Burkitt lymphoma with a duplication of der(8)t(2;8). Interpretation of a complex karyotype by chromosome painting

Novel genomic imbalances and chromosome translocations involving c-myc gene in Burkitt's lymphoma

In this study, CA46 and ST486, two Epstein-Barr (EBV) negative cell lines derived from sporadic BL, were analyzed by multicolor spectral karyotyping, G-banding, fluorescence in situ hybridization with single-copy gene probes, and comparative genomic hybridization (CGH). In addition to reciprocal t(8;14)(q24;q32) translocation involving c-myc and IgH loci, we identified a t(7;8;14)(q11.2;q24;q32) translocation in CA 46 cells and t(8;14;18)(q24;q32;q23) in ST486 cells. Both rearrangements were not previously described in BL and resulted in transposition of myc sequences in a new genomic configuration. Several DNA imbalances mapped by CGH at the same sites in both lines, may reflect recurrent genomic changes that are relevant to pathogenesis of BL. We tested the tumorigenicity of these lines by injecting cells intraperitoneally in SCID mice. In two separate experiments, CA46 cells produced tumors 2 weeks after cell inoculation while ST486 cells induced only one tumor after a long latency period. Partial duplication of the long arm of chromosome 1 involving variable bands but always band 1q23 is the second most common alteration in BL and is known to be associated with aggressive tumors and poor prognosis. Duplication of the bands 1q23-24 commonly observed in EBV-negative lines was identified only in highly tumorigenic CA46 cells suggesting that this region harbor gene(s) associated with tumor cell invasiveness.

Applying watershed algorithms to the segmentation of clustered nuclei

Cluster division is a critical issue in fluorescence microscopy-based analytical cytology when preparation protocols do not provide appropriate separation of objects. Overlooking clustered nuclei and analyzing only isolated nuclei may dramatically increase analysis time or affect the statistical validation of the results. Automatic segmentation of clustered nuclei requires the implementation of specific image segmentation tools. Most algorithms are inspired by one of the two following strategies: 1) cluster division by the detection of internuclei gradients; or 2) division by definition of domains of influence (geometrical approach). Both strategies lead to completely different implementations, and usually algorithms based on a single view strategy fail to correctly segment most clustered nuclei, or perform well just for a specific type of sample. An algorithm based on morphological watersheds has been implemented and tested on the segmentation of microscopic nuclei clusters. This algorithm provides a tool that can be used for the implementation of both gradient- and domain-based algorithms, and, more importantly, for the implementation of mixed (gradient- and shape-based) algorithms. Using this algorithm, almost 90% of the test clusters were correctly segmented in peripheral blood and bone marrow preparations. The algorithm was valid for both types of samples, using the appropriate markers and transformations.