Title |
Precision medicine for cancer with next-generation functional diagnostics
|
---|---|
Published in |
Nature Reviews Cancer, November 2015
|
DOI | 10.1038/nrc4015 |
Pubmed ID | |
Authors |
Adam A. Friedman, Anthony Letai, David E. Fisher, Keith T. Flaherty |
Abstract |
Precision medicine is about matching the right drugs to the right patients. Although this approach is technology agnostic, in cancer there is a tendency to make precision medicine synonymous with genomics. However, genome-based cancer therapeutic matching is limited by incomplete biological understanding of the relationship between phenotype and cancer genotype. This limitation can be addressed by functional testing of live patient tumour cells exposed to potential therapies. Recently, several 'next-generation' functional diagnostic technologies have been reported, including novel methods for tumour manipulation, molecularly precise assays of tumour responses and device-based in situ approaches; these address the limitations of the older generation of chemosensitivity tests. The promise of these new technologies suggests a future diagnostic strategy that integrates functional testing with next-generation sequencing and immunoprofiling to precisely match combination therapies to individual cancer patients. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 25 | 40% |
United Kingdom | 4 | 6% |
Spain | 3 | 5% |
Australia | 3 | 5% |
Korea, Republic of | 2 | 3% |
Canada | 1 | 2% |
Belgium | 1 | 2% |
India | 1 | 2% |
Chile | 1 | 2% |
Other | 3 | 5% |
Unknown | 19 | 30% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 33 | 52% |
Scientists | 19 | 30% |
Practitioners (doctors, other healthcare professionals) | 7 | 11% |
Science communicators (journalists, bloggers, editors) | 4 | 6% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 4 | <1% |
Russia | 2 | <1% |
Canada | 2 | <1% |
France | 1 | <1% |
Italy | 1 | <1% |
Australia | 1 | <1% |
Korea, Republic of | 1 | <1% |
Switzerland | 1 | <1% |
South Africa | 1 | <1% |
Other | 6 | <1% |
Unknown | 723 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 158 | 21% |
Student > Ph. D. Student | 139 | 19% |
Student > Master | 89 | 12% |
Student > Bachelor | 62 | 8% |
Other | 40 | 5% |
Other | 131 | 18% |
Unknown | 124 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 150 | 20% |
Agricultural and Biological Sciences | 147 | 20% |
Medicine and Dentistry | 111 | 15% |
Engineering | 55 | 7% |
Computer Science | 25 | 3% |
Other | 105 | 14% |
Unknown | 150 | 20% |