ArticleThe journal of pathology. Clinical research2022
A prognostic six-gene expression risk-score derived from proteomic profiling of the metastatic colorectal cancer secretome.
Article in The journal of pathology. Clinical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Integrated meta-analysis of colorectal cancer public proteomic datasets for biomarker discovery and validation.PLoS computational biology · 2024Pooled it
- A Genome-Wide Association Study of Colorectal Cancer Mortality Outcomes Among Individuals of African and Admixture Ancestry.Molecular carcinogenesis · 2026Article
- CD109 Drives Stemness and Chemoresistance in Colorectal Cancer via LRRC8A/AKAP12/PKCα-Mediated STAT3 Activation and WNT Signaling.International journal of biological sciences · 2026Article
- Review
- Prediction of overall survival in stage II and III colon cancer through machine learning of rapidly-acquired proteomics.Cell discovery · 2024Article
- Machine learning in onco-pharmacogenomics: a path to precision medicine with many challenges.Frontiers in pharmacology · 2023Review
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The necessity to accurately predict recurrence and clinical outcome in early stage colorectal cancer (CRC) is critical to identify those patients who may benefit from adjuvant chemotherapy. Here, we developed and validated a gene-based risk-score algorithm for patient stratification and personalised treatment in early stage disease based on alterations in the secretion of metastasis-related proteins. A quantitative label-free proteomic analysis of the secretome of highly and poorly metastatic CRC cell lines with different genetic backgrounds revealed 153 differentially secreted proteins (fold-change >5). These changes in the secretome were validated at the transcriptomic level. Starting from 119 up-regulated proteins, a six-gene/protein-based prognostic signature composed of IGFBP3, CD109, LTBP1, PSAP, BMP1, and NPC2 was identified after sequential discovery, training, and validation in four different cohorts. This signature was used to develop a risk-score algorithm, named SEC6, for patient stratification. SEC6 risk-score components showed higher expression in the poor prognosis CRC subtypes: consensus molecular subtype 4 (CMS4), CRIS-B, and stem-like. High expression of the signature was also associated with patients showing dMMR, CIMP
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