Evidence map›Paper›PMID 29132397›Full record

ArticleJournal of hematology & oncology2017

Kinase profiling of liposarcomas using RNAi and drug screening assays identified druggable targets.

Deepika Kanojia, Manoj Garg, Jacqueline Martinez, Anand M T, Samuel B Luty, Ngan B Doan, Jonathan W Said, Charles Forscher, Jeffrey W Tyner, H Phillip Koeffler

RetractedOpen access · goldAbstract readRetracted Publication
In one paragraph

Article in Journal of hematology & oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

16 citing papers in PubMed, 29 citations in OpenAlex.

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  8. The multifaceted role of reactive oxygen species in tumorigenesis.Cellular and molecular life sciences : CMLS · 2020
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  14. A brief overview of antitumoral actions of bruceine D.Exploration of targeted anti-tumor therapy · 2020
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 2 countries.

Deepika KanojiaCancer Science Institute of Singapore, National University of Singapore, Singapore, 117599, Singapore. csidk@nus.edu.sg.
Manoj GargCancer Science Institute of Singapore, National University of Singapore, Singapore, 117599, Singapore.
Jacqueline MartinezCell, Developmental & Cancer, Oregon Health & Science University, Portland, Oregon, 97239, USA.
Anand M TCancer Science Institute of Singapore, National University of Singapore, Singapore, 117599, Singapore.
Samuel B LutyCell, Developmental & Cancer, Oregon Health & Science University, Portland, Oregon, 97239, USA.
Ngan B DoanDepartment of Pathology and Laboratory Medicine, Ronald Reagan UCLA Medical Center, Los Angeles, California, 90095, USA.
Jonathan W SaidDepartment of Pathology and Laboratory Medicine, Ronald Reagan UCLA Medical Center, Los Angeles, California, 90095, USA.
Charles ForscherDivision of Hematology/Oncology, Cedars-Sinai Medical Center, University of California School of Medicine, Los Angeles, California, 90048, USA.
Jeffrey W TynerCell, Developmental & Cancer, Oregon Health & Science University, Portland, Oregon, 97239, USA.
H Phillip KoefflerCancer Science Institute of Singapore, National University of Singapore, Singapore, 117599, Singapore.
National University of Singapore · SGOregon Health & Science University · USCedars-Sinai Medical Center · USRonald Reagan UCLA Medical Center · US

Funding

Connecting Genomic Alterations in Liposarcomas with Drug Responses and Identification of New Therapeutic ApproachesR01CA200992 · NCI · CEDARS-SINAI MEDICAL CENTER · PI KOEFFLER, HAROLD PHILLIP · 2016 to 2020
$1.8M
ROR1 as a Therapeutic Target in Acute Lymphoblastic LeukemiaR00CA151457 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI TYNER, JEFFREY WALLACE · 2012 to 2014
$723k
National Institutes of Health 1R01CA200992-01A1NCI NIH HHS R00 CA151457NCI NIH HHS R01 CA200992
6 · The paper itself

Abstract

backgroundLiposarcoma, the most common soft tissue tumor, is understudied cancer, and limited progress has been made in the treatment of metastatic disease. The Achilles heel of cancer often is their kinases that are excellent therapeutic targets. However, very limited knowledge exists of therapeutic critical kinase targets in liposarcoma that could be potentially used in disease management.

methodsLarge RNAi and small-molecule tyrosine kinase inhibitor screens were performed against the proliferative capacity of liposarcoma cell lines of different subtypes. Each small molecule inhibitor was either FDA approved or in a clinical trial.

resultsScreening assays identified several previously unrecognized targets including PTK2 and KIT in liposarcoma. We also observed that ponatinib, multi-targeted tyrosine kinase inhibitor, was the most effective drug with anti-growth effects against all cell lines. In vitro assays showed that ponatinib inhibited the clonogenic proliferation of liposarcoma, and this anti-growth effect was associated with apoptosis and cell cycle arrest at the G0/G1 phase as well as a decrease in the KIT signaling pathway. In addition, ponatinib inhibited in vivo growth of liposarcoma in a xenograft model.

conclusionsTwo large-scale kinase screenings identified novel liposarcoma targets and a FDA-approved inhibitor, ponatinib with clear anti-liposarcoma activity highlighting its potential therapy for treatment of this deadly tumor.

Indexed as

AnimalsCell ProliferationDrug Evaluation, PreclinicalHumansImidazolesLiposarcomaMiceMice, Inbred NODMice, SCIDProtein Kinase InhibitorsPyridazinesRNA InterferenceImidazolesponatinibProtein Kinase InhibitorsPyridazinesKinase inhibitorLiposarcomaPonatinibTherapeutics

Identifiers

PMID29132397
PMCPMC5683536
OpenAlexW2770666138

What OpenQuestion 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 OpenQuestion graph.