Title |
Cell-Free DNA Next-Generation Sequencing in Pancreatobiliary Carcinomas
|
---|---|
Published in |
Cancer Discovery, September 2015
|
DOI | 10.1158/2159-8290.cd-15-0274 |
Pubmed ID | |
Authors |
Oliver A. Zill, Claire Greene, Dragan Sebisanovic, Lai Mun Siew, Jim Leng, Mary Vu, Andrew E. Hendifar, Zhen Wang, Chloe E. Atreya, Robin K. Kelley, Katherine Van Loon, Andrew H. Ko, Margaret A. Tempero, Trever G. Bivona, Pamela N. Munster, AmirAli Talasaz, Eric A. Collisson |
Abstract |
Patients with pancreatic and biliary carcinomas lack personalized treatment options, in part because biopsies are often inadequate for molecular characterization. Cell-free DNA (cfDNA) sequencing may enable a precision oncology approach in this setting. We attempted to prospectively analyze 54 genes in tumor and cfDNA for 26 patients. Tumor sequencing failed in nine patients (35%). In the remaining 17, 90.3% (95% CI: 73.1-97.5%) of mutations detected in tumor biopsies were also detected in cfDNA. The diagnostic accuracy of cfDNA sequencing was 97.7%, with 92.3% average sensitivity and 100% specificity across five informative genes. Changes in cfDNA correlated well with tumor marker dynamics in serial sampling (r=0.93). We demonstrate that cfDNA sequencing is feasible, accurate, and sensitive in identifying tumor-derived mutations without prior knowledge of tumor genotype or the abundance of circulating tumor DNA. cfDNA sequencing should be considered in pancreatobiliary cancer trials where tissue sampling is unsafe, infeasible, or otherwise unsuccessful. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 50% |
United Kingdom | 1 | 10% |
China | 1 | 10% |
Italy | 1 | 10% |
Unknown | 2 | 20% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 6 | 60% |
Scientists | 3 | 30% |
Practitioners (doctors, other healthcare professionals) | 1 | 10% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | <1% |
Ireland | 1 | <1% |
Unknown | 216 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 52 | 24% |
Student > Ph. D. Student | 32 | 15% |
Student > Master | 18 | 8% |
Other | 14 | 6% |
Student > Bachelor | 14 | 6% |
Other | 41 | 19% |
Unknown | 48 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 59 | 27% |
Agricultural and Biological Sciences | 41 | 19% |
Biochemistry, Genetics and Molecular Biology | 37 | 17% |
Computer Science | 3 | 1% |
Immunology and Microbiology | 3 | 1% |
Other | 20 | 9% |
Unknown | 56 | 26% |