domingo, 30 de diciembre de 2012

Study of genetic and epigenetic alterations i... [Anticancer Res. 2013] - PubMed - NCBI

Study of genetic and epigenetic alterations i... [Anticancer Res. 2013] - PubMed - NCBI

Anticancer Res. 2013 Jan;33(1):191-7.

Study of genetic and epigenetic alterations in urine samples as diagnostic markers for prostate cancer.

Source

Department of Genetics, St. Savvas Anticancer Hospital, Alexandras Ave 171, 11522, Athens, Greece. dthimios@hotmail.com.

Abstract

BACKGROUND:

Early diagnosis of prostate cancer and identification of new prognostic factors remain main issues in prostate cancer research. In this study, we sought to test a panel of cancer-specific markers in urine samples as an aid for early cancer diagnosis.

MATERIALS AND METHODS:

Sedimented urine samples of 66 candidates for needle biopsy were tested. Real time-polymerase chain reaction (RT-PCR) was applied to detect the expression of transmembrane protease serine-2 and Ets-related gene fusion (TMPRSS2-ERG), Ets-related gene (ERG), prostate cancer antigen-3 (PCA3), and serine peptidase inhibitor kazal type-1 (SPINK1) transcripts. For testing of the methylation status of Glutahione S-tranferase P (GSTP1) and Ras association domain family member-1(RASSF1A) promoter region, methylation-specific PCR (MSP-PCR) was applied.

RESULTS:

Among the tested parameters, the presence of TMPRSS2-ERG (OR=9.044, 95% CI=2.207-37.066, p=0.002), as well as a positive test result for PCA3 (OR=7.549, 95% CI=1,858-30,672, p=0.005) were associated with the subsequent diagnosis of prostate cancer. A multivariable logistic regression including all the significantly associated variables [prostate-specific antigen (PSA), digital rectal examination (DRE), TMPRSS2-ERG and PCA3], yielded a model with area under the receiver-operating characteristic curve (AUC) =0.894 (95% CI=0.772-1.00).

CONCLUSION:

A multiplexed quantitative PCR analysis on sedimented urine, in conjunction with the results of serum PSA levels and DRE, has the potential to accurately foresee subsequent needle biopsy outcomes. On the basis of the above, algorithms may be designed to guide decisions for needle biopsy.
PMID:
23267145
[PubMed - in process]

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