Evidence map›Paper›PMID 33417917›Full record

ArticleThe Journal of investigative dermatology2021

Computational Drug Repositioning Identifies Statins as Modifiers of Prognostic Genetic Expression Signatures and Metastatic Behavior in Melanoma.

Wesley Y Yu, Sheena T Hill, E Ricky Chan, John J Pink, Kevin Cooper, Sancy Leachman, Amanda W Lund, Rajan Kulkarni, Jeremy S Bordeaux

Open access · greenAbstract read
In one paragraph

Article in The Journal of investigative dermatology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

7 citing papers in PubMed, 16 citations in OpenAlex.

  1. Life Factors and Melanoma: From the Macroscopic State to the Molecular Mechanism.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

9 authors at 4 institutions in 1 country.

Wesley Y YuDepartment of Dermatology, Oregon Health & Science University, Portland, Oregon, USA. Electronic address: yuwe@ohsu.edu.
Sheena T HillDepartment of Dermatology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.
E Ricky ChanInstitute for Computational Biology, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA.
John J PinkCase Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio, USA.
Kevin CooperDepartment of Dermatology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.
Sancy LeachmanDepartment of Dermatology, Oregon Health & Science University, Portland, Oregon, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA.
Amanda W LundRonald O. Perelman Department of Dermatology, NYU Grossman School of Medicine, New York, New York, USA; Department of Pathology, NYU Grossman School of Medicine, New York, New York, USA; Laura and Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, New York, USA.
Rajan KulkarniDepartment of Dermatology, Oregon Health & Science University, Portland, Oregon, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA.
Jeremy S BordeauxDepartment of Dermatology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.
Oregon Health & Science University · USUniversity Hospitals of Cleveland · USCase Western Reserve University · USNYU Langone’s Laura and Isaac Perlmutter Cancer Center

Funding

TUMOR METABOLISM PROGRAMP30CA043703 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI Amar Desai · 1987 to 2026
$142.3M
Clinical and Translational Science Collaborative of ClevelandUL1TR002548 · NCATS · CASE WESTERN RESERVE UNIVERSITY · PI MCCOMSEY, GRACE A · 2018 to 2022
$35.5M
NCATS NIH HHS UL1 TR002548NCI NIH HHS P30 CA043703
6 · The paper itself

Abstract

Despite advances in melanoma treatment, more than 70% of patients with distant metastasis die within 5 years. Proactive treatment of early melanoma to prevent metastasis could save lives and reduce overall healthcare costs. Currently, there are no treatments specifically designed to prevent early melanoma from progressing to metastasis. We used the Connectivity Map to conduct an in silico drug screen and identified 3-hydroxy-3-methylglutaryl-coenzyme A reductase inhibitors (statins) as a drug class that might prevent melanoma metastasis. To confirm the in vitro effect of statins, RNA sequencing was completed on A375 cells after treatment with fluvastatin to describe changes in the melanoma transcriptome. Statins induced differential expression in genes associated with metastasis and are used in commercially available prognostic tests for melanoma metastasis. Finally, we completed a chart review of 475 patients with melanoma. Patients taking statins were less likely to have metastasis at the time of melanoma diagnosis in both univariate and multivariate analyses (24.7% taking statins vs. 37.6% not taking statins, absolute risk reduction = 12.9%, P = 0.038). These findings suggest that statins might be useful as a treatment to prevent melanoma metastasis. Prospective trials are required to verify our findings and to determine the mechanism of metastasis prevention.

Indexed as

Drug RepositioningAgedComputer SimulationDatasets as TopicGene Expression ProfilingGene Expression Regulation, NeoplasticHumansHydroxymethylglutaryl-CoA Reductase InhibitorsMelanomaMiddle AgedPrognosisSkin NeoplasmsSurvival AnalysisTranscriptomeHydroxymethylglutaryl-CoA Reductase Inhibitors

Identifiers

PMID33417917
PMCPMC8238797
OpenAlexW3118238985

What OpenQuestion holds

Textmetadata
LicenceTDM
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.