Transcriptomics analysis and its applications in cancer

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http://urn.fi/URN:ISBN:978-951-51-6866-5
Title: Transcriptomics analysis and its applications in cancer
Author: Cervera Taboada, Alejandra
Other contributor: Helsingin yliopisto, lääketieteellinen tiedekunta
Helsingfors universitet, medicinska fakulteten
University of Helsinki, Faculty of Medicine
Biolääketieteellinen tohtoriohjelma
Doktorandprogrammet i biomedicin
Doctoral Programme in Biomedicine
Publisher: Helsingin yliopisto
Date: 2020-12-14
Language: en
URI: http://urn.fi/URN:ISBN:978-951-51-6866-5
http://hdl.handle.net/10138/321797
Thesis level: Doctoral dissertation (article-based)
Abstract: Cancer is a collection of diseases that combined are one of the leading causes of deaths worldwide. Although great strides have been made in finding cures for certain cancers, the heterogeneity caused by both the tissue in which cancer originates and the mutations acquired in the cell’s DNA results in unsuccessful treatments for some patients. The genetic alterations caused by carcinogenics or by random mutations acquired during normal cell division promotes changes in the cell’s metabolism. These changes are usually reflected in abnormal gene expression that can be studied to understand the underlying mechanisms giving rise to cancer as well as suggest treatments that can exploit each tumor’s specific vulnerabilities. RNA-Seq is a technology that allows the identification and quantification of the genes that are being expressed inside the cell in a given moment. RNA-Seq has several characteristics and advantages that allow a diversity of applications to exist. For example, apart from quantifying gene expression, it can be used to detect different variants of the same gene, has base pair resolution which is informative of the gene sequence, and can also be used to quantify other RNA molecules besides messenger RNA (mRNA), such as microRNAs. The two main aims of this work are to provide computational methods for data analysis of RNA-Seq and to show specific applications of RNA-Seq that can shed light into cancer mechanisms. In Publications I and IV we developed the Sequence Processesing Integration and Analysis (SePIA) and the Fusion Gene Integration (FUNGI) toolsets that facilitate the creation of reproducible pipelines for investigating different aspects of the cancer transcriptome. SePIA’s utility is showcased with the analysis of datasets from two public data repositories. One of the analysis shows a standard RNA-Seq analysis, while the second one produced a pipeline for mRNA-microRNA integration. The second toolset, FUNGI, is aimed specifically at finding reliable gene fusions with oncogenic potential. To demonstrate FUNGI’s features, we analyzed 107 in-house samples and processed over 400 public samples from a public data repository. FUNGI allowed us to detect fusions in ovarian cancer with a higher prevalence than previously recognized. Additionally, we identified a fusion gene that has not been reported before in ovarian cancer, but that can be targeted with a drug currently in clinical trials. In Publication II we investigated the role of alternative splicing in diffuse large B-cell lymphoma and were able to show that isoform-level instead of gene-level is better at discriminating between subtypes. Additionally, specific isoforms, such as APH1A, KCNH6, and ABCB1, were correlated with survival. In Publication III, we used RNA-Seq to complement the phasing of genetic variants with somatic mutations in tumor suppressor genes. In this study we found enrichment of haplotype combinations that suggest that haploinsufficiency of tumor suppressor genes is enriched in cancer patients. SePIA and FUNGI are tools that can be used by the community to explore their datasets and contribute to the acquisition of knowledge in the field of cancer genetics with next generation sequencing. The applications of RNA-Seq studies included in this dissertation showed that RNA-Seq can be effectively used to aid in the classification of cancer subtypes, and that RNA-Seq can be used in combination with DNA sequencing to explore gene expression mediated by genetic variation in cancer.Syöpä on kokoelma sairauksia, jotka yhdessä ovat yksi suurimmista kuolemaan johtavista syistä maailmanlaajuisesti. Vaikka monien syöpien hoidossa on tapahtunut suuria edistysaskelia, joidenkin potilaiden kohdalla hoidot epäonnistuvat koska kudos, josta kasvain saa alkunsa, sekä muutokset, joita kertyy solun DNA:han, aiheuttavat suuria eroavaisuuksia sekä kasvainten kesken, että niiden sisällä. Karsinogeenien aiheuttamat tai normaalin solunjakautumisen yhteydessä sattumalta tapahtuvat muutokset solun perimässä aiheuttavat muutoksia solun aineenvaihdunnassa. Nämä muutokset heijastuvat yleensä epänormaalina geenien ilmentymisenä, joita tutkimalla voidaan selvittää syövän syntyyn vaikuttavia mekanismeja ja ehdottaa hoitoja, jotka kohdistuvat yksittäisen kasvaimen erityisiin heikkouksiin. Tämän väitöskirjatyön päätavoitteina on ollut kehittää laskennallisia menetelmiä geenien ilmentymisen analysointiin sekä osoittaa käytännössä, miten niiden avulla saadaan lisätietoa syövän syntymekanismeista. Tätä varten kehitimme kaksi työkalupakettia, jotka edesauttavat luotettavasti toistettavien työnkulkujen luomista sýövän transkriptomin, eli sen kaikkien RNA-molekyylien, tutkimiseen. Näiden työkalujen avulla pystyimme vakioimaan transkriptiodatan analyysin ja tunnistamaan sellaisia poikkeuksia geenisekvensseissä tai muutoksia geenien ilmentymisessä, joilla on merkitystä syövän etenemisessä tai jotka liittyvät syövän eri alatyyppeihin.
Subject: biomedicine
Rights: Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.


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