A panel of DNA methylation markers for the classification of consensus molecular subtypes 2 and 3 in patients with colorectal cancer

Inge van den Berg, Marcel Smid, Robert R J Coebergh van den Braak, Mark A van de Wiel, Carolien H M van Deurzen, Vanja de Weerd, John W M Martens, Jan N M IJzermans, Saskia M Wilting, Inge van den Berg, Marcel Smid, Robert R J Coebergh van den Braak, Mark A van de Wiel, Carolien H M van Deurzen, Vanja de Weerd, John W M Martens, Jan N M IJzermans, Saskia M Wilting

Abstract

Consensus molecular subtypes (CMSs) can guide precision treatment of colorectal cancer (CRC). We aim to identify methylation markers to distinguish between CMS2 and CMS3 in patients with CRC, for which an easy test is currently lacking. To this aim, fresh-frozen tumor tissue of 239 patients with stage I-III CRC was analyzed. Methylation profiles were obtained using the Infinium HumanMethylation450 BeadChip. We performed adaptive group-regularized logistic ridge regression with post hoc group-weighted elastic net marker selection to build prediction models for classification of CMS2 and CMS3. The Cancer Genome Atlas (TCGA) data were used for validation. Group regularization of the probes was done based on their location either relative to a CpG island or relative to a gene present in the CMS classifier, resulting in two different prediction models and subsequently different marker panels. For both panels, even when using only five markers, accuracies were > 90% in our cohort and in the TCGA validation set. Our methylation marker panel accurately distinguishes between CMS2 and CMS3. This enables development of a targeted assay to provide a robust and clinically relevant classification tool for CRC patients.

Trial registration: ClinicalTrials.gov NCT00647530.

Keywords: colon cancer; consensus molecular subtypes; marker panel; methylation.

Conflict of interest statement

The authors declare no conflict of interest.

© 2021 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

Figures

Fig. 1
Fig. 1
Principal component analysis (PCA) of DNA methylation profiles from all CMS2 and CMS3 samples present in the MATCH and TCGA cohorts. Principal components were calculated for DNA methylation profiles of 286 colorectal cancer tissues (146 from MATCH cohort (black) and 140 from TCGA cohort (red)). PC1, PC2, and PC3 are shown on the x‐, y, and z‐axis, respectively, where each dot represents 1 sample. Samples are colored based on their cohort of origin (MATCH in black and TCGA in red).
Fig. 2
Fig. 2
Principal component analysis (PCA) of DNA methylation profiles from all CMS2 and CMS3 samples present in the MATCH and TCGA cohorts. Principal components were calculated for DNA methylation profiles of 286 colorectal cancer tissues (242 CMS2 samples (black) and 44 CMS3 samples). PC1, PC2, and PC3 are shown on the x‐, y‐, and z‐axis, respectively, where each dot represents 1 sample. Samples are colored based on CMS classification (CMS2 in black and CMS3).
Fig. 3
Fig. 3
Box plots showing the median methylation levels observed in CMS2 and CMS3 samples where probes are grouped based on their location relative to a CpG island (CGI). These are box‐and‐whisker plots, showing the distribution of the data following the standard conventions; the median as horizontal bar within the box, which depicts the middle 50% of observations. The whiskers extend to 1.5 IQR (interquartile range) below Q1 and above Q3 (lower and upper quartile, respectively). Median methylation levels are shown in CMS2 (white) and CMS3 (gray) samples from the MATCH (left) and TCGA (right) cohorts in A. for all probes included (n = 45 721), in B. for probes located in CpG islands (CGI; n = 19 837), in C. for probes located in CGI shores (n = 11 111), in D. for probes located in CGI shelves (n = 2167), and in E. for probes located in the open sea (n = 12570). *P < 0.05; **P < 0.01; and ***P < 0.001 (Mann–Whitney U‐test).
Fig. 4
Fig. 4
Evaluation of the (gr)ridge prediction models in the training dataset (MATCH). Receiver –operating characteristic (ROC) curves are shown for (A) ordinary ridge (black) and group‐regularized ridge (grridge) models with CpG codata (gray) and CMSori codata (gray dashed line), (B) grridge models based on CpG codata with post hoc group‐weighted elastic net feature selection of 15 (red), 10 (green), and 5 (blue) markers, and (C) grridge models based on CMSori codata with post hoc group‐weighted elastic net feature selection of 15 (red), 10 (green), and 5 (blue) markers. In (D) the obtained probabilities for CMS3 are plotted for CpG codata (solid fill) and CMSori codata (striped fill) models with all features (gray), 15 markers (red), 10 markers (green), and 5 markers (blue).

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