Cited by 62Colorectal Cancer Treatments and StudiesGenetic factors in colorectal cancerGene expression and cancer classification

The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.

A Clinically Applicable Gene-Expression Classifier Reveals Intrinsic and Extrinsic Contributions to Consensus Molecular Subtypes in Primary and Metastatic Colon Cancer

Published version of a preprint

Abstract

Purpose: Four consensus molecular subtypes (CMS1–4) of colorectal cancer were identified in primary tumors and found to be associated with distinctive biological features and clinical outcomes. Given that distant metastasis largely accounts for colorectal cancer–related mortality, we examined the molecular and clinical attributes of CMS in metastatic colorectal cancer (mCRC). Experimental Design: We developed a colorectal cancer–focused NanoString-based CMS classifier that is ideally suited to interrogate archival tissues. We successfully used this panel in the CMS classification of formalin-fixed paraffin-embedded (FFPE) tissues from mCRC cohorts, one of which is composed of paired primary tumors and metastases. Finally, we developed novel mouse implantation models to enable modeling of colorectal cancer in vivo at relevant sites. Results: Using our classifier, we find that the biological hallmarks of mCRC, including CMS, are in general highly similar to those observed in nonmetastatic early-stage disease. Importantly, our data demonstrate that CMS1 has the worst outcome in relapsed disease, compared with other CMS. Assigning CMS to primary tumors and their matched metastases reveals mostly concordant subtypes between primary and metastasis. Molecular analysis of matched discordant pairs reveals differences in stromal composition at each site. The development of two novel in vivo orthotopic implantation models further reinforces the notion that extrinsic factors may impact on CMS identification in matched primary and metastatic colorectal cancer. Conclusions: We describe the utility of a NanoString panel for CMS classification of FFPE clinical samples. Our work reveals the impact of intrinsic and extrinsic factors on colorectal cancer heterogeneity during disease progression.

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Crossref · 10.1158/1078-0432.ccr-18-3032

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Metadata

Authors
Piskol, R., Huw, L., Sergin, I., Kljin, C., Modrusan, Z., Kim, D., Kljavin, N., Tam, R., Patel, R., Burton, J., Penuel, E., Qu, X., Koeppen, H., Sumiyoshi, T., de Sauvage, F., Lackner, M. R., de Sousa e Melo, F., & Kabbarah, O.
Affiliations
  • Genentech (US)
  • 4Molecular Biology, Genentech, Inc., South San Francisco, California.
  • 6Discovery Oncology, Genentech, Inc., South San Francisco, California.
Corresponding author
Kabbarah, Omar
Venue
Clinical Cancer Research
Published
2019-07-15
Volume
25
Issue
14
Pages
4431-4442
ISSN
  • 1078-0432 (ISSN-L)
  • 1557-3265
OpenAlex
W2937956378
Cited by
62
References
47
Citations by year
2026: 5 · 2025: 4 · 2024: 7 · 2023: 7 · 2022: 12 · 2021: 13 · 2020: 10 · 2019: 4
FWCI
4.08
Type
journal article
Language
en
Open access
closed
Locations
  • Clinical Cancer Research (publishedVersion)
  • PubMed (publishedVersion)
Funders
GenentechGenentech (Genentech, Inc.)
Topics
  • Health Sciences › Medicine › Oncology › Colorectal Cancer Treatments and Studies
  • Health Sciences › Medicine › Pathology and Forensic Medicine › Genetic factors in colorectal cancer
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Keywords
consensus molecular subtypes, metastatic colorectal cancer, gene expression classifier, NanoString, formalin-fixed paraffin-embedded tissue, primary tumor versus metastasis, tumor heterogeneity, relapse, prognostic stratification
MeSH terms
Animals, Female, Humans, Mutation, Neoplasm Metastasis, Neoplasm Staging, Tumor Cells, Cultured, Biomarkers, Tumor, Colorectal Neoplasms, Cohort Studies, Gene Expression Regulation, Neoplastic, Mice, Inbred NOD, Clinical Trials, Phase II as Topic, Clinical Trials, Phase III as Topic, Gene Expression Profiling, Xenograft Model Antitumor Assays, Mice, Molecular Typing

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