Evidence map›Paper›PMID 29286307›Full record

ReviewGenes2017

Signaling Pathways Driving Aberrant Splicing in Cancer Cells.

Vânia Gonçalves, Joana F S Pereira, Peter Jordan

Open access · goldAbstract readReview
In one paragraph

Review in Genes, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
4.0field-weighted citation impact, top 5% 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

44 citing papers in PubMed, 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

3 authors at 2 institutions in 1 country.

Vânia GonçalvesDepartment of Human Genetics, Instituto Nacional de Saúde Doutor Ricardo Jorge, Avenida Padre Cruz, 1649-016 Lisboa, Portugal. vania.goncalves@insa.min-saude.pt.
Joana F S PereiraDepartment of Human Genetics, Instituto Nacional de Saúde Doutor Ricardo Jorge, Avenida Padre Cruz, 1649-016 Lisboa, Portugal. joana.pereira@insa.min-saude.pt.
Peter JordanDepartment of Human Genetics, Instituto Nacional de Saúde Doutor Ricardo Jorge, Avenida Padre Cruz, 1649-016 Lisboa, Portugal. peter.jordan@insa.min-saude.pt.
National Institute of Health Dr. Ricardo Jorge · PTUniversity of Lisbon · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aberrant profiles of pre-mRNA splicing are frequently observed in cancer. At the molecular level, an altered profile results from a complex interplay between chromatin modifications, the transcriptional elongation rate of RNA polymerase, and effective binding of the spliceosome to the generated transcripts. Key players in this interplay are regulatory splicing factors (SFs) that bind to gene-specific splice-regulatory sequence elements. Although mutations in genes of some SFs were described, a major driver of aberrant splicing profiles is oncogenic signal transduction pathways. Signaling can affect either the transcriptional expression levels of SFs or the post-translational modification of SF proteins, and both modulate the ratio of nuclear versus cytoplasmic SFs in a given cell. Here, we will review currently known mechanisms by which cancer cell signaling, including the mitogen-activated protein kinases (MAPK), phosphatidylinositol 3 (PI3)-kinase pathway (PI3K) and wingless (Wnt) pathways but also signals from the tumor microenvironment, modulate the activity or subcellular localization of the Ser/Arg rich (SR) proteins and heterogeneous nuclear ribonucleoproteins (hnRNPs) families of SFs.

Indexed as

alternative splicingcancer cellgenetic programsignaling pathwaytumorigenesistumor microenvironment

Identifiers

PMID29286307
PMCPMC5793162
OpenAlexW2780276291

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.