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A Label-Free Proteomic Approach for the Identification of Biomarkers in the Exosome of Endometrial Cancer Serum

Sommella, Eduardo
•
Capaci, Valeria
•
Aloisio, Michelangelo
altro
Ura, Blendi
2022
  • journal article

Periodico
CANCERS
Abstract
Endometrial cancers (ECs) are mostly adenocarcinomas arising from the inner part of the uterus. The identification of serum biomarkers, either soluble or carried in the exosome, may be useful in making an early diagnosis. We used label-free quantification mass spectrometry (LFQ-MS)-based proteomics to investigate the proteome of exosomes in the albumin-depleted serum from 12 patients with EC, as compared to 12 healthy controls. After quantification and statistical analysis, we found significant changes in the abundance (p < 0.05) of 33 proteins in EC vs. control samples, with a fold change of ≥1.5 or ≤0.6. Validation using Western blotting analysis in 36 patients with EC as compared to 36 healthy individuals confirmed the upregulation of APOA1, HBB, CA1, HBD, LPA, SAA4, PF4V1, and APOE. A multivariate logistic regression model based on the abundance of these proteins was able to separate the controls from the EC patients with excellent sensitivity levels, particularly for stage 1 ECs. The results show that using LFQ-MS to explore the specific proteome of serum exosomes allows for the identification of biomarkers in EC. These observations suggest that PF4V1, CA1, HBD, and APOE represent biomarkers that are able to reach the clinical stage, after a validation phase.
DOI
10.3390/cancers14246262
WOS
WOS:000902261200001
Archivio
https://hdl.handle.net/11368/3039958
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85144940625
https://www.mdpi.com/2072-6694/14/24/6262
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9776976/
Diritti
open access
license:creative commons
license:creative commons
license uri:http://creativecommons.org/licenses/by/4.0/
license uri:http://creativecommons.org/licenses/by/4.0/
FVG url
https://arts.units.it/bitstream/11368/3039958/1/A Label-Free Proteomic Approach for the Identification of Biomarkers - Cancers 2022.pdf
Soggetti
  • LFQ-MS

  • biomarker

  • endometrial cancer

  • exosome

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