Title |
Circulating tumour DNA sequence analysis as an alternative to multiple myeloma bone marrow aspirates
|
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Published in |
Nature Communications, May 2017
|
DOI | 10.1038/ncomms15086 |
Pubmed ID | |
Authors |
Olena Kis, Rayan Kaedbey, Signy Chow, Arnavaz Danesh, Mark Dowar, Tiantian Li, Zhihua Li, Jessica Liu, Mark Mansour, Esther Masih-Khan, Tong Zhang, Scott V. Bratman, Amit M. Oza, Suzanne Kamel-Reid, Suzanne Trudel, Trevor J. Pugh |
Abstract |
The requirement for bone-marrow aspirates for genomic profiling of multiple myeloma poses an obstacle to enrolment and retention of patients in clinical trials. We evaluated whether circulating cell-free DNA (cfDNA) analysis is comparable to molecular profiling of myeloma using bone-marrow tumour cells. We report here a hybrid-capture-based Liquid Biopsy Sequencing (LB-Seq) method used to sequence all protein-coding exons of KRAS, NRAS, BRAF, EGFR and PIK3CA in 64 cfDNA specimens from 53 myeloma patients to >20,000 × median coverage. This method includes a variant filtering algorithm that enables detection of tumour-derived fragments present in cfDNA at allele frequencies as low as 0.25% (median 3.2%, range 0.25-46%). Using LB-Seq analysis of 48 cfDNA specimens with matched bone-marrow data, we detect 49/51 likely somatic mutations, with subclonal hierarchies reflecting tumour profiling (96% concordance), and four additional mutations likely missed by bone-marrow testing (>98% specificity). Overall, LB-Seq is a high fidelity adjunct to genetic profiling of bone-marrow in multiple myeloma. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 31% |
China | 1 | 8% |
Netherlands | 1 | 8% |
Unknown | 7 | 54% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 10 | 77% |
Practitioners (doctors, other healthcare professionals) | 2 | 15% |
Scientists | 1 | 8% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 166 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 42 | 25% |
Student > Ph. D. Student | 22 | 13% |
Student > Bachelor | 19 | 11% |
Other | 16 | 10% |
Student > Doctoral Student | 12 | 7% |
Other | 26 | 16% |
Unknown | 29 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 47 | 28% |
Biochemistry, Genetics and Molecular Biology | 44 | 27% |
Agricultural and Biological Sciences | 19 | 11% |
Computer Science | 6 | 4% |
Engineering | 5 | 3% |
Other | 12 | 7% |
Unknown | 33 | 20% |