| Title |
Genome-Wide Profiling Identified a Set of miRNAs that Are Differentially Expressed in Glioblastoma Stem Cells and Normal Neural Stem Cells
|
|---|---|
| Published in |
PLOS ONE, April 2012
|
| DOI | 10.1371/journal.pone.0036248 |
| Pubmed ID | |
| Authors |
Ming-Fei Lang, Su Yang, Chunnian Zhao, Guoqiang Sun, Kiyohito Murai, Xiwei Wu, Jinhui Wang, Hanlin Gao, Christine E. Brown, Xiaoxuan Liu, Jiehua Zhou, Ling Peng, John J. Rossi, Yanhong Shi |
| Abstract |
A major challenge in cancer research field is to define molecular features that distinguish cancer stem cells from normal stem cells. In this study, we compared microRNA (miRNA) expression profiles in human glioblastoma stem cells and normal neural stem cells using combined microarray and deep sequencing analyses. These studies allowed us to identify a set of 10 miRNAs that are considerably up-regulated or down-regulated in glioblastoma stem cells. Among them, 5 miRNAs were further confirmed to have altered expression in three independent lines of glioblastoma stem cells by real-time RT-PCR analysis. Moreover, two of the miRNAs with increased expression in glioblastoma stem cells also exhibited elevated expression in glioblastoma patient tissues examined, while two miRNAs with decreased expression in glioblastoma stem cells displayed reduced expression in tumor tissues. Furthermore, we identified two oncogenes, NRAS and PIM3, as downstream targets of miR-124, one of the down-regulated miRNAs; and a tumor suppressor, CSMD1, as a downstream target of miR-10a and miR-10b, two of the up-regulated miRNAs. In summary, this study led to the identification of a set of miRNAs that are differentially expressed in glioblastoma stem cells and normal neural stem cells. Characterizing the role of these miRNAs in glioblastoma stem cells may lead to the development of miRNA-based therapies that specifically target tumor stem cells, but spare normal stem cells. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 3% |
| Brazil | 2 | 2% |
| Italy | 1 | <1% |
| Denmark | 1 | <1% |
| Unknown | 98 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 27 | 26% |
| Researcher | 19 | 18% |
| Student > Master | 14 | 13% |
| Student > Bachelor | 12 | 11% |
| Professor > Associate Professor | 5 | 5% |
| Other | 12 | 11% |
| Unknown | 16 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 43 | 41% |
| Biochemistry, Genetics and Molecular Biology | 18 | 17% |
| Medicine and Dentistry | 17 | 16% |
| Neuroscience | 4 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 2% |
| Other | 5 | 5% |
| Unknown | 16 | 15% |