ArticleHeliyon2024
Vasculogenic mimicry-related gene prognostic index for predicting prognosis, immune microenvironment in clear cell renal cell carcinoma.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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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
3 citing papers in PubMed.
- A novel prognostic model based on vasculogenic mimicry in ovarian cancer.Translational cancer research · 2026Article
- Review
- Leveraging Single-Cell Multi-Omics to Decode Tumor Microenvironment Diversity and Therapeutic Resistance.Pharmaceuticals (Basel, Switzerland) · 2025Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Clear cell renal cell carcinoma (ccRCC) is a highly aggressive cancer associated with higher death rates. However, traditional anti-angiogenic therapies have limited effectiveness due to drug resistance. Vascular mimicry (VM) provides a different way for tumors to develop blood vessels without relying on endothelial cells or angiogenesis. However, the intricate mechanisms and interplay between it and the immune microenvironment in ccRCC remain unclear. Methods: A PubMed and GeneCards literature review was conducted to identify VM-related genes (VMRGs). VMRGs expression profiles were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), developing a novel VM risk score model and nomogram for ccRCC. The EBI ArrayExpress database (the validation set) was obtained to validate the prognostic model. The relationship between VMRGs risk score clinical characteristics and immune infiltration was investigated. Finally, the expression of six model VMRGs was validated using single-cell analysis, GEPIA, Human Protein Atlas (HPA), and quantitative Real-time PCR (qRT-PCR). Results: Cox regression analysis and nomogram identified L1CAM, TEK, CLDN4, EFNA1, SERPINF1, and MALAT1 as independent prognostic risk factors, which could be used to stratify the ccRCC population into two risk groups with distinct immune profiles and responsiveness to immunotherapy. The results of single-cell analysis, GEPIA, HPA, and qRT-PCR validated the model genes' expression. Conclusions: Our novel findings constructed a convenient and reliable 6 gene signatures as potential immunologic and prognostic biomarkers of VM in ccRCC.
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Registered trials
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