Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Poster display session

2040 - Genome-wide methylation analysis reveals a prognostic classifier for non-metastatic colorectal cancer (ProMCol)


11 Sep 2017


Poster display session


Cancers in Adolescents and Young Adults (AYA);  Translational Research;  Colon and Rectal Cancer


Melanie Gündert


Annals of Oncology (2017) 28 (suppl_5): v22-v42. 10.1093/annonc/mdx363


M. Gündert1, D. Edelmann2, A. Benner2, L. Jansen3, M. Jia3, V. Walter3, P. Knebel4, E. Herpel5, J. Chang-Claude6, M. Hoffmeister3, H. Brenner3, B. Burwinkel1

Author affiliations

  • 1 Division Of Molecular Epidemiology, German Cancer Research Center, 69120 - Heidelberg/DE
  • 2 Division Of Biostatistics, German Cancer Research Center, 69120 - Heidelberg/DE
  • 3 Division Of Clinical Epidemiology And Aging Research, German Cancer Research Center, 69120 - Heidelberg/DE
  • 4 Department Of General, Visceral And Transplantation Surgery, University of Heidelberg, 69120 - Heidelberg/DE
  • 5 Department Of General Pathology, Institute of Pathology, 69120 - Heidelberg/DE
  • 6 Division Of Cancer Epidemiology, Unit Of Genetic Epidemiology, German Cancer Research Center, 69120 - Heidelberg/DE


Abstract 2040


Currently, pathological staging according to the tumor-node-metastasis system remains the gold standard for the prediction of patient survival in colorectal cancer (CRC) but this classification system provides insufficient information and therefore additional prognostic markers are needed.


A genome-wide methylation analysis was done for two independent cohorts of non-metastatic CRC patients (screening cohort n = 578 and validation cohort n = 308). Initially, genome-wide differentially methylated CpG sites between 34 pairs of tumor and normal mucosa tissue samples from the same patients were identified. A variable screening for prognostic CpG sites was performed in the screening cohort using marginal testing based on the Cox model and subsequent adjustment of the p-values via independent hypothesis weighting (IHW) using the difference between tumor and normal mucosa tissue as auxiliary covariate. From the 1000 CpG sites with the smallest adjusted p-value, the 20 CpG sites with the smallest Brier Score for 3-year overall survival (in the screening cohort) were selected. Applying principal component analysis on these CpG sites, we derived a methylation-based classifier for the prognosis of non-metastatic CRC (ProMCol).


The ProMCol classifier was independently validated in the validation cohort, where it showed a significant reduction in the Brier score. Regarding the three year survival, the prediction error was reduced from 0.132 (calculated only with clinical variables), to 0.124 (combination of clinical variables with ProMCol classifier). An additional replication analysis showed that the ProMCol classifier was significantly associated with overall survival (OS) of non-metastatic CRC patients in the screening (HR = 0.22, 95%CI=0.13-0.35, p=6.2E-10) and the validation cohort (HR = 0.40, 95%CI=0.22-0.74, p=0.003), adjusted for standard clinical factors. Patients with a high methylation status, represented by higher values of the ProMCol classifier, showed a better prognosis for OS than patients with a low methylation status and lower ProMCol classifier values.


The usage of the ProMCol classifier could improve the prognostic accuracy for non-metastatic CRC patients.

Clinical trial identification

Legal entity responsible for the study

Barbara Burwinkel, German Cancer Research Center


German Research Council, German Federal Ministry of Education and Research


All authors have declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.