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Functional divergence and convergence between the transcript network and gene network in lung adenocarcinoma

Overview of attention for article published in OncoTargets and therapy, January 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (57th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

twitter
3 tweeters

Citations

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2 Dimensions

Readers on

mendeley
9 Mendeley
Title
Functional divergence and convergence between the transcript network and gene network in lung adenocarcinoma
Published in
OncoTargets and therapy, January 2016
DOI 10.2147/ott.s94897
Pubmed ID
Authors

Min-Kung Hsu, Feng-Chi Chen, Chia-Lin Pan

Abstract

Alternative RNA splicing is a critical regulatory mechanism during tumorigenesis. However, previous oncological studies mainly focused on the splicing of individual genes. Whether and how transcript isoforms are coordinated to affect cellular functions remain underexplored. Also of great interest is how the splicing regulome cooperates with the transcription regulome to facilitate tumorigenesis. The answers to these questions are of fundamental importance to cancer biology. Here, we report a comparative study between the transcript-based network (TN) and the gene-based network (GN) derived from the transcriptomes of paired tumor-normal tissues from 77 lung adenocarcinoma patients. We demonstrate that the two networks differ significantly from each other in terms of patient clustering and the number and functions of network modules. Interestingly, the majority (89.5%) of multi-transcript genes have their transcript isoforms distributed in at least two TN modules, suggesting regulatory and functional divergences between transcript isoforms. Furthermore, TN and GN modules share onlŷ50%-60% of their biological functions. TN thus appears to constitute a regulatory layer separate from GN. Nevertheless, our results indicate that functional convergence and divergence both occur between TN and GN, implying complex interactions between the two regulatory layers. Finally, we report that the expression profiles of module members in both TN and GN shift dramatically yet concordantly during tumorigenesis. The mechanisms underlying this coordinated shifting remain unclear yet are worth further explorations. We show that in lung adenocarcinoma, transcript isoforms per se are coordinately regulated to conduct biological functions not conveyed by the network of genes. However, the two networks may interact closely with each other by sharing the same or related biological functions. Unraveling the effects and mechanisms of such interactions will significantly advance our understanding of this deadly disease.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 %
Italy 1 11%
Unknown 8 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 67%
Student > Master 1 11%
Professor 1 11%
Researcher 1 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 56%
Biochemistry, Genetics and Molecular Biology 2 22%
Engineering 2 22%

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 03 February 2016.
All research outputs
#3,008,082
of 7,089,314 outputs
Outputs from OncoTargets and therapy
#135
of 843 outputs
Outputs of similar age
#131,309
of 319,703 outputs
Outputs of similar age from OncoTargets and therapy
#21
of 206 outputs
Altmetric has tracked 7,089,314 research outputs across all sources so far. This one has received more attention than most of these and is in the 56th percentile.
So far Altmetric has tracked 843 research outputs from this source. They receive a mean Attention Score of 1.3. This one has done well, scoring higher than 82% 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 319,703 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 57% of its contemporaries.
We're also able to compare this research output to 206 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.