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Qualitative and Quantitative Requirements for Assessing Prognostic Markers in Prostate Cancer.

ABSTRACT: Molecular prognostic markers are urgently needed in order to improve therapy decisions in prostate cancer. To better understand the requirements for biomarker studies, we re-analyzed prostate cancer tissue microarray immunohistochemistry (IHC) data from 39 prognosis markers in subsets of 50 - >10,000 tumors. We found a strong association between the "prognostic power" of individual markers and the number of tissues that should be minimally included in such studies. The prognostic relevance of more than 90% of the 39 IHC markers could be detected if ?6400 tissue samples were analyzed. Studying markers of tissue quality, including immunohistochemistry of ets-related gene (ERG) and vimentin, and fluorescence in-situ hybridization analysis of human epidermal growth factor receptor 2 (HER2), we found that 18% of tissues in our tissue microarray (TMA) showed signs of reduced tissue preservation and limited immunoreactivity. Comparing the results of Kaplan-Meier survival analyses or associations to ERG immunohistochemistry in subsets of tumors with and without exclusion of these defective tissues did not reveal statistically relevant differences. In summary, our study demonstrates that TMA-based marker validation studies using biochemical recurrence as an endpoint require at least 6400 individual tissue samples for establishing statistically relevant associations between the expression of molecular markers and patient outcome if weak to moderate prognosticators should also be reliably identified.

SUBMITTER: Burdelski C

PROVIDER: S-EPMC5003445 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Qualitative and Quantitative Requirements for Assessing Prognostic Markers in Prostate Cancer.

Burdelski Christoph C Matuszewska Aleksandra A Kluth Martina M Koop Christina C Grupp Katharina K Steurer Stefan S Wittmer Corinna C Minner Sarah S Tsourlakis Maria Christina MC Sauter Guido G Schlomm Thorsten T Simon Ronald R

Microarrays (Basel, Switzerland) 20140417 2

Molecular prognostic markers are urgently needed in order to improve therapy decisions in prostate cancer. To better understand the requirements for biomarker studies, we re-analyzed prostate cancer tissue microarray immunohistochemistry (IHC) data from 39 prognosis markers in subsets of 50 - >10,000 tumors. We found a strong association between the "prognostic power" of individual markers and the number of tissues that should be minimally included in such studies. The prognostic relevance of mo ...[more]

PMID: 27600340

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Project description:BackgroundProstate cancer (PCa) is an immune-responsive disease. The current study sought to explore a robust immune-related prognostic gene signature for PCa.MethodsData were retrieved from the tumor Genome Atlas (TCGA) database and GSE46602 database for performing the least absolute shrinkage and selection operator (LASSO) cox regression model analysis. Immune related genes (IRGs) data were retrieved from ImmPort database.ResultsThe weighted gene co-expression network analysis (WGCNA) showed that nine functional modules are correlated with the biochemical recurrence of PCa, including 259 IRGs. Univariate regression analysis and survival analysis identified 35 IRGs correlated with the prognosis of PCa. LASSO Cox regression model analysis was used to construct a risk prognosis model comprising 18 IRGs. Multivariate regression analysis showed that risk score was an independent predictor of the prognosis of PCa. A nomogram comprising a combination of this model and other clinical features showed good prediction accuracy in predicting the prognosis of PCa. Further analysis showed that different risk groups harbored different gene mutations, differential transcriptome expression and different immune infiltration levels. Patients in the high-risk group exhibited more gene mutations compared with those in the low-risk group. Patients in the high-risk groups showed high-frequency mutations in TP53. Immune infiltration analysis showed that M2 macrophages were significantly enriched in the high-risk group implying that it affected prognosis of PCa patients. In addition, immunostimulatory genes were differentially expressed in the high-risk group compared with the low-risk group. BIRC5, as an immune-related gene in the prediction model, was up-regulated in 87.5% of prostate cancer tissues. Knockdown of BIRC5 can inhibit cell proliferation and migration.ConclusionIn summary, a risk prognosis model based on IGRs was developed. A nomogram comprising a combination of this model and other clinical features showed good accuracy in predicting the prognosis of PCa. This model provides a basis for personalized treatment of PCa and can help clinicians in making effective treatment decisions.

Project description:Men with familial prostate cancer and African American men are at risk for developing prostate cancer at younger ages. Genetic markers predicting early-onset prostate cancer may provide clinically useful information to guide screening strategies for high-risk men. We evaluated clinical information from six polymorphisms associated with early-onset prostate cancer in a longitudinal cohort of high-risk men enrolled in prostate cancer early detection with significant African American participation.Eligibility criteria include ages 35 to 69 with a family history of prostate cancer or African American race. Participants undergo screening and biopsy per study criteria. Six markers associated with early-onset prostate cancer [rs2171492 (7q32), rs6983561 (8q24), rs10993994 (10q11), rs4430796 (17q12), rs1799950 (17q21), and rs266849 (19q13)] were genotyped. Cox models were used to evaluate time to prostate cancer diagnosis and prostate-specific antigen (PSA) prediction for prostate cancer by genotype. Harrell's concordance index was used to evaluate predictive accuracy for prostate cancer by PSA and genetic markers.Four hundred and sixty participants with complete data and ? 1 follow-up visit were included. Fifty-six percent were African American. Among African American men, rs6983561 genotype was significantly associated with earlier time to prostate cancer diagnosis (P = 0.005) and influenced prediction for prostate cancer by the PSA (P < 0.001). When combined with PSA, rs6983561 improved predictive accuracy for prostate cancer compared with PSA alone among African American men (PSA = 0.57 vs. PSA + rs6983561 = 0.75, P = 0.03).Early-onset marker rs6983561 adds potentially useful clinical information for African American men undergoing prostate cancer risk assessment. Further study is warranted to validate these findings.Genetic markers of early-onset prostate cancer have potential to refine and personalize prostate cancer early detection for high-risk men.

Dataset Information

Qualitative and Quantitative Requirements for Assessing Prognostic Markers in Prostate Cancer.

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Qualitative and Quantitative Requirements for Assessing Prognostic Markers in Prostate Cancer.

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