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Detection of GNAS mutations in intramuscular / cellular myxomas as diagnostic tool in the classification of myxoid soft tissue tumors

Overview of attention for article published in Diagnostic Pathology, August 2018
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Citations

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Title
Detection of GNAS mutations in intramuscular / cellular myxomas as diagnostic tool in the classification of myxoid soft tissue tumors
Published in
Diagnostic Pathology, August 2018
DOI 10.1186/s13000-018-0734-8
Pubmed ID
Authors

Sandra Sunitsch, Magdalena Maria Gilg, Karl Kashofer, Franz Gollowitsch, Andreas Leithner, Bernadette Liegl-Atzwanger

Abstract

Intramuscular / cellular myxomas and low-grade myxofibrosarcomas are two different tumor entities with a significant histological overlap, especially if dealing with small biopsies. Despite the morphological similarities, they differ considerably in their biological behaviour. Intramuscular / cellular myxoma rarely shows signs of recurrence and never metastasizes, in contrast to myxofibrosarcoma that tends to recur more aggressively and to metastasize haematologically. Therefore, it is of great importance to distinguish these lesions - evaluation of GNAS mutation status could be of tremendous help. We reviewed 13 cases with intramuscular / cellular myxomas. The 13 cases included 5 men and 8 women, aged from 33 to 71 years (mean age 55.5 years). Immunohistochemistry was performed as well as next generation sequencing. Ten cases were located in the lower extremities and three cases were located in the upper extremities. Two lesions were initially misdiagnosed as a low-grade myxofibrosarcoma. Performing next generation sequencing 12 out of 13 specimens showed a GNAS mutation. Our findings demonstrate that GNAS mutations are more common in intramuscular / cellular myxomas, than had been reported in literature in the past. Next generation sequencing for determining GNAS mutation status on small biopsies or diagnostically challenging cases facilitates the diagnosis of intramuscular / cellular myxoma and separates this tumor entity from its mimics.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters 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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Other 3 33%
Student > Master 2 22%
Professor 1 11%
Lecturer 1 11%
Student > Postgraduate 1 11%
Other 0 0%
Unknown 1 11%
Readers by discipline Count As %
Medicine and Dentistry 6 67%
Unknown 3 33%

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 17 August 2018.
All research outputs
#10,209,848
of 13,384,293 outputs
Outputs from Diagnostic Pathology
#459
of 833 outputs
Outputs of similar age
#154,418
of 223,479 outputs
Outputs of similar age from Diagnostic Pathology
#3
of 6 outputs
Altmetric has tracked 13,384,293 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 833 research outputs from this source. They receive a mean Attention Score of 2.3. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.