ArticleDisease markers2022
Identification of Novel Prognostic Signatures for Clear Cell Renal Cell Carcinoma Based on ceRNA Network Construction and Immune Infiltration Analysis.
Article in Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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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
7 citing papers in PubMed, 7 citations in OpenAlex.
- Kidney-specific HIF-1α-dependent ARL10/miR-1271-5p overexpression in clear cell renal cell carcinoma.British journal of cancer · 2026Article
- Relationship between lncRNA MALAT1 and Chemo-radiotherapy Resistance of Cancer Cells: Uncovered Truths.Cell biochemistry and biophysics · 2024Review
- Machine Learning Gene Signature to Metastatic ccRCC Based on ceRNA Network.International journal of molecular sciences · 2024Article
- A review on the role of long non-coding RNA and microRNA network in clear cell renal cell carcinoma and its tumor microenvironment.Cancer cell international · 2023Review
- Mapping the tumor microenvironment in clear cell renal carcinoma by single-cell transcriptome analysis.Frontiers in genetics · 2023Article
- Article
- Identification of a Novel Tumor Inflammation Signature for Risk Stratification, Prognosis Prediction, and Immune Status in Colorectal Cancer.BioMed research international · 2022Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Clear cell renal cell carcinoma (ccRCC) carries significant morbidity and mortality globally and is often resistant to conventional radiotherapy and chemotherapy. Immune checkpoint blockade (ICB) has received attention in ccRCC patients as a promising anticancer treatment. Furthermore, competitive endogenous RNA (ceRNA) networks are crucial for the occurrence and progression of various tumors. This study was aimed at identifying reliable prognostic signatures and exploring potential mechanisms between ceRNA regulation and immune cell infiltration in ccRCC patients. Methods and Results: Gene expression profiling and clinical information of ccRCC samples were obtained from The Cancer Genome Atlas (TCGA) database. Through comprehensive bioinformatic analyses, differentially expressed mRNAs (DEmRNAs; Conclusion: On the basis of the ceRNA networks and TIICs, we constructed two prognostic signatures with excellent predictive value and explored possible molecular regulatory mechanisms, which might contribute to the improvement of prognosis and individualized treatment for ccRCC patients.
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Registered trials
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