Evidence map›Paper›PMID 28206648›Full record

ArticleNucleic acids research2017

Knowledge about the presence or absence of miRNA isoforms (isomiRs) can successfully discriminate amongst 32 TCGA cancer types.

Aristeidis G Telonis, Rogan Magee, Phillipe Loher, Inna Chervoneva, Eric Londin, Isidore Rigoutsos

Abstract read
In one paragraph

Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 133 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
133citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

133 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. In silico unwinding ofRNA biology · 2026
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Quantification of Tissue and Circulating MicroRNAs by Droplet Digital PCR.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  12. IsomiR stoichiometry changes as disease biomarkers.Molecular therapy. Nucleic acids · 2025
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. ncRNA Editing: Functional Characterization and Computational Resources.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  20. Article

73 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Aristeidis G TelonisComputational Medicine Center, Sidney Kimmel Medical College, Thomas Jefferson University, Thomas Jefferson University, PA 19107, USA.
Rogan MageeComputational Medicine Center, Sidney Kimmel Medical College, Thomas Jefferson University, Thomas Jefferson University, PA 19107, USA.
Phillipe LoherComputational Medicine Center, Sidney Kimmel Medical College, Thomas Jefferson University, Thomas Jefferson University, PA 19107, USA.
Inna ChervonevaDivision of Biostatistics, Thomas Jefferson University, Philadelphia, PA 19107, USA.
Eric LondinComputational Medicine Center, Sidney Kimmel Medical College, Thomas Jefferson University, Thomas Jefferson University, PA 19107, USA.
Isidore RigoutsosComputational Medicine Center, Sidney Kimmel Medical College, Thomas Jefferson University, Thomas Jefferson University, PA 19107, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Isoforms of human miRNAs (isomiRs) are constitutively expressed with tissue- and disease-subtype-dependencies. We studied 10 271 tumor datasets from The Cancer Genome Atlas (TCGA) to evaluate whether isomiRs can distinguish amongst 32 TCGA cancers. Unlike previous approaches, we built a classifier that relied solely on 'binarized' isomiR profiles: each isomiR is simply labeled as 'present' or 'absent'. The resulting classifier successfully labeled tumor datasets with an average sensitivity of 90% and a false discovery rate (FDR) of 3%, surpassing the performance of expression-based classification. The classifier maintained its power even after a 15× reduction in the number of isomiRs that were used for training. Notably, the classifier could correctly predict the cancer type in non-TCGA datasets from diverse platforms. Our analysis revealed that the most discriminatory isomiRs happen to also be differentially expressed between normal tissue and cancer. Even so, we find that these highly discriminating isomiRs have not been attracting the most research attention in the literature. Given their ability to successfully classify datasets from 32 cancers, isomiRs and our resulting 'Pan-cancer Atlas' of isomiR expression could serve as a suitable framework to explore novel cancer biomarkers.

Indexed as

Cluster AnalysisDatasets as TopicHumansMicroRNAsNeoplasmsRNA IsoformsMicroRNAsRNA Isoforms

Identifiers

PMID28206648
PMCPMC5389567

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.