| Title |
Modeling head and neck cancer stem cell-mediated tumorigenesis
|
|---|---|
| Published in |
Cellular and Molecular Life Sciences, May 2016
|
| DOI | 10.1007/s00018-016-2226-x |
| Pubmed ID | |
| Authors |
Alexander T. Pearson, Trachette L. Jackson, Jacques E. Nör |
| Abstract |
A large body of literature has emerged supporting the importance of cancer stem cells (CSCs) in the pathogenesis of head and neck cancers. CSCs are a subpopulation of cells within a tumor that share the properties of self-renewal and multipotency with stem cells from normal tissue. Their functional relevance to the pathobiology of cancer arises from the unique properties of tumorigenicity, chemotherapy resistance, and their ability to metastasize and invade distant tissues. Several molecular profiles have been used to discriminate a stem cell from a non-stem cell. CSCs can be grown for study and further enriched using a number of in vitro techniques. An evolving option for translational research is the use of mathematical and computational models to describe the role of CSCs in complex tumor environments. This review is focused discussing the evidence emerging from modeling approaches that have clarified the impact of CSCs to the biology of cancer. |
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 % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 3% |
| Unknown | 37 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 26% |
| Student > Master | 7 | 18% |
| Student > Bachelor | 6 | 16% |
| Researcher | 3 | 8% |
| Professor | 2 | 5% |
| Other | 4 | 11% |
| Unknown | 6 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 13 | 34% |
| Biochemistry, Genetics and Molecular Biology | 8 | 21% |
| Agricultural and Biological Sciences | 5 | 13% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Immunology and Microbiology | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 7 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 24 August 2017.
All research outputs
#16,757,751
of 24,649,404 outputs
Outputs from Cellular and Molecular Life Sciences
#4,437
of 5,623 outputs
Outputs of similar age
#185,178
of 304,058 outputs
Outputs of similar age from Cellular and Molecular Life Sciences
#67
of 91 outputs
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