Evidence map›Paper›PMID 25115192›Full record

ArticleBMC medical genomics2014

Gene signatures ESC, MYC and ERG-fusion are early markers of a potentially dangerous subtype of prostate cancer.

Morten Beck Rye, Helena Bertilsson, Finn Drabløs, Anders Angelsen, Tone F Bathen, May-Britt Tessem

Abstract read
In one paragraph

Article in BMC medical genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Epigenetic Regulation in Prostate Cancer Progression.Current molecular biology reports · 2018
    Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Morten Beck RyeDepartment of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), P,O, Box 8905, N-7491 Trondheim, Norway. morten.rye@ntnu.no.
Helena Bertilsson
Finn Drabløs
Anders Angelsen
Tone F Bathen
May-Britt Tessem

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGood prognostic tools for predicting disease progression in early stage prostate cancer (PCa) are still missing. Detection of molecular subtypes, for instance by using microarray gene technology, can give new prognostic information which can assist personalized treatment planning. The detection of new subtypes with validation across additional and larger patient cohorts is important for bringing a potential prognostic tool into the clinic.

methodsWe used fresh frozen prostatectomy tissue of high molecular quality to further explore four molecular subtype signatures of PCa based on Gene Set Enrichment Analysis (GSEA) of 15 selected gene sets published in a previous study. For this analysis we used a statistical test of dependent correlations to compare reference signatures to signatures in new normal and PCa samples, and also explore signatures within and between sample subgroups in the new samples.

resultsAn important finding was the consistent signatures observed for samples from the same patient independent of Gleason score. This proves that the signatures are robust and can surpass a normally high tumor heterogeneity within each patient. Our data did not distinguish between four different subtypes of PCa as previously published, but rather highlighted two groups of samples which could be related to good and poor prognosis based on survival data from the previous study.The poor prognosis group highlighted a set of samples characterized by enrichment of ESC, ERG-fusion and MYC + rich signatures in patients diagnosed with low Gleason score,. The other group consisted of PCa samples showing good prognosis as well as normal samples. Accounting for sample composition (the amount of benign structures such as stroma and epithelial cells in addition to the cancer component) was important to improve subtype assignments and should also be considered in future studies.

conclusionOur study validates a previous molecular subtyping of PCa in a new patient cohort, and identifies a subgroup of PCa samples highly interesting for detecting high risk PCa at an early stage. The importance of taking sample tissue composition into account when assigning subtype is emphasized.

Indexed as

Gene FusionBiomarkers, TumorCryopreservationEmbryonic Stem CellsHumansMaleNeoplasm GradingPrognosisProstatectomyProstatic NeoplasmsProto-Oncogene Proteins c-mycTrans-ActivatorsTranscriptional Regulator ERGBiomarkers, TumorERG protein, humanMYC protein, humanProto-Oncogene Proteins c-mycTrans-ActivatorsTranscriptional Regulator ERG

Identifiers

PMID25115192
PMCPMC4147934

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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.