| Title |
Single-Cell RNA-Sequencing in Glioma
|
|---|---|
| Published in |
Current Oncology Reports, April 2018
|
| DOI | 10.1007/s11912-018-0673-2 |
| Pubmed ID | |
| Authors |
Eli Johnson, Katherine L. Dickerson, Ian D. Connolly, Melanie Hayden Gephart |
| Abstract |
In this review, we seek to summarize the literature concerning the use of single-cell RNA-sequencing for CNS gliomas. Single-cell analysis has revealed complex tumor heterogeneity, subpopulations of proliferating stem-like cells and expanded our view of tumor microenvironment influence in the disease process. Although bulk RNA-sequencing has guided our initial understanding of glioma genetics, this method does not accurately define the heterogeneous subpopulations found within these tumors. Single-cell techniques have appealing applications in cancer research, as diverse cell types and the tumor microenvironment have important implications in therapy. High cost and difficult protocols prevent widespread use of single-cell RNA-sequencing; however, continued innovation will improve accessibility and expand our of knowledge gliomas. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 69 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 14% |
| Student > Ph. D. Student | 9 | 13% |
| Student > Master | 9 | 13% |
| Other | 6 | 9% |
| Student > Doctoral Student | 6 | 9% |
| Other | 6 | 9% |
| Unknown | 23 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 12 | 17% |
| Agricultural and Biological Sciences | 10 | 14% |
| Immunology and Microbiology | 4 | 6% |
| Medicine and Dentistry | 4 | 6% |
| Neuroscience | 2 | 3% |
| Other | 4 | 6% |
| Unknown | 33 | 48% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 April 2018.
All research outputs
#13,900,608
of 23,041,514 outputs
Outputs from Current Oncology Reports
#496
of 890 outputs
Outputs of similar age
#176,465
of 329,244 outputs
Outputs of similar age from Current Oncology Reports
#16
of 28 outputs
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