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Hunting a Silent Killer. Biomolecular Approaches in Ovarian Cancer

Arildsen, Nicolai LU (2019) In Lund University, Faculty of Medicine Doctoral Dissertation Series 2019(20).
Abstract
Ovarian cancer is a heterogeneous disease and recent advances in improving patient outcome have
been limited. It is estimated that a woman’s risk of developing ovarian cancer during her lifetime is about 1 in 70, making it a frequently occurring cancer type in women.
This thesis investigated biological events in ovarian cancer, which were translated into clinically relevant observations using different biomolecular approaches.
Study I investigated the use of sex steroid hormone receptor expression as a prognostic marker in ovarian cancer. We evaluated the expression of estrogen receptor (ER)α, ERβ, progesterone receptor (PR) and androgen receptor (AR) in a cohort of serous and endometrioid cancers. We found that expression of... (More)
Ovarian cancer is a heterogeneous disease and recent advances in improving patient outcome have
been limited. It is estimated that a woman’s risk of developing ovarian cancer during her lifetime is about 1 in 70, making it a frequently occurring cancer type in women.
This thesis investigated biological events in ovarian cancer, which were translated into clinically relevant observations using different biomolecular approaches.
Study I investigated the use of sex steroid hormone receptor expression as a prognostic marker in ovarian cancer. We evaluated the expression of estrogen receptor (ER)α, ERβ, progesterone receptor (PR) and androgen receptor (AR) in a cohort of serous and endometrioid cancers. We found that expression of PR and AR was associated with favorable outcome, and co-expression of AR and PR granted an additional prognostic effect. Although we were unable to detect any association between mRNA expression and a favorable outcome in an independent data set, molecular subtypes in the data set differentially expressed PGR and ESR1. Whether this effect accounted for the reported improved outcome in some of the subgroups remains to be investigated.
Study II characterized ovarian clear cell carcinomas (OCCC) with the purpose of identifying potential treatment candidates. OCCC presents a distinct molecular subtype of ovarian cancer, with high chemoresistance. Through integrative bioinformatics we evaluated combined gene expression data, DNA sequencing data and protein expression data from OCCC tumors. The collective data suggested Rho GTPases as a potential treatment candidate in OCCC.
Study III evaluated the effect of targeting Rho GTPases in OCCC using simvastatin and CID-1067700 in OCCC cell lines. All OCCC cell lines were more sensitive to simvastatin as compared to conventional platinum-based chemotherapy. Both of the drugs we evaluated were found to disorganize the cytoskeleton and inhibit migration. The cellular response mechanisms differed between cell lines, however a potential effect on both the PI3K/AKT/mTOR and RAS/ERK pathways was suggested.
Study IV aimed at evaluating the effects of screening prediagnostic liquid based vaginal samples for TP53 mutations, an approach applied for early detection of ovarian cancer. We identified 8 women with somatic TP53 mutations in high-grade serous ovarian cancer (HGSOC) and analyzed both prediagnostic (presymptomatic) and diagnostic vaginal samples. We used ultrasensitive droplet digital PCR (ddPCR) (IBSAFE™) and found mutations in diagnostic samples from 75% (6/8) of the patients; however, no mutations were detected in the prediagnostic samples. Despite this ddPCR was able to analyze samples with very limited DNA, where other methods would fail. This provides a basis for the further evaluation of IBSAFE™ in a larger cohort of patients.
In conclusion, these studies further characterized ovarian cancer biology and heterogeniety, and have provided the basis for future studies in ovarian cancer with the potential of improving outcome. (Less)
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author
supervisor
opponent
  • Dr Brenton, James, Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Ovarian cancer, Molecular biology, genetic variant, TP53 mutation, early detection, Drug Screening Assays, Antitumor, bioinformatics, next generation sequencing, NGS, prognostic and predictive biomarkers, ovarian clear cell cancer, high-grade serous ovarian cancer
in
Lund University, Faculty of Medicine Doctoral Dissertation Series
volume
2019
issue
20
pages
100 pages
publisher
Lund University: Faculty of Medicine
defense location
Onkologiklinikens föreläsningssal, Klinikgatan 5, Skånes Universitetssjukhus i Lund
defense date
2019-03-28 13:00:00
ISSN
1652-8220
ISBN
978-91-7619-749-3
language
English
LU publication?
yes
id
36538ded-f6d2-4530-bf76-c1b2b50414c3
date added to LUP
2019-02-18 17:25:17
date last changed
2019-11-19 13:50:06
@phdthesis{36538ded-f6d2-4530-bf76-c1b2b50414c3,
  abstract     = {Ovarian cancer is a heterogeneous disease and recent advances in improving patient outcome have<br/>been limited. It is estimated that a woman’s risk of developing ovarian cancer during her lifetime is about 1 in 70, making it a frequently occurring cancer type in women.<br/>This thesis investigated biological events in ovarian cancer, which were translated into clinically relevant observations using different biomolecular approaches.<br/>Study I investigated the use of sex steroid hormone receptor expression as a prognostic marker in ovarian cancer. We evaluated the expression of estrogen receptor (ER)α, ERβ, progesterone receptor (PR) and androgen receptor (AR) in a cohort of serous and endometrioid cancers. We found that expression of PR and AR was associated with favorable outcome, and co-expression of AR and PR granted an additional prognostic effect. Although we were unable to detect any association between mRNA expression and a favorable outcome in an independent data set, molecular subtypes in the data set differentially expressed PGR and ESR1. Whether this effect accounted for the reported improved outcome in some of the subgroups remains to be investigated.<br/>Study II characterized ovarian clear cell carcinomas (OCCC) with the purpose of identifying potential treatment candidates. OCCC presents a distinct molecular subtype of ovarian cancer, with high chemoresistance. Through integrative bioinformatics we evaluated combined gene expression data, DNA sequencing data and protein expression data from OCCC tumors. The collective data suggested Rho GTPases as a potential treatment candidate in OCCC.<br/>Study III evaluated the effect of targeting Rho GTPases in OCCC using simvastatin and CID-1067700 in OCCC cell lines. All OCCC cell lines were more sensitive to simvastatin as compared to conventional platinum-based chemotherapy. Both of the drugs we evaluated were found to disorganize the cytoskeleton and inhibit migration. The cellular response mechanisms differed between cell lines, however a potential effect on both the PI3K/AKT/mTOR and RAS/ERK pathways was suggested.<br/>Study IV aimed at evaluating the effects of screening prediagnostic liquid based vaginal samples for TP53 mutations, an approach applied for early detection of ovarian cancer. We identified 8 women with somatic TP53 mutations in high-grade serous ovarian cancer (HGSOC) and analyzed both prediagnostic (presymptomatic) and diagnostic vaginal samples. We used ultrasensitive droplet digital PCR (ddPCR) (IBSAFE™) and found mutations in diagnostic samples from 75% (6/8) of the patients; however, no mutations were detected in the prediagnostic samples. Despite this ddPCR was able to analyze samples with very limited DNA, where other methods would fail. This provides a basis for the further evaluation of IBSAFE™ in a larger cohort of patients.<br/>In conclusion, these studies further characterized ovarian cancer biology and heterogeniety, and have provided the basis for future studies in ovarian cancer with the potential of improving outcome.},
  author       = {Arildsen, Nicolai},
  isbn         = {978-91-7619-749-3},
  issn         = {1652-8220},
  language     = {eng},
  number       = {20},
  publisher    = {Lund University: Faculty of Medicine},
  school       = {Lund University},
  series       = {Lund University, Faculty of Medicine Doctoral Dissertation Series},
  title        = {Hunting a Silent Killer. Biomolecular Approaches in Ovarian Cancer},
  url          = {https://lup.lub.lu.se/search/ws/files/61031788/Hunting_a_Silent_Killer_e_spik.pdf},
  volume       = {2019},
  year         = {2019},
}