Proteomic Landscape of Colorectal Cancer Derived Liver Metastasis Reveals Three Distinct Phenotypes With Specific Signaling and Enhanced Survival

Colorectal carcinoma is a major global disease with the second highest mortality rate among carcinomas. The liver is the most common site for metastases which portends a poor prognosis. Nonetheless, considerable heterogeneity of colorectal cancer liver metastases (CRC-LM) exists, evidenced by varied...

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Published inMolecular & cellular proteomics Vol. 24; no. 8; p. 101026
Main Authors Nissen, Paula, Popova, Nadezhda V., Gocke, Antonia, Smit, Daniel J., Wong, Geoffrey Yuet Mun, McKay, Matthew J., Hugh, Thomas J., David, Kerstin, Juhl, Hartmut, Voß, Hannah, Marquardt, Jens U., Nashan, Björn, Schlüter, Hartmut, Molloy, Mark P., Jücker, Manfred
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.08.2025
American Society for Biochemistry and Molecular Biology
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ISSN1535-9476
1535-9484
1535-9484
DOI10.1016/j.mcpro.2025.101026

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Summary:Colorectal carcinoma is a major global disease with the second highest mortality rate among carcinomas. The liver is the most common site for metastases which portends a poor prognosis. Nonetheless, considerable heterogeneity of colorectal cancer liver metastases (CRC-LM) exists, evidenced by varied recurrence and survival patterns in patients undergoing curative-intent resection. Our understanding of the basis for this biological heterogeneity is limited. We investigated this by proteomic analysis of 152 CRC-LM obtained from three different medical centers in Germany and Australia using mass spectrometry-based differential quantitative proteomics. The proteomics data of the individual cohorts were harmonized through batch-effect correction algorithms to build a large multicenter cohort. Applying ConsensusClusterPlus to the proteome data yielded three distinct CRC-LM phenotypes (referred to as CRLM-SD (splice-driven), CRLM-CA (complement-associated), and CRLM-OM (oxidative metabolic)). The CRLM-SD phenotype showed higher abundance of key regulators of alternative splicing as well as extracellular matrix proteins commonly associated with tumor cell growth. The CRLM-CA phenotype was characterized by a higher abundance of proteins involved in the classical pathway part of the complement system including the membrane attack complex proteins and those with antithrombotic activity. The CRLM-OM phenotype showed higher abundance of proteins involved in various metabolic pathways including amino acids and fatty acids metabolism, which correlated in the literature with advanced proliferation of metastases and increased recurrence. Patients classified as CRLM-OM had a significantly lower overall survival in comparison to CRLM-CA patients. Finally, we identified a set of prognosis-associated biomarkers for each group including EpCAM, CEACAM1, CEACAM5, and CEACAM6 for CRLM-SD, DCN, TIMP3, and OLFM4 for CRLM-CA and FMO3, CES2 and AGXT for CRLM-OM. In summary, the discovery of three proteomic subgroups associated with distinct signaling pathways and survival of the CRC-LM patients provides a novel classification for risk stratification, prognosis and potentially novel therapeutic targets in CRC-LM. [Display omitted] •Liver metastases are common in colorectal cancer patients and are heterogeneous.•Metastases heterogeneity is often neglected but important to specify treatment.•Proteomics of a multicenter cohort revealed three major liver metastases subtypes.•Proteomic liver metastases subtypes were associated with patient survival.•Novel therapeutic targets recognizable by proteomic profiling of liver metastases. Proteomic analysis of a large muticenter cohort of colorectal carcinoma liver metastases samples revealed a differentiation into three proteomic phenotypes, independent of clinical parameters. The differentially regulated proteins and signaling pathways were associated with different prognostic features through literature mining. The findings from literature were consistent with the overall survival determined for each subgroup. The proposed biomarkers and enriched signaling pathways may enhance prognosis prediction and novel therapy development.
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ISSN:1535-9476
1535-9484
1535-9484
DOI:10.1016/j.mcpro.2025.101026