Evidence map›Paper›PMID 31727951›Full record

ArticleScientific reports2019

Mebendazole for Differentiation Therapy of Acute Myeloid Leukemia Identified by a Lineage Maturation Index.

Yulin Li, Daniel Thomas, Anja Deutzmann, Ravindra Majeti, Dean W Felsher, David L Dill

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

13 citing papers in PubMed, 18 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Yulin LiCenter for Immunotherapy Research, Houston Methodist Research Institute, Houston, TX, 77030, USA. yli@houstonmethodist.org.
Daniel ThomasDivision of Hematology, Department of Medicine, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, 94305, CA, USA.
Anja DeutzmannDivision of Oncology, Department of Medicine and Pathology, Stanford University School of Medicine, Stanford, 94305, CA, USA.
Ravindra MajetiDivision of Hematology, Department of Medicine, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, 94305, CA, USA.
Dean W FelsherDivision of Oncology, Department of Medicine and Pathology, Stanford University School of Medicine, Stanford, 94305, CA, USA.
David L DillDepartment of Computer Science, Stanford University, Stanford, CA, 94305, USA.
Stanford University · USHouston Methodist · US

Funding

TRANS-NETWORK PROJECTSU54CA143907 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI SHIBATA, DARRYL K · 2009 to 2013
$15.2M
MODELING THE ROLE OF PROGRESSION IN FOLLICULAR LYMPHOMAU54CA149145 · NCI · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2010 to 2014
$12.1M
Pre-Leukemic Hematopoietic Stem Cells and Clonal Evolution in Human AMLR01CA188055 · NCI · STANFORD UNIVERSITY · PI MAJETI, RAVINDRA · 2014 to 2018
$1.6M
The Role of Suv420h1 Histone Methyltransferase in MYC-Driven TumorigenesisK22CA207598 · NCI · METHODIST HOSPITAL RESEARCH INSTITUTE · PI LI, YULIN · 2017 to 2019
$565k
Discovery of Synthetic Lethal Targets for Recurrent Epigenetic Mutations in Acute Myeloid LeukemiaK99CA207731 · NCI · STANFORD UNIVERSITY · PI THOMAS, DANIEL · 2017 to 2018
$347k
NCI NIH HHS K22 CA207598NCI NIH HHS K99 CA207731NCI NIH HHS R01 CA188055NCI NIH HHS U54 CA143907NCI NIH HHS U54 CA149145U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) R01CA188055U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) U54CA143907
6 · The paper itself

Abstract

Accurate assessment of changes in cellular differentiation status in response to drug treatments or genetic perturbations is crucial for understanding tumorigenesis and developing novel therapeutics for human cancer. We have developed a novel computational approach, the Lineage Maturation Index (LMI), to define the changes in differentiation state of hematopoietic malignancies based on their gene expression profiles. We have confirmed that the LMI approach can detect known changes of differentiation state in both normal and malignant hematopoietic cells. To discover novel differentiation therapies, we applied this approach to analyze the gene expression profiles of HL-60 leukemia cells treated with a small molecule drug library. Among multiple drugs that significantly increased the LMIs, we identified mebendazole, an anti-helminthic clinically used for decades with no known significant toxicity. We tested the differentiation activity of mebendazole using primary leukemia blast cells isolated from human acute myeloid leukemia (AML) patients. We determined that treatment with mebendazole induces dramatic differentiation of leukemia blast cells as shown by cellular morphology and cell surface markers. Furthermore, mebendazole treatment significantly extended the survival of leukemia-bearing mice in a xenograft model. These findings suggest that mebendazole may be utilized as a low toxicity therapeutic for human acute myeloid leukemia and confirm the LMI approach as a robust tool for the discovery of novel differentiation therapies for cancer.

Indexed as

AnimalsAntineoplastic AgentsCell DifferentiationCell LineageCell ProliferationComputational BiologyDrug RepositioningGene Expression ProfilingGene Expression Regulation, NeoplasticHL-60 CellsHumansLeukemia, Myeloid, AcuteMebendazoleMiceSmall Molecule LibrariesXenograft Model Antitumor AssaysAntineoplastic AgentsMebendazoleSmall Molecule Libraries

Identifiers

PMID31727951
PMCPMC6856101
OpenAlexW2984960344

What OpenQuestion holds

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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 OpenQuestion graph.