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Investigations of genomic changes induced by the FAC drug combination

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posted on 15.12.2014, 10:42 by Jolanta Agnieszka Obszynska
At the present, researchers are not able to predict which individual patients might be susceptible to developing AML. Current research carried out in various laboratories is focused on identifying potential markers that would allow for identification of such patients. The analysis of gene expression profiles of cells treated with the FAC drug regime gave an insight on the impact that the chemotherapeutics have on non-cancerous cells. Exposure to the FAC drug regime caused many changes in gene expression profiles of treated cells. Experiments examining the impact of single doses treatments and combined FAC regime showed variations in gene expression responses to the xenobiotics. Gene expression profiles varied depending on the amount of time that the cells were exposed to the FAC drugs. Shorter exposure to FAC drugs generated more overexpresed genes. During the microarray analysis, synergistic interactions between FAC drugs were discovered. Such synergistic interactions could be very important for future drug discovery and population studies. Two candidate biomarkers were also investigated as potential indicators of susceptibility to developing secondary leukaemias. Minisatellite MS1 and MLL/AF4 translocations were analysed. Minisatellites are highly sensitive repeat regions in human genome that might be susceptible to changes induced by xenobiotics. MS1 has a highly variable internal structure, because of its variability and unstable nature, it was chosen to act as biomarker. An alternative method to detect DNA damage by identification of MLL/AF4 translocations was explored in this project. Chromosomal aberrations between those genes may cause secondary leukaemeia in cancer patients. PCR based techniques were utilised to detect any MLL/AF4 translocations present both in cell lines and in patients' DNA. Both minisatellites MS1 and MLL/AF4 translocations proved not to be suitable candidates as biomarkers.


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University of Leicester

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