Cargando…

Space- and Time-Resolved Metabolomics of a High-Grade Serous Ovarian Cancer Mouse Model

SIMPLE SUMMARY: The underlying mechanisms associated with ovarian cancer progression remain largely unknown, making it one of the most lethal cancers. To understand the disease pathogenesis, our study involved longitudinal serum metabolomics profiling of a triple-mutant mouse model of ovarian cancer...

Descripción completa

Detalles Bibliográficos
Autores principales: Sah, Samyukta, Ma, Xin, Botros, Andro, Gaul, David A., Yun, Sylvia R., Park, Eun Young, Kim, Olga, Moore, Samuel G., Kim, Jaeyeon, Fernández, Facundo M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104348/
https://www.ncbi.nlm.nih.gov/pubmed/35565391
http://dx.doi.org/10.3390/cancers14092262
_version_ 1784707772565159936
author Sah, Samyukta
Ma, Xin
Botros, Andro
Gaul, David A.
Yun, Sylvia R.
Park, Eun Young
Kim, Olga
Moore, Samuel G.
Kim, Jaeyeon
Fernández, Facundo M.
author_facet Sah, Samyukta
Ma, Xin
Botros, Andro
Gaul, David A.
Yun, Sylvia R.
Park, Eun Young
Kim, Olga
Moore, Samuel G.
Kim, Jaeyeon
Fernández, Facundo M.
author_sort Sah, Samyukta
collection PubMed
description SIMPLE SUMMARY: The underlying mechanisms associated with ovarian cancer progression remain largely unknown, making it one of the most lethal cancers. To understand the disease pathogenesis, our study involved longitudinal serum metabolomics profiling of a triple-mutant mouse model of ovarian cancer that captured the dynamic metabolic response from disease onset until mouse death. These experiments were complemented with spatial lipidomic profiling of the entire reproductive system of the triple-mutant mice, enabling us to visualize the tissue heterogeneity and lipid alterations within tumors. A combined longitudinal and spatial map of metabolomic alterations associated with ovarian cancer progression is presented, serving as a comprehensive guide towards understanding the disease origin and progression. ABSTRACT: The dismally low survival rate of ovarian cancer patients diagnosed with high-grade serous carcinoma (HGSC) emphasizes the lack of effective screening strategies. One major obstacle is the limited knowledge of the underlying mechanisms of HGSC pathogenesis at very early stages. Here, we present the first 10-month time-resolved serum metabolic profile of a triple mutant (TKO) HGSC mouse model, along with the spatial lipidome profile of its entire reproductive system. A high-coverage liquid chromatography mass spectrometry-based metabolomics approach was applied to longitudinally collected serum samples from both TKO (n = 15) and TKO control mice (n = 15), tracking metabolome and lipidome changes from premalignant stages to tumor initiation, early stages, and advanced stages until mouse death. Time-resolved analysis showed specific temporal trends for 17 lipid classes, amino acids, and TCA cycle metabolites, associated with HGSC progression. Spatial lipid distributions within the reproductive system were also mapped via ultrahigh-resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry and compared with serum lipid profiles for various lipid classes. Altogether, our results show that the remodeling of lipid and fatty acid metabolism, amino acid biosynthesis, TCA cycle and ovarian steroidogenesis are critical components of HGSC onset and development. These metabolic alterations are accompanied by changes in energy metabolism, mitochondrial and peroxisomal function, redox homeostasis, and inflammatory response, collectively supporting tumorigenesis.
format Online
Article
Text
id pubmed-9104348
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-91043482022-05-14 Space- and Time-Resolved Metabolomics of a High-Grade Serous Ovarian Cancer Mouse Model Sah, Samyukta Ma, Xin Botros, Andro Gaul, David A. Yun, Sylvia R. Park, Eun Young Kim, Olga Moore, Samuel G. Kim, Jaeyeon Fernández, Facundo M. Cancers (Basel) Article SIMPLE SUMMARY: The underlying mechanisms associated with ovarian cancer progression remain largely unknown, making it one of the most lethal cancers. To understand the disease pathogenesis, our study involved longitudinal serum metabolomics profiling of a triple-mutant mouse model of ovarian cancer that captured the dynamic metabolic response from disease onset until mouse death. These experiments were complemented with spatial lipidomic profiling of the entire reproductive system of the triple-mutant mice, enabling us to visualize the tissue heterogeneity and lipid alterations within tumors. A combined longitudinal and spatial map of metabolomic alterations associated with ovarian cancer progression is presented, serving as a comprehensive guide towards understanding the disease origin and progression. ABSTRACT: The dismally low survival rate of ovarian cancer patients diagnosed with high-grade serous carcinoma (HGSC) emphasizes the lack of effective screening strategies. One major obstacle is the limited knowledge of the underlying mechanisms of HGSC pathogenesis at very early stages. Here, we present the first 10-month time-resolved serum metabolic profile of a triple mutant (TKO) HGSC mouse model, along with the spatial lipidome profile of its entire reproductive system. A high-coverage liquid chromatography mass spectrometry-based metabolomics approach was applied to longitudinally collected serum samples from both TKO (n = 15) and TKO control mice (n = 15), tracking metabolome and lipidome changes from premalignant stages to tumor initiation, early stages, and advanced stages until mouse death. Time-resolved analysis showed specific temporal trends for 17 lipid classes, amino acids, and TCA cycle metabolites, associated with HGSC progression. Spatial lipid distributions within the reproductive system were also mapped via ultrahigh-resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry and compared with serum lipid profiles for various lipid classes. Altogether, our results show that the remodeling of lipid and fatty acid metabolism, amino acid biosynthesis, TCA cycle and ovarian steroidogenesis are critical components of HGSC onset and development. These metabolic alterations are accompanied by changes in energy metabolism, mitochondrial and peroxisomal function, redox homeostasis, and inflammatory response, collectively supporting tumorigenesis. MDPI 2022-04-30 /pmc/articles/PMC9104348/ /pubmed/35565391 http://dx.doi.org/10.3390/cancers14092262 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sah, Samyukta
Ma, Xin
Botros, Andro
Gaul, David A.
Yun, Sylvia R.
Park, Eun Young
Kim, Olga
Moore, Samuel G.
Kim, Jaeyeon
Fernández, Facundo M.
Space- and Time-Resolved Metabolomics of a High-Grade Serous Ovarian Cancer Mouse Model
title Space- and Time-Resolved Metabolomics of a High-Grade Serous Ovarian Cancer Mouse Model
title_full Space- and Time-Resolved Metabolomics of a High-Grade Serous Ovarian Cancer Mouse Model
title_fullStr Space- and Time-Resolved Metabolomics of a High-Grade Serous Ovarian Cancer Mouse Model
title_full_unstemmed Space- and Time-Resolved Metabolomics of a High-Grade Serous Ovarian Cancer Mouse Model
title_short Space- and Time-Resolved Metabolomics of a High-Grade Serous Ovarian Cancer Mouse Model
title_sort space- and time-resolved metabolomics of a high-grade serous ovarian cancer mouse model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104348/
https://www.ncbi.nlm.nih.gov/pubmed/35565391
http://dx.doi.org/10.3390/cancers14092262
work_keys_str_mv AT sahsamyukta spaceandtimeresolvedmetabolomicsofahighgradeserousovariancancermousemodel
AT maxin spaceandtimeresolvedmetabolomicsofahighgradeserousovariancancermousemodel
AT botrosandro spaceandtimeresolvedmetabolomicsofahighgradeserousovariancancermousemodel
AT gauldavida spaceandtimeresolvedmetabolomicsofahighgradeserousovariancancermousemodel
AT yunsylviar spaceandtimeresolvedmetabolomicsofahighgradeserousovariancancermousemodel
AT parkeunyoung spaceandtimeresolvedmetabolomicsofahighgradeserousovariancancermousemodel
AT kimolga spaceandtimeresolvedmetabolomicsofahighgradeserousovariancancermousemodel
AT mooresamuelg spaceandtimeresolvedmetabolomicsofahighgradeserousovariancancermousemodel
AT kimjaeyeon spaceandtimeresolvedmetabolomicsofahighgradeserousovariancancermousemodel
AT fernandezfacundom spaceandtimeresolvedmetabolomicsofahighgradeserousovariancancermousemodel