Evidence map›Paper›PMID 24445778›Full record

ArticleLaboratory investigation; a journal of technical methods and pathology2014

Robust global microRNA expression profiling using next-generation sequencing technologies.

Shirley Tam, Richard de Borja, Ming-Sound Tsao, John D McPherson

Abstract read
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In one paragraph

Article in Laboratory investigation; a journal of technical methods and pathology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing 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

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

  1. A comprehensive investigation of identifying miRNA biomarkers and their potential role in age-related cataract by meta-analysis and bioinformatics analysis.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2025
    Pooled it
  2. Trial
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  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Challenges and opportunities in processing NanoString nCounter data.Computational and structural biotechnology journal · 2024
    Review
  11. miRNAs in HCC, pathogenesis, and targets.Hepatology (Baltimore, Md.) · 2024
    Article
  12. Review
  13. Article
  14. Article
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  16. Article
  17. Review
  18. Unique miRomics Expression Profiles inInternational journal of molecular sciences · 2023
    Article
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  20. Article

20 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

4 authors.

Shirley Tam1] Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada [2] Princess Margaret Cancer Centre, University Health Networks, Toronto, ON, Canada [3] Genome Technologies, Ontario Institute for Cancer Research, Toronto, ON, Canada.
Richard de BorjaInformatics and Bio-Computing, Ontario Institute for Cancer Research, Toronto, ON, Canada.
Ming-Sound Tsao1] Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada [2] Princess Margaret Cancer Centre, University Health Networks, Toronto, ON, Canada [3] Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.
John D McPherson1] Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada [2] Genome Technologies, Ontario Institute for Cancer Research, Toronto, ON, Canada [3] Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

miRNAs are a class of regulatory molecules involved in a wide range of cellular functions, including growth, development and apoptosis. Given their widespread roles in biological processes, understanding their patterns of expression in normal and diseased states will provide insights into the consequences of aberrant expression. As such, global miRNA expression profiling of human malignancies is gaining popularity in both basic and clinically driven research. However, to date, the majority of such analyses have used microarrays and quantitative real-time PCR. With the introduction of digital count technologies, such as next-generation sequencing (NGS) and the NanoString nCounter System, we have at our disposal many more options. To make effective use of these different platforms, the strengths and pitfalls of several miRNA profiling technologies were assessed, including a microarray platform, NGS technologies and the NanoString nCounter System. Overall, NGS had the greatest detection sensitivity, largest dynamic range of detection and highest accuracy in differential expression analysis when compared with gold-standard quantitative real-time PCR. Its technical reproducibility was high, with intrasample correlations of at least 0.95 in all cases. Furthermore, miRNA analysis of formalin-fixed, paraffin-embedded (FFPE) tissue was also evaluated. Expression profiles between paired frozen and FFPE samples were similar, with Spearman's ρ>0.93. These results show the superior sensitivity, accuracy and robustness of NGS for the comprehensive profiling of miRNAs in both frozen and FFPE tissues.

Indexed as

AnimalsCarcinoma, Non-Small-Cell LungCell Line, TumorGene Expression ProfilingHeterograftsHigh-Throughput Nucleotide SequencingHistological TechniquesHumansLung NeoplasmsMiceMice, Inbred NODMice, SCIDMicroRNAsReal-Time Polymerase Chain ReactionRNA, NeoplasmSequence Analysis, RNAMicroRNAsRNA, Neoplasm

Identifiers

PMID24445778

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.