Bioinformatics analysis of proteins involved in pathogenesis of myeloid malignancies

[B. S. Gemović]

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Molekularna biologija - Bioinformatika / Molecular biology - Bioinformatics

Mijeloidni maligniteti su klonalne bolesti ćelija mijeloidne krvne loze, koje su, pre svega, posledica poremećaja samoobnavljanja i diferencijacije hematopoetskih matičnih ćelija. Godišnja incidenca u Evropi je 7,5-8,6/100 000, a prosečna petogodišnja stopa preživljavanja pacijenata, uz primenu standardne terapije, je 37%. S obzirom da maligniteti najčešće nose više od jedne vodeće – ‘driver’ mutacije, pri čemu je velika intra- i interkancerska genetička heterogenost, postoji potreba za individualizovanim terapeutskim pristupom svakom pacijentu. Personalizovana medicina označava princip postizanja maksimalne terapijske efikasnosti kroz upotrebu ciljanih terapeutika kod biološki okarakterisanih pacijenata. Bioinformatika ima značajnu ulogu u identifikaciji ciljnih molekula za razvoj terapije, racionalnom dizajnu lekova i identifikaciji informativnih biomarkera za prateću dijagnostiku. Predmet istraživanja u ovom radu bili su geni i njihovi proteinski produkti koji imaju važnu ulogu u patogenezi mijeloidnih maligniteta. WT1 je transkripcioni faktor, koji kontroliše ekspresiju gena uključenih u apoptozu, proliferaciju i diferencijaciju. Ovaj gen ima povećanu ekspresiju u 70-90%, a mutiran je u ~10% akutnih mijeloidnih leukemija (AML) i učestvuje u preko 40 protein-protein interakcija, koje su vremenski i kontekstno zavisne. Mapiranje celokupne mreže WT1 kofaktora doprineće identifikaciji novih molekula i interakcija, koje su potencijalni targeti za ciljanu terapiju AML. Nedavno otkriven tumor supresor u karcinomu dojke, NISCH, ispoljava efekat preko RAC signalnog puta, koji je ključan u regulaciji hematopoeze i uključen u patogenezu mijeloidnih maligniteta, i smatra se atraktivnim targetom za ciljanu terapiju. Poznavanje funkcionalnih domena NISCH-a će omogućiti dizajn i optimizaciju jedinjenja sa antikancerskim delovanjem...

Myeloid malignancies are clonal diseases of myeloid cell line, which arise, primary, as a consequence of aberrant self-renewal and differentiation of hematopoietic stem cells. Annual incidence in Europe is 7.5-8.6/100 000 and the mean 5-year survival rate, with standard therapy, is 37%. Since malignancies often carry more than one driver mutation, with high intra- and inter-cancer genetic heterogeneity, there is a need for individualized therapeutic approach to each patient. Personalized medicine is based on the principle of achieving maximal therapeutic efficacy through the use of targeted drugs for biologically characterized patients. Bioinformatics has an important role in identification of molecules for targeted therapy, rational drug design and identification of informative biomarkers for companion diagnostics. The subject of this research included genes and their protein products that have important roles in the pathogenesis of myeloid malignancies. WT1 is a transcription factor that controls the expression of genes involved in apoptosis, proliferation and differentiation. This gene is overexpressed in 70-90%, mutated in ~10% of acute myeloid leukemia (AML) and it is engaged in more than 40 time- and context-dependant protein-protein interactions. Characterizing entire network of WT1 cofactors can improve identification of new molecules and their interactions that could be targets for therapy of AML. Recently identified tumor suppressor in breast cancer, NISCH, affects RAC signaling pathway, which is important in regulation of hematopoiesis and has a role in pathogenesis of myeloid malignancies, so it is considered an attractive target for targeted therapy. Characterization of functional domains of NISCH can enable design and optimization of compounds with anticancer effect...

mijeloidni maligniteti, personalizovana medicina, protein-protein interakcije, proteinski domeni, aminokiselinske substitucije, metod informacionog spektra, WT1, NISCH, epigenetički regulatori

myeloid malignancies, personalized medicine, protein-protein interactions, protein domains, amino acid substitutions, Informational Spectrum Method, WT1, NISCH, epigenetic regulators

577.2:616.155.392(043.3)

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