The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
DNA Methylation Biomarkers for Blood-Based Colorectal Cancer Screening
Abstract
Background: Sensitive, specific blood-based tests are difficult to develop unless steps are taken to maximize performance characteristics at every stage of marker discovery and development. We describe a sieving strategy for identifying high-performing marker assays that detect colorectal cancer (CRC)-specific methylated DNA in plasma. Methods: We first used restriction enzyme–based discovery methods to identify marker candidates with obviously different methylation patterns in CRC tissue and nonpathologic tissue. We then used a selection process incorporating microarrays and/or real-time PCR analysis of tissue samples to further test marker candidates for maximum methylation in CRC tissue and minimum amplification in tissues from both healthy individuals and patients with other diseases. Real-time assays of 3 selected markers were validated with plasma samples from 133 CRC patients and 179 healthy control individuals in the same age range. Results: Restriction enzyme–based testing identified 56 candidate markers. This group was reduced to 6 with microarray and real-time PCR testing. Three markers, TMEFF2, NGFR, and SEPT9, were tested with plasma samples. TMEFF2 methylation was detected in 65% [95% confidence interval, 56%–73%] of plasma samples from CRC patients and not detected in 69% (62%–76%) of the controls. The corresponding results for NGFR were 51% (42%–60%) and 84% (77%–89%); for SEPT9, the values were 69% (60%–77%) and 86% (80%–91%). Conclusions: The stringent criteria applied at all steps of the selection and validation process enabled successful identification and ranking of blood-based marker candidates.
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
Cites
(1990) · Choice Reviews Online · doi:10.5860/choice.27-3338 · Cited by 35,305
Cited by
A decade of exploring the cancer epigenome—biological and translational implications
Baylin, S. B., & Jones, P. A. (2011) · Nature Reviews Cancer · doi:10.1038/nrc3130 · Cited by 2,871
Epigenetics of colorectal cancer: biomarker and therapeutic potential
Jung, G., Hernández-Illán, E., Moreira, L., Balaguer, F., & Goel, A. (2020) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-019-0230-y · Cited by 813
Epigenetic Alterations in Colorectal Cancer: Emerging Biomarkers
Okugawa, Y., Grady, W. M., & Goel, A. (2015) · Gastroenterology · doi:10.1053/j.gastro.2015.07.011 · Cited by 782
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
Metadata
- Authors
- Lofton-Day, C., Model, F., DeVos, T., Tetzner, R., Distler, J., Schuster, M., Song, X., Lesche, R., Liebenberg, V., Ebert, M., Molnar, B., Grützmann, R., Pilarsky, C., & Sledziewski, A.
- Venue
- Clinical Chemistry
- Publisher
- Oxford University Press (OUP)
- Published
- 2008-02-01
- Volume
- 54
- Issue
- 2
- Pages
- 414-423
- ISSN
- 0009-9147 (ISSN-L)
- 1530-8561
- OpenAlex
- W2115578647
- Cited by
- 493
- References
- 1
- FWCI
- 5.15
- Type
- journal article
- Language
- en
- Open access
- closed
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: DNA Methylation Biomarkers for Blood-Based Colorectal Cancer Screening. https://app.cochat.ai/papers/10.1373/clinchem.2007.095992
- The paper
- Lofton-Day, C., Model, F., DeVos, T., Tetzner, R., Distler, J., Schuster, M., Song, X., Lesche, R., Liebenberg, V., Ebert, M., Molnar, B., Grützmann, R., Pilarsky, C., & Sledziewski, A. (2008). DNA Methylation Biomarkers for Blood-Based Colorectal Cancer Screening. Clinical Chemistry. https://doi.org/10.1373/clinchem.2007.095992
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.