Gaucher disease is a hereditary genetic abnormality which defects the pathway of sphingolipid catabolism. The mutation of GBA gene which encodes lysosomal β-glucosidase enzyme is the main characteristics of the disease also is observed in different cancer types. To find the relation between the disease and colon adenocarcinoma, the responsible gene expression of Gaucher disease was analyzed. The gene expression of colon adenocarcinoma was was compared between death and alive patients and analyzed statistically to profile the differences between Gaucher disease genes expression changes. GBA, GBA2, GBA3, SCARB2 and PSAP have the maximum genetic alteration which is observed in colon adenocarcinoma.

Mixed-lineage leukemia (MLL) is a subtype of acute myeloid leukemia with more aggressive prognosis than other subtypes. Translocations of MLL gene with other partner genes, forming the MLL-fusion proteins (MLL-FPs), are the main characteristics of MLL leukemia. Many studies have demonstrated that MLL-FPs such as: MLL-AF4, MLL-AF6, MLL-AF9, MLL-AF10, MLL-ENL, MLL-ELL, MLL-EPS15, as well as partial tandem duplication are the most common abnormalities that play significant role in MLL-rearranged leukemia. Gene expression profiles from 197 patients and 180 clinical data were downloaded from TCGA database. R statistical program has classified clinical and genomic data simultaneously according to cytogenetic abnormalities. As a result of this analysis, the most frequent 47 MLLFPs genes expression have been detected and compared with other cytogenetic abnormalities such as t(4;11), t(9;11), t(8;21), t(15;17), complex, inversion 16, trisomy 8 and cytogenetically normal AML. 35 out of 46 MLL-FPs genes presented with abnormal gene expression profile. This study showed that MLL-FPs are not just active and related with MLL, but also with other subtypes of AML.

Invasive breast cancer is a heterogeneous disease. The analysis of one or a group of specific gene expression profiles may not be enough to understand molecular activities in cancer cells. Therefore, a method which gives us the opportunity to compare similar up and down regulated gene expression profiles, is needed. The main purpose of our work is to sort the extreme high and low expressed genes and extract, compare and cluster them. Expression profiles of 598 samples of invasive breast cancer and 48 samples of normal tissue have been analysed to create a new algorithm called Extreme Gene Expression Family (EGEF). The EGEF algorithm sorted, grouped and compared the highest and the lowest expressed genes (n = 100). According to the hierarchical clustering result, dense and light memberships of gene families are detected. The resulting analysis allows us to predict which genes would show similar expression signatures in invasive breast cancer and to us to recognize specific biological activities and processes. EGEF algorithm can be used to detect expression signatures in other cancers and biological processes.

Invasive breast cancer is a heterogeneous disease. The analysis of one or a group of specific gene expression profiles may not be enough to understand molecular activities in cancer cells. Therefore, a method which gives us the opportunity to compare similar up and down regulated gene expression profiles, is needed. The main purpose of our work is to sort the extreme high and low expressed genes and extract, compare and cluster them. Expression profiles of 598 samples of invasive breast cancer and 48 samples of normal tissue have been analysed to create a new algorithm called Extreme Gene Expression Family (EGEF). The EGEF algorithm sorted, grouped and compared the highest and the lowest expressed genes (n = 100). According to the hierarchical clustering result, dense and light memberships of gene families are detected. The resulting analysis allows us to predict which genes would show similar expression signatures in invasive breast cancer and to us to recognize specific biological activities and processes. EGEF algorithm can be used to detect expression signatures in other cancers and biological processes.

Microdeletion syndromes are caused by chromosomal deletions of less than 5 megabases which can be detected by fluorescence in situ hybridization (FISH). We evaluated the most commonly detected microdeletions for the period from June 01, 2008 to June 01, 2015 in the Federation of Bosnia and Herzegovina, including DiGeorge, Prader-Willi/Angelman, Wolf-Hirschhorn, and Williams syndromes. We report 4 patients with DiGeorge syndromes, 4 patients with Prader-Willi/Angelman, 4 patients with Wolf-Hirschhorn syndrome, and 3 patients with Williams syndrome in the analyzed 7 year period. Based on the positive FISH results for each syndrome, the incidence was calculated for the Federation of Bosnia and Herzegovina. These are the first reported frequencies of the microdeletion syndromes in the Federation of Bosnia and Herzegovina.

The guanine rich locations are present in human genome. Previous studies have shown that the presence of G rich sequences and motifs may be significant for gene activity and function. We decided to focus our interest to identify G rich motifs in promoters of oncogenes and tumor suppressor genes. We used a set of 100 most common oncogenes and tumor suppressor genes (TSG) for this analysis. We collected 600nt long promoters with -500 and +100 TSS (transcription start site) from the oncogenes and TSG set. Using a computer program, we calculated the G densities using numbers and locations of G forms with 100nt moving widow. We included G numbers from 2 to 7 guanines. Analysis shows that G density increases from -500 to +100 and more from TSS. G density is found to be maximum within -/+100 of TSS. The results of G densities were compared with the expression data of the selected oncogenes and tumor suppressor genes in patients with colon cancer (n=174).

This study aims to compare the advantages of two widely used methods for fetal chromosomal detection, karyotyping and QF-PCR, together with the indications for invasive prenatal diagnosis. We retrospectively investigated 888 amniocenteses analyzed by karyotyping only or karyotyping combined with QF-PCR. We assessed the results of each method and compared them to the indications for prenatal testing including maternal age, fetal ultrasound findings, and serum screening. We found 39 (4.4%) abnormalities, where 59% of those abnormalities were numerical and 41% were structural abnormalities undetectable by QF-PCR methods. Many structural abnormalities do not have clinical significance and we found that 23% of found structural abnormalities were clinically significant but undetectable by QF-PCR (0.3% of all amniocentesis analyzed). Additional 23% of found structural abnormalities were balanced translocations which can have rare clinically significant consequences. In total, 46% of found structural abnormalities had possible clinical consequences, which were undetectable by QF-PCR, or by noninvasive prenatal testing for five common aneuploidies. Thus, QF-PCR is a reliable method to detect most common fetal aneuploidies, but karyotyping should be used if any other chromosomal abnormalities are suspected. Even though QF-PCR is a fast and reliable method, physicians should be aware of the limitations of various methodologies for detection of fetal abnormalities and assign the proper method to the indication for amniocentesis.