Evidence map›Paper›PMID 22123976›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2011

Molecular classification of prostate cancer using curated expression signatures.

Elke K Markert, Hideaki Mizuno, Alexei Vazquez, Arnold J Levine

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 110 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
110citing papers in PubMed, 1 pooled it
19.5field-weighted citation impact, top 1% 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

110 citing papers in PubMed, 1 synthesis or guideline pooled it, 183 citations in OpenAlex.

  1. Pooled it
  2. Copy number alteration burden predicts prostate cancer relapse.Proceedings of the National Academy of Sciences of the United States of America · 2014
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50 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 4 institutions in 2 countries.

Elke K MarkertSimons Center for Systems Biology, Institute for Advanced Study, Princeton, NJ 08540, USA.
Hideaki Mizuno
Alexei Vazquez
Arnold J Levine
Center for Systems Biology · USInstitute for Advanced Study · USKyushu Institute of Technology · JPRutgers Cancer Institute of New Jersey

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High Gleason score is currently the best prognostic indicator for poor prognosis in prostate cancer. However, a significant number of patients with low Gleason scores develop aggressive disease as well. In an effort to understand molecular signatures associated with poor outcome in prostate cancer, we analyzed a microarray dataset characterizing 281 prostate cancers from a Swedish watchful-waiting cohort. Patients were classified on the basis of their mRNA microarray signature profiles indicating embryonic stem cell expression patterns (stemness), inactivation of the tumor suppressors p53 and PTEN, activation of several oncogenic pathways, and the TMPRSS2-ERG fusion. Unsupervised clustering identified a subset of tumors manifesting stem-like signatures together with p53 and PTEN inactivation, which had very poor survival outcome, a second group with intermediate survival outcome, characterized by the TMPRSS2-ERG fusion, and three groups with benign outcome. The stratification was validated on a second independent dataset of 150 tumor and metastatic samples from a clinical cohort at Memorial Sloan-Kettering Cancer Center. This classification is independent of Gleason score and therefore provides useful unique molecular profiles for prostate cancer prognosis, helping to predict poor outcome in patients with low or average Gleason scores.

Indexed as

RNA, MessengerBayes TheoremEmbryonic Stem CellsGene Expression ProfilingHumansMaleMicroarray AnalysisNeoplasm GradingOncogene Proteins, FusionPrognosisProstatic NeoplasmsPTEN PhosphohydrolaseSwedenTumor Suppressor Protein p53Watchful WaitingOncogene Proteins, FusionPTEN PhosphohydrolasePTEN protein, humanRNA, MessengerTMPRSS2-ERG fusion protein, humanTumor Suppressor Protein p53

Identifiers

PMID22123976
PMCPMC3248553
OpenAlexW1996386813

What OpenQuestion holds

Textmetadata
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.