| Chapter title |
A High-Throughput siRNA Screening Platform to Identify MYC-Synthetic Lethal Genes as Candidate Therapeutic Targets.
|
|---|---|
| Chapter number | 12 |
| Book title |
The Myc Gene
|
| Published in |
Methods in molecular biology, September 2013
|
| DOI | 10.1007/978-1-62703-429-6_12 |
| Pubmed ID | |
| Book ISBNs |
978-1-62703-428-9, 978-1-62703-429-6
|
| Authors |
Grandori C, Carla Grandori |
| Abstract |
Targeted therapeutics toward specific genes and pathways represent the future of oncological treatments. However, several commonly activated oncogenes, such as MYC, have proven difficult to target by pharmacological agents. To broaden the menu of potentially druggable therapeutic targets, we describe a method to detect genes essential for the survival of MYC overexpressing cells, which we will refer to as MYC-synthetic lethal genes (MYC-SL) (Toyoshima et al., Proc Natl Acad Sci USA 109:9545-9550, 2012). These genes represent candidate targets for drug development to be utilized for MYC-driven cancers as well as probes to further our understanding of the biology of MYC-driven tumorigenesis. The discovery platform includes the following components: (1) an isogenic cell system that enables overexpression of MYC without oncogene-induced senescence (OIS) response (Benanti and Galloway, Mol Cell Biol 24:2842-2852, 2004; Benanti et al., Mol Cancer Res 5:1181-1189, 2007); (2) arrayed siRNA libraries targeting individual genes; (3) automated laboratory equipment for dispensing of cells, siRNAs, and readout assays; and (4) bioinformatics and software for data mining and visualization. This flexible platform can be readily applied to other oncogenes or tumor suppressor genes. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 3 | 25% |
| Student > Ph. D. Student | 3 | 25% |
| Researcher | 3 | 25% |
| Student > Bachelor | 2 | 17% |
| Student > Postgraduate | 1 | 8% |
| Other | 0 | 0% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 42% |
| Medicine and Dentistry | 2 | 17% |
| Computer Science | 1 | 8% |
| Nursing and Health Professions | 1 | 8% |
| Immunology and Microbiology | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 1 | 8% |