Proteomic Profiling of Bacterial Extracellular Vesicles for Exploring Ovarian Cancer Biomarkers

Extracellular vesicles (EVs) are present in body fluids and act as disease biomarkers. Emerging evidence has proven that EVs are released not only from mammalian cells but also from bacteria. Ovarian cancer has a dismal prognosis because of difficulties in early detection. This study aimed to identify bacterial EV (BEV) proteins associated with ovarian cancer. Fifteen patients with ovarian cancer or non-cancer were recruited, and EVs were isolated from the ascites. BEVs were recovered from seven in vitro-cultured strains of bacteria present in the vaginal microbiota, and LC-MS/MS analysis was performed. The detected peptide data were annotated to both human and bacterial references, and the human data showed that the profiles of cancer EVs were distinct from those of patients with non-cancer. As analysed by bacterial proteins, P15636_Protease1 was found as the BEV-associated protein highly expressed in patients with cancer. To distinguish patients with cancer, the area under the curve was 0.88 (95% CI, 0.64-1.00). In addition, homology analysis showed that P15636_Protease1 is a unique protein only detected in bacteria. In this study, ovarian cancer-specific bacterial proteins were identified on EVs, and BEVs in bodily fluids are promising in the discovery of disease biomarkers.

Authors

Institutions

Publication Details

Journal
Journal of Extracellular Biology
Published
2025-10-01
DOI
https://doi.org/10.1002/jex2.70073
Citations
2
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
1.61

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Proteomic Profiling of Bacterial Extracellular Vesicles for Exploring Ovarian Cancer Biomarkers

Masami Kitagawa, Kosuke Yoshida, Yukari Nagao, Ryosuke Uekusa et al.
2 citations
Journal of Extracellular Biology
Extracellular vesicles in disease
1.61
article

Proteomic Profiling of Bacterial Extracellular Vesicles for Exploring Ovarian Cancer Biomarkers

Masami Kitagawa, Kosuke Yoshida, Yukari Nagao, Ryosuke Uekusa, Eri Asano‐Inami, Kentaro Taki, Yusuke Yamamoto, Kazuhiro Suzuki, Nobuhisa Yoshikawa, Kaoru Niimi, Akira Yokoi, Hiroaki Kajiyama
article en
2 citations

Abstract

Extracellular vesicles (EVs) are present in body fluids and act as disease biomarkers. Emerging evidence has proven that EVs are released not only from mammalian cells but also from bacteria. Ovarian cancer has a dismal prognosis because of difficulties in early detection. This study aimed to identify bacterial EV (BEV) proteins associated with ovarian cancer. Fifteen patients with ovarian cancer or non-cancer were recruited, and EVs were isolated from the ascites. BEVs were recovered from seven in vitro-cultured strains of bacteria present in the vaginal microbiota, and LC-MS/MS analysis was performed. The detected peptide data were annotated to both human and bacterial references, and the human data showed that the profiles of cancer EVs were distinct from those of patients with non-cancer. As analysed by bacterial proteins, P15636_Protease1 was found as the BEV-associated protein highly expressed in patients with cancer. To distinguish patients with cancer, the area under the curve was 0.88 (95% CI, 0.64-1.00). In addition, homology analysis showed that P15636_Protease1 is a unique protein only detected in bacteria. In this study, ovarian cancer-specific bacterial proteins were identified on EVs, and BEVs in bodily fluids are promising in the discovery of disease biomarkers.

Journal of Extracellular BiologyVol. 4(10)
Japan Science and Technology Agency (JP), Nagoya University Hospital (JP), National Cancer Research Institute (GB), Nagoya University (JP)
Naito Foundation, Japan Agency for Medical Research and Development, Japan Society for the Promotion of Science, Japan Science and Technology Agency
Openalex Percentile: Top 14%
Extracellular vesicles in disease
1.61
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.