Evidence map›Paper›PMID 23970479›Full record

ReviewCancer research2013

mRNA splicing variants: exploiting modularity to outwit cancer therapy.

Scott M Dehm

Abstract readReview
In one paragraph

Review in Cancer research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.7field-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

23 citing papers in PubMed, 42 citations in OpenAlex.

  1. Review
  2. Article
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  11. Article
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  13. Review
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  15. Article
  16. Review
  17. Article
  18. Alternative RNA structure-coupled gene regulations in tumorigenesis.International journal of molecular sciences · 2014
    Review
  19. Article
  20. 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

1 author at 1 institution in 1 country.

Scott M DehmDepartment of Laboratory Medicine and Pathology, Masonic Cancer Center, University of Minnesota Twin Cities, Minneapolis, MN 55455, USA. dehm@umn.edu
University of Minnesota · US

Funding

AR Gene Rearrangements and AR Signaling in Prostate CancerR01CA174777 · NCI · UNIVERSITY OF MINNESOTA · PI Scott M. Dehm · 2013 to 2026
$4.9M
NCI NIH HHS R01 CA174777NCI NIH HHS R01CA174777
6 · The paper itself

Abstract

Systemic cancer therapy has traditionally exploited vulnerabilities in cancer cells, a strategy which has become more precise with the identification and targeting of driver oncogenes. However, persistent tumor growth due to primary (de novo) or secondary (acquired) resistance limits therapeutic efficacy for many patients. Alternative splicing is important for increasing the diversity of the cellular proteome, and is a process frequently deregulated during cancer development and progression. In cancer cells, diverse splicing alterations have been identified that eliminate protein domains or enzymatic activities required for efficacy of cancer therapies, promote gain of novel signaling functions that circumvent cancer therapies, and uncouple signaling pathways from upstream regulatory points that are blocked by cancer therapies. The mechanisms underlying these splicing changes range from stable alterations in gene sequence/structure to deregulation of splicing regulatory factors. In this review, the role of splice variants in cancer therapy resistance will be discussed, with examples of how mechanistic understanding of these processes has led to the development of novel strategies for therapy resensitization.

Indexed as

AnimalsAntineoplastic AgentsDrug Resistance, NeoplasmGenetic VariationHumansNeoplasm ProteinsNeoplasmsRNA SplicingAntineoplastic AgentsNeoplasm Proteins

Identifiers

PMID23970479
PMCPMC3766449
OpenAlexW2114048083

What OpenQuestion holds

Textmetadata
LicenceTDM
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.