Evidence map›Paper›PMID 31505091›Full record

ArticleMolecular oncology2019

Identification of microRNAs involved in pathways which characterize the expression subtypes of NSCLC.

Ann Rita Halvorsen, Miriam Ragle Aure, Åsa Kristina Õjlert, Odd Terje Brustugun, Steinar Solberg, Daniel Nebdal, Åslaug Helland

Open access · goldAbstract read
In one paragraph

Article in Molecular oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.7field-weighted citation impact, top 36% 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

10 citing papers in PubMed, 14 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

7 authors at 3 institutions in 1 country.

Ann Rita HalvorsenDepartment of Cancer Genetics, Institute for Cancer Research, OUS Radiumhospitalet, Oslo, Norway.ORCID 0000-0003-1223-7948
Miriam Ragle AureDepartment of Cancer Genetics, Institute for Cancer Research, OUS Radiumhospitalet, Oslo, Norway.
Åsa Kristina ÕjlertDepartment of Cancer Genetics, Institute for Cancer Research, OUS Radiumhospitalet, Oslo, Norway.ORCID 0000-0002-2888-8406
Odd Terje BrustugunDepartment of Cancer Genetics, Institute for Cancer Research, OUS Radiumhospitalet, Oslo, Norway.
Steinar SolbergDepartment of Cardiothoracic Surgery, Oslo University Hospital-Rikshospitalet, Norway.
Daniel NebdalDepartment of Cancer Genetics, Institute for Cancer Research, OUS Radiumhospitalet, Oslo, Norway.
Åslaug HellandDepartment of Cancer Genetics, Institute for Cancer Research, OUS Radiumhospitalet, Oslo, Norway.
Norwegian Cancer Society · NOUniversity of Oslo · NOOslo University Hospital · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dysregulation of microRNAs is a common mechanism in the development of lung cancer, but the relationship between microRNAs and expression subtypes in non-small-cell lung cancer (NSCLC) is poorly explored. Here, we analyzed microRNA expression from 241 NSCLC samples and correlated this with the expression subtypes of adenocarcinomas (AD) and squamous cell carcinomas (SCC) to identify microRNAs specific for each subtype. Gene set variation analysis and the hallmark gene set were utilized to calculate gene set scores specific for each sample, and these were further correlated with the expression of the subtype-specific microRNAs. In ADs, we identified nine aberrantly regulated microRNAs in the terminal respiratory unit (TRU), three in the proximal inflammatory (PI), and nine in the proximal proliferative subtype (PP). In SCCs, 1, 5, 5, and 9 microRNAs were significantly dysregulated in the basal, primitive, classical, and secretory subtypes, respectively. The subtype-specific microRNAs were highly correlated to specific gene sets, and a distinct pattern of biological processes with high immune activity for the AD PI and SCC secretory subtypes, and upregulation of cell cycle-related processes in AD PP, SCC primitive, and SCC classical subtypes were found. Several in silico predicted targets within the gene sets were identified for the subtype-specific microRNAs, underpinning the findings. The results were significantly validated in the LUAD (n = 492) and LUSC (n = 380) TCGA dataset (False discovery rates-corrected P-value < 0.05). Our study provides novel insight into how expression subtypes determined with discrete biological processes may be regulated by subtype-specific microRNAs. These results may have importance for the development of combinatory therapeutic strategies for lung cancer patients.

Indexed as

Carcinoma, Non-Small-Cell LungGene Expression Regulation, NeoplasticLung NeoplasmsMicroRNAsRNA, NeoplasmAgedFemaleGene Expression ProfilingHumansMaleMicroRNAsRNA, Neoplasmadenocarcinomaexpression subtypesmicroRNAnon-small-cell lung cancerpathwaypredicted targetsquamous cell carcinoma

Identifiers

PMID31505091
PMCPMC6887593
OpenAlexW2972856069

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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.