Određivanje ishodišne stanice tumora na temelju raspodjele različitih tipova mutacija

master's thesis

• Title (english): Cell-of-origin determination based on the distribution of different mutation types in cancer
• Author: Ivan Bakšić
• Mentor: Rosa Karlić (mentor)
• Committee member: Kristian Vlahoviček (predsjednik povjerenstva)
• Committee member: Inga Urlić (član povjerenstva)
• Committee member: Dunja Leljak-Levanić (član povjerenstva)
• Committee member: Nenad Malenica (član povjerenstva)
• Granter: University of Zagreb; Faculty of Science; (Department of Biology); Zagreb
• Defense date and country: 2022-04-21, Croatia
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Biology

Abstract

Usporedbom tumorskih obrazaca mutacija s kromatinskim obilježjima stanica pojedinih tipova
tkiva moguće je tumor povezati s izvornim tipom zdrave stanice iz koje je tumor nastao. U ovome
radu proveo sam istraživanje na 722 uzorka melanoma i tumora jetre te na integracijskim mjestima
hepatitis B virusa. Cilj je bio pomoću Random Forest regresijske analize odrediti ishodišnu stanicu
tumora na temelju korelacije između kromatinskih obilježja zdravih tkiva i varijanti jednog
nukleotida, insercija i delecija te virsunih integracijskih mjesta. Nadalje, u radu su provedena
metodološka istraživanja kojima se htjelo postići poboljšanje u određivanju ihodišnih stanica i
istražiti kako broj mutacija utječe na kvalitetu predviđanja. Dokazano je kako je frekvencija
varijanti jednog nukleotida povećana u regijama otvorenog kromatina kod tumorskih stanica
melanoma te da je moguće postići značajno povećanje snage predviđanja isključenjem stršećih
vrijednosti. Također je utvrđeno da s podacima varijanti jednog nukleotida tumora jetre, insercija
i delecija te virusnih integracijskih mjesta korištenim u ovome radu nije moguće pouzdano i točno
odrediti ishodišnu stanicu te da značajno smanjenje broja mutacija neće nužno dovesti do
smanjenja kvalitete predviđanja ishodišnje stanice.

Abstract (english)

It is possible to corelate tumor with the healthy tissue it originated by using comparison of
mutational landscape with chromatin marks of the normal cells. In this work I carried out research
on 722 melanoma and liver carcinoma samples and on hepatitis B virus integration sites. The goal
of this research was to determine COO correlations between chromatin marks and single nucleotide
variance, insertions and deletions and hepatitis B integration sites using the Random Forest
regression analysis. Moreover, this work provides methodological research with the goal of
improving cell-of-origin determination and observing the effect of different mutation number on
the quality of the prediction. It was proven that the melanoma single nucleotide variance frequency
is higher in open chromatin regions and that it was possible to considerably increase prediction
power by outlier exclusion. It was also determined that liver carcinoma single nucleotide variance
data, insertion and deletion data and virus integration site data used in this work do not provide
accurate nor reliable cell-of-origin prediction. Finally, it was determined how usage of considerably
lower number of mutations does not necessarily lower the prediction power of the cell-of origin.

• Keywords: ishodišna-stanica; tumor; melanom; HBV; VIS; Random-Forest
• Keywords (english): Cell-of-origin; Cancer; Melanoma; HBV; VIS; Random-Forest
• Language: croatian
• URN:NBN: urn:nbn:hr:217:265845
• Study programme: Title: Molecular Biology; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra molekularne biologije (magistar/magistra molekularne biologije)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2022-05-03 07:59:40