New tools in cytometry.

Cytometry aims to analyze cells, of any type, using dedicated instruments. The quantitative aspect makes flow cytometry (FCM) a good complementary tool for morphology. Most of the identification tools are based on immunostaining of cell structure details and more and more tools are available in terms of specificities and labels. FCM is under exponential development thanks to technical, immunological and data analysis progresses. Actual generations are now routinely using 6 to 10 simultaneous immuno-labeling on 20 to 100,000 cells, at high speed and short sample preparation and can easily detect rare events at frequency below 10-4 cells. Data interpretation is complex and requires expertise. Mathematical tools are available to support analysis and classification of cells based. Cells from tissues can also be analyzed by FCM after mechanical and or enzymatic separation, but in situ cells can also be analyzed with the help of cytometry. Very new instruments bring spectral analysis, image in flow and mass spectrometry. Medical applications are very broad, notably in hemopathies, immunology, solid tumors, but also microbiology, toxicology, drug discovery, food and environmental industry. But, the limit of FCM is its dependence on operator from sample preparation, instrument settings up to data analysis and a strong effort is now under progress for standardization and constitution of international data bank for references and education.

Microsatellite profile in hormonal receptor genes associated with breast cancer.

Given that breast cancer is depending on multiple hormonal influences, the nuclear receptors, estrogen receptor alpha, estrogen receptor beta and androgen receptor, are candidates for cancer susceptibility markers. We conducted an association study in a case-control population (139 cases and 145 controls) by genotyping three potentially functional microsatellites (TA)n, (CA)n and (CAG)n in the ERa, ERb and AR genes respectively. For (CAG)n polymorphism, a significant difference was observed using a cut-off 15 repeats CAG between genotypes short-short/short-long/long-long in cases and control subjects (p = 0.009) and also between the distribution of short/long allele in the two groups of individuals (p = 0.001). Genotypes comprising one or two short (CAG)n sequences had higher risk of breast cancer compared to genotypes with two long allele (odds ratio = 1,93; confidence interval = 1.05-3.55; p = 0.03). No significant difference was observed in allele frequency or in short/long allele percentage for (CA)n or (TA)n polymorphism (cut-off 22 CA and 19 TA repeats), neither in genotype frequencies (short-short, short-long or long-long). When the three microsatellite genotype were taken in analysis, the profile short CA-long TA-short CAG could clearly discriminate between cases and controls (p = 0.006). Also, this combined genotype profile has greater predictive values for breast cancer than (CAG)n genotype alone (predictive positive value 57,1% versus 53,7% and predictive negative value 53% versus 23% respectively). Our results sustain a polygenic model of breast cancer with gene-gene interactions; combined effects of three low-risk polymorphisms conferred significant genetic predisposition. Genotyping hormonal receptor genes ERa, ERb and AR could be a useful genetic marker for defining disease risk.