↓ Skip to main content

MicroRNA expression profiling for the prediction of resistance to neoadjuvant radiochemotherapy in squamous cell carcinoma of the esophagus

Overview of attention for article published in Journal of Translational Medicine, April 2018
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 (80th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
1 news outlet
twitter
1 X user

Citations

dimensions_citation
37 Dimensions

Readers on

mendeley
26 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
MicroRNA expression profiling for the prediction of resistance to neoadjuvant radiochemotherapy in squamous cell carcinoma of the esophagus
Published in
Journal of Translational Medicine, April 2018
DOI 10.1186/s12967-018-1492-9
Pubmed ID
Authors

Julia Slotta-Huspenina, Enken Drecoll, Marcus Feith, Daniel Habermehl, Stephanie Combs, Wilko Weichert, Marcus Bettstetter, Karen Becker, Rupert Langer

Abstract

MicroRNAs (miRNAs) play an important role in cancer biology. Neoadjuvant radiochemotherapy followed by surgery is a standard treatment for locally advanced esophageal squamous cell carcinoma (ESCC). However, a subset of patients do not respond. We evaluated whether miRNA profiles can predict resistance to radiochemotherapy. Formalin-fixed, paraffin-embedded pretherapeutic biopsies of patients treated by radiochemotherapy followed by esophagectomy were analyzed. The response was determined by histopathological tumor regression grading. miRNA profiling was performed by microarray analysis (Agilent platform) in 16 non-responders and 15 responders. Differentially expressed miRNAs were confirmed by real-time quantitative PCR (qRT-PCR) in an expanded cohort of 53 cases. The miRNA profiles within and between non-responders and responders were highly similar (r = 0.96, 0.94 and 0.95). However, 12 miRNAs were differentially expressed (> twofold; p ≤ 0.025): non-responders showed upregulation of hsa-miR-1323, hsa-miR-3678-3p, hsv2-miR-H7-3p, hsa-miR-194*, hsa-miR-3152, kshv-miR-K12-4-3p, hsa-miR-665 and hsa-miR-3659 and downregulation of hsa-miR-126*, hsa-miR-484, hsa-miR-330-3p and hsa-miR-3653. qRT-PCR analysis confirmed the microarray findings for hsa-miR-194* and hsa-miR-665 (p < 0.001 each) with AUC values of 0.811 (95% CI 0.694-0.927) and 0.817 (95% CI 0.704-0.930), respectively, in ROC analysis. Our results indicate that miRNAs are involved in the therapeutic response in ESCC and suggest that miRNA profiles could facilitate pretherapeutic patient selection.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 23%
Student > Bachelor 3 12%
Student > Ph. D. Student 3 12%
Lecturer 2 8%
Librarian 1 4%
Other 4 15%
Unknown 7 27%
Readers by discipline Count As %
Medicine and Dentistry 7 27%
Biochemistry, Genetics and Molecular Biology 4 15%
Pharmacology, Toxicology and Pharmaceutical Science 2 8%
Agricultural and Biological Sciences 2 8%
Unspecified 1 4%
Other 1 4%
Unknown 9 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 April 2023.
All research outputs
#3,017,975
of 23,642,687 outputs
Outputs from Journal of Translational Medicine
#491
of 4,190 outputs
Outputs of similar age
#62,557
of 327,594 outputs
Outputs of similar age from Journal of Translational Medicine
#12
of 101 outputs
Altmetric has tracked 23,642,687 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,190 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done well, scoring higher than 87% 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 327,594 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 80% of its contemporaries.
We're also able to compare this research output to 101 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.