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The application of metabolomics in ovarian cancer management: a systematic review
  1. Yousra Ahmed-Salim1,
  2. Nicolas Galazis2,
  3. Timothy Bracewell-Milnes3,
  4. David L Phelps4,
  5. Benjamin P Jones5,
  6. Maxine Chan6,
  7. Maria D Munoz-Gonzales7,
  8. Tomoko Matsuzono8,
  9. James Richard Smith9,
  10. Joseph Yazbek9,
  11. Jonathan Krell9,
  12. Sadaf Ghaem-Maghami10 and
  13. Srdjan Saso5
  1. 1Hillingdon Hospitals NHS Foundation Trust, Uxbridge, UK
  2. 2Department of Obstetrics and Gynaecology, Northwick Park Hospital, Harrow, UK
  3. 3Department of Obstetrics and Gynaecology, Chelsea and Westminster Hospital, London, UK
  4. 4Department of Gynaecological Oncology, Hammersmith Hospital Campus, Du Cane Road, Imperial College Healthcare NHS Trust, London, UK
  5. 5Division of Surgery and Cancer, Institute of Reproductive and Developmental Biology, Hammersmith Hospital Campus, Du Cane Road, Imperial College London, London, UK
  6. 6South Kensington Campus, Imperial College London Department of Materials, London, UK
  7. 7Department of Gynaecology, Ramon y Cajal University Hospital, Madrid, Spain
  8. 8Queen Elizabeth Hospital, Department of Obstetrics and Gynaecology, Hong Kong, Hong Kong
  9. 9West London Gynaecological Cancer Centre, Queen Charlotte’s Hospital, Hammersmith Hospital Campus, Du Cane Road, Imperial College Healthcare NHS Trust, London, UK
  10. 10Department of Gynaecological Oncology, West London Gynaecological Cancer Centre, Queen Charlotte’s Hospital, Hammersmith Hospital Campus, Imperial College London and NHS Trust, Du Cane Road, Imperial College London, London, UK
  1. Correspondence to Dr Srdjan Saso, Division of Surgery and Cancer, Institute of Reproductive and Developmental Biology, Hammersmith Hospital Campus, Du Cane Road, Imperial College London, London, UK; srdjan.saso01{at}imperial.ac.uk

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.

  • ovarian cancer

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Footnotes

  • Contributors YA-S and NG were the main contributors in preparation, writing, and revision of the manuscript and gathering of data. MDM-G and TM were responsible for data extraction. DLP, BPJ, MC, and TB-M were responsible for independently cross-checking the study search, data extraction, and quality assessment as well as revision of the manuscript. JRS, SG-M, JK, and JY contributed to the revision for important intellectual content. SS was responsible for the original manuscript design and drafting. In addition, he is also the guarantor for this paper and accepts full responsibility for the work and/or the conduct of the study.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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