Posters
« Back
Knockdown of long noncoding RNAs in breast cancer
EP22865
Poster Title: Knockdown of long noncoding RNAs in breast cancer
Submitted on 31 Mar 2015
Author(s): 1 Jennii Luu, 2 Jesper Maag, 1 Yanny Handoko, 3 Richard Redvers, 3,4 Robin L. Anderson, 5 Maren M. Gross , 2 Marcel E. Dinger, and 1,3 Kaylene J. Simpson 1 Victorian Centre for Functional Genomics, Peter MacCallum Cancer Centre; 2 Genome Informatics, The Kinghorn Cancer Centre, The Garvan Institute of Medical Research; 3 Metastasis Research Laboratory, Peter MacCallum Cancer Centre, 4 Sir Peter MacCallum Department of Oncology, University of Melbourne;
Affiliations: GE Healthcare Dharmacon, Inc.
Poster Views: 2,042
View poster »


Poster Information
Abstract: Traditionally genetics has held a protein centric view with RNA seen as an intermediate step between DNA and protein. Recently, the emerging evidence of pervasive transcription throughout the genome has challenged this view1,2. Long noncoding RNAs (lncRNA) are selectively expressed during different cell cycles3 as well as transcribed differently in specific cell types4, which emphasizes their importance in regulating cell specification. lncRNAs can work on every stage of transcription from chromatin remodeling, controlling transcription to post-transcriptional processing through various mechanisms such as directly binding to transcription activation sites, working as decoys for transcript suppressors/activators or as guiding/scaffold molecules for chromatin remodeling complexes5.

Increasing numbers of studies have associated disease with lncRNAs. However, such studies have typically only focused on exploring the function of individual lncRNAs. In preliminary studies, we investigated the functional consequences of lncRNA knockdown in the breast cell lines MCF 10A and MDA-MB-231 using cell viability and morphology as readouts. Using high throughput siRNA screening protocols established in the Victorian Centre for Functional Genomics, we have knocked down all targets in the Dharmacon™ Lincode™ siRNA Library collection (currently 2,231) in both cell lines and quantitated changes using high content imaging. Here we report the functional consequences of lncRNA knockdown in breast cell lines and correlate with patient tumor data.
Summary: RNAi global collaboration study using Lincode siRNA in a primary screen of tumor and nontumor breast cell lines. Hundreds of lncRNAs are found to affect viability and cell morphology of breast cancer. Presented at Keystone Symposia on Long Noncoding RNAs: From Evolution to Function, Mar 15 - Mar 20, 2015.References: 1. ENCODE. An integrated encyclopedia of DNA elements in the human
genome. Nature. 488(7414),57–74 (2013)
2. G. Liu, J. S. Mattick, et al. A meta-analysis of the genomic and transcriptomic composition of complex life. Cell Cycle. 12(13), (2013)
3. T. Hung, Y. Wang et al. Extensive and co- ordinated transcription of noncoding RNAs within cell-cycle promoters. Nature Genetics. 43(7), 621–629 (2011)
4. E. A. Gibb, E. A. Vucic et al. Human cancer long noncoding rna transcriptomes. PloS One. 6(10) e25915, (2011)
5. T. R. Mercer, M. E. Dinger et al. Long noncoding RNAs: insights into functions.
Nature Reviews Genetics, 10(3), 155–159 (2009)
6. T. R. Mercer, J. S. Mattick. Structure and function of long noncoding RNAs in epigenetic regulation. Nature Structural & Molecular Biology. 20(3),
300-307 (2013)
7. A. Necsulea, M. Soumillion et al. The evolution of lncRNA repertoires and expression patterns in tetrapods. Nature. (505) 635-640, (2014
Report abuse »
Questions
Ask the author a question about this poster.
Ask a Question »

Creative Commons

Related Posters


Genetic Engineering in Male Sterility for Hybrid Variety Development
Abir Hasan Joy

VITVO: Mimicking In Vivo Complexity By The Innovative 3D Model
Olivia Candini1, Giulia Grisendi1, Elisabetta Manuela Foppiani1, Matteo Brogli1, Beatrice Aramini2, Valentina Masciale3, Carlotta Spano1, Tiziana Petrachi4, Elena Veronesi4, Pierfranco Conte5,6, Giorgio Mari1 & Massimo Dominici1,3

Digiceuticals
Helana Lutfi and Shaban Nuredini

Characterization of patient-derived organoids cultured on a gas-rich, liquid-liquid interface
James T. Shoemaker, Katherine R. Richardson, Jamie Arnst, Adam Marcus, Jelena Vukasinovic

Machine Learning: A New Breakthrough in Medical Diagnosis
Punitha Mahendran, Anis Joelaira, Chai Yong Chia, Fazidatul Aziz, Hasyimah Emran, Siew Fun Lee, Wai Kit Wong, Yee Yan Tang, Li Yang Wong