Sequential Plasma Metabolome and Proteome Analyses to Develop a Novel Monitoring Strategy for Patients with Epithelial Ovarian Cancer: A Pilot Study

Epithelial ovarian cancer (EOC) is diagnosed at an advanced stage in over half of the patients and its prognosis remains unfavorable. CA125, one of the most frequent positive tumor markers in patients with EOC, has certain limitations. Therefore, more accurate clinical biomarkers are needed. Liquid biopsy with cancer related molecules, such as circulating tumor DNA, is a new option for cancer diagnosis and prognosis. We explored the potential of plasma metabolomic and proteomic analyses as novel monitoring methods for the patients with EOC. Of seven patients, six experienced disease recurrence or progression. CA125 plasma measurements were conducted for disease monitoring. Plasma metabolome and proteome analyses were performed using liquid chromatography-tandem mass spectrometry. Ten and four metabolome indicators were significantly increased and decreased in association with chemotherapeutic resistance, respectively. In addition, thirty-seven and nine proteins displayed high and low levels associated with chemotherapeutic resistance, respectively. Several metabolome pathways and protein concentrations corresponded to the clinical course of each patient. This pilot study suggested the potential of the assessment of metabolome and proteome analysis as a useful tool for developing novel monitoring biomarkers for patients with recurrent EOC.

Authors

Institutions

Publication Details

Journal
International Journal of Molecular Sciences
Published
2025-06-06
DOI
https://doi.org/10.3390/ijms26125435
Citations
2
Primary Topic
Ovarian cancer diagnosis and treatment
Type
article
Field-Weighted Citation Impact
3.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sequential Plasma Metabolome and Proteome Analyses to Develop a Novel Monitoring Strategy for Patients with Epithelial Ovarian Cancer: A Pilot Study

Muneaki Shimada, Yusuke Shibuya, Kengo Kinoshita, Shogo Shigeta et al.
2 citations
International Journal of Molecular Sciences
Ovarian cancer diagnosis and treatment
3.40
article

Sequential Plasma Metabolome and Proteome Analyses to Develop a Novel Monitoring Strategy for Patients with Epithelial Ovarian Cancer: A Pilot Study

Muneaki Shimada, Yusuke Shibuya, Kengo Kinoshita, Shogo Shigeta, S. Koshiba, Jun Yasuda, Yasunobu Okamura, Naomi Matsukawa, Eiji Hishinuma, Ikuko N. Motoike, Takamichi Minato
article en
2 citations

Abstract

Epithelial ovarian cancer (EOC) is diagnosed at an advanced stage in over half of the patients and its prognosis remains unfavorable. CA125, one of the most frequent positive tumor markers in patients with EOC, has certain limitations. Therefore, more accurate clinical biomarkers are needed. Liquid biopsy with cancer related molecules, such as circulating tumor DNA, is a new option for cancer diagnosis and prognosis. We explored the potential of plasma metabolomic and proteomic analyses as novel monitoring methods for the patients with EOC. Of seven patients, six experienced disease recurrence or progression. CA125 plasma measurements were conducted for disease monitoring. Plasma metabolome and proteome analyses were performed using liquid chromatography-tandem mass spectrometry. Ten and four metabolome indicators were significantly increased and decreased in association with chemotherapeutic resistance, respectively. In addition, thirty-seven and nine proteins displayed high and low levels associated with chemotherapeutic resistance, respectively. Several metabolome pathways and protein concentrations corresponded to the clinical course of each patient. This pilot study suggested the potential of the assessment of metabolome and proteome analysis as a useful tool for developing novel monitoring biomarkers for patients with recurrent EOC.

International Journal of Molecular SciencesVol. 26(12)
Tohoku University (JP), Hachinohe Gakuin University (JP), Miyagi Prefectural Hospital Organization (JP), Tohoku Medical Megabank Organization (JP)
Openalex Percentile: Top 8%
Ovarian cancer diagnosis and treatment
3.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.