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Technical validation of an RT-qPCR in vitro diagnostic test system for the determination of breast cancer molecular subtypes by quantification of ERBB2, ESR1, PGR and MKI67 mRNA levels from formalin-fi…

Overview of attention for article published in BMC Cancer, July 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)

Mentioned by

news
2 news outlets
policy
1 policy source
twitter
1 tweeter

Citations

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30 Dimensions

Readers on

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55 Mendeley
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Title
Technical validation of an RT-qPCR in vitro diagnostic test system for the determination of breast cancer molecular subtypes by quantification of ERBB2, ESR1, PGR and MKI67 mRNA levels from formalin-fixed paraffin-embedded breast tumor specimens
Published in
BMC Cancer, July 2016
DOI 10.1186/s12885-016-2476-x
Pubmed ID
Authors

Mark Laible, Kornelia Schlombs, Katharina Kaiser, Elke Veltrup, Stefanie Herlein, Sotiris Lakis, Robert Stöhr, Sebastian Eidt, Arndt Hartmann, Ralph M. Wirtz, Ugur Sahin

Abstract

MammaTyper is a novel CE-marked in vitro diagnostic RT-qPCR assay which assigns routinely processed breast cancer specimens into the molecular subtypes Luminal A-like, Luminal B-like (HER2 positive or negative), HER2 positive (non-luminal) and Triple negative (ductal) according to the mRNA expression of ERBB2, ESR1, PGR and MKI67 and the St Gallen consensus surrogate clinical definition. Until now and regarding formalin-fixed, paraffin-embedded material (FFPE), this has been a task mostly accomplished by immunohistochemistry (IHC). However the discrepancy rates of IHC for the four breast cancer biomarkers are frequently under debate, especially for Ki-67 which carries the highest degree of inter- and even intra-observer variability. Herein we describe a series of studies in FFPE specimens which aim to fully validate the analytical performance of the MammaTyper assay, including the site to site reproducibility of the individual marker measurements. Tumor RNA was extracted with the novel RNXtract RNA extraction kit. Synthetic RNA was used to assess the sensitivity of the RNXtract kit. DNA and RNA specific qPCR assays were used so as to determine analyte specificity of RNXtract. For the assessment of limit of blank, limit of detection, analytical measurement range and PCR efficiency of the MammaTyper kit serial dilutions of samples were used. Analytical precision studies of MammaTyper were built around two different real time PCR platforms and involved breast tumor samples belonging to different subtypes analyzed across multiple sites and under various stipulated conditions. The MammaTyper assay robustness was tested against RNA input variations, alternative extraction methods and tumor cell content. Individual assays were linear up to at least 32.33 and 33.56 Cqs (quantification cycles) for the two qPCR platforms tested. PCR efficiency ranged from 99 to 109 %. In qPCR platform 1, estimates for assay specific inter-site standard deviations (SD) were between 0.14 and 0.20 Cqs accompanied by >94 % concordant single marker assignments for all four markers. In platform 2, the inter-site SD estimates were between 0.40 and 0.66 Cqs while the concordance for single marker assignments was >94 % for all four markers. The agreement reached between the two qPCR systems located in one site was 100 % for ERBB2, 96.9 % for ESR1, 97.2 % for PGR and 98.6 % for MKI67. RT-qPCR for individual markers was stable up to a 64-fold dilution for a typical clinical sample. There was no change in assay performance detected at the level of individual markers or subtypes after using different RNA isolation methods. The presence of up to 80 % of surrounding non-tumor tissue including in situ carcinoma did not affect the assay output. Sixteen out of 20 RNXtract eluates yielded more than 50 ng/μl of RNA (average RNA output: 233 ng/μl), whereas DNA contamination per sample was restricted to less than 15 ng/μl. Median recovery rate of RNA extraction was 91.0 %. In this study the performance characteristics of MammaTyper were successfully validated. The various sources of analytical perturbations resulted in negligible variations in individual marker assessments. Therefore, MammaTyper may serve as a technical improvement to current standards for decentralized FFPE-based routine assessment of the commonly used breast cancer biomarkers and for molecular subtyping of breast cancer specimens.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 2%
Uruguay 1 2%
Unknown 53 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 18%
Student > Bachelor 8 15%
Other 6 11%
Student > Ph. D. Student 5 9%
Student > Master 5 9%
Other 14 25%
Unknown 7 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 22%
Medicine and Dentistry 10 18%
Agricultural and Biological Sciences 5 9%
Nursing and Health Professions 4 7%
Computer Science 4 7%
Other 8 15%
Unknown 12 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 January 2019.
All research outputs
#1,007,954
of 14,110,318 outputs
Outputs from BMC Cancer
#170
of 5,380 outputs
Outputs of similar age
#26,246
of 258,768 outputs
Outputs of similar age from BMC Cancer
#1
of 1 outputs
Altmetric has tracked 14,110,318 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,380 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done particularly well, scoring higher than 96% 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 258,768 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 89% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them