Evidence map›Paper›PMID 20576088›Full record

ArticleBreast cancer research : BCR2010

RNA interference (RNAi) screening approach identifies agents that enhance paclitaxel activity in breast cancer cells.

Joshua A Bauer, Fei Ye, Clayton B Marshall, Brian D Lehmann, Christopher S Pendleton, Yu Shyr, Carlos L Arteaga, Jennifer A Pietenpol

Abstract read
In one paragraph

Article in Breast cancer research : BCR, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

35 citing papers in PubMed.

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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

8 authors.

Joshua A BauerDepartment of Biochemistry, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2200 Pierce Avenue, Nashville, TN 37232, USA. josh.bauer@vanderbilt.edu
Fei Ye
Clayton B Marshall
Brian D Lehmann
Christopher S Pendleton
Yu Shyr
Carlos L Arteaga
Jennifer A Pietenpol

Funding

Tumor Immunology and Microenvironment Research ProgramP30CA068485 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MATTHEW J TYSKA · 1995 to 2026
$172.8M
Structural Biology Facility CoreP30ES000267 · NIEHS · VANDERBILT UNIVERSITY · PI GUENGERICH, F PETER · 1985 to 2014
$20.3M
VIRUSES, NUCLEIC ACIDS, GROWTH, AND CANCERT32CA009385 · NCI · VANDERBILT UNIVERSITY · PI RULEY, HENRY EARL · 1985 to 2007
$4.1M
P53 SIGNALING AND CELLULAR RESPONSE AFTER STRESSR01CA070856 · NCI · VANDERBILT UNIVERSITY · PI PIETENPOL, JENNIFER A · 1997 to 2010
$3.8M
p63 Signaling in Epithelial Cell Growth and CancerR01CA105436 · NCI · VANDERBILT UNIVERSITY · PI PIETENPOL, JENNIFER A · 2004 to 2014
$3.1M
TGF-BETAS AND RECEPTORS AND HUMAN BREAST CELLSR01CA062212 · NCI · VANDERBILT UNIVERSITY · PI ARTEAGA, CARLOS L · 1995 to 2009
$2.9M
Identification of druggable targets for triple-negative breast cancerF32CA138106 · NCI · VANDERBILT UNIVERSITY · PI BAUER, JOSHUA A. · 2009 to 2009
$50k
NCI NIH HHS CA009385-25NCI NIH HHS CA070856NCI NIH HHS CA105436NCI NIH HHS CA62212NCI NIH HHS CA68485NCI NIH HHS CA95131NCI NIH HHS F32 CA138106NIEHS NIH HHS ES00267
6 · The paper itself

Abstract

introductionPaclitaxel is a widely used drug in the treatment of patients with locally advanced and metastatic breast cancer. However, only a small portion of patients have a complete response to paclitaxel-based chemotherapy, and many patients are resistant. Strategies that increase sensitivity and limit resistance to paclitaxel would be of clinical use, especially for patients with triple-negative breast cancer (TNBC).

methodsWe generated a gene set from overlay of the druggable genome and a collection of genomically deregulated gene transcripts in breast cancer. We used loss-of-function RNA interference (RNAi) to identify gene products in this set that, when targeted, increase paclitaxel sensitivity. Pharmacological agents that targeted the top scoring hits/genes from our RNAi screens were used in combination with paclitaxel, and the effects on the growth of various breast cancer cell lines were determined.

resultsRNAi screens performed herein were validated by identification of genes in pathways that, when previously targeted, enhanced paclitaxel sensitivity in the pre-clinical and clinical settings. When chemical inhibitors, CCT007093 and mithramycin, against two top hits in our screen, PPMID and SP1, respectively, were used in combination with paclitaxel, we observed synergistic growth inhibition in both 2D and 3D breast cancer cell cultures. The transforming growth factor beta (TGFbeta) receptor inhibitor, LY2109761, that targets the signaling pathway of another top scoring hit, TGFbeta1, was synergistic with paclitaxel when used in combination on select breast cancer cell lines grown in 3D culture. We also determined the relative paclitaxel sensitivity of 22 TNBC cell lines and identified 18 drug-sensitive and four drug-resistant cell lines. Of significance, we found that both CCT007093 and mithramycin, when used in combination with paclitaxel, resulted in synergistic inhibition of the four paclitaxel-resistant TNBC cell lines.

conclusionsRNAi screening can identify druggable targets and novel drug combinations that can sensitize breast cancer cells to paclitaxel. This genomic-based approach can be applied to a multitude of tumor-derived cell lines and drug treatments to generate requisite pre-clinical data for new drug combination therapies to pursue in clinical investigations.

Indexed as

Antineoplastic Agents, PhytogenicBiomarkers, TumorBreast NeoplasmsCell Line, TumorDrug Resistance, NeoplasmDrug SynergismFemaleHumansNeoplasms, Basal CellPaclitaxelRNA InterferenceRNA, Small InterferingAntineoplastic Agents, PhytogenicBiomarkers, TumorPaclitaxelRNA, Small Interfering

Identifiers

PMID20576088
PMCPMC2917036

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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.