Title |
Unraveling the clonal hierarchy of somatic genomic aberrations
|
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Published in |
Genome Biology, August 2014
|
DOI | 10.1186/s13059-014-0439-6 |
Pubmed ID | |
Authors |
Davide Prandi, Sylvan C Baca, Alessandro Romanel, Christopher E Barbieri, Juan-Miguel Mosquera, Jacqueline Fontugne, Himisha Beltran, Andrea Sboner, Levi A Garraway, Mark A Rubin, Francesca Demichelis |
Abstract |
Defining the chronology of molecular alterations may identify milestones in carcinogenesis. To unravel the temporal evolution of aberrations from clinical tumors, we developed CLONET, which upon estimation of tumor admixture and ploidy infers the clonal hierarchy of genomic aberrations. Comparative analysis across 100 sequenced genomes from prostate, melanoma, and lung cancers established diverse evolutionary hierarchies, demonstrating the early disruption of tumor-specific pathways. The analyses highlight the diversity of clonal evolution within and across tumor types that might be informative for risk stratification and patient selection for targeted therapies. CLONET addresses heterogeneous clinical samples seen in the setting of precision medicine. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Scientists | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 3% |
Italy | 3 | 2% |
Korea, Republic of | 1 | <1% |
Ireland | 1 | <1% |
Norway | 1 | <1% |
Australia | 1 | <1% |
France | 1 | <1% |
Spain | 1 | <1% |
United Kingdom | 1 | <1% |
Other | 0 | 0% |
Unknown | 137 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 50 | 33% |
Student > Ph. D. Student | 31 | 20% |
Student > Bachelor | 12 | 8% |
Other | 9 | 6% |
Student > Doctoral Student | 8 | 5% |
Other | 24 | 16% |
Unknown | 18 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 56 | 37% |
Biochemistry, Genetics and Molecular Biology | 32 | 21% |
Medicine and Dentistry | 22 | 14% |
Computer Science | 12 | 8% |
Mathematics | 2 | 1% |
Other | 4 | 3% |
Unknown | 24 | 16% |