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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 (74th percentile)
  • Average Attention Score compared to outputs of the same age and source

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11 X users
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2 Facebook pages

Citations

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50 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.

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X Demographics

The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 20%
Researcher 10 20%
Student > Bachelor 6 12%
Student > Doctoral Student 3 6%
Student > Postgraduate 3 6%
Other 6 12%
Unknown 12 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 34%
Agricultural and Biological Sciences 5 10%
Nursing and Health Professions 2 4%
Neuroscience 2 4%
Computer Science 2 4%
Other 9 18%
Unknown 13 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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
#4,623,149
of 23,577,654 outputs
Outputs from Genome Medicine
#878
of 1,466 outputs
Outputs of similar age
#79,968
of 311,551 outputs
Outputs of similar age from Genome Medicine
#21
of 30 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,466 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.9. This one is in the 39th percentile – i.e., 39% 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 311,551 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 74% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.