Evidence map›Paper›PMID 32120790›Full record

ArticleCancers2020

Sphere-Forming Culture for Expanding Genetically Distinct Patient-Derived Glioma Stem Cells by Cellular Growth Rate Screening.

Kayoung Shin, Hyemi Shin, Hee Jin Cho, Hyunju Kang, Jin-Ku Lee, Yun Jee Seo, Yong Jae Shin, Donggeon Kim, Harim Koo, Doo-Sik Kong and 4 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 45% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 4 institutions in 1 country.

Kayoung ShinDepartment of Health Sciences and Technology, Samsung Advanced Institute for Health Science and Technology, Sungkyunkwan University, Seoul 06531, Korea.
Hyemi ShinResearch Institute for Future Medicine, Samsung Medical Center, Seoul 06351, Korea.
Hee Jin ChoResearch Institute for Future Medicine, Samsung Medical Center, Seoul 06351, Korea.
Hyunju KangGraduate School of Biomedical Science, Ajou University School of Medicine, Suwon 16499, Korea.
Jin-Ku LeeGraduate School of Biomedical Science, Ajou University School of Medicine, Suwon 16499, Korea.
Yun Jee SeoResearch Institute for Future Medicine, Samsung Medical Center, Seoul 06351, Korea.
Yong Jae ShinResearch Institute for Future Medicine, Samsung Medical Center, Seoul 06351, Korea.
Donggeon KimResearch Institute for Future Medicine, Samsung Medical Center, Seoul 06351, Korea.
Harim KooDepartment of Health Sciences and Technology, Samsung Advanced Institute for Health Science and Technology, Sungkyunkwan University, Seoul 06531, Korea.
Doo-Sik KongDepartment of Neurosurgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06531, Korea.
Ho Jun SeolDepartment of Neurosurgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06531, Korea.
Jung-Il LeeDepartment of Neurosurgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06531, Korea.
Hye Won LeeDepartment of Hospital Medicine, Yonsei University College of Medicine, Seoul 03722, Korea.
Do-Hyun NamDepartment of Health Sciences and Technology, Samsung Advanced Institute for Health Science and Technology, Sungkyunkwan University, Seoul 06531, Korea.
Samsung Medical Center · KRSamsung (South Korea) · KRAjou University · KRYonsei University · KR

Funding

Korean Government (MSIP) NRF-2016R1A5A2945889Ministry of Education, Republic of Korea NRF-2017R1A2B4011780Ministry of health & welfare, Republic of Korea HI14C3418
6 · The paper itself

Abstract

Diffusely infiltrating gliomas (DIGs) are difficult to completely resect and are associated with a high rate of tumor relapse and progression from low- to high-grade glioma. In particular, optimized short-term culture-enriching patient-derived glioma stem cells (GSCs) are essential for customizing the therapeutic strategy based on clinically feasible in vitro drug screening for a wide range of DIGs, owing to the high inter-tumoral heterogeneity. Herein, we constructed a novel high-throughput culture condition screening platform called 'GFSCAN', which evaluated the cellular growth rates of GSCs for each DIG sample in 132 serum-free combinations, using 13 previously reported growth factors closely associated with glioma aggressiveness. In total, 72 patient-derived GSCs with available genomic profiles were tested in GFSCAN to explore the association between cellular growth rates in specific growth factor combinations and genomic/molecular backgrounds, including isocitrate dehydrogenase 1 (IDH1) mutation, chromosome arm 1p and 19q co-deletion, ATRX chromatin remodeler alteration, and transcriptional subtype. GSCs were clustered according to the dependency on epidermal growth factor and basic fibroblast growth factor (E&F), and isocitrate dehydrogenase 1 (IDH1) wild-type GSCs showed higher E&F dependencies than IDH1 mutant GSCs. More importantly, we elucidated optimal combinations for IDH1 mutant glioblastoma and lower grade glioma GSCs with low dependencies on E&F, which could be an aid in clinical decision-making for these DIGs. Thus, we demonstrated the utility of GFSCAN in personalizing in vitro cultivation to nominate personalized therapeutic options, in a clinically relevant time frame, for individual DIG patients, where standard clinical options have been exhausted.

Indexed as

diffuse infiltrating gliomagenomic profilingglioma stem cellsgrowth factorpersonalized medicineshort-term cultivation screening platform

Identifiers

PMID32120790
PMCPMC7139415
OpenAlexW3010316650

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.