| 1. |
- Mucci, Lorelei A., et al.
(författare)
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Nine-gene molecular signature is not associated with prostate cancer death in a watchful waiting cohort
- 2008
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - Baltimore : Waverly Press. - 1055-9965 .- 1538-7755. ; 17:1, s. 249-251
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Tidskriftsartikel (refereegranskat)abstract
- Tumor molecular markers hold promise to distinguish potentially lethal from indolent prostate cancer and to guide treatment choices. A previous study identified a nine-gene molecular signature in tumors associated with prostate-specific antigen relapse after prostatectomy. We examined this molecular model in relation to prostate cancer death among 172 men with initially localized disease. We quantified protein expression of the nine genes in tumors to classify progression risk. Accounting for clinical prognostic factors, the nine-gene model did not provide discrimination to predict lethal and indolent prostate cancer.
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| 2. |
- Mucci, Lorelei A., et al.
(författare)
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Testing a multigene signature of prostate cancer death in the Swedish Watchful Waiting Cohort
- 2008
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - Philadelphia : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 17:7, s. 1682-1688
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Tidskriftsartikel (refereegranskat)abstract
- Although prostate cancer is a leading cause of cancer death, most men die with and not from their disease, underscoring the urgency to distinguish potentially lethal from indolent prostate cancer. We tested the prognostic value of a previously identified multigene signature of prostate cancer progression to predict cancer-specific death. The Örebro Watchful Waiting Cohort included 172 men with localized prostate cancer of whom 40 died of prostate cancer. We quantified protein expression of the markers in tumor tissue by immunohistochemistry and stratified the cohort by quintiles according to risk classification. We accounted for clinical variables (age, Gleason, nuclear grade, and tumor volume) using Cox regression and calculated receiver operator curves to compare discriminatory ability. The hazard ratio of prostate cancer death increased with increasing risk classification by the multigene model, with a 16-fold greater risk comparing highest-risk versus lowest-risk strata, and predicted outcome independent of clinical factors (P = 0.002). The best discrimination came from combining information from the multigene markers and clinical data, which perfectly classified the lowest-risk stratum where no one developed lethal disease; using the two lowest-risk groups as reference, the hazard ratio (95% confidence interval) was 11.3 (4.0-32.8) for the highest-risk group and difference in mortality at 15 years was 60% (50-70%). The combined model provided greater discriminatory ability (area under the curve = 0.78) than the clinical model alone (area under the curve = 0.71; P = 0.04). Molecular tumor markers can add to clinical variables to help distinguish lethal and indolent prostate cancer and hold promise to guide treatment decisions.
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| 3. |
- Sboner, Andrea, et al.
(författare)
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Molecular sampling of prostate cancer: a dilemma for predicting disease progression
- 2010
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Ingår i: BMC Medical Genomics. - London, United Kingdom : BioMed Central. - 1755-8794. ; 3:8
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Tidskriftsartikel (refereegranskat)abstract
- Background: Current prostate cancer prognostic models are based on pre-treatment prostate specific antigen (PSA) levels, biopsy Gleason score, and clinical staging but in practice are inadequate to accurately predict disease progression. Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models. Methods: We analyzed a Swedish Watchful Waiting cohort with up to 30 years of clinical follow up using a novel method for gene expression profiling. This cDNA-mediated annealing, selection, ligation, and extension (DASL) method enabled the use of formalin-fixed paraffin-embedded transurethral resection of prostate (TURP) samples taken at the time of the initial diagnosis. We determined the expression profiles of 6100 genes for 281 men divided in two extreme groups: men who died of prostate cancer and men who survived more than 10 years without metastases (lethals and indolents, respectively). Several statistical and machine learning models using clinical and molecular features were evaluated for their ability to distinguish lethal from indolent cases. Results: Surprisingly, none of the predictive models using molecular profiles significantly improved over models using clinical variables only. Additional computational analysis confirmed that molecular heterogeneity within both the lethal and indolent classes is widespread in prostate cancer as compared to other types of tumors. Conclusions: The determination of the molecularly dominant tumor nodule may be limited by sampling at time of initial diagnosis, may not be present at time of initial diagnosis, or may occur as the disease progresses making the development of molecular biomarkers for prostate cancer progression challenging.
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| 4. |
- Setlur, Sunita R., et al.
(författare)
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Estrogen-dependent signaling in a molecularly distinct subclass of aggressive prostate cancer
- 2008
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Ingår i: Journal of the National Cancer Institute. - Oxford : Oxford University Press. - 0027-8874 .- 1460-2105. ; 100:11, s. 815-825
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The majority of prostate cancers harbor gene fusions of the 5'-untranslated region of the androgen-regulated transmembrane protease serine 2 (TMPRSS2) promoter with erythroblast transformation-specific transcription factor family members. The common fusion between TMPRESS2 and v-ets erythroblastosis virus E26 oncogene homolog (avian) (ERG) is associated with a more aggressive clinical phenotype, implying the existence of a distinct subclass of prostate cancer defined by this fusion. METHODS: We used complementary DNA-mediated annealing, selection, ligation, and extension to determine the expression profiles of 6144 transcriptionally informative genes in archived biopsy samples from 455 prostate cancer patients in the Swedish Watchful Waiting cohort (1987-1999) and the United States-based Physicians(') Health Study cohort (1983-2003). A gene expression signature for prostate cancers with the TMPRSS2-ERG fusion was determined using partitioning and classification models and used in computational functional analysis. Cell proliferation and TMPRSS2-ERG expression in androgen receptor-negative (NCI-H660) prostate cancer cells after treatment with vehicle or estrogenic compounds were assessed by viability assays and quantitative polymerase chain reaction, respectively. All statistical tests were two-sided. RESULTS: We identified an 87-gene expression signature that distinguishes TMPRSS2-ERG fusion prostate cancer as a discrete molecular entity (area under the curve = 0.80, 95% confidence interval [CI] = 0.792 to 0.81; P < .001). Computational analysis suggested that this fusion signature was associated with estrogen receptor (ER) signaling. Viability of NCI-H660 cells decreased after treatment with estrogen (viability normalized to day 0, estrogen vs vehicle at day 8, mean = 2.04 vs 3.40, difference = 1.36, 95% CI = 1.12 to 1.62) or ERbeta agonist (ERbeta agonist vs vehicle at day 8, mean = 1.86 vs 3.40, difference = 1.54, 95% CI = 1.39 to 1.69) but increased after ERalpha agonist treatment (ERalpha agonist vs vehicle at day 8, mean = 4.36 vs 3.40, difference = 0.96, 95% CI = 0.68 to 1.23). Similarly, expression of TMPRSS2-ERG decreased after ERbeta agonist treatment (fold change over internal control, ERbeta agonist vs vehicle at 24 hours, NCI-H660, mean = 0.57- vs 1.0-fold, difference = 0.43-fold, 95% CI = 0.29- to 0.57-fold) and increased after ERalpha agonist treatment (ERalpha agonist vs vehicle at 24 hours, mean = 5.63- vs 1.0-fold, difference = 4.63-fold, 95% CI = 4.34- to 4.92-fold). CONCLUSIONS: TMPRSS2-ERG fusion prostate cancer is a distinct molecular subclass. TMPRSS2-ERG expression is regulated by a novel ER-dependent mechanism.
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