Title |
Detection of TP53/PIK3CA Mutations in Cell-Free Plasma DNA From Metastatic Breast Cancer Patients Using Next Generation Sequencing
|
---|---|
Published in |
Clinical Breast Cancer, May 2016
|
DOI | 10.1016/j.clbc.2016.05.004 |
Pubmed ID | |
Authors |
Chiaki Nakauchi, Naofumi Kagara, Kenzo Shimazu, Atsushi Shimomura, Yasuto Naoi, Masafumi Shimoda, Seung Jin Kim, Shinzaburo Noguchi |
Abstract |
Circulating tumor DNA (ctDNA) within a liquid biopsy is a promising marker for genotyping metastatic tumors. We performed next generation whole exon sequencing of TP53 and PIK3CA genes, which are the 2 most common genetic alterations in breast cancer, in plasma DNA (pDNA) of 17 metastatic breast cancer (MBC) patients and in tumor DNA (tDNA) from their primary tumors. We identified 11 mutations (6 in TP53 and 5 in PIK3CA) in tDNA from 8 patients (47%) and 13 mutations (6 in TP53 and 7 in PIK3CA) in pDNA from 7 patients (41%). Six mutations in pDNA were also identified in tDNA but seven were not. Six MBC patients with TP53 and/or PIK3CA mutations in pDNA had a significantly worse survival rate (P < .05) after recurrence than that of the other 8 MBC patients without these mutations. Carcinoembryonic antigen and cancer antigen 15-3 levels did not correlate with prognosis (P = .675 and P = .877, respectively). These results suggest that mutations in ctDNA can be detected with next generation sequencing in MBC patients and could be a more useful prognostic factor for survival after recurrence than conventional tumor markers. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Sweden | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 69 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 9 | 13% |
Student > Ph. D. Student | 8 | 12% |
Student > Bachelor | 7 | 10% |
Other | 6 | 9% |
Student > Master | 5 | 7% |
Other | 11 | 16% |
Unknown | 23 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 19 | 28% |
Biochemistry, Genetics and Molecular Biology | 13 | 19% |
Agricultural and Biological Sciences | 4 | 6% |
Neuroscience | 2 | 3% |
Computer Science | 1 | 1% |
Other | 7 | 10% |
Unknown | 23 | 33% |