Evidence map›Paper›PMID 39671264›Full record

ArticleAnti-cancer drugs2025

Screening of a kinase inhibitor library identified novel targetable kinase pathways in triple-negative breast cancer.

Caroline H Rinderle, Christopher V Baker, Courtney B Lagarde, Khoa Nguyen, Sara Al-Ghadban, Margarite D Matossian, Van T Hoang, Elizabeth C Martin, Bridgette M Collins-Burow, Simak Ali and 3 more

Abstract read
In one paragraph

Article in Anti-cancer drugs, 2025. 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. Translational andrology and urology · 2025
    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

13 authors.

Caroline H RinderleDepartment of Microbiology, Immunology and Genetics, University of North Texas Health Science Center, Fort Worth, TX.
Christopher V BakerDepartment of Microbiology, Immunology and Genetics, University of North Texas Health Science Center, Fort Worth, TX.
Courtney B LagardeDepartment of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, Tulane Cancer Center, New Orleans, LA, USA.
Khoa NguyenDepartment of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, Tulane Cancer Center, New Orleans, LA, USA.
Sara Al-GhadbanDepartment of Microbiology, Immunology and Genetics, University of North Texas Health Science Center, Fort Worth, TX.
Margarite D MatossianDepartment of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, Tulane Cancer Center, New Orleans, LA, USA.
Van T HoangDepartment of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, Tulane Cancer Center, New Orleans, LA, USA.
Elizabeth C MartinDepartment of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, Tulane Cancer Center, New Orleans, LA, USA.
Bridgette M Collins-BurowDepartment of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, Tulane Cancer Center, New Orleans, LA, USA.
Simak AliDepartment of Surgery & Cancer, Imperial College London, London, UK.
David H DrewryStructural Genomics Consortium, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy.
Matthew E BurowDepartment of Medicine, Section of Hematology and Oncology, Tulane University School of Medicine, Tulane Cancer Center, New Orleans, LA, USA.
Bruce A BunnellDepartment of Microbiology, Immunology and Genetics, University of North Texas Health Science Center, Fort Worth, TX.

Funding

BASIC RESEARCH TRAINING IN MEDICAL ONCOLOGYT32CA009566 · NCI · UNIVERSITY OF CHICAGO · PI OLUFUNMILAYO F. OLOPADE · 1987 to 2026
$10.5M
NCI NIH HHS T32 CA009566
6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) is a highly invasive breast cancer subtype that is challenging to treat due to inherent heterogeneity and absence of estrogen, progesterone, and human epidermal growth factor 2 receptors. Kinase signaling networks drive cancer growth and development, and kinase inhibitors are promising anti-cancer strategies in diverse cancer subtypes. Kinase inhibitor screens are an efficient, valuable means of identifying compounds that suppress cancer cell growth in vitro , facilitating the identification of kinase vulnerabilities to target therapeutically. The Kinase Chemogenomic Set is a well-annotated library of 187 kinase inhibitor compounds that indexes 215 kinases of the 518 in the known human kinome representing various kinase networks and signaling pathways, several of which are understudied. Our screen revealed 14 kinase inhibitor compounds effectively inhibited TNBC cell growth and proliferation. Upon further testing, three compounds, THZ531, THZ1, and PFE-PKIS 29, had the most significant and consistent effects across a range of TNBC cell lines. These cyclin-dependent kinase (CDK)12/CDK13, CDK7, and phosphoinositide 3-kinase inhibitors, respectively, decreased metabolic activity in TNBC cell lines and promote a gene expression profile consistent with the reversal of the epithelial-to-mesenchymal transition, indicating these kinase networks potentially mediate metastatic behavior. These data identified novel kinase targets and kinase signaling pathways that drive metastasis in TNBC.

Indexed as

Cell ProliferationProtein Kinase InhibitorsTriple Negative Breast NeoplasmsAntineoplastic AgentsCell Line, TumorDrug Screening Assays, AntitumorEpithelial-Mesenchymal TransitionFemaleHumansSignal TransductionSmall Molecule LibrariesAntineoplastic AgentsProtein Kinase InhibitorsSmall Molecule Libraries

Identifiers

PMID39671264
PMCPMC11634125

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.