Dataset Information

Metabolomics of biomarker discovery in ovarian cancer: a systematic review of the current literature.

ABSTRACT: Metabolomics is the emerging member of "omics" sciences advancing the understanding, diagnosis and treatment of many cancers, including ovarian cancer (OC).To systematically identify the metabolomic abnormalities in OC detection, and the dominant metabolic pathways associated with the observed alterations.An electronic literature search was performed, up to and including January 15th 2016, for studies evaluating the metabolomic profile of patients with OC compared to controls. QUADOMICS tool was used to assess the quality of the twenty-three studies included in this systematic review.Biological samples utilized for metabolomic analysis include: serum/plasma (n = 13), urine (n = 4), cyst fluid (n = 3), tissue (n = 2) and ascitic fluid (n = 1). Metabolites related to cellular respiration, carbohydrate, lipid, protein and nucleotide metabolism were significantly altered in OC. Increased levels of tricarboxylic acid cycle intermediates and altered metabolites of the glycolytic pathway pointed to perturbations in cellular respiration. Alterations in lipid metabolism included enhanced fatty acid oxidation, abnormal levels of glycerolipids, sphingolipids and free fatty acids with common elevations of palmitate, oleate, and myristate. Increased levels of glutamine, glycine, cysteine and threonine were commonly reported while enhanced degradations of tryptophan, histidine and phenylalanine were found. N-acetylaspartate, a brain amino acid, was found elevated in primary and metastatic OC tissue and ovarian cyst fluid. Further, elevated levels of ketone bodies including 3-hydroxybutyrate were commonly reported. Increased levels of nucleotide metabolites and tocopherols were consistent through out the studies.Metabolomics presents significant new opportunities for diagnostic biomarker development, elucidating previously unknown mechanisms of OC pathogenesis.

SUBMITTER: Turkoglu O

PROVIDER: S-EPMC5557039 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Metabolomics of biomarker discovery in ovarian cancer: a systematic review of the current literature.

Turkoglu Onur O Zeb Amna A Graham Stewart S Szyperski Thomas T Szender J Brian JB Odunsi Kunle K Bahado-Singh Ray R

Metabolomics : Official journal of the Metabolomic Society 20160308 4

<h4>Introduction</h4>Metabolomics is the emerging member of "omics" sciences advancing the understanding, diagnosis and treatment of many cancers, including ovarian cancer (OC).<h4>Objectives</h4>To systematically identify the metabolomic abnormalities in OC detection, and the dominant metabolic pathways associated with the observed alterations.<h4>Methods</h4>An electronic literature search was performed, up to and including January 15th 2016, for studies evaluating the metabolomic profile of p ...[more]

PMID: 28819352

Similar Datasets

Project description:While ovarian cancer remains the most lethal gynecological malignancy in the United States, there are no biomarkers available that are able to predict therapeutic responses to ovarian malignancies. One major hurdle in the identification of useful biomarkers has been the ability to obtain enough ovarian cancer cells from primary tissues diagnosed in the early stages of serous carcinomas, the most deadly subtype of ovarian tumor. In order to detect ovarian cancer in a state of hyperproliferation, we analyzed the implications of molecular signaling cascades in the ovarian cancer cell line OVCAR3 in a temporal manner, using a mass-spectrometry-based proteomics approach. OVCAR3 cells were treated with EGF(1), and the time course of cell progression was monitored based on Akt phosphorylation and growth dynamics. EGF-stimulated Akt phosphorylation was detected at 12 h post-treatment, but an effect on proliferation was not observed until 48 h post-exposure. Growth-stimulated cellular lysates were analyzed for protein profiles between treatment groups and across time points using iTRAQ labeling and mass spectrometry. The protein response to EGF treatment was identified via iTRAQ analysis in EGF-stimulated lysates relative to vehicle-treated specimens across the treatment time course. Validation studies were performed on one of the differentially regulated proteins, lysosomal-associated membrane protein 1 (LAMP-1), in human tissue lysates and ovarian tumor tissue sections. Further, tissue microarray analysis was performed to demarcate LAMP-1 expression across different stages of epithelial ovarian cancers. These data support the use of this approach for the efficient identification of tissue-based markers in tumor development related to specific signaling pathways. LAMP-1 is a promising biomarker for studies of the progression of EGF-stimulated ovarian cancers and might be useful in predicting treatment responses involving tyrosine kinase inhibitors or EGF receptor monoclonal antibodies.

Dataset Information

Metabolomics of biomarker discovery in ovarian cancer: a systematic review of the current literature.

Publications

Metabolomics of biomarker discovery in ovarian cancer: a systematic review of the current literature.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets