Three-dimensional distribution patterns of CD34 antigen on nonactivated cord blood cells.

Circulating immature blood cells are inhomogeneous in most cytometric parameters, including CD34 expression. This surface antigen forms patches, and we studied their spatial distribution pattern by processing staggered and digitalized microscopical images; the number, fluorescence intensity, and volume were determined in randomly identified CD34-positive cord blood cells in suspension. Quantitative fluorescence analysis of individual CD34-labeled cells was performed after acquisition of microscopical images in high resolution by using a CCD camera and adjacent deconvolution. Two major (n = 42 and n = 41) and one minor (n = 5) group of haematopoietic progenitors with different CD34+ distribution patterns were detected. All CD34 antigen patches are localized on the spherical cell membrane, and differ most significantly in fluorescence intensity (P < 10(-4)), antigen volume (P < 0.004), and patch number per cell (P < 0.02). If all parameters are employed, 96.6% of CD34+ cells are correctly classified into one of the three groups as shown by discriminant analysis. If fluorescence intensity is eliminated, recognition efficiency decreases to 68.2%, indicating that this is the most powerful single parameter. While total fluorescence intensity is most characteristic for each group, total patch volume and number per cell, and heterogeneity of patch volumes and their spatial distribution also contribute significantly to reliable classification into their groups.

Validation of image processing tools for 3-D fluorescence microscopy.

3-D optical fluorescent microscopy becomes nowadays an efficient tool for volumic investigation of living biological samples. Using optical sectioning technique, a stack of 2-D images is obtained. However, due to the nature of the system optical transfer function and non-optimal experimental conditions, acquired raw data usually suffer from some distortions. In order to carry out biological analysis, raw data have to be restored by deconvolution. The system identification by the point-spread function is useful to obtain the knowledge of the actual system and experimental parameters, which is necessary to restore raw data. It is furthermore helpful to precise the experimental protocol. In order to facilitate the use of image processing techniques, a multi-platform-compatible software package called VIEW3D has been developed. It integrates a set of tools for the analysis of fluorescence images from 3-D wide-field or confocal microscopy. A number of regularisation parameters for data restoration are determined automatically. Common geometrical measurements and morphological descriptors of fluorescent sites are also implemented to facilitate the characterisation of biological samples. An example of this method concerning cytogenetics is presented.

A cytogenetic study of 397 consecutive acute myeloid leukemia cases identified three with a t(7;21) associated with 5q abnormalities and exhibiting similar clinical and biological features, suggesting a new, rare acute myeloid leukemia entity.

The RUNX1 gene is implicated in numerous chromosomal translocations that occur in acute myeloid leukemia (AML) and result in chimeric genes. In this study, 397 consecutive AML cases were analyzed using RUNX1 fluorescence in situ hybridization (FISH) probes. Three cases of the recently described translocation, t(7;21)(p22;q22), were identified, which expressed RUNX1-USP42 (ubiquitin-specific protease 42) fusion transcripts, associated with 5q abnormalities and hyperploidy. These cases displayed homogeneous morphological features (including phagocytosis) and aberrantly expressed CD56 and CD7 lymphoid antigens. Although very few data are available from previously reported cases, when these features are present, a detailed chromosomal analysis, including hybridization with RUNX1 FISH probes, should be performed at diagnosis to recognize chromosomal abnormalities. Additional cases of t(7;21) positive AML should be evaluated to characterize this potentially rare AML entity in greater detail.

Cell surface CD43 determination improves diagnostic precision in late B-cell diseases.

Panels of immunological markers are useful in refining diagnosis in view of certain variability between B-cell leukaemias. A statistical multivariate approach was used on 100 B leukaemias (preliminary sample) to explore the potential value of the combination of CD43, and the classical markers CD5, CD23, CD79b, FMC7, CD22 and surface immunoglobulin to differentiate chronic lymphoid leukaemia (CLL) from lymphoma (non-CLL). CD43 was highly effective (P < 0.00001) and its inclusion in the panels improved the accuracy of discrimination in a 'control' sample of 74 B leukaemias to 98.6%. Inclusion of CD43 facilitates the diagnosis of B-lymphoproliferative disorders and improves their classification.