DNA methylation-based biomarkers and prediction models for the survival of patients with colorectal cancer: systematic review and external validation study
Yuan, T.; Edelmann, D.; Kather, J. N.; Fan, Z.; Tagscherer, K. E.; Roth, W.; Bewerunge-Hudler, M.; Brobeil, A.; Kloor, M.; Blaeker, H.; Burwinkel, B.; Brenner, H.; Hoffmeister, M.
Show abstract
ObjectivesTo identify existing DNA methylation-based prognostic biomarkers and prediction models for colorectal cancer (CRC) prognosis and to validate them in a large external cohort. DesignSystematic review and external validation study. Data sourceSystematic search in PubMed and Web of Science until October 2022 to identify epigenome-wide studies reporting methylation at CpG sites (CpGs) associated with survival among CRC patients. Validation data were drawn from the 2310 CRC patients of the DACHS study recruited from 22 hospitals in the Rhine-Neckar region in the southwest of Germany. Main outcome measuresOverall survival (OS) in CRC patients. ResultsWe identified 200 unique CpGs and 10 CpG-based prognostic models derived from 15 studies. In the external validation analysis, 1252 of 2310 patients died during follow-up (median 10.4 years). Thirty-nine CpGs (20%) and five prognostic models (50%) were independently associated with overall survival after adjustment for clinical variables. The five models had unsatisfactory discrimination ability, with area under the receiver operating characteristic curves at five years ranging from 0.54 to 0.60. The calibration accuracy of the five models using recalibrated baseline survival was also poor, and no relevant added prognostic value to traditional clinical variables was observed. Based on the Prediction Model Risk of Bias Assessment Tool, all models were rated as high risk of bias. ConclusionsOnly 20% of published CpGs associated with survival in CRC patients could be externally validated. So far derived published CpG-based prognostic models for CRC do not seem to be useful for clinical practice. Summary boxO_ST_ABSWhat is already known on this topicC_ST_ABSO_LISeveral studies have suggested that DNA methylation biomarkers could have the potential to improve prognostic accuracy for patients with colorectal cancer (CRC), but these studies mostly did not include large-scale external validation C_LIO_LIMany CpG sites associated with CRC prognosis and prognostic models based on these CpGs have been proposed C_LIO_LIAn independent study to validate these biomarkers and prediction models is essential for assessing their utility in clinical practice, but has not yet performed C_LI What this study addsO_LIThis external validation study verified the prognostic relevance of a fraction of existing DNA methylation-based prognostic biomarkers for CRC C_LIO_LIPublished CpG-based prognostic models all performed poorly in our external validation and were rated as at high risk of bias, so they do not seem to be useful for clinical practice C_LI
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Deeper insights into long-term survival heterogeneity of Pancreatic Ductal Adenocarcinoma (PDAC) patients using integrative individual- and group-level transcriptome network analyses 91%
- Molecular Drivers of Tumor Progression in Microsatellite Stable APC Mutation-Negative Colorectal Cancers 91%
- Survival Genie, a web platform for survival analysis across pediatric and adult cancers. 91%
Similar papers in this journal
- Osteosarcoma: novel prognostic biomarkers using circulating and cell-free tumour DNA 91%
- Development of an artificial intelligence-generated, explainable treatment recommendation system for urothelial carcinoma and renal cell carcinoma to support multidisciplinary cancer conferences 90%
- Repurposing cardiovascular disease prediction models for cancer 88%
Similar papers in this journal
- Survival-Inferred Fragility of Statistical Significance in Phase III Oncology Trials 91%
- Explainable, federated deep learning model predicts disease progression risk of cutaneous squamous cell carcinoma 91%
- Image-Based Consensus Molecular Subtyping in Rectal Cancer Biopsies and Response to Neoadjuvant Chemoradiotherapy 90%
Similar papers in this journal
- A new colorectal cancer risk prediction model incorporating family history, personal and environmental factors 92%
- The Gastric Cancer Registry: A Genomic Translational Resource for Multidisciplinary Research in Stomach Malignancies 90%
- Smoking methylation marks for prediction of urothelial cancer risk 88%
Similar papers in this journal
- Circulating serum miRNAs predict response to platinum chemotherapy in high-grade serous ovarian cancer 90%
- Added-value of whole exome and RNA Sequencing in advanced and refractory cancer patients with no molecular-based treatment recommendation based on a 90-gene panel 89%
- Macrophage Infiltration and ITGB2 Expression in ESCC: A Novel Correlation 89%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.