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TP53 mutation analysis in chronic lymphocytic leukemia: comparison of different detection methods

Overview of attention for article published in Tumor Biology, December 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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3 X users
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1 Google+ user

Citations

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37 Mendeley
Title
TP53 mutation analysis in chronic lymphocytic leukemia: comparison of different detection methods
Published in
Tumor Biology, December 2014
DOI 10.1007/s13277-014-2971-0
Pubmed ID
Authors

Barbara Kantorova, Jitka Malcikova, Jana Smardova, Sarka Pavlova, Martin Trbusek, Nikola Tom, Karla Plevova, Boris Tichy, Sim Truong, Eva Diviskova, Jana Kotaskova, Alexandra Oltova, Nancy Patten, Yvona Brychtova, Michael Doubek, Jiri Mayer, Sarka Pospisilova

Abstract

TP53 gene defects represent a strong adverse prognostic factor for patient survival and treatment resistance in chronic lymphocytic leukemia (CLL). Although various methods for TP53 mutation analysis have been reported, none of them allow the identification of all occurring sequence variants, and the most suitable methodology is still being discussed. The aim of this study was to determine the limitations of commonly used methods for TP53 mutation examination in CLL and propose an optimal approach for their detection. We examined 182 CLL patients enriched for high-risk cases using denaturing high-performance liquid chromatography (DHPLC), functional analysis of separated alleles in yeast (FASAY), and the AmpliChip p53 Research Test in parallel. The presence of T53 gene mutations was also evaluated using ultra-deep next generation sequencing (NGS) in 69 patients. In total, 79 TP53 mutations in 57 (31 %) patients were found; among them, missense substitutions predominated (68 % of detected mutations). Comparing the efficacy of the methods used, DHPLC and FASAY both combined with direct Sanger sequencing achieved the best results, identifying 95 % and 93 % of TP53-mutated patients. Nevertheless, we showed that in CLL patients carrying low-proportion TP53 mutation, the more sensitive approach, e.g., ultra-deep NGS, might be more appropriate. TP53 gene analysis using DHPLC or FASAY is a suitable approach for mutation detection. Ultra-deep NGS has the potential to overcome shortcomings of methods currently used, allows the detection of minor proportion mutations, and represents thus a promising methodology for near future.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 19%
Student > Master 6 16%
Researcher 6 16%
Student > Bachelor 5 14%
Student > Doctoral Student 2 5%
Other 6 16%
Unknown 5 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 32%
Agricultural and Biological Sciences 9 24%
Medicine and Dentistry 5 14%
Decision Sciences 1 3%
Nursing and Health Professions 1 3%
Other 2 5%
Unknown 7 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 December 2014.
All research outputs
#13,185,276
of 22,775,504 outputs
Outputs from Tumor Biology
#866
of 2,622 outputs
Outputs of similar age
#169,042
of 353,184 outputs
Outputs of similar age from Tumor Biology
#48
of 166 outputs
Altmetric has tracked 22,775,504 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,622 research outputs from this source. They receive a mean Attention Score of 2.2. This one has gotten more attention than average, scoring higher than 66% 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 353,184 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 166 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 70% of its contemporaries.