Evidence map›Paper›PMID 39315277›Full record

ArticleResearch square2024

Reversal Gene Expression Assessment for Drug Repurposing, a Case Study of Glioblastoma.

Shixue Sun, Zeenat Shyr, Kathleen McDaniel, Yuhong Fang, Dingyin Tao, Catherine Z Chen, Wei Zheng, Qian Zhu

Abstract readPreprint
In one paragraph

Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Shixue SunNCATS: National Center for Advancing Translational Sciences.ORCID 0000-0002-0929-977X
Zeenat ShyrNCATS: National Center for Advancing Translational Sciences.
Kathleen McDanielNCATS ETB: National Center for Advancing Translational Sciences Early Translation Branch.
Yuhong FangNCATS: National Center for Advancing Translational Sciences.
Dingyin TaoNCATS: National Center for Advancing Translational Sciences.
Catherine Z ChenNCATS: National Center for Advancing Translational Sciences.
Wei ZhengNCATS: National Center for Advancing Translational Sciences.
Qian ZhuNCATS: National Center for Advancing Translational Sciences.ORCID 0000-0002-4858-6333

Funding

Drug Repurposing Screening for Rare and Neglected DiseasesZIATR000018 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI ZHENG, WEI · 2015 to 2025
$24.6M
Informatics Research CoreZIATR000410 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI MATHE, EWY · 2020 to 2020
$595k
Intramural NIH HHS ZIA TR000410
6 · The paper itself

Abstract

Glioblastoma (GBM) is a rare brain cancer with an exceptionally high mortality rate, which illustrates the pressing demand for more effective therapeutic options. Despite considerable research efforts on GBM, its underlying biological mechanisms remain unclear. Furthermore, none of the United States Food and Drug Administration (FDA) approved drugs used for GBM deliver satisfactory survival improvement. This study presents a novel computational pipeline by utilizing gene expression data analysis for GBM for drug repurposing to address the challenges in rare disease drug development, particularly focusing on GBM. The GBM Gene Expression Profile (GGEP) was constructed with multi-omics data to identify drugs with reversal gene expression to GGEP from the Integrated Network-Based Cellular Signatures (iLINCS) database. We prioritized the candidates via hierarchical clustering of their expression signatures and quantification of their reversal strength by calculating two self-defined indices based on the GGEP genes' log

Indexed as

Drug RepurposingGlioblastomaMulti-Omics AnalysisRare DiseasesReversal Gene Expression

Identifiers

PMID39315277
PMCPMC11419258

What OpenQuestion holds

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Registered trials

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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.