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| Status |
Public on Dec 01, 2013 |
| Title |
Genomic Signatures of Metastasis in Prostate Cancer |
| Organism |
Homo sapiens |
| Experiment type |
Genome variation profiling by SNP array
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| Summary |
Background:
Metastases result in 90% of all cancer deaths. Prostate cancer primary tumors evolve to become metastatic through selective alterations, such as amplification and deletion of genomic DNA.
Methods:
Genomic DNA copy number alterations were used to develop a gene signature that measured the metastatic potential of a prostate cancer primary tumor. We studied the genomic landscape of these alterations in 294 primary tumors and 49 metastases from 5 independent cohorts. Receiver-operating characteristic cross-validation and Kaplan-Meier survival analysis were performed to assess the accuracy of our predictive model. The signature was measured in a panel of 337 cancer cell lines from 29 different tissue origins.
Results:
We identified 399 copy number alterations around genes that were over-represented in metastases and predictive of whether a primary tumor will metastasize. Cross-validation analysis resulted in a predictive accuracy of 80.5% and log rank analysis of the metastatic potential score was significantly related to the endpoint of metastasis-free survival (p=0.014). The metastatic signature was observed in cell lines originating from lung, breast, colon, thyroid, rectum, pancreas and melanoma. The signature was comprised in part of genes of known or putative metastatic role — 8 solute carrier genes, 6 Cadherin family genes and 5 potassium channel genes — that function in metabolism, cell-to-cell adhesion and escape from anoikis/apoptosis.
Conclusions:
Somatic Copy number alterations are an independent predictor of metastatic potential. The data indicate a prognostic utility for using primary tumor genomics to assist in clinical decision making and developing therapeutics for prostate and likely other cancers.
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| Overall design |
genomic DNA from 29 prostate cancer tumors with matched normals run on Affymetrix 6.0 SNP arrays.
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| Contributor(s) |
Pearlman A, Campbell C, Brooks E, Genshaft A, Shajahan S, Ittmann M, Bova GS, Melamed J, Holcomb I, Schneider R, Shao Y, Ostrer H |
| Citation(s) |
25419216 |
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| Submission date |
Feb 07, 2011 |
| Last update date |
Jan 28, 2020 |
| Contact name |
Alex Pearlman |
| E-mail(s) |
alexander.pearlman@einstein.yu.edu, harry.ostrer@einstein.yu.edu
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| Organization name |
Albert Einstein College of Medicine
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| Department |
Pediatrics and Genetics
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| Street address |
1300 Morris Park Avenue
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| City |
Bronx |
| State/province |
NY |
| ZIP/Postal code |
10461 |
| Country |
USA |
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| Platforms (1) |
| GPL6801 |
[GenomeWideSNP_6] Affymetrix Genome-Wide Human SNP 6.0 Array |
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| Samples (58)
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| Relations |
| BioProject |
PRJNA137447 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE27105_RAW.tar |
2.5 Gb |
(http)(custom) |
TAR (of CEL, CHP) |
| Processed data included within Sample table |
| Processed data provided as supplementary file |
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