Evidence map›Paper›PMID 36511578›Full record

ArticleRNA biology2023

Dynamic and static circulating cancer microRNA biomarkers - a validation study.

Masood Abu-Halima, Andreas Keller, Lea Simone Becker, Ulrike Fischer, Annika Engel, Nicole Ludwig, Fabian Kern, Trine B Rounge, Hilde Langseth, Eckart Meese and 1 more

Open access · goldAbstract read
In one paragraph

Article in RNA biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-weighted citation impact, top 38% 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

7 citing papers in PubMed, 7 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

11 authors at 4 institutions in 3 countries.

Masood Abu-HalimaInstitute of Human Genetics, Saarland University, Homburg, Germany.
Andreas KellerThese authors contributed equally to the study.
Lea Simone BeckerInstitute of Human Genetics, Saarland University, Homburg, Germany.
Ulrike FischerInstitute of Human Genetics, Saarland University, Homburg, Germany.
Annika EngelHelmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Center for Infection Research, Saarland University Campus, Saarbrücken, Germany.
Nicole LudwigInstitute of Human Genetics, Saarland University, Homburg, Germany.
Fabian KernHelmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Center for Infection Research, Saarland University Campus, Saarbrücken, Germany.
Trine B RoungeDepartment of Research, Cancer Registry of Norway, Norway.
Hilde LangsethDepartment of Research, Cancer Registry of Norway, Norway.
Eckart MeeseInstitute of Human Genetics, Saarland University, Homburg, Germany.
Verena KellerHelmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Center for Infection Research, Saarland University Campus, Saarbrücken, Germany.
Saarland University · DEHelmholtz Institute for Pharmaceutical Research Saarland · DEImperial College London · GBUniversity of Oslo · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For cancers and other pathologies, early diagnosis remains the most promising path to survival. Profiling of longitudinal cohorts facilitates insights into trajectories of biomarkers. We measured microRNA expression in 240 serum samples from patients with colon, lung, and breast cancer and from cancer-free controls. Each patient provided at least two serum samples, one prior to diagnosis and one following diagnosis. The median time interval between the samples was 11.6 years. Using computational models, we evaluated the circulating profiles of 21 microRNAs. The analysis yielded two sets of biomarkers, static ones that show an absolute difference between certain cancer types and controls and dynamic ones where the level over time provided higher diagnostic information content. In the first group, miR-99a-5p stands out for all three cancer types. In the second group, miR-155-5p allows to predict lung cancers and colon cancers. Classification in samples from cancer and non-cancer patients using gradient boosted trees reached an average accuracy of 79.9%. The results suggest that individual change over time or an absolute value at one time point may predict a disease with high specificity and sensitivity.

Indexed as

Circulating MicroRNAMicroRNAsNeoplasmsBiomarkersBiomarkers, TumorEarly Detection of CancerGene Expression ProfilingHumansBiomarkersBiomarkers, TumorCirculating MicroRNAMicroRNAsMIRN155 microRNA, humanMIRN99 microRNA, humanbiomarkerbreast cancercancercolon cancermicroRNAmiR-155miR-99a

Identifiers

PMID36511578
PMCPMC9754110
OpenAlexW4311350569

What OpenQuestion holds

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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.