The Contribution of Lipidomics in Ovarian Cancer Management: A Systematic Review
Lipidomics is a comprehensive study of all lipid components in living cells, serum, plasma, or tissues, with the aim of discovering diagnostic, prognostic, and predictive biomarkers for diseases such as malignant tumors. This systematic review evaluates studies, applying lipidomics to the diagnosis,...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/24/18/13961 |
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| author | Vasiliki Tzelepi Helen Gika Olga Begou Eleni Timotheadou |
| author_facet | Vasiliki Tzelepi Helen Gika Olga Begou Eleni Timotheadou |
| author_sort | Vasiliki Tzelepi |
| collection | DOAJ |
| description | Lipidomics is a comprehensive study of all lipid components in living cells, serum, plasma, or tissues, with the aim of discovering diagnostic, prognostic, and predictive biomarkers for diseases such as malignant tumors. This systematic review evaluates studies, applying lipidomics to the diagnosis, prognosis, prediction, and differentiation of malignant and benign ovarian tumors. A literature search was performed in PubMed, Science Direct, and SciFinder. Only publications written in English after 2012 were included. Relevant citations were identified from the reference lists of primary included studies and were also included in our list. All studies included referred to the application of lipidomics in serum/plasma samples from human cases of OC, some of which also included tumor tissue samples. In some of the included studies, metabolome analysis was also performed, in which other metabolites were identified in addition to lipids. Qualitative data were assessed, and the risk of bias was determined using the ROBINS-I tool. A total of twenty-nine studies were included, fifteen of which applied non-targeted lipidomics, seven applied targeted lipidomics, and seven were reviews relevant to our objectives. Most studies focused on the potential application of lipidomics in the diagnosis of OC and showed that phospholipids and sphingolipids change most significantly during disease development. In conclusion, this systematic review highlights the potential contribution of lipids as biomarkers in OC management. |
| first_indexed | 2024-03-10T22:40:24Z |
| format | Article |
| id | doaj.art-864d2dd9771b41209977cf2886b0b17d |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-10T22:40:24Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-864d2dd9771b41209977cf2886b0b17d2023-11-19T11:05:47ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672023-09-0124181396110.3390/ijms241813961The Contribution of Lipidomics in Ovarian Cancer Management: A Systematic ReviewVasiliki Tzelepi0Helen Gika1Olga Begou2Eleni Timotheadou3Department of Oncology, “Papageorgiou” General Hospital, 56429 Thessaloniki, GreeceBiomic_Auth, Bioanalysis and Omics Lab, Centre for Interdisciplinary Research of Aristotle University of Thessaloniki, Innovation Area of Thessaloniki, 57001 Thermi, GreeceBiomic_Auth, Bioanalysis and Omics Lab, Centre for Interdisciplinary Research of Aristotle University of Thessaloniki, Innovation Area of Thessaloniki, 57001 Thermi, GreeceDepartment of Oncology, “Papageorgiou” General Hospital, 56429 Thessaloniki, GreeceLipidomics is a comprehensive study of all lipid components in living cells, serum, plasma, or tissues, with the aim of discovering diagnostic, prognostic, and predictive biomarkers for diseases such as malignant tumors. This systematic review evaluates studies, applying lipidomics to the diagnosis, prognosis, prediction, and differentiation of malignant and benign ovarian tumors. A literature search was performed in PubMed, Science Direct, and SciFinder. Only publications written in English after 2012 were included. Relevant citations were identified from the reference lists of primary included studies and were also included in our list. All studies included referred to the application of lipidomics in serum/plasma samples from human cases of OC, some of which also included tumor tissue samples. In some of the included studies, metabolome analysis was also performed, in which other metabolites were identified in addition to lipids. Qualitative data were assessed, and the risk of bias was determined using the ROBINS-I tool. A total of twenty-nine studies were included, fifteen of which applied non-targeted lipidomics, seven applied targeted lipidomics, and seven were reviews relevant to our objectives. Most studies focused on the potential application of lipidomics in the diagnosis of OC and showed that phospholipids and sphingolipids change most significantly during disease development. In conclusion, this systematic review highlights the potential contribution of lipids as biomarkers in OC management.https://www.mdpi.com/1422-0067/24/18/13961ovarian cancerdiagnosticprognosticpredictive biomarkerlipidomics |
| spellingShingle | Vasiliki Tzelepi Helen Gika Olga Begou Eleni Timotheadou The Contribution of Lipidomics in Ovarian Cancer Management: A Systematic Review International Journal of Molecular Sciences ovarian cancer diagnostic prognostic predictive biomarker lipidomics |
| title | The Contribution of Lipidomics in Ovarian Cancer Management: A Systematic Review |
| title_full | The Contribution of Lipidomics in Ovarian Cancer Management: A Systematic Review |
| title_fullStr | The Contribution of Lipidomics in Ovarian Cancer Management: A Systematic Review |
| title_full_unstemmed | The Contribution of Lipidomics in Ovarian Cancer Management: A Systematic Review |
| title_short | The Contribution of Lipidomics in Ovarian Cancer Management: A Systematic Review |
| title_sort | contribution of lipidomics in ovarian cancer management a systematic review |
| topic | ovarian cancer diagnostic prognostic predictive biomarker lipidomics |
| url | https://www.mdpi.com/1422-0067/24/18/13961 |
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