Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Decoding pan-cancer complexity. Multiomic insights from the lung and breast

Nacer, Deborah F. LU orcid (2024) In Lund University, Faculty of Medicine Doctoral Dissertation Series
Abstract
Cancer presently represents a significant global health challenge, illustrated by the high incidence and mortality rates associated with lung and breast cancer. Technological advances and concerted large-scale initiatives have yielded vast amounts of cancer data to be used for research purposes. The objective of this thesis is to capitalize on the current state of the bioinformatics field to develop and employ tools that extract biological insights from multiomic data across a range of cancer types. Utilizing publicly available data sets from our research group and from other researchers worldwide, two of the included studies were centered on methodological development. Firstly, we successfully applied a gene-expression-based prognostic... (More)
Cancer presently represents a significant global health challenge, illustrated by the high incidence and mortality rates associated with lung and breast cancer. Technological advances and concerted large-scale initiatives have yielded vast amounts of cancer data to be used for research purposes. The objective of this thesis is to capitalize on the current state of the bioinformatics field to develop and employ tools that extract biological insights from multiomic data across a range of cancer types. Utilizing publicly available data sets from our research group and from other researchers worldwide, two of the included studies were centered on methodological development. Firstly, we successfully applied a gene-expression-based prognostic tool originally developed for lung adenocarcinoma, the most common histological subtype of lung cancer, to multiple cancer types, demonstrating the broad applicability of such classifiers (Paper I). Secondly, we refined a method for adjusting DNA methylation data based on the mixture of malignant and non-malignant cells in tumor samples, enhancing biological interpretability of such methylation data sets (Paper III). The remaining studies investigated the biological heterogeneity within lung and breast tumors. Specifically, we stratified breast cancer patients from southern Sweden according to whether they had had genes associated with increased breast cancer risk screened for variants and compared the two resulting groups, obtaining a real-world read-out of the current screening guidelines and patient selection criteria (Paper II). Lastly, we subdivided lung adenocarcinoma into four distinct subgroups based on adjusted DNA methylation data and characterized the resulting sample clusters, both showing congruence to previously proposed mRNA and protein subtypes and providing novel insights into this malignancy (Paper IV). Taken together, the findings presented in this thesis have contributed to our collective understanding of the complex cancer biology landscape. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • PhD McGranahan, Nicholas, Department of Oncology, University College London, London, United Kingdom
organization
publishing date
type
Thesis
publication status
published
subject
in
Lund University, Faculty of Medicine Doctoral Dissertation Series
issue
2024:91
pages
86 pages
publisher
Lund University, Faculty of Medicine
defense location
Belfragesalen, BMC D15, Klinikgatan 32 i Lund
defense date
2024-06-18 09:00:00
ISSN
1652-8220
ISBN
978-91-8021-586-2
language
English
LU publication?
yes
id
fba92f08-7a73-48a8-849a-a718cea8dc2c
date added to LUP
2024-05-15 11:35:46
date last changed
2024-05-24 13:04:16
@phdthesis{fba92f08-7a73-48a8-849a-a718cea8dc2c,
  abstract     = {{Cancer presently represents a significant global health challenge, illustrated by the high incidence and mortality rates associated with lung and breast cancer. Technological advances and concerted large-scale initiatives have yielded vast amounts of cancer data to be used for research purposes. The objective of this thesis is to capitalize on the current state of the bioinformatics field to develop and employ tools that extract biological insights from multiomic data across a range of cancer types. Utilizing publicly available data sets from our research group and from other researchers worldwide, two of the included studies were centered on methodological development. Firstly, we successfully applied a gene-expression-based prognostic tool originally developed for lung adenocarcinoma, the most common histological subtype of lung cancer, to multiple cancer types, demonstrating the broad applicability of such classifiers (Paper I). Secondly, we refined a method for adjusting DNA methylation data based on the mixture of malignant and non-malignant cells in tumor samples, enhancing biological interpretability of such methylation data sets (Paper III). The remaining studies investigated the biological heterogeneity within lung and breast tumors. Specifically, we stratified breast cancer patients from southern Sweden according to whether they had had genes associated with increased breast cancer risk screened for variants and compared the two resulting groups, obtaining a real-world read-out of the current screening guidelines and patient selection criteria (Paper II). Lastly, we subdivided lung adenocarcinoma into four distinct subgroups based on adjusted DNA methylation data and characterized the resulting sample clusters, both showing congruence to previously proposed mRNA and protein subtypes and providing novel insights into this malignancy (Paper IV). Taken together, the findings presented in this thesis have contributed to our collective understanding of the complex cancer biology landscape.}},
  author       = {{Nacer, Deborah F.}},
  isbn         = {{978-91-8021-586-2}},
  issn         = {{1652-8220}},
  language     = {{eng}},
  number       = {{2024:91}},
  publisher    = {{Lund University, Faculty of Medicine}},
  school       = {{Lund University}},
  series       = {{Lund University, Faculty of Medicine Doctoral Dissertation Series}},
  title        = {{Decoding pan-cancer complexity. Multiomic insights from the lung and breast}},
  url          = {{https://lup.lub.lu.se/search/files/183527868/Deborah_Figueiredo_Nacer_de_Oliveira_-_WEBB.pdf}},
  year         = {{2024}},
}