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Methylation analysis of plasma cell-free DNA for breast cancer early detection using bisulfite next-generation sequencing

Overview of attention for article published in Tumor Biology, July 2016
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  • Good Attention Score compared to outputs of the same age and source (69th percentile)

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75 Mendeley
Title
Methylation analysis of plasma cell-free DNA for breast cancer early detection using bisulfite next-generation sequencing
Published in
Tumor Biology, July 2016
DOI 10.1007/s13277-016-5190-z
Pubmed ID
Authors

Zibo Li, Xinwu Guo, Lili Tang, Limin Peng, Ming Chen, Xipeng Luo, Shouman Wang, Zhi Xiao, Zhongping Deng, Lizhong Dai, Kun Xia, Jun Wang

Abstract

Circulating cell-free DNA (cfDNA) has been considered as a potential biomarker for non-invasive cancer detection. To evaluate the methylation levels of six candidate genes (EGFR, GREM1, PDGFRB, PPM1E, SOX17, and WRN) in plasma cfDNA as biomarkers for breast cancer early detection, quantitative analysis of the promoter methylation of these genes from 86 breast cancer patients and 67 healthy controls was performed by using microfluidic-PCR-based target enrichment and next-generation bisulfite sequencing technology. The predictive performance of different logistic models based on methylation status of candidate genes was investigated by means of the area under the ROC curve (AUC) and odds ratio (OR) analysis. Results revealed that EGFR, PPM1E, and 8 gene-specific CpG sites showed significantly hypermethylation in cancer patients' plasma and significantly associated with breast cancer (OR ranging from 2.51 to 9.88). The AUC values for these biomarkers were ranging from 0.66 to 0.75. Combinations of multiple hypermethylated genes or CpG sites substantially improved the predictive performance for breast cancer detection. Our study demonstrated the feasibility of quantitative measurement of candidate gene methylation in cfDNA by using microfluidic-PCR-based target enrichment and bisulfite next-generation sequencing, which is worthy of further validation and potentially benefits a broad range of applications in clinical oncology practice. Quantitative analysis of methylation pattern of plasma cfDNA by next-generation sequencing might be a valuable non-invasive tool for early detection of breast cancer.

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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 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Uruguay 1 1%
Unknown 73 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 27%
Student > Bachelor 13 17%
Student > Master 8 11%
Student > Ph. D. Student 5 7%
Other 4 5%
Other 8 11%
Unknown 17 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 23 31%
Medicine and Dentistry 13 17%
Agricultural and Biological Sciences 9 12%
Nursing and Health Professions 4 5%
Computer Science 1 1%
Other 6 8%
Unknown 19 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 28 July 2016.
All research outputs
#15,380,359
of 22,881,154 outputs
Outputs from Tumor Biology
#1,051
of 2,623 outputs
Outputs of similar age
#235,176
of 364,029 outputs
Outputs of similar age from Tumor Biology
#24
of 92 outputs
Altmetric has tracked 22,881,154 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,623 research outputs from this source. They receive a mean Attention Score of 2.3. This one has gotten more attention than average, scoring higher than 53% 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 364,029 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 92 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.