[DNA arrays: technological aspects and applications]. / Puces à ADN: technologie et applications.

The Human Genome Project has allowed considerable progress in the construction of physical and genetic maps and the identification of genes involved in human sicknesses. The accelerated accumulation of biological information and knowledge is due in large part to the sequencing projects of other organisms, which in fact paved the way for the Human Genome Project. In parallel, recently developed techniques which take advantage of genomic sequences allow large scale molecular analyses resulting in the functional annotation of many of the proteins represented by these genes. This is the goal of functional genomics. These progresses are at the origin of the present revolution in biomedical research. DNA microarrays are playing a dominant role compared to the other developing technologies since they are relatively easy to make and use and are applicable to numerous scientific inquiries. They allow the simultaneous analysis of several thousands of genes in biological samples from sick or healthy tissues, at the genome or transcriptome level. The data obtained is expected to result in major advances in the health sciences. In addition to an improved understanding of the complex molecular interaction networks of healthy cells and tissues, a more precise genetic characterization of the molecular mechanisms involved in pathology should result in the identification of new therapeutic targets and the development of new medicines. The genetic profiles thus obtained should also permit the definition of new pathologic subclasses not recognizable by traditional clinical factors, as well as new markers for susceptibility to certain illnesses, and new prognostic markers or methods of predicting responses to treatment. In this article, we present the different approaches and potential applications of DNA microarray technology, in particular as applied to cancer research.

Gene expression profiling of primary breast carcinomas using arrays of candidate genes.

Breast cancer is characterized by an important histoclinical heterogeneity that currently hampers the selection of the most appropriate treatment for each case. This problem could be solved by the identification of new parameters that better predict the natural history of the disease and its sensitivity to treatment. A large-scale molecular characterization of breast cancer could help in this context. Using cDNA arrays, we studied the quantitative mRNA expression levels of 176 candidate genes in 34 primary breast carcinomas along three directions: comparison of tumor samples, correlations of molecular data with conventional histoclinical prognostic features and gene correlations. The study evidenced extensive heterogeneity of breast tumors at the transcriptional level. A hierarchical clustering algorithm identified two molecularly distinct subgroups of tumors characterized by a different clinical outcome after chemotherapy. This outcome could not have been predicted by the commonly used histoclinical parameters. No correlation was found with the age of patients, tumor size, histological type and grade. However, expression of genes was differential in tumors with lymph node metastasis and according to the estrogen receptor status; ERBB2 expression was strongly correlated with the lymph node status (P < 0.0001) and that of GATA3 with the presence of estrogen receptors (P < 0.001). Thus, our results identified new ways to group tumors according to outcome and new potential targets of carcinogenesis. They show that the systematic use of cDNA array testing holds great promise to improve the classification of breast cancer in terms of prognosis and chemosensitivity and to provide new potential therapeutic targets.

Expression scanning of an array of growth control genes in human tumor cell lines.

Analysis of gene expression on a medium- or large-scale is an increasingly recognized method for functional and clinical investigations based on the now extensive catalog of known or partially sequenced genes. The accessibility of this approach can be enhanced by using readily available technology (macroarrays on Nylon, radioactive detection) and the IMAGE resource to assemble sets of targets. We have set up such a medium-scale, flexible system and validated it by the study of quantitative expression levels for 120 genes in six cell lines, including three mammary carcinoma cell lines. A number of important parameters are identified as necessary for the assembly of a valid set and the obtention of good-quality quantitative data. The extensive data assembled in this survey identified potential targets of carcinogenesis, for example the CRABP2 and GATA3 transcription factor genes. We also demonstrate the feasibility of this procedure for relatively small tumor samples, without recourse to probe amplification methods.

Engagement of natural cytotoxicity programs regulates AP-1 expression in the NKL human NK cell line.

NK cell cytotoxicity is a fast and efficient mechanism of target cell lysis. Using transcription analysis, such as multiplex messenger assays, we show here that natural cytotoxicity exerted by the human NKL cell line correlates with mRNA accumulation of very early activator protein (AP)-1 transcription factor genes such as JunB, FosB and c-Fos. In addition, DNA-binding activities of Jun-Fos heterodimers were observed by electrophoretic mobility shift assays during the course of natural cytotoxicity. Interaction between immunoglobulin-like transcript-2/leukocyte Ig-like receptor 1 on NKL cells and HLA-B27 on target cells leads to an impairment of NKL natural cytotoxicity, which correlates with an absence of JunB, FosB, and c-Fos transcription, as well as an absence of their DNA-binding activity. Our studies thus indicate that, despite the rapidity of NK cell-mediated lysis, AP-1 transcription factor is activated during the early stage of NK cell cytolytic programs and that engagement of NK cell inhibitory receptors for MHC class I molecules impairs the very early activation of AP-1.