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Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis

Ovarian cancer (OC) is a heterogeneous disease with the highest mortality rate and the poorest prognosis among gynecological malignancies. Because of the absence of specific early symptoms, most OC patients are often diagnosed at late stages. Thus, improved biomarkers of OC for use in research and c...

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Detalles Bibliográficos
Autores principales: Xiao, Yinan, Bi, Meiyu, Guo, Hongyan, Li, Mo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035645/
https://www.ncbi.nlm.nih.gov/pubmed/35439677
http://dx.doi.org/10.1016/j.ebiom.2022.104001
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author Xiao, Yinan
Bi, Meiyu
Guo, Hongyan
Li, Mo
author_facet Xiao, Yinan
Bi, Meiyu
Guo, Hongyan
Li, Mo
author_sort Xiao, Yinan
collection PubMed
description Ovarian cancer (OC) is a heterogeneous disease with the highest mortality rate and the poorest prognosis among gynecological malignancies. Because of the absence of specific early symptoms, most OC patients are often diagnosed at late stages. Thus, improved biomarkers of OC for use in research and clinical practice are urgently needed. The last decade has seen increasingly rapid advances in sequencing and biotechnological methodologies. Consequently, multiple omics technologies, including genomic/transcriptomic sequencings and proteomic/metabolomic mass spectra, have been widely applied to analyze tissue- and liquid-derived samples from OC patients. The integration of multi-omics data has increased our knowledge of the disease and identified valuable OC biomarkers. In this review, we summarize the recent advances and perspectives in the use of multi-omics technologies in OC research and highlight potential applications of multi-omics for identifying novel biomarkers and improving clinical assessments.
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spelling pubmed-90356452022-04-26 Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis Xiao, Yinan Bi, Meiyu Guo, Hongyan Li, Mo EBioMedicine Review Ovarian cancer (OC) is a heterogeneous disease with the highest mortality rate and the poorest prognosis among gynecological malignancies. Because of the absence of specific early symptoms, most OC patients are often diagnosed at late stages. Thus, improved biomarkers of OC for use in research and clinical practice are urgently needed. The last decade has seen increasingly rapid advances in sequencing and biotechnological methodologies. Consequently, multiple omics technologies, including genomic/transcriptomic sequencings and proteomic/metabolomic mass spectra, have been widely applied to analyze tissue- and liquid-derived samples from OC patients. The integration of multi-omics data has increased our knowledge of the disease and identified valuable OC biomarkers. In this review, we summarize the recent advances and perspectives in the use of multi-omics technologies in OC research and highlight potential applications of multi-omics for identifying novel biomarkers and improving clinical assessments. Elsevier 2022-04-16 /pmc/articles/PMC9035645/ /pubmed/35439677 http://dx.doi.org/10.1016/j.ebiom.2022.104001 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review
Xiao, Yinan
Bi, Meiyu
Guo, Hongyan
Li, Mo
Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis
title Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis
title_full Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis
title_fullStr Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis
title_full_unstemmed Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis
title_short Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis
title_sort multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035645/
https://www.ncbi.nlm.nih.gov/pubmed/35439677
http://dx.doi.org/10.1016/j.ebiom.2022.104001
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