MassIVE MSV000097198

Partial Public PXD061094

Proteomics of bacterial and ovarian cancer ascites extracellular vesicles

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Description

Extracellular vesicles (EVs) are present in body fluids, and they can be 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 benign tumors 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 benign tumors. [doi:10.25345/C5QB9VJ1W] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: bacteria, ovarian cancer, ascites, extracellular vesicles ; DatasetType:Proteomics

Contact

Principal Investigators:
(in alphabetical order) 		Akira Yokoi, Nagoya University, Japan
Submitting User: NU2261Yoshida

Publications

Asano-Inami E, Yokoi A, Yoshida K, Taki K, Kitagawa M, Suzuki K, Uekusa R, Nagao Y, Yoshikawa N, Niimi K, Yamamoto Y, Kajiyama H.
Proteomic Profiling of Bacterial Extracellular Vesicles for Exploring Ovarian Cancer Biomarkers.
J Extracell Biol. 2025 Oct;4(10):e70073. Epub 2025 Oct 8.

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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct technical replicates across all analyses (original submission and reanalyses) associated with this dataset.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
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