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Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing
Published on: September 25, 2011
Immune-Metabolic Profiling Reveals Functional Heterogeneity Within Colorectal Cancer Consensus Molecular Subtypes
Sergio Madurga1,2, David López-Blanco2,3,4, Carles Foguet5,6
1Department of Material Science and Physical Chemistry and Research Institute of Theoretical and Computational Chemistry of University of Barcelona (IQTCUB), Universitat de Barcelona, 08028 Barcelona, Spain.
Colorectal cancer (CRC) subtypes show distinct immune-metabolic profiles, refining the Consensus Molecular Subtype (CMS) classification. This reveals hidden tumor heterogeneity and potential metabolic vulnerabilities for targeted therapies.
Area of Science:
- Oncology
- Molecular Biology
- Cancer Metabolism
Background:
- The Consensus Molecular Subtype (CMS) classification is crucial for colorectal cancer (CRC) stratification.
- However, CMS classification does not fully address immune-metabolic heterogeneity within tumor microenvironments.
Purpose of the Study:
- To refine CMS classification by integrating an immune-metabolic gene signature.
- To systematically characterize functional diversity across CMS1-4 colorectal cancer subtypes.
Main Methods:
- Analysis of transcriptomic data from 2918 CRC samples across three independent cohorts (GSE1, TCGA, GSE2).
- Integration of a validated immune-metabolic gene signature to stratify CMS subtypes.
Main Results:
- CMS subtypes exhibit distinct immune-metabolic distributions across datasets.
- CMS4 tumors show glycolytic and immunosuppressive profiles; CMS2 and CMS3 are oxidative and metabolically flexible.
- CMS1 tumors segregate into two distinct immune-metabolic profiles, highlighting heterogeneity.
Conclusions:
- Integrating immune-metabolic profiling refines CMS classification, revealing previously unrecognized functional heterogeneity.
- This approach provides a better framework for interpreting tumor-microenvironment states in colorectal cancer.
- Identifies context-specific metabolic vulnerabilities with potential clinical relevance for CRC treatment.
