Evidence map›Paper›PMID 39132250›Full record

ArticleBioinformation2024

Decoding the anti-cancer potential of Pexidartinib (PLX3397), a Fms-like tyrosine kinase 3 inhibitor, using next-generation knowledge discovery methods.

Roaa Mahdi Alreemi

Abstract read
In one paragraph

Article in Bioinformation, 2024. 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
–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

1 citing paper in PubMed.

  1. 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.

Roaa Mahdi AlreemiDepartment of Biochemistry, College of Science, University of Jeddah, Jeddah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute Myeloid Leukemia (AML) is a complex hematologic malignancy characterized by the rapid proliferation of abnormal myeloid precursor cells. The FMS-like tyrosine kinase 3 (FLT3), a receptor tyrosine kinase, plays a pivotal role in regulating cell survival, proliferation, and differentiation within the hematopoietic system. Mutations in FLT3, particularly internal tandem duplications (ITDs) and point mutations within the tyrosine kinase domain (TKD), are prevalent in AML and are associated with poor prognosis and increased risk of relapse. The development of targeted therapies has revolutionized the landscape of cancer treatment by focusing on the inhibition of kinase signalling. Small-molecule inhibitors designed to selectively target receptor tyrosine kinases, such as PLX3397, have shown promising results in preclinical studies and early phase clinical trials. PLX3397 exerts its inhibitory effects by targeting CSF1R and KIT, leading to the disruption of receptor tyrosine kinase signalling cascades, suppression of leukemic cell growth, and induction of apoptosis. This study emphasizes the significance of FLT3 as a receptor tyrosine kinase as a therapeutic target for PLX3397. After evaluating the usefulness of PLX3397 as an enzyme inhibitor using ADMET prediction, PLX3397 was prepared for molecular docking in the FLT3 crystal structure (PDB: 4XUF). A molecular dynamics simulation was performed on PLX3397 to evaluate its binding affinity and protein stability in a simulated physiological environment. In conclusion, targeting FLT3 as a receptor tyrosine kinase with PLX3397 represents a promising therapeutic strategy for improving outcomes in patients with FLT3-mutated AML. Further clinical investigations are warranted to validate the efficacy and safety of PLX3397 and to optimize treatment strategies for AML patients based on the FLT3 mutational status.

Indexed as

AMLFLT3PLX3397receptor tyrosine kinasetargeted therapy

Identifiers

PMID39132250
PMCPMC11309106

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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.