ArticleFrontiers in genetics2020
Identification of a Novel Signature and Construction of a Nomogram Predicting Overall Survival in Clear Cell Renal Cell Carcinoma.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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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Who cites it
5 citing papers in PubMed.
- Label-free quantitative proteomics reveals the mechanisms of Aurora kinase B in renal cell carcinoma.SAGE open medicine · 2024Article
- Radiomic Signatures Associated with CD8Cancers · 2022Review
- Development of a Phagocytosis-Dependent Gene Signature to Predict Prognosis and Response to Checkpoint Inhibition in Clear-Cell Renal Cell Carcinoma.Frontiers in immunology · 2022Article
- Identification of Ligand-Receptor Pairs Associated With Tumour Characteristics in Clear Cell Renal Cell Carcinoma.Frontiers in immunology · 2022Article
- A Necroptosis-Related lncRNA Signature Predicts Prognosis and Indicates the Immune Microenvironment in Soft Tissue Sarcomas.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundClear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC), which accounts for majority of RCC-related deaths. It is clearly essential to further identify more novel prognostic signatures and therapeutic targets. MATERIAL AND
methodsWe identified differentially expressed genes (DEGs) between ccRCC and adjacent normal tissues in GEO database using a Robust Rank Aggregation (RRA) method. An mRNA signature (mRNASig) based on DEGs was developed using Cox and LASSO analysis in the TCGA database and validated in the ICGC database. Afterward, the influence of mRNASig mRNAs on the immune microenvironment in ccRCC was explored using comprehensive bioinformatics analysis.
resultsA total of 957 robust DEGs were identified using the RRA method. mRNASig comprised CEP55, IFI44, NCF4, and TCIRG1 and was developed and validated to identify high-risk patients who had poorer prognosis than low-risk patients. A nomogram was also constructed based on mRNASig, AJCC stage, and tumor grade. The mRNASig were closely related to a variety of tumor-infiltrating lymphocytes, especially including CD8+ T cells, activated CD4+ memory T cells, regulatory T cells, activated NK cells, and resting NK cells. The mRNASig were also correlated positively with the expression of CTLA4, LAG3, PDCD1, TIGIT, and HAVCR2.
conclusionWe developed and validated mRNASig to assist clinicians in making personalized treatment decisions. Furthermore, CEP55, IFI44, NCF4, and TCIRG1 may be novel potential targets for future treatment of ccRCC.
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