The application of metabolomics in ovarian cancer management: a systematic review

Abstract

Metabolomics, the global analysis of metabolites in a biological specimen, could potentially provide a fast method of biomarker identification for ovarian cancer. This systematic review aims to examine findings from studies that apply metabolomics to the diagnosis, prognosis, treatment, and recurrence of ovarian cancer. A systematic search of English language publications was conducted on PubMed, Science Direct, and SciFinder. It was augmented by a snowball strategy, whereby further relevant studies are identified from reference lists of included studies. Studies in humans with ovarian cancer which focus on metabolomics of biofluids and tumor tissue were included. No restriction was placed on the time of publication. A separate review of targeted metabolomic studies was conducted for completion. Qualitative data were summarized in a comprehensive table. The studies were assessed for quality and risk of bias using the ROBINS-I tool. 32 global studies were included in the main systematic review. Most studies applied metabolomics to diagnosing ovarian cancer, within which the most frequently reported metabolite changes were a down-regulation of phospholipids and amino acids: histidine, citrulline, alanine, and methionine. Dysregulated phospholipid metabolism was also reported in the separately reviewed 18 targeted studies. Generally, combinations of more than one significant metabolite as a panel, in different studies, achieved a higher sensitivity and specificity for diagnosis than a single metabolite; for example, combinations of different phospholipids. Widespread metabolite differences were observed in studies examining prognosis, treatment, and recurrence, and limited conclusions could be drawn. Cellular processes of proliferation and invasion may be reflected in metabolic changes present in poor prognosis and recurrence. For example, lower levels of lysine, with increased cell invasion as an underlying mechanism, or glutamine dependency of rapidly proliferating cancer cells. In conclusion, this review highlights potential metabolites and biochemical pathways which may aid the clinical care of ovarian cancer if further validated.

Wide-Targeted Metabolome Analysis Identifies Potential Biomarkers for Prognosis Prediction of Epithelial Ovarian Cancer

“…Regarding other lipids, a significant increase in TGs and a significant decrease in CEs were observed in EOC patients [ 16 , 18 ]. Previous studies on metabolomic profiling of ovarian cancer patient samples have not reported consistent results on TGs, and there are only a few studies analyzing CEs.…”

“…Reactions involving these amino acids are regulated by the metabolic reprogramming of cancer [ 30 , 31 , 32 ]. In ovarian cancer, decreased levels of methionine, alanine, histidine, tryptophan, lysine, valine, and threonine have been detected [ 16 , 18 ]. Here, we found significantly increased levels of lysine, isoleucine, aspartic acid, glycine, and threonine, and significantly decreased levels of histidine, valine, tryptophan, tyrosine, and glutamine in the plasma of patients with EOC.…”

“…By targeting specific metabolites related to the proliferation, progression, and metastasis of cancer cells, some studies have developed therapeutic strategies for various cancers, thereby demonstrating that metabolomics profiling is a valuable strategy for identifying new cancer risk biomarkers [ 10 , 11 , 12 , 13 , 14 , 15 ]. Recent comparative studies of ovarian cancer patients and healthy female volunteers have identified biomarkers from tissue, plasma, and urine samples [ 16 , 17 , 18 ]. To date, only CA-125, one of the serum cancer antigens, is recommended as a biomarker for diagnosis or follow-up in daily practice but its sensitivity and specificity are not so high against EOC [ 19 ].…”

Precision medicine approaches in metabolic disorders and target organ damage: where are we now, and where are we going?

“…Table 1 illustrates the concept of a personalized Table 1. A personalized approach based on metabolic analysis in some common types of cancer [48,[50][51][52][53]…”

“…Breast Nuclear magnetic resonance metabolomics may be used for phenotyping of breast cancer patients, using different biospecimens, such as tissues, blood serum/plasma, and urine [48] Prostate Some urine metabolomics studies identified consistency in the dysregulation of 15 metabolites, while 18 metabolites were found consistently altered in the prostate tissue, including alanine, arginine, uracil, glutamate, fumarate, and citrate Of great interest are reports of altered valine, taurine, leucine, and citrate as the common denominators in both urine and tissue studies, thereby emphasizing the human metabolome as a promising target for identifying novel biomarkers for prostate cancer diagnosis [51] Ovaries Downregulation of both phospholipids and histidine, citrulline, alanine, and methionine were the most often observed biochemical changes. Compared to a single metabolite, the combination of multiple metabolites as a panel achieved a better diagnostic accuracy [52] Thyroid Identification of novel molecular markers of thyroid cancer promises to help identify distinct disease metabolic phenotypes, which may lead to a more personalized therapy while assisting in both the diagnosis and prediction of disease behavior [53] approach based on metabolic analysis in some common types of cancer.…”