Title |
The genomic landscape of chronic lymphocytic leukemia: clinical implications
|
---|---|
Published in |
BMC Medicine, May 2013
|
DOI | 10.1186/1741-7015-11-124 |
Pubmed ID | |
Authors |
Víctor Quesada, Andrew J Ramsay, David Rodríguez, Xose S Puente, Elías Campo, Carlos López-Otín |
Abstract |
A precise understanding of the genomic and epigenomic features of chronic lymphocytic leukemia (CLL) may benefit the study of the disease's staging and treatment. While recent reports have shed some light on these aspects, several challenges need to be addressed before translating this research into clinical practice. Thus, even the best candidate driver genes display low mutational rates compared to other tumors. This means that a large percentage of cases do not display clear tumor-driving point mutations, or show candidate driving point mutations with no obvious biochemical relationship to the more frequently mutated genes. This genomic landscape probably reflects either an unknown underlying biochemical mechanism playing a key role in CLL or multiple biochemical pathways independently driving the development of this tumor. The elucidation of either scenario will have important consequences on the clinical management of CLL. Herein, we review the recent advances in the definition of the genomic landscape of CLL and the ongoing research to characterize the underlying biochemical events that drive this disease. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 25% |
United States | 2 | 25% |
Unknown | 4 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 63% |
Scientists | 2 | 25% |
Practitioners (doctors, other healthcare professionals) | 1 | 13% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 3% |
United Kingdom | 1 | 1% |
Poland | 1 | 1% |
Germany | 1 | 1% |
Unknown | 72 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 20 | 26% |
Student > Ph. D. Student | 18 | 23% |
Student > Bachelor | 7 | 9% |
Student > Master | 7 | 9% |
Professor > Associate Professor | 4 | 5% |
Other | 9 | 12% |
Unknown | 12 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 19 | 25% |
Biochemistry, Genetics and Molecular Biology | 18 | 23% |
Medicine and Dentistry | 16 | 21% |
Immunology and Microbiology | 3 | 4% |
Social Sciences | 2 | 3% |
Other | 6 | 8% |
Unknown | 13 | 17% |