ArticlePeerJ2020
A 14 immune-related gene signature predicts clinical outcomes of kidney renal clear cell carcinoma.
Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 15 citations in OpenAlex.
- A novel immune-related gene signature for predicting immunotherapy outcomes and survival in clear cell renal cell carcinoma.Scientific reports · 2023Article
- Article
- Comprehensive analysis of the collagen family members as prognostic markers in clear cell renal cell carcinoma.Translational cancer research · 2022Article
- A multivariate statistical test for differential expression analysis.Scientific reports · 2022Article
- Article
- Article
- A united risk model of 11 immune‑related gene pairs and clinical stage for prediction of overall survival in clear cell renal cell carcinoma patients.Bioengineered · 2021Article
- Characterization of Molecular Heterogeneity Associated With Tumor Microenvironment in Clear Cell Renal Cell Carcinoma to Aid Immunotherapy.Frontiers in cell and developmental biology · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Kidney renal clear cell carcinoma (KIRC) is the leading cause of kidney cancer-related deaths. Currently, there are no studies in tumor immunology investigating the use of signatures as a predictor of overall survival in KIRC patients. Our study attempts to establish an immune-related gene risk signature to predict clinical outcomes in KIRC. A total of 528 patients from The Cancer Genome Atlas (TCGA) database were included in our analysis and randomly divided into training (
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Registered trials
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