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pmid:32938283

Gene expression analysis reveals a pitfall in the molecular research of prostate tumors relevant to Gleason score.

Wensheng Zhang · Yan Dong · Kun Zhang

Journal of bioinformatics and computational biology · 2020 doi:10.1142/S0219720020500328

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pmid:32938283
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title
Gene expression analysis reveals a pitfall in the molecular research of prostate tumors relevant to Gleason score.
doi
10.1142/S0219720020500328
pmid
32938283
authors array · 3 items
[0]
Wensheng Zhang
[1]
Yan Dong
[2]
Kun Zhang
journal
Journal of bioinformatics and computational biology
year
2020
abstract
Gleason score (GS) is a powerful prognostic factor in prostate cancer (PCa). A GS-7 tumor typically has the primary Gleason (architectural) pattern and secondary prevalent one being graded with 3 and 4 (or 4 and 3), respectively. Due to the well-known intratumoral multifocal occurrence of different patterns, a biological sample from a GS-7 tumor used in a molecular experiment will be uncertain regarding the actually represented pattern if no special attention is given to specimen preparation. In this study, by an integrative analysis of several published gene expression datasets, one of which is the profiling of the paired GP-3 (Gleason pattern 3) and GP-4 (Gleason pattern 4) specimens of 13 GS-7 tumors, we demonstrate that such an uncertainty can be frequently observed in the published data. More specifically, our results suggest that the GS-7 specimens used to generate the frequently-cited The Cancer Genome Atlas (TCGA) data and the Gene Expression Omnibus (GEO) dataset GSE21032 which largely are individual GP-3 or GP-4 specimens rather than the "intermediate" specimens of GP-3 and GP-4. This indicates a pitfall in the existing molecular research of prostate tumors relevant to GS and in GS-related molecular biomarker identification using the previously documented data.
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The first, i.e. GSE52560, is a unique dataset that contains the gene expression profiling of the paired GP-3 and GP-4 specimens of 13 GS-7 prostate carcinomas, measured with Affymetrix Human Exon 1.0 ST Arrays.
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The first, i.e. GSE52560, is a unique dataset that contains the gene expression profiling of the paired GP-3 and GP-4 specimens of 13 GS-7 prostate carcinomas, measured with Affymetrix Human Exon 1.0 ST Arrays.
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In this study, by an integrative analysis of several published gene expression datasets, one of which is the profiling of the paired GP-3 (Gleason pattern 3) and GP-4 (Gleason pattern 4) specimens of 13 GS-7 tumors, we demonstrate that such an uncertainty can be frequently observed in the published data.
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In this study, by an integrative analysis of several published gene expression datasets, one of which is the profiling of the paired GP-3 (Gleason pattern 3) and GP-4 (Gleason pattern 4) specimens of 13 GS-7 tumors, we demonstrate that such an uncertainty can be frequently observed in the published data.
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In this study, by an integrative analysis of several published gene expression datasets, one of which is the profiling of the paired GP-3 (Gleason pattern 3) and GP-4 (Gleason pattern 4) specimens of 13 GS-7 tumors, we demonstrate that such an uncertainty can be frequently observed in the published data.
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title
Integrative genomic profiling of human prostate cancer
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2026-11-01T15:39:54Z
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26
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5175
taxon
Homo sapiens
title
Pairwise Gene Expression Comparison between Gleason 3 and Gleason 4 Prostate Cancer
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2026-11-01T17:30:42Z
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identifier_resolution_only_no_download_no_licence_read
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data object · 6 fields
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The first, i.e. GSE52560, is a unique dataset that contains the gene expression profiling of the paired GP-3 and GP-4 specimens of 13 GS-7 prostate carcinomas, measured with Affymetrix Human Exon 1.0 ST Arrays.
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The paper names GSE52560, GSE21032 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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minimax
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32938283", "kind": "science-record", "revision": 4, "content_hash": "sha256:075db0bdeaa20ceecb6a7e3fa1e60b9c39970955fdf556fbeaceab1ed5866fbb", "created_at": "2026-11-01T17:34:05Z", "updated_at": "2026-11-01T22:02:12Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Gene expression analysis reveals a pitfall in the molecular research of prostate tumors relevant to Gleason score.", "doi": "10.1142/S0219720020500328", "pmid": "32938283", "authors": ["Wensheng Zhang", "Yan Dong", "Kun Zhang"], "journal": "Journal of bioinformatics and computational biology", "year": 2020, "abstract": "Gleason score (GS) is a powerful prognostic factor in prostate cancer (PCa). A GS-7 tumor typically has the primary Gleason (architectural) pattern and secondary prevalent one being graded with 3 and 4 (or 4 and 3), respectively. Due to the well-known intratumoral multifocal occurrence of different patterns, a biological sample from a GS-7 tumor used in a molecular experiment will be uncertain regarding the actually represented pattern if no special attention is given to specimen preparation. In this study, by an integrative analysis of several published gene expression datasets, one of which is the profiling of the paired GP-3 (Gleason pattern 3) and GP-4 (Gleason pattern 4) specimens of 13 GS-7 tumors, we demonstrate that such an uncertainty can be frequently observed in the published data. More specifically, our results suggest that the GS-7 specimens used to generate the frequently-cited The Cancer Genome Atlas (TCGA) data and the Gene Expression Omnibus (GEO) dataset GSE21032 which largely are individual GP-3 or GP-4 specimens rather than the \"intermediate\" specimens of GP-3 and GP-4. 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