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Comprehending the proteomic landscape of ovarian cancer : A road to the discovery of disease biomarkers

Mukherjee, Shuvolina LU ; Sundfeldt, Karin ; Borrebaeck, Carl A.K. LU and Jakobsson, Magnus E. LU (2021) In Proteomes 9(2).
Abstract

Despite recent technological advancements allowing the characterization of cancers at a molecular level along with biomarkers for cancer diagnosis, the management of ovarian cancers (OC) remains challenging. Proteins assume functions encoded by the genome and the complete set of proteins, termed the proteome, reflects the health state. Comprehending the circulatory proteomic profiles for OC subtypes, therefore, has the potential to reveal biomarkers with clinical utility concerning early diagnosis or to predict response to specific therapies. Furthermore, characterization of the proteomic landscape of tumor-derived tissue, cell lines, and PDX models has led to the molecular stratification of patient groups, with implications for... (More)

Despite recent technological advancements allowing the characterization of cancers at a molecular level along with biomarkers for cancer diagnosis, the management of ovarian cancers (OC) remains challenging. Proteins assume functions encoded by the genome and the complete set of proteins, termed the proteome, reflects the health state. Comprehending the circulatory proteomic profiles for OC subtypes, therefore, has the potential to reveal biomarkers with clinical utility concerning early diagnosis or to predict response to specific therapies. Furthermore, characterization of the proteomic landscape of tumor-derived tissue, cell lines, and PDX models has led to the molecular stratification of patient groups, with implications for personalized therapy and management of drug resistance. Here, we review single and multiple marker panels that have been identified through proteomic investigations of patient sera, effusions, and other biospecimens. We discuss their clinical utility and implementation into clinical practice.

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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Biomarkers, Ovarian cancer, Proteomics
in
Proteomes
volume
9
issue
2
article number
25
publisher
MDPI AG
external identifiers
  • scopus:85107317596
  • pmid:34070600
ISSN
2227-7382
DOI
10.3390/proteomes9020025
language
English
LU publication?
yes
id
c154797e-ce05-4be5-8fce-bc9a9cbe361a
date added to LUP
2021-06-24 14:43:43
date last changed
2024-04-20 07:54:01
@article{c154797e-ce05-4be5-8fce-bc9a9cbe361a,
  abstract     = {{<p>Despite recent technological advancements allowing the characterization of cancers at a molecular level along with biomarkers for cancer diagnosis, the management of ovarian cancers (OC) remains challenging. Proteins assume functions encoded by the genome and the complete set of proteins, termed the proteome, reflects the health state. Comprehending the circulatory proteomic profiles for OC subtypes, therefore, has the potential to reveal biomarkers with clinical utility concerning early diagnosis or to predict response to specific therapies. Furthermore, characterization of the proteomic landscape of tumor-derived tissue, cell lines, and PDX models has led to the molecular stratification of patient groups, with implications for personalized therapy and management of drug resistance. Here, we review single and multiple marker panels that have been identified through proteomic investigations of patient sera, effusions, and other biospecimens. We discuss their clinical utility and implementation into clinical practice.</p>}},
  author       = {{Mukherjee, Shuvolina and Sundfeldt, Karin and Borrebaeck, Carl A.K. and Jakobsson, Magnus E.}},
  issn         = {{2227-7382}},
  keywords     = {{Biomarkers; Ovarian cancer; Proteomics}},
  language     = {{eng}},
  number       = {{2}},
  publisher    = {{MDPI AG}},
  series       = {{Proteomes}},
  title        = {{Comprehending the proteomic landscape of ovarian cancer : A road to the discovery of disease biomarkers}},
  url          = {{http://dx.doi.org/10.3390/proteomes9020025}},
  doi          = {{10.3390/proteomes9020025}},
  volume       = {{9}},
  year         = {{2021}},
}