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MicroRNAs as markers of progression in cervical cancer: a systematic review

Overview of attention for article published in BMC Cancer, June 2018
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

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1 policy source
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2 X users

Citations

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140 Dimensions

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130 Mendeley
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Title
MicroRNAs as markers of progression in cervical cancer: a systematic review
Published in
BMC Cancer, June 2018
DOI 10.1186/s12885-018-4590-4
Pubmed ID
Authors

Barbara Pardini, Daniela De Maria, Antonio Francavilla, Cornelia Di Gaetano, Guglielmo Ronco, Alessio Naccarati

Abstract

Invasive cervical cancer (ICC) is caused by high-risk human papillomavirus types (HR-HPVs) and is usually preceded by a long phase of intraepithelial neoplasia (CIN). Before invasion, (epi) genetic changes, potentially applicable as molecular markers within cervical screening, occur in HPV host cells. Epigenetic alterations, such as dysregulation of microRNA (miRNA) expression, are frequently observed in ICC. The mechanisms and role of miRNA dysregulation in cervical carcinogenesis are still largely unknown. We provide an overview of the studies investigating miRNA expression in relation to ICC progression, highlighting their common outcomes and their weaknesses/strengths. To achieve this, we systematically searched through Pubmed database all articles between January 2010 and December 2017. From the 24 studies retrieved, miR-29a and miR-21 are the most frequently down- and up-regulated in ICC progression, respectively. Microarray-based studies show a small overlap, with miR-10a, miR-20b, miR-9, miR-16 and miR-106 found repeatedly dysregulated. miR-34a, miR-125 and miR-375 were also found dysregulated in cervical exfoliated cells in relation to cancer progression. The pivotal role of miRNAs in ICC progression and initial development is becoming more and more relevant. Available studies are essentially based on convenience material, entailing possible selection bias, and frequently of small size: all these points still represent a limitation to a wide comprehension of miRNAs relevant for ICC. The targeted approach instead of a genome-wide investigation still precludes the identification of all the relevant miRNAs in the process. The implementation of deep sequencing on large scale population-based studies will help to discover and validate the relation between altered miRNA expression and CC progression for the identification of biomarkers. Optimally, once explored on a miRNome scale, small specific miRNA signatures maybe used in the context of screening.

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

Geographical breakdown

Country Count As %
Unknown 130 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 22 17%
Student > Ph. D. Student 20 15%
Student > Master 13 10%
Researcher 11 8%
Student > Doctoral Student 5 4%
Other 17 13%
Unknown 42 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 30 23%
Medicine and Dentistry 23 18%
Agricultural and Biological Sciences 6 5%
Immunology and Microbiology 4 3%
Nursing and Health Professions 3 2%
Other 16 12%
Unknown 48 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 20 November 2023.
All research outputs
#7,099,186
of 25,287,709 outputs
Outputs from BMC Cancer
#1,803
of 8,916 outputs
Outputs of similar age
#113,015
of 336,120 outputs
Outputs of similar age from BMC Cancer
#38
of 144 outputs
Altmetric has tracked 25,287,709 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 8,916 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 79% 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 336,120 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 66% of its contemporaries.
We're also able to compare this research output to 144 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 72% of its contemporaries.