Browse
Submit Data
Databases
API
Help

Dataset Information

34 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Adipocyte-like signature in ovarian cancer minimal residual disease identifies metabolic vulnerabilities of tumor-initiating cells.

ABSTRACT: Similar to tumor-initiating cells (TICs), minimal residual disease (MRD) is capable of reinitiating tumors and causing recurrence. However, the molecular characteristics of solid tumor MRD cells and drivers of their survival have remained elusive. Here we performed dense multiregion transcriptomics analysis of paired biopsies from 17 ovarian cancer patients before and after chemotherapy. We reveal that while MRD cells share important molecular signatures with TICs, they are also characterized by an adipocyte-like gene expression signature and a portion of them had undergone epithelial-mesenchymal transition (EMT). In a cell culture MRD model, MRD-mimic cells showed the same phenotype and were dependent on fatty acid oxidation (FAO) for survival and resistance to cytotoxic agents. These findings identify EMT and FAO as attractive targets to eradicate MRD in ovarian cancer and make a compelling case for the further testing of FAO inhibitors in treating MRD.

SUBMITTER: Artibani M

PROVIDER: S-EPMC8262282 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

An Adipocyte-like Signature in Ovarian Cancer Minimal Residual Disease Identifies Metabolic Vulnerabilities of Tumor Initiating Cells

Project description:Recurrence and metastasis are the main causes of death for cancer patients. Relapse can also occur when complete response is achieved, due to the Minimal Residual Disease (MRD) cells that survive treatment. Here we show that the knowledge gap in solid tumors MRD biology can be reduced studying ovarian cancer and we provide the first molecular characterization of MRD. Transcriptomics analysis of 120 tumor biopsies from 17 patients with different response to treatment revealed that the MRD cells have a very specific adipocyte-like signature. These cells also upregulate fatty acid oxidation (FAO), displaying a vulnerability that can be targeted therapeutically. These findings identify FAO as an attractive target to eradicate MRD in ovarian cancer and make a compelling case for the use of FAO inhibitors in neo-adjuvant settings.

2021-05-05 | GSE162714 | GEO

An Adipocyte-like Signature in Ovarian Cancer Minimal Residual Disease Identifies Metabolic Vulnerabilities of Tumor Initiating Cells

Project description:An Adipocyte-like Signature in Ovarian Cancer Minimal Residual Disease Identifies Metabolic Vulnerabilities of Tumor Initiating Cells

| PRJNA682733 | ENA

Hypomethylation signature of tumor-initiating cells predicts poor prognosis of ovarian cancer patients.

Project description:DNA methylation contributes to tumor formation, development and metastasis. Epigenetic dysregulation of stem cells is thought to predispose to malignant development. The clinical significance of DNA methylation in ovarian tumor-initiating cells (OTICs) remains unexplored. We analyzed the methylomic profiles of OTICs (CP70sps) and their derived progeny using a human methylation array. qRT-PCR, quantitative methylation-specific PCR (qMSP) and pyrosequencing were used to verify gene expression and DNA methylation in cancer cell lines. The methylation status of genes was validated quantitatively in cancer tissues and correlated with clinicopathological factors. ATG4A and HIST1H2BN were hypomethylated in OTICs. Methylation analysis of ATG4A and HIST1H2BN by qMSP in 168 tissue samples from patients with ovarian cancer showed that HIST1H2BN methylation was a significant and independent predictor of progression-free survival (PFS) and overall survival (OS). Multivariate Cox regression analysis showed that patients with a low level of HIST1H2BN methylation had poor PFS (hazard ratio (HR), 4.5; 95% confidence interval (CI), 1.4-14.8) and OS (HR, 4.3; 95% CI, 1.3-14.0). Hypomethylation of both ATG4A and HIST1H2BN predicted a poor PFS (HR, 1.8; 95% CI, 1.0-3.6; median, 21 months) and OS (HR, 1.7; 95% CI, 1.0-3.0; median, 40 months). In an independent cohort of ovarian tumors, hypomethylation predicted early disease recurrence (HR, 1.7; 95% CI, 1.1-2.5) and death (HR, 1.4; 95% CI, 1.0-1.9). The demonstration that expression of ATG4A in cells increased their stem properties provided an indication of its biological function. Hypomethylation of ATG4A and HIST1H2BN in OTICs predicts a poor prognosis for ovarian cancer patients.

| S-EPMC3943526 | biostudies-literature

Functional Genomics Identifies Metabolic Vulnerabilities in Pancreatic Cancer.

Project description:Pancreatic ductal adenocarcinoma (PDA) is a deadly cancer characterized by complex metabolic adaptations that promote survival in a severely hypoxic and nutrient-limited tumor microenvironment (TME). Modeling microenvironmental influences in cell culture has been challenging, and technical limitations have hampered the comprehensive study of tumor-specific metabolism in vivo. To systematically interrogate metabolic vulnerabilities in PDA, we employed parallel CRISPR-Cas9 screens using in vivo and in vitro systems. This work revealed striking overlap of in vivo metabolic dependencies with those in vitro. Moreover, we identified that intercellular nutrient sharing can mask dependencies in pooled screens, highlighting a limitation of this approach to study tumor metabolism. Furthermore, metabolic dependencies were similar between 2D and 3D culture, although 3D culture may better model vulnerabilities that influence certain oncogenic signaling pathways. Lastly, our work demonstrates the power of genetic screening approaches to define in vivo metabolic dependencies and pathways that may have therapeutic utility.

| S-EPMC7790858 | biostudies-literature

Integrated molecular profiling of patient-derived ovarian cancer models identifies clinically relevant signatures and tumor vulnerabilities.

Project description:High-grade serous ovarian carcinoma (HGSOC) is a highly aggressive and intractable neoplasm, mainly because of its rapid dissemination into the abdominal cavity, a process that is favored by tumor-associated peritoneal ascites. The precise molecular alterations involved in HGSOC onset and progression remain largely unknown due to the high biological and genetic heterogeneity of this tumor. We established a set of different tumor samples (termed the As11-set) derived from a single HGSOC patient, consisting of peritoneal ascites, primary tumor cells, ovarian cancer stem cells (OCSC) and serially propagated tumor xenografts. The As11-set was subjected to an integrated RNA-seq and DNA-seq analysis which unveiled molecular alterations that marked the different types of samples. Our profiling strategy yielded a panel of signatures relevant in HGSOC and in OCSC biology. When such signatures were used to interrogate the TCGA dataset from HGSOC patients, they exhibited prognostic and predictive power. The molecular alterations also identified potential vulnerabilities associated with OCSC, which were then tested functionally in stemness-related assays. As a proof of concept, we defined PI3K signaling as a novel druggable target in OCSC.

| S-EPMC9310611 | biostudies-literature

Metabolic memory underlying minimal residual disease in breast cancer

Project description: Not available

| S-BSST713 | biostudies-other

Metabolic memory underlying minimal residual disease in breast cancer.

Project description:Tumor relapse from treatment-resistant cells (minimal residual disease, MRD) underlies most breast cancer-related deaths. Yet, the molecular characteristics defining their malignancy have largely remained elusive. Here, we integrated multi-omics data from a tractable organoid system with a metabolic modeling approach to uncover the metabolic and regulatory idiosyncrasies of the MRD. We find that the resistant cells, despite their non-proliferative phenotype and the absence of oncogenic signaling, feature increased glycolysis and activity of certain urea cycle enzyme reminiscent of the tumor. This metabolic distinctiveness was also evident in a mouse model and in transcriptomic data from patients following neo-adjuvant therapy. We further identified a marked similarity in DNA methylation profiles between tumor and residual cells. Taken together, our data reveal a metabolic and epigenetic memory of the treatment-resistant cells. We further demonstrate that the memorized elevated glycolysis in MRD is crucial for their survival and can be targeted using a small-molecule inhibitor without impacting normal cells. The metabolic aberrances of MRD thus offer new therapeutic opportunities for post-treatment care to prevent breast tumor recurrence.

| S-EPMC8543468 | biostudies-literature

A metabolic signature of colon cancer initiating cells.

Project description:Colon cancer initiating cells (CCICs) are more tumorigenic and metastatic than the majority of colorectal cancer (CRC) cells. CCICs have also been associated with stem cell-like properties. However, there is a lack of system-level understanding of what mechanisms distinguish CCICs from common CRC cells. We compared the transcriptomes of CD133+ CCICs and CD133- CRC cells from multiple sources, which identified a distinct metabolic signature for CD133(high) CCICs. High-resolution unbiased metabolomics was then performed to validate this CCIC metabolic signature. Specifically, levels of enzymes and metabolites involved in glycolysis, the citric acid (TCA) cycle, and cysteine and methionine metabolism are altered in CCICs. Analyses of the alterations further suggest an epigenetic link. This metabolic signature provides mechanistic insights into CCIC phenotypes and may serve as potential biomarkers and therapeutic targets for future CRC treatment.

| S-EPMC4302416 | biostudies-literature

Integrated analysis identifies different metabolic signatures for tumor-initiating cells in a murine glioblastoma model.

Project description:BackgroundThe metabolic preference of malignant glioma for glycolysis as an energy source is a potential therapeutic target. As a result of the cellular heterogeneity of these tumors, however, the relation between glycolytic preference, tumor formation, and tumor cell clonogenicity has remained unknown. To address this issue, we analyzed the metabolic profiles of isogenic glioma-initiating cells (GICs) in a mouse model.MethodsGICs were established by overexpression of H-Ras(V12) in Ink4a/Arf-null neural stem cells. Subpopulations of these cells were obtained by single-cell cloning, and clones differing in extracellular acidification potential were assessed for metabolic characteristics. Tumors formed after intracranial implantation of these clones in mice were examined for pathological features of glioma and expression of glycolytic enzymes.ResultsMalignant transformation of neural stem cells resulted in a shift in metabolism characterized by an increase in lactic acid production. However, isogenic clonal populations of GICs manifested pronounced differences in glucose and oxygen consumption, lactate production, and nucleoside levels. These differences were paralleled by differential expression of glycolytic enzymes such as hexokinase 2 and pyruvate kinase M2, with this differential expression also being evident in tumors formed by these clones in vivo.ConclusionsThe metabolic characteristics of glioma cells appear early during malignant transformation and persist until the late stages of tumor formation. Even isogenic clones may be heterogeneous in terms of metabolic features, however, suggesting that a more detailed understanding of the metabolic profile of glioma is imperative for effective therapeutic targeting.

| S-EPMC4096179 | biostudies-literature

Minimal residual disease and circulating tumor cells in breast cancer.

Project description:Tumor cell dissemination in bone marrow or other organs is thought to represent an important step in the metastatic process. The detection of bone marrow disseminated tumor cells is associated with worse outcome in early breast cancer. Moreover, the detection of peripheral blood circulating tumor cells is an adverse prognostic factor in metastatic breast cancer, and emerging data suggest that this is also true for early disease. Beyond enumeration, the characterization of these cells has the potential to improve risk assessment, treatment selection and monitoring, and the development of novel therapeutic agents, and to advance our understanding of the biology of metastasis.

| S-EPMC3262191 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data