Image-based assessment of extracellular mucin-to-tumor area predicts consensus molecular subtypes (CMS) in colorectal cancer

Nguyen, Huu-Giao; Lundström, Oxana; Blank, Annika; Dawson, Heather; Lugli, Alessandro; Anisimova, Maria; Zlobec, Inti

doi:10.1038/s41379-021-00894-8

Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-23798

Publication type:	Article in scientific journal
Type of review:	Peer review (publication)
Title:	Image-based assessment of extracellular mucin-to-tumor area predicts consensus molecular subtypes (CMS) in colorectal cancer
Authors:	Nguyen, Huu-Giao Lundström, Oxana Blank, Annika Dawson, Heather Lugli, Alessandro Anisimova, Maria Zlobec, Inti
et. al:	No
DOI:	10.1038/s41379-021-00894-8 10.21256/zhaw-23798
Published in:	Modern Pathology
Volume(Issue):	35
Page(s):	240
Pages to:	248
Issue Date:	2-Sep-2021
Publisher / Ed. Institution:	Nature Publishing Group
ISSN:	0893-3952 1530-0285
Language:	English
Subject (DDC):	572: Biochemistry
Abstract:	The backbone of all colorectal cancer classifications including the consensus molecular subtypes (CMS) highlights microsatellite instability (MSI) as a key molecular pathway. Although mucinous histology (generally defined as >50% extracellular mucin-to-tumor area) is a "typical" feature of MSI, it is not limited to this subgroup. Here, we investigate the association of CMS classification and mucin-to-tumor area quantified using a deep learning algorithm, and the expression of specific mucins in predicting CMS groups and clinical outcome. A weakly supervised segmentation method was developed to quantify extracellular mucin-to-tumor area in H&E images. Performance was compared to two pathologists' scores, then applied to two cohorts: (1) TCGA (n = 871 slides/412 patients) used for mucin-CMS group correlation and (2) Bern (n = 775 slides/517 patients) for histopathological correlations and next-generation Tissue Microarray construction. TCGA and CPTAC (n = 85 patients) were used to further validate mucin detection and CMS classification by gene and protein expression analysis for MUC2, MUC4, MUC5AC and MUC5B. An excellent inter-observer agreement between pathologists' scores and the algorithm was obtained (ICC = 0.92). In TCGA, mucinous tumors were predominantly CMS1 (25.7%), CMS3 (24.6%) and CMS4 (16.2%). Average mucin in CMS2 was 1.8%, indicating negligible amounts. RNA and protein expression of MUC2, MUC4, MUC5AC and MUC5B were low-to-absent in CMS2. MUC5AC protein expression correlated with aggressive tumor features (e.g., distant metastases (p = 0.0334), BRAF mutation (p < 0.0001), mismatch repair-deficiency (p < 0.0001), and unfavorable 5-year overall survival (44% versus 65% for positive/negative staining). MUC2 expression showed the opposite trend, correlating with less lymphatic (p = 0.0096) and venous vessel invasion (p = 0.0023), no impact on survival.The absence of mucin-expressing tumors in CMS2 provides an important phenotype-genotype correlation. Together with MSI, mucinous histology may help predict CMS classification using only histopathology and should be considered in future image classifiers of molecular subtypes.
URI:	https://digitalcollection.zhaw.ch/handle/11475/23798
Fulltext version:	Published version
License (according to publishing contract):	CC BY 4.0: Attribution 4.0 International
Departement:	Life Sciences and Facility Management
Organisational Unit:	Institute of Computational Life Sciences (ICLS)
Published as part of the ZHAW project:	Trans-omic approach to colorectal cancer: an integrative computational and clinical perspective
Appears in collections:	Publikationen Life Sciences und Facility Management

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Nguyen, H.-G., Lundström, O., Blank, A., Dawson, H., Lugli, A., Anisimova, M., & Zlobec, I. (2021). Image-based assessment of extracellular mucin-to-tumor area predicts consensus molecular subtypes (CMS) in colorectal cancer. Modern Pathology, 35, 240–248. https://doi.org/10.1038/s41379-021-00894-8

Nguyen, H.-G. et al. (2021) ‘Image-based assessment of extracellular mucin-to-tumor area predicts consensus molecular subtypes (CMS) in colorectal cancer’, Modern Pathology, 35, pp. 240–248. Available at: https://doi.org/10.1038/s41379-021-00894-8.

H.-G. Nguyen et al., “Image-based assessment of extracellular mucin-to-tumor area predicts consensus molecular subtypes (CMS) in colorectal cancer,” Modern Pathology, vol. 35, pp. 240–248, Sep. 2021, doi: 10.1038/s41379-021-00894-8.

NGUYEN, Huu-Giao, Oxana LUNDSTRÖM, Annika BLANK, Heather DAWSON, Alessandro LUGLI, Maria ANISIMOVA und Inti ZLOBEC, 2021. Image-based assessment of extracellular mucin-to-tumor area predicts consensus molecular subtypes (CMS) in colorectal cancer. Modern Pathology. 2 September 2021. Bd. 35, S. 240–248. DOI 10.1038/s41379-021-00894-8

Nguyen, Huu-Giao, Oxana Lundström, Annika Blank, Heather Dawson, Alessandro Lugli, Maria Anisimova, and Inti Zlobec. 2021. “Image-Based Assessment of Extracellular Mucin-to-Tumor Area Predicts Consensus Molecular Subtypes (CMS) in Colorectal Cancer.” Modern Pathology 35 (September): 240–48. https://doi.org/10.1038/s41379-021-00894-8.

Nguyen, Huu-Giao, et al. “Image-Based Assessment of Extracellular Mucin-to-Tumor Area Predicts Consensus Molecular Subtypes (CMS) in Colorectal Cancer.” Modern Pathology, vol. 35, Sept. 2021, pp. 240–48, https://doi.org/10.1038/s41379-021-00894-8.