specific biological information is sought. Their analysis requires efficient and reliable algorithms for dimensional reduction, classification and annotation. RESULTS: We study networks of co-expressed genes obtained from DNA microarray experiments. The mathematical concept of curvature on graphs is used to group genes or samples into clusters to which relevant gene or sample annotations are automatically assigned. Application to publicly available yeast and human lymphoma data demonstrates the reliability of the method in spite of its simplicity, especially with respect to the small number of parameters involved. CONCLUSIONS: We provide a method for automatically determining relevant gene clusters among the many genes monitored with microarrays. The automatic annotations and the graphical interface improve the readability of the data. A C++ implementation, called Trixy, is available from http://tagc.univ-mrs.fr/bioinformatics/trixy.html.

Algorithms↗
PubMed2003

Breast cancer revisited using DNA array-based gene expression profiling.

Breast cancer is a complex genetic disease characterized by the accumulation of multiple molecular alterations. The resulting clinical heterogeneity makes current diagnostic and therapeutic strategies less than perfectly adapted to each patient. Pathological and clinical factors are insufficient to capture the complex cascade of events that drive the clinical behavior of tumors. High-throughput molecular technologies provide novel tools to tackle this complexity. In particular, DNA arrays allow the simultaneous and quantitative analysis of the mRNA expression levels of thousands of genes in a single assay. Potential applications are multiple in the cancer field and the first research results are promising; comprehensive gene expression profiles of breast tumors are providing insights into mammary oncogenesis and are revealing new tumor subgroups previously indistinguishable. Significant advances will be the identification of new diagnostic, prognostic and predictive biomarkers as well as the discovery of new potential therapeutic targets. This review presents recent applications of DNA arrays in breast cancer research and discusses some issues to address in the near future to allow the technology to reach its full potential.

Breast Neoplasms↗
PubMed2002

Prognosis of breast cancer and gene expression profiling using DNA arrays.

Breast cancer is a complex genetic disease characterized by the accumulation of multiple molecular alterations. The resulting clinical heterogeneity makes current therapeutic strategies-based on clinicopathlogical factors-less than perfectly adapted to each patient. Today, DNA arrays, by allowing the simultaneous and quantitative analysis of the mRNA expression levels of thousands of genes in a single assay, provide novel tools to tackle this complexity. Potential applications are multiple in the cancer field and the first research results are promising. Using home-made DNA arrays in an approach easily compatible with academic research-nylon support and radioactive detection-we identified a predictor set of 23 genes whose expression patterns differentiated two groups of breast cancer patients with different survival after adjuvant chemotherapy. We then validated and further extended these results in a larger, independent and homogeneous series of poor prognosis primary breast cancers treated with adjuvant anthracyclin-based chemotherapy. We confirmed the prognostic classification provided by the 23-gene set predictor. We then improved the predictor set and refined the classification by sorting the tumors into three classes with significantly different long-term survival. These results show the potential of the technology with an accessible approach for academic research teams. We also showed that nylon DNA arrays with radioactive detection are associated with excellent sensitivity, an advantage in clinical situations where the amount of available material is limited.

Breast Neoplasms↗