To the top

Page Manager: Webmaster
Last update: 9/11/2012 3:13 PM

Tell a friend about this page
Print version

Computational exploration… - University of Gothenburg, Sweden Till startsida
Sitemap
To content Read more about how we use cookies on gu.se

Computational exploration of cancer genomes

Doctoral thesis
Authors Joakim Karlsson
ISBN 978-91-7833-291-5
Publisher Göteborgs universitet
Publication year 2019
Published at Institute of Biomedicine, Department of Medical Biochemistry and Cell Biology
Language en
Links hdl.handle.net/2077/58233
Keywords Cancer genomics, Transcriptomics, Driver genes, Copy number changes, Immunogenomics, Cancer of unknown primary, Uveal melanoma
Subject categories Biochemistry and Molecular Biology, Cancer and Oncology

Abstract

Cancer evolves due to changes in DNA that give a cell an advantage at the expense of the remaining organism. These alterations range from individual base substitutions to broad losses or duplications of chromosomal material. This thesis explores how DNA and RNA sequencing can guide discovery of altered genes responsible for cancer development, profile the immune landscapes of tumors and support the diagnosis of difficult cases. In the first of three studies, we examined DNA and RNA from the tumors of a patient with metastatic cancer but an uncertain diagnosis. We discovered that these tumors harbored a mutational signature associated with ultraviolet radiation. This restricted the possible sites of origin to those that can be exposed to sunlight. To confirm this, gene expression estimates were then compared to a large database of multiple cancer types. This gave a perfect match to cutaneous melanoma, thus enabling a certain diagnosis. The second study established a method for searching candidate cancer genes that are altered by genomic copy number changes. The method integrates estimates of copy number changes with gene expression to prioritize genes concurrently and consistently altered with respect to both, putting greater emphasis on copy number changes comprising smaller chromosomal regions, which tend to exclude unselected genes from consideration. This system was able to retrieve known cancer genes as top candidates in several cancer types. In addition, this method also implemented a way to examine regions of DNA where genes are currently not known to exist. In the final study, we molecularly profiled metastatic uveal melanoma (UM), a rare but difficult to treat eye cancer. We reintroduced a functional version of the tumor suppressor BAP1 into one deficient tumor, resulting in a global transcriptional shift towards a less metastatic subtype. We also found one tumor harboring a specific mutational signature that has not previously been observed in UM, and which might suggest a new risk factor. Next, we narrowed down a set of candidate genes potentially influencing tumor behavior via broad copy number changes, which could possibly be drug targets. Finally, we transcriptomically profiled tumor-infiltrating T-cells and found these to be in exhausted states, possibly explaining the failures of immunotherapy in UM. Despite this, they were in several cases capable of tumor recognition. In conclusion, this thesis explores molecular data of cancers from a number of different angles. The results should have relevance for diagnostic principles and may suggest candidate genes for future functional studies.

Page Manager: Webmaster|Last update: 9/11/2012
Share:

The University of Gothenburg uses cookies to provide you with the best possible user experience. By continuing on this website, you approve of our use of cookies.  What are cookies?