Small Extracellular Vesicles Isolated from Serum May Serve as Signal-Enhancers for the Monitoring of CNS Tumors
Liquid biopsy-based methods to test biomarkers (e.g., serum proteins and extracellular vesicles) may help to monitor brain tumors. In this proteomics-based study, we aimed to identify a characteristic protein fingerprint associated with central nervous system (CNS) tumors. Overall, 96 human serum sa...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-07-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/21/15/5359 |
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| author | Gabriella Dobra Matyas Bukva Zoltan Szabo Bella Bruszel Maria Harmati Edina Gyukity-Sebestyen Adrienn Jenei Monika Szucs Peter Horvath Tamas Biro Almos Klekner Krisztina Buzas |
| author_facet | Gabriella Dobra Matyas Bukva Zoltan Szabo Bella Bruszel Maria Harmati Edina Gyukity-Sebestyen Adrienn Jenei Monika Szucs Peter Horvath Tamas Biro Almos Klekner Krisztina Buzas |
| author_sort | Gabriella Dobra |
| collection | DOAJ |
| description | Liquid biopsy-based methods to test biomarkers (e.g., serum proteins and extracellular vesicles) may help to monitor brain tumors. In this proteomics-based study, we aimed to identify a characteristic protein fingerprint associated with central nervous system (CNS) tumors. Overall, 96 human serum samples were obtained from four patient groups, namely glioblastoma multiforme (GBM), non-small-cell lung cancer brain metastasis (BM), meningioma (M) and lumbar disc hernia patients (CTRL). After the isolation and characterization of small extracellular vesicles (sEVs) by nanoparticle tracking analysis (NTA) and atomic force microscopy (AFM), liquid chromatography -mass spectrometry (LC-MS) was performed on two different sample types (whole serum and serum sEVs). Statistical analyses (ratio, Cohen’s d, receiver operating characteristic; ROC) were carried out to compare patient groups. To recognize differences between the two sample types, pairwise comparisons (Welch’s test) and ingenuity pathway analysis (IPA) were performed. According to our knowledge, this is the first study that compares the proteome of whole serum and serum-derived sEVs. From the 311 proteins identified, 10 whole serum proteins and 17 sEV proteins showed the highest intergroup differences. Sixty-five proteins were significantly enriched in sEV samples, while 129 proteins were significantly depleted compared to whole serum. Based on principal component analysis (PCA) analyses, sEVs are more suitable to discriminate between the patient groups. Our results support that sEVs have greater potential to monitor CNS tumors, than whole serum. |
| first_indexed | 2024-03-10T18:08:58Z |
| format | Article |
| id | doaj.art-4d945e416bc64a429cfc562433fa582a |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-10T18:08:58Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-4d945e416bc64a429cfc562433fa582a2023-11-20T08:14:30ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672020-07-012115535910.3390/ijms21155359Small Extracellular Vesicles Isolated from Serum May Serve as Signal-Enhancers for the Monitoring of CNS TumorsGabriella Dobra0Matyas Bukva1Zoltan Szabo2Bella Bruszel3Maria Harmati4Edina Gyukity-Sebestyen5Adrienn Jenei6Monika Szucs7Peter Horvath8Tamas Biro9Almos Klekner10Krisztina Buzas11Laboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, H-6726 Szeged, HungaryLaboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, H-6726 Szeged, HungaryDepartment of Medical Chemistry, Faculty of Medicine, University of Szeged, H-6720 Szeged, HungaryDepartment of Medical Chemistry, Faculty of Medicine, University of Szeged, H-6720 Szeged, HungaryLaboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, H-6726 Szeged, HungaryLaboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, H-6726 Szeged, HungaryDepartment of Neurosurgery, Clinical Centre, University of Debrecen, H-4032 Debrecen, HungaryDepartment of Medical Physics and Informatics, Faculty of Medicine, University of Szeged, H-6720 Szeged, HungaryLaboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, H-6726 Szeged, HungaryDepartment of Immunology, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, HungaryDepartment of Neurosurgery, Clinical Centre, University of Debrecen, H-4032 Debrecen, HungaryLaboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, H-6726 Szeged, HungaryLiquid biopsy-based methods to test biomarkers (e.g., serum proteins and extracellular vesicles) may help to monitor brain tumors. In this proteomics-based study, we aimed to identify a characteristic protein fingerprint associated with central nervous system (CNS) tumors. Overall, 96 human serum samples were obtained from four patient groups, namely glioblastoma multiforme (GBM), non-small-cell lung cancer brain metastasis (BM), meningioma (M) and lumbar disc hernia patients (CTRL). After the isolation and characterization of small extracellular vesicles (sEVs) by nanoparticle tracking analysis (NTA) and atomic force microscopy (AFM), liquid chromatography -mass spectrometry (LC-MS) was performed on two different sample types (whole serum and serum sEVs). Statistical analyses (ratio, Cohen’s d, receiver operating characteristic; ROC) were carried out to compare patient groups. To recognize differences between the two sample types, pairwise comparisons (Welch’s test) and ingenuity pathway analysis (IPA) were performed. According to our knowledge, this is the first study that compares the proteome of whole serum and serum-derived sEVs. From the 311 proteins identified, 10 whole serum proteins and 17 sEV proteins showed the highest intergroup differences. Sixty-five proteins were significantly enriched in sEV samples, while 129 proteins were significantly depleted compared to whole serum. Based on principal component analysis (PCA) analyses, sEVs are more suitable to discriminate between the patient groups. Our results support that sEVs have greater potential to monitor CNS tumors, than whole serum.https://www.mdpi.com/1422-0067/21/15/5359extracellular vesiclescancer biomarkerproteomics |
| spellingShingle | Gabriella Dobra Matyas Bukva Zoltan Szabo Bella Bruszel Maria Harmati Edina Gyukity-Sebestyen Adrienn Jenei Monika Szucs Peter Horvath Tamas Biro Almos Klekner Krisztina Buzas Small Extracellular Vesicles Isolated from Serum May Serve as Signal-Enhancers for the Monitoring of CNS Tumors International Journal of Molecular Sciences extracellular vesicles cancer biomarker proteomics |
| title | Small Extracellular Vesicles Isolated from Serum May Serve as Signal-Enhancers for the Monitoring of CNS Tumors |
| title_full | Small Extracellular Vesicles Isolated from Serum May Serve as Signal-Enhancers for the Monitoring of CNS Tumors |
| title_fullStr | Small Extracellular Vesicles Isolated from Serum May Serve as Signal-Enhancers for the Monitoring of CNS Tumors |
| title_full_unstemmed | Small Extracellular Vesicles Isolated from Serum May Serve as Signal-Enhancers for the Monitoring of CNS Tumors |
| title_short | Small Extracellular Vesicles Isolated from Serum May Serve as Signal-Enhancers for the Monitoring of CNS Tumors |
| title_sort | small extracellular vesicles isolated from serum may serve as signal enhancers for the monitoring of cns tumors |
| topic | extracellular vesicles cancer biomarker proteomics |
| url | https://www.mdpi.com/1422-0067/21/15/5359 |
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