Paula Nissen, Nadezhda V Popova, Antonia Gocke, Daniel J Smit, Geoffrey Yuet Mun Wong, Matthew J McKay, Thomas J Hugh, Kerstin David, Hartmut Juhl, Hannah Voß, Jens U Marquardt, Björn Nashan, Hartmut Schlüter, Mark P Molloy, Manfred Jücker
{"title":"结直肠癌源性肝转移的蛋白质组学景观揭示了三种不同的表型,具有特定的信号传导和增强的生存。","authors":"Paula Nissen, Nadezhda V Popova, Antonia Gocke, Daniel J Smit, Geoffrey Yuet Mun Wong, Matthew J McKay, Thomas J Hugh, Kerstin David, Hartmut Juhl, Hannah Voß, Jens U Marquardt, Björn Nashan, Hartmut Schlüter, Mark P Molloy, Manfred Jücker","doi":"10.1016/j.mcpro.2025.101026","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"101026"},"PeriodicalIF":5.5000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335997/pdf/","citationCount":"0","resultStr":"{\"title\":\"Proteomic Landscape of Colorectal Cancer Derived Liver Metastasis Reveals Three Distinct Phenotypes With Specific Signaling and Enhanced Survival.\",\"authors\":\"Paula Nissen, Nadezhda V Popova, Antonia Gocke, Daniel J Smit, Geoffrey Yuet Mun Wong, Matthew J McKay, Thomas J Hugh, Kerstin David, Hartmut Juhl, Hannah Voß, Jens U Marquardt, Björn Nashan, Hartmut Schlüter, Mark P Molloy, Manfred Jücker\",\"doi\":\"10.1016/j.mcpro.2025.101026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":18712,\"journal\":{\"name\":\"Molecular & Cellular Proteomics\",\"volume\":\" \",\"pages\":\"101026\"},\"PeriodicalIF\":5.5000,\"publicationDate\":\"2025-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335997/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Molecular & Cellular Proteomics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.mcpro.2025.101026\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/7/4 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular & Cellular Proteomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.mcpro.2025.101026","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/4 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
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 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.
期刊介绍:
The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action.
The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data.
Scope:
-Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights
-Novel experimental and computational technologies
-Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes
-Pathway and network analyses of signaling that focus on the roles of post-translational modifications
-Studies of proteome dynamics and quality controls, and their roles in disease
-Studies of evolutionary processes effecting proteome dynamics, quality and regulation
-Chemical proteomics, including mechanisms of drug action
-Proteomics of the immune system and antigen presentation/recognition
-Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease
-Clinical and translational studies of human diseases
-Metabolomics to understand functional connections between genes, proteins and phenotypes