Evidence map›Paper›PMID 29423032›Full record

ArticleOncotarget2018

Small non-coding RNA profiling in human biofluids and surrogate tissues from healthy individuals: description of the diverse and most represented species.

Giulio Ferrero, Francesca Cordero, Sonia Tarallo, Maddalena Arigoni, Federica Riccardo, Gaetano Gallo, Guglielmo Ronco, Marco Allasia, Neha Kulkarni, Giuseppe Matullo and 4 more

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 10% of its field
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

39 citing papers in PubMed, 1 synthesis or guideline pooled it, 68 citations in OpenAlex.

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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

14 authors at 5 institutions in 3 countries.

Giulio FerreroDepartment of Computer Science, University of Turin, Turin, Italy.
Francesca CorderoDepartment of Computer Science, University of Turin, Turin, Italy.
Sonia TaralloItalian Institute for Genomic Medicine, IIGM (formerly Human Genetics Foundation, HuGeF), Turin, Italy.
Maddalena ArigoniMolecular Biotechnology Center, Department of Biotechnology and Health Sciences, University of Turin, Turin, Italy.
Federica RiccardoMolecular Biotechnology Center, Department of Biotechnology and Health Sciences, University of Turin, Turin, Italy.
Gaetano GalloDepartment of Medical and Surgical Sciences, University of Catanzaro, Catanzaro, Italy.
Guglielmo RoncoCenter for Cancer Epidemiology and Prevention, AO City of Health and Science, Turin, Italy.
Marco AllasiaDepartment of Surgical Sciences, University of Turin and Città della Salute e della Scienza, Turin, Italy.
Neha KulkarniMolecular Biotechnology Center, Department of Biotechnology and Health Sciences, University of Turin, Turin, Italy.
Giuseppe MatulloItalian Institute for Genomic Medicine, IIGM (formerly Human Genetics Foundation, HuGeF), Turin, Italy.
Paolo VineisItalian Institute for Genomic Medicine, IIGM (formerly Human Genetics Foundation, HuGeF), Turin, Italy.
Raffaele A CalogeroMolecular Biotechnology Center, Department of Biotechnology and Health Sciences, University of Turin, Turin, Italy.
Barbara PardiniItalian Institute for Genomic Medicine, IIGM (formerly Human Genetics Foundation, HuGeF), Turin, Italy.
Alessio NaccaratiItalian Institute for Genomic Medicine, IIGM (formerly Human Genetics Foundation, HuGeF), Turin, Italy.
University of Turin · ITItalian institute for Genomic Medicine · ITImperial College London · GBMagna Graecia University · ITPiedmont Reference Center for Epidemiology and Cancer Prevention · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The role of non-coding RNAs in different biological processes and diseases is continuously expanding. Next-generation sequencing together with the parallel improvement of bioinformatics analyses allows the accurate detection and quantification of an increasing number of RNA species. With the aim of exploring new potential biomarkers for disease classification, a clear overview of the expression levels of common/unique small RNA species among different biospecimens is necessary. However, except for miRNAs in plasma, there are no substantial indications about the pattern of expression of various small RNAs in multiple specimens among healthy humans. By analysing small RNA-sequencing data from 243 samples, we have identified and compared the most abundantly and uniformly expressed miRNAs and non-miRNA species of comparable size with the library preparation in four different specimens (plasma exosomes, stool, urine, and cervical scrapes). Eleven miRNAs were commonly detected among all different specimens while 231 miRNAs were globally unique across them. Classification analysis using these miRNAs provided an accuracy of 99.6% to recognize the sample types. piRNAs and tRNAs were the most represented non-miRNA small RNAs detected in all specimen types that were analysed, particularly in urine samples. With the present data, the most uniformly expressed small RNAs in each sample type were also identified. A signature of small RNAs for each specimen could represent a reference gene set in validation studies by RT-qPCR. Overall, the data reported hereby provide an insight of the constitution of the human miRNome and of other small non-coding RNAs in various specimens of healthy individuals.

Indexed as

microRNAsnext-generation sequencingnon-invasive biomarkerssmall non-coding RNA profilingsurrogate tissues

Identifiers

PMID29423032
PMCPMC5790449
OpenAlexW2774085034

What OpenQuestion holds

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LicenceCC BY
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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.