Analiza povezanosti somatskih varijanti tumora s mutacijma i mutacijskim potpisima

master's thesis

• Title (english): Association analysis of somatic tumor variants with mutations and mutational signatures
• Author: Ingrid Tomljanović
• Mentor: Fran Supek (mentor)
• Mentor: Dubravko Pavoković (mentor)
• Committee member: Dubravko Pavoković (predsjednik povjerenstva)
• Committee member: Antun Alegro (član povjerenstva)
• Committee member: Marin Ježić (član povjerenstva)
• Committee member: Biljana Balen (član povjerenstva)
• Granter: University of Zagreb; Faculty of Science; (Department of Biology); Zagreb
• Defense date and country: 2019-03-08, Croatia
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Biology

Abstract

Tijekom života pacijenta, genom stanice raka postupno nakuplja somatske mutacije uslijed djelovanja raznih endogenih i egzogenih mutacijskih procesa. Genomske otiske ovih procesa moguće je razlučiti iz podataka o somatskim mutacijama tumora te ih nazivamo mutacijskim potpisima. Cilj ovog diplomskog rada bio je proučiti povezanost opsežnog skupa somatskih mutacija koje pripadaju 721 odabranom genu sa 30 mutacijskih potpisa i zamjenskih varijabli na 33 različita tipa raka. Dvostrano neparametarsko testiranje primijenjeno je na razini svih tipova raka te pojedinih tipova raka u svrhu testiranja pojedinih ponavljajućih somatskih mutacija te testiranja tereta mutacija u ponavljajuće mutiranim genima na osnovi podatkovnog seta TCGA MC3 koji sadrži ~10,000 uzoraka. Analize su podijeljene po statusu hipermutiranosti uzoraka te predviđenom dobroćudnom ili zloćudnom tipu mutacija. Rezultati su u svrhu ispravka višestrukog testiranja hipoteza podvrgnuti metodi genomske kontrole te Benjamini-Hochbergovoj metodi i filtrirani po apsolutnoj vrijednosti veličine učinka. Testiranjem pojedinih mutacija otkrivene su 62 značajne poveznice, dok su testiranjem tereta mutacija otkrivene 162 značajne poveznice na razini pojedinih tipova raka i svim podskupovima podataka. Većina otkrivenih poveznica predstavljaju nova otkrića i moguće vrijedne ciljeve budućih istraživanja mutacijskih procesa aktivnih u stanicama raka.

Abstract (english)

Throughout the lifetime of a patient, the genome of a cancer cell gradually accumulates somatic mutations due to a variety of endogenous and exogenous mutational processes. The genomic fingerprints of those processes can be deconvoluted from tumor somatic mutation data and are termed mutational signatures. The goal of this master thesis was to assess the relationships of a comprehensive set of somatic mutations belonging to a list of 721 selected genes with the 30 mutational signatures and their proxies across 33 different cancer types. Two-sided nonparametric testing was employed on both pan-cancer and per-cancer type levels to individually test recurrent somatic mutations and to perform burden testing of recurrently mutated genes based on the TCGA MC3 dataset comprising ~10,000 samples. Analyses were stratified by sample hypermutation status and predicted benign or pathogenic mutation character. Results were submitted to genomic control and Benjamini-Hochberg multiple testing correction procedures and filtered using absolute effect sizes. Individual mutation testing identified 62 significant associations, while burden testing identified 162 significant associations on the per-cancer type level across data subsets. The majority of identified associations were novel findings and constitute potentially valuable targets for future research into the mutational processes operative in cancer cells.

• Keywords: mutacijski potpisi; TCGA; somatske mutacije; pogonski geni; COSMIC; testiranje tereta; genomska kontrola
• Keywords (english): mutational signatures; TCGA; somatic mutations; driver genes; COSMIC; burden testing; genomic control
• Language: croatian
• URN:NBN: urn:nbn:hr:217:440763
• 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: Embargoed access; Embargo expiration date: 2021-03-08
• Created on: 2019-04-10 09:05:17