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Distinct metabolic responses of an ovarian cancer stem cell line.

ABSTRACT: BACKGROUND: Cancer metabolism is emerging as an important focus area in cancer research. However, the in vitro cell culture conditions under which much cellular metabolism research is performed differ drastically from in vivo tumor conditions, which are characterized by variations in the levels of oxygen, nutrients like glucose, and other molecules like chemotherapeutics. Moreover, it is important to know how the diverse cell types in a tumor, including cancer stem cells that are believed to be a major cause of cancer recurrence, respond to these variations. Here, in vitro environmental perturbations designed to mimic different aspects of the in vivo environment were used to characterize how an ovarian cancer cell line and its derived, isogenic cancer stem cells metabolically respond to environmental cues. RESULTS: Mass spectrometry was used to profile metabolite levels in response to in vitro environmental perturbations. Docetaxel, the chemotherapeutic used for this experiment, caused significant metabolic changes in amino acid and carbohydrate metabolism in ovarian cancer cells, but had virtually no metabolic effect on isogenic ovarian cancer stem cells. Glucose deprivation, hypoxia, and the combination thereof altered ovarian cancer cell and cancer stem cell metabolism to varying extents for the two cell types. Hypoxia had a much larger effect on ovarian cancer cell metabolism, while glucose deprivation had a greater effect on ovarian cancer stem cell metabolism. Core metabolites and pathways affected by these perturbations were identified, along with pathways that were unique to cell types or perturbations. CONCLUSIONS: The metabolic responses of an ovarian cancer cell line and its derived isogenic cancer stem cells differ greatly under most conditions, suggesting that these two cell types may behave quite differently in an in vivo tumor microenvironment. While cancer metabolism and cancer stem cells are each promising potential therapeutic targets, such varied behaviors in vivo would need to be considered in the design and early testing of such treatments.

SUBMITTER: Vermeersch KA

PROVIDER: S-EPMC4308021 | biostudies-other | 2014

REPOSITORIES: biostudies-other

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Distinct metabolic responses of an ovarian cancer stem cell line.

Vermeersch Kathleen A KA Wang Lijuan L McDonald John F JF Styczynski Mark P MP

BMC systems biology 20141218

<h4>Background</h4>Cancer metabolism is emerging as an important focus area in cancer research. However, the in vitro cell culture conditions under which much cellular metabolism research is performed differ drastically from in vivo tumor conditions, which are characterized by variations in the levels of oxygen, nutrients like glucose, and other molecules like chemotherapeutics. Moreover, it is important to know how the diverse cell types in a tumor, including cancer stem cells that are believed ...[more]

PMID: 25518943

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Project description:<h4>Background</h4>Cancer metabolism is emerging as an important focus area in cancer research. However, the in vitro cell culture conditions under which much cellular metabolism research is performed differ drastically from in vivo tumor conditions, which are characterized by variations in the levels of oxygen, nutrients like glucose, and other molecules like chemotherapeutics. Moreover, it is important to know how the diverse cell types in a tumor, including cancer stem cells that are believed to be a major cause of cancer recurrence, respond to these variations. Here, in vitro environmental perturbations designed to mimic different aspects of the in vivo environment were used to characterize how an ovarian cancer cell line and its derived, isogenic cancer stem cells metabolically respond to environmental cues.<h4>Results</h4>Mass spectrometry was used to profile metabolite levels in response to in vitro environmental perturbations. Docetaxel, the chemotherapeutic used for this experiment, caused significant metabolic changes in amino acid and carbohydrate metabolism in ovarian cancer cells, but had virtually no metabolic effect on isogenic ovarian cancer stem cells. Glucose deprivation, hypoxia, and the combination thereof altered ovarian cancer cell and cancer stem cell metabolism to varying extents for the two cell types. Hypoxia had a much larger effect on ovarian cancer cell metabolism, while glucose deprivation had a greater effect on ovarian cancer stem cell metabolism. Core metabolites and pathways affected by these perturbations were identified, along with pathways that were unique to cell types or perturbations.<h4>Conclusions</h4>The metabolic responses of an ovarian cancer cell line and its derived isogenic cancer stem cells differ greatly under most conditions, suggesting that these two cell types may behave quite differently in an in vivo tumor microenvironment. While cancer metabolism and cancer stem cells are each promising potential therapeutic targets, such varied behaviors in vivo would need to be considered in the design and early testing of such treatments.

Project description:Ovarian Cancer is the fifth most common cancer in females and remains the most lethal gynecological malignancy as most patients are diagnosed at late stages of the disease. Despite initial responses to therapy, recurrence of chemo-resistant disease is common. The presence of residual cancer stem cells (CSCs) with the unique ability to adapt to several metabolic and signaling pathways represents a major challenge in developing novel targeted therapies. The objective of this study is to investigate the transcripts of putative ovarian cancer stem cell (OCSC) markers in correlation with transcripts of receptors, transporters, and enzymes of the energy generating metabolic pathways involved in high grade serous ovarian cancer (HGSOC). We conducted correlative analysis in data downloaded from The Cancer Genome Atlas (TCGA), studies of experimental OCSCs and their parental lines from Gene Expression Omnibus (GEO), and Cancer Cell Line Encyclopedia (CCLE). We found positive correlations between the transcripts of OCSC markers, specifically CD44, and glycolytic markers. TCGA datasets revealed that NOTCH1, CD133, CD44, CD24, and ALDH1A1, positively and significantly correlated with tricarboxylic acid cycle (TCA) enzymes. OVCAR3-OCSCs (cancer stem cells derived from a well-established epithelial ovarian cancer cell line) exhibited enrichment of the electron transport chain (ETC) mainly in complexes I, III, IV, and V, further supporting reliance on the oxidative phosphorylation (OXPHOS) phenotype. OVCAR3-OCSCs also exhibited significant increase in CD36, ACACA, SCD, and CPT1A, with CD44, CD133, and ALDH1A1 exhibiting positive correlations with lipid metabolic enzymes. TCGA data show positive correlations between OCSC markers and glutamine metabolism enzymes, whereas in OCSC experimental models of GSE64999, GSE28799, and CCLE, the number of positive and negative correlations observed was significantly lower and was different between model systems. Appropriate integration and validation of data model systems with those in patients' specimens is needed not only to bridge our knowledge gap of metabolic programing of OCSCs, but also in designing novel strategies to target the metabolic plasticity of dormant, resistant, and CSCs.

Project description:Ovarian cancer is a complicated malady associated with cancer stem cells (CSCs) contributing to 238,700 estimated new cases and 151,900 deaths per year, worldwide. CSCs comprise a tiny fraction of tumor-bulk responsible for cancer recurrence and eventual mortality. CSCs or tumor initiating cells are responsible for self-renewal, differentiation and proliferative potential, tumor initiation capability, its progression, drug resistance and metastatic spread. Although several biomarkers are implicated in these processes, their distribution within the ovary and association with single cell type has neither been established nor demonstrated across ovarian tumor developmental stages. Therefore, precise identification, thorough characterization and effective targeted destruction of dormant and highly proliferating potent CSC populations is an immediate need.In view of this, distribution of various CSC (ALDH1/2, C-KIT, CD133, CD24 and CD44) and cell proliferation (KI67) specific markers in the ovarian surface epithelium (OSE) and cortex regions in normal ovary, and benign, borderline and high grade metastatic ovarian tumors by immuno-histochemistry and confocal microscopy was studied. We further confirmed their expression by RT-PCR analysis. Co-expression analysis of stem cell (OCT4, SSEA4) and CSC (ALDH1/2, CD44 and LGR5) markers with proliferation marker (KI67) in HG tumors revealed dual positive proliferating stem and CSCs, few non-proliferating stem/CSC (SSEA4+/KI67- and ALDH1/2+/KI67-) and only KI67+ cells in cortex, signifying dynamic populations and interesting cellular hierarchy in cortex region. Smaller spherical (? 5 ?m) and larger spindle/elliptical shaped (~?10 ?m) cell populations with high nucleo-cytoplasmic ratio were detected across all samples (including normal ovaries) but with variable distribution and characteristic stage-wise marker expression across different tumor stages.Diverse stem and CSC populations expressing characteristic markers revealing distinct phenotypes (spherical ?5 ?m and spindle/elliptical ~?10 ?m) were distributed within different tumor stages studied signifying dynamic and probable functional hierarchy within these cell types. Involvement of extra-ovarian sites of origin of stem and CSCs requires rigorous evaluation. Quantitative analysis of potent CSC populations, their mechanisms and pathways for self-renewal, chemo-resistance, metastatic spread etc. with respect to various markers studied, will provide better insights and targets for developing effective therapeutics to prevent metastasis and eventually help improve patient mortality.

Project description:BackgroundOVARIAN CARCINOMAS CONSIST OF AT LEAST FIVE DISTINCT DISEASES: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of origin. Molecular characteristics have become the new standard for clinical pathology, however development of tailored type-specific therapies is hampered by a failure of basic research to recognize that model systems used to study these diseases must also be stratified. Unrelated model systems do offer value for study of biochemical processes but specific cellular context needs to be applied to assess relevant therapeutic strategies.MethodsWe have focused on the identification of clear cell carcinoma cell line models. A panel of 32 "ovarian cancer" cell lines has been classified into histotypes using a combination of mutation profiles, IHC mutation-surrogates, and a validated immunohistochemical model. All cell lines were identity verified using STR analysis.ResultsMany described ovarian clear cell lines have characteristic mutations (including ARID1A and PIK3CA) and an overall molecular/immuno-profile typical of primary tumors. Mutations in TP53 were present in the majority of high-grade serous cell lines. Advanced genomic analysis of bona-fide clear cell carcinoma cell lines also support copy number changes in typical biomarkers such at MET and HNF1B and a lack of any recurrent expressed re-arrangements.ConclusionsAs with primary ovarian tumors, mutation status of cancer genes like ARID1A and TP53 and a general immuno-profile serve well for establishing histotype of ovarian cancer cell We describe specific biomarkers and molecular features to re-classify generic "ovarian carcinoma" cell lines into type specific categories. Our data supports the use of prototype clear cell lines, such as TOV21G and JHOC-5, and questions the use of SKOV3 and A2780 as models of high-grade serous carcinoma.

Dataset Information

Distinct metabolic responses of an ovarian cancer stem cell line.

Publications

Distinct metabolic responses of an ovarian cancer stem cell line.

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