Computer aided analysis of additional chromosome aberrations in Philadelphia chromosome positive acute lymphoblastic leukaemia using a simplified computer readable cytogenetic notation

Bradtke, Jutta; Balz, Harald; Fonatsch, Christa; Heinze, Barbara; Jauch, Anna; Mohr, Brigitte; Schoch, Claudia; Rieder, Harald
January 2003
BMC Bioinformatics;2003, Vol. 4, p4
Academic Journal
Background: The analysis of complex cytogenetic databases of distinct leukaemia entities may help to detect rare recurring chromosome aberrations, minimal common regions of gains and losses, and also hot spots of genomic rearrangements. The patterns of the karyotype alterations may provide insights into the genetic pathways of disease progression. Results: We developed a simplified computer readable cytogenetic notation (SCCN) by which chromosome findings are normalised at a resolution of 400 bands. Lost or gained chromosomes or chromosome segments are specified in detail, and ranges of chromosome breakpoint assignments are recorded. Software modules were written to summarise the recorded chromosome changes with regard to the respective chromosome involvement. To assess the degree of karyotype alterations the ploidy levels and numbers of numerical and structural changes were recorded separately, and summarised in a complex karyotype aberration score (CKAS). The SCCN and CKAS were used to analyse the extend and the spectrum of additional chromosome aberrations in 94 patients with Philadelphia chromosome positive (Ph-positive) acute lymphoblastic leukemia (ALL) and secondary chromosome anomalies. Dosage changes of chromosomal material represented 92.1% of all additional events. Recurring regions of chromosome losses were identified. Structural rearrangements affecting (peri)centromeric chromosome regions were recorded in 24.6% of the cases. Conclusions: SCCN and CKAS provide unifying elements between karyotypes and computer processable data formats. They proved to be useful in the investigation of additional chromosome aberrations in Ph-positive ALL, and may represent a step towards full automation of the analysis of large and complex karyotype databases.


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