ArticleMolecular cancer2024
A multidimensional recommendation framework for identifying biological targets to aid the diagnosis and treatment of liver metastasis in patients with colorectal cancer.
Article in Molecular cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Machine learning-derived mast cell-associated angiogenesis features can serve as prognostic targets for clear cell renal cell carcinoma.Translational andrology and urology · 2026Article
- Why health recommender systems struggle to reach clinical practice: A lifecycle-oriented systematic review.iScience · 2026Article
- KLRB1 gene in tumor immune regulation and disease prognosis: a multidimensional role review.Discover oncology · 2026Review
- N7-Methylguanosine Modification in Colorectal Cancer: Molecular Insights and Clinical Implications.International journal of molecular sciences · 2026Review
- METTL1-mediated mOncogene · 2026Article
- Single-cell transcriptome analysis reveals regulatory programs associated with tumor resistance during immunotherapy in colorectal cancer.International journal of surgery (London, England) · 2026Article
- Molecular mechanisms and functions of guanylate-binding protein 2 in inflammation and cancer (Review).Oncology letters · 2025Review
- Advancing prognostic and therapeutic prediction in lung squamous cell carcinoma through integrated multi-omics analysis and 117 machine learning combinations.Journal of thoracic disease · 2025Article
- m5C RNA modification in colorectal cancer: mechanisms and therapeutic targets.Journal of translational medicine · 2025Review
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Authors and funding
17 authors.
Funding
Abstract
The quest to understand the molecular mechanisms of tumour metastasis and identify pivotal biomarkers for cancer therapy is increasing in importance. Single-omics analyses, constrained by their focus on a single biological layer, cannot fully elucidate the complexities of tumour molecular profiles and can thus overlook crucial molecular targets. In response to this limitation, we developed a multiobjective recommendation system (RJH-Metastasis 1.0) anchored in a multiomics knowledge graph to integrate genome, transcriptome, and proteome data and corroborative literature evidence and then conducted comprehensive analyses of colorectal cancer with liver metastasis (CRCLM). A total of 25 key genes significantly associated with CRCLM were recommended by our system, and GNB1, GATAD2A, GBP2, MACROD1, and EIF5B were further highlighted. Specifically, GNB1 presented fewer mutations but elevated RNA transcription and protein expression in CRCLM patients. The role of GNB1 in promoting the malignant behaviours of colon cancer cells was demonstrated via in vitro and in vivo studies. Aberrant expression of GNB1 could be regulated by METTL1-driven m7G modification. METTL1 knockdown decreased m7G modification in the 3' UTR of GNB1, increasing its mRNA transcription and translation during liver metastasis. Furthermore, GNB1 induced the formation of an immunosuppressive microenvironment by promoting the CLEC2C-KLRB1 interaction between memory B cells and KLRB1
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