Consensus molecular subtypes classification of colorectal cancer as a predictive factor for chemotherapeutic efficacy against metastatic colorectal cancer

736 Background: Since treatment options of chemotherapy for metastatic colorectal cancer (mCRC) have been diversified, biomarkers which could predict efficacy of chemotherapies are needed for optimal treatment. In this study, we analyzed the association of the treatment outcomes by several chemotherapies and the consensus molecular subtypes (CMS), which was developed from large-scale comprehensive gene expression analysis of colorectal cancer (Guinney J et al. Nat Med 21:1350-6, 2015). Methods: A total of 193 patients with previously treated mCRC were classified in 4 subtypes, CMS1 to CMS4 by using the microarrays data of primary tumors and the “CMS classifier” package for the R software. Then the association between the subtypes and the treatment outcomes was analyzed retrospectively. Results: The193 cases were classified into 21 CMS1, 53 CMS2, 69 CMS3 and 50 CMS4. The molecular characteristics of each subtype such as mutation status of KRAS and BRAF genes, and DNA methylation status were consistent with those of the previous study. First-line chemotherapies of the 193 patients were oxaliplatin (OX)-based treatment (121 patients), irinotecan (IRI)-based treatment (59 patients) and others (13 patients). In CMS4, the median progression-free survival (PFS) of the IRI-based group was significantly longer than that of the OX-based group (21.8 months vs. 10.5 months, p < 0.01). The median overall survival (OS) and objective response rate of the IRI-based group were also better than that of the OX-based group in CMS4. Among 193 patients, 103 were RAS wild-type and treated with anti-EGFR antibody. The effect of the anti-EGFR treatment was low in CMS1 (median PFS: 2.4 months, p < 0.01, median OS: 5.7 months, p < 0.01) and whereas was high in CMS2 (median PFS: 8.0 months, p = 0.05, median OS: 26.6 months, p = 0.02). CMS significantly correlated with PFS and OS after anti-EGFR treatment by univariate analysis. However the most useful predictive biomarker was a DNA methylation status by multivariable analysis. Conclusions: The biological characteristics of CMS may affect the therapeutic effect of anti-cancer agents in mCRC and, therefore, might be a new predictive factor of anti-cancer treatment.

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Consensus molecular subtypes in metastatic colorectal cancer treated with sequential versus combined fluoropyrimidine, bevacizumab and irinotecan (XELAVIRI trial)

European Journal of Cancer ◽

10.1016/j.ejca.2021.08.017 ◽

2021 ◽

Vol 157 ◽

pp. 71-80

Author(s):

Arndt Stahler ◽

Volker Heinemann ◽

Veronika Schuster ◽

Kathrin Heinrich ◽

Annika Kurreck ◽

...

Keyword(s):

Colorectal Cancer ◽

Metastatic Colorectal Cancer ◽

Molecular Subtypes

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Classification of Colorectal Cancer in Molecular Subtypes by Immunohistochemistry

Methods in Molecular Biology - Colorectal Cancer ◽

10.1007/978-1-4939-7765-9_11 ◽

2018 ◽

pp. 179-191 ◽

Cited By ~ 8

Author(s):

Sanne ten Hoorn ◽

Anne Trinh ◽

Joan de Jong ◽

Lianne Koens ◽

Louis Vermeulen

Keyword(s):

Colorectal Cancer ◽

Molecular Subtypes

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

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.3545 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 3545-3545

Author(s):

Inge van Den Berg ◽

Marcel Smid ◽

Robert R.J. Coebergh van den Braak ◽

Mark A van de Wiel ◽

Carolien H. M. Van Deurzen ◽

...

Keyword(s):

Colorectal Cancer ◽

Dna Methylation ◽

Prediction Models ◽

Molecular Subtypes ◽

Cpg Island ◽

Methylation Marker ◽

Marker Selection ◽

Fresh Frozen ◽

Classification Tool

3545 Background: Consensus molecular subtypes (CMSs) can guide precision treatment of colorectal cancer (CRC). Currently available assays can identify CMS1 and CMS4 cases well, while a dedicated test to distinguish CMS2 and 3 is lacking. This study aimed to identify a panel of methylation markers to distinguish between CMS2 and 3 in patients with CRC. Methods: Fresh-frozen tumor tissue of 239 patients with stage I-III CRC was included. CMS classification was performed on RNA-seq data using the single-sample-prediction parameter from the “CMSclassifier” package. Methylation profiles were obtained using the Infinium HumanMethylation450 BeadChip. We performed adaptive group-regularised logistic ridge-regression with post-hoc group-weighted elastic net marker selection to build prediction models for classification of CMS2 and CMS3 based on 15, 10 or 5 markers. Data from TCGAwas used for validation. Results: Overall methylation profiles differed between CMS2 and CMS3. Group-regularisation 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 5 markers, sensitivity, specificity, and accuracy were > 90%. Validation showed comparable performances. Conclusions: Our highly sensitive and specific methylation marker panel can be used to distinguish CMS2 and 3. This enables development of a qPCR DNA methylation assay in patients with CRC to provide a specific and non-invasive classification tool.

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