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Integrated genomic analysis of mitochondrial RNA processing in human cancers

Overview of attention for article published in Genome Medicine, April 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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12 tweeters
facebook
2 Facebook pages

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
28 Mendeley
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1 CiteULike
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Title
Integrated genomic analysis of mitochondrial RNA processing in human cancers
Published in
Genome Medicine, April 2017
DOI 10.1186/s13073-017-0426-0
Pubmed ID
Authors

Youssef Idaghdour, Alan Hodgkinson

Abstract

The mitochondrial genome is transcribed as continuous polycistrons of RNA containing multiple genes. As a consequence, post-transcriptional events are critical for the regulation of gene expression and therefore all aspects of mitochondrial function. One particularly important process is the m(1)A/m(1)G RNA methylation of the ninth position of different mitochondrial tRNAs, which allows efficient processing of mitochondrial mRNAs and protein translation, and de-regulation of genes involved in these processes has been associated with altered mitochondrial function. Although mitochondria play a key role in cancer, the status of mitochondrial RNA processing in tumorigenesis is unknown. We measure and assess mitochondrial RNA processing using integrated genomic analysis of RNA sequencing and genotyping data from 1226 samples across 12 different cancer types. We focus on the levels of m(1)A and m(1)G RNA methylation in mitochondrial tRNAs in normal and tumor samples and use supervised and unsupervised statistical analysis to compare the levels of these modifications to patient whole genome genotypes, nuclear gene expression, and survival outcomes. We find significant changes to m(1)A and m(1)G RNA methylation levels in mitochondrial tRNAs in tumor tissues across all cancers. Pathways of RNA processing are strongly associated with methylation levels in normal tissues (P = 3.27 × 10(-31)), yet these associations are lost in tumors. Furthermore, we report 18 gene-by-disease-state interactions where altered RNA methylation levels occur under cancer status conditional on genotype, implicating genes associated with mitochondrial function or cancer (e.g., CACNA2D2, LMO2, and FLT3) and suggesting that nuclear genetic variation can potentially modulate an individual's ability to maintain unaltered rates of mitochondrial RNA processing under cancer status. Finally, we report a significant association between the magnitude of methylation level changes in tumors and patient survival outcomes. We report widespread variation of mitochondrial RNA processing between normal and tumor tissues across all cancer types investigated and show that these alterations are likely modulated by patient genotype and may impact patient survival outcomes. These results highlight the potential clinical relevance of altered mitochondrial RNA processing and provide broad new insights into the importance and complexity of these events in cancer.

Twitter Demographics

The data shown below were collected from the profiles of 12 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 21%
Researcher 6 21%
Student > Bachelor 4 14%
Student > Doctoral Student 2 7%
Student > Master 2 7%
Other 3 11%
Unknown 5 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 32%
Agricultural and Biological Sciences 5 18%
Engineering 2 7%
Medicine and Dentistry 2 7%
Computer Science 2 7%
Other 3 11%
Unknown 5 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 30 May 2017.
All research outputs
#2,712,380
of 14,372,231 outputs
Outputs from Genome Medicine
#628
of 1,007 outputs
Outputs of similar age
#69,225
of 266,702 outputs
Outputs of similar age from Genome Medicine
#7
of 11 outputs
Altmetric has tracked 14,372,231 research outputs across all sources so far. Compared to these this one has done well and is in the 77th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,007 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.6. This one is in the 36th percentile – i.e., 36% 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 266,702 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 73% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.