RESUMO
In medical genetics, each genetic variant is evaluated as an independent entity regarding its clinical importance. However, in most complex diseases, variant combinations in specific gene networks, rather than the presence of a particular single variant, predominates. In the case of complex diseases, disease status can be evaluated by considering the success level of a team of specific variants. We propose a high dimensional modelling based method to analyse all the variants in a gene network together, which we name "Computational Gene Network Analysis" (CoGNA). To evaluate our method, we selected two gene networks, mTOR and TGF- ß. For each pathway, we generated 400 control and 400 patient group samples. mTOR and TGF- ß pathways contain 31 and 93 genes of varying sizes, respectively. We produced Chaos Game Representation images for each gene sequence to obtain 2-D binary patterns. These patterns were arranged in succession, and a 3-D tensor structure was achieved for each gene network. Features for each data sample were acquired by exploiting Enhanced Multivariance Products Representation to 3-D data. Features were split as training and testing vectors. Training vectors were employed to train a Support Vector Machines classification model. We achieved more than 96% and 99% classification accuracies for mTOR and TGF- ß networks, respectively, using a limited amount of training samples.
RESUMO
Background: Cytogenetic findings are important prognostic factors in acute myeloid leukemia. Large systematic data about chromosomal characteristics of Turkish AML patients have not been reported to date. Objectives: The karyotypic profiles of 157 adult AML patients were evaluated retrospectively and compared with other reports from different populations. Methods: Cytogenetics analyses were performed on bone marrow samples using G-banding. Patients were categorized according to their cytogenetic results into four groups with the addition of a normal karyotyped group to the favorable, intermediate and adverse groups of European Leukemia Network. Results: Cytogenetic analyses were carried out successfully in 138 patients (88%). Abnormal karyotypes were found in 79 (57.2%) patients of which 13 (9.4%) were in favorable, 37 (26.8%) in intermediate and 29 (21%) in adverse groups. t(8;21) (5%) was the most common favorable abnormality while monosomal karyotypes (15.9%) in adverse group. Conclusion: This single center study is the most comprehensive study about the cytogenetic profile of acute myeloid leukemia in Turkey with comparison of other population-based studies. While there were similarities and differences with different publications, our results did not show a marked tendency to the findings of any specific geographic region.
