Evidence mapPaperPMID 41427337Full record

ArticlebioRxiv : the preprint server for biology2025

From

Esraa A Salim, Xiaojia Ji, Michael Tarpley, Maria S Dixon, Weifan Zheng, John E Scott, Kevin P Williams

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

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

7 authors.

Esraa A SalimBiomanufacturing Research Institute and Technology Enterprise, North Carolina Central University, Durham, NC, USA.
Xiaojia JiBiomanufacturing Research Institute and Technology Enterprise, North Carolina Central University, Durham, NC, USA.
Michael TarpleyBiomanufacturing Research Institute and Technology Enterprise, North Carolina Central University, Durham, NC, USA.
Maria S DixonBiomanufacturing Research Institute and Technology Enterprise, North Carolina Central University, Durham, NC, USA.
Weifan ZhengBiomanufacturing Research Institute and Technology Enterprise, North Carolina Central University, Durham, NC, USA.
John E ScottBiomanufacturing Research Institute and Technology Enterprise, North Carolina Central University, Durham, NC, USA.
Kevin P WilliamsBiomanufacturing Research Institute and Technology Enterprise, North Carolina Central University, Durham, NC, USA.ORCID 0000-0002-6930-4630

Funding

Research Capacity CoreU54MD012392 · NORTH CAROLINA CENTRAL UNIVERSITY · 2025 to 2025
$3.4M
Cellular Mechanisms in Fetal Alcohol Spectrum DisordersR01AA026068 · NIAAA · UNIV OF NORTH CAROLINA CHAPEL HILL · 2021 to 2025
$1.7M
Scientific Mentoring and Research Experiences CoreU54AA030451 · NORTH CAROLINA CENTRAL UNIVERSITY · 2025 to 2025
$1.1M
Addressing the Biology of Health Disparities by Targeting Geographical Ancestry-driven Variants of ImmunityR01MD017405 · MOREHOUSE SCHOOL OF MEDICINE · 2025 to 2025
$667k
NIAAA NIH HHS R01 AA026068NIAAA NIH HHS U54 AA030451NIMHD NIH HHS R01 MD017405NIMHD NIH HHS U54 MD012392
6 · The paper itself

Abstract

Drug repurposing offers a promising approach for identifying novel treatments, especially for rare cancers like inflammatory breast cancer (IBC), an aggressive type with limited therapeutic options. Here, we present a comprehensive validation and verification study of compounds identified through two computational approaches: Literature Wide Association Studies (LWAS) and Gene Reversal Rate (GRR), using orthogonal cell viability assays in 2D models across IBC and non-IBC cell lines. In the SUM149 IBC cell line, repurposed compounds predicted from LWAS achieved a 70% success rate, with several showing nanomolar potency, while those predicted from GRR showed a 38% success rate. Through systematic combination screening in both 2D and 3D-spheroid models, we identified novel synergistic compound pairs targeting crosstalk between IGF1-R, EGFR and PI3K/Akt/mTOR pathways, with high synergy scores across multiple reference models. Using these combinations, western blotting analysis revealed significant suppression in the phosphorylation of key signaling proteins and downstream effectors, while wound healing assays demonstrated reduced cell migration for some combinations, suggesting effective pathway inhibition. To further validate these findings at the transcriptional level, RNA-Seq analysis in SUM149 cells confirmed that the GRR drug combinations significantly reversed the IBC gene expression signature (IBC-GES). These findings not only validated our computational predictions but also identified promising combination strategies that could potentially overcome drug resistance in IBC. Our integrated computational-experimental approach establishes a framework for systematic drug repurposing and highlights novel therapeutic combinations warranting further investigation.

Indexed as

breast cancerdrug combinationsdrug repurposinginflammatory breast cancer (IBC)PI3K/Akt/mTORRNA-SeqSUM149

Identifiers

PMID41427337
PMCPMC12713162

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.