Evidence map›Paper›PMID 30412601›Full record

ArticlePloS one2018

Comparative mRNA and miRNA transcriptome analysis of a mouse model of IGFIR-driven lung cancer.

Robert A Jones, Sarah E Franks, Roger A Moorehead

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

3 authors.

Robert A JonesDepartment of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.ORCID 0000-0001-7665-9301
Sarah E FranksDepartment of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.
Roger A MooreheadDepartment of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mouse models of cancer play an important role in elucidating the molecular mechanisms that contribute to tumorigenesis. The extent to which these models resemble one another and their human counterparts at the molecular level is critical in understanding tumorigenesis. In this study, we carried out a comparative gene expression analysis to generate a detailed molecular portrait of a transgenic mouse model of IGFIR-driven lung cancer. IGFIR-driven tumors displayed a strong resemblance with established mouse models of lung adenocarcinoma, particularly EGFR-driven models highlighted by elevated levels of the EGFR ligands Ereg and Areg. Cross-species analysis revealed a shared increase in human lung adenocarcinoma markers including Nkx2.1 and Napsa as well as alterations in a subset of genes with oncogenic and tumor suppressive properties such as Aurka, Ret, Klf4 and Lats2. Integrated miRNA and mRNA analysis in IGFIR-driven tumors identified interaction pairs with roles in ErbB signaling while cross-species analysis revealed coordinated expression of a subset of conserved miRNAs and their targets including miR-21-5p (Reck, Timp3 and Tgfbr3). Overall, these findings support the use of SPC-IGFIR mice as a model of human lung adenocarcinoma and provide a comprehensive knowledge base to dissect the molecular pathogenesis of tumor initiation and progression.

Indexed as

AnimalsComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKruppel-Like Factor 4Lung NeoplasmsMiceMice, TransgenicMicroRNAsMolecular Sequence AnnotationReceptors, SomatomedinRNA, MessengerSpecies SpecificityTranscriptomeKLF4 protein, humanKlf4 protein, mouseKruppel-Like Factor 4MicroRNAsReceptors, SomatomedinRNA, Messenger

Identifiers

PMID30412601
PMCPMC6226179

What OpenQuestion holds

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LicenceCC BY
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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.