Evidence map›Paper›PMID 39125057›Full record

ReviewMolecules (Basel, Switzerland)2024

A Phenotypic Approach to the Discovery of Potent G-Quadruplex Targeted Drugs.

Stephen Neidle

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
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

1 author.

Stephen NeidleThe School of Pharmacy, University College London, London WC1N 1AX, UK.ORCID 0000-0003-0622-6548

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

G-quadruplex (G4) sequences, which can fold into higher-order G4 structures, are abundant in the human genome and are over-represented in the promoter regions of many genes involved in human cancer initiation, progression, and metastasis. They are plausible targets for G4-binding small molecules, which would, in the case of promoter G4s, result in the transcriptional downregulation of these genes. However, structural information is currently available on only a very small number of G4s and their ligand complexes. This limitation, coupled with the currently restricted information on the G4-containing genes involved in most complex human cancers, has led to the development of a phenotypic-led approach to G4 ligand drug discovery. This approach was illustrated by the discovery of several generations of tri- and tetra-substituted naphthalene diimide (ND) ligands that were found to show potent growth inhibition in pancreatic cancer cell lines and are active in in vivo models for this hard-to-treat disease. The cycles of discovery have culminated in a highly potent tetra-substituted ND derivative, QN-302, which is currently being evaluated in a Phase 1 clinical trial. The major genes whose expression has been down-regulated by QN-302 are presented here: all contain G4 propensity and have been found to be up-regulated in human pancreatic cancer. Some of these genes are also upregulated in other human cancers, supporting the hypothesis that QN-302 is a pan-G4 drug of potential utility beyond pancreatic cancer.

Indexed as

Antineoplastic AgentsDrug DiscoveryG-QuadruplexesAnimalsCell Line, TumorGene Expression Regulation, NeoplasticHumansImidesLigandsNaphthalenesPhenotypePromoter Regions, GeneticAntineoplastic AgentsImidesLigandsnaphthalenediimideNaphthalenespancreatic cancerphenotypic screeningQN-302quadruplex DNAstructure-based design

Identifiers

PMID39125057
PMCPMC11314571

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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.