↓ Skip to main content

Comparison of quantification algorithms for circulating cell-free DNA methylation biomarkers in blood plasma from cancer patients

Overview of attention for article published in Clinical Epigenetics, December 2017
Altmetric Badge

Mentioned by

twitter
2 X users

Citations

dimensions_citation
34 Dimensions

Readers on

mendeley
47 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
Comparison of quantification algorithms for circulating cell-free DNA methylation biomarkers in blood plasma from cancer patients
Published in
Clinical Epigenetics, December 2017
DOI 10.1186/s13148-017-0425-4
Pubmed ID
Authors

Luka de Vos, Heidrun Gevensleben, Andreas Schröck, Alina Franzen, Glen Kristiansen, Friedrich Bootz, Dimo Dietrich

Abstract

SHOX2 and SEPT9 methylation in circulating cell-free DNA (ccfDNA) in blood are established powerful and clinically valuable biomarkers for diagnosis, staging, prognosis, and monitoring of cancer patients. The aim of the present study was to evaluate different quantification algorithms (relative quantification, absolute quantification, quasi-digital PCR) with regard to their clinical performance. Methylation analyses were performed in a training cohort (141 patients with head and neck squamous cell carcinoma [HNSCC], 170 control cases) and a testing cohort (137 HNSCC cases, 102 controls). DNA was extracted from plasma samples, bisulfite-converted, and analyzed via quantitative real-time PCR. SHOX2 and SEPT9 methylations were assessed separately and as panel [mean SEPT9/SHOX2 ] using the ΔCT method for absolute quantification and the ΔΔCT-method for relative quantification. Quasi-digital PCR was defined as the number of amplification-positive PCR replicates. The diagnostic (sensitivity, specificity, area under the curve (AUC) of the receiver operating characteristic (ROC)) and prognostic accuracy (hazard ratio (HR) from Cox regression) were evaluated. Sporadic methylation in control samples necessitated the introduction of cutoffs resulting in 61-63% sensitivity/90-92% specificity (SEPT9/training), 53-57% sensitivity/87-90% specificity (SHOX2/training), and 64-65% sensitivity/90-91% specificity (mean SEPT9/SHOX2 /training). Results were confirmed in a testing cohort with 54-56% sensitivity/88-90% specificity (SEPT9/testing), 43-48% sensitivity/93-95% specificity (SHOX2/testing), and 49-58% sensitivity/88-94% specificity (mean SEPT9/SHOX2 /testing). All algorithms showed comparable cutoff-independent diagnostic accuracy with largely overlapping 95% confidence intervals (SEPT9: AUCtraining = 0.79-0.80; AUCtesting = 0.74-0.75; SHOX2: AUCtraining = 0.78-0.81, AUCtesting = 0.77-0.79; mean SEPT9/SHOX2 : AUCtraining = 0.81-0.84, AUCtesting = 0.80). The accurate prediction of overall survival was possible with all three algorithms (training cohort: HR SEPT9  = 1.23-1.90, HR SHOX2  = 1.14-1.85, HRmeanSEPT9/SHOX2  =1.19-1.89 ; testing cohort: HR SEPT9  =1.22-1.67, HR SHOX2  = 1.15-1.71, HRmeanSEPT9/SHOX2  = 1.12-1.77). The concordant clinical performance based on different quantification algorithms allows for the application of various diagnostic platforms for the analysis of ccfDNA methylation biomarkers.

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

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 17%
Student > Master 6 13%
Student > Bachelor 6 13%
Student > Ph. D. Student 5 11%
Student > Postgraduate 2 4%
Other 7 15%
Unknown 13 28%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 32%
Medicine and Dentistry 13 28%
Agricultural and Biological Sciences 2 4%
Nursing and Health Professions 2 4%
Sports and Recreations 1 2%
Other 1 2%
Unknown 13 28%
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 08 December 2017.
All research outputs
#18,577,751
of 23,009,818 outputs
Outputs from Clinical Epigenetics
#1,005
of 1,264 outputs
Outputs of similar age
#325,770
of 437,935 outputs
Outputs of similar age from Clinical Epigenetics
#19
of 23 outputs
Altmetric has tracked 23,009,818 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,264 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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 437,935 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.