| Title |
Tumour heterogeneity: principles and practical consequences
|
|---|---|
| Published in |
Virchows Archiv, July 2016
|
| DOI | 10.1007/s00428-016-1987-9 |
| Pubmed ID | |
| Authors |
Giorgio Stanta, Stephan Wenzel Jahn, Serena Bonin, Gerald Hoefler |
| Abstract |
Two major reasons compel us to study tumour heterogeneity: firstly, it represents the basis of acquired therapy resistance, and secondly, it may be one of the major sources of the low level of reproducibility in clinical cancer research. The present review focuses on the heterogeneity of neoplastic disease, both within the primary tumour and between primary tumour and metastases. We discuss different levels of heterogeneity and the current understanding of the phenomenon, as well as imminent developments relevant for clinical research and diagnostic pathology. It is necessary to develop new tools to study heterogeneity and new biomarkers for heterogeneity. Established and new in situ methods will be very useful. In future studies, not only clonal heterogeneity needs to be addressed but also non-clonal phenotypic heterogeneity which might be important for therapy resistance. We also review heterogeneity established in major tumour types, in order to explore potential similarities that might help to define new strategies for targeted therapy. |
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 % |
|---|---|---|
| France | 1 | 50% |
| Brazil | 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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 40 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 20% |
| Researcher | 7 | 18% |
| Student > Master | 7 | 18% |
| Professor | 3 | 8% |
| Other | 2 | 5% |
| Other | 2 | 5% |
| Unknown | 11 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 12 | 30% |
| Medicine and Dentistry | 11 | 28% |
| Agricultural and Biological Sciences | 2 | 5% |
| Psychology | 1 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 13 | 33% |
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 15 July 2016.
All research outputs
#15,380,162
of 22,880,691 outputs
Outputs from Virchows Archiv
#1,272
of 1,951 outputs
Outputs of similar age
#226,646
of 354,681 outputs
Outputs of similar age from Virchows Archiv
#17
of 24 outputs
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