High-Throughput Strategies for the Discovery of Anticancer Drugs by Targeting Transcriptional Reprogramming

Transcriptional reprogramming contributes to the progression and recurrence of cancer. However, the poorly elucidated mechanisms of transcriptional reprogramming in tumors make the development of effective drugs difficult, and gene expression signature is helpful for connecting genetic information and pharmacologic treatment. So far, there are two gene-expression signature-based high-throughput drug discovery approaches: L1000, which measures the mRNA transcript abundance of 978 “landmark” genes, and high-throughput sequencing-based high-throughput screening (HTS2); they are suitable for anticancer drug discovery by targeting transcriptional reprogramming. L1000 uses ligation-mediated amplification and hybridization to Luminex beads and highlights gene expression changes by detecting bead colors and fluorescence intensity of phycoerythrin signal. HTS2 takes advantage of RNA-mediated oligonucleotide annealing, selection, and ligation, high throughput sequencing, to quantify gene expression changes by directly measuring gene sequences. This article summarizes technological principles and applications of L1000 and HTS2, and discusses their advantages and limitations in anticancer drug discovery.

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MECHANISM-BASED HIGH-THROUGHPUT SCREENING FOR NOVEL ANTICANCER DRUG DISCOVERY

Anticancer Drug Development ◽

10.1016/b978-012072651-6/50015-2 ◽

2002 ◽

pp. 249-267 ◽

Cited By ~ 3

Author(s):

Wynne Aherne ◽

Michelle Garrett ◽

Ted McDonald ◽

Paul Workman

Keyword(s):

Drug Discovery ◽

Anticancer Drug ◽

High Throughput ◽

High Throughput Screening ◽

Anticancer Drug Discovery

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Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data

Blood ◽

10.1182/blood-2007-11-126003 ◽

2008 ◽

Vol 111 (12) ◽

pp. 5654-5662 ◽

Cited By ~ 128

Author(s):

Duane C. Hassane ◽

Monica L. Guzman ◽

Cheryl Corbett ◽

Xiaojie Li ◽

Ramzi Abboud ◽

...

Keyword(s):

Gene Expression ◽

Stem Cells ◽

High Throughput ◽

In Silico ◽

High Throughput Screening ◽

Drug Targets ◽

Expression Profiles ◽

Gene Expression Signature ◽

Myelogenous Leukemia ◽

Expression Signature

Abstract Increasing evidence indicates that malignant stem cells are important for the pathogenesis of acute myelogenous leukemia (AML) and represent a reservoir of cells that drive the development of AML and relapse. Therefore, new treatment regimens are necessary to prevent relapse and improve therapeutic outcomes. Previous studies have shown that the sesquiterpene lactone, parthenolide (PTL), ablates bulk, progenitor, and stem AML cells while causing no appreciable toxicity to normal hematopoietic cells. Thus, PTL must evoke cellular responses capable of mediating AML selective cell death. Given recent advances in chemical genomics such as gene expression-based high-throughput screening (GE-HTS) and the Connectivity Map, we hypothesized that the gene expression signature resulting from treatment of primary AML with PTL could be used to search for similar signatures in publicly available gene expression profiles deposited into the Gene Expression Omnibus (GEO). We therefore devised a broad in silico screen of the GEO database using the PTL gene expression signature as a template and discovered 2 new agents, celastrol and 4-hydroxy-2-nonenal, that effectively eradicate AML at the bulk, progenitor, and stem cell level. These findings suggest the use of multicenter collections of high-throughput data to facilitate discovery of leukemia drugs and drug targets.

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Versatile pathway-centric approach based on high-throughput sequencing to anticancer drug discovery

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1200305109 ◽

2012 ◽

Vol 109 (12) ◽

pp. 4609-4614 ◽

Cited By ~ 36

Author(s):

H. Li ◽

H. Zhou ◽

D. Wang ◽

J. Qiu ◽

Y. Zhou ◽

...

Keyword(s):

Drug Discovery ◽

Anticancer Drug ◽

High Throughput ◽

High Throughput Sequencing ◽

Anticancer Drug Discovery

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Genomics and Systems Biology.

Blood ◽

10.1182/blood.v112.11.sci-51.sci-51 ◽

2008 ◽

Vol 112 (11) ◽

pp. sci-51-sci-51

Author(s):

Todd R. Golub

Keyword(s):

Gene Expression ◽

High Throughput ◽

Biological Networks ◽

High Throughput Screening ◽

Expression Profiles ◽

Low Cost ◽

Gene Expression Profiles ◽

Gene Expression Signature ◽

Small Molecule Libraries ◽

Approved Drugs

Genomics holds particular potential for the elucidation of biological networks that underlie disease. For example, gene expression profiles have been used to classify human cancers, and have more recently been used to predict graft rejection following organ transplantation. Such signatures thus hold promise both as diagnostic approaches and as tools with which to dissect biological mechanism. Such systems-based approaches are also beginning to impact the drug discovery process. For example, it is now feasible to measure gene expression signatures at low cost and high throughput, thereby allowing for the screening libraries of small molecule libraries in order to identify compounds capable of perturbing a signature of interest (even if the critical drivers of that signature are not yet known). This approach, known as Gene Expression-Based High Throughput Screening (GE-HTS), has been shown to identify candidate therapeutic approaches in AML, Ewing sarcoma, and neuroblastoma, and has identified tool compounds capable of inhibiting PDGF receptor signaling. A related approach, known as the Connectivity Map (www.broad.mit.edu/cmap) attempts to use gene expression profiles as a universal language with which to connect cellular states, gene product function, and drug action. In this manner, a gene expression signature of interest is used to computationally query a database of gene expression profiles of cells systematically treated with a large number of compounds (e.g., all off-patent FDA-approved drugs), thereby identifying potential new applications for existing drugs. Such systems level approaches thus seek chemical modulators of cellular states, even when the molecular basis of such altered states is unknown.

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