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Status |
Public on Jun 30, 2019 |
Title |
The Proteogenomic Landscape of Curable Prostate Cancer [microarray] |
Organism |
Homo sapiens |
Experiment type |
Expression profiling by array
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Summary |
DNA sequencing studies have identified specific recurrent somatic mutations that drive the aggressiveness of localized prostate cancers. Surprisingly, though, it is poorly understood how the prostate cancer proteome is shaped by genomic, epigenomic and transcriptomic dysregulation. To fill this gap, we profiled the whole genomes, methylomes, epigenomes, transcriptomes and proteomes of 55 localized, intermediate-risk, prostate cancers. This multi-modal dataset revealed that the genomic subtypes of prostate cancer converge on four proteomic subtypes, which are associated with distinct clinical trajectories. ETS fusion genes, the most common mutation in prostate tumours, perturb the proteome and transcriptome in divergent ways – with different genes and pathways affected at each level. Indeed, mRNA abundance changes explain only ~10% of variability in protein levels. Perhaps as a direct result, prognostic biomarkers that combine genomic or epigenomic features with proteomic ones significantly outperform those comprised of either molecular feature alone. These data suggest that the proteome of prostate cancer is shaped by a complex interplay of genomic, epigenomic, transcriptomic and post-transcriptional dysregulation.
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Overall design |
In total we have 214 samples (213 unique samples) accross 5 different batches. Batch 1, 3, 4 and 5 are based on the HuGene2.0 platfrom whereas batch 2 is based on HTA2.0 platform
Please note that CPCG0398_rep is a technical replicate of CPCG0398, therefore the CPCG0398 column in the Matrix_processed_data.tsv represents the average of the original CPCG0398 and the CPCG0398_rep.
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Contributor(s) |
Shiah Y, Boutros PC |
Citation(s) |
30889379, 34716314 |
Submission date |
Nov 23, 2017 |
Last update date |
Nov 30, 2021 |
Contact name |
Yu-Jia Shiah |
E-mail(s) |
sylvia.shiah@oicr.on.ca
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Organization name |
Ontario Institute for Cancer Research
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Department |
Informatics and Bio-computing
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Street address |
MaRS Centre 661 University Avenue Suite 510
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City |
Toronto |
State/province |
Ontario |
ZIP/Postal code |
M5G 0A3 |
Country |
Canada |
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Platforms (2) |
GPL16686 |
[HuGene-2_0-st] Affymetrix Human Gene 2.0 ST Array [transcript (gene) version] |
GPL17586 |
[HTA-2_0] Affymetrix Human Transcriptome Array 2.0 [transcript (gene) version] |
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Samples (213)
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Relations |
BioProject |
PRJNA419650 |
Supplementary file |
Size |
Download |
File type/resource |
GSE107299_Matrix_processed_data.tsv.gz |
30.9 Mb |
(ftp)(http) |
TSV |
GSE107299_RAW.tar |
2.9 Gb |
(http)(custom) |
TAR (of CEL) |
Processed data are available on Series record |
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