↓ Skip to main content

Cell-free DNA as a molecular tool for monitoring disease progression and response to therapy in breast cancer patients

Overview of attention for article published in Breast Cancer Research and Treatment, December 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

news
1 news outlet
twitter
2 X users

Citations

dimensions_citation
52 Dimensions

Readers on

mendeley
64 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Cell-free DNA as a molecular tool for monitoring disease progression and response to therapy in breast cancer patients
Published in
Breast Cancer Research and Treatment, December 2015
DOI 10.1007/s10549-015-3635-5
Pubmed ID
Authors

Diana H. Liang, Joe E. Ensor, Zhe-bin Liu, Asmita Patel, Tejal A. Patel, Jenny C. Chang, Angel A. Rodriguez

Abstract

Due to the spatial and temporal genomic heterogeneity of breast cancer, genomic sequencing obtained from a single biopsy may not capture the complete genomic profile of tumors. Thus, we propose that cell-free DNA (cfDNA) in plasma may be an alternate source of genomic information to provide comprehensive data throughout a patient's clinical course. We performed a retrospective chart review of 100 patients with stage 4 or high-risk stage 3 breast cancer. The degree of agreement between genomic alterations found in tumor DNA (tDNA) and cfDNA was determined by Cohen's Kappa. Clinical disease progression was compared to mutant allele frequency using a two-sided Fisher's exact test. The presence of mutations and mutant allele frequency was correlated with progression-free survival (PFS) using a Cox proportional hazards model and a log-rank test. The most commonly found genomic alterations were mutations in TP53 and PIK3CA, and amplification of EGFR and ERBB2. PIK3CA mutation and ERBB2 amplification demonstrated robust agreement between tDNA and cfDNA (Cohen's kappa = 0.64 and 0.77, respectively). TP53 mutation and EGFR amplification demonstrated poor agreement between tDNA and cfDNA (Cohen's kappa = 0.18 and 0.33, respectively). The directional changes of TP53 and PIK3CA mutant allele frequency were closely associated with response to therapy (p = 0.002). The presence of TP53 mutation (p = 0.0004) and PIK3CA mutant allele frequency [p = 0.01, HR 1.074 (95 % CI 1.018-1.134)] was excellent predictors of PFS. Identification of selected cancer-specific genomic alterations from cfDNA may be a noninvasive way to monitor disease progression, predict PFS, and offer targeted therapy.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
Ireland 1 2%
Unknown 62 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 17%
Student > Master 8 13%
Student > Bachelor 7 11%
Student > Doctoral Student 6 9%
Student > Ph. D. Student 6 9%
Other 10 16%
Unknown 16 25%
Readers by discipline Count As %
Medicine and Dentistry 17 27%
Biochemistry, Genetics and Molecular Biology 13 20%
Agricultural and Biological Sciences 9 14%
Pharmacology, Toxicology and Pharmaceutical Science 3 5%
Mathematics 1 2%
Other 4 6%
Unknown 17 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 April 2023.
All research outputs
#4,305,031
of 23,662,553 outputs
Outputs from Breast Cancer Research and Treatment
#749
of 4,768 outputs
Outputs of similar age
#70,188
of 393,034 outputs
Outputs of similar age from Breast Cancer Research and Treatment
#15
of 66 outputs
Altmetric has tracked 23,662,553 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,768 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one has done well, scoring higher than 84% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 393,034 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 66 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.