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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Atypical Teratoid/Rhabdoid Tumors Are Comprised of Three Epigenetic Subgroups with Distinct Enhancer Landscapes
|
|---|---|
| Published in |
Cancer Cell, February 2016
|
| DOI | 10.1016/j.ccell.2016.02.001 |
| Pubmed ID | |
| Authors |
Pascal D. Johann, Serap Erkek, Marc Zapatka, Kornelius Kerl, Ivo Buchhalter, Volker Hovestadt, David T.W. Jones, Dominik Sturm, Carl Hermann, Maia Segura Wang, Andrey Korshunov, Marina Rhyzova, Susanne Gröbner, Sebastian Brabetz, Lukas Chavez, Susanne Bens, Stefan Gröschel, Fabian Kratochwil, Andrea Wittmann, Laura Sieber, Christina Geörg, Stefan Wolf, Katja Beck, Florian Oyen, David Capper, Peter van Sluis, Richard Volckmann, Jan Koster, Rogier Versteeg, Andreas von Deimling, Till Milde, Olaf Witt, Andreas E. Kulozik, Martin Ebinger, Tarek Shalaby, Michael Grotzer, David Sumerauer, Josef Zamecnik, Jaume Mora, Nada Jabado, Michael D. Taylor, Annie Huang, Eleonora Aronica, Anna Bertoni, Bernhard Radlwimmer, Torsten Pietsch, Ulrich Schüller, Reinhard Schneppenheim, Paul A. Northcott, Jan O. Korbel, Reiner Siebert, Michael C. Frühwald, Peter Lichter, Roland Eils, Amar Gajjar, Martin Hasselblatt, Stefan M. Pfister, Marcel Kool |
| Abstract |
Atypical teratoid/rhabdoid tumor (ATRT) is one of the most common brain tumors in infants. Although the prognosis of ATRT patients is poor, some patients respond favorably to current treatments, suggesting molecular inter-tumor heterogeneity. To investigate this further, we genetically and epigenetically analyzed 192 ATRTs. Three distinct molecular subgroups of ATRTs, associated with differences in demographics, tumor location, and type of SMARCB1 alterations, were identified. Whole-genome DNA and RNA sequencing found no recurrent mutations in addition to SMARCB1 that would explain the differences between subgroups. Whole-genome bisulfite sequencing and H3K27Ac chromatin-immunoprecipitation sequencing of primary tumors, however, revealed clear differences, leading to the identification of subgroup-specific regulatory networks and potential therapeutic targets. |
X Demographics
The data shown below were collected from the profiles of 28 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 29% |
| Spain | 3 | 11% |
| United Kingdom | 3 | 11% |
| Canada | 1 | 4% |
| France | 1 | 4% |
| Switzerland | 1 | 4% |
| Portugal | 1 | 4% |
| India | 1 | 4% |
| Belgium | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 8 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 43% |
| Scientists | 12 | 43% |
| Practitioners (doctors, other healthcare professionals) | 3 | 11% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 428 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | <1% |
| Spain | 2 | <1% |
| United States | 2 | <1% |
| Portugal | 1 | <1% |
| United Kingdom | 1 | <1% |
| Italy | 1 | <1% |
| Japan | 1 | <1% |
| Czechia | 1 | <1% |
| Unknown | 417 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 69 | 16% |
| Student > Ph. D. Student | 64 | 15% |
| Student > Bachelor | 46 | 11% |
| Student > Postgraduate | 40 | 9% |
| Student > Master | 33 | 8% |
| Other | 85 | 20% |
| Unknown | 91 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 115 | 27% |
| Medicine and Dentistry | 105 | 25% |
| Agricultural and Biological Sciences | 68 | 16% |
| Neuroscience | 8 | 2% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | <1% |
| Other | 30 | 7% |
| Unknown | 98 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 28. 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 14 December 2021.
All research outputs
#1,427,441
of 26,017,215 outputs
Outputs from Cancer Cell
#1,028
of 3,188 outputs
Outputs of similar age
#23,192
of 316,588 outputs
Outputs of similar age from Cancer Cell
#19
of 54 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,188 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.9. This one has gotten more attention than average, scoring higher than 67% 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 316,588 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 54 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 64% of its contemporaries.