Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Castration-Resistant Prostate Cancer (CRPC)

ABSTRACT: Gene expression data from Agilent-014850 4x44K human expression array for CRPC Prostate Cancer study with Xenograph data. RNA was isolated using the mirVana total RNA protocol (part #AM1560, Ambion, Austin, TX). RNA integrity was verified using a 2100 Bioanalyzer (part #G2938A) with nano chips (parts #5067-15101 and #G4411B; Agilent Technologies, Alto, CA). RNA concentrations were determined using a Nanodrop spectrophotometer (Thermo Scientific, Wilmington, DE). Tumor messenger RNA expression was assessed using a human whole-genome oligo TMA kit from Agilent (prod #G4112F) according to the manufacturer’s protocol and as described previously. In the Characteristics field, we have the notation like "Pt Dxed in 2001; hormone Tx; chemo Tx 2002; HRPC by 2002". That means the patient was admitted in 2001, did hormone and chemo treatment in 2002, and HRPC 2002. They are standard prostate cancer treatments.

ORGANISM(S): Homo sapiens

SUBMITTER: Heng Huang

PROVIDER: E-GEOD-33277 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 that experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Results: Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67 - 0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. Conclusion: A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer. 545 formalin-fixed paraffin-embedded (FFPE) tissue samples from primary prostate cancer obtained from Radical Prostatectomy.

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Castration-Resistant Prostate Cancer (CRPC)

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