The DOI matches its Crossref record.
Quantitative Methylation-Specific Polymerase Chain Reaction Gene Patterns in Urine Sediment Distinguish Prostate Cancer Patients From Control Subjects
Open accessAbstract
Purpose: Aberrant promoter hypermethylation of several known or putative tumor suppressor genes occurs frequently during the pathogenesis of prostate cancers and is a promising marker for cancer detection. We sought to develop a test for prostate cancer based on a quantitative methylation-specific polymerase chain reaction (QMSP) of multiple genes in urine sediment DNA. Patients and Methods: We tested urine sediment DNA for aberrant methylation of nine gene promoters (p16INK4a, p14 ARF, MGMT, GSTP1, RARβ2, CDH1 [E-cadherin], TIMP3, Rassf1A, and APC) from 52 patients with prostate cancer and 21 matched primary tumors by quantitative fluorogenic real-time polymerase chain reaction. We also analyzed urine sediments from 91 age-matched individuals without any history of genitourinary malignancy as controls. Results: Promoter hypermethylation of at least one of the genes studied was detected in urine samples from all 52 prostate cancer patients. Urine samples from the 91 controls without evidence of genitourinary cancer revealed no methylation of the p16, ARF, MGMT, and GSTP1 gene promoters, whereas methylation of RARβ2, TIMP3, CDH1, Rassf1A, and APC was detected at low levels. Conclusion: Overall, methylation found in urine samples matched the methylation status in the primary tumor. A combination of only four genes (p16, ARF, MGMT, and GSTP1) would theoretically allow us to detect 87% of prostate cancers with 100% specificity. Our data support further development of the noninvasive QMSP assay in urine DNA for early detection and surveillance of prostate cancer.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Cancer epigenetics reaches mainstream oncology
Rodríguez-Paredes, M., & Esteller, M. (2011) · Nature Medicine · doi:10.1038/nm.2305 · Cited by 1,205
DNA methylation profiling in the clinic: applications and challenges
Heyn, H., & Esteller, M. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3270 · Cited by 746
Analysis of DNA methylation in cancer: location revisited
Koch, A., Joosten, S. C., Feng, Z., de Ruijter, T. C., Draht, M. X., Melotte, V., Smits, K. M., Veeck, J., Herman, J. G., Van Neste, L., et al. (2018) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-018-0004-4 · Cited by 710
Self-citationCan urinary exosomes act as treatment response markers in prostate cancer?
Mitchell, P. J., Welton, J., Staffurth, J., Court, J., Mason, M. D., Tabi, Z., & Clayton, A. (2009) · Journal of Translational Medicine · doi:10.1186/1479-5876-7-4 · Cited by 313
Turner, J. D., Pelascini, L. P. L., Macedo, J. A., & Muller, C. P. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn897 · Cited by 104
Metadata
- Authors
- Hoque, M. O., Topaloglu, O., Begum, S., Henrique, R., Rosenbaum, E., Van Criekinge, W., Westra, W. H., & Sidransky, D.
- Venue
- Journal of Clinical Oncology
- Published
- 2005-09-20
- Volume
- 23
- Issue
- 27
- Pages
- 6569-6575
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- OpenAlex
- W2009052021
- Cited by
- 240
- References
- 0
- FWCI
- 6.57
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Quantitative Methylation-Specific Polymerase Chain Reaction Gene Patterns in Urine Sediment Distinguish Prostate Cancer Patients From Control Subjects. https://app.cochat.ai/papers/10.1200/jco.2005.07.009
- The paper
- Hoque, M. O., Topaloglu, O., Begum, S., Henrique, R., Rosenbaum, E., Van Criekinge, W., Westra, W. H., & Sidransky, D. (2005). Quantitative Methylation-Specific Polymerase Chain Reaction Gene Patterns in Urine Sediment Distinguish Prostate Cancer Patients From Control Subjects. Journal of Clinical Oncology. https://doi.org/10.1200/jco.2005.07.009
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.