We propose that the apoptotic function of p53 has an important role in B-cell homeostasis, which is important for the prevention of B-cell lymphomas. We created a mouse model (mDpro) that lacked residues 58-88 of the proline-rich domain of p53. mDpro is defective for apoptosis, but is able to arrest cell-cycle progression in hematopoietic tissues. mDpro develops late-onset B-cell lymphoma, but not the thymic T-cell tumors found in p53-null mice. Interestingly, mDpro lymphomas comprised incorrectly differentiated B cells. B-cell irregularities were also detected in mDpro before tumor onset, in which aged mice showed an increased population of inappropriately differentiated B cells in the bone marrow and spleen. We predict that by keeping B-cell populations in check, p53-dependent apoptosis prevents irregular B cells from eventuating in lymphomas.

In quantitative single-cell studies, the critical part is the low amount of nucleic acids present and the resulting experimental variations. In addition biological data obtained from heterogeneous tissue are not reflecting the expression behaviour of every single-cell. These variations can be derived from natural biological variance or can be introduced externally. Both have negative effects on the quantification result. The aim of this study is to make quantitative single-cell studies more transparent and reliable in order to fulfil the MIQE guidelines at the single-cell level. The technical variability introduced by RT, pre-amplification, evaporation, biological material and qPCR itself was evaluated by using RNA or DNA standards. Secondly, the biological expression variances of GAPDH, TNFα, IL-1β, TLR4 were measured by mRNA profiling experiment in single lymphocytes. The used quantification setup was sensitive enough to detect single standard copies and transcripts out of one solitary cell. Most variability was introduced by RT, followed by evaporation, and pre-amplification. The qPCR analysis and the biological matrix introduced only minor variability. Both conducted studies impressively demonstrate the heterogeneity of expression patterns in individual cells and showed clearly today's limitation in quantitative single-cell expression analysis.

Detection of chromosomal aneuploidies using fetal cells isolated from maternal blood, for prenatal non-invasive genetic investigation, has been a long-sought goal of clinical genetics to replace amniocentesis and chorionic villous sampling to avoid any risk to the fetus. The purpose of this study was to develop a sensitive and specific new assay for diagnosing aneuploidy with circulating fetal cells isolated from maternal blood as previously reported using two novel approaches: (i) simultaneous immunocytochemistry (ICC) evaluation using a monoclonal antibody for i-antigen, followed by fluorescence in situ hybridization (FISH); (ii) dual-probe FISH analysis of interphase nuclei using two differently labeled probes, specific for different loci of chromosomes 21 and 18; in addition, short tandem repeats (STR) analysis on single cells isolated by micromanipulation was applied to confirm the presence of fetal cells in the cell sample enriched from maternal blood. Blood samples were obtained from women carrying trisomic fetuses, and from non-pregnant women and men as controls. Using ICC-FISH approach, a large heterogeneity in immunostaining pattern was observed, which is a source of very subjective signal interpretation. Differently, dual-probe FISH analysis provided for a correct diagnosis of all pregnancies: the mean percentage of trisomic cells was 0.5% (range, 0.36-0.76%), while the mean percentage of trisomic cells in the control group (normal pregnancies or non-pregnant women) was ≤0.20%. The application of the dual-probe FISH protocol on fetal cells isolated from maternal blood enables accurate molecular detection of fetal aneuploidy, thus providing a foundation for development of non-invasive prenatal diagnostic testing.

Our work discloses a complete workflow to detect, count and genetically analyze individual CTCs isolated from blood samples. This method has a central impact on the early detection of metastasis development. The combination of cell quantification and genetic analysis provides the clinicians with a powerful tool not available so far.

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