ArticleHeliyon2024
Prediction of immune infiltration and prognosis for patients with cholangiocarcinoma based on a cuproptosis-related lncRNA signature.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 4 citations in OpenAlex.
- mTOR signaling in cholangiocarcinoma: mechanistic insights and therapeutic opportunities.Frontiers in pharmacology · 2026Review
- Genome-wide meta-QTL approach identifies consensus loci associated with agriculturally important tomato fruit traits.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Targeting cuproptosis for cancer therapy: Focus on the anti-tumor immune system.Cancer pathogenesis and therapy · 2025Review
- Copper homeostasis and copper-induced cell death in tumor immunity: implications for therapeutic strategies in cancer immunotherapy.Biomarker research · 2024Review
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Cholangiocarcinoma (CHOL) is a malignant disease that affects the digestive tract, and it is characterized by a poor prognosis. This research sought to explore the involvement of cuproptosis-related lncRNAs (CRLs) in the prognostic prediction and immune infiltration of cholangiocarcinoma. Methods: The expression profiles and clinical data of CHOL patients were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and CRLs were defined via co-expression analysis. Two molecular clusters distinguished by cuproptosis-related genes (CRGs) were produced. Then a risk signature consisted by four CRLs was formed, and all samples were separated into low- and high-risk groups using a risk score. Kaplan-Meier survival analysis, principal component analysis, differentially expressed analysis, immune cell infiltration analysis, and sensitivities analysis of chemotherapy drugs were conducted between the two groups. Simultaneously, the expression values of four lncRNAs confirmed by real-time PCR in our own 20 CHOL samples were brought into the risk model. Results: The CHOL samples could be differentiated into two molecular clusters, which displayed contrasting survival times. Additionally, patients with higher risk scores had significantly worse prognosis compared to those in the low-risk group. Furthermore, both immune infiltration and enrichment analysis revealed significant discrepancies in the tumor immune microenvironment (TIME) between different risk groups. Moreover, the predictive power and the correlation with CA19-9 and CEA of risk signature were validated in our own samples. Conclusion: We developed a risk signature which could serve as an independent prognostic factor and offer a promising prediction for not only prognosis but also TIME in CHOL patients.
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