ArticleBioengineered2021
A new prognostic risk model based on autophagy-related genes in kidney renal clear cell carcinoma.
Article in Bioengineered, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 14 citations in OpenAlex.
- hsa-miR-21-5p can serve as a standard biomarker in clear cell renal cell carcinoma by promoting tumor progression and influencing immune evasion.Discover oncology · 2025Article
- Identification and Validation of a Prognostic Signature Based on mRNAs Associated with Low-Density Lipoprotein Receptor-Related Proteins for Kidney Renal Clear Cell Carcinoma: Insights Into Tumor Immune Microenvironment, Mutation Patterns, and Personalized Treatment Strategies.International journal of general medicine · 2025Article
- Article
- DMOIT: denoised multi-omics integration approach based on transformer multi-head self-attention mechanism.Frontiers in genetics · 2024Article
- Construction and verification of a novel prognostic risk model for kidney renal clear cell carcinoma based on immunity-related genes.Frontiers in genetics · 2023Article
- Development of a Novel Sphingolipid Signaling Pathway-Related Risk Assessment Model to Predict Prognosis in Kidney Renal Clear Cell Carcinoma.Frontiers in cell and developmental biology · 2022Article
- Comprehensive characterisation of immunogenic cell death in melanoma revealing the association with prognosis and tumor immune microenvironment.Frontiers in immunology · 2022Article
- Cuprotosis-Related Genes: Predicting Prognosis and Immunotherapy Sensitivity in Pancreatic Cancer Patients.Journal of oncology · 2022Article
- Prognostic Signature and Therapeutic Value Based on Membrane Lipid Biosynthesis-Related Genes in Breast Cancer.Journal of oncology · 2022Article
- The Role of ERBB Signaling Pathway-Related Genes in Kidney Renal Clear Cell Carcinoma and Establishing a Prognostic Risk Assessment Model for Patients.Frontiers in genetics · 2022Article
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed to explore the potential role of autophagy-related genes in kidney renal clear cell carcinoma (KIRC) and develop a new prognostic-related risk model. In our research, we used multiple bioinformatics methods to perform a pan-cancer analysis of the CNV, SNV, mRNA expression, and overall survival of autophagy-related genes, and displayed the results in the form of heat maps. We then performed cluster analysis and LASSO regression analysis on these autophagy-related genes in KIRC. In the cluster analysis, we successfully divided patients with KIRC into five clusters and found that there was a clear correlation between the classification and two clinicopathological features: tumor, and stage. In LASSO regression analysis, we used 13 genes to create a new prognostic-related risk model in KIRC. The model showed that the survival rate of patients with KIRC in the high-risk group was significantly lower than that in the low-risk group, and that there was a correlation between this grouping and the patients' metastasis, tumor, stage, grade, and fustat. The results of the ROC curve suggested that this model has good prediction accuracy. The results of multivariate Cox analysis show that the risk score of this model can be used as an independent risk factor for patients with KIRC. In summary, we believe that this research provides valuable data supporting future clinical treatment and scientific research.
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