prikaz prve stranice dokumenta Detection of somatic mutations and mutational signatures in pancreatic cancer using RNA-sequencing data
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master's thesis
Detection of somatic mutations and mutational signatures in pancreatic cancer using RNA-sequencing data
Zagreb: University of Zagreb, Faculty of Science, 2023. urn:nbn:hr:217:857654
Pantlik, Jan
University of Zagreb
Faculty of Science
Department of Biology

Institutional repository: Repository of the Faculty of Science

Cite this document

Pantlik, J. (2023). Detection of somatic mutations and mutational signatures in pancreatic cancer using RNA-sequencing data (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:857654

Pantlik, Jan. "Detection of somatic mutations and mutational signatures in pancreatic cancer using RNA-sequencing data." Master's thesis, University of Zagreb, Faculty of Science, 2023. https://urn.nsk.hr/urn:nbn:hr:217:857654

Pantlik, Jan. "Detection of somatic mutations and mutational signatures in pancreatic cancer using RNA-sequencing data." Master's thesis, University of Zagreb, Faculty of Science, 2023. https://urn.nsk.hr/urn:nbn:hr:217:857654

Pantlik, J. (2023). 'Detection of somatic mutations and mutational signatures in pancreatic cancer using RNA-sequencing data', Master's thesis, University of Zagreb, Faculty of Science, accessed 03 May 2024, https://urn.nsk.hr/urn:nbn:hr:217:857654

Pantlik J. Detection of somatic mutations and mutational signatures in pancreatic cancer using RNA-sequencing data [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2023 [cited 2024 May 03] Available at: https://urn.nsk.hr/urn:nbn:hr:217:857654

J. Pantlik, "Detection of somatic mutations and mutational signatures in pancreatic cancer using RNA-sequencing data", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:217:857654

Metadata
TitleDetection of somatic mutations and mutational signatures in pancreatic cancer using RNA-sequencing data
Title (croatian)Detekcija somatskih mutacija i mutacijskih potpisa tumora gušterače korištenjem podataka RNA-sekvenciranja
AuthorJan Pantlik
MentorRosa Karlić (mentor)
MentorPaula Štancl (komentor)
Committee memberRosa Karlić (predsjednik povjerenstva)
Committee memberTomislav Ivanković (član povjerenstva)
Committee memberMaja Matulić (član povjerenstva)
Committee memberDamjan Franjević (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Science
(Department of Biology)
Zagreb
Defense date and country2023-09-27, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Biology
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is an extremely deadly cancer whose late detection and aggressive nature pose significant challenges, leading to treatment failures. Recent oncological advancements have substantially enhanced survival rates for various cancers by utilizing novel techniques for early detection and personalized therapies. The scope of clinical genetic testing has been significantly broadened by recent advancements in next-generation sequencing technologies, which have enabled the cataloging of genetic variation in population samples and the determination of cancer driver genes. RNA sequencing (RNA-Seq) has great potential for the identification of somatic mutations and mutational signatures associated with different mutational processes. The goal of this research is to use RNA-seq data to detect variants and identify mutational signatures present in PDAC tumor samples. Mutations were called with the variant-calling tool Strelka2, annotated, and compared to somatic variants identified from exome sequencing data. Detected mutations were then utilized to build mutational catalogs for mutational signature fitting with signature.tools.lib. The results showed that SBS1, SBS5, SBS18, and SBS123 are the most frequent mutational signatures in analyzed PDAC samples. Mutational signature analysis using RNA sequence data showed exciting potential as a novel and precise method for tumor characterization, which could help tumor diagnosis and treatment.
Abstract (croatian)
Duktalni adenokarcinom gušterače (engl. pancreatic ductal adenocarcinoma, PDAC) izrazito je smrtonosan karcinom, čije kasno otkrivanje i agresivnost predstavljaju velike prepreke koje dovode do neuspjeha u liječenju. Napreci u polju onkologije, prvenstveno unaprjeđenje tehnika ranog otkrivanja karcinoma i personalizirane terapije, znatno su poboljšali stope preživljavanja pacijenata oboljelih od karcinoma. Zahvaljujući napretku tehnologija sekvenciranja nove generacije značajno su proširene mogućnosti genetskog testiranja te je sad moguća preciznija kategorizacija genetskih varijanti detektiranih iz uzoraka unutar populacije te određivanje onkogena. Sekvenciranje RNA (RNA-Seq) ima veliki potencijal za identifikaciju somatskih mutacija i mutacijskih potpisa povezanih s različitim mutacijskim procesima. Cilj ovog istraživanja je korištenje RNA-seq podataka za otkrivanje varijanti i identificiranje mutacijskih potpisa prisutnih u uzorcima PDAC tumora. Mutacije su određene pomoću alata za pozivanje varijanti Strelka2, anotirane i uspoređene sa somatskim varijantama identificiranim iz podataka sekvenciranja eksoma. Detektirane mutacije su zatim korištene za izradu mutacijskih kataloga u svrhu identifikacije mutacijskog potpisa pomoću signature.tools.lib alata. Rezultati su pokazali da su SBS1, SBS5, SBS18 i SBS123 najčešći mutacijski potpisi u analiziranim uzorcima PDAC. Analiza mutacijskih potpisa korištenjem podataka sekvenci RNA pokazala je uzbudljiv potencijal kao nova i precizna metoda za karakterizaciju tumora, koja bi mogla pomoći u dijagnozi i liječenju tumora.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:217:857654
Study programmeTitle: Molecular Biology
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra molekularne biologije (magistar/magistra molekularne biologije)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2023-10-25 08:28:31