ArticleBioengineered2021
A novel long non-coding RNA-based prognostic signature for renal cell carcinoma patients with stage IV and histological grade G4.
Article in Bioengineered, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Circulating Tumor Function: A Systems Biology Framework for Liquid Biopsy in Genitourinary Cancers.Genes · 2026Review
- NUTM2A-AS1 as a potential key regulator in cancer: unraveling its ceRNA networks and impact on tumor biology.European journal of medical research · 2025Review
- A depression-related lncRNA signature predicts the clinical outcome and immune characteristics of gastric cancer.Heliyon · 2024Article
- Identification of potential novel N6-methyladenosine effector-related lncRNA biomarkers for serous ovarian carcinoma: a machine learning-based exploration in the framework of 3P medicine.Frontiers in pharmacology · 2024Article
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- The role of long noncoding RNA H19 in gynecological pathologies: Insights into gene regulation and immune modulation (Review).International journal of molecular medicine · 2023Review
- Construction of anoikis-related lncRNAs risk model: Predicts prognosis and immunotherapy response for gastric adenocarcinoma patients.Frontiers in pharmacology · 2023Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed to establish a lncRNA-based signature for predicting the prognosis of patients with high stage and grade renal cell carcinoma (RCC). According to the Surveillance, Epidemiology, and End Results (SEER) database, sex, age, grade, stage, surgery, chemotherapy, radiation, tumor size, and marital status were the independent prognostic factors for RCC and also had significant correlations with the overall survival through Cox univariate and multivariate analyses. Noticeably, among these influencing factors, the histological classification of undifferentiated group and pathological stage IV had the greatest prognostic risks for RCC patients. Furthermore, based on the samples at stage IV and histological grade G4 from The Cancer Genome Atlas (TCGA) portal, 9 key lncRNAs, including KIAA2012, CCNT2-AS1, ITPKB-AS1, TBX2-AS1, NUTM2A-AS1, LINC02522, LINC02384, LINC01559, and LINC00865 were identified and a prognostic signature was constructed by Lasso analysis and Cox regression model. The Kaplan-Meier analysis suggested that patients at stage IV and histological grade of G4 in high risk score group had a worse overall survival than that in low risk score group. The following receiver operating characteristic curve (ROC) curves also showed that this signature possesses a better predictive power performance. Pathway enrichment analysis discovered that 9 lncRNAs held potential roles in cell division, cell cycle, DNA damage and cytokines levels in RCC. This work indicates that the established 9-lncRNA signature has a good capacity in predicting the prognosis of RCC patients with stage IV and histological grade of G4, and may be helpful for guiding the treatment strategies for RCC patients.
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