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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-23798
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dc.contributor.authorNguyen, Huu-Giao-
dc.contributor.authorLundström, Oxana-
dc.contributor.authorBlank, Annika-
dc.contributor.authorDawson, Heather-
dc.contributor.authorLugli, Alessandro-
dc.contributor.authorAnisimova, Maria-
dc.contributor.authorZlobec, Inti-
dc.date.accessioned2021-12-20T10:30:36Z-
dc.date.available2021-12-20T10:30:36Z-
dc.date.issued2021-09-02-
dc.identifier.issn0893-3952de_CH
dc.identifier.issn1530-0285de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/23798-
dc.description.abstractThe 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.de_CH
dc.language.isoende_CH
dc.publisherNature Publishing Groupde_CH
dc.relation.ispartofModern Pathologyde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subject.ddc572: Biochemiede_CH
dc.titleImage-based assessment of extracellular mucin-to-tumor area predicts consensus molecular subtypes (CMS) in colorectal cancerde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.organisationalunitInstitut für Computational Life Sciences (ICLS)de_CH
dc.identifier.doi10.1038/s41379-021-00894-8de_CH
dc.identifier.doi10.21256/zhaw-23798-
dc.identifier.pmid34475526de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end248de_CH
zhaw.pages.start240de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume35de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.funding.snf193832de_CH
zhaw.webfeedComputational Genomicsde_CH
zhaw.funding.zhawTrans-omic approach to colorectal cancer: an integrative computational and clinical perspectivede_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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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.


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