Evidence map›Paper›PMID 37875819›Full record

ArticleClinical proteomics2023

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

Narae Kang, Hyun Jeong Oh, Ji Hye Hong, Hyo Eun Moon, Yona Kim, Hyeon-Jeong Lee, Hophil Min, Hyeonji Park, Sang Hun Lee, Sun Ha Paek and 1 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Clinical proteomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 41% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Chaperonin in health and disease.Molecular biomedicine · 2026
    Review
  2. Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 1 country.

Narae Kang *New Drug Development Center, Heungdeok-gu, Chungbuk, Cheongju-si, 28160, Korea.
Hyun Jeong Oh *School of Mechanical Engineering, Korea University, Seoul, 024841, Republic of Korea.
Ji Hye Hong *New Drug Development Center, Heungdeok-gu, Chungbuk, Cheongju-si, 28160, Korea.
Hyo Eun MoonDepartment of Neurosurgery, Cancer Research Institute and Ischemic/Hypoxic Disease Institute, Seoul National University, 28 Yeongeon-dong, Jongno-gu, Seoul, 03080, Korea.
Yona KimDepartment of Neurosurgery, Cancer Research Institute and Ischemic/Hypoxic Disease Institute, Seoul National University, 28 Yeongeon-dong, Jongno-gu, Seoul, 03080, Korea.
Hyeon-Jeong LeeDepartment of Molecular Medicine & Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, 28 Yeongeon-dong, Jongno-gu, Seoul, 03080, Korea.
Hophil MinDoping Control Center, Korea Institute of Science and Technology, Hwarang-ro 14-gil, Seongbuk-gu, Seoul, 02792, Korea.
Hyeonji ParkNew Drug Development Center, Heungdeok-gu, Chungbuk, Cheongju-si, 28160, Korea.
Sang Hun LeeDepartment of Chemical and Biological Engineering, Hanbat National University, Daejeon, 34158, Korea.
Sun Ha Paek *Department of Neurosurgery, Cancer Research Institute and Ischemic/Hypoxic Disease Institute, Seoul National University, 28 Yeongeon-dong, Jongno-gu, Seoul, 03080, Korea. paeksh@snu.ac.kr.
Jonghwa Jin *New Drug Development Center, Heungdeok-gu, Chungbuk, Cheongju-si, 28160, Korea. jichang011@kbiohealth.kr.
Advanced Institute of Convergence Technology · KRSeoul National University · KRHanbat National University · KRKorea Institute of Science and Technology · KRKorea University · KR

Funding

Bio & Medical Technology Development Program of the National Research Foundation 2015M3C7A1028926Bio & Medical Technology Development Program of the National Research Foundation 2020M3A9G8022029Electronics and Telecommunications Research Institute (ETRI) grant funded by the Korean government 21YB1500Institute of Information & communications Technology Planning & Evaluation (IITP) grant NRF-2017M3A9G4052982Institute of Information & communications Technology Planning & Evaluation (IITP) grant NRF-2022M3A9G8082637Soonchunhyang University Research Fund; the National Research Foundation of Korea (NRF) grant funded by the Korea government(MSIT) 2023R1A2C200769911the Korea Research Institute of Bioscience and Biotechnology (KRIBB) Research Initiative Program KGM456212109816the National Research Foundation of Korea Grant NRF2017M3C7A1047392the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) 2020R1C1C1011255
6 · The paper itself

Abstract

Glioblastoma 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.

Indexed as

BiomarkerGlioblastomaMRMPrimary cellQuantitative proteomics

Identifiers

PMID37875819
PMCPMC10598909
OpenAlexW4387903123

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.