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A Clinically Applicable Gene-Expression Classifier Reveals Intrinsic and Extrinsic Contributions to Consensus
Robert Piskol1, Ling Huw2, Ismail Sergin3
1Bioinformatics and Computational Biology, Genentech, Inc., South San Francisco, California. desousaf@gene.com omarkabbarah@gmail.com.
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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