Transcriptome Complexity In Cancer Research

Results of recent transcriptome analysis efforts continue to reveal the complexity of the transcriptome. Findings emphasize the need for more sophisticated and better integrated tools and technologies. Development of such tools and processes has received increasing focus for investigators studying cancer where gene expression and regulation has long shown a significant role in disease pathology.

One such study by Tanney et al., (See Publication of the Month below) demonstrates the use of large-scale sequencing, gene expression profiling, and mining of public databases to characterize a non-small cell lung cancer transcriptome. The combined data was used to generate the first, high density, disease-focused transcriptome microarray.

In addition, these investigators had to consider the challenges presented by typically low quality and quantity of RNA obtained from clinical samples.  Such specimens are generally scarce, severely compromised, and likely stored for long periods of time. 

In this study, Tanney et al. used the NuGEN WT-Ovation(tm) FFPE System V2 for RNA amplification and the FL-Ovation(tm) cDNA Biotin Module V2 for fragmentation and labeling of their samples.


NuGEN target preparation solutions are particularly attuned to such studies as they are uniquely designed to enable investigation of small and degraded RNA obtained from clinical sample sets.



Publication of the Month

Generation of a non-small cell lung cancer transcriptome microarray 
Austin Tanney, Gavin R Oliver, Vadim Farztdinov, Richard D Kennedy, Jude M Mulligan, Ciaran E Fulton, Susan M Farragher, John K Field, Patrick G Johnston, D Paul Harkin, Vitali Proutski and Karl A Mulligan
BMC Medical Genomics, May 2008, 1:20 doi:10.1186/1755-8794-1-20

Abstract
Background:  Non-small cell lung cancer (NSCLC) is the leading cause of cancer mortality worldwide. At present, no reliable biomarkers are available to guide the management of this condition. Microarray technology may allow appropriate biomarkers to be identified, but present platforms are lacking disease focus and are thus likely to miss potentially vital information contained in patient tissue samples.

Methods:  A combination of large-scale in-house sequencing, gene expression profiling and public sequence and gene expression data mining were used to characterize the transcriptome of NSCLC and the data used to generate a disease-focused microarray- the Lung Cancer DSA research tool.

Results:  Built on the Affymetrix GeneChip® platform, the Lung Cancer DSA research tool allows for interrogation of ~60,000 transcripts relevant to Lung Cancer, tens of thousands of which are unavailable on leading commercial microarrays.

Conclusion:  We have developed the first high-density disease specific transcriptome microarray. We present the array design process and the results of experiments carried out to demonstrate the array's utility. This approach serves as a template for the development of other disease transcriptome microarrays, including non-neoplastic diseases.


Customer Feature

Developing a prognostic multigene expression signature for neuroblastoma

Dr. Jo Vandesompele pictured here (front row second from the right) with his team at the Ghent University Hospital Center for Medical Genetics. 


Jo Vandesompele, PhD
Professor, Functional Genomics and Applied Bioinformatics
Ghent University, Belgium
Co-founder and CEO, Biogazelle

"Neuroblastoma is one of the most frequent solid tumors in children. Despite advances in intensive multi-modal therapies, survival rates for high risk patients remain disappointingly below 50%. More accurate assessment of prognosis is of importance to further improve the choice of risk-related therapy for children with neuroblastoma.

To reach this goal our aim was to validate a carefully in house developed prognostic multigene expression signature on an unprecedented series of more than 700 tumor samples using an optimized high-throughput qPCR platform, based on rigorous quality control, validated assays and a powerful data-analysis pipeline (employing the qBasePlus real-time PCR analysis software). As fresh frozen tumor biopsies are often small and material available for research purposes scarce, we set out to amplify minute amounts of total RNA, generating a cDNA resource for future expression profiling of hundreds of genes.

Thorough evaluation of various competitive products resulted in the selection of the WT-Ovation(tm) RNA Amplification System (NuGEN) for unbiased and straightforward amplification of our precious starting material. Applying this technology to our tumor biopsies, PhD candidate Joëlle Vermeulen (second row second from the right) could validate the multigene expression signature as a powerful independent prognostic factor for children with neuroblastoma. This study could simply not have been performed without WT-Ovation. The results of this study have been presented at the bi-annual Advances in Neuroblastoma Research meeting (Chiba, Japan) and are currently being prepared in a manuscript."

Other Team Publications
qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data
Jan Hellemans, Geert Mortier, Anne De Paepe, Frank Speleman, Jo Vandesompele
Genome Biol. 2007;8(2):R19

Small-molecule MDM2 antagonists as a new therapy concept for neuroblastoma
Tom Van Maerken, Frank Speleman, Joëlle Vermeulen, Irena Lambertz, Sarah De Clercq, Els De Smet, Nurten Yigit, Vicky Coppens, Jan Philippé Anne De Paepe  Jean-Chistophe Marine, Jo Vandesompele
Cancer Res. 2006 Oct 1;66(19):9646-55

Human fetal neuroblast and neuroblastoma transcriptome analysis confirms neuroblast origin and highlights neuroblastoma candidate genes
Katleen De Preter, Jo Vandesompele, Pierre Heimann, Nurten Yigit, Siv Beckman, Alexander Schramm, Angelica Eggert, Raymond L Stallings, Yves Benoit , Marleen Renard  Anne De Paepe, Genevieve Laureys, Sven Pohlman, Frank Speleman
Genome Biol. 2006;7(9):R84. Erratum in: Genome Biol. 2007;8(1):401.

Identification and expression analysis of genes associated with bovine blastocyst formation
Karen Goossens, Ann Van Soom, Mario Van Poucke, Leen Vandaele, Jo Vandesompele, Alex Van Zeveren and Luc J Peelman
BMC Developmental Biology, June 2007, 7:64 doi:10.1186/1471-213X-7-64


Are you facing high throughput challenges?

NuGEN Automation Solutions enable high throughput target preparation for large scale gene expression profiling projects. Our Automation Solutions bring robust, flexible Ovation Systems to your workflows to accelerate discoveries and enable access to a wide range of minute and degraded samples.

NuGEN automation program builds validated scripts for various combinations of NuGEN assays and automation platforms. Currently the Ovation Whole Blood RNA amplification, Fragmentation and Biotin Labeling protocols have been successfully automated on the following platforms:

     * The Beckman Biomek® ArrayPLEX
     * The Beckman Biomek® FX
     * Affymetrix GeneChip® Array Station (GCAS)

Automation of additional NuGEN products, specifically the WT-Ovation FFPE RNA amplification and the powerful WT-Ovation Exon Module for use with the Affymetrix GeneChip® Gene and Exon ST arrays is underway.  Contact us to learn more about our Automation Solutions and how they can improve your workflows.


Attending the Atlantic Omics Symposium and Expo in Canada?
Stop by BioLynx Booth #6 and learn about NuGEN Solutions.

Delta Beausejour, Moncton, New Brunswick, Canada, August 19-20, 2008

 
Ovation® Systems:
Accelerating Your Discoveries, Enabling Your Vision

The NuGEN Ovation® Systems family of RNA amplification and labeling products enables sensitive, robust gene expression profiling and novel signature discovery using a variety of challenging biological samples such as FFPE, whole blood, LCM, fine needle aspirates, tissue biopsies, sorted cell, and more. 

These flexible, modular products let you chose your preferred analytical platform; Affymetrix GeneChip® 3-prime or ST, Agilent, Illumina microarrays, or qPCR.


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www.nugeninc.com