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Network-based analysis of oligodendrogliomas predicts novel cancer gene candidates within the region of the 1p/19q co-deletion

Overview of attention for article published in Acta Neuropathologica Communications, June 2018
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4 tweeters

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Title
Network-based analysis of oligodendrogliomas predicts novel cancer gene candidates within the region of the 1p/19q co-deletion
Published in
Acta Neuropathologica Communications, June 2018
DOI 10.1186/s40478-018-0544-y
Pubmed ID
Authors

Josef Gladitz, Barbara Klink, Michael Seifert

Abstract

Oligodendrogliomas are primary human brain tumors with a characteristic 1p/19q co-deletion of important prognostic relevance, but little is known about the pathology of this chromosomal mutation. We developed a network-based approach to identify novel cancer gene candidates in the region of the 1p/19q co-deletion. Gene regulatory networks were learned from gene expression and copy number data of 178 oligodendrogliomas and further used to quantify putative impacts of differentially expressed genes of the 1p/19q region on cancer-relevant pathways. We predicted 8 genes with strong impact on signaling pathways and 14 genes with strong impact on metabolic pathways widespread across the region of the 1p/19 co-deletion. Many of these candidates (e.g. ELTD1, SDHB, SEPW1, SLC17A7, SZRD1, THAP3, ZBTB17) are likely to push, whereas others (e.g. CAP1, HBXIP, KLK6, PARK7, PTAFR) might counteract oligodendroglioma development. For example, ELTD1, a functionally validated glioblastoma oncogene located on 1p, was overexpressed. Further, the known glioblastoma tumor suppressor SLC17A7 located on 19q was underexpressed. Moreover, known epigenetic alterations triggered by mutated SDHB in paragangliomas suggest that underexpressed SDHB in oligodendrogliomas may support and possibly enhance the epigenetic reprogramming induced by the IDH-mutation. We further analyzed rarely observed deletions and duplications of chromosomal arms within oligodendroglioma subcohorts identifying putative oncogenes and tumor suppressors that possibly influence the development of oligodendroglioma subgroups. Our in-depth computational study contributes to a better understanding of the pathology of the 1p/19q co-deletion and other chromosomal arm mutations. This might open opportunities for functional validations and new therapeutic strategies.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 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 > Ph. D. Student 8 31%
Researcher 3 12%
Student > Bachelor 2 8%
Student > Doctoral Student 2 8%
Librarian 1 4%
Other 3 12%
Unknown 7 27%
Readers by discipline Count As %
Medicine and Dentistry 8 31%
Biochemistry, Genetics and Molecular Biology 6 23%
Neuroscience 3 12%
Agricultural and Biological Sciences 1 4%
Chemistry 1 4%
Other 1 4%
Unknown 6 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 04 July 2018.
All research outputs
#7,759,956
of 13,799,368 outputs
Outputs from Acta Neuropathologica Communications
#451
of 725 outputs
Outputs of similar age
#133,200
of 271,216 outputs
Outputs of similar age from Acta Neuropathologica Communications
#1
of 1 outputs
Altmetric has tracked 13,799,368 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 725 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.0. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
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 271,216 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them