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Glial cell proteome using targeted quantitative methods for potential multi-diagnostic biomarkers

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dc.contributor.authorKang, Narae-
dc.contributor.authorOh, Hyun Jeong-
dc.contributor.authorHong, Ji Hye-
dc.contributor.authorMoon, Hyo Eun-
dc.contributor.authorKim, Yona-
dc.contributor.authorLee, Hyeon-Jeong-
dc.contributor.authorMin, Hophil-
dc.contributor.authorPark, Hyeonji-
dc.contributor.authorLee, Sang Hun-
dc.contributor.authorPeak, Sun Ha-
dc.contributor.authorJin, Jonghwa-
dc.date.accessioned2023-10-30T01:18:03Z-
dc.date.available2023-10-30T10:18:49Z-
dc.date.issued2023-10-24-
dc.identifier.citationClinical Proteomics, Vol.20(1):45ko_KR
dc.identifier.issn1559-0275-
dc.identifier.urihttps://hdl.handle.net/10371/195799-
dc.description.abstractGlioblastoma is one of the most malignant primary brain cancer. Despite surgical resection with modern technology followed by chemo-radiation therapy with temozolomide, resistance to the treatment and recurrence is common due to its aggressive and infiltrating nature of the tumor with high proliferation index. The median survival time of the patients with glioblastomas is less than 15 months. Till now there has been no report of molecular target specific for glioblastomas. Early diagnosis and development of molecular target specific for glioblastomas are essential for longer survival of the patients with glioblastomas. Development of biomarkers specific for glioblastomas is most important for early diagnosis, estimation of the prognosis, and molecular target therapy of glioblastomas. To that end, in this study, we have conducted a comprehensive proteome study using primary cells and tissues from patients with glioblastoma. In the discovery stage, we have identified 7429 glioblastoma-specific proteins, where 476 proteins were quantitated using Tandem Mass Tag (TMT) method; 228 and 248 proteins showed up and down-regulated pattern, respectively. In the validation stage (20 selected target proteins), we developed quantitative targeted method (MRM: Multiple reaction monitoring) using stable isotope standards (SIS) peptide. In this study, five proteins (CCT3, PCMT1, TKT, TOMM34, UBA1) showed the significantly different protein levels (t-test: p value ≤ 0.05, AUC ≥ 0.7) between control and cancer groups and the result of multiplex assay using logistic regression showed the 5-marker panel showed better sensitivity (0.80 and 0.90), specificity (0.92 and 1.00), error rate (10 and 2%), and AUC value (0.94 and 0.98) than the best single marker (TOMM34) in primary cells and tissues, respectively. Although we acknowledge that the model requires further validation in a large sample size, the 5 protein marker panel can be used as baseline data for the discovery of novel biomarkers of the glioblastoma.ko_KR
dc.description.sponsorshipThis work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. NRF-2017M3A9G4052982, NRF-2022M3A9G8082637) This research was partly supported by the Bio & Medical Technology Development Program of the National Research Foundation (Grant Nos. 2015M3C7A1028926 & 2020M3A9G8022029); the National Research Foundation of Korea Grant (Grant No. NRF2017M3C7A1047392) of the Ministry of Science and ICT, Republic of Korea; the Korea Research Institute of Bioscience and Biotechnology (KRIBB) Research Initiative Program (KGM456212109816); Electronics and Telecommunications Research Institute (ETRI) grant funded by the Korean government (21YB1500); Soonchunhyang University Research Fund; the National Research Foundation of Korea (NRF) grant funded by the Korea government(MSIT) (No. 2023R1A2C200769911). H.J. Oh was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1C1C1011255) and a Korea University Grantko_KR
dc.language.isoenko_KR
dc.publisherBMCko_KR
dc.subjectMRM-
dc.subjectGlioblastoma-
dc.subjectPrimary cell-
dc.subjectBiomarker-
dc.subjectQuantitative proteomics-
dc.titleGlial cell proteome using targeted quantitative methods for potential multi-diagnostic biomarkersko_KR
dc.typeArticleko_KR
dc.identifier.doi10.1186/s12014-023-09432-xko_KR
dc.citation.journaltitleClinical Proteomicsko_KR
dc.language.rfc3066en-
dc.rights.holderBioMed Central Ltd., part of Springer Nature-
dc.date.updated2023-10-29T04:14:14Z-
dc.citation.number1ko_KR
dc.citation.volume20ko_KR
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