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Golgi protein GOLM1 is a tissue and urine biomarker of prostate cancer.

ABSTRACT: Prostate cancer is the most common type of tumor found in American men and is the second leading cause of cancer death in males. To identify biomarkers that distinguish prostate cancer from normal, we compared multiple gene expression profiling studies. Through meta-analysis of expression array data from multiple prostate cancer studies, we identified GOLM1 (Golgi membrane protein 1, Golm 1) as consistently up-regulated in clinically localized prostate cancer. This observation was confirmed by reverse transcription-polymerase chain reaction (RT-PCR) and validated at the protein level by immunoblot assay and immunohistochemistry. Prostate epithelial cells were identified as the cellular source of GOLM1 expression using laser capture microdissection. Immunohistochemical staining localized the GOLM1 signal to the subapical cytoplasmic region, typical of a Golgi distribution. Surprisingly, GOLM1 immunoreactivity was detected in the supernatants of prostate cell lines and in the urine of patients with prostate cancer. The mechanism by which intact GOLM1 might be released from cells has not yet been elucidated. GOLM1 transcript levels were measured in urine sediments using quantitative PCR on a cohort of patients presenting for biopsy or radical prostatectomy. We found that urinary GOLM1 mRNA levels were a significant predictor of prostate cancer. Further, GOLM1 outperformed serum prostate-specific antigen (PSA) in detecting prostate cancer. The area under the receiver-operating characteristic curve was 0.622 for GOLM1 (P = .0009) versus 0.495 for serum PSA (P = .902). Our data indicating the up-regulation of GOLM1 expression and its appearance in patients' urine suggest GOLM1 as a potential novel biomarker for clinically localized prostate cancer.

SUBMITTER: Varambally S

PROVIDER: S-EPMC2570605 | biostudies-literature | 2008 Nov

REPOSITORIES: biostudies-literature

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Golgi protein GOLM1 is a tissue and urine biomarker of prostate cancer.

Varambally Sooryanarayana S Laxman Bharathi B Mehra Rohit R Cao Qi Q Dhanasekaran Saravana M SM Tomlins Scott A SA Granger Jill J Vellaichamy Adaikkalam A Sreekumar Arun A Yu Jianjun J Gu Wenjuan W Shen Ronglai R Ghosh Debashis D Wright Lorinda M LM Kladney Raleigh D RD Kuefer Rainer R Rubin Mark A MA Fimmel Claus J CJ Chinnaiyan Arul M AM

Neoplasia (New York, N.Y.) 20081101 11

Prostate cancer is the most common type of tumor found in American men and is the second leading cause of cancer death in males. To identify biomarkers that distinguish prostate cancer from normal, we compared multiple gene expression profiling studies. Through meta-analysis of expression array data from multiple prostate cancer studies, we identified GOLM1 (Golgi membrane protein 1, Golm 1) as consistently up-regulated in clinically localized prostate cancer. This observation was confirmed by r ...[more]

PMID: 18953438

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Project description:BackgroundProstate cancer diagnosis using the PSA test remains controversial because of overdiagnosis and overtreatment of potentially indolent cancers. There remains a need to increase the diagnostic lead time and to target treatment to patients with significant disease. One possible approach to overcome the limitations of PSA is to screen men for the molecular signature of early PCA, monitor the rate of disease progression and target treatment to patients who are likely to benefit from it. Such an approach requires a large panel of markers that define a molecular clock for PCA. We recently developed a panel of 19 markers for the non-invasive detection of PCA from urine DNA. It raised the possibility that additional methylation markers could be successfully analyzed from urine DNA, a prerequisite for increasing the diagnostic lead time and enabling disease monitoring.MethodsWe developed semi-quantitative polymerase chain reaction assays for 13 additional markers and determined their methylation status in 150 urine DNAs from 94 patients with elevated PSA. Eighty five samples were obtained following DRE and 65 samples were from first void. We combined the data of the 13 new markers with the previously reported 19 markers and calculated the sensitivity, specificity, negative and positive predictive values at every threshold from one to 32 positive markers.ResultsUsing 10of32 positive markers as the threshold to recommend a biopsy yields a sensitivity of 81% (95% CI 0.68-0.93) and 93% (95% CI 0.84-1.02) and a specificity of 76% (95% CI 0.63-0.88) and 77% (95% CI 0.63-0.91) from DRE and FV DNA, respectively. The PPV was 71% and 77% and the NPV was 85% and 93% from DRE and FV, respectively.ConclusionsThis study shows that large marker panels can be analyzed from urine DNA without loss of sensitivity or specificity. Using 32 markers improved the stratification of patients undergoing screening for PCA particularly for patients below the 10of32 threshold. The results show the utility of larger biomarker panels for PCA diagnosis and suggest that the development of the panels needed to monitor disease progression could be successfully accomplished.

Project description:BackgroundProstate cancer (PC) is a multifocal disease. DNA methylation alterations are not restricted to the immediate peritumor environment, but spatially widespread in the adjacent and distant histologically normal prostate tissues. In the current study, we utilized high-throughput methylation arrays to identify epigenetic changes in the urine from men with and without cancer.Design, setting, and participantsDNA urine samples were enriched for methylated fragments using MBD methyl-binding antibodies and applied to high density CytoScanHD arrays. Significant loci were validated using quantitative pyrosequencing and binary logistic regression modeling applied to urine sample analyses in a training (n = 83) and validation approach (n = 84). Methylation alterations in prostate tissues using pyrosequencing at the PLA2G16 locus were examined in 38 histologically normal specimens from men with (TA, n = 26) and without (NTA, n = 12) cancer and correlated to gene expression.ResultsMethylation microarrays identified 3,986 loci showing significantly altered methylation in the urine samples from patients with PC compared to those without (TA vs NTA; p<0.01). These loci were then compared against subjects with their prostates removed to exclude non-prostate cell markers yielding 196 significant regions. Multiple CpGs adjacent to PLA2G16 CpG island showed increased methylation in TA compared to NTA (p<0.01) in a large validation study of urine samples. The predictive accuracy of PLA2G16 methylation at CG2 showed the highest predictive value at 0.8 (odds ratio, 1.37; 95% confidence interval, 1.16-1.62; p<0.001). Using a probability cutoff of 0.065, the sensitivity and specificity of the multivariate model was 92% and 35%. When histologically normal prostate tissues/biopsies from patients with PC (TA) were compared to subjects without cancer, significant hypermethylation of PLA2G16 was noted (odds ratio, 1.35; 95% confidence interval, 1.07-1.71; p = 0.01).ConclusionPLA2G16 methylation defines an extensive field defect in histologically normal prostate tissue associated with PC. PLA2G16 methylation in urine and prostate tissues can detect the presence of PC.

Dataset Information

Golgi protein GOLM1 is a tissue and urine biomarker of prostate cancer.

Publications

Golgi protein GOLM1 is a tissue and urine biomarker of prostate cancer.

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