Evidence map›Paper›PMID 25032733›Full record

ArticleBritish journal of cancer2014

Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

M Shipitsin, C Small, S Choudhury, E Giladi, S Friedlander, J Nardone, S Hussain, A D Hurley, C Ernst, Y E Huang and 7 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in British journal of cancer, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed
13.3field-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

74 citing papers in PubMed, 143 citations in OpenAlex.

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14 more citing papers are in PubMed but not listed here.

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

17 authors at 1 institution in 1 country.

M ShipitsinMetamark Genetics Inc., Cambridge, MA 02142, USA.
C SmallMetamark Genetics Inc., Cambridge, MA 02142, USA.
S ChoudhuryMetamark Genetics Inc., Cambridge, MA 02142, USA.
E GiladiMetamark Genetics Inc., Cambridge, MA 02142, USA.
S FriedlanderMetamark Genetics Inc., Cambridge, MA 02142, USA.
J NardoneMetamark Genetics Inc., Cambridge, MA 02142, USA.
S HussainMetamark Genetics Inc., Cambridge, MA 02142, USA.
A D HurleyMetamark Genetics Inc., Cambridge, MA 02142, USA.
C ErnstMetamark Genetics Inc., Cambridge, MA 02142, USA.
Y E HuangMetamark Genetics Inc., Cambridge, MA 02142, USA.
H ChangMetamark Genetics Inc., Cambridge, MA 02142, USA.
T P NifongMetamark Genetics Inc., Cambridge, MA 02142, USA.
D L RimmDepartment of Pathology, Yale University Medical School, New Haven, CT 06520, USA.
J DunyakMetamark Genetics Inc., Cambridge, MA 02142, USA.
M LodaDepartment of Pathology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA.
D M BermanDepartment of Pathology and Molecular Medicine and Queen's Cancer Research Institute, Queen's University, Kingston, ON, Canada K7L 3N6.
P Blume-JensenMetamark Genetics Inc., Cambridge, MA 02142, USA.
Queen's University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKey challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation.

methodsProstatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively.

resultsUsing a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error.

conclusionsOur results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

Indexed as

ActininAgedAlkyl and Aryl TransferasesArea Under CurveBiomarkers, TumorBiopsy, Fine-NeedleCullin ProteinsDNA-Binding ProteinsFollow-Up StudiesHSP70 Heat-Shock ProteinsHumansImage Processing, Computer-AssistedMaleMembrane ProteinsMiddle AgedMitochondrial ProteinsActininACTN1 protein, humanAlkyl and Aryl TransferasesBiomarkers, TumorCUL2 protein, humanCullin ProteinsDERL1 protein, humanDNA-Binding ProteinsHSP70 Heat-Shock ProteinsHSPA9 protein, humanMembrane ProteinsMitochondrial ProteinsPLAG1 protein, humanprenyl diphosphate synthase, subunit 2, humanRibosomal Protein S6RNA-Binding Protein FUSSmad2 ProteinSmad4 ProteinSMAD4 protein, humanVDAC1 protein, humanVoltage-Dependent Anion Channel 1Y-Box-Binding Protein 1

Identifiers

PMID25032733
PMCPMC4453845
OpenAlexW2136365117

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.