Evidence map›Paper›PMID 35852875›Full record

ArticleJCI insight2022

An in vivo model of glioblastoma radiation resistance identifies long noncoding RNAs and targetable kinases.

Christian T Stackhouse, Joshua C Anderson, Zongliang Yue, Thanh Nguyen, Nicholas J Eustace, Catherine P Langford, Jelai Wang, James R Rowland, Chuan Xing, Fady M Mikhail and 10 more

Open access · goldAbstract read
In one paragraph

Article in JCI insight, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

15 citing papers in PubMed, 20 citations in OpenAlex.

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  14. Cancer Cells Enter an Adaptive Persistence to Survive Radiotherapy and Repopulate Tumor.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
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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

20 authors at 3 institutions in 1 country.

Christian T StackhouseDepartment of Neurosurgery.
Joshua C AndersonDepartment of Radiation Oncology, and.
Zongliang YueInformatics Institute, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA. Birmingham, Alabama, USA.
Thanh NguyenInformatics Institute, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA. Birmingham, Alabama, USA.
Nicholas J EustaceDepartment of Radiation Oncology, and.
Catherine P LangfordDepartment of Neurosurgery.
Jelai WangInformatics Institute, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA. Birmingham, Alabama, USA.
James R RowlandDepartment of Physics, The Ohio State University, Columbus, Ohio, USA.
Chuan XingDepartment of Radiation Oncology, and.
Fady M MikhailDepartment of Genetics, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA.
Xiangqin CuiDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA.
Hasan AlrefaiDepartment of Radiation Oncology, and.
Ryan E BashDivision of Neuropathology, Department of Pathology, and.
Kevin J LeeDepartment of Radiation Oncology, and.
Eddy S YangDepartment of Radiation Oncology, and.
Anita B HjelmelandDepartment of Cell, Developmental, and Integrative Biology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA.
C Ryan MillerDivision of Neuropathology, Department of Pathology, and.
Jake Y ChenInformatics Institute, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA. Birmingham, Alabama, USA.
G Yancey GillespieDepartment of Neurosurgery.
Christopher D WilleyDepartment of Radiation Oncology, and.
University of Alabama at Birmingham · USEmory University · USThe Ohio State University · US

Funding

Glioblastoma tumor microenvironmental influence on acquired and inherent cancer therapy resistance.U01CA223976 · NCI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI CHEN, JAKE YUE, CUI, XIANGQIN · 2018 to 2022
$4.8M
NCI NIH HHS U01 CA223976
6 · The paper itself

Abstract

Key molecular regulators of acquired radiation resistance in recurrent glioblastoma (GBM) are largely unknown, with a dearth of accurate preclinical models. To address this, we generated 8 GBM patient-derived xenograft (PDX) models of acquired radiation therapy-selected (RTS) resistance compared with same-patient, treatment-naive (radiation-sensitive, unselected; RTU) PDXs. These likely unique models mimic the longitudinal evolution of patient recurrent tumors following serial radiation therapy. Indeed, while whole-exome sequencing showed retention of major genomic alterations in the RTS lines, we did detect a chromosome 12q14 amplification that was associated with clinical GBM recurrence in 2 RTS models. A potentially novel bioinformatics pipeline was applied to analyze phenotypic, transcriptomic, and kinomic alterations, which identified long noncoding RNAs (lncRNAs) and targetable, PDX-specific kinases. We observed differential transcriptional enrichment of DNA damage repair pathways in our RTS models, which correlated with several lncRNAs. Global kinomic profiling separated RTU and RTS models, but pairwise analyses indicated that there are multiple molecular routes to acquired radiation resistance. RTS model-specific kinases were identified and targeted with clinically relevant small molecule inhibitors. This cohort of in vivo RTS patient-derived models will enable future preclinical therapeutic testing to help overcome the treatment resistance seen in patients with GBM.

Indexed as

GlioblastomaRNA, Long NoncodingAnimalsDisease Models, AnimalGenomicsHumansNeoplasm Recurrence, LocalXenograft Model Antitumor AssaysRNA, Long NoncodingBrain cancerNoncoding RNAsOncologyRadiation therapy

Identifiers

PMID35852875
PMCPMC9462495
OpenAlexW4286220325

What Socratic 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 Socratic graph.