ArticleFrontiers in immunology2024
Unraveling the role of ADAMs in clinical heterogeneity and the immune microenvironment of hepatocellular carcinoma: insights from single-cell, spatial transcriptomics, and bulk RNA sequencing.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- The ADAM Family of Proteases: Structure, Substrates, and Roles in Liver Diseases.International journal of molecular sciences · 2026Review
- Mechanisms and therapeutic strategies of bidirectional crosstalk between hepatic stellate cell-derived cancer-associated fibroblasts and T cells in immune evasion and therapeutic resistance of hepatocellular carcinoma.Frontiers in immunology · 2026Review
- Advancing liver cancer diagnosis and treatment with multi-omics approaches: a systematic review.Discover oncology · 2025Review
- Integrated bioinformatic and machine learning analysis identifies MCM7 and ADAM17 as potential biomarkers for early stage gastric cancer.Journal of gastrointestinal oncology · 2025Article
- Mapping molecular landscapes in triple-negative breast cancer: insights from spatial transcriptomics.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- Multi-Omics Profiling Reveals Glycerolipid Metabolism-Associated Molecular Subtypes and Identifies ALDH2 as a Prognostic Biomarker in Pancreatic Cancer.Metabolites · 2025Article
- Fabrication and Characterization of Electrospun DegraPolMaterials (Basel, Switzerland) · 2025Article
- MAZ-mediated tumor progression and immune evasion in hormone receptor-positive breast cancer: Targeting tumor microenvironment and PCLAF+ subtype-specific therapy.Translational oncology · 2025Article
- Thymidine kinase 1 related to Prolif-like T cells promoted GBM through regulation of cell cycle and EMT signals: a comprehensive research based on multi-omics analysis and experimental validation.Frontiers in immunology · 2025Article
- Single-cell RNA sequencing and immune microenvironment analysis reveal PLOD2-driven malignant transformation in cervical cancer.Frontiers in immunology · 2024Article
- Macrophage-related Genomic Signatures Predict HCC Prognosis and Therapy Response.Cancer genomics & proteomicsArticle
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7 authors.
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Abstract
Background: Hepatocellular carcinoma (HCC) is a prevalent and heterogeneous tumor with limited treatment options and unfavorable prognosis. The crucial role of a disintegrin and metalloprotease (ADAM) gene family in the tumor microenvironment of HCC remains unclear. Methods: This study employed a novel multi-omics integration strategy to investigate the potential roles of ADAM family signals in HCC. A series of single-cell and spatial omics algorithms were utilized to uncover the molecular characteristics of ADAM family genes within HCC. The GSVA package was utilized to compute the scores for ADAM family signals, subsequently stratified into three categories: high, medium, and low ADAM signal levels through unsupervised clustering. Furthermore, we developed and rigorously validated an innovative and robust clinical prognosis assessment model by employing 99 mainstream machine learning algorithms in conjunction with co-expression feature spectra of ADAM family genes. To validate our findings, we conducted PCR and IHC experiments to confirm differential expression patterns within the ADAM family genes. Results: Gene signals from the ADAM family were notably abundant in endothelial cells, liver cells, and monocyte macrophages. Single-cell sequencing and spatial transcriptomics analyses have both revealed the molecular heterogeneity of the ADAM gene family, further emphasizing its significant impact on the development and progression of HCC. In HCC tissues, the expression levels of ADAM9, ADAM10, ADAM15, and ADAM17 were markedly elevated. Elevated ADAM family signal scores were linked to adverse clinical outcomes and disruptions in the immune microenvironment and metabolic reprogramming. An ADAM prognosis signal, developed through the utilization of 99 machine learning algorithms, could accurately forecast the survival duration of HCC, achieving an AUC value of approximately 0.9. Conclusions: This study represented the inaugural report on the deleterious impact and prognostic significance of ADAM family signals within the tumor microenvironment of HCC.
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